Process and apparatus for the carbonatation of lime and other reactive dusts

Abstract

A process and apparatus provide batch carbonatation of a fluent pulverulent body (101) in four or five distinct phases (P1, P2, P3, P4, P5) defined by the varying viscosity profile of the mixture (100), wherein the particles (102) are mixed with water (W) and a carbonic gas (G) and also agglomerated to form seed particles (103) and, optionally, larger pellets (104) within the mixing vessel (20). Process parameters may be adjusted based on the chemical composition and / or sensed viscosity profile of the batch (101'), optionally by means of a machine learning model (80).

Description

[0001] Process and apparatus for the carbonatation of lime and other reactive dusts

[0002] This invention relates to processes for treatment of alkaline dusts and other industrial waste streams by carbonatation.

[0003] In this specification, the term carbonatation means a process in which lime or another carbonate forming substance reacts with a carbonic gas, such as carbon dioxide, to produce a carbonate, such as calcium carbonate.

[0004] Carbonate forming compounds include for example calcium oxide, calcium hydroxide, limonite, calcite, and a wide variety of other compounds which may be based on, for example, calcium, silicon, iron, magnesium, or aluminium.

[0005] Carbonatation can be used as a method for sequestering carbon from carbon dioxide contained in waste gases from an industrial process, using waste products from the same or other industrial processes, for example, as discussed in

[0006] Kusin et al: Carbon dioxide sequestration of iron ore mining waste under low-reaction condition of a direct mineral carbonation process. Environ Sci Pollut Res Int. 2023 Feb;30(9):22188-22210. doi: 10.1007 / sll356-022-23677-3. Epub 2022 Oct 25. PMID: 36282383. (https: / / pubmed.ncbi.nlm.nih.gov / 36282383 / )

[0007] Advantageously, the end product of the carbonatation process may be useable, for example, as aggregate for use as a bulk material in building or for the production of building materials such as blocks. Thus, two voluminous waste streams may be combined in a carbon negative process to form a useful bulk product.

[0008] The waste feedstock for the carbonatation process may include industrial waste products such as fly ash, air pollution control residue (APCR) and cement kiln dust (CKD) or cement bypass dust (CBD).

[0009] APCR is a waste produced during a flue gas treatment process that removes contaminants (e.g. heavy metals, chlorides, or other pollutants) from the flue gas. The flue gas may be generated by incineration of a feedstock, commonly by incineration of municipal solid waste in waste-to-energy plants. Typically the APCR will include a mixture of dusts of lime and activated carbon that are added to the flue gas as reagents, together with fly ash generated by incineration of the feedstock and entrained in the flue gas.

[0010] The chemical composition of APCR varies widely with the nature of the feedstock and also the parameters of the incineration process.Cement kiln dust (CKD) is separated from the exhaust gas generated during calcination of a feedstock in a cement kiln. Some CKD is recycled through the kiln, but huge volumes are produced as waste. CKD may include or consist of cement bypass dust (CBD), which typically contains high levels of free lime and contaminants such as chlorides, which may be derived from combustion of the fuel used to heat the kiln. The CBD is removed from the process in order to control the chemical composition (e.g. the chloride content) of the final cement product.

[0011] It is known to process a mixture of waste alkaline dusts with a larger particulate additive such as sand or crushed limestone together with water in a mixer, with a small proportion of portland cement. The water reacts with the dust in an exothermic hydration reaction, and the remaining water then forms a film around the particles which, in contact with the carbonic gas, facilitates the subsequent carbonatation reactions with the gas which flows through the mixing vessel. The carbonatation reaction is allowed to proceed, e.g. for about half an hour, before the damp mixture is discharged to a pelletiser in which the carbonatated dust particles agglomerate around the larger particulates to form pellets, assisted by the cement which acts as a binder.

[0012] By way of example, GB2612187 A teaches a mixer with rotating blade assemblies that move in planetary motion about vertical axes within a fixed vessel, for use in a carbonatation process to avoid dust entrainment in the gas flow.

[0013] Typically the larger particulate additive, e.g. sand or limestone, forms about half or more of the solid content of the mixture, which however can add cost since often it will not be produced as a waste stream.

[0014] The wide variation in surface area and chemical composition, hence reactivity of the dust can also be problematic since it strongly affects the exotherm of the hydration reaction and, in consequence, the viscosity and water content of the subsequent mixture. Typically it is difficult or impossible to predict accurately the reactivity of any given batch of dust, even from a single source, and so the process conditions are often set by rule-of-thumb, frequently resulting in a mixture that is too dry (and so not completely reacted) or too wet (and so not suitable for pelletisation).

[0015] The process time must also be long enough to obtain complete reaction of the mixture, which unnecessarily reduces throughput (and so efficiency) for more reactive batches.

[0016] It is a general object of the present invention to provide an apparatus and method that addresses at least some of these issues.

[0017] Summary of the InventionIn accordance with the present invention there are provided, in a first aspect, an apparatus, and in a second aspect, a process, as defined in the respective independent claims.

[0018] The dependent claims define optional features.

[0019] In its first aspect, the invention provides an apparatus for carbonatation of a fluent body of solid particles by reaction with a carbonic gas, at least some of the solid particles being dust particles.

[0020] The apparatus is operable to process multiple batches sequentially, each in accordance with a process, wherein each batch is formed from a different said fluent body.

[0021] The apparatus includes a control system, a vessel for containing the fluent body, a rotor surface arranged within the vessel for rotation about an axis, and an actuator, operable by the control system to drive the rotor surface in rotation about the axis.

[0022] The apparatus further includes a water flow control means, operable by the control system to admit water into the vessel to form a mixture with the fluent body, and a gas flow control means, operable by the control system to control a flow of the gas into the vessel at a gas flow rate.

[0023] The apparatus further includes a sensing means that is arranged to sense a viscosity of the mixture within the vessel, and to generate viscosity data as a time series representing the sensed viscosity of the mixture over time.

[0024] The control system is arranged to receive the viscosity data from the sensing means, and to supply power to the actuator, and to operate the water and gas flow control means, to process each batch in accordance with the process.

[0025] For each batch, the process includes a first, hydration phase including an initial mixing period; followed by a second, hydration and carbonatation phase; followed by a third, carbonatation phase having a third phase duration; followed by a fourth, nucleation phase.

[0026] During the first, hydration phase, both the fluent body and a first volume of water are introduced into the vessel, and the gas flow rate is limited for the initial mixing period to not more than a first gas flow rate value, and the actuator is operated to drive the rotor surface in rotation, to mix the fluent body and the water to form the mixture, and the viscosity of the mixture defines, over time, a first viscosity profile, wherein the first viscosity profile defines a progressive increase in viscosity.

[0027] The viscosity of the mixture defines a first viscosity peak value following said progressive increase in viscosity of the first viscosity profile.

[0028] After the initial mixing period, the gas flow rate is increased to a second gas flow rate value, higher than the first gas flow rate value.During the second, hydration and carbonatation phase, a second volume of water is introduced into the vessel, and the actuator is operated to drive the rotor surface in rotation, to mix the fluent body with the second volume of water, and the viscosity of the mixture defines, over time, a second viscosity profile, wherein the second viscosity profile defines a progressive decrease in viscosity to a reduced viscosity value, lower than the first viscosity peak value.

[0029] During the third, carbonatation phase, the actuator is operated to drive the rotor surface in rotation, to expose fresh surfaces of the mixture for reaction with the gas, and the viscosity of the mixture defines, over time, a third viscosity profile having a smaller rate of change than each of the first viscosity profile and the second viscosity profile.

[0030] The control system is arranged, after the third phase duration, to terminate the third, carbonatation phase and initiate the fourth, nucleation phase by operating the water flow control means to introduce, into the vessel, a third volume of water, wherein the third volume of water is selected to cause a progressive agglomeration of the dust particles to form seed particles during the fourth, nucleation phase.

[0031] During the fourth, nucleation phase, the actuator is operated to drive the rotor surface in rotation, to mix the fluent body with the third volume of water, and the viscosity of the mixture defines, over time, a fourth viscosity profile, wherein the fourth viscosity profile defines a progressive increase in viscosity having a greater rate of change than the third viscosity profile and corresponding to said progressive agglomeration of the dust particles to form seed particles.

[0032] In its second aspect, the invention provides a process for carbonatation of a fluent body of solid particles by reaction with a carbonic gas, at least some of the solid particles being dust particles, by means of an apparatus.

