A digital workflow for the optimization of solvent-mediated recycling of polymer waste streams

Abstract

The following generally relates to recycling polymer waste materials, and more particularly to selecting a solvent, or solvent mixture, to be used to separate polymers from a polymer waste material as pail of a recycling process. For example, if a polymer waste material including multiple individual polymers is not first separated into individual polymers, the recycling process may not produce a useful product. In some embodiments, one or more processors determine a solvent composition and temperature to use the solvent composition at to separate individual polymers out of the polymer waste material.

Description

32471 / 240556 / PCA DIGITAL WORKFLOW FOR THE OPTIMIZATION OF SOLVENT-MEDIATED RECYCLING OF POLYMER WASTE STREAMSCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 682,477, entitled “Digital Workflow for the Optimization of Solvent-mediated Recycling of Polymer Waste Streams” (filed August 13, 2024), the entirety of which is incorporated by reference herein.FIELD

[0002] The present disclosure generally relates to recycling polymer waste materials, and more particularly to selecting a solvent or solvent mixture to be used to separate polymers from a polymer waste material as pail of a recycling process.BACKGROUND

[0003] It is often desirable to recycle polymers. However, many materials do not comprise only a single polymer. For example, often, it is desirable to recycle a material that includes multiple layers of polymers or a waste stream consisting of multiple polymers. However, if the recycling process is attempted without first separating the individual polymers, the material produced from the recycling process may not have useful properties (e.g., the recycling process will be unsuccessful).

[0004] The systems and methods disclosed herein provide solutions to these problems and may provide solutions to the ineffectiveness, insecurities, difficulties, inefficiencies, encumbrances, and / or other drawbacks of conventional techniques.SUMMARY

[0005] In one aspect, a computer-implemented method for determining a solvent composition to be used in a recycling process may be provided. In one example, the method may include: receiving, via one or more processors, with a calculation engine, information of a polymer waste material, the polymer waste material including a first polymer and a second polymer; receiving, via the one or more processors, with an optimizer: (i) information of one or more solvents, and (ii) the information of the polymer waste material; generating, via the one or more processors, with the optimizer, a first request for at least one first datapoint including solubility information,32471 / 240556 / PC the first request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material; sending, via the one or more processors, from the optimizer to the calculation engine, the first request; receiving, via the one or more processors, with the optimizer, the at least one first datapoint; until an objective function is satisfied, at each iteration of a plurality of iterations: generating, via the one or more processors, with the optimizer, a new request for at least one new datapoint including solubility information, the new request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material, and (iii) a previously generated at least one datapoint including solubility information; sending, via the one or more processors, from the optimizer to the calculation engine, the new request; and receiving, via the one or more processors, with the optimizer, the at least one new datapoint; and determining, via the one or more processors, with the optimizer, based on at least one datapoint received from a final iteration of the plurality of iterations, the solvent composition. The method may include additional, fewer, or alternate actions, including those discussed elsewhere herein.

[0006] In another aspect, a computer device configured for determining a solvent composition to be used in a recycling process may be provided. In one example, the computer device may include one or more processors configured to: receive, with a calculation engine, information of a polymer waste material, the polymer waste material including a first polymer and a second polymer; receive, with an optimizer: (i) information of one or more solvents, and (ii) the information of the polymer waste material; generate, with the optimizer, a first request for at least one first datapoint including solubility information, the first request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material; send, from the optimizer to the calculation engine, the first request; receive, with the optimizer, the at least one first datapoint; until an objective function is satisfied, at each iteration of a plurality of iterations: generate, with the optimizer, a new request for at least one new datapoint including solubility information, the new request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material, and (iii) a previously generated at least one datapoint including solubility information; send, from the optimizer to the calculation engine, the new request; and receive, with the optimizer, the at least one new datapoint; and determine, with the optimizer, based on at least one datapoint received from a32471 / 240556 / PC final iteration of the plurality of iterations, the solvent composition. The computer device may include additional, less, or alternate functionality, including that discussed elsewhere herein.

[0007] In yet another aspect, a computer system configured for determining a solvent composition to be used in a recycling process may be provided. In one example, the computer system may include: one or more processors; and / or one or more non-transitory memories coupled to the one or more processors. The one or more non-transitory memories may include computer-executable instructions stored therein that, when executed by the one or more processors, may cause the one or more processors to: receive, with a calculation engine, information of a polymer waste material, the polymer waste material including a first polymer and a second polymer; receive, with an optimizer: (i) information of one or more solvents, and(ii) the information of the polymer waste material; generate, with the optimizer, a first request for at least one first datapoint including solubility information, the first request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material; send, from the optimizer to the calculation engine, the first request; receive, with the optimizer, the at least one first datapoint; until an objective function is satisfied, at each iteration of a plurality of iterations: generate, with the optimizer, a new request for at least one new datapoint including solubility information, the new request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material, and(iii) a previously generated at least one datapoint including solubility information; send, from the optimizer to the calculation engine, the new request; and receive, with the optimizer, the at least one new datapoint; and determine, with the optimizer, based on at least one datapoint received from a final iteration of the plurality of iterations, the solvent composition. The computer system may include additional, less, or alternate functionality, including that discussed elsewhere herein.BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Advantages will become more apparent to those skilled in the art from the following description of the preferred embodiments which have been shown and described by way of illustration. As will be realized, the present embodiments may be capable of other and different embodiments, and their details are capable of modification in various respects. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive.32471 / 240556 / PC

[0009] The figures described below depict various aspects of the applications, methods, and systems disclosed herein. It should be understood that each figure depicts an embodiment of a particular aspect of the disclosed applications, systems and methods, and that each of the figures is intended to accord with a possible embodiment thereof. Furthermore, wherever possible, the following description refers to the reference numerals included in the following figures, in which features depicted in multiple figures are designated with consistent reference numerals.

[0010] Figure 1 depicts an example computer system for determining a solvent composition to be used in a recycling process.

[0011] Figure 2 illustrates an example microtome section of a multilayer plastic laminate in polarized light.

[0012] Figure 3 illustrates another example microtome section of a multilayer plastic laminate in polarized light.

[0013] Figure 4 illustrates an example process for removing a polymer from a polymer waste material.

[0014] Figure 5 depicts an example flow diagram representing an exemplary computer- implemented method or implementation for determining a solvent composition to be used in a recycling process.

