System and method for estimating catalyst trim effectiveness in mixed metallocene catalysts for polymerization processes

Abstract

An example method includes: (A) receiving a polymerization process dataset having properties of a polyethylene (PE) resin prepared using a multi-component catalyst composition and different operating parameters of a gas phase reactor system; (B) setting a catalyst trim validity value of the multi-component catalyst composition as an initial value; (C) training a respective process model for each of the properties of the PE resin of the polymerization process dataset using the catalyst trim validity values to produce a set of trained process models; (D) optimizing the catalyst trim validity value using the set of trained process models to determine a Minimized Square Error Sum (SSE) value of a model residual; (E) repeating steps (C) and (D) until a decrease in the minimized SSE value is less than a predetermined threshold; and (F) outputting a catalyst trim validity value for the multi-component catalyst composition and the trained process model for the set.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 482,719, filed February 1, 2023, entitled “System and Method for Estimating the Effectiveness of Catalyst Trimming in a Mixed Metallocene Catalyst for Use in a Polymerization Process,” the entire contents of which are incorporated herein by reference. Technical Field

[0002] The present disclosure relates generally to catalyst slurry mixtures. In particular, the present disclosure relates to a soft sensor technique for characterizing catalyst slurry mixtures to estimate the effectiveness of catalyst trimming in polymerization processes, such as gas phase polyethylene (GPPE) polymerization processes and slurry phase polymerization processes. Background Art

[0003] Supported multicomponent catalysts are widely used in commercial-scale polymer production because they enable the production of multimodal polymer resins. For example, a supported bicomponent catalyst comprises a support on which two types of active sites are disposed. The relative contribution to polymerization between the first and second active sites determines the composition of the resulting multimodal polymer resin, where the relative contribution of each active site depends on the ratio of active sites on the supported bicomponent catalyst.

[0004] The method for preparing a supported two-component catalyst can include reacting a first catalyst component containing a precursor of a first type of active site and a second catalyst component containing a precursor of a second type of active site under conditions suitable for converting at least a portion of the precursors of the first and second types of active sites into an activated form. The molar ratio of the two types of active sites is not necessarily equal to the molar ratio of the two precursors used to prepare the supported catalyst. There may be several reasons for the difference, including that the two precursors may have different activation energies, sometimes referred to as activation efficiencies, resulting in very different activations of the two catalyst precursors used during catalyst preparation. Even if the molar ratio of the two catalyst precursors remains constant during catalyst preparation, the molar ratio of the two types of active sites obtained on the supported catalyst may also change due to fluctuations in the relative activation energies during catalyst preparation.

[0005] Furthermore, there are currently no analytical techniques that can directly probe the ratio of the two types of active sites on supported catalysts. Without knowing the ratio of active sites in a two-component catalyst system, it is generally impossible to determine the composition of the polymer resin product before using the two-component catalyst system. Ideally, a two-component catalyst system would be characterized to determine the ratio of active sites before using the two-component catalyst system in a polymerization application, so that the catalyst response in the reactor and the composition of the resin product can be more easily controlled.

[0006] References of potential interest in this regard include: U.S. Patent Publication Nos. US2020 / 0071437 and US2022 / 0033535, and U.S. Patent Nos. 8,429,100; 6,546,379; 7,505,949; 6,243,696; 11,288,577; 11,203,653; 10,494,462; 9,963,528 and 10,865,259. Summary of the Invention SUMMARY OF THE INVENTION

[0007] Disclosed herein is an exemplary soft sensor system comprising at least one memory configured to store a polymerization process dataset of a multi-component catalyst composition, wherein the polymerization process dataset includes properties of a polyethylene (PE) resin produced using the multi-component catalyst composition and various operating parameters of a gas-phase reactor system. The soft sensor system also comprises at least one processor configured to execute the stored instructions to perform an action. The actions include: (A) setting a catalyst trim effectiveness value of the multi-component catalyst composition to an initial value; (B) using the catalyst trim effectiveness value of the multi-component catalyst composition to train a corresponding process model for each of the properties of the PE resin in the polymerization process data set to generate a set of trained process models; (C) optimizing the catalyst trim effectiveness value of the multi-component catalyst composition based on the set of trained process models to determine a minimized sum of squared error (SSE) value of model residuals; (D) repeating steps (B) and (C) until the decrease in the minimized SSE value is less than a predetermined threshold; and (E) outputting or storing the catalyst trim effectiveness value of the multi-component catalyst composition and the set of trained process models.

[0008] Further disclosed herein is an example method for operating a soft sensor system. The method comprises: (A) receiving a polymerization process dataset of a multi-component catalyst composition, wherein the polymerization process dataset comprises properties of a polyethylene (PE) resin prepared using the multi-component catalyst composition and various operating parameters of a gas phase reactor system; (B) setting a catalyst trim effectiveness value for the multi-component catalyst composition to an initial value; (C) using the catalyst trim effectiveness value for the multi-component catalyst composition to train a corresponding process model for each of the properties of the PE resin in the polymerization process dataset to generate a set of trained process models; (D) optimizing the catalyst trim effectiveness value for the multi-component catalyst composition based on the set of trained process models to determine a minimized sum of squared errors (SSE) value of model residuals; (E) repeating steps (C) and (D) until the minimized SSE value decreases by less than a predetermined threshold; and (F) outputting or storing the catalyst trim effectiveness value for the multi-component catalyst composition and the set of trained process models.

[0009] Further disclosed herein is an example non-transitory computer-readable medium storing instructions executable by a processor of a soft sensor system. The instructions include instructions for: (A) receiving a polymerization process dataset of a multi-component catalyst composition, wherein the polymerization process dataset includes properties of a polyethylene (PE) resin produced using the multi-component catalyst composition and various operating parameters of a gas phase reactor system; (B) setting a catalyst trim effectiveness value for the multi-component catalyst composition to an initial value; (C) using the catalyst trim effectiveness value for the multi-component catalyst composition to train a corresponding process model for each of the properties of the PE resin in the polymerization process dataset to generate a set of trained process models; (D) optimizing the catalyst trim effectiveness value for the multi-component catalyst composition based on the set of trained process models to determine a minimized sum of squared errors (SSE) value of model residuals; (E) repeating steps (C) and (D) until the minimized SSE value decreases by less than a predetermined threshold; and (F) outputting or storing the catalyst trim effectiveness value for the multi-component catalyst composition and the set of trained process models.

[0010] These and other features and properties of the disclosed methods and systems of the present disclosure, as well as their advantageous applications and / or uses, will become apparent from the detailed description that follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] To assist one skilled in the relevant art in making and using the subject matter of the present invention, reference is made to the accompanying drawings, in which:

[0012] Figure 1 is a schematic diagram of a gas phase reactor system including a soft sensor system according to certain embodiments of the present disclosure.

[0013] Figure 2A Example methods of preparing and using a bicomponent catalyst system in the production of a multimodal polymer according to certain embodiments of the present disclosure are presented.

[0014] Figure 2B The contribution of active sites of a two-component catalyst according to certain embodiments of the present disclosure is shown.

[0015] Figure 2C Shown are the preparation of a two-component catalyst system according to certain embodiments of the present disclosure and the ratio of two types of activation sites on the two-component catalyst.

[0016] Figure 3A A flow diagram for the production of a post-trim catalyst according to certain embodiments of the present disclosure is shown.

[0017] Figure 3B The relative proportions of the two types of active sites in the trimmed catalyst according to certain embodiments of the present disclosure are shown.

[0018] Figure 4 is a flow chart showing a process for generating a gas phase polyethylene (GPPE) polymerization process data set according to certain embodiments of the present disclosure.

[0019] Figure 5 is a flow chart showing a process for determining a catalyst trim effectiveness value (η) and a trained process model for a multi-component catalyst composition according to certain embodiments of the present disclosure.

[0020] Figure 6 is a diagram showing an example plot of minimized sum of squared error (SSE) values ​​of model residuals versus number of optimization iterations for catalyst trim effectiveness values ​​(η) according to certain embodiments of the present disclosure.

[0021] Figure 7 is a flow chart showing a process for operating a soft sensor system using a catalyst trim effectiveness value (η) and a trained process model to predict properties of a polyethylene (PE) resin produced using a multi-component catalyst composition according to certain embodiments of the present disclosure.

[0022] Figure 8 is a flow chart showing a process for operating a smart sensor system using a catalyst trim effectiveness value (η), a trained process model, and desired properties of the PE resin to be produced to determine predicted operating parameters for a GPPE polymerization process according to certain embodiments of the present disclosure. Detailed Description of the Invention

[0023] Disclosed herein are methods for estimating the trimming effectiveness of supported catalysts in slurries, and methods for predicting the material properties of olefin products based on the estimated trimming effectiveness. Gas phase polymerization in a fluidized bed is an industrial process for polymerizing ethylene and ethylene comonomers to produce polyethylene polymers and copolymer compositions. It is generally known in the art that the composition distribution (CD) and molecular weight distribution (MWD) of polyolefins affect the properties of polyolefins. In order to reduce or avoid certain trade-offs between desired properties, bimodal polymers are becoming increasingly important in the polyolefin industry. Catalyst design and loading technology have allowed the development of single-reactor bimetallic (bicomponent) catalyst systems capable of producing bimodal polyethylene. The composition of the active sites in a bicomponent catalyst system (i.e., the molar ratio of the two types of active sites) is typically different from the molar ratio of the two catalyst compound precursors used to prepare the bicomponent catalyst. The evaluation of the active site composition of a bicomponent catalyst system relies on polymerization testing because there is no established or commercial analytical method to provide a direct evaluation of the active site ratio of the catalyst.

[0024] The supported catalyst is added to a diluent to form a catalyst slurry and pumped into a polymerization reactor. Catalyst solution can be added (i.e., "trim") to the catalyst slurry to adjust one or more properties of the polymer being formed in the reactor "in situ." However, such "trim" methods are limited because the trimmed catalyst is typically not characterized prior to introduction into the polymerization reactor, as described above.

[0025] As used herein, the indefinite article "a" or "an" shall mean "at least one" unless specified to the contrary or the context clearly indicates otherwise. Thus, embodiments using "a-olefin" include embodiments in which one, two, or more a-olefins are used, unless otherwise specified or the context clearly indicates that only one a-olefin is used.

[0026] As used herein, "wt%" means percent by weight, "vol%" means percent by volume, "mol%" means molar percent, "ppm" means parts per million, and "ppm wt" and "wppm" are used interchangeably and refer to parts per million by weight. Unless otherwise indicated, all concentrations are expressed based on the total amount of the composition in question. Unless otherwise indicated, temperatures are given in degrees Celsius (° C.).

[0027] "Olefin" is a linear, branched or cyclic compound of carbon and hydrogen having at least one double bond. For the purposes of this specification and the appended claims, when a polymer or copolymer is referred to as comprising an olefin, such as ethylene and at least one C3 to C 20When an α-olefin is used, the olefin present in such a polymer or copolymer is the polymerized form of the olefin. For example, when a copolymer is said to have an "ethylene" content of 35% to 55% by weight, it is understood that the repeating units / monomer units, or simply units, in the copolymer are derived from ethylene in the polymerization reaction, and that the derived units are present at 35% to 55% by weight, based on the weight of the copolymer. For the purposes of this disclosure, ethylene shall be considered an α-olefin.

[0028] A "polymer" has two or more repeating units / monomer units or simply units that are the same or different. A "homopolymer" is a polymer having identical units. A "copolymer" is a polymer having two or more units that are different from each other. A "terpolymer" is a polymer having three units that are different from each other. The term "different" as used in reference to units indicates that the units differ from each other by at least one atom or are isomerically different. The definition of copolymer as used herein includes terpolymers and the like. Likewise, the definition of polymer as used herein includes homopolymers, copolymers, and the like. In addition, the terms "polyethylene copolymer," "ethylene copolymer," and "ethylene-based polymer" are used interchangeably to refer to a copolymer that includes at least 50 mol% units derived from ethylene.

[0029] The nomenclature of the elements and their groups used herein is according to the new notation as published in HAWLEYS CONDENSED CHEMICALDICTIONARY, 13th edition, John Wiley & Sons, Inc., (1997) (reproduced with permission of IUPAC), unless reference is made to previous IUPAC forms (which also appear therein) indicated by Roman numerals, or unless otherwise indicated. IUPAC refers to the International Union of Pure and Applied Chemistry.

[0030] As used herein, the term "slurry catalyst mixture" refers to the contact product comprising at least one catalyst compound and a carrier fluid (e.g., mineral oil), and optionally, one or more of an activator, a co-activator, and a support. In a preferred embodiment, the slurry catalyst mixture comprises a contact product comprising at least two catalyst compounds and a carrier fluid (e.g., mineral oil), and optionally, one or more of an activator, a co-activator, and a support.

[0031] As used herein, the term "catalyst system" refers to a combination of at least one catalyst compound, an optional activator, an optional co-activator, and an optional support material. Thus, in some embodiments, when the optional activator, optional co-activator, and optional support material are absent, the catalyst system may comprise only a single catalyst compound. In other embodiments, when the optional activator, optional co-activator, and optional support material are absent, the catalyst system may comprise only two or more catalyst compounds. For purposes of this disclosure, when a catalyst system is described as comprising a neutral, stable form of a component, it will be understood by those skilled in the art that the ionic form of the component is the form that reacts with the monomer to produce a polymer. The catalyst systems, catalysts, and activators of this disclosure are intended to encompass ionic forms in addition to the neutral forms of the compounds / components.

[0032] Metallocene catalysts are organometallic compounds having at least one π-bonded cyclopentadienyl moiety (or substituted cyclopentadienyl moiety), more typically two π-bonded cyclopentadienyl moieties or substituted cyclopentadienyl moieties, bonded to a transition metal. In the description herein, metallocene catalysts may be described as catalyst precursors, premetallocene catalyst compounds, metallocene catalyst compounds, or transition metal compounds, and these terms are used interchangeably. An "anionic ligand" is a negatively charged ligand that contributes one or more electron pairs to a metal ion. For purposes of this disclosure, with respect to metallocene catalyst compounds, the term "substituted" means that a hydrogen radical has been replaced with a hydrocarbyl, heteroatom, or heteroatom-containing group. For example, methylcyclopentadiene (Cp) is a Cp group substituted with a methyl group.

[0033] "Alkoxide" includes an oxygen atom bonded to an alkyl group, the alkyl group being C1-C 10 Hydrocarbyl. The alkyl group may be linear, branched, or cyclic. The alkyl group may be saturated or unsaturated. In at least one embodiment, the alkyl group may contain at least one aromatic group.