[0033] The apparatus includes a vessel for containing the fluent body, and a rotor surface arranged within the vessel for rotation about an axis, and is operable to process multiple batches sequentially, each in accordance with the process, wherein each batch is formed from a different said fluent body.

[0034] The process includes, for each respective batch: mixing the fluent body with water, in the vessel, to form a mixture; providing a flow of the gas into the vessel at a gas flow rate; and sensing a viscosity of the mixture within the vessel to generate viscosity data as a time series representing the sensed viscosity of the mixture over time.

[0035] The process further includes, for each respective batch: a first, hydration phase including an initial mixing period; followed by a second, hydration and carbonatation phase; followed by a third, carbonatation phase having a third phase duration; followed by a fourth, nucleation phase.During the first, hydration phase: both the fluent body and a first volume of water are introduced into the vessel, and the gas flow rate is limited for the initial mixing period to not more than a first gas flow rate value, and the rotor surface is driven in rotation, to mix the fluent body and the water to form the mixture, and the viscosity of the mixture defines, over time, a first viscosity profile, wherein the first viscosity profile defines a progressive increase in viscosity.

[0036] The viscosity of the mixture defines a first viscosity peak value following said progressive increase in viscosity of the first viscosity profile.

[0037] After the initial mixing period, the gas flow rate is increased to a second gas flow rate value, higher than the first gas flow rate value.

[0038] During the second, hydration and carbonatation phase, a second volume of water is introduced into the vessel, and the rotor surface is driven in rotation, to mix the fluent body with the second volume of water; and the viscosity of the mixture defines, over time, a second viscosity profile, wherein the second viscosity profile defines a progressive decrease in viscosity to a reduced viscosity value, lower than the first viscosity peak value.

[0039] During the third, carbonatation phase, the rotor surface is driven in rotation, to expose fresh surfaces of the mixture for reaction with the gas, and the viscosity of the mixture defines, over time, a third viscosity profile having a smaller rate of change than each of the first viscosity profile and the second viscosity profile.

[0040] After the third phase duration, the third, carbonatation phase is terminated, and the fourth, nucleation phase is initiated, by introducing, into the vessel, a third volume of water, wherein the third volume of water is selected to cause a progressive agglomeration of the dust particles to form seed particles during the fourth, nucleation phase.

[0041] During the fourth, nucleation phase, the rotor surface is driven in rotation, to mix the fluent body with the third volume of water; and the viscosity of the mixture defines, over time, a fourth viscosity profile, wherein the fourth viscosity profile defines a progressive increase in viscosity having a greater rate of change than the third viscosity profile and corresponding to said progressive agglomeration of the dust particles to form seed particles.

[0042] In its first and second aspects, by operating the apparatus and adding water at selected intervals in accordance with the defined phases of the process, which are identified by the sensed viscosity profile of the mixture in the vessel, the invention combines both carbonatation and at least nucleation, or optionally, full pelletisation in the same mixer.

[0043] The invention thus provides a more efficient and integrated process, making it possible to produce a useful final product in the form of an aggregate from a feedstock that may consist principally or wholly of a dust without admixture with a larger particulate.Moreover, by determining key process parameter values during the process, based on the sensed viscosity data, the process can be optimised for the reactivity of the batch, even where the batch properties are unknown at the beginning of the process. This makes it possible to adjust the batch viscosity and the process dwell time for each batch and so provides a more efficient process with higher throughput.

[0044] In particular, the process parameter values can be determined based on the first viscosity profile which provides an initial indication of the reactivity of the batch, and optionally further adjusted based on real time viscosity data from the batch later in the process. By using a machine learning model, the parameter value selection can be derived based on characteristic trends in the viscosity profile, which are identified based on previously processed batches forming the training data set.

[0045] The novel process is generally described herein as embodied in a control system of the apparatus. However, it will be understood that optional features of the method may be practiced in any desired manner, and need not necessarily be embodied in the control system.

[0046] Further features and advantages will be evident from the illustrative examples of the novel apparatus and process that will now be described, purely by way of example and without limitation to the scope of the claims, and with reference to the accompanying drawings, in which:

[0047] Fig. 1 approximates a typical viscosity data set illustrating an embodiment of the novel process over time.

[0048] Fig. 2 is a schematic drawing of an embodiment of the novel apparatus.

[0049] Fig. 3 illustrates the agglomeration of dust particles during nucleation and pelletisation. Fig. 4 shows the chemical composition data obtained by testing a series of samples of the dust obtained from a single cement plant.

[0050] Fig. 5 is another illustration of the chemical composition data presented in Fig. 4 for four of the samples.

[0051] Fig. 6 shows a real viscosity data set obtained by processing one batch in the apparatus. Fig. 7 shows how the viscosity data of Fig. 6 is sampled to obtain a data set comprising discrete value points for the first and second phases of the process.

[0052] Fig. 8 shows four more viscosity data sets, each obtained by processing multiple batches of the material that was sampled to obtain the data shown in the four pie charts of Fig. 5, respectively.

[0053] Fig. 9 is a simplified schematic drawing of a neural network model of the machine learning control subsystem, showing how the viscosity data set of Fig. 7 is processed by the model to obtain an inferred percentage of each target constituent in the batch.Fig. 10 illustrates the training data for the model.

[0054] Figs. 11a and lib show a set of data points for the proportion of lime, drawn from the data set of Fig. 4, but excluded from the model training data, wherein Fig. lib also shows the corresponding data points inferred by the model.

[0055] Figs. 12 and 13 illustrate the reaction of lime as modelled by the algorithm of the chemical kinetics control subsystem.

[0056] The apparatus

[0057] Fig. 2 shows just one example of an apparatus for use in accordance with embodiments of the process as illustrated in Fig. 1, for carbonatation of a fluent body 101 of solid particles 102 by reaction with a carbonic gas G, wherein at least some of the solid particles 102 are dust particles 102'.

[0058] The apparatus is operable to process multiple batches 101' sequentially, each in accordance with the process, wherein each batch 101' is formed from a different fluent body 101.

[0059] The control system

[0060] The process may be embodied in a control system 10 of the apparatus, which as illustrated may include a processor 13 and a memory 14. The processor 13 may execute instructions stored in non-volatile memory 14 to control the apparatus in accordance with the process.

[0061] The steps of the process may be performed by the remaining elements of the apparatus which include an actuator 40, a water flow control means 60, a gas flow control means 70, and a sensing means 51.

[0062] The mixer

[0063] The apparatus includes a mixer comprising a vessel 20 for containing the fluent body 101, and a rotor surface or surfaces 31 arranged within the vessel 20 for rotation about an axis X31. The vessel 20 contains both the mixture 100 and the gas G which is in contact with the surface of the mixture 100 during carbonatation. Together, the vessel 20 and the rotor surface 31 define a mixer.

[0064] The actuator 40 may be a motor (e.g. an electric motor or a hydraulic motor) and is operable by the control system 10 to drive the rotor surface 31 in rotation about the axis X31.

[0065] Preferably the vessel 20 defines an enclosed volume that contains the gas G during the process, as shown.The rotor surface 31 may be a surface of a rotor 30 that is movable relative to a static vessel 20, as exemplified by the illustrated embodiment.

[0066] Alternatively (not shown), the rotor surface may be an interior surface of the vessel, wherein the vessel is driven in rotation. The interior surface of the vessel may include fins or blades or other elements that agitate the mixture as the vessel rotates. Alternatively or additionally, a fixed surface or an array of fixed surfaces (e.g. fixed blades) may be arranged within the vessel so that the mixture set in motion by rotation of the interior surface of the vessel will impinge on the fixed surface or surfaces, causing a stirring action which exposes fresh surfaces of the mixture for reaction with the gas. Alternatively or additionally, the vessel may include moving rotor surfaces that move relative to the vessel as the vessel rotates.

[0067] In each case, the rotor surface (e.g. surfaces 31 as illustrated) or the fixed surface or surfaces may be arranged to extend down through the top surface of the fluent body 101 within the vessel, so that a moving cavity is created in the mixture 100 behind the rotor surface 31 or fixed surface as the the top surface of the mixture 100 is disrupted by movement of the mixture 100 past the respective surfaces. The cavity exposes fresh surfaces of the mixture 100 for reaction with the gas G.

[0068] As illustrated, the rotor surface(s) or fixed surface(s) may include two or more blades, spaced apart radially with respect to the rotation axis X31 of the rotor, wherein each blade extends down through the surface of the mixture 100 towards the base of the vessel 20, so as to cut through the mixture 100 as the rotor surface 31 rotates about the axis X31.