[0015] Figure 6 depicts example polymers, and example functions and applications of the example polymers.

[0016] Figure 7 depicts another example flow diagram representing an exemplary computer- implemented method or implementation for determining a solvent composition to be used in a recycling process.

[0017] Figure 8 depicts example measurements related to selecting a solvent and an anti solvent.

[0018] Figure 9 depicts an example process for separating a polymer waste material including three polymers.

[0019] Figure 10 depicts an example of a multilayer film, and an example of a physical mixture.32471 / 240556 / PCDETAILED DESCRIPTION

[0020] It is often desirable to recycle polymers. However, many materials do not include only a single polymer. For example, it is often desirable to recycle a material that includes multiple layers of polymers. Examples of such materials are illustrated by Figures 2 and 3, which depict example food packaging materials. More particularly, Figure 2 illustrates an example microtome section of a multilayer plastic laminate in polarized light; and Figure 3 illustrates another example microtome section of a multilayer plastic laminate in polarized light.

[0021] However, if the recycling process is attempted without first separating the individual polymers, the material produced from the recycling process may not have useful properties (e.g., the recycling process will be unsuccessful).

[0022] To this end, Figure 4 illustrates an example process for removing a polymer from a polymer waste material. In the illustrated example, the multilayer film 410 (e.g., the polymer waste material, such as a polymer waste stream, etc.) includes three layers: first layer 411 (e.g., polyethylene (PE)), second layer 412 (e.g., ethylene vinyl alcohol (EVOH)), and third layer 413 (e.g., poly(ethylene terephthalate) (PET)). The example process may begin when the PE (e.g., the first layer 411) is dissolved in a solvent. Next, a filter is applied to remove the dissolved PE. Next, the PE is removed (e.g., via precipitation and / or filtration). If desired, the example process may repeat to separate the second layer 412 from the third layer 413 although a different solvent would have to be selected.

[0023] In this example process, to remove individual polymers out of the polymer waste material, a solvent must be selected. However, it may be difficult to determine an optimal solvent and temperature which will effectively and selectively dissolve one polymer over the others. The techniques described herein address this challenge.Example System

[0024] To this end, Figure 1 illustrates an example computer system 100 for determining a solvent composition to be used in a recycling process in which the exemplary computer- implemented methods described herein may be implemented. The high-level architecture includes both hardware and software applications, as well as various data communications channels for communicating data between the various hardware and software components.32471 / 240556 / PC

[0025] Broadly speaking, a computing device 102 may determine a solvent composition and / or an optimal temperature to use the solvent composition at as part of a recycling process. The computing device 102 may include one or more processors 120 such as one or more microprocessors, controllers, and / or any other suitable type of processor. The computing device 102 may further include a memory 122 (e.g., volatile memory, non-volatile memory) accessible by the one or more processors 120 (e.g., via a memory controller). The one or more processors 120 may interact with the memory 122 to obtain and execute, for example, computer-readable instructions stored in the memory 122. Additionally or alternatively, computer-readable instructions may be stored on one or more removable media (e.g., a compact disc, a digital versatile disc, removable flash memory, etc.) that may be coupled to the computing device 102 to provide access to the computer-readable instructions stored thereon. In particular, the computer- readable instructions stored on the memory 122 may include instructions for executing various applications, such as calculation engine 124, and / or optimizer 126.

[0026] In operation, and as will be described in further detail elsewhere herein, the calculation engine 124, and optimizer 126 may work together to determine an optimal solvent or solvent mixture. For example, the optimizer 126 may request one or more datapoints from the calculation engine 124. Once the one or more datapoints are received, the optimizer 126 may attempt to optimize an objective function (e.g., including optimization criterion or set of criteria). Subsequently, the optimizer 126 may request additional one or more datapoints, and the process may repeat until an optimal solvent and / or temperature are determined.

[0027] In some examples, the optimizer 126 includes: (i) non-dominated sorting genetic algorithm, or (ii) Bayesian optimization.

[0028] Once the optimal solvent and / or temperature are determined, they may be sent to recycling facility 150. The recycling facility 150 may include one or more servers including one or more processors such as one or more microprocessors, controllers, and / or any other suitable type of processor. The one or more servers of the recycling facility 150 may further include a memory (e.g., volatile memory, non-volatile memory) accessible by the one or more processors of the one or more servers of the recycling facility 150 (e.g., via a memory controller). These one or more processors may interact with the memory to obtain and execute, for example, computer-readable instructions stored in the memory. Additionally or alternatively, computer-32471 / 240556 / PC readable instructions may be stored on one or more removable media (e.g., a compact disc, a digital versatile disc, removable flash memory, etc.) of the one or more servers of the recycling facility 150 to provide access to the computer-readable instructions stored thereon.

[0029] The example system 100 may also include external database 180 and / or internal database 118, which may store any type of information. Examples of information stored by the external database 180 and / or internal database 118 include: solvent information (e.g., a library of solvents, properties of solvents, etc.), polymer information, etc.

[0030] In addition, further regarding the example system 100, the illustrated exemplary components may be configured to communicate, e.g., via a network 104 (which may be a wired or wireless network, such as the internet), with any other component. Furthermore, although the example system 100 illustrates only one of each of the components, any number of the example components are contemplated (e.g., any number of computing devices, recycling facilities, databases, etc.).Example Method

[0031] Figure 5 illustrates an example flow diagram representing an exemplary computer- implemented method or implementation 500 for determining a solvent composition to be used in a recycling process. The example method 500 may be implemented in a computing environment 100, such as the example system 100.

[0032] The example method 500 may begin at block 502 when the one or more processors 120 (e.g., via the calculation engine 124) receive information of a polymer waste material and / or information of solvents. The polymer waste material 410 may include more than one polymer. Examples of polymers, as well as example functions and applications of the example polymers, are shown in Figure 6. Examples of the polymers include: ethylene vinyl acetate, polycarbonate, polyvinylchloride, polyethylene naphthalate, glycol modified polyethylene terephthalate, ethylene acrylic acid, polyethylene, polypropylene, polyamide, polyethylene terephthalate, polystyrene, ethylene vinyl alcohol, polyvinylidene, etc. In some examples, the polymers include one or more oligomers.