[0034] "Asymmetric" as used in connection with the indenyl compounds of the present invention means that the substitution at the 4-position is different, or the substitution at the 2-position is different, or the substitution at the 4-position is different and the substitution at the 2-position is different.

[0035] The properties and performance of the polyethylene composition can be advanced by a combination of: (1) varying one or more reactor conditions, such as reactor temperature, hydrogen concentration, comonomer concentration, etc.; and (2) selecting and feeding a dual catalyst system having a first catalyst and a second catalyst. The dual catalyst system can advantageously be tailored with additional first and / or second catalyst as needed. Such catalyst tailoring methods provide for easy adjustment of polyethylene properties by allowing adjustment of the ratio of the first and second catalysts in the dual catalyst system fed to the reactor.

[0036] In various embodiments according to the present disclosure, the slurry catalyst mixture may include a first catalyst compound, which may be a "high molecular weight component," and a second catalyst compound, which may be a "low molecular weight component." In other words, the first catalyst may primarily provide the high molecular weight portion of the polymer, and the second catalyst may primarily provide the low molecular weight portion of the polymer (e.g., the first catalyst tends to produce relatively high molecular weight polymer chains; while the second catalyst tends to produce relatively low molecular weight polymer chains). In at least one embodiment, a dual catalyst system may be present in a catalyst tank of a reactor system, and the molar ratio of the first catalyst compound to the second catalyst compound of the dual catalyst system may be from 99:1 to 1:99, e.g., from 90:10 to 10:90, e.g., from 85:15 to 50:50, e.g., from 75:25 to 50:50, e.g., from 60:40 to 40:60. Consistent with the above description of the trimming catalyst system, the first catalyst compound and / or the second catalyst compound may be added to the polymerization process as a trimming catalyst to adjust the molar ratio of the first catalyst compound to the second catalyst compound. In at least one embodiment, the first catalyst compound and the second catalyst compound are each metallocene catalyst compounds. Gas phase reactor

[0037] Figure 1 1 is a schematic diagram of a gas phase reactor system 100 showing the addition of at least two catalysts, at least one of which is added as a trim catalyst. The catalyst slurry mixture from catalyst tank 106 and the solution catalyst mixture from trim pot 108 can be mixed online. For example, the solution catalyst mixture and the catalyst slurry mixture can be mixed by utilizing a mixer, such as a static mixer 109 and / or a stirred vessel. Alternatively, any suitable mixer can be used, including, for example, mixing in a conduit, mixing using a mixing device, or mixing in a continuously stirred tank. Any mixer capable of contacting the solution catalyst mixture and the catalyst slurry mixture can be used.

[0038] Catalyst tank 106 contains a first catalyst slurry mixture. The first catalyst slurry mixture can be prepared by any suitable method, including, for example, by mixing particles of the first catalyst with mineral oil. Catalyst tank 106 can be a stirred holding tank configured to maintain a uniform solid concentration. In at least one embodiment, catalyst tank 106 can be maintained at an elevated temperature (relative to room temperature), such as 30°C to 80°C. Alternatively, catalyst tank 106 can be maintained at 30°C to 40°C, 40°C to 50°C, 50°C to 60°C, 60°C to 80°C, or any range therebetween. The elevated temperature can be achieved by electrically tracing the catalyst tank 106 using, for example, a heating blanket. Maintaining catalyst tank 106 at an elevated temperature can further reduce or eliminate the formation of solid residues on the vessel walls, which otherwise might slide down the wall and cause blockage in downstream transport lines. In at least one embodiment, catalyst tank 106 can have a volume of 0.5 cubic meters (m 3 ) to 8.0m 3 Alternatively, the volume of the catalyst tank 106 may be 0.5m 3 Up to 1.0m 3 , 1.0m 3 Up to 2.0m 3 , 2.0m 3 Up to 3.0m 3 3.0m 3 Up to 4.0m 3 , 4.0m 3 Up to 5.0m 3 5.0m 3 Up to 6.0m 3 、6.0m 3 Up to 7.0m 3 、7.0m 3 Up to 8.0m 3 range, or any range in between.

[0039] The catalyst tank 106 can be maintained at a pressure of 1.0 bar to 4.0 bar. Alternatively, the pressure of the catalyst tank 106 can be in the range of 1.0 bar to 1.5 bar, 1.5 bar to 2.0 bar, 2.0 bar to 2.5 bar, 2.5 bar to 3.0 bar, 3.0 bar to 3.5 bar, 3.5 bar to 4.0 bar, or any range therebetween. In at least one embodiment, the pipes 130 and 140 of the gas phase reactor system 100 can be maintained at an elevated temperature (relative to room temperature), for example, 30°C to 80°C. Alternatively, the temperature of the pipes 130 and 140 can be in the range of 30°C to 40°C, 40°C to 50°C, 50°C to 60°C, 60°C to 80°C, or any range therebetween. The elevated temperature can be achieved by electrically tracing the pipes 130 and / or 140 using, for example, a heating blanket. Maintaining conduit 130 and / or conduit 140 at an elevated temperature may provide the same or similar benefits as described with respect to the elevated temperature of catalyst canister 106 .

[0040] The solution catalyst mixture prepared by mixing the solvent and at least one second catalyst and / or activator may be placed in another container, such as a trim tank 108. The trim tank 108 may have a 0.5 m 3 Up to 1.0m 3 , 1.0m 3 Up to 2.0m 3 , 2.0m 3 Up to 3.0m 3 3.0m 3 Up to 4.0m 3 , 4.0m 3 Up to 5.0m 3 5.0m 3 Up to 6.0m 3 、6.0m 3 Up to 7.0m 3 、7.0m 3 Up to 8.0m 3 or any range of volumes therebetween. Trim tank 108 can be maintained at an elevated temperature (relative to room temperature), for example, 30° C. to 80° C. Alternatively, the temperature of trim tank 108 can be in the range of 30° C. to 40° C., 40° C. to 50° C., 50° C. to 60° C., 60° C. to 80° C., or any range therebetween. Trim tank 108 can be heated by, for example, electrically tracing trim tank 108 via a heating blanket. Maintaining trim tank 108 at an elevated temperature can provide for reduced or eliminated foaming in conduit 130 and / or conduit 140 when the catalyst slurry mixture from catalyst tank 106 is combined in-line (also referred to herein as "on-line") with the solution catalyst mixture from trim tank 108.

[0041] The catalyst slurry mixture can then be combined in-line with the solution catalyst mixture to form a slurry / solution catalyst mixture or a final catalyst composition. Optionally, a nucleating agent 107, such as silica, alumina, fumed silica, or any other suitable particulate material can be added to the slurry and / or solution in-line and / or in the catalyst tank 106 or trim tank 108 (this optional addition is not included in the catalyst tank 106). Figure 1 ). Similarly, additional activators or catalyst compounds can be added online. For example, a second catalyst slurry mixture comprising a different catalyst can be introduced from a second catalyst tank or "catalytic tank" (which can include wax and mineral oil). The two catalyst slurry mixtures can be used as a catalyst system with or without the addition of a solution catalyst mixture from the trim tank 108. The controller 152 can include a computer system, a microcontroller, a programmable logic controller, or any other control system capable of monitoring and regulating process variables within the gas phase reactor system 100. The controller 152 can also include other devices that perform control, including sensors, actuators, and control algorithms.

[0042] Catalyst slurry mixture and solution catalyst mixture can be mixed online.For example, solution catalyst mixture and catalyst slurry mixture can be mixed by utilizing mixing vessel, such as static mixer 109 and / or stirred vessel.In some embodiments, mixing vessel may include static mixer 109, followed by stirred vessel.The mixing of catalyst slurry mixture and solution catalyst mixture is enough to allow the catalyst compound in solution catalyst mixture to be dispersed in catalyst slurry mixture, so that catalyst component (initially in solution) migrates to supported activator (initially present in slurry).Described combination can form the uniform dispersion of catalyst compound on described supported activator, thus forms catalyst composition.The time length that slurry and solution can contact can be in the range of 1 minute to 4 hours.Or, this time length can be 1 minute to 10 minutes, 10 minutes to 30 minutes, 30 minutes to 1 hour, 1 hour to 1.5 hours, 1.5 hours to 2 hours, 2 hours to 2.5 hours, 2.5 hours to 3 hours, 3 hours to 3.5 hours, 3.5 hours to 4 hours, or any scope therebetween.

[0043] The static mixer 109 of the gas phase reactor system 100 can be maintained at an elevated temperature (relative to room temperature), for example, from 30°C to 80°C. Alternatively, the temperature of the static mixer 109 can be in the range of from 30°C to 40°C, from 40°C to 50°C, from 50°C to 60°C, from 60°C to 80°C, or any range therebetween. The elevated temperature of the static mixer 109 can be achieved by electrically tracing the static mixer 109 using, for example, a heating blanket. Maintaining the static mixer 109 at an elevated temperature can reduce or eliminate foaming in the static mixer 109 and can promote mixing of the catalyst slurry mixture and the catalyst solution (compared to lower temperatures), which reduces run time in the static mixer and the overall polymerization process.

[0044] Optionally, an aluminum alkyl, an aluminum ethoxylate, an aluminoxane, an antistatic agent, or a borate activator, such as a C1 to C 15 Alkyl aluminum (such as triisobutyl aluminum, trimethyl aluminum, etc.), C1 to C 15 Ethoxylated alkylaluminum or methylaluminoxane, ethylaluminoxane, isobutylaluminoxane, modified aluminoxane etc. are added to the mixture of the described slurry / solution catalyst mixture in pipeline.Alkylates (alkyls), antistatic agents, borate activators and / or aluminoxane can be directly added to the combination of described solution catalyst mixture and catalyst slurry mixture from alkyl container 110, or can be added via extra alkane (for example, hexane, heptane and / or octane) carrier stream, for example, from carrier container 112.Extra alkylates, antistatic agents, borate activators and / or aluminoxane can be by 500ppm at the most, 1 to 300ppm, 10ppm to 300ppm, or 10 to 100ppm exist.Carrier gas 114 such as nitrogen, argon, ethane, propane etc. can be added online to the mixture of described slurry and solution.In embodiments, carrier gas can be added at a rate of 0.5 kilograms per hour (kg / hr) to 45kg / hr. Alternatively, the carrier gas addition rate can range from 0.5 kg / hr to 1.0 kg / hr, 1.0 kg / hr to 10 kg / hr, 10 kg / hr to 20 kg / hr, 20 kg / hr to 30 kg / hr, 30 kg / hr to 45 kg / hr, or any range therebetween.

[0045] A liquid carrier stream can be introduced into the combination of the solution catalyst mixture and the catalyst slurry mixture. The mixture of solution, slurry, and liquid carrier stream can be passed through a mixer or length of pipe for mixing prior to contact with the gaseous carrier stream. Similarly, a comonomer 116, such as hexene, another α-olefin, or a diolefin, can be added in-line to the mixture of slurry and solution.

[0046] A gas stream 126 (e.g., cycle or recycle gas 124, monomer, nitrogen, or other material) can be introduced into an injection nozzle 148, which can include a support tube 128 at least partially surrounded by an injection tube 120. The slurry / solution catalyst mixture can pass through the injection tube 120 into the fluidized bed reactor 122. In at least one embodiment, the injection tube 120 can atomize the slurry / solution mixture. Any number of suitable pipe sizes and configurations can be used to atomize and / or inject the slurry / solution mixture.

[0047] The fluidized bed reactor 122 may include a reaction zone 132 and a deceleration zone 134. The reaction zone 132 may include a bed 136, which may include a bed of growing polymer particles, the formed polymer particles, a small amount of catalyst particles fluidized by the continuous flow of gaseous monomer, and a diluent passing through the reaction zone to remove the heat of polymerization. Optionally, a portion of the recycle gas 124 may be cooled and compressed to form a liquid, which, upon re-entering the reaction zone, may increase the heat removal capacity of the recycle gas stream. A suitable gas flow rate can be readily determined experimentally. The rate at which gaseous monomer is added to the recycle gas stream may be equal to the rate at which particulate polymer product and its associated monomer are removed from the reactor, and the composition of the gas passing through the reactor may be adjusted to maintain a substantially steady-state gaseous composition within the reaction zone. The gas exiting the reaction zone 132 may be passed to the deceleration zone 134, where entrained particles may be removed, for example, by gravity separation, as the entrained particles slow and fall back into the reaction zone 132. If desired, finer entrained particles and dust can be removed in a separation system 138, such as a cyclone separator and / or a fine filter. The recycle gas 124 can be passed through a heat exchanger 144, where at least a portion of the heat of polymerization can be removed. The gas can then be compressed in a compressor 142 and returned to the reaction zone 132. To promote particle formation in the fluidized bed reactor 122, a nucleating agent 118 (e.g., fumed silica) can be added directly to the fluidized bed reactor 122. Conventional trim polymerization methods include introducing nucleating agents into the polymerization reactor. In addition, when a metallocene catalyst or other similar catalyst is used in a gas phase reactor, oxygen or fluorobenzene can be added directly to the fluidized bed reactor 122 or to the gas stream 126 to control the polymerization rate.

[0048] Figure 1It is not restrictive because additional solution catalyst mixture and / or catalyst slurry mixture can be used.For example, catalyst slurry mixture can be combined with two or more solution catalyst mixtures with identical or different catalyst compounds and / or activator.Similarly, solution catalyst mixture can be combined with two or more catalyst slurry mixtures, and each of the catalyst slurry mixtures has identical or different supports and identical or different catalyst compounds and / or activator.Similarly, two or more catalyst slurry mixtures can be combined with two or more solution catalyst mixtures such as online, wherein each catalyst slurry mixture includes identical or different supports and can include identical or different catalyst compounds and / or activator, and solution catalyst mixture can include identical or different catalyst compounds and / or activator.For example, catalyst slurry mixture can contain supported activator and two different catalyst compounds, and two solution catalyst mixtures, each solution catalyst mixture contains one of the catalyst in the slurry, and wherein each solution catalyst mixture can be combined with slurry online independently.

[0049] The reactor temperature of the fluidized bed process can be in the range of 30°C to 200°C. Alternatively, the reactor temperature can be in the range of 30°C to 40°C, 40°C to 50°C, 50°C to 80°C, 80°C to 100°C, 100°C to 150°C, 150°C to 200°C, or any range therebetween. Typically, the reactor can be operated at a suitable temperature taking into account the sintering temperature of the polymer product in the reactor. Therefore, in various embodiments, the upper temperature limit can be the melting temperature of the polyethylene copolymer produced in the reactor. However, higher temperatures can result in narrower molecular weight distribution, which can be improved by adding catalysts or other co-catalysts.