[0069] Although the rotor may move with a planetary motion if desired, it is found perfectly satisfactory in practice to arrange the rotor surface to move in simple rotation about a fixed axis X31 without planetary motion. This considerably simplifies the drive assembly when compared with prior art planetary arrangements.

[0070] The rotor may be an assembly that moves in rotation about a fixed axis in a static vessel. The fixed axis X31 may be vertical, which is found to be very effective in assisting the nucleation and pelletisation of the mixture.

[0071] In alternative arrangements (not shown), the rotor may include a local axis about which the rotor surface rotates, wherein the rotor axis is acollinear (i.e. is not collinear) with the fixed axis about which the rotor rotates. The fixed axis may be vertical. The local axis may be vertical (so the rotor surface defines a planetary motion) or horizontal (so the rotor surface does not define a planetary motion).

[0072] Two or more such rotor axes may be spaced apart around the fixed axis, with one or more rotor surfaces moving in rotation about each respective local axis as the local axes move inrotation with the rotor assembly about the fixed axis. For example, the rotor could have two or more local rotor assemblies extending from a central hub. For example, two such local assemblies may extend in opposite directions in diametrically opposed relation from the central hub and rotate about a common horizontal axis perpendicular to the fixed vertical axis about which the hub rotates.

[0073] The mixer may include both a stirrer unit which rotates at a relatively low speed (e.g. about 80 RPM) to mix the water and dust, and a high speed agitator unit which rotates at a higher speed than the stirrer unit (e.g. about 400 RPM) to break down dry lumps of dust that tend to form when the dust is hydrated, as known in the art. Both units may be mounted on a common rotor that rotates at lower speed, e.g. about 20 RPM so that both units sweep the volume of the vessel.

[0074] However, it has been found that a satisfactory result can be obtained from a mixer that does not include a high speed agitator unit, and moreover, that any of a wide variety of conventional mixers can be used satisfactorily, particularly the types used for combining cement, aggregate and water to produce batches of concrete.

[0075] It has been observed that after the first use cycle, the agitator blade assembly will often become coated in hydrated dust to such an extent as to form in effect a solid, rotating lump in which the blades can no longer be discerned.

[0076] When the mixer is then used to produce a further batch of carbonatated material, the condition of the agitator is observed to have little or no effect on the quality of the material produced.

[0077] Surprisingly, in tests, it was found that when the high speed agitator failed, this had little effect on the process, and nucleation and pelletisation was unimpaired.

[0078] It is believed that this is due at least in part to the seed particles formed in the nucleation phase P4 which effectively break down any remaining dry lumps of dust in the mixture, even where no high speed agitator is provided, and even where the fluent body 101 consists entirely of dust particles 102' without any coarse fraction as commonly used in prior art processes.

[0079] Since the agitator requires a powerful motor, both capital and running costs can thus be reduced by simply dispensing with the agitator.

[0080] It is found that mixers that move the rotor surface 31 in a constant direction of rotation about a fixed axis can provide effective nucleation and pelletisation. The fixed axis X31 may be a fixed vertical axis, as shown.

[0081] Each batch 101' may include around 750kg or more of particulate material, so the vessel may have a capacity of about 1500 litres. A rotating vessel of this size will typically tilt in order todischarge the batch, which adds significant complexity and cost. Therefore it is preferred to employ a moving rotor surface in a static vessel, as illustrated.

[0082] The interior surface 21 of the vessel may be a surface of revolution about the rotation axis X31, as illustrated, which is simple and effective for nucleation and pelletisation.

[0083] In the illustrated example, shown schematically, the rotor 30 includes multiple blades 31', only some of which are shown, each defining a respective rotor surface 31, mounted on a central hub 33 that rotates about a fixed vertical axis X31 in a static vessel 20 with a cylindrical interior wall 21. The blades 31' are spaced apart angularly around the axis X31. Each blade 31' extends downwardly from the distal end of a respective shaft 32 that extends radially from the hub 33. Each blade 31' may have a scraper portion 34 at its lower end near the base of the vessel 20. Each radial shaft 32 is rotatable about its respective length axis relative to the hub 33, and is biased to a rest position (as illustrated) by a spring within the hub 33. In use, the torque reaction of the mixture 100 deflects the blade 31' and so rotates the radial shaft 32 against the restoring force of its spring (rotation R32), lifting the scraper portion 34 as the blade moves through the mixture 100. The blades 31' are arranged at different radial distances from the rotor axis X31' so that they sweep the whole volume of the vessel 20 as the rotor 30 rotates.

[0084] Mixers of the general type illustrated are available from Sicoma S.r.l. of Ponte Valleceppi, Perugia, Italy.

[0085] The fluent body 101 may be admitted through an inlet 25 at the top or side of the vessel, e.g. from a supply conveyor 26. The inlet 25 may be sealed by an inlet door (not shown) to contain the gas G within the vessel.

[0086] The vessel 20 may have a discharge door 22, e.g. in the base of the vessel as shown or in the sidewall, that is selectively opened and closed to discharge the mixture 100, e.g. onto a discharge conveyor 24. The door may be operated by a door actuator 23 controlled by the control system 10.

[0087] The gas may be introduced via a gas inlet 74 and exhausted via a gas outlet 74. The vessel 20 may be substantially fluidly sealed from the ambient environment during at least the carbonatation phases of the process, except for the gas and water inlets, and openable before or during the initial period Pla to introduce the fluent body 101 via the inlet 25, and after the process to discharge the nucleated or pelletised mixture 100 via the discharge door 22. The discharged mixture may be directed to an end use (e.g. to make building blocks) or may be discharged for further pelletisation to an external pelletiser of known type, e.g .a drum or pan type pelletiser.The sensing means

[0088] The sensing means 51 is arranged to sense a viscosity of the mixture 100 within the vessel 20, and to generate viscosity data 81 as a time series representing the sensed viscosity of the mixture 100 over time, and the control system 10 is arranged to receive the viscosity data from the sensing means 51.

[0089] The sensing means can be any sensor or sensing arrangement that generates a signal indicative of the viscosity of the mixture. The sensing means may include a contact part in contact with the mixture that moves relative to the mixture 100, and an sensor that measures (either directly or indirectly) a force between the contact part and the mixture, e.g. as a torque reaction or as applied power or speed or deflection or any other measurable parameter.

[0090] The sensing means 51 may be arranged to sense variations in power supplied to the actuator 40, wherein the power is arranged to vary responsive to a varying torque reaction of the mixture 100 at the rotor surface 31, and so represents the viscosity of the mixture 100. In the illustrated embodiment, the sensing means 51 senses the current I flowing to the actuator 40, represented on the Y axis in Fig. 1 over time t on a scale from 0 (zero) to 1 (maximum).

[0091] To ensure that the current I is a faithful analogue of the viscosity of the mixture, the control system 10 may be arranged to supply power (or in accordance with the method, power may be supplied) to the actuator 40 to operate the actuator 40 to drive the rotor surface 31 in rotation at a substantially constant speed A2 during at least a part of the process.

[0092] This arrangement is illustrated in Figs. 1 and 2, wherein the actuator 40 is an electric motor and the actuator speed A(s) is plotted over time t. Voltage is constant, and so current I varies with viscosity to maintain constant speed. Of course, other parameters could be monitored depending on the motor control arrangement.

[0093] It should be noted that in the example of Fig. 1, actuator speed A(s) was reduced at the beginning of the second time period P5b of the fifth, pelletisation phase. The sudden drop in actuator current I between the first and second time periods P5a and P5b of the pelletisation phase reflects the reduction in actuator speed A(s) rather than an reduction in viscosity. Moving average viscosity traces V5a' and V5b' thus indicate approximately constant viscosity through the pelletisation phase P5, further discussed below.

[0094] In alternative arrangements, the sensing means could be separate from the actuator or motor that drives the rotor. For example, the sensing means could be arranged to sense angular deflection of the blade shaft 32 of one or more of the rotor blades 31'.

[0095] Water flow WThe water flow control means 60 is operable by the control system 10 to admit water W into the vessel to form a mixture 100 with the fluent body 101.

[0096] The water flow control means may be any arrangement for controllably starting and stopping or increasing and reducing a flow of water, such as a water pump that can be turned on or off, or (as illustrated) a valve operable by the control system 10 to admit water W from a pressurised water supply, e.g. a water main or a tank.