[0033] In some embodiments, the information of the polymer waste material further includes polymer properties of polymers within the polymer waste material 410 (e.g., first polymer 411,32471 / 240556 / PC second polymer 412, third polymer 413, etc.) including: (i) percent crystallinity, (ii) free energy of fusion, (iii) enthalpy of fusion, (iv) entropy of fusion, (v) melting temperature, (vi) heat capacity at constant pressure, (vii) molecular weight, and / or (viii) chemical structure.Optionally, an experimentally determined solubility at a single temperature may be used to back calculate the free energy of fusion.

[0034] In some examples where the information of the material includes the vapor pressure, the vapor pressure (e.g., for each individual solvent, etc.) is in the form of the vapor pressure on a grid of temperatures within a temperature window. If this data is not available in a database, density functional theory (DFT) calculations may be ran on the molecular structures to generate sigma profiles, and COSMO-RS theory may be used to calculate the grid of vapor pressure.

[0035] In some embodiments, the information of one or more solvents includes a library of solvents. Additionally or alternatively, examples of the information of the one or more solvents include, for respective solvents: (i) a boiling temperature, (ii) parameters describing a dependence of saturated vapor pressure on temperature (e.g. Antoine parameters), (iii) a cost, (iv) a heat of vaporization, (v) a toxicity score, (vi) vapor pressure, and / or (vii) a melting point.

[0036] In some examples where the information of the one or more solvents includes the vapor pressure, the vapor pressure (e.g., for each individual solvent, etc.) is in the form of the vapor pressure on a grid of temperatures within a temperature window. If this data is not available in a database, DFT calculations may be run on the molecular structures to generate sigma profiles, and COSMO-RS theory may be used to calculate the grid of vapor pressure.

[0037] At block 504, the optimizer 126 may receive (i) the information of one or more solvents, (ii) the information of the polymer waste material, and / or (iii) one or more solvent constraints.

[0038] Examples of the solvent constraints include: a number of individual solvents to be included in the solvent composition; a solvent toxicity score constraint on the solvent composition (e.g., a toxicity score less than X); a cost constraint on the solvent composition (e.g., a cost less than X); a solvent heat of vaporization constraint on the solvent composition (e.g., a solvent heat of vaporization less than X); a temperature range in which to operate the solvent composition, and / or a boiling point of the solvent composition.32471 / 240556 / PC

[0039] At block 506, the optimizer 126 may generate a first request for at least one first datapoint from the calculation engine 124.

[0040] In some embodiments, the first request may be generated based on: (i) the information of one or more solvents, and / or (ii) the information of the polymer waste material.

[0041] In some embodiments, generating the first request may include screening solvents listed in the information of the one or more solvents based on: (i) chemical properties of solvents of the one or more solvents, (ii) process requirements of the recycling process, and / or (iii) environmental characteristics of respective solvents in the one or more solvents.

[0042] In some embodiments, the first request is generated further based on the solvent constraint.

[0043] In some embodiments, as pail of generating the first request, the optimizer 126 may perform multi-objective optimization (e.g., on the data from the information of one or more solvents, and / or the information of the polymer waste material, etc.) to determine the Pareto Front, giving all possible optimal solutions (e.g. temperature and solvent mixture composition) for trade-offs in selection criteria, for example, selectivity versus total solvent cost. Additionally or alternatively, the optimizer 126 may perform single-objective optimization to determine optimal conditions to maximize selectivity, for example by adding one or more of the solvent constraints on other performance indicators. Examples of the solvent constraints include: a number of individual solvents to be included in the solvent composition; a solvent toxicity score constraint on the solvent composition; a cost constraint on the solvent composition; a solvent heat of vaporization constraint on the solvent composition; and a temperature range in which to operate the solvent composition.

[0044] At block 508, the optimizer 126 may send the first request to the calculation engine 124.

[0045] At block 510, the calculation engine 124 may determine the requested one or more datapoints. In some embodiments, the calculation engine 124 may use a “COnductor-like Screening MOdel for Realistic Solvents” (COSMO-RS) technique to determine the one or more datapoints. Examples of the datapoints may include datapoints for chemical properties, such as solubility, insolubility, chemical potentials, sigma profiles, etc.32471 / 240556 / PC

[0046] In some embodiments, the at least one first datapoint is determined based on a section of a structure of a polymer, rather than the entire structure of the polymer. Advantageously, determining datapoints based on a section rather than the entire structure greatly improves technical functioning. In particular, this may greatly reduce the overall computation time (e.g., from days to minutes, etc.).

[0047] In some examples where the information of the one or more solvents includes vapor pressure on a grid of temperatures, the determination at block 510 may include, for each temperature, calculating the chemical potentials (e.g., datapoints) of each pure component and / or each solvent (or solvent mixture).

[0048] In some examples where the datapoints include solubility, DFT calculations are not used, or are only used on part of the polymer molecule (however, it should be appreciated that COSMO-RS calculation requires sigma profiles from a DFT calculation). In some such examples, polymer solubility may be determined by using COSMO-RS theory calculated sigma profiles computed for repeating units of the polymer chain. In some such examples, a surrogate thermodynamic model (STM) may be used. In some such examples, the theoretical framework of the STM enables calculation (e.g., explicitly or with low computational effort) of activity coefficients of the components for polymer- solvent mixtures (e.g., individual polymers and / or solvents). Furthermore, the model parameters can be determined based on results of COSMO- RS theory calculations for polymer- solvent mixtures (in particular oligomer-solvent mixtures) and / or fitted to experimental thermodynamic data such as oligomer / polymer solubilities. A model (e.g., the STM or other model) may then extrapolate the activity coefficients to the polymer limit with model parameters determined for polymers- solvents (in particular oligomers- solvents) mixtures.

[0049] In some embodiments, the STM: (i) has a COSMO-RS theory based parametrization framework; and / or (ii) a databank that contains precalculated and / or experimentally determined model parameters for the STM. In some embodiments, the one or more processors 120 (e.g., via the calculation engine 124) define a set of model parameters to use STM for the given list of solvents and polymers. The one or more processors 120 (e.g., via the calculation engine 124) may refer to the model databank to determine which values of the model parameters are already known, and which ones must be determined. The one or more processors 120 (e.g., via the32471 / 240556 / PC calculation engine 124) may use an appropriate model parameterization protocol to compute the unknown model parameters based on COSMO-RS theory calculations and / or on the available experimental thermodynamic data. The one or more processors 120 (e.g., via the calculation engine 124) may update the model databank with the new parameter’s values. The one or more processors 120 (e.g., via the calculation engine 124) may retrieve all model parameters from the model databank, pass them to the STM to compute activity coefficients of the components for the targeted polymer- solvent mixture as function of the temperature, overall mixture composition, polymer molecular’ weight and / or polymer chain composition. Subsequently, the one or more processors 120 (e.g., via the calculation engine 124) may compute polymer solubility values using the estimated activity coefficients and resulting from them other thermodynamic mixture properties (e.g. overall Gibbs excess free energy of the liquid phases), as well as by taking into account other polymer properties in standard thermodynamic relations describing phase equilibria conditions.