[0050] Hydrogen can be used in the polymerization process to help control or otherwise regulate the final properties of polyolefins. Using certain catalyst systems, increasing the concentration (partial pressure) of hydrogen can improve the flow index of polyethylene polymers, such as melt index. Therefore, melt index may be affected by the concentration of hydrogen. The amount of hydrogen in polymerization can be expressed as the molar ratio relative to total polymerizable monomers, for example, ethylene, or a blend of ethylene and hexene or propylene. The amount of hydrogen used in the polymerization process can be the amount for reaching the melt index required for the final polyolefin polymer. For example, the molar ratio of hydrogen to total monomers (H2: monomers) can be 0.0001 or greater, 0.0005 or greater, or 0.001 or greater. In addition, the molar ratio of hydrogen to total monomers (H2: monomers) can be 10 or lower, 5 or lower, 3 or lower, or 0.10 or lower. The scope of the molar ratio of hydrogen to monomers can include any combination of any molar ratio upper limit and any molar ratio lower limit described herein. In various embodiments, the amount of hydrogen in the reactor at any time may be in the range of up to 5,000 ppm, up to 4,000 ppm, up to 3,000 ppm, or 50 ppm to 5,000 ppm, or 50 ppm to 2,000 ppm. The amount of hydrogen in the reactor may be in the range of 1 ppm, 50 ppm, or 100 ppm to 400 ppm, 800 ppm, 1,000 ppm, 1,500 ppm, or 2,000 ppm, based on weight. Additionally, the ratio of hydrogen to total monomer (H2:monomer) may be in the range of 0.00001:1 to 2:1, 0.005:1 to 1.5:1, or 0.0001:1 to 1:1. The reactor pressure(s) in a gas phase process (single stage or two or more stages) can vary from 690 kilopascals (kPa) to 1,379 kPa, or from 1,724 kPa to 2,414 kPa, or from 2,759 kPa to 3,448 kPa.

[0051] The gas phase reactor may be capable of producing 10 kilograms / hour (kg / hr) to greater than 455 kg / hr, greater than 4,540 kg / hr, greater than 11,300 kg / hr, greater than 15,900 kg / hr, greater than 22,700 kg / hr, or greater than 29,000 kg / hr to 45,500 kg / hr of polymer.

[0052] In embodiments, the polymer product may have a melt index ratio (MIR) of from 10 to less than 300, or in many embodiments, from 20 to 66, e.g., from 25 to 55. Melt index (MI, I2) may be measured according to ASTM D-1238-20, wherein the melt index is determined using a 2.1 kg load and the melt index ratio is determined by the ratio of a 21.6 kg load to a 2.1 kg load, both at 190°C.

[0053] The polymer product may have a viscosity of 0.89 g / cm3 (g / cm 3 )、0.90g / cm 3 , 0.91g / cm 3 or 0.92g / cm 3 to 0.93g / cm 3 , 0.95g / cm 3 , 0.96g / cm 3 or 0.97g / cm 3 The density of the polymer product can be determined according to ASTM D-792-20. The polymer can have a density of 0.25 g / cm3 measured according to ASTM D-1895-17 Method B. 3 Up to 0.5g / cm 3 For example, the bulk density of a polymer can be 0.30 g / cm 3 , 0.32g / cm 3 or 0.33g / cm 3 to 0.40g / cm 3 , 0.44g / cm 3 or 0.48g / cm 3 .

[0054] The polymerization process according to various embodiments may include contacting one or more olefin monomers with a catalyst slurry mixture that may include mineral oil and catalyst particles. The one or more olefin monomers may be ethylene and / or propylene, and the polymerization process may include heating the one or more olefin monomers and the catalyst system to 70° C. or higher to form an ethylene polymer or a propylene polymer.

[0055] Useful monomers herein include substituted or unsubstituted C2 to C 40 α-olefins, such as C2 to C 20 α-olefins, such as C2 to C 12 α-olefins, such as ethylene, propylene, butene, pentene, hexene, heptene, octene, nonene, decene, undecene, dodecene and isomers thereof. For example, the monomers may include ethylene and one or more selected from propylene or C4 to C 40 Olefins, such as C4 to C 20 Olefins, such as C6 to C 12 Optional comonomers of olefins. C4 to C 40 The olefin monomers may be linear, branched or cyclic. 40 The cyclic olefins may be strained or unstrained, monocyclic or polycyclic, and may optionally include heteroatoms and / or one or more functional groups.

[0056] In some embodiments, C2 to C 40 The α-olefin monomers and optional comonomers include ethylene, propylene, butene, pentene, hexene, heptene, octene, nonene, decene, undecene, dodecene, norbornene, norbornadiene, dicyclopentadiene, cyclopentene, cycloheptene, cyclooctene, cyclooctadiene, cyclododecene, 7-oxanorbornene, 7-oxanorbornadiene, substituted derivatives thereof, and isomers thereof, such as hexene, heptene, octene, nonene, decene, dodecene, cyclooctene, 1,5-cyclooctadiene, 1-hydroxy-4-cyclooctene, 1-acetoxy-4-cyclooctene, 5-methylcyclopentene, cyclopentene, dicyclopentadiene, norbornene, norbornadiene, and their corresponding homologs and derivatives, such as norbornene, norbornadiene, and dicyclopentadiene.

[0057] In various embodiments, one or more dienes may be present in the polymer product at up to 10 wt %, such as 0.00001 to 1.0 wt %, such as 0.002 to 0.5 wt %, such as 0.003 to 0.2 wt %, based on the total weight of the composition. 500 ppm or less of the diene may be added to the polymerization, such as 400 ppm or less, or such as 300 ppm or less; additionally or alternatively, at least 50 ppm or 100 ppm or more, or 150 ppm or more of the diene may be added to the polymerization.

[0058] Diene monomers include any hydrocarbon structure having at least two unsaturated bonds, such as C4 to C 30wherein at least two of the unsaturated bonds are easily introduced into the polymer by stereospecific or non-stereospecific catalysts (one or more). Diene monomers can be selected from α, ω-diene monomers (i.e., divinyl monomers). Diene monomers are linear divinyl monomers, for example, those containing 4 to 30 carbon atoms. The example of diene can include, but is not limited to butadiene, pentadiene, hexadiene, heptadiene, octadiene, nonadiene, decadiene, 11 carbon diene, 12 carbon diene, 13 carbon diene, 14 carbon diene, 15 carbon diene, 16 carbon diene, 17 carbon diene, 18 carbon diene, 19 carbon diene, 21 carbon diene, 22 carbon diene, 23 carbon diene, 24 carbon diene, 25 carbon diene, 26 carbon diene. , heptacosadiene, octacosadiene, nonacosadiene, triacontadecadiene, 1,6-heptadiene, 1,7-octadiene, 1,8-nonadiene, 1,9-decadiene, 1,10-undecadiene, 1,11-dodecadiene, 1,12-tridecadiene, 1,13-tetradecadiene, and low molecular weight polybutadiene (e.g., having a weight average molecular weight (Mw) of less than 1000 grams per mole (g / mol)). Cyclic dienes include cyclopentadiene, vinyl norbornene, norbornadiene, ethylidene norbornene, divinylbenzene, dicyclopentadiene, or dienes containing higher rings with or without substituents at various ring positions.

[0059] The catalyst compositions (catalysts and / or catalyst systems) disclosed herein can be capable of producing ethylene polymers having a Mw of from 40,000 g / mol, 70,000 g / mol, 90,000 g / mol, or 100,000 g / mol to 200,000 g / mol, 300,000 g / mol, 600,000 g / mol, 1,000,000 g / mol, or 1,500,000 g / mol. The ethylene polymers can have a melt index (MI) of 0.6 or greater g / 10 min, such as 0.7 or greater g / 10 min, such as 0.8 or greater g / 10 min, such as 0.9 or greater g / 10 min, such as 1.0 or greater g / 10 min, such as 1.1 or greater g / 10 min, such as 1.2 or greater g / 10 min.

[0060] "Catalyst productivity" is a measure of how many grams of polymer (P) are produced over a period of T hours using a polymerization catalyst comprising W grams of catalyst (cat); and can be expressed as: P / (T x W) and expressed in units of gPgcat -1 hr -1The productivity of the catalyst composition disclosed herein can be at least 50 g (polymer) / g (catalyst) / hour, such as 500 or more g (polymer) / g (catalyst) / hour, such as 800 or more g (polymer) / g (catalyst) / hour, such as 5,000 or more g (polymer) / g (catalyst) / hour, such as 6,000 or more g (polymer) / g (catalyst) / hour. Method for preparing slurry catalyst mixture

[0061] The container or vessel can be used for producing or otherwise preparing the slurry catalyst mixture. One or more mineral oils can be introduced into the container. The mineral oil can be heated to a temperature of 30°C to 100°C in the container. Alternatively, the mineral oil can be heated to a temperature of 30°C to 40°C, 40°C to 50°C, 50°C to 60°C, 60°C to 80°C, 80°C to 100°C or any range therebetween, to produce heated mineral oil. The moisture concentration of the heated mineral oil can be reduced to produce dry mineral oil. For example, the moisture concentration of the heated mineral oil can be reduced by at least one of the following: (i) passing the first inert gas through the heated mineral oil, (ii) passing the second inert gas through the head space of the container, (iii) subjecting the heated mineral oil to a vacuum, and (iv) adding the aluminum-containing compound to the heated mineral oil. In various embodiments, two or more, three or more, or four or more of the above may be used in combination; for example, according to some embodiments, a combination of (i) and (ii); and / or in certain embodiments, a combination of (iii) and (iv).

[0062] With respect to (i) and (ii), the first and / or second inert gas may independently be or include, but is not limited to, nitrogen, carbon dioxide, argon, or any mixture thereof. The amount of the first and / or second inert gas (passing through the mineral oil or into the headspace of the container) may be metered based on volume turnover rates (where each turnover rate is equal to the volume of the container) and may be within a range from a lower limit of 5, 10, 15, or 20 volume turnover rates to an upper limit of 30, 40, 45, 50, 55, or 60 volume turnover rates (ranges from any lower limit to any upper limit are contemplated). The container volume is not limited, but may be, for example, 0.75, 1.15, 1.5, 1.9, or 2.3 cubic meters (m 3 ) to 3, 3.8, 5.7 or 7.6m 3In the range of the upper limit of 1 hour (hr), 2hr, 3hr, 4hr or 5hr to 6hr, 8hr, 10hr, 12hr, 24hr or longer time period through heated mineral oil. About (iii), heated mineral oil can be subjected to vacuum (for example, less than 101kPa absolute pressure, less than 75kPa absolute pressure, less than 60kPa absolute pressure or less than the pressure of 55kPa absolute pressure). In various embodiments, the scope of vacuum pressure can be from the lower limit of any one of 0.67, 1, 10, 15 or 20kPa absolute pressure to the upper limit of any one of 30, 40, 55, 60, 65 or 80kPa absolute pressure, wherein contemplated herein the scope from any aforementioned lower limit to any aforementioned upper limit. Heated mineral oil can be subjected to vacuum 1 hour (hr), 2hr, 3hr, 4hr or 5hr to 6hr, 8hr, 10hr, 12hr, 24hr or longer time period. About (iv), the aluminum-containing compound can be or can include but is not limited to by formula AlR (3-a) X a The compound represented by wherein R is a branched or straight chain alkyl, cycloalkyl, heterocycloalkyl, aryl or hydride group containing 1 to 30 carbon atoms, X is a halogen, and a is 0, 1 or 2. For example, the aluminum-containing compound can be or can include trihexylaluminum, triethylaluminum, trimethylaluminum, triisobutylaluminum, diisobutylaluminum bromide, diisobutylaluminum hydride, methylaluminoxane, modified methylaluminoxane, ethylaluminoxane, isobutylaluminoxane or any mixture thereof. The modified methylaluminoxane can be prepared by the hydrolysis of trimethylaluminum and higher trialkylaluminum such as triisobutylaluminum. The modified methylaluminoxane is usually more soluble in aliphatic solvents and more stable during storage. There are multiple well-known methods for preparing aluminoxanes and modified aluminoxanes.

[0063] The dry mineral oil may have a moisture concentration of less than or equal to 100 parts per million parts of water (ppmw), less than or equal to 85 ppmw, less than or equal to 70 ppmw, less than or equal to 60 ppmw, less than or equal to 55 ppmw, less than or equal to 50 ppmw, less than or equal to 45 ppmw, less than or equal to 40 ppmw, less than or equal to 35 ppmw, less than or equal to 30 ppmw, less than or equal to 25 ppmw, or less than or equal to 20 ppmw, as measured according to ASTM D1533-12. The dry mineral oil may have a moisture concentration of less than or equal to 100 parts per million parts of water (ppmw), less than or equal to 85 ppmw, less than or equal to 70 ppmw, less than or equal to 60 ppmw, less than or equal to 55 ppmw, less than or equal to 50 ppmw, less than or equal to 45 ppmw, less than or equal to 40 ppmw, less than or equal to 35 ppmw, less than or equal to 30 ppmw, less than or equal to 25 ppmw, or less than or equal to 20 ppmw, as measured according to ASTM D4052-18a at 25°C. 3 , 0.86g / cm 3 or 0.87g / cm 3 to 0.88g / cm 3 , 0.89g / cm 3 or 0.9g / cm 3and / or the dry mineral oil may have a kinematic viscosity at 40° C. of 50 centistokes (cSt), 75 cSt, or 100 cSt to 150 cSt, 200 cSt, 250 cSt, or 300 cSt according to ASTM D341-20e1. Optionally, the dry mineral oil may also or alternatively have an average molecular weight of 250 g / mol, 300 g / mol, 350 g / mol, 400 g / mol, 450 g / mol, or 500 g / mol to 550 g / mol, 600 g / mol, 650 g / mol, 700 g / mol, or 750 g / mol according to ASTM D2502-14(2019)e1.