[0097] In the illustrated example, the water is admitted via the valve 60 to an array of jets or sprinklers 61 inside the vessel. In practice, the jets or sprinklers 61 can be used also to clean the vessel after operation, e.g. on plant shutdown.

[0098] Gas flow G

[0099] The gas flow control means 70 is operable by the control system 10 to control a flow of the gas G into the vessel 20 at a gas flow rate G2, G3.

[0100] The gas flow control means may be any arrangement for controllably starting and stopping or increasing and reducing a flow of gas, such as a pump or a valve or moveable baffle or deflector arrangement.

[0101] The gas G may be stored, for example in a pressurised tank, and released selectively into the vessel via a valve controlled by the control system 10. The vessel may be configured to contain the gas at atmospheric pressure or slightly above or below atmospheric pressure, and to replenish the gas from the tank to maintain a constant pressure in the vessel as the gas G reacts with the mixture 100.

[0102] In many applications however, the gas flow control means 70 is configured to control the flow of gas G so that it flows through the vessel 20, where some or all of the carbon compounds in the gas are captured by reaction with the fluent body, with the remaining fraction of the gas flowing out of the vessel again.

[0103] This latter arrangement is illustrated in Fig. 2 and makes it possible to draw the flow of gas G directly from an upstream process such as a combustion process. The flow of gas G may contain carbon dioxide along with other gases, combustion products and / or entrained particles.

[0104] The gas flow control means may include a valve or baffle arrangement for selectively directing the flow of gas from the upstream process through the vessel or through a bypass duct (not shown) to bypass the vessel.

[0105] Alternatively, as illustrated, the gas flow control means 70 may include a pump or impeller, e.g. a fan 71 driven by a fan motor 72 as shown, to urge the gas flow G through the vessel. Thespeed of the fan can be controlled by the control system 10 to control the flow of gas G through the vessel.

[0106] The fan may be arranged to exhaust the gas G out of the vessel via outlet 74, causing gas G to be drawn in through inlet 73 and thus creating a slight underpressure in the vessel 20 relative to ambient atmospheric pressure, so that the gas G cannot escape from the vessel 20 in case a leak should develop.

[0107] This is particularly suitable for operation in an enclosed area, such as where the apparatus is arranged in an ISO shipping container or the like for turnkey operation. The container can be simply delivered and placed on site close to the upstream process facility with a fluid connection between the vessel within the container and the upstream process gas ducts. The particulate feedstock is delivered to the container, and the pelletised mixture is removed, e.g. by truck or conveyor, providing a convenient, self-contained solution for carbon capture and conversion of waste dust into useful product.

[0108] The carbonic gas

[0109] The carbonic gas G may be any gas containing carbon in a form that can react with the fluent body. It may consist of carbon dioxide or a mixture of carbon dioxide with one or more other gases, typically nitrogen, nitrogen oxides, carbon monoxide and / or other combustion products. The carbonic gas typically contains more than 10%, more typically more than 50% but less than 100% CO2, e.g. up to about 75% CO2 by volume.

[0110] The fluent body

[0111] The fluent body 101 consists of solid particles 102, at least some of which are dust particles 102'.

[0112] By a solid particle is meant a particle of solid material, without limitation as to the shape of the particle; dust particles may have any morphology including, for example, microspheres as commonly found in fly ash.

[0113] Advantageously, the dust particles 102' may form at least 40%, 50%, 60%, 70%, 80%, 90% or 95%, or even up to 100% by weight of the solid particles 102 of the fluent body 101. Preferably the dust particles 102' may form more than 50% by weight of the solid particles 102. In this way the novel process may be used to convert waste dusts into a useful aggregate without, or with relatively little, addition of larger particulates such as sand or powdered minerals, which have been necessary in some prior art processes.Optionally however, the solid particles may include a proportion of non-dust particles, such as sand or powdered minerals, for example, where it is desired to produce a final aggregate product that includes those other materials. The non-dust particles may form any desired proportion of the fluent body by weight, which may be a minor proportion, for example, less than 50%, 40%, 30%, 20%, 10%, or 5% by weight.

[0114] The dust

[0115] In this specification, a dust means a powder having a particle size small enough to be entrained in a waste gas stream from which the dust is extracted. Typically the dust particles 102' have a maximum diameter substantially less than 1mm, such as about 300 microns or less, often about 100 microns or less, down to as small as a few tens of microns or even 1 micron or less. The surface area of the dust particles 102' will vary with particle size and shape, which in turn depends on how they are produced.

[0116] The reactivity of the dust particles 102' will vary with their surface area and chemical composition. The chemical composition is often highly variable, even between different batches of dust from the same source, depending for example on changing feedstock and process conditions.

[0117] The dust may be extracted from a flue gas generated during an upstream industrial process such as incineration or calcination of a feedstock. The dust may be a fly ash, which is to say, an ash that is entrained in flue gas.

[0118] Dusts such as APCR, CKD and CBD may be highly alkaline and typically have a small particle size and high surface area, resulting in a relatively low bulk density, often less than about 1000kg / mA3, for example, around 500 - 750 kg / mA3.

[0119] Nucleation and pelletisation

[0120] In operation, the apparatus mixes the dust and water to form a hydrated mixture 100, and further mixes that hydrated mixture with the gas flow G to carbonatate the mixture. The mixing action has the additional effect of forming the resulting carbonatated mixture into seed particles 103, typically of about 1mm - 2mm diameter. These seed particles 103 produce a fluent mixture that can be used for a variety of useful purposes, typically as a bulk building material, and optionally may be further pelletised to form larger pellets 104 having a diameter of several millimetres up to one or two centimetres or more. The larger pellets 104 can be used as an aggregate, for example, for producing building blocks, or for concrete. This further pelletisation can be achieved by further mixing in the mixer, or by discharging the mixture of seed particles to aseparate pelletiser. In each case the seed particles agglomerate together to form larger, discrete pellets of a more or less uniform size range.

[0121] Typically the solid particles 102 will contain calcium or magnesium silicates or oxides which react with carbon dioxide to form calcium carbonate. The formation of calcium carbonate reduces the pH of the system, stabilises many heavy metals contained in the residue and, during nucleation, also binds the grains together producing a hardened product within minutes.

[0122] Advantageously, the fluent body need not include cement or sand as often used as a binder and filler, respectively, in prior art processes that convert a waste feedstock into an aggregate.

[0123] The changing viscosity of the mixture that defines the phases of the process reflects the chemical and physical changes that occur in the mixture as the reactive constituents in the solid particles are hydrated and then react with the carbonic gas. The complex and interrelated chemical transformations will proceed, some sequentially and some simultaneously, at a rate that depends on temperature and free water availability and the exposed surface area of the particles, which in turn depends on the free moisture content and the extent to which the dust particles have agglomerated. Agglomeration reduces exposed surface area and so slows carbonatation. A greater or lesser amount of free water can lubricate the particles, reducing the viscosity of the mixture, or cause the dust to become sticky and so increase the viscosity of the mixture, depending also on particle size which increases through the process. The reactivity of the dust together with particle size will determine the exotherm which, together with the thickness of the water film, in turn determines the rate at which free water is driven off as steam. Carbonatation converts a sticky dust into harder particles and also cements particles together to form seed particles. Further carbonatation after initial nucleation agglomerates the cemented seed particles to form pellets, reducing the viscosity of the mixture. Seed particles or pellets coated with a free water film will entrain unreacted dust and so become sticky, again increasing the viscosity of the mixture until the unreacted material is hardened by carbonatation. The availability of unreacted dust at each time point in the process will reflect the reactivity of the particles which varies within each batch from one particle to another.

[0124] Variable feedstock

[0125] Where successive batches of the feedstock (i.e. the solid particles 102 or dust particles 102' that make up the fluent body) have substantially the same chemical composition, hence the same reactivity, the process can be controlled by a defined routine that may be stored in the memory 14 of the control system 10.However, a further challenge arises in that, for many commercial applications, the feedstock is highly variable. For such applications, the process can be adapted to the feedstock by various techniques of adaptive process control that manage the complexly interrelated process parameter discussed above, as further discussed below.

[0126] It is found that the reactivity of the particles 102 (particularly dust particles 102') depends principally on their chemical composition (mineralogy). The reactive constituents of the particles 102 may include, for example, any or all of: Lime, Larnite, Calcite, Sylvite, Portlandite, Mummeite, and Gehlenite. These seven constituents may be selected as the target constituents of the chemical analysis, as in the illustrated examples, although a more limited selection could be made. Generally the most significant constituent is lime.