[0050] At block 512, the calculation engine 124 may send the at least one first datapoint to the optimizer 126. At block 514, the optimizer 126 may receive the at least one first datapoint.

[0051] From here, the optimizer 126 may continue to request datapoints from the calculation engine 124. In particular, datapoints may continue to be requested until an objective function is satisfied, thereby forming an iterative process. In some embodiments, the objective function includes a solubility parameter or an insolubility parameter. In some embodiments, the insolubility parameter may be used to determine an antisolvent. In some embodiments, the optimizer 126 requests further datapoints and utilizes the objective function via a non-dominated sorting genetic algorithm, and / or Bayesian optimization.

[0052] At block 516, the optimizer 126 may generate a new request for at least one new datapoint (e.g., including solubility information, etc.). The request may be generated based on: (i) the information of one or more solvents, (ii) the information of the polymer waste material, and / or (iii) a previously generated at least one datapoint (e.g. , one or more datapoints received at block 514) (e.g., including solubility information, etc.). In some embodiments, the new request is also based on the solvent constraint.

[0053] In some embodiments, as part of generating the new request, the optimizer 126 may perform multi-objective optimization (e.g., on the datapoints, etc.) to determine the Pareto Front,32471 / 240556 / PC giving all possible optimal solutions (e.g. temperature and solvent mixture composition) for trade-offs in selection criteria, for example, selectivity versus total solvent cost. Additionally or alternatively, the optimizer 126 may perform single-objective optimization to determine optimal conditions to maximize selectivity, for example by adding one or more of the solvent constraints on other performance indicators.

[0054] At block 518, the optimizer 126 may send the new request to the calculation engine 124.

[0055] At block 520, the calculation engine 124 may determine the at least one new data point. In some embodiments, the at least one new datapoint is determined similarly as in block 510 e.g., via a COSMO-RS technique, etc.). Examples of the datapoints may include datapoints for chemical properties, such as solubility, insolubility, chemical potentials, etc.

[0056] In some examples where the information of the one or more solvents includes vapor pressure on a grid of temperatures, the determination at block 520 may include, for each temperature, calculating the chemical potentials (e.g., datapoints) of each pure component and each solvent (or solvent mixture).

[0057] In some examples where the datapoints include solubility, DFT calculations are not used, or are only used on part of the polymer molecule (however, it should be appreciated that COSMO-RS calculation requires sigma profiles from a DFT calculation). In some such examples, polymer solubility may be determined by using COSMO-RS theory calculated sigma profiles computed for repeating units of the polymer chain. In some such examples, a surrogate thermodynamic model (STM) may be used. In some such examples, the theoretical framework of the STM enables calculation (e.g., explicitly or with low computational effort) of activity coefficients of the components for polymer- solvent mixtures (e.g., individual polymers and / or solvents). Furthermore, the model parameters can be determined based on results of COSMO- RS theory calculations for polymer- solvent mixtures (in particular oligomer- solvent mixtures) and / or fitted to experimental thermodynamic data such as oligomer / polymer solubilities. A model (e.g., the STM or other model) may then extrapolate the activity coefficients to the polymer limit with model parameters determined for polymers- solvents (in particular oligomers- solvents) mixtures.32471 / 240556 / PC

[0058] In some embodiments, the STM: (i) has a COSMO-RS theory based parametrization framework; and / or (ii) a databank that contains precalculated and / or experimentally determined model parameters for the STM. In some embodiments, the one or more processors 120 (e.g., via the calculation engine 124) define a set of model parameters to use STM for the given list of solvents and polymers. The one or more processors 120 e.g., via the calculation engine 124) may refer to the model databank to determine which values of the model parameters are already known, and which ones must be determined. The one or more processors 120 (e.g., via the calculation engine 124) may use an appropriate model parameterization protocol to compute the unknown model parameters based on COSMO-RS theory calculations and / or on the available experimental thermodynamic data. The one or more processors 120 (e.g., via the calculation engine 124) may update the model databank with the new parameter’s values. The one or more processors 120 (e.g., via the calculation engine 124) may retrieve all model parameters from the model databank, pass them to the STM to compute activity coefficients of the components for the targeted polymer- solvent mixture as function of the temperature, overall mixture composition, polymer molecular weight and / or polymer chain composition. Subsequently, the one or more processors 120 (e.g., via the calculation engine 124) may compute polymer solubility values using the estimated activity coefficients and resulting from them other thermodynamic mixture properties (e.g. overall Gibbs excel energy of the liquid phases), as well as by taking into account other polymer properties in standard thermodynamic relations describing phase equilibria conditions.

[0059] At block 522, the calculation engine 124 may send the at least one new datapoint to the optimizer 126. At block 524, the optimizer 126 may receive the at least one new datapoint.

[0060] At block 526, the optimizer 126 may determine if the objective function is satisfied. For example, if the objective function indicates that the solubility must be within a particular range, and the at least one new datapoint is within the particular range, the optimizer 126 may determine that the objective function has been satisfied. In another example, if the objective function indicates that the insolubility is within a particular range (e.g., an antisolvent composition is being determined), and the at least one new datapoint is within the particular range, the optimizer 126 may determine that the objective function has been satisfied. Additionally or alternatively, the objective function may include optimization criteria (e.g., lack of change in the objective function, a predetermined number of iterations, etc.).32471 / 240556 / PC

[0061] In some examples where the data points comprise chemical potentials, the optimizer 126 may use COSMO-RS theory to calculate each polymer solubility in each solvent (or solvent mixture) as a function of temperature. The solubility may then be input to an objective function to determine if the objective function has been satisfied.

[0062] If the objective function has not been satisfied, the example process 500 may return (e.g., iterate) back to block 516 where a new request is generated.