[0064] Once dry mineral oil is produced, the catalyst particles can be introduced into the dry mineral oil to produce a mixture. The mixture can be mixed, blended, stirred or otherwise agitated for at least 2 hours to remove at least a portion of any gas that may be present in the pores of the catalyst particles to produce a slurry catalyst mixture. In some embodiments, the mixture can be stirred for 2 hours, 2.5 hours, 3 hours, 3.5 hours, 4 hours, 4.5 hours, 5 hours or more to produce a slurry catalyst mixture; and / or during the stirring of the mixture, the temperature of the mixture can be maintained at a temperature of 50°C, 55°C, 60°C or 65°C to 75°C, 80°C, 85°C or 90°C. In other embodiments, the temperature of the mixture can be allowed to cool. For example, the mixture can be allowed to cool to a temperature of 45°C, 40°C, 35°C or 30°C during the stirring of the mixture.

[0065] The container can include one or more mixing devices that can be configured to mix, blend, stir or otherwise stir the mixture in the container. For example, the mixing device can be a rotatable mixing device. Suitable rotatable mixing devices can include one or more blades or impellers that are configured to stir one or more components of the slurry catalyst mixture in the container when rotating. The rotatable mixing device can rotate at 40 revs / min (rpm), 50 rpm, 75 rpm or 100 rpm to 150 rpm, 175 rpm, 200 rpm, 225 rpm or 250 rpm. As another example, the mixture can be stirred via ultrasonic waves; and / or it can be stirred by moving the container, for example, rolling the container or rotating the container back and forth along its axis.

[0066] The mineral oil may also be stirred during introduction into the vessel; during heating of the mineral oil; during reduction of the water concentration in the mineral oil; and / or during introduction of the catalyst particles into the mineral oil.

[0067] The mineral oil in the slurry catalyst mixture may also be referred to as a diluent. In addition, in addition to the mineral oil, the slurry catalyst mixture may optionally include one or more additional diluents. Additional diluents may be or may include, but are not limited to, toluene, ethylbenzene, xylene, pentane, hexane, heptane, octane, other hydrocarbons, or any combination thereof.

[0068] The slurry catalyst mixture can have a solids content of 1% to 40% by weight. For example, the slurry catalyst mixture can have a solids content of 1% to 5% by weight, 5% to 10% by weight, 10% to 15% by weight, 15% to 20% by weight, 20% to 25% by weight, 25% to 30% by weight, 35% to 40% by weight, or any range therebetween.

[0069] While wax has heretofore been considered essential for many slurry catalyst mixtures, for example, for stability (especially for storage and transportation), it should be noted that the slurry catalyst mixtures of various embodiments herein may advantageously omit wax. Thus, according to such embodiments, the slurry catalyst mixture may be free of any wax having a melting point greater than or equal to 25° C. at atmospheric pressure, based on the total weight of the slurry catalyst mixture. More generally, the slurry catalyst mixture may contain less than or equal to 3 wt%, less than or equal to 2.5 wt%, less than or equal to 2 wt%, less than or equal to 1.5 wt%, less than or equal to 1 wt%, less than or equal to 0.9 wt%, less than or equal to 0.8 wt%, less than or equal to 0.7 wt%, less than or equal to 0.6 wt%, less than or equal to 0.5 wt%, less than or equal to 0.4 wt%, less than or equal to 0.3 wt%, less than or equal to 0.2 wt%, or less than or equal to 0.1 wt% of any wax having a melting point greater than or equal to 25° C. at atmospheric pressure, based on the total weight of the slurry catalyst mixture. The term "wax" as used herein includes petrolatum, also known as vaseline or petroleum wax. Petroleum wax includes paraffin wax and microcrystalline wax, which includes slack wax and scale wax. If present, the wax may have a viscosity of 0.7 g / cm 3 , 0.73g / cm 3 or 0.75g / cm 3 to 0.87g / cm 3 , 0.9g / cm 3 or 0.95g / cm 3If present, the wax may have a kinematic viscosity at 100°C of from 5 cSt, 10 cSt, or 15 cSt to 25 cSt, 30 cSt, or 35 cSt. If present, the wax may have a melting point at atmospheric pressure of from 25°C, 35°C, or 50°C to 80°C, 90°C, or 100°C. If present, the wax may have a boiling point of 200°C or higher, 225°C or higher, or 250°C or higher.

[0070] The term "wax" also refers to or otherwise includes any wax that is not considered to be a petroleum wax, including animal wax, vegetable wax, mineral fossil or ozokerite, olefinic polymer and polyol ether-ester, chlorinated naphthalene and hydrocarbon wax. Animal wax may include beeswax, lanolin, shellac wax and Chinese insect wax. Vegetable wax may include carnauba wax, candelilla wax, bayberry wax and sugarcane wax. Fossil paraffin or ozokerite may include ozocerite, ceresin and montan. Olefinic polymer and polyol ether-ester include polyethylene glycol and methoxypolyethylene glycol. Hydrocarbon wax includes the wax produced via the Fischer-Tropsch synthesis process.

[0071] Once the slurry catalyst mixture has been produced, the slurry catalyst mixture can be transferred from the vessel to a catalyst tank or cat tank configured to introduce the slurry catalyst mixture into a gas phase polymerization reactor, such as Figure 1In the gas phase polymerization reactor described in

[0014] , the container can be located on-site at a manufacturing facility that includes a gas phase polymerization reactor. Thus, in various embodiments, the container can be located on-site at a manufacturing facility that includes a gas phase polymerization reactor. By preparing the slurry catalyst mixture on-site at the manufacturing facility, the use of slurry catalyst cylinders for transporting the slurry catalyst mixture can be avoided because the slurry catalyst mixture can be introduced into a catalyst tank or "cat pot" during preparation, and the slurry catalyst mixture can be introduced from the catalyst tank or "cat pot" into the gas phase polymerization reactor. By preparing the slurry catalyst mixture on-site at the manufacturing facility, the slurry catalyst mixture can be introduced into the gas phase polymerization reactor within a period of less than or equal to 180 minutes, less than or equal to 150 minutes, less than or equal to 125 minutes, less than or equal to 100 minutes, less than or equal to 80 minutes, less than or equal to 60 minutes, less than or equal to 50 minutes, or less than or equal to 40 minutes after the start of stirring of the mixture. On the other hand, by preparing the slurry catalyst mixture on-site at the manufacturing facility, the slurry catalyst mixture can be introduced into the gas phase polymerization reactor within a time period of less than or equal to 180 minutes, less than or equal to 150 minutes, less than or equal to 125 minutes, less than or equal to 100 minutes, less than or equal to 80 minutes, less than or equal to 60 minutes, less than or equal to 50 minutes, or less than or equal to 40 minutes after terminating or stopping agitation of the mixture.

[0072] Although, as described above, wax can be advantageously omitted in certain catalyst mixtures where storage and / or shipping stability is not required, it has surprisingly been discovered that wax and / or additional diluent in certain catalyst mixtures can aid the polymerization process in certain circumstances, e.g., depending on the nature(s) of the catalyst compound(s) in the slurry catalyst mixture. Thus, it is surprising that even when one would think it would be desirable to omit wax or other diluent (e.g., because increased storage / shipping stability is not desired), it has been discovered that certain catalyst slurries should include wax or other diluent. Thus, methods according to various embodiments can include identifying slurry catalyst mixture(s) that require wax and / or additional diluent, and including wax in such slurry catalyst mixture(s) (preferably also while not including wax and / or additional diluent in the slurry catalyst mixture when no processing advantage can be obtained through the presence of the wax and / or diluent).

[0073] Thus, according to some embodiments, the polymerization method may include introducing a carrier gas, one or more olefins, and a first slurry catalyst mixture into a polymerization reactor at a first time. The first slurry catalyst mixture may include the contact product of one or more catalysts selected from the first group of catalysts, a first support, a first activator, a first mineral oil, and a wax having a melting point greater than or equal to 25° C. at atmospheric pressure. The first slurry catalyst mixture may include greater than 1% by weight of the wax based on the total weight of the first slurry catalyst mixture. The one or more olefins may be polymerized in the presence of the first catalyst within the polymerization reactor to produce a first polymer product.

[0074] Then, at a second time after the first time, a second slurry catalyst mixture can be introduced into the polymerization reactor. This can occur, for example, as part of a grade transition in a polymer production activity (for example, the first slurry catalyst mixture can be stopped before, during, or shortly after the introduction of the second slurry catalyst mixture). The second slurry catalyst mixture may include the contact product of one or more catalysts selected from the second group of catalysts, a second support, a second activator, and a second mineral oil. The one or more catalysts selected from the second group of catalysts are preferably different from the one or more catalysts selected from the first group of catalysts; however, the first and second supports, activators, and / or mineral oils may be the same or different. In contrast to the first slurry catalyst mixture, the second slurry catalyst mixture may not contain or include less than or equal to 1% by weight of any wax having a melting point greater than or equal to 25° C. at atmospheric pressure, based on the total weight of the slurry catalyst mixture. The second slurry catalyst mixture can be prepared, in particular, according to the above-described method, requiring the removal of water from the slurry catalyst mixture. The polymerization process may also include polymerizing one or more olefins in the presence of a second catalyst in the polymerization reactor to produce a second polymer product. The carrier gas may be or may include, but is not limited to, nitrogen, argon, ethane, propane, or any mixture thereof. The one or more olefins may be or may include one or more substituted or unsubstituted C2 to C 40 α-olefins, as further described below.

[0075] In particular, it is believed that the catalysts in the first group of catalysts and the catalysts in the second group of catalysts will generally have different bulk densities, which can help identify which slurry catalyst mixtures may benefit from wax and / or additional diluents and which may not benefit from wax and / or additional diluents. For example, one or more catalysts in the first group of catalysts may have a bulk density greater than or equal to 0.43 g / cm 3 , greater than or equal to 0.44g / cm 3 or greater than or equal to 0.45g / cm 3 On the other hand, one or more catalysts in the second group of catalysts may have a bulk density of less than 0.45 g / cm 3 , less than 0.44g / cm3 , less than 0.43g / cm 3 , less than 0.42g / cm 3 , less than 0.41g / cm 3 or less than 0.40g / cm 3 In other words, in various embodiments, the bulk density of one or more catalysts in the first group of catalysts is greater than the bulk density of one or more catalysts in the second group of catalysts. catalyst particles

[0076] Catalyst or catalyst compound can be or can include but not limited to, one or more metallocene catalyst compounds.In some embodiments, catalyst can include at least the first metallocene catalyst compound and the second metallocene catalyst compound, and wherein the first and second metallocene catalyst compounds have chemical structures different from each other.Metallocene catalyst compound can include the Cp ligand (cyclopentadienyl and ligand similar to cyclopentadienyl isolobal) with one or more and at least one 3rd family to 12th family metal atom bonds, and one or more leaving groups (one or more) catalyst compound bonded to the at least one metal atom.In further embodiments, catalyst further includes the 3rd and / or the 4th metallocene catalyst compound, and wherein the 3rd and the 4th metallocene catalyst compound have chemical structures different from each other and chemical structures different from the first and the second metallocene catalyst compounds.

[0077] Catalyst systems employing mixtures of two metallocene catalysts, particularly mixtures of (1) biscyclopentadienyl hafnocene (preferably bridged biscyclopentadienyl hafnocene) and (2) zirconocene, such as indenyl-cyclopentadienyl zirconocene (preferably unbridged indenyl-cyclopentadienyl zirconocene), are also suitable.

[0078] In some embodiments, the metallocene catalyst compound includes hafnocene. Suitable hafnocenes may include bridged or unbridged hafnocenes, preferably bridged hafnocenes, such as dichloro bis(n-propylcyclopentadienyl) hafnium, dimethyl bis(n-propylcyclopentadienyl) hafnium, dichloro (n-propylcyclopentadienyl, pentamethylcyclopentadienyl) hafnium, dimethyl (n-propylcyclopentadienyl, pentamethylcyclopentadienyl) hafnium, dichloro (n-propylcyclopentadienyl, pentamethylcyclopentadienyl) hafnium, hafnium, dimethyl·bis(n-butylcyclopentadienyl) hafnium, dimethyl·bis(n-butylcyclopentadienyl) hafnium, dimethyl·bis(1-methyl-3-n-butylcyclopentadienyl) hafnium, and combinations thereof.

[0079] Other suitable hafnocene compounds include, but are not limited to, rac / meso Me2Si(Me3SiCH2Cp)2HfMe2; rac / meso Me2Si(Me3SiCH2Cp)2HfMe2; rac / meso Ph2Si(Me3SiCH2Cp)2HfMe2; rac / meso (CH2)3Si(Me3SiCH2Cp)2HfMe2; rac / meso (CH2)4Si(Me3SiCH2Cp)2HfMe2; rac / meso (C6F5)2Si(Me3SiCH2Cp)2HfMe2; rac / meso (CH2)3Si(Me3SiCH2Cp)2HfMe2; rac / meso (C6F5)2Si(Me3SiCH2Cp)2HfMe2; rac / meso (CH2)3Si(Me3SiCH2Cp)2HfMe2 iCH2Cp)2ZrMe2; rac / meso Me2Ge(Me3SiCH2Cp)2HfMe2; rac / meso Me2Si(Me2PhSiCH2Cp)2HfMe2; rac / meso Ph2Si(Me2PhSiCH2Cp)2HfMe2; Me2Si(Me4Cp)(Me2PhSiCH2Cp)HfMe2 and combinations thereof.

[0080] As described above, suitable catalyst compounds may additionally or alternatively include zirconocenes, such as unbridged zirconocenes, including, but not limited to, bis(indenyl)zirconium dichloride, bis(indenyl)zirconium dimethyl, bis(tetrahydro-1-indenyl)zirconium dichloride, bis(tetrahydro-1-indenyl)zirconium dimethyl, rac / meso-bis(1-ethylindenyl)zirconium dichloride, rac / meso-bis(1-ethylindenyl)zirconium dimethyl, rac / meso-bis(1-methylindenyl)zirconium dichloride, rac / meso-bis(1-methylindenyl)zirconium dimethyl, )zirconium dichloride, racemic / meso-bis(1-propylindenyl)zirconium dimethyl, racemic / meso-bis(1-propylindenyl)zirconium dichloride, racemic / meso-bis(1-butylindenyl)zirconium dimethyl, racemic / meso-bis(1-butylindenyl)zirconium dichloride, meso-bis(1-ethylindenyl)zirconium dimethyl, meso-bis(1-ethylindenyl)zirconium dimethyl, (1-methylindenyl)(pentamethylcyclopentadienyl)zirconium dichloride, (1-methylindenyl)(pentamethylcyclopentadienyl)zirconium dimethyl and combinations thereof. Slurry catalyst mixture including activator and support

[0081] As described above, in addition to one or more catalysts, the slurry catalyst mixture may also include one or more activators and / or supports. The term "activator" refers to any compound or combination of compounds that can activate a single-site catalyst compound or component (e.g., by generating a cationic species of the catalyst component), whether supported or unsupported. For example, this can include extracting at least one leaving group (the "X" group in the single-site catalyst compounds described herein) from the metal center of the single-site catalyst compound / component. An activator may also be referred to as a "co-catalyst." For example, a slurry catalyst mixture may include two or more activators (e.g., aluminoxanes and modified aluminoxanes) and a catalyst compound, or a slurry catalyst mixture may include a supported activator and more than one catalyst compound. In a particular embodiment, a slurry catalyst mixture may include at least one support, at least one activator, and at least two catalyst compounds. For example, a slurry may include at least one support, at least one activator, and two different catalyst compounds, which may be added individually or in combination to produce a slurry catalyst mixture. For example, a mixture of a support (e.g., silica) and an activator (e.g., aluminoxane) may be contacted with a first catalyst compound, allowed to react, and thereafter the mixture may be contacted with a second different catalyst compound, such as in a trimming system. Also, additional catalyst compounds (third, fourth, etc.) can be contacted in a similar manner, either sequentially or together with the first and / or second catalyst compounds.