[0127] Non-reactive constituents may include, for example: Anhydrite, Brownmillerite, Corundum, Periclase, Quartz, and amorphous content.

[0128] In the illustrated examples, adaptive process control was based on the balance of the seven key constituents listed above as determined by chemical analysis of samples. This can be done by X-ray diffraction or any other desired method.

[0129] The novel process can be adapted to control also for other characteristics of the solid particles which will also affect the process. However, where the feedstock is drawn from the same upstream source and tends to have the same particle morphology, these other characteristics may be assumed to be fairly constant. They may include:

[0130] Grain attributes (size distribution, surface area and shape)

[0131] Density attributes (loose, tapped, particle)

[0132] Chloride content

[0133] CO2 reactivity

[0134] By way of example, Fig. 4 shows the proportion, as a percentage (wt%) of the total weight of each sample (S#), of each of the seven target reactive constituents in each of about 85 consecutive numbered samples of dust. The samples were taken from consecutive deliveries of dust from a single commercial upstream process, and are numbered in sequence corresponding to the sequence of the deliveries, and the data was obtained by testing each sample by X-ray diffraction. The seven target constituents are indicated as follows:

[0135] (i) Lime

[0136] (ii) Larnite

[0137] (iii) Calcite

[0138] (iv) Sylvite

[0139] (v) Portlandite(vi) Mummeite (present in few samples)

[0140] (vii) Gehlenite (present in few samples)

[0141] It can be seen that the composition is highly variable from one delivery to another.

[0142] Fig. 5 is another illustration of the data presented in Fig. 4 for sample numbers (S#) 64, 68, 73, and 83 respectively, showing the proportions of the respective target constituents with the remaining sector indicating other constituents.

[0143] Even where the feedstock to the process is a dust that is generated as a waste product by a single upstream process plant (e.g. a cement manufacturing plant), the initial or upstream feedstocks to the upstream process will often vary (e.g. when derived from different sources, or when derived from a source that is itself variable, such as quarried material that comes from different rock strata, or municipal waste used as a fuel and having an unpredictable composition.) The upstream process conditions can also vary, for example, reflecting changes in the status or throughput of the plant, or periodic operations such as the addition of lime dust to control contaminants in the various other upstream feedstocks.

[0144] Hence, the waste product of the upstream process, which becomes the feedstock of the novel apparatus, may be highly variable. However, that variation will generally be within an envelope that is predictable; for example, the feedstock will generally contain the same basic chemical constituents in proportions that vary within broadly known limits, with occasional outlying compositions reflecting exceptional upstream process conditions such as plant shutdowns and restarts.

[0145] The chemical transformations that occur during the novel process are complex and are sensitively dependent on the chemical composition of the feedstock. Hence, a variable feedstock results in highly variable behaviour during the process. In particular, the reactivity of the feedstock varies very widely with chemical composition, to the extent that of two different batches of feedstock, even from the same upstream process, one batch can require nearly 200% of the quantity of water required by the other batch for complete carbonatation. Typically a 750kg batch of dry dust can require anything from 350I to 600I of water to fully carbonatate and agglomerate, absorbing up to about 10wt% or 75kg CO2 during the process.

[0146] The problem is compounded by the practicalities of storing and transporting the pulverulent feedstock. For example, a large volume of dust can be transported by lorry and stored in a silo 110 (Fig. 10), holding, say, around 15 tonnes of dust. Each batch of feedstock (say around 750kg) is then removed from the bottom of the silo and admitted to the vessel 20. The silo 110 will be filled from the top by successive deliveries of dust. Each lorry load may have a slightly different composition, reflecting variations in the upstream process. The dust may also vary incomposition through the volume of a single load. Thus, the silo will contain dust that varies in composition, and the dust will be stratified through the height of the silo. Typically the silo will be cylindrical with a conical base, and the dust will flow out of the silo via an outlet located at the lowest point. Since the fastest flow is in the centre of the silo, the boundaries between adjacent strata will curve down progressively towards the outlet as each batch of dust is withdrawn from the silo. So, each batch drawn from the silo may contain a mixture of two or more batches of dust as delivered to the silo, in variable proportions depending on their position in the silo at the time the subject batch is withdrawn; each of which, in turn, may include portions of different compositions.

[0147] Surprisingly, it is found that even this level of complexity can be managed very successfully to optimise the process by adaptive process control based on an Al model that is trained on data reflecting the process conditions, as further discussed below.

[0148] The process

[0149] The control system 10 is arranged to supply power to the actuator 40, and to operate the water and gas flow control means 60, 70, to process each batch in accordance with the process, during which dust particles 102' are agglomerated to form seed particles 103 and then, optionally, further agglomerated to form yet larger pellets 104, as illustrated in Fig. 3.

[0150] An example of the process is illustrated in Fig. 1, which shows an approximation of the viscosity data typically captured during the process when carried out in the apparatus, which may be configured as shown in Fig. 2.

[0151] Fig. 1 shows four traces A (actuator), G (gas), W (water), and I (actuator current, representing viscosity data), all on a common time scale t.

[0152] Trace A represents the actuator speed A(s) over time t on a scale from 0 (actuator stopped) through Al (medium speed) to A2 (maximum speed).

[0153] Trace G represents the gas flow rate G(f) over time t, on a scale from G1 (first, minimum or zero flow rate) through G2 (second, medium flow rate) to G3 (third, maximum flow rate).

[0154] Trace W represents the flow of water W(f) over time t on a scale from 0 (zero flow) to 1 (maximum flow). Generally the volume of water admitted to the vessel is controlled by the duration (time t) of each water addition rather than the flow rate, but the flow rate can be varied as convenient to suit the control and water inlet arrangement.

[0155] The actuator motor current I is shown over time t on a scale from 0 (zero) to 1 (maximum) on the Y-axis at the bottom of the figure, and represents the viscosity of the mixture 100 (with the caveat noted above regarding the step change in actuator speed).The process includes mixing the fluent body 101 with water W, in the vessel 20, to form a mixture 100; providing a flow of the gas G into the vessel 20 at a gas flow rate G2, G3; and sensing a viscosity of the mixture 100 within the vessel 20 to generate viscosity data as a time series representing the sensed viscosity of the mixture 100 over time.

[0156] For each respective batch 101', the process defines four distinct sequential phases Pl, P2, P3, P4, as illustrated in the example of Fig. 1.

[0157] The first, hydration phase Pl includes an initial mixing period Pla, and is followed by a second, hydration and carbonatation phase P2, which is followed by a third, carbonatation phase P3 having a third phase duration P3', which is followed by a fourth, nucleation phase P4.

[0158] The process is controlled as described herein to carefully manage the staged addition of water in accordance with the phases of the process, as defined by the sensed viscosity of the mixture which changes in accordance with the same general sequential schema in each successful iteration of the process (which is to say, in the same general way for most batches 101').

[0159] It is found that when the process is controlled in this way, the reactivity of a typical waste feedstock is sufficient to convert the entire fluent body into an aggregate (during the nucleation and pelletisation phases of the process) even without the use of prior art binders or fillers.

[0160] Although not bound by theory, this is believed to be due to the maintenance of a thin film of free water on the surface of the particles, which is sufficient to promote the carbonatation reaction with the carbonic gas while not so much as to form a slurry which has the opposite effect, excluding gas from the surface of the particles.

[0161] The challenge is to avoid both an insufficiency of free water (due to evaporation by the exotherm of the reaction) and a superfluity of free water. This is achieved by monitoring the viscosity profile of the mixture to identify each of the defined phases of the process, and managing the addition of water to maintain this optimal state through the later phases of the process.

[0162] For comparison, in Fig. 1, traces F4 and F5 (in broken lines) illustrate a typical example trace of actuator current I for a failed batch, in which the batch viscosity departs markedly from the predicted viscosity profile V4, V5 respectively. This can occur when the water additions result in a mixture that is too dry or too wet, due to a chemical composition that lies outside the expected range. The control system 10 may be arranged to terminate the process when a failed batch is identified.

[0163] The viscosity profile : moving averageAlthough in the illustrated example the approximated typical viscosity data trace exhibits a generally smooth profile, in practice the trace may show fluctuations which however follow a moving average that approximates the trace as shown in Fig. 1. This can be seen in the example viscosity data sets of Fig. 8.