[0063] If the objective function has been satisfied, at block 528, the calculation engine 124 and / or optimizer 126 may determine: (i) the solvent composition (e.g., to be used in the recycling process), (ii) an optimal temperature (e.g., to use the solvent composition dissolve the polymer at), (iii) an optimal precipitation temperature (e.g., to remove the solvent composition at), and / or (iv) antisolvent composition (e.g., to be used to remove the solvent composition). In some embodiments, the calculation engine 124 and / or optimizer 126 may also determine predicted separation efficiency, cost, and / or maximal toxicity score for the solvent composition and / or antisolvent composition. Furthermore, in some embodiments, the calculation engine 124 and / or optimizer 126 may also determine a (possibly ranked) list of the best solvent compositions and / or antisolvent compositions (e.g., a list of solvent compositions with the highest solubilities; a list of antisolvent compositions with the highest insolubilities; etc.), as well as predicted separation efficiency, cost, and / or maximal toxicity score for each solvent composition and / or antisolvent composition on the list.

[0064] In some embodiments, the determination at block 528 may be based on at least one datapoint received from the final iteration of the plurality of iterations (e.g., a datapoint for the iteration when the optimizer 126 determines that the objective function has been satisfied).

[0065] In some embodiments where the solvent composition includes a first solvent and a second solvent, the determination at block 528 also includes a proportion of the first solvent and / or a proportion of the second solvent. In embodiments with more than two solvents, the determination may include a proportion of any solvent to any other solvent (or combination of solvents).

[0066] In some embodiments where an antisolvent is being determined, the determined antisolvent composition includes a first antisolvent and a second antisolvent, and the32471 / 240556 / PC determination at block 528 also includes a proportion of the first antisolvent and / or a proportion of the second antisolvcnt.

[0067] In some embodiments, the calculation engine 124 and / or optimizer 126 may determine a graphical visualization of a Pareto Front. In some examples, the Pareto Front includes multiple objectives (e.g., temperature, solvent mixture composition, toxicity, cost, etc.), and inputs (e.g., solvent compositions, temperature, etc.) to determine optimal solutions. This may be useful to a user if the user wishes to analyze and / or understand how the determinations at block 528 were made.

[0068] Any of the determination(s) made at block 528 may be displayed (e.g., via a display device of the one or more processors 120 or the recycling facility 150, etc.).

[0069] Following block 528, the process may return to block 504 to, for example, determine a new solvent composition to be used to remove another polymer from the polymer waste material 410.

[0070] It should be understood that not all blocks and / or events of the exemplary signal diagrams and / or flowcharts are required to be performed. Moreover, the exemplary signal diagrams and / or flowcharts are not mutually exclusive (e.g., block(s) / events from each example signal diagram and / or flowchart may be performed in any other signal diagram and / or flowchart). The exemplary signal diagrams and / or flowcharts may include additional, less, or alternate functionality, including that discussed elsewhere herein.Additional Examples

[0071] Figure 7 depicts an example process 700 including using solubility parameters 702 (e.g., the Hansen solubility parameters) to determine (i) the solvent composition (e.g., to be used in the recycling process), (ii) an optimal temperature (e.g., to use the solvent composition dissolve the polymer at), (iii) an optimal precipitation temperature (e.g., to remove the solvent composition at), and / or (iv) antisolvent (e.g., to be used to remove the solvent composition). As illustrated, in some embodiments, explicit solvent modeling 704 may be performed via the optimizer 126. In some embodiments, implicit solvent modeling 706 may be performed by the calculation engine 124.

[0072] Figure 8 depicts example measurements related to selecting an antisolvent.32471 / 240556 / PC

[0073] Figure 9 depicts an example process for separating a polymer waste material including three polymers: first polymer 411, second polymer 12, and third polymer 413.

[0074] Figure 10 depicts an example of a multilayer film, and an example of a physical mixture.Additional Aspects

[0075] Aspect 1. A computer-implemented method for determining a solvent composition to be used in a recycling process, the method comprising: receiving, via one or more processors, with a calculation engine, information of a polymer waste material, the polymer waste material including a first polymer and a second polymer; receiving, via the one or more processors, with an optimizer: (i) information of one or more solvents, and (ii) the information of the polymer waste material; generating, via the one or more processors, with the optimizer, a first request for at least one first datapoint including solubility information, the first request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material; sending, via the one or more processors, from the optimizer to the calculation engine, the first request; receiving, via the one or more processors, with the optimizer, the at least one first datapoint; until an objective function is satisfied, at each iteration of a plurality of iterations: generating, via the one or more processors, with the optimizer, a new request for at least one new datapoint including solubility information, the new request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material, and (iii) a previously generated at least one datapoint including solubility information; sending, via the one or more processors, from the optimizer to the calculation engine, the new request; and receiving, via the one or more processors, with the optimizer, the at least one new datapoint; and determining, via the one or more processors, with the optimizer, based on at least one datapoint received from a final iteration of the plurality of iterations, the solvent composition.32471 / 240556 / PC

[0076] Aspect 2. The computer-implemented method of aspect 1 , further comprising determining, via the one or more processors, with the optimizer, based on the at least one datapoint received from the final iteration of the plurality of iterations, an optimal temperature to use the solvent composition at.

[0077] Aspect 3. The computer-implemented method of any one of aspects 1-2, wherein the solvent composition comprises: (i) a first solvent, (ii) a proportion of the first solvent, (iii) a second solvent, and (iv) a proportion of the second solvent.

[0078] Aspect 4. The computer- implemented method of any one of aspects 1-3, wherein the optimizer comprises: (i) non-dominated sorting genetic algorithm, or (ii) Bayesian optimization.

[0079] Aspect 5. The computer- implemented method of any one of aspects 1-4, wherein the information of the polymer waste material includes: (i) a chemical structure of the first polymer, and (ii) a chemical structure of the second polymer.

[0080] Aspect 6. The computer-implemented method of any one of aspects 1-5, wherein the information of the polymer waste material further includes: polymer properties of the first polymer including: (i) percent crystallinity, (ii) free energy of fusion, (iii) enthalpy of fusion, (iv) entropy of fusion, (v) melting temperature, (vi) heat capacity at constant pressure, and / or (vii) molecular weight; and / or polymer properties of the second polymer including: (i) percent crystallinity, (ii) free energy of fusion, (iii) enthalpy of fusion, (iv) entropy of fusion, (v) melting temperature, (vi) heat capacity at constant pressure, and / or (vii) molecular weight.