[0082] The molar ratio of the metal in the activator to the metal in the catalyst compound in the slurry catalyst mixture can be from 1000:1 to 0.5:1, from 300:1 to 1:1, from 100:1 to 1:1, or from 150:1 to 1:1. The slurry catalyst mixture can include a support material, which can be any inert particulate support material known in the art, including but not limited to silica, fumed silica, alumina, clay, talc, or other support materials, such as those disclosed above. In one embodiment, the slurry can include silica and an activator, such as methylaluminoxane ("MAO"), modified methylaluminoxane ("MMAO"), as discussed further below. In embodiments, the activator includes an aluminoxane compound, a modified aluminoxane compound, and an ionizing anion precursor compound that extracts reactive, sigma-bound metal ligands, cationizes the metal compound, and provides a charge-balancing non-coordinating or weakly coordinating anion.

[0083] As mentioned above, one or more organoaluminum compounds, such as one or more alkylaluminum compounds, can be used together with aluminoxane. For example, alkylaluminum materials that can be used include diethylaluminum ethoxylate, diethylaluminum chloride and / or diisobutylaluminum hydride. Examples of trialkylaluminum compounds include, but are not limited to, trimethylaluminum, triethylaluminum ("TEAL"), triisobutylaluminum ("TiBAL"), tri-n-hexylaluminum, tri-n-octylaluminum, tripropylaluminum, tributylaluminum, and the like.

[0084] Suitable supports include, but are not limited to, active and inactive materials, synthetic or naturally occurring zeolites, and inorganic materials such as clays and / or oxides such as silica, alumina, zirconia, titania, silica-alumina, ceria, magnesia, or combinations thereof. In particular, the support can be silica-alumina, alumina, and / or a zeolite, especially alumina. The silica-alumina can be naturally occurring or in the form of a gelatinous precipitate or gel comprising a mixture of silica and a metal oxide.

[0085] In some embodiments, at least a portion of the slurry catalyst mixture may be contacted with a solution catalyst mixture to create or otherwise form a slurry / solution catalyst mixture. Solution Catalyst Mixture - Trimming Solution

[0086] The solution catalyst mixture may include a solvent and only catalyst compound (one or more), such as one or more metallocene catalyst compounds, or may further include an activator. In some embodiments employing two catalyst compounds, the solution catalyst mixture may be or may include, but is not limited to, the contact product of a solvent / diluent and a first catalyst or a second catalyst compound. In embodiments employing more than two catalyst compounds, the solution catalyst mixture may include any one or more contact products of a solvent / diluent and a first, second, third, or other catalyst compound. The catalyst compound (one or more) in the solution catalyst mixture may be unloaded. In addition, the slurry / solution catalyst mixture may be introduced into a gas phase polymerization reactor.

[0087] The solution catalyst mixture (if used) can be prepared by dissolving the catalyst compound(s) and optional activator in a liquid solvent. The liquid solvent can be an alkane, such as a C5 to C 30 Alkanes, or C5 to C 10 Alkanes. Cycloalkanes (e.g., cyclohexane) and aromatic compounds (e.g., toluene) may also be used. Mineral oil may be used as other alkanes such as one or more C5 to C 30Alkane is replaced or supplemented as solvent. The mineral oil in the solution catalyst mixture (if used) can have the same properties as the mineral oil that can be used to prepare the slurry catalyst mixture, as described above. The solvent should be liquid and relatively inert under polymerization conditions. Optionally, the solvent used in the solution catalyst mixture can be different from the diluent used in the slurry catalyst mixture. Or, on the other hand, the solvent used in the solution catalyst mixture can be identical with the diluent, i.e., the mineral oil (one or more) used in the slurry catalyst mixture and any additional diluent.

[0088] If the solution catalyst mixture includes both catalyst compound(s) and activator(s), the ratio of metal in the activator to metal in all catalyst compounds(s) in the solution catalyst mixture may be from 1000:1 to 0.5:1, from 300:1 to 1:1, or from 150:1 to 1:1. In various embodiments, the activator and catalyst compound(s) may be present together in the solution catalyst mixture in an amount of up to 90 wt%, up to 50 wt%, up to 20 wt%, such as up to 10 wt%, up to 5 wt%, less than 1 wt%, or between 100 ppm and 1 wt%, based on the weight of the solvent, activator, and catalyst. The one or more activators in the solution catalyst mixture, if used, may be the same as or different from the one or more activators used in the slurry catalyst mixture.

[0089] The solution catalyst mixture may include any one of the catalyst compounds (one or more) of the present disclosure. When the catalyst is dissolved in a solution, higher solubility may be required. Accordingly, the catalyst in the solution catalyst mixture may typically include a metallocene, which may have a higher solubility than other catalysts. In the polymerization process, any of the above-mentioned solution catalyst mixtures may be combined with any of the above-mentioned slurry catalyst mixtures. In addition, more than one solution catalyst mixture may be used. Continuity Additives-Static Control Agents

[0090] In the gas phase polyethylene production process, it may be necessary to use one or more static control agents to help promote the regulation of static levels in the reactor. A continuity additive is a chemical composition that can affect or drive the static charge (negative, positive, or to zero) in the fluidized bed when introduced into the reactor. The continuity additive used can depend at least in part on the properties of the static charge, and the selection of the static control agent can depend at least in part on the polymer being produced and / or the single site catalyst compound being used and vary. In some embodiments, a continuity additive or static control agent can be introduced into the reactor in an amount of 0.05ppm to 200ppm. Alternatively, the amount of the continuity additive or static control agent can be in the range of 0.05ppm to 2ppm, 5ppm, or 10ppm, or in the range of 20ppm to 50ppm, 75ppm, 100ppm, 150ppm, or 200ppm.

[0091] In some embodiments, the continuity additive may be or may include aluminum stearate. Continuity additives may be selected because they can absorb static charges in the fluidized bed without adversely affecting productivity. Other suitable continuity additives may be or may include, but are not limited to, aluminum distearate, ethoxylated amines, and combinations thereof. In some embodiments, the continuity additive comprises a mixture of a polysulfone copolymer, a polymeric polyamine, and an oil-soluble sulfonic acid. Any continuity additive may be used alone or in combination.

[0092] In some embodiments, the continuity additive may include fatty acid amines, amide-hydrocarbon or ethoxylated-amide compounds, carboxylate compounds (such as aryl-carboxylates and long-chain hydrocarbon carboxylates) and fatty acid-metal complexes; alcohols, ethers, sulfate compounds, metal oxides and other compounds known in the art. Some specific examples of control agents may be or may include, but are not limited to, 1,2-diether organic compounds, magnesium oxide, glycerides, ethoxylated amines (such as N,N-bis(2-hydroxyethyl)octadecylamine), alkyl sulfonates and alkoxylated fatty acid esters, N-oleyl anthranilate chromium salts, medialan acid and calcium salts of di-tert-butylphenol, α-olefin-acrylonitrile copolymers and polymeric polyamines, sorbitan monooleate, glycerol monostearate, methyl toluate, dimethyl maleate, dimethyl fumarate, triethylamine, 3,3-diphenyl-3-(imidazol-1-yl)-propyne and similar compounds. In some embodiments, another continuity additive may include a metal carboxylate, optionally with other compounds.

[0093] In some embodiments, the continuity additive can include an extracted metal carboxylate, such as an extracted metal carboxylate, which can be combined with an amine-containing reagent. For example, the extracted metal carboxylate can be combined with an antistatic agent, such as a fatty amine, such as a blend of ethoxylated stearylamine and zinc stearate, or a blend of ethoxylated stearylamine, zinc stearate, and octadecyl-3,5-di-tert-butyl-4-hydroxyhydrocinnamate.

[0094] Other continuity additives may include ethyleneimine additives, such as polyethyleneimine having the general formula:—(CH2—CH2—NH) n —, where n can be from 10 to 10,000. The polyethyleneimine can be linear, branched, or hyperbranched (i.e., forming a dendritic or dendritic polymer structure). The polyethyleneimine can be a homopolymer or copolymer of ethyleneimine or a mixture thereof (hereinafter referred to as polyethyleneimine(s)). Although represented by the chemical formula —(CH2-CH2-NH) n A linear polymer represented by - can be used as the polyethyleneimine, but materials having primary, secondary, and tertiary branching can also be used. Induced condensing agent

[0095] In the gas phase polyethylene preparation method, it may be necessary to use one or more induced condensing agents in the reactor. "Induced condensing agent (ICA)" used herein refers to one or more induced condensable fluids, which are volatile liquid hydrocarbons that can be selected from saturated hydrocarbons containing 2 to 10 carbon atoms, preferably 3 to 10 carbon atoms. Some suitable saturated hydrocarbons are propane, n-butane, isobutane, n-pentane, isopentane, neopentane, n-hexane, isohexane and other saturated C6 hydrocarbons, n-heptane, n-octane and other saturated C7 and C8 hydrocarbons, or mixtures thereof. A class of preferred induced condensable hydrocarbons includes C5 and C6 saturated hydrocarbons. Another class of preferred hydrocarbons includes C4 to C6 saturated hydrocarbons. Preferred hydrocarbons used as condensable fluids include pentane, for example isopentane. Condensable fluids can also include polymerizable condensable comonomers such as olefins, diolefins or mixtures thereof, including some monomers that can be partially or completely introduced into the polymer product as mentioned herein. End Use

[0096] Polymers produced by the methods disclosed herein and their blends can be used for forming operations such as film, sheet and fiber extrusion and coextrusion as well as blow molding, injection molding and roller molding. Films include blown or cast films formed by coextrusion or by lamination, which can be used as shrink films, adhesive films, stretch films, sealing films, oriented films, snack packaging, heavy-duty bags, grocery bags, baked and frozen food packaging, medical packaging, industrial liners, diaphragms, etc. in food contact and non-food contact applications. Fibers include melt spinning, solution spinning and meltblown fiber operations to be used in the manufacture of filters, diaper fabrics, medical garments, geotextiles, etc. in a woven or nonwoven form. Extruded products include medical tubing, wire and cable coatings, pipelines, geomembranes and pond liners. Molded products include single and multi-story buildings in the form of bottles, troughs, large hollow products, rigid food containers and toys.

[0097] In some embodiments, the present invention provides the polymkeric substance of the present invention.Particularly, any aforementioned polymer, for example ethylene copolymer or its blend, can be used for monolayer or multilayer blow molding, extrusion and / or shrink film.These films can be formed by many well-known extrusion or coextrusion techniques, for example blown film processing technology, wherein composition can be extruded through annular die with molten state, then expand to form uniaxial or biaxially oriented melt, then cool and form tubular, blown film, then can axially cut and launch to form flat film.Film can be non-oriented, uniaxially oriented or biaxially oriented to identical or different degree subsequently.

[0098] The polymkeric substance produced herein can further be blended with one or more second polymers and be used for film, molded parts and other typical applications.In one embodiment, the second polymer can be selected from ethylene homopolymer, ethylene copolymer and blend thereof.Useful second ethylene copolymer can comprise one or more comonomers except ethene, and can be random copolymer, statistical copolymer (as tatis tical copolymer), block copolymer and / or its blend.The method for preparing the second ethylene polymer is unrestricted, because it can pass through slurry, solution, gas phase, high pressure or other suitable methods, and by using the catalyst system that is suitable for polyethylene polymerization, for example Ziegler-Natta type catalyst, chromium catalyst, metallocene type catalyst, other suitable catalyst system or its combination, or by free radical polymerization preparation. Two-component catalyst system in slurry

[0099] As described above, due to different activation energies and activation efficiencies, the molar ratio of the various (e.g., at least two) types of active sites (e.g., deposited and supported catalyst compounds) on the two-component catalyst system is not necessarily equal to the molar ratio of the catalyst compound precursors used to prepare the supported catalyst system. Figure 2AExample processes for producing a two-component catalyst system (labeled "Two-Component Catalyst" in Figure 2) and using the two-component catalyst system in the production of a multimodal polymer are shown. Figure 2B The contribution of two types of active sites (supported active catalyst compounds) in the two-component catalyst system to the polymerization is shown. Figure 2C The relationship between the molar ratio of the two types of active sites in the two-component catalyst system and the molar ratio of the two types of catalyst compound precursors used to prepare the two-component catalyst system is shown. Figure 2A It can be seen that the relative contribution of the two types of active sites to polymerization (which in turn can be used to determine the composition of the resulting multimodal polymer) depends on the molar ratio of the two types of active sites on the support (catalyst compound) in the binary catalyst system. To date, the assessment of the molar ratio of the two types of active sites in a binary catalyst system has relied solely on polymerization tests (e.g., back-calculating the molar ratio of the two active sites based on the properties of the produced polymer).