[0164] Thus, in this specification, each of the first, second, third and fourth viscosity profiles VI, V2, V3, V4 may be defined as a moving average of the viscosity data over the respective phase of the process.

[0165] It is found that the fifth viscosity profile V5a, V5b exhibits typically a more marked fluctuation, as shown, for which reason it is also defined by its moving average V5a', V5b' as further discussed below.

[0166] In each case, the moving average may be a simple moving average.

[0167] The first, hydration phase Pl

[0168] During the first, hydration phase Pl, both the fluent body 101 and a first volume of water W1 are introduced into the vessel 20.

[0169] The gas flow rate G(f) is limited for the initial mixing period Pla to not more than a first gas flow rate value Gl.

[0170] The rotor surface(s) 31 is(are) driven in rotation, to mix the fluent body 101 and the water W to form the mixture 100. In the apparatus, this is accomplished by operation of the actuator 40.

[0171] The first volume of water W1 may be a fixed volume, which is to say, it is predefined and does not vary from batch to batch. This provides repeatable process conditions for each batch 101' so that the first viscosity profile VI varies only with the composition of the fluent body 101. The first volume W1 may be for example about 701 for a dry fluent body 101 of 750kg.

[0172] The first gas flow rate value Gl may be zero, i.e. no gas flows through the vessel during the initial mixing period Pla, as in the illustrated example. Alternatively it may be a relatively low flow rate, for example, if the fan 71 operates at an idle speed or if the baffle or gas flow valve is imperfectly sealed.

[0173] It is found that irrespective of the design of the rotor, entrainment of the dust particles 102' into the flow of gas G exhausted from the vessel 20 is substantially prevented by limiting the first gas flow rate value Gl to a low or zero value during the initial mixing period Pla while the dry dust is wetted down. Optionally thereafter, the gas flow rate may be increased first to an intermediate value G2 before further increasing to the maximum value G3, which further avoids dust entrainment in case dry lumps remain.When the first volume of water W1 is mixed with the fluent body 101, the solid particles 102 stick together, increasing viscosity, and undergo an exothermic hydration reaction.

[0174] As shown in Fig. 1, the viscosity of the mixture 100 defines, over time, a first viscosity profile VI, which defines a progressive increase in viscosity. The viscosity of the mixture defines a first viscosity peak value Vvl following this progressive increase in viscosity of the first viscosity profile VI.

[0175] During hydration the temperature of the mixture increases to warm to very hot, depending on the reactivity of the material. Typically the heat of the hydration reaction will be sufficient to drive off the free water film as steam.

[0176] The first, hydration phase Pl may last a few minutes, for example, about four minutes (or shorter or longer to suit the general type of feedstock), and the duration of the remaining phases may be in approximately the relative proportions shown in Fig.l (depending of course on the process parameter values).

[0177] Increased gas flow

[0178] At some time after the initial mixing period Pla, and preferably at or shortly after the beginning of the second phase P2 as illustrated, the gas flow rate is increased to a second gas flow rate value G2, higher than the first gas flow rate value Gl.

[0179] Where the first gas flow rate Gl is zero, the second gas flow rate value G2 may represent starting the fan 71 at low speed. This introduces the gas G into the vessel. The carbonatation reaction begins as the hydrated particles 102 react with the gas G.

[0180] The second, hydration and carbonatation phase P2

[0181] During the second, hydration and carbonatation phase P2, a second volume of water W2 is introduced into the vessel 20, and the rotor surface 31 is driven in rotation, to mix the fluent body 101 with the second volume of water W2. In the apparatus, this is accomplished by operation of the actuator 40.

[0182] The second, hydration and carbonatation phase P2 may begin when the viscosity reaches its first viscosity peak value Vvl.

[0183] The calculated second water volume W2 may be added as quickly as possible as the viscosity begins to fall after the end of the first, hydration phase Pl.

[0184] Thus, the control system 10 may be arranged to operate the water flow control means 60 to introduce the second volume of water W2 into the vessel 20 at a beginning of the second,hydration and carbonatation phase P2 (and so before the viscosity of the mixture 100 reaches the reduced viscosity value Vv2.)

[0185] The gas flow G may be started or increased to its second gas flow rate value G2 at the same time as the second water volume W2 is added, so that the gas G reacts with the hydrated particles 102 to form carbonates. The exothermic hydration reaction continues for those particles 102 that are not yet fully hydrated.

[0186] The second water volume W2 may be calculated to be sufficient to maintain the water film around the hot particles while it is driven off as steam by the continuing, typically strongly exothermic hydration reaction, without being so much as to form a slurry.

[0187] The control system 10 may be arranged to operate the water flow control means 60 to introduce the second volume of water W2 into the vessel 20, during the second, hydration and carbonatation phase P2, responsive to sensing a reduction in a rate of the progressive increase in viscosity of the first viscosity profile VI, or responsive to sensing the first viscosity peak value Vvl, or responsive to sensing the decrease in viscosity from the first viscosity peak value Vvl.

[0188] The viscosity of the mixture 100 defines, over time, a second viscosity profile V2, which defines a progressive decrease in viscosity to a reduced viscosity value Vv2, lower than the first viscosity peak value Vvl.

[0189] The viscosity (torque reaction) may fall as the second water volume W2 is driven off as steam.

[0190] When the fluent body 101 is substantially fully hydrated, the exothermic reaction slows and the temperature stabilises, leaving the particles 102 coated with a water film. The viscosity (torque reaction) now stabilises to a relatively constant value, marking the beginning of the third, carbonatation phase P3.

[0191] The third, carbonatation phase P3

[0192] During the third, carbonatation phase P3, the rotor surface 31 is driven in rotation, to expose fresh surfaces of the mixture 100 for reaction with the gas G. In the apparatus, this is accomplished by operation of the actuator 40.

[0193] The viscosity of the mixture 100 defines, over time, a third viscosity profile V3 having a smaller rate of change than each of the first viscosity profile VI and the second viscosity profile V2.

[0194] The third, carbonatation phase P3 may start when the viscosity profile reaches a constant value.The hydration reaction may continue into the third, carbonatation phase P3 for any remaining particles that were not fully hydrated in the first and second phases, but with a much weaker exotherm.

[0195] For most batches 101' it is found that most of the carbonatation will occur in the third phase P3, but it is found that the viscosity remains at a constant value for as long as the third phase P3 lasts.

[0196] The free moisture content tends to vary depending on the strength of the ongoing hydration reaction, which depends mainly on the reactivity of the particles 102. This in turn reflects the chemistry of the particles 102 and their surface area.

[0197] In order to maintain the optimal water film around the particles 102, adaptive process control may be used to determine one or two supplementary volumes of water (Wsl, Ws2) to be added, each each at a respective time point, as further discussed below. Since there is little or no change in viscosity to indicate the status of the reaction, this determination may be made based on the first viscosity profile VI.

[0198] The Wsl time point may be at 50% of the time from the beginning of the second phase P2 to the end of the third phase P3. The Ws2 time point may be at 75% of the time from the beginning of the second phase P2 to the end of the third phase P3.

[0199] Adaptive process control may also be used to determine the third phase duration P3', which also may be based on the first viscosity profile VI.

[0200] The third phase P3 ends when the fourth, nucleation phase P4 is initiated by adding the third volume of water W3.

[0201] The fourth, nucleation phase P4

[0202] After the third phase duration P3', the third, carbonatation phase P3 is terminated, and the fourth, nucleation phase P4 is initiated, by introducing, into the vessel 20, a third volume of water W3. The third volume W3 may be a fixed (predefined) volume, and may be a relatively large volume, for example, about 801 for a 750kg dry fluent body.

[0203] In the apparatus, this is accomplished by operation of the water flow control means 60 by the control system 10.

[0204] The third volume of water W3 is selected to cause a progressive agglomeration of the dust particles 102' to form seed particles 103 during the fourth, nucleation phase P4.

[0205] During the fourth, nucleation phase P4, the rotor surface 31 is driven in rotation, to mix the fluent body 101 with the third volume of water W3. In the apparatus, this is accomplished by operation of the actuator 40.The viscosity of the mixture 100 defines, over time, a fourth viscosity profile V4, which defines a progressive increase in viscosity having a greater rate of change than the third viscosity profile V3 and corresponding to the progressive agglomeration of the dust particles 102' to form seed particles 103 (Fig. 3).