[0081] Aspect 7. The computer-implemented method of any one of aspects 1-6, wherein the objective function includes a solubility parameter.

[0082] Aspect 8. The computer- implemented method of any one of aspects 1-7, wherein the information of the one or more solvents comprises a plurality of solvents, and the generating the first request includes: screening, via the one or more processors, with the optimizer, the plurality of solvents based on: (i) chemical properties of solvents of the plurality of solvents, (ii) process requirements of the recycling process, and / or (iii) environmental characteristics of the solvents of the plurality of solvents.32471 / 240556 / PC

[0083] Aspect 9. The computer-implemented method of any one of aspects 1 -8, wherein the information of one or more solvents includes, for respective solvents of the one or more solvents:(i) a boiling temperature, (ii) a parameters describing a dependence of saturated vapor pressure on temperature, (iii) a cost, (iv) a heat of vaporization, (v) a toxicity score, and / or (vi) a melting point.

[0084] Aspect 10. The computer-implemented method of any one of aspects 1-9, further comprising: receiving, via the one or more processors, with the optimizer, a solvent constraint specifying: a number of individual solvents to be included in the solvent composition; a solvent toxicity score constraint on the solvent composition; a cost constraint on the solvent composition; a solvent heat of vaporization constraint on the solvent composition; and / or a temperature range in which to operate the solvent composition; and wherein the first request is generated further based on the solvent constraint; and wherein the new requests are generated further based on the solvent constraint.

[0085] Aspect 11. The computer- implemented method of any one of aspects 1-10, further comprising: generating, via the one or more processors, with the calculation engine, the at least one first datapoint based on a section of a structure of the first polymer, wherein the section does not include the entire structure of the first polymer.

[0086] Aspect 12. The computer- implemented method of any one of aspects 1-11, further comprising: determining, via the one or more processors, with the optimizer, an antisolvent composition for the solvent composition by optimizing an insolubility parameter.

[0087] Aspect 13. The computer- implemented method of any one of aspects 1-12, further comprising: determining, via the one or more processors, a precipitation temperature to remove the polymer at.32471 / 240556 / PC

[0088] Aspect 14. A computer device for determining a solvent composition to be used in a recycling process, the computer device comprising one or more processors configured to: receive, with a calculation engine, information of a polymer waste material, the polymer waste material including a first polymer and a second polymer; receive, with an optimizer: (i) information of one or more solvents, and (ii) the information of the polymer waste material; generate, with the optimizer, a first request for at least one first datapoint including solubility information, the first request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material; send, from the optimizer to the calculation engine, the first request; receive, with the optimizer, the at least one first datapoint; until an objective function is satisfied, at each iteration of a plurality of iterations: generate, with the optimizer, a new request for at least one new datapoint including solubility information, the new request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material, and (iii) a previously generated at least one datapoint including solubility information; send, from the optimizer to the calculation engine, the new request; and receive, with the optimizer, the at least one new datapoint; and determine, with the optimizer, based on at least one datapoint received from a final iteration of the plurality of iterations, the solvent composition.

[0089] Aspect 15. The computer device of aspect 1 , wherein the one or more processors are further configured to determine, with the optimizer, based on the at least one datapoint received from the final iteration of the plurality of iterations, an optimal temperature to use the solvent composition at.

[0090] Aspect 16. The computer device of any one of aspects 14-15, wherein the solvent composition comprises: (i) a first solvent, (ii) a proportion of the first solvent, (iii) a second solvent, and (iv) a proportion of the second solvent.

[0091] Aspect 17. The computer device of any one of aspects 14-16, further including a display device configured to display a representation of the solvent composition.32471 / 240556 / PC

[0092] Aspect 18. A computer system for determining a solvent composition to be used in a recycling process, the computer system comprising: one or more processors; and one or more non-transitory memories, the one or more non-transitory memories having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to: receive, with a calculation engine, information of a polymer waste material, the polymer waste material including a first polymer and a second polymer; receive, with an optimizer: (i) information of one or more solvents, and (ii) the information of the polymer waste material; generate, with the optimizer, a first request for at least one first datapoint including solubility information, the first request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material; send, from the optimizer to the calculation engine, the first request; receive, with the optimizer, the at least one first datapoint; until an objective function is satisfied, at each iteration of a plurality of iterations: generate, with the optimizer, a new request for at least one new datapoint including solubility information, the new request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material, and (iii) a previously generated at least one datapoint including solubility information; send, from the optimizer to the calculation engine, the new request; and receive, with the optimizer, the at least one new datapoint; and determine, with the optimizer, based on at least one datapoint received from a final iteration of the plurality of iterations, the solvent composition.

[0093] Aspect 19. The computer system of aspect 18, wherein the solvent composition comprises: (i) a first solvent, (ii) a proportion of the first solvent, (iii) a second solvent, and (iv) a proportion of the second solvent.

[0094] Aspect 20. The computer system of any one of aspects 18-19, further comprising a display device, the one or more non-transitory memories having stored thereon computerexecutable instructions that, when executed by the one or more processors, cause the one or more processors to display a representation of the solvent composition on the display device.32471 / 240556 / PCOTHER MATTERS

[0095] Although the text herein sets forth a detailed description of numerous different embodiments, it should be understood that the legal scope of the invention is defined by the words of the claims set forth at the end of this patent. The detailed description is to be construed as exemplary only and does not describe every possible embodiment, as describing every possible embodiment would be impractical, if not impossible. One could implement numerous alternate embodiments, using either current technology or technology developed after the filing date of this patent, which would still fall within the scope of the claims.

[0096] It should also be understood that, unless a term is expressly defined in this patent using the sentence “As used herein, the term ‘ ’ is hereby defined to mean...” or a similar sentence, there is no intent to limit the meaning of that term, either expressly or by implication, beyond its plain or ordinary meaning, and such term should not be interpreted to be limited in scope based upon any statement made in any section of this patent (other than the language of the claims). To the extent that any term recited in the claims at the end of this disclosure is referred to in this disclosure in a manner consistent with a single meaning, that is done for sake of clarity only so as to not confuse the reader, and it is not intended that such claim term be limited, by implication or otherwise, to that single meaning.