[0100] Combined with the above Figure 1 An example of online trimming is described. The online trimming method allows a base supported catalyst system (comprising the contact product of a support, optional activator(s) and one, two or more catalyst compounds) to react with one, two or more additional catalyst compounds (which may be the same as or different from the catalyst compound(s) in the base supported catalyst system) to produce a trimmed catalyst characterized by different ratios of the two or more catalyst compounds (i.e., two or more types of active sites on the two-component catalyst system) before entering the gas phase reactor. Generally, it will be preferred to contact a base supported catalyst system having two (or three, etc.) catalyst compounds deposited thereon (i.e., two, three, etc. active sites) with an additional catalyst compound of one type of the two (or more) catalyst compounds deposited on the base supported catalyst system; thus, the ratio of the deposited catalyst compounds on the support in the trimmed catalyst system can be adjusted. Figure 3A The production flow of the tailored catalyst system is shown. Figure 3BIt is shown that the relative proportions of the two types of active sites, A* and B*, in the trimmed catalyst system depend on the original proportions in the base catalyst system, the trim level (the amount of precursor B trimmed per gram of base catalyst system), and the trim efficiency. In this example, "trim efficiency" is the percentage of trimmed precursor B that is activated; more generally, "trim efficiency" is the percentage of trimmed catalyst compound(s) (i.e., those added by contacting the catalyst slurry with the catalyst trimming solution according to the catalyst trimming method described above) that is actually activated (i.e., active in the trimmed catalyst system). In general, it is difficult to accurately predict and control the proportions of active sites in the trimmed catalyst.

[0101] It should be noted that although much of the discussion and examples herein focus on a two-component catalyst system (having two catalyst compounds), it is contemplated that the methods and systems described herein can be readily adapted for use with systems employing three, four, or more catalyst compounds. Thus, references herein to a "two-component catalyst" can be viewed more generally as references to a "multi-component catalyst" having two or more catalyst compounds (i.e., two or more types of active sites) deposited on a support. Soft sensors for estimating trimming effectiveness

[0102] In view of the foregoing, trimming efficiency is an important parameter of a multi-component catalyst system. In particular, trimming efficiency significantly affects the properties of the resulting polymer product, such as density, melt index (MI), melt index ratio (MIR), stiffness, toughness, and processability. However, there are currently no established or commercially available analytical methods (e.g., hardware-sensor based methods) to directly measure the trimming efficiency of a multi-component catalyst system. Therefore, embodiments of the present invention relate to soft sensor systems that are capable of determining a catalyst trimming effectiveness value (η) for a multi-component catalyst system (e.g., a two-component catalyst system), wherein the catalyst trimming effectiveness is an estimate or approximation of the actual trimming efficiency within the multi-component catalyst system. Thus, the catalyst trimming effectiveness value (η) ranges between zero (indicating no trimming effectiveness) and one (indicating total trimming effectiveness). As used herein, a "soft sensor" or "virtual sensor" is a set of computer-executable instructions (e.g., software instructions) that, when executed by a processor of a computing system, is designed to receive a set of inputs, process these inputs using one or more mathematical models, and provide at least one output from the one or more mathematical models. It will be understood that although the following discussion refers to gas phase polyethylene (GPPE) polymerization processes and polyethylene (PE) resins as examples, in other embodiments, the technology disclosed herein can be applied to other types of polymerization reactors (e.g., slurry phase polymerization systems) and other types of polymer products.

[0103] like Figure 1 As shown, in certain embodiments, the gas phase reactor system 100 may include a soft sensor system 160 having suitable computer circuitry to implement the soft sensor technology disclosed herein. Figure 1 In the illustrated embodiment, the soft sensor system 160 includes at least one processor 162 (e.g., processing circuitry, a central processing unit (CPU), a graphics processing unit (GPU)), at least one memory 164 (e.g., random access memory (RAM), read-only memory (ROM), a non-transitory computer-readable medium), and at least one storage device 166 (e.g., a solid-state drive, a hard drive, a flash drive). As discussed below, the memory 164 and / or storage device 166 are designed to store instructions (e.g., software instructions, computer-executable code) and data (e.g., inputs, outputs, intermediates) executed by the at least one processor 162 to perform the techniques described herein. In some embodiments, the soft sensor system 160 includes at least one networking device 168 (e.g., a wired or wireless networking interface) that enables the soft sensor system 160 to send and receive data, such as receiving input from a user, receiving information about the configuration or operation of other components of the gas-phase reactor system 100, adjusting the configuration or operation of other components of the gas-phase reactor system 100, providing output to a user, and the like. In some embodiments, the soft sensor system 160 can be implemented separately from the gas phase reactor system 100, such as in a server room, in a data center, or in a cloud-based environment.

[0104] Figure 41 is a flow chart of an embodiment of a process 170 for generating a gas phase polyethylene (GPPE) polymerization process data set 172. As discussed below, the GPPE polymerization process data set 172 is used by the soft sensor system 160 to determine a corresponding catalyst trim effectiveness value (η) for a given multi-component catalyst composition. For the embodiment shown, the process 170 begins by generating (block 174) a design of experiments (DOE) to collect a GPPE polymerization process data set 172 for a multi-component catalyst composition (e.g., a two-component catalyst composition) under various operating parameters of the gas phase reactor system 100. These operating parameters may include, but are not limited to, different catalyst formulations, different trim-to-catalyst ratios, and different parameters of the gas phase reactor system 100 (e.g., different mixing temperatures, reaction temperatures, mixing times, reaction times, reactor pressures, flow rates). Generally, the DOE seeks to ensure that the experimental data for the GPPE polymerization process data set 172 substantially or completely covers the high-dimensional independent variable space of the multi-component catalyst. In some embodiments, the DOE may be generated using an active learning approach, while in some embodiments, the DOE may be generated using classical screening, follow-up, and response surface experimental designs, or other suitable techniques.

[0105] for Figure 4 In the embodiment shown in FIG. 1 , process 170 continues (block 174) with a corresponding GPPE polymerization process for each experiment of the DOE to produce a corresponding polyethylene (PE) resin using a multi-component catalyst composition. Additionally, at block 174, each PE resin is characterized to determine relevant properties of each corresponding PE resin. Properties of the PE resin may include, but are not limited to, density, melt index (MI), and melt index ratio (MIR), which may be determined as discussed above. In certain embodiments, one or more aspects of performing the GPPE polymerization process and / or characterizing one or more aspects of the resulting PE resin may be automated to reduce costs and increase efficiency. The result or output of process 170 is a GPPE polymerization process dataset 172, which includes the operating parameters for each experiment of the DOE and the characterized properties of the PE resin produced by each of these experiments. In certain embodiments, the soft sensor system 160 may receive information regarding the operating parameters of each GPPE polymerization process directly from one or more components of the gas phase reactor system 100 and / or information regarding the characterization of the PE resin directly from the equipment used to perform these analyses, which information is then included in the GPPE polymerization process dataset 172.

[0106] Figure 5FIG. 8 is a flow chart of an embodiment of a process 80 for determining a catalyst trim effectiveness value (η) 182 and a trained process model 184 for a multi-component catalyst composition associated with a GPPE polymerization process dataset 172. The process 80 may be stored as computer-executable instructions (e.g., software) in at least one memory 164 and may be executed by Figure 1 The at least one processor 162 of the soft sensor system 160 shown is executed. Figure 5 As shown, it can be seen from Figure 4 The generated GPPE aggregation method data set 172 discussed is provided as input to the process 80 .

[0107] for Figure 5 In the embodiment shown in FIG, process 80 begins with processor 162 determining (block 186) (e.g., calculating or assuming) an initial catalyst trim effectiveness value (η) for the multi-component catalyst composition. In some embodiments, it can be assumed that the initial catalyst trim effectiveness value (η) for the multi-component catalyst composition is a predetermined value (e.g., 0.5). In some embodiments, processor 162 can calculate the initial catalyst trim effectiveness value (η) for the multi-component catalyst composition based on known catalyst activation fundamentals (e.g., a priori methods), for example, using Equation 1: Formula 1: η = f(MAO in activated catalyst, T 环境 , t 接触 , trim_solvent, ...), where: MAO in activated catalyst is the amount of activator such as MAO or MMAO present in the activated multicomponent catalyst composition (e.g., in grams); T 环境 is the ambient temperature (e.g., in degrees Celsius); t 接触 is the contact time of the multicomponent catalyst composition (e.g., in static mixer 109); trim_solvent is a property of the trim solvent. In other embodiments, other inputs related to operating parameters of the multi-component catalyst composition and / or gas phase reactor system may also be used in accordance with the present disclosure, as indicated by the ellipses in the list of input parameters for function f of Equation 1. A person of ordinary skill having the benefit of this disclosure will recognize other parameters (i.e., other catalyst fundamentals) that may affect trim efficiency based on the details of a given process in which the control methods and systems of this disclosure are being deployed.

[0108] for Figure 5In the embodiment shown in FIG, process 80 continues with processor 162 using the current catalyst trim effectiveness value (η) of the multicomponent catalyst composition to train (block 188) a corresponding process model for each property of the PE resin present in the GPPE polymerization process data set 172. Each process model is trained using a suitable machine learning method, including but not limited to: an elastic net regularization method, a least absolute shrinkage and selection operator (LASSO) method, a ridge regression method and a stepwise regression method, a random forest, a gradient boosting method, a neural network, a Gaussian process model, a support vector machine, and a multivariate adaptive regression spline. During training, each process model "learns" the relationship between a specific PE resin property (e.g., density, MI, MIR) of the GPPE polymerization process data set 172, the activated multicomponent catalyst composition, and the operating parameters of the GPPE polymerization process. In certain embodiments, an example process model is represented by Equation 2: Formula 2: Resin properties = g(CatComp,T,H-to-M,C-to-M,ICA,M-PP,t), in: Resin properties are specific properties of PE resin (e.g., density, MI, MIR); CatComp is an activated multi-component catalyst composition; T is the reactor bed temperature (e.g., in degrees Celsius); H-to-M is the ratio of hydrogen to α-olefin monomer (e.g., ethylene gas) in the reactor; C-to-M is the ratio of one or more α-olefin comonomers (e.g., hexene) to α-olefin monomer in the reactor; ICA is the amount (e.g., mole percent) of induced condensing agent (ICA) (e.g., isopentane, isobutane) in the reactor; M-PP is the partial pressure of the α-olefin monomer in the reactor (e.g., in kilopascals); t is the reactor residence time of the PE resin (eg, in seconds).

[0109] The CatComp value is calculated using the current catalyst trim effectiveness value (η) of the activated multicomponent catalyst composition associated with the multicomponent catalyst in Equation 2. For example, in a two-component catalyst composition including (e.g., from catalyst tank 106) catalyst A (e.g., a hafnocene catalyst or a bridged biscyclopentadienyl hafnocene catalyst) and catalyst B (e.g., a zirconocene catalyst or an unbridged indenyl-cyclopentadienyl zirconocene catalyst), where catalyst B also serves as a trim catalyst (e.g., from the trim solution in trim tank 108), the CatComp of the activated multicomponent catalyst composition can be calculated using Equation 3: Formula 3: in: A s is the amount of catalyst A loaded onto the support (e.g., moles of catalyst); B s is the amount of catalyst B loaded onto the support (e.g., moles of catalyst); and B t is the amount of Catalyst B provided as trim (eg, moles of catalyst). η is the trimmed effectiveness value of Catalyst B (already defined). Thus, for the exemplary activated two-component catalyst formulation, the CatComp value can be in the range between 0 and 1. It will be appreciated that for other multi-component catalyst systems (e.g., three-component catalyst systems, four-component catalyst systems, five-component catalyst systems), according to the present disclosure, Equation 3 will be modified to reflect the contribution of each catalyst component of the multi-component catalyst. For example, the disclosed method can be used for a three-catalyst system, where catalyst A and catalyst B are initially loaded onto a support, and catalyst C (initially not loaded onto a support) is provided as a trim.

[0110] for Figure 5 In the illustrated embodiment, process 80 continues with processor 162 optimizing (block 190) the catalyst trim effectiveness value (η) for the multi-component catalyst composition, wherein the optimization is determined with reference to the objective of minimizing the sum of squared errors (SSE) of the model residuals. For example, in certain embodiments, the sum of squared errors (SSE) of the model residuals may be calculated based on the predicted and measured properties of all PE resins produced using the multi-component catalyst according to Equation 4: Formula 4: SSE=∑(MIR P -MIR m ) 2 +∑(MI P -MI m ) 2 +∑(D P -D m )2 ,in: MIR p is the melt index ratio predicted by the melt index ratio process model of PE resin; MIR m is the melt index ratio measured for PE resin; MI p It is the melt index predicted by the melt index process model of PE resin; MI m is the melt index measured for PE resin; D p is the density predicted by the density process model of PE resin; D m is the measured density of PE resin. Thus, each sigma symbol (Σ) iterates through each PE resin product contained in the multi-component catalyst GPPE polymerization process data set 172, summing the squares of the differences between the predicted and measured property values. Because the properties of the PE resin predicted by the process model depend on the catalyst trim effectiveness value (η), as described above, during the optimization of block 190, the catalyst trim effectiveness value (η) of the multi-component catalyst can be varied (e.g., increased or decreased) until the SSE value reaches a minimum (e.g., a local minimum) where the predicted and measured property values ​​of the PE resin are closest for the current version or iteration of the process model. This process of varying the trim effectiveness value (η) of the multi-component catalyst to obtain a minimized SSE value (i.e., minimizing the SSE value) is what is meant by "optimizing" the catalyst trim effectiveness value.

[0111] for Figure 5In the illustrated embodiment, process 80 continues with the processor 162 determining (decision block 192) whether the change (e.g., decrease) in the minimized SSE value (ΔSSE) between the current iteration of block 190 and the previous iteration of block 190 is less than a predetermined threshold value (e.g., 5%, 2%, 1%). In some embodiments, prior to the first iteration of block 190, the previously minimized SSE value may be initialized to a particular value (e.g., zero) such that any value of SSE determined in the first iteration of block 190 results in a ΔSSE at decision block 192 greater than the predetermined threshold value. When this occurs, the processor 162 returns to block 188 and continues to retrain the process model using the current catalyst trim effectiveness value (η) for each catalyst formulation, and then repeats the actions of block 190 to again optimize the catalyst trim effectiveness value (η) to minimize the SSE value calculated using the retrained process model. In a second iteration of decision block 192, processor 162 determines whether the change between the minimized SSE value determined in the first iteration of block 190 and the minimized SSE value determined in the second iteration of block 190 (ΔSSE) is less than a predetermined threshold. Therefore, when ΔSSE is greater than the predetermined threshold, processor 162 continues to iterate blocks 188 and 190.