[0206] The control system 10 may be arranged to increase the gas flow rate, at or near a beginning of the fourth, nucleation phase P4, to a third gas flow rate value G3, higher than the second gas flow rate value G2.

[0207] Adaptive process control may be used to make a determination to add one or more, e.g. up to five additional volume of water Wai, Wa2, Wa3, Wa4, Wa5, as further discussed below.

[0208] The determination may be based on the fourth viscosity profile V4, and may be calculated from the gradient and rate of change of the fourth viscosity profile V4. This maintains the optimal water film around the particles.

[0209] The control system 10 may be arranged to terminate the fourth, nucleation phase P4 by discharging the mixture 100 from the vessel 20.

[0210] Alternatively, the process may continue in a fifth, pelletisation phase P5.

[0211] The fifth, pelletisation phase

[0212] The fourth viscosity profile V4 may define a progressive increase in viscosity to a second viscosity peak value Vv3, higher than the first viscosity peak value Vvl, and the control system 10 may be arranged to supply power to the actuator 40, and to operate the water and gas flow control means 60, 70, to define, following the fourth, nucleation phase P4, a fifth, pelletisation phase P5.

[0213] During the fifth, pelletisation phase P5, the actuator 40 is operated to drive the rotor surface 31 in rotation, to cause a further, progressive agglomeration of the particles 102 to form pellets 104 (Fig. 3) which are generally spheroidal and larger than the seed particles 103 and increase progressively in size.

[0214] The viscosity of the mixture 100 defines, over time, a fifth viscosity profile V5a, V5b, wherein a moving average V5a', V5b' of the fifth viscosity profile V5a, V5b has a smaller rate of change than the fourth viscosity profile V4.

[0215] Optionally, during the fifth, pelletisation phase P5, the control system 10 may be arranged to operate the actuator 40 at a first period speed or power A2 for a first time period P5a, and then, after the first time period P5a, at a second period speed or power Al, lower than the first period speed or power A2, for a second time period P5b. This provides more economical operation and is the reason for the step change in actuator current I between the two parts of thefifth viscosity profile V5a, V5b. This step change in actuator current I does not indicate any step change in viscosity, but on the contrary, indicates relatively constant viscosity V5a, V5b when actuator speed A(s) is taken into account.

[0216] The control system 10 may be arranged to operate the gas flow control means 70 to maintain a flow of the gas G into the vessel 20 to react with the mixture 100 during the fifth, pelletisation phase P5. This makes it possible for carbonatation to continue (or even for most carbonatation to occur) during the fifth, pelletisation phase, P5, which suits certain types of feedstock and optimises carbon uptake and aggregate properties.

[0217] Adaptive process control for variable feedstocks

[0218] In order to adapt the process for variable feedstocks, adaptive process control can be used to to define at least one parameter value of the process based on an indication specific to the batch 101' being processed, and then to adjust the process, for the respective batch 101', in accordance with the defined parameter value.

[0219] Adaptive process control may be carried out by a chemical kinetics control subsystem 12, or by a machine learning (artificial intelligence, Al) control subsystem 11, or by a combination of both subsystems.

[0220] The indication may be based on a chemical analysis of the batch 101' and / or on the viscosity data generated while processing the respective batch 101', particularly the first viscosity profile VI.

[0221] The first viscosity profile VI can be assessed by a machine learning (artificial intelligence, Al) model 80 trained on a data set including the sensed viscosity data from previous mixture batches processed in a corresponding (identical or equivalent) apparatus in accordance with the process, together with chemical analysis data from those same batches.

[0222]

[0223] control by a chemical kinetics control

[0224]

[0225] The control system 10 may include a chemical kinetics control subsystem 12 including an algorithm based on a set of equations representing chemical reactions occurring within the mixture 100 during the process.

[0226] The chemical kinetics control subsystem 12 is arranged to receive an indication of a chemical composition of each batch 101', and then, based on the indication, to define at least one parameter value of the process by means of the algorithm, and then to adjust the process, for the respective batch 101', in accordance with the defined parameter value.The indication could be provided as an input to the control system (e.g. via a keyboard or other input interface to the algorithm running on the processor 13). Alternatively the indication can be provided by a machine learning model 80 (also referred to herein as an artificial intelligence (Al) model) based on the sensed viscosity data of the respective batch 101'7as further discussed below.

[0227] The algorithm is built from equations reflecting the reactions of the principal reactive constituents of the feedstock during carbonatation, which are well known in the art.

[0228] By way of example, the carbonatation of lime (CaO) into calcium carbonate (CaCO3) via calcium hydroxide as an intermediate product can be represented by the following balance equations:

[0229]

[0230] The equations of the algorithm are designed to calculate the molar masses of the reactants including water, based on the balance equations and the tested or inferred proportion of lime in the fluent body 101, and the required volume of water can then be added through the process as a defined parameter value determined by the equations. The quantity of CO2 captured during the reaction can also be calculated as a parameter value that changes over time, and that value can be used, for example, to define the duration of one or more phases of the process.

[0231] For example, the balance equations would indicate the following molar masses for the hydration of lime in a 750kg dry fluent body containing 16wt% lime:

[0232]

[0233] Given CaO + H20 -> Ca(OH)2:

[0234] CaO moles = 120,000 g of CaO / 18.02 g / mol of H2O ~ 2140 moles A 1:1 molar ratio between CaO and H2O is shown, hence:

[0235] H2O moles required = CaO moles ~ 2140 moles

[0236] H2O required = H2O moles required x H2O molar mass

[0237] = 2140 moles x 18.02 g / moles

[0238] = 38.56 Kgl ' l

[0239] Hence, 38.56 litres of water is required to fully hydrate 120 kg of lime.

[0240] The subsequent carbonatation reaction is modelled in a similar way, and a series of differential equations are constructed to reflect the reactions occurring for the target constituents of the mixture, including the rate at which each reaction proceeds, which in turn depends inter alia on the exotherm of the reactions and relevant constants as known in the art, allowing for heat loss from the mixture. Values may be determined experimentally or measured during operation of the mixer, since many reactions are temperature dependent (and many are also exothermic) and any given mixer will have a characteristic rate of heat loss.

[0241] The final equations are necessarily complex, but can be designed based on well understood principles to reflect the selected target constituents of the mixture (which in turn reflect the selected source of the feedstock) and the thermal characteristics of the selected mixing apparatus.

[0242] By way of example, Fig. 12 illustrates the reaction of lime as defined by the equations of the algorithm over time t in seconds (s), with mass m in kilograms (kg) on the Y axis.

[0243] It can be seen that the Calcium Oxide reactant shrinks exponentially, whilst the Calcium Carbonate product grows at a given rate. The Calcium Hydroxide (intermediate

[0244] product) grows with the depletion of Calcium Oxide and shrinks with the formation of Calcium Carbonate. The reaction is temperature dependent and exothermic, as indicated by the exponential increases in temperature and then slow decline as the Calcium Oxide depletes. The temperature then begins to returns to ambient.

[0245] Fig. 13 illustrates over time t in seconds (s) the amount of carbon dioxide CO2 in kilograms (kg) on the Y axis captured during the same reaction, as indicated by the equations. The broken line indicates that the maximum limit for captured CO2 as indicated by the equations (93kg CO2 for 120kg CO) is reached at about 250 seconds, and so this value can be used to determine the third phase duration P3' for that batch.

[0246]

[0247] control based on viscosity data

[0248] The control system 10 may be arranged, while processing a respective batch 101', to define at least one parameter value of the process, based at least on the viscosity data generated while processing the respective batch 101'; and then to adjust the process, for the respective batch 101', in accordance with the defined parameter value.

[0249] In a particularly preferred approach, the control system 10 may be arranged, while processing a respective batch 101', after the first, hydration phase Pl, to define at least one parameter value of the process, based on the first viscosity profile VI of the respective batch 101'obtained during the first, hydration phase Pl; and then, after the first, hydration phase Pl, to adjust the process, for the respective batch 101', in accordance with the defined parameter value.

[0250] This approach can be implemented by a machine learning subsystem 11 which will now be discussed.

[0251] The machine learning control subsystem

[0252] The control system 10 may include a machine learning control subsystem 11 which includes a machine learning model 80. The machine learning model 80 is arranged to generate, based on the first viscosity profile VI of the respective batch 101', inferred characteristics of the respective batch 101'. The defined parameter value is based on the inferred characteristics.