[0097] Throughout this specification, plural instances may implement components, operations, or structures described as a single instance. Although individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed concurrently, and nothing requires that the operations be performed in the order illustrated. Structures and functionality presented as separate components in example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter herein.

[0098] Additionally, certain embodiments are described herein as including logic or a number of routines, subroutines, applications, or instructions. These may constitute either software (code embodied on a non-transitory, tangible machine-readable medium) or hardware. In hardware, the routines, etc., are tangible units capable of performing certain operations and may be32471 / 240556 / PC configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., a standalone, client or server computer system) or one or more hardware modules of a computer system e.g., a processor or a group of processors) may be configured by software (e.g. , an application or application portion) as a hardware module that operates to perform certain operations as described herein.

[0099] In various embodiments, a hardware module may be implemented mechanically or electronically. For example, a hardware module may comprise dedicated circuitry or logic that is permanently configured (e.g., as a special-purpose processor, such as a field programmable gate array (FPGA) or an application- specific integrated circuit (ASIC) to perform certain operations). A hardware module may also comprise programmable logic or circuitry (e.g., as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations. It will be appreciated that the decision to implement a hardware module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.

[0100] Accordingly, the term “hardware module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. Considering embodiments in which hardware modules are temporarily configured (e.g., programmed), each of the hardware modules need not be configured or instantiated at any one instance in time. For example, where the hardware modules comprise a general-purpose processor configured using software, the general-purpose processor may be configured as respective different hardware modules at different times. Software may accordingly configure a processor, for example, to constitute a particular hardware module at one instance of time and to constitute a different hardware module at a different instance of time.

[0101] Hardware modules can provide information to, and receive information from, other hardware modules. Accordingly, the described hardware modules may be regarded as being communicatively coupled. Where multiple of such hardware modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and32471 / 240556 / PC buses) that connect the hardware modules. In embodiments in which multiple hardware modules arc configured or instantiated at different times, communications between such hardware modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware modules have access. For example, one hardware module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information).

[0102] The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. The modules referred to herein may, in some example embodiments, comprise processor- implemented modules.

[0103] Similarly, the methods or routines described herein may be at least partially processor- implemented. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented hardware modules. The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors may be distributed across a number of geographic locations.

[0104] Unless specifically stated otherwise, discussions herein using words such as “processing,” “computing,” “calculating,” “determining,” “presenting,” “displaying,” or the like may refer to actions or processes of a machine (e.g., a computer) that manipulates or transforms data represented as physical (e.g., electronic, magnetic, or optical) quantities within one or more memories (e.g., volatile memory, non-volatile memory, or a combination thereof), registers, or other machine components that receive, store, transmit, or display information.32471 / 240556 / PC

[0105] As used herein any reference to “one embodiment” or “an embodiment” means that a particular' clement, feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.

[0106] Some embodiments may be described using the expression “coupled” and “connected” along with their derivatives. For example, some embodiments may be described using the term “coupled” to indicate that two or more elements are in direct physical or electrical contact. The term “coupled,” however, may also mean that two or more elements are not in direct contact with each other, but yet still co-operate or interact with each other. The embodiments are not limited in this context.

[0107] As used herein, the terms “comprises,” “comprising,” “includes,” “including,” “has,” “having” or any other variation thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Further, unless expressly stated to the contrary, “or” refers to an inclusive or and not to an exclusive or. For example, a condition A or B is satisfied by any one of the following: A is true (or present) and B is false (or not present), A is false (or not present) and B is true (or present), and both A and B are true (or present).

[0108] In addition, use of the “a” or “an” are employed to describe elements and components of the embodiments herein. This is done merely for convenience and to give a general sense of the description. This description, and the claims that follow, should be read to include one or at least one and the singular also includes the plural unless it is obvious that it is meant otherwise.

[0109] Upon reading this disclosure, those of skill in the art will appreciate still additional alternative structural and functional designs for the approaches described herein. Thus, while particular embodiments and applications have been illustrated and described, it is to be understood that the disclosed embodiments are not limited to the precise construction and components disclosed herein. Various modifications, changes and variations, which will be apparent to those skilled in the art, may be made in the arrangement, operation and details of the32471 / 240556 / PC method and apparatus disclosed herein without departing from the spirit and scope defined in the appended claims.

[0110] The particular features, structures, or characteristics of any specific embodiment may be combined in any suitable manner and in any suitable combination with one or more other embodiments, including the use of selected features without corresponding use of other features. In addition, many modifications may be made to adapt a particular application, situation or material to the essential scope and spirit of the present invention. It is to be understood that other variations and modifications of the embodiments of the present invention described and illustrated herein are possible in light of the teachings herein and are to be considered part of the spirit and scope of the present invention.

[0111] While the preferred embodiments of the invention have been described, it should be understood that the invention is not so limited and modifications may be made without departing from the invention. The scope of the invention is defined by the appended claims, and all devices that come within the meaning of the claims, either literally or by equivalence, are intended to be embraced therein.

[0112] It is therefore intended that the foregoing detailed description be regar ded as illustrative rather than limiting, and that it be understood that it is the following claims, including all equivalents, that are intended to define the spirit and scope of this invention.

[0113] Furthermore, the patent claims at the end of this patent application are not intended to be construed under 35 U.S.C. § 112(f) unless traditional means-plus-function language is expressly recited, such as “means for” or “step for” language being explicitly recited in the claim(s). The systems and methods described herein are directed to an improvement to computer functionality, and improve the functioning of conventional computers.

Claims

32471 / 240556 / PCWHAT IS CLAIMED:

1. A computer-implemented method for determining a solvent composition to be used in a recycling process, the method comprising: receiving, via one or more processors, with a calculation engine, information of a polymer waste material, the polymer waste material including a first polymer and a second polymer; receiving, via the one or more processors, with an optimizer: (i) information of one or more solvents, and (ii) the information of the polymer waste material; generating, via the one or more processors, with the optimizer, a first request for at least one first datapoint including solubility information, the first request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material; sending, via the one or more processors, from the optimizer to the calculation engine, the first request; receiving, via the one or more processors, with the optimizer, the at least one first datapoint; until an objective function is satisfied, at each iteration of a plurality of iterations: generating, via the one or more processors, with the optimizer, a new request for at least one new datapoint including solubility information, the new request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material, and (iii) a previously generated at least one datapoint including solubility information; sending, via the one or more processors, from the optimizer to the calculation engine, the new request; and receiving, via the one or more processors, with the optimizer, the at least one new datapoint; and determining, via the one or more processors, with the optimizer, based on at least one datapoint received from a final iteration of the plurality of iterations, the solvent composition.