[0112] for Figure 5 In the illustrated embodiment, once the processor 162 determines in decision block 192 that the ΔSSE is less than a predetermined threshold, the processor 162 responds by outputting or storing (block 194) the current catalyst trim effectiveness value (η) for the multi-component catalyst composition 182, which may be referred to as the optimized catalyst trim effectiveness value. Additionally, the processor 162 outputs or stores a trained process model 184 (e.g., a density process model, an MI process model, an MIR process model) associated with the multi-component catalyst composition. In certain embodiments, the optimized catalyst trim effectiveness value (η) and the trained process model may be appropriately stored in the memory 164 and / or storage device 166 for later use. It will be appreciated that as additional PE resins are produced using the multi-component catalyst composition and characterized over time, the GPPE polymerization process data set 172 may be supplemented to include such data, and the process 80 may be repeated to further adjust or refine the catalyst trim effectiveness value (η) 182 and the trained process model 184 associated with the multi-component catalyst composition.

[0113] To better illustrate how the SSE value changes with catalyst trim effectiveness value (η), Figure 6 is to show that the minimized SSE value is relative to that obtained by the η optimization process ( Figure 5190 ) with each iteration producing a revised catalyst trim effectiveness value (e.g., η1, η2, η3, η4, η5, η6). For this example, the minimized SSE value begins at a relative maximum in the first iteration of block 190 (e.g., η1), and the minimized SSE value decreases with each subsequent iteration (e.g., η2, η3, η4, η5, η6). However, with each iteration of block 190, the decrease in the minimized SSE value also decreases, such that ΔSSE is maximum between the first two iterations of block 190 (e.g., between η1 and η2) and decreases with each subsequent iteration of block 190. At the sixth iteration, the ΔSSE resulting from the last two catalyst trim effectiveness values ​​(e.g., η5 and η6) is lower than ΔSSE relative to η1. Figure 5 The predetermined threshold for discussion, and Figure 5 The process 80 ends by selecting the catalyst trim effectiveness value (eg, η 6 ) determined by the last iteration of block 190 as the catalyst trim effectiveness value 182 for the multi-component catalyst composition.

[0114] Figure 7 is a flow chart showing an embodiment of process 210 in which processor 162 may use Figure 5 The process 210 can be stored as computer-executable instructions (e.g., software) in at least one memory 164 and can be used by the user to predict the properties of the PE resin produced using the multi-component catalyst composition using the catalyst trim effectiveness value (η) 182 provided by the process 80 and the trained process model 184. Figure 1 At least one processor 162 of the illustrated soft sensor system 160 executes.

[0115] for Figure 7 In the embodiment shown in FIG, the processor 162 receives a catalyst trim effectiveness value (η) 182 for the multi-component catalyst composition and a trained process model 184 associated with the multi-component catalyst composition, which is determined as described above. The processor 162 also receives input defining various operating parameters 212 of the GPPE polymerization process for producing PE resin. In certain embodiments, the soft sensor system 160 can communicate directly with one or more components of the gas phase reactor system 100 to directly and automatically determine the current configuration or operating parameters of these components.

[0116] for Figure 7, the processor 162 then predicts (block 214) one or more properties of the PE resin using the catalyst trim effectiveness value (η) 182 of the multi-component catalyst composition, one or more trained process models 184, and the operating parameters 212 of the GPPE polymerization process to be used to produce the PE resin. For the embodiment shown, the processor 162 outputs a predicted density 216 of the PE resin, a predicted melt index (MI) 218 ​​of the PE resin, and a predicted melt index ratio (MIR) 220 of the PE resin. Thus, the embodiments disclosed herein enable prediction of the properties of a PE resin produced using a multi-component catalyst composition for a given set of operating parameters. It can be appreciated that Figure 7 The process 210 is provided as an example only, and in other embodiments, the processor 162 may use the catalyst trim effectiveness value (η) 182 and the trained process model 184 in different ways to improve the polymerization process.

[0117] For example, Figure 8 1 is a flow chart showing an embodiment of a process 230 in which the processor 162 may use the catalyst trim effectiveness value (η) 182, the trained process model 184, and the desired properties of the PE resin to be produced by the multi-component catalyst composition to determine predicted operating parameters 232 for the GPPE polymerization process. The process 230 may be stored as computer-executable instructions (e.g., software) in the at least one memory 164 and may be executed by Figure 1 At least one processor 162 of the illustrated soft sensor system 160 executes.

[0118] for Figure 8In the embodiment shown in FIG, the processor 162 receives a catalyst trim effectiveness value (η) 182 for the multi-component catalyst composition and a trained process model 184 associated with the multi-component catalyst composition, determined as discussed above, and inputs defining desired properties of the PE resin (e.g., user input). For the embodiment shown, the inputs include a desired density 234 for the PE resin, a desired melt index (MI) 236 for the PE resin, and a desired melt index ratio (MIR) 238 for the PE resin. The processor 162 then uses the catalyst trim effectiveness value (η) 182 for the multi-component catalyst composition, the trained process model 184, and the desired properties 234, 236, and 238 of the PE resin (e.g., density, MI, MIR) to determine (block 240) one or more predicted operating parameters 232 for the GPPE polymerization process, wherein the predicted operating parameters 232 are expected to produce a PE resin having the desired properties. In certain embodiments, the soft sensor system 160 can communicate directly with one or more components of the gas phase reactor system 100 to modify or adjust the current configuration or operating parameters of these components based on the predicted operating parameters 232. Thus, the embodiments disclosed herein enable prediction of operating parameters for GPPE polymerization for use with a multi-component catalyst composition to produce a PE resin having one or more desired properties. Additional Implementation Options

[0119] Thus, the present disclosure may provide soft sensor systems, methods, and computer-readable media for determining catalyst trim effectiveness values ​​for multi-component catalyst compositions. The methods and systems may include any of the various features disclosed herein, including one or more of the following statements.

[0120] Statement 1. A soft sensor system comprising: at least one memory configured to store a polymerization process data set of a multi-component catalyst composition, wherein the polymerization process data set includes one or more properties of a polyethylene (PE) resin prepared using the multi-component catalyst composition and different operating parameters of a gas phase reactor system; and at least one processor configured to execute stored instructions to perform actions, the actions comprising: (A) setting a catalyst trim effectiveness value of the multi-component catalyst composition to an initial value; (B) training a corresponding process model for each of the one or more properties of the PE resin in the polymerization process data set using the catalyst trim effectiveness value of the multi-component catalyst composition to generate a set of one or more trained process models; (C) optimizing the catalyst trim effectiveness value of the multi-component catalyst composition based on the set of trained process models to minimize a sum of squared errors (SSE) value of model residuals; (D) repeating steps (B) and (C) until the decrease in the minimized SSE value is less than a predetermined threshold; and (E) outputting or storing the optimized catalyst trim effectiveness value of the multi-component catalyst composition and the set of one or more trained process models.

[0121] Statement 2. The soft sensor system of statement 1, wherein, in order to set the catalyst trimming effectiveness value of the multi-component catalyst composition to the initial value, the at least one processor is configured to execute stored instructions to perform actions including: calculating the initial value based on basic principles of catalyst activation, wherein the basic principles of catalyst activation include one or more of the following: the amount of activator in the multi-component catalyst composition, the ambient temperature, the contact time and the trimming solvent.

[0122] Statement 3. The soft sensor system of statement 1, wherein, to set the catalyst trim effectiveness value of the multi-component catalyst composition to the initial value, the at least one processor is configured to execute stored instructions to perform actions comprising: setting the initial value to a predetermined initial value.

[0123] Statement 4. The soft sensor system of any of Statements 1-3, wherein the one or more properties of the PE resins of the polymerization process data set include one or more of the following: density, melt index (MI) and melt index ratio (MIR) of each of the PE resins, and wherein the group of trained process models includes a density process model, an MI process model and a MIR process model.

[0124] Statement 5. The soft sensor system of any one of Statements 1-4, wherein each respective trained process model in the group of one or more trained process models is configured to predict one of the respective properties of the PE resin based on: the activated form of the multi-component catalyst composition, the temperature of the fluidized bed reactor of the gas phase reactor system, the ratio of hydrogen to α-olefin monomer in the fluidized bed reactor of the gas phase reactor system, the ratio of α-olefin comonomer to α-olefin monomer in the fluidized bed reactor of the gas phase reactor system, the amount of induced condensing agent (ICA) in the fluidized bed reactor of the gas phase reactor system, the partial pressure of α-olefin monomer in the fluidized bed reactor of the gas phase reactor system, and the residence time of the PE resin in the fluidized bed reactor of the gas phase reactor system.

[0125] Statement 6. The soft sensor system of Statement 5, wherein the multi-component catalyst composition is a two-component catalyst having a first catalyst compound and a second catalyst compound loaded onto a carrier, wherein the second catalyst compound is also a trimming catalyst, and wherein the activated form of the multi-component catalyst composition is calculated as the amount of the first catalyst compound loaded onto the carrier divided by the sum of the amount of the first catalyst compound loaded onto the carrier, the amount of the second catalyst compound loaded onto the carrier, and the amount of the second catalyst compound provided as a trimming catalyst multiplied by a catalyst trimming effectiveness value.

[0126] Statement 7. The soft sensor system of any one of Statements 1-6, wherein the at least one processor is configured to execute stored instructions to perform actions comprising: (F) receiving a set of operating parameters for the gas phase reactor system; and (G) using the received set of operating parameters, the catalyst trim effectiveness value, and at least one trained process model from the set of trained process models to determine at least one predicted property of a potential PE resin to be produced using the multicomponent catalyst composition and the gas phase reactor system according to the received set of operating parameters; (H) controlling the gas phase reactor system to produce a PE resin product based at least in part on the at least one predicted property of the potential PE resin; wherein controlling the gas phase reactor system comprises adjusting one or more operating parameters of the gas phase reactor system, or maintaining the one or more operating parameters of the gas phase reactor system constant; and further wherein the PE resin product is produced based on said (H) control.

[0127] Statement 8. The soft sensor system of any one of Statements 1-6, wherein the at least one processor is configured to execute stored instructions to perform actions comprising: (F) receiving a set of desired properties for a potential PE resin; and (G) using the received set of desired properties, the catalyst trim effectiveness value, and the set of trained process models to determine one or more predicted operating parameters of the gas phase reactor system to be used for producing a potential PE resin having the received set of desired properties using the multi-component catalyst composition; further wherein the potential PE resin is produced using the one or more predicted operating parameters of the gas phase reactor system.

[0128] Statement 9. The soft sensor system of any one of Statements 1-8, wherein the multicomponent catalyst composition comprises a silica-containing support, an aluminoxane-containing activator, and two metallocene catalysts.

[0129] Statement 10. The soft sensor system of Statement 9, wherein said two metallocene catalysts comprise a bridged biscyclopentadienyl hafnocene and an unbridged indenyl-cyclopentadienyl zirconocene.

[0130] Statement 11. A method comprising: (A) obtaining a polymerization process data set for a multi-component catalyst composition, wherein the polymerization process data set includes one or more properties of a polyethylene (PE) resin polymerized from ethylene monomer and an α-olefin comonomer using the multi-component catalyst composition and different operating parameters of a gas phase reactor system; (B) setting a catalyst trim effectiveness value for the multi-component catalyst composition to an initial value; (C) training a corresponding process model for each of the one or more properties of the PE resin in the polymerization process data set using the catalyst trim effectiveness value for the multi-component catalyst composition to produce a set of one or more trained process models; (D) optimizing the catalyst trim effectiveness value for the multi-component catalyst composition based on the one or more trained process models of the set to minimize a sum of squared errors (SSE) value of model residuals; (E) repeating steps (C) and (D) until the decrease in the minimized SSE value is less than a predetermined threshold; and (F) outputting or storing the optimized catalyst trim effectiveness value for the multi-component catalyst composition and the one or more trained process models of the set.

[0131] Statement 12. The method of statement 11, wherein the one or more properties of the PE resins of the polymerization process data set include one or more of the following: density, melt index (MI) and melt index ratio (MIR) of each of the PE resins, and wherein the group of trained process models includes a density process model, an MI process model and a MIR process model.

[0132] Statement 13. The method of any of Statements 11 and 12, wherein each respective trained process model in the set of one or more trained process models is configured to predict one of the respective properties of the PE resin based on: the activated form of the multicomponent catalyst composition, the temperature of the fluidized bed reactor of the gas phase reactor system, the ratio of hydrogen to α-olefin monomer in the fluidized bed reactor of the gas phase reactor system, the ratio of α-olefin comonomer to α-olefin monomer in the fluidized bed reactor of the gas phase reactor system, the amount of induced condensing agent (ICA) in the fluidized bed reactor of the gas phase reactor system, the partial pressure of α-olefin monomer in the fluidized bed reactor of the gas phase reactor system, and the residence time of the PE resin in the fluidized bed reactor of the gas phase reactor system.

[0133] Statement 14. The method of any of Statements 11-13, further comprising: (F) receiving a set of operating parameters for a gas phase reactor system; (G) using the received set of operating parameters, the catalyst trim effectiveness value, and at least one trained process model from the set of trained process models to determine at least one predicted property of a potential PE resin to be produced using the multicomponent catalyst composition and the gas phase reactor system according to the received set of operating parameters; (H) controlling the gas phase reactor system to produce a PE resin product based at least in part on the at least one predicted property of the potential PE resin; wherein controlling the gas phase reactor system comprises adjusting one or more operating parameters of the gas phase reactor system, or maintaining the one or more operating parameters of the gas phase reactor system constant; and (G) producing a PE resin product.

[0134] Statement 15. The method of any of Statements 11-13, further comprising: (F) receiving a set of desired properties for a potential PE resin; (G) using the received set of desired properties, the catalyst trim effectiveness value, and the set of trained process models to determine one or more predicted operating parameters of the gas phase reactor system to be used for producing a potential PE resin having the received set of desired properties using the multi-component catalyst composition; and (H) producing the potential PE resin using the one or more predicted operating parameters of the gas phase reactor system.

[0135] Statement 16. The method of any one of Statements 11-14, wherein the α-olefin comonomer comprises one or more C2-C 20 α-olefin comonomer.

[0136] Statement 17. The method of Statement 16, wherein the α-olefin comonomer comprises one or more C3-C 12 α-olefin comonomer.

[0137] Statement 18. The method of Statement 17, wherein the α-olefin comonomer comprises 1-butene, 1-hexene, 1-octene, or a combination thereof.