2. The computer- implemented method of claim 1, further comprising determining, via the one or more processors, with the optimizer, based on at least one datapoint received from32471 / 240556 / PC at least one iteration of the plurality of iterations, an optimal temperature to use the solvent composition at.

3. The computer-implemented method of claim 1, wherein the solvent composition comprises: (i) a first solvent, (ii) a proportion of the first solvent, (iii) a second solvent, and (iv) a proportion of the second solvent.

4. The computer-implemented method of claim 1, wherein the optimizer comprises: (i) non-dominated sorting genetic algorithm, or (ii) Bayesian optimization .

5. The computer- implemented method of claim 1, wherein the information of the polymer waste material includes: (i) a chemical structure of the first polymer, and (ii) a chemical structure of the second polymer.

6. The computer-implemented method of claim 5, wherein the information of the polymer waste material further includes: polymer properties of the first polymer including: (i) percent crystallinity, (ii) free energy of fusion, (iii) enthalpy of fusion, (iv) entropy of fusion, (v) melting temperature, (vi) heat capacity at constant pressure, and / or (vii) molecular weight; and / or polymer properties of the second polymer including: (i) percent crystallinity, (ii) free energy of fusion, (iii) enthalpy of fusion, (iv) entropy of fusion, (v) melting temperature, (vi) heat capacity at constant pressure, and / or (vii) molecular weight.

7. The computer-implemented method of claim 1, wherein the objective function includes a solubility parameter.

8. The computer-implemented method of claim 1, wherein the information of the one or more solvents comprises a plurality of solvents, and the generating the first request includes: screening, via the one or more processors, with the optimizer, the plurality of solvents based on: (i) chemical properties of solvents of the plurality of solvents, (ii) process requirements32471 / 240556 / PC of the recycling process, and / or (iii) environmental characteristics of the solvents of the plurality of solvents.

9. The computer-implemented method of claim 1, wherein the information of one or more solvents includes, for respective solvents of the one or more solvents: (i) a boiling temperature, (ii) parameters describing a dependence of saturated vapor pressure on temperature, (iii) a cost, (iv) a heat of vaporization, (v) a toxicity score, and / or (vi) a melting point.

10. The computer-implemented method of claim 1, further comprising: receiving, via the one or more processors, with the optimizer, a solvent constraint specifying: a number of individual solvents to be included in the solvent composition; a solvent toxicity score constraint on the solvent composition; a cost constraint on the solvent composition; a solvent heat of vaporization constraint on the solvent composition; and / or a temperature range in which to operate the solvent composition; and wherein the first request is generated further based on the solvent constraint; and wherein the new requests are generated further based on the solvent constraint.

11. The computer-implemented method of claim 1, further comprising: generating, via the one or more processors, with the calculation engine, the at least one first datapoint based on a section of a structure of the first polymer, wherein the section does not include the entire structure of the first polymer.

12. The computer-implemented method of claim 1, further comprising: determining, via the one or more processors, with the optimizer, an antisolvent composition for the solvent composition by optimizing an insolubility parameter.

13. The computer- implemented method of claim 1, further comprising: determining, via the one or more processors, a precipitation temperature to remove the polymer at.32471 / 240556 / PC14. A computer device for determining a solvent composition to be used in a recycling process, the computer device comprising one or more processors configured to: receive, with a calculation engine, information of a polymer waste material, the polymer waste material including a first polymer and a second polymer; receive, with an optimizer: (i) information of one or more solvents, and (ii) the information of the polymer waste material; generate, with the optimizer, a first request for at least one first datapoint including solubility information, the first request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material; send, from the optimizer to the calculation engine, the first request; receive, with the optimizer, the at least one first datapoint; until an objective function is satisfied, at each iteration of a plurality of iterations: generate, with the optimizer, a new request for at least one new datapoint including solubility information, the new request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material, and (iii) a previously generated at least one datapoint including solubility information; send, from the optimizer to the calculation engine, the new request; and receive, with the optimizer, the at least one new datapoint; and determine, with the optimizer, based on at least one datapoint received from a final iteration of the plurality of iterations, the solvent composition.

15. The computer device of claim 14, wherein the one or more processors are further configured to determine, with the optimizer, based on at least one datapoint received from at least one iteration of the plurality of iterations, an optimal temperature to use the solvent composition at.

16. The computer device of claim 14, wherein the solvent composition comprises: (i) a first solvent, (ii) a proportion of the first solvent, (iii) a second solvent, and (iv) a proportion of the second solvent.32471 / 240556 / PC17. The computer device of claim 14, further including a display device configured to display a representation of the solvent composition.

18. A computer system for determining a solvent composition to be used in a recycling process, the computer system comprising: one or more processors; and one or more non-transitory memories, the one or more non-transitory memories having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to: receive, with a calculation engine, information of a polymer waste material, the polymer waste material including a first polymer and a second polymer; receive, with an optimizer: (i) information of one or more solvents, and (ii) the information of the polymer waste material; generate, with the optimizer, a first request for at least one first datapoint including solubility information, the first request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material; send, from the optimizer to the calculation engine, the first request; receive, with the optimizer, the at least one first datapoint; until an objective function is satisfied, at each iteration of a plurality of iterations: generate, with the optimizer, a new request for at least one new datapoint including solubility information, the new request generated based on: (i) the information of one or more solvents, and (ii) the information of the polymer waste material, and (iii) a previously generated at least one datapoint including solubility information; send, from the optimizer to the calculation engine, the new request; and receive, with the optimizer, the at least one new datapoint; and determine, with the optimizer, based on at least one datapoint received from a final iteration of the plurality of iterations, the solvent composition.

19. The computer system of claim 18, wherein the solvent composition comprises: (i) a first solvent, (ii) a proportion of the first solvent, (iii) a second solvent, and (iv) a proportion of the second solvent.32471 / 240556 / PC20. The computer system of claim 18, further comprising a display device, the one or more non-transitory memories having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to display a representation of the solvent composition on the display device.

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