[0138] Statement 19. A non-transitory computer-readable medium storing instructions executable by a processor of a soft sensor system, the instructions comprising instructions for: (A) receiving a polymerization process data set for a multi-component catalyst composition, wherein the polymerization process data set comprises one or more properties of a polyethylene (PE) resin polymerized from ethylene monomer and an α-olefin comonomer using the multi-component catalyst composition and different operating parameters of a gas phase reactor system; (B) setting a catalyst trim effectiveness value for the multi-component catalyst composition to an initial value; (C) training a corresponding process model for each of the one or more properties of the PE resin in the polymerization process data set using the catalyst trim effectiveness value for the multi-component catalyst composition to generate a set of one or more trained process models; (D) optimizing the catalyst trim effectiveness value for the multi-component catalyst composition based on the set of trained process models to minimize a sum of squared errors (SSE) value of model residuals; (E) repeating steps (C) and (D) until the decrease in the minimized SSE value is less than a predetermined threshold; and (F) outputting or storing the optimized catalyst trim effectiveness value for the multi-component catalyst composition and the set of one or more trained process models.

[0139] Statement 20. The medium of statement 19, wherein the soft sensor system is communicatively coupled to one or more components of the gas phase reactor system, and wherein the instructions further include instructions for: (F) receiving a set of operating parameters of the gas phase reactor system from one or more components of the gas phase reactor system; (G) using the received set of operating parameters, the catalyst trim effectiveness value, and at least one trained process model from the set of trained process models to determine at least one predicted property of a potential PE resin to be produced using the multicomponent catalyst composition and the gas phase reactor system based on the received set of operating parameters; and (H) controlling the gas phase reactor system to produce a PE resin product based at least in part on the at least one predicted property of the potential PE resin; wherein controlling the gas phase reactor system includes adjusting one or more operating parameters of the gas phase reactor system, or maintaining the one or more operating parameters of the gas phase reactor system constant; and further wherein the PE resin product is produced based on said (H) control.

[0140] Statement 21. The medium of statement 19, wherein the soft sensor system is communicatively coupled to one or more components of the gas phase reactor system, and wherein the instructions further include instructions for: (F) receiving a set of desired properties for a potential PE resin; (G) using the received set of desired properties, the catalyst trim effectiveness value, and the set of trained process models to determine one or more predicted operating parameters of the gas phase reactor system to be used to produce a potential PE resin having the received set of desired properties using the multi-component catalyst composition; and (H) adjusting the configuration of at least one component of the gas phase reactor system to produce a potential PE resin based on the one or more predicted operating parameters of the gas phase reactor system; further wherein the potential PE resin is produced using the one or more predicted operating parameters of the gas phase reactor system.

[0141] Although the present disclosure has been described in terms of a number of embodiments and examples, it will be appreciated by those skilled in the art, after reading this disclosure, that other embodiments may be designed without departing from the scope and spirit of the present disclosure as described herein. Although various embodiments have been discussed, this disclosure encompasses all combinations of all those embodiments.

[0142] Although compositions, methods, and processes are described herein as "comprising," "containing," "having," or "including" various components or steps, the compositions and methods may also "consist essentially of" or "consist of" the various components and steps. Unless otherwise specified, the phrase "consisting essentially of" does not exclude the presence of other steps, elements, or materials (whether or not specifically mentioned in the specification) so long as these steps, elements, or materials do not affect the basic and novel characteristics of the disclosure, and further, they do not exclude impurities and variations normally associated with the elements and materials used.

[0143] All numerical values ​​in the detailed description are modified by the value indicated by "about," and take into account experimental error and variations that would be expected by a person of ordinary skill in the art.

[0144] In view of the foregoing description, many changes, modifications and variations will be apparent to those skilled in the art without departing from the spirit or scope of the disclosure, and when numerical lower limits and numerical upper limits are listed herein, ranges from any lower limit to any upper limit are contemplated.

Claims

1. Soft sensor system, including: at least one memory configured to store a polymerization process data set for a multi-component catalyst composition, wherein the polymerization process data set includes one or more properties of a polyethylene (PE) resin produced using the multi-component catalyst composition and various operating parameters of a gas phase reactor system; and At least one processor configured to execute stored instructions to perform actions comprising: (A) setting the catalyst trim effectiveness value of the multi-component catalyst composition to an initial value; (B) training a corresponding process model for each of the one or more properties of the PE resin of the polymerization process dataset using the catalyst trim effectiveness value for the multicomponent catalyst composition to produce a set of one or more trained process models; (C) optimizing a catalyst trim effectiveness value of the multicomponent catalyst composition based on the set of trained process models to minimize a sum of squared errors (SSE) value of model residuals; (D) repeating steps (B) and (C) until the decrease in the minimized SSE value is less than a predetermined threshold; and (E) outputting or storing the optimized catalyst trim effectiveness value for the multi-component catalyst composition and the set of one or more trained process models.

2. The soft sensor system of claim 1, wherein: To set the catalyst trim effectiveness value of the multi-component catalyst composition to the initial value, the at least one processor is configured to execute stored instructions to perform actions including: The initial value is calculated based on catalyst activation fundamentals including one or more of the following: amount of activator in the multi-component catalyst composition, ambient temperature, contact time, and trim solvent.

3. The soft sensor system of claim 1, wherein: To set the catalyst trim effectiveness value of the multi-component catalyst composition to the initial value, the at least one processor is configured to execute stored instructions to perform actions including: The initial value is set to a predetermined initial value.

4. The soft sensor system of claim 1 or any one of claims 2-3, wherein the properties of the PE resins of the polymerization process dataset include one or more of the following: density, melt index (MI) and melt index ratio (MIR) of each of the PE resins, and wherein the trained process models of the group include a density process model, an MI process model and a MIR process model.

5. The soft sensor system of claim 1 or any one of claims 2-4, wherein each corresponding trained process model in the group of one or more trained process models is configured to predict one of the corresponding properties of the PE resin based on: (i) the activated form of the multi-component catalyst composition, (ii) the temperature of the fluidized bed reactor of the gas phase reactor system, (iii) the ratio of hydrogen to α-olefin monomer in the fluidized bed reactor of the gas phase reactor system, (iv) the ratio of α-olefin comonomer to α-olefin monomer in the fluidized bed reactor of the gas phase reactor system, (v) the amount of induced condensing agent (ICA) in the fluidized bed reactor of the gas phase reactor system, (vi) the partial pressure of the α-olefin monomer in the fluidized bed reactor of the gas phase reactor system and (vii) the residence time of the PE resin in the fluidized bed reactor of the gas phase reactor system.

6. The soft sensor system of claim 5, wherein the multi-component catalyst composition is a two-component catalyst having a first catalyst compound and a second catalyst compound loaded onto a support, wherein the second catalyst compound is also a trimming catalyst, and wherein the activated form of the multi-component catalyst composition is calculated as the amount of the first catalyst compound loaded onto the support divided by the sum of (i) the amount of the first catalyst compound loaded onto the support, (ii) the amount of the second catalyst compound loaded onto the support, and (iii) the amount of the second catalyst compound provided as a trimming catalyst multiplied by a catalyst trimming effectiveness value.

7. The soft sensor system of claim 1 or any one of claims 2-6, wherein the at least one processor is configured to execute stored instructions to perform actions comprising: (F) receiving a set of operating parameters for the gas phase reactor system; and (G) determining at least one predicted property of a potential PE resin to be produced using the multicomponent catalyst composition and gas phase reactor system according to the received set of operating parameters using the received set of operating parameters, the catalyst trim effectiveness value, and at least one trained process model from the set of trained process models; (H) controlling the gas phase reactor system to produce a PE resin product based at least in part on at least one predicted property of the latent PE resin; wherein controlling the gas phase reactor system comprises adjusting one or more operating parameters of the gas phase reactor system, or maintaining the one or more operating parameters of the gas phase reactor system constant; and Further wherein a PE resin product is produced based on said (H) control.

8. The soft sensor system of claim 1 or any one of claims 2-6, wherein the at least one processor is configured to execute stored instructions to perform actions comprising: (F) receiving a set of desired properties of a potential PE resin; and (G) using the received set of desired properties, the catalyst trim effectiveness value, and the set of trained process models to determine one or more predicted operating parameters of the gas phase reactor system to be used for producing a potential PE resin having the received set of desired properties using the multicomponent catalyst composition; Further wherein the latent PE resin is produced using one or more predicted operating parameters of the gas phase reactor system.

9. The soft sensor system of claim 1 or any one of claims 2 to 8, wherein the multi-component catalyst composition comprises a silica-containing support, an aluminoxane-containing activator, and two metallocene catalysts.

10. The soft sensor system of claim 9, wherein the two metallocene catalysts comprise a bridged biscyclopentadienyl hafnocene and an unbridged indenyl-cyclopentadienyl zirconocene.

11. Methods, comprising: (A) obtaining a polymerization process data set for a multicomponent catalyst composition, wherein the polymerization process data set comprises one or more properties of a polyethylene (PE) resin polymerized from ethylene monomer and an α-olefin comonomer using the multicomponent catalyst composition and different operating parameters of a gas phase reactor system; (B) setting the catalyst trim effectiveness value of the multi-component catalyst composition to an initial value; (C) training a corresponding process model for each of the one or more properties of the PE resin of the polymerization process dataset using the catalyst trim effectiveness value for the multicomponent catalyst composition to produce a set of one or more trained process models; (D) optimizing a catalyst trim effectiveness value of the multicomponent catalyst composition based on the set of one or more trained process models to minimize a sum of squared errors (SSE) value of model residuals; (E) repeating steps (C) and (D) until the decrease in the minimized SSE value is less than a predetermined threshold; and (F) outputting or storing the optimized catalyst trim effectiveness value for the multi-component catalyst composition and the set of one or more trained process models.

12. The method of claim 11, wherein the one or more properties of the PE resins of the polymerization process data set include one or more of the following: density, melt index (MI) and melt index ratio (MIR) of each of the PE resins, and wherein the trained process models of the group include a density process model, an MI process model and a MIR process model.

13. The method of claim 11 or claim 12, wherein each respective trained process model in the set of one or more trained process models is configured to predict one respective property of the PE resin based on: (i) the activated form of the multicomponent catalyst composition, (ii) the temperature of the fluidized bed reactor of the gas phase reactor system, (iii) the ratio of hydrogen to α-olefin monomer in the fluidized bed reactor of the gas phase reactor system, (iv) the ratio of α-olefin comonomer to α-olefin monomer in the fluidized bed reactor of the gas phase reactor system, (v) the amount of induced condensing agent (ICA) in the fluidized bed reactor of the gas phase reactor system, (vi) the partial pressure of the α-olefin monomer in the fluidized bed reactor of the gas phase reactor system, and (vii) the residence time of the PE resin in the fluidized bed reactor of the gas phase reactor system.

14. The method of claim 11 or any one of claims 12-13, further comprising: (F) receiving a set of operating parameters for the gas phase reactor system; (G) determining at least one predicted property of a potential PE resin to be produced using the multicomponent catalyst composition and gas phase reactor system according to the received set of operating parameters using the received set of operating parameters, the catalyst trim effectiveness value, and at least one trained process model from the set of trained process models; (H) controlling the gas phase reactor system to produce a PE resin product based at least in part on at least one predicted property of the latent PE resin; wherein controlling the gas phase reactor system comprises adjusting one or more operating parameters of the gas phase reactor system, or maintaining the one or more operating parameters of the gas phase reactor system constant; and (G) Producing PE resin products.

15. The method of claim 11 or any one of claims 12-13, further comprising: (F) receiving a set of desired properties of a potential PE resin; (G) using the received set of desired properties, the catalyst trim effectiveness value, and the set of trained process models to determine one or more predicted operating parameters of the gas phase reactor system to be used for producing a potential PE resin having the received set of desired properties using the multicomponent catalyst composition; and (H) producing a latent PE resin using one or more predicted operating parameters of the gas phase reactor system.

16. The process of claim 11 or any one of claims 12-15, wherein the α-olefin comonomer comprises one or more C3 to C 20 α-olefin comonomer.

17. The method of claim 16, wherein the α-olefin comonomer comprises 1-butene, 1-hexene, 1-octene, or a combination thereof.

18. A non-transitory computer-readable medium storing instructions executable by a processor of a soft sensor system, the instructions comprising instructions for: (A) receiving a polymerization process data set for a multicomponent catalyst composition, wherein the polymerization process data set comprises one or more properties of a polyethylene (PE) resin polymerized from ethylene monomer and an α-olefin comonomer using the multicomponent catalyst composition and different operating parameters of a gas phase reactor system; (B) setting the catalyst trim effectiveness value of the multi-component catalyst composition to an initial value; (C) training a corresponding process model for each of the one or more properties of the PE resin of the polymerization process dataset using the catalyst trim effectiveness value for the multicomponent catalyst composition to produce a set of one or more trained process models; (D) optimizing a catalyst trim effectiveness value of the multicomponent catalyst composition based on the set of trained process models to minimize a sum of squared errors (SSE) value of model residuals; (E) repeating steps (C) and (D) until the decrease in the minimized SSE value is less than a predetermined threshold; and (F) outputting or storing the optimized catalyst trim effectiveness value for the multi-component catalyst composition and the set of one or more trained process models.

19. The medium of claim 18, wherein the soft sensor system is communicatively coupled to one or more components of the gas phase reactor system, and wherein the instructions further comprise instructions for: (F) receiving a set of operating parameters of the gas phase reactor system from one or more components of the gas phase reactor system; (G) determining at least one predicted property of a potential PE resin to be produced using the multicomponent catalyst composition and gas phase reactor system according to the received set of operating parameters using the received set of operating parameters, the catalyst trim effectiveness value, and at least one trained process model from the set of trained process models; and (H) controlling the gas phase reactor system to produce a PE resin product based at least in part on at least one predicted property of the latent PE resin; wherein controlling the gas phase reactor system comprises adjusting one or more operating parameters of the gas phase reactor system, or maintaining the one or more operating parameters of the gas phase reactor system constant; and Further wherein a PE resin product is produced based on said (H) control.

20. The medium of claim 18, wherein the soft sensor system is communicatively coupled to one or more components of the gas phase reactor system, and wherein the instructions further comprise instructions for: (F) receiving a set of desired properties of a potential PE resin; (G) using the received set of desired properties, the catalyst trim effectiveness value, and the set of trained process models to determine one or more predicted operating parameters of the gas phase reactor system to be used for producing a potential PE resin having the received set of desired properties using the multicomponent catalyst composition; and (H) adjusting the configuration of at least one component of the gas phase reactor system to produce a latent PE resin based on one or more predicted operating parameters of the gas phase reactor system; Further wherein the latent PE resin is produced using one or more predicted operating parameters of the gas phase reactor system.

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