[0253] As illustrated in Fig. 10, the machine learning model 80 may be based on a training data set including the viscosity data 81 or averaged viscosity data 81 generated by processing, with an instance of the apparatus, each of a plurality of the batches 101' in accordance with the process.

[0254] The inferred characteristics may represent a chemical composition of the respective batch 101'. The chemical composition may be expressed for example as a proportion (e.g. a weight percentage) of each of the seven target constituents (i) - (vii) as discussed above.

[0255] The control system 10 may also include a chemical kinetics control subsystem 12 including an algorithm based on a set of equations representing chemical reactions occurring within the mixture 100 during the process. The chemical kinetics control subsystem 12 is arranged to receive the inferred characteristics from the machine learning control subsystem 11, and then to define the parameter value based on the inferred characteristics.

[0256] The machine learning model 80 may be based on a training data set 81, 82 including the viscosity data 81 or averaged viscosity data 81 generated by processing, with an instance of the apparatus, each of a plurality of the batches 101' in accordance with the process; and, for each respective one of the plurality of batches 101', or for each respective one of a plurality of groups 101" of batches of the plurality of batches 101', a chemical composition analysis 82 representative of that respective one or group 101" of the plurality of batches 101'.

[0257] In-batch adaptive process control

[0258] In addition to any of the adaptive process control arrangements based on the first viscosity profile VI as described above, the control system 10 may be arranged to further adjust the process for the respective batch, while processing the respective batch 101', based at least on the viscosity data generated, subsequent to the first, hydration phase Pl, while processing the respective batch 101'.This means that after setting the process parameters based on the initial viscosity profile VI, the process can be further adapted depending on how the subsequent viscosity profile develops. This allows the control system 10 to adapt in real time, during the process, to variations in the characteristics of each batch that depart from the batch profile predicted based on its initial viscosity profile VI.

[0259] The first viscosity profile VI

[0260] Defined parameter values may be calculated as discussed above, based on the following three key characteristics of the first viscosity profile VI:

[0261] (i) - the slope rate (rate of increase during the first phase Pl)

[0262] (ii) - the first viscosity peak value Vvl

[0263] (iii) - the total energy (= the area under the slope during the first phase Pl)

[0264] Some example parameter values that can be defined by adaptive process control

[0265] In the above discussion, adaptive process control is used to define at least one parameter value of the process. The parameter values defined by adaptive process control (the Defined Parameter Value(s), below) can include any or all of the following:

[0266] Defined Parameter value: the third phase duration P3'

[0267] The Defined Parameter Value may include the third phase duration P3', i.e. how long it lasts. In this way the duration of the process can be optimised for both throughput and carbon capture (carbonatation) of each batch.

[0268] Defined Parameter value: the second volume of water W2

[0269] The Defined Parameter Value may include the second volume of water W2, i.e. how much is added.

[0270] The second volume of water W2 may be calculated based on the first viscosity profile VI, particularly the three key characteristics mentioned above.

[0271] The second volume of water W2 is selected to maintain a film of water around the particles 102 of the mixture, which maintains the hydration reaction in the secondary hydration phase, while avoiding excess free water that will form a slurry, or insufficient free water which will hinder hydration and carbonatation.

[0272] A slurry is to be avoided because it hinders carbonatation and nucleation, resulting in a failed batch.Defined Parameter value: supplementary volume determination

[0273] The Defined Parameter Value may include a supplementary volume determination as to whether or not at least one supplementary volume of water Wsl, Ws2 is to be introduced into the vessel 20 during the third, carbonatation phase P3; and, responsive to a positive supplementary volume determination, during the third, carbonatation phase P3, an addition of the at least one supplementary volume of water Wsl, Ws2 into the vessel 20.

[0274] The at least one supplementary volume of water may include at least two supplementary volumes of water Wsl, Ws2 which are introduced into the vessel 20 sequentially in temporally spaced relation, i.e. with a time delay after introducing one volume and before introducing the next, as illustrated in Fig. 1.

[0275] The Defined Parameter Value may further include the or each supplementary volume of water Wsl, Ws2 (which is to say, what volume of water is added at each introduction into the vessel).

[0276] Additional volume determination

[0277] In any of the above described arrangements of adaptive process control, the control system 10 may be further arranged, while processing a respective batch 101', to make an additional volume determination, based on at least the fourth viscosity profile V4, as to whether or not at least one additional volume of water Wai, Wa2, Wa3, Wa4, Wa5 is to be introduced into the vessel 20 during the fourth, nucleation phase P4; and, responsive to a positive additional volume determination, during the fourth, nucleation phase P4, after a delay period following the introduction of the third volume of water W3, to introduce the at least one additional volume of water Wai, Wa2, Wa3, Wa4, Wa5 into the vessel 20.

[0278] The at least one additional volume of water may include at least two additional volumes of water Wai, Wa2, Wa3, Wa4, Wa5 which are introduced into the vessel 20 sequentially in temporally spaced relation (i.e. with a time gap in-between each addition and the next).

[0279] The control system (10) may be arranged to determine the or each additional volume of water Wai, Wa2, Wa3, Wa4, Wa5 (i.e. how much to add) based on at least the viscosity data generated while processing the respective batch 101'. Alternatively, each additional volume may be a fixed additional volume, which may be relatively small, e.g. about 201 for a 750kg dry fluent body.

[0280] Example viscosity data setsFig. 6 shows a real viscosity data set obtained by processing one batch 101' in the apparatus, wherein the Y axis represents the actuator motor current I in amps A, and the X axis represents the time of day t during one morning run of the apparatus while the respective batch 101' was nucleated and pelletised.

[0281] Fig. 7 shows how the viscosity data of Fig. 6 is sampled to obtain a data set comprising discrete value points (at time points to ...tn), here representing the first and second phases Pl, P2 of the process.

[0282] Fig. 8 shows four more viscosity data sets, each obtained by processing multiple batches of the material that was sampled to obtain samples S#64, S#68, S#73, and S#83, respectively. The chemical compositions obtained by testing each of the four samples by X-ray diffraction are shown in Figs. 4 and 5. For each data set in Fig. 8, the multiple traces represent the viscosity data obtained from each batch 101' of the group 101" of batches that was processed in the apparatus, and the discrete data points represent the average values of all of those viscosity data sets at each sampled time point during the first and second phases Pl, P2 of the process, the time points being numbered on the X-axis indicating time t. The varying viscosity of the mixture is indicated by variations in the sensed actuator current I on the Y-axis, which was monitored while driving the rotor in rotation at a constant speed.

[0283] The machine learning (Al) model

[0284] As can be appreciated from Fig. 4 and Fig. 8 and the foregoing discussion, the input data is noisy with outliers. The model is selected to adapt and generalize to account for irregularities in the data.

[0285] In tests it was found that an artificial neural network (ANN) regression model is suitable, although other approaches are possible. Fig. 9 shows schematically how the ANN is made up of multiple layers of interconnected artificial neurons, including an input layer, a number of intermediate or hidden layers, and an output layer. Each neuron is connected to every other neuron in the next layer.

[0286] It has been found experimentally that the model may work well when the input layer has a total of 160 data points, with four successive hidden layers prior to the single output layer, each hidden layer having half as many neurons as the previous layer. By way of example, the model may have 160 inputs interconnected to 58 neurons, which in turn are interconnected to 29 neurons, with these interconnected to 15 neurons, then interconnected to 7, and finally these are connected to a single output neuron.There are many complex and subtle relationships between the first viscosity profile VI of the batch, which provides the input data points in the first (input) layer of the model, and the respective target constituent (i) - (vii) of the inferred chemical composition of the batch which represents the output layer of the model. These relationships are not fully understood, but include the proportion of lime (i) which is believed to be the most significant determinant of the first viscosity profile VI. A low concentration of Portlandite (v) is believed to affect the rate at which the viscosity declines from the first viscosity peak value Vvl, hence the second viscosity profile V2.

[0287] Fig. 9 shows as a simplified example how sixteen discrete data point values (at time points to ...tn) taken from the viscosity data set of Fig. 7 during the first phase Pl of the process are input into the model to obtain an inferred weight percentage of each of the target constituents ((i) - (vii) wt%) in that individual batch 101'. In practice, a larger set of discrete data point values may be used. A set of 160 data points is found to work well.

[0288] Training data

[0289] Referring to Fig. 10, the machine learning (e.g. ANN) model 80 is trained with labelled data representing the viscosity and chemical composition analysis for each of a plurality of batches 101' processed in the apparatus.

[0290] For practicality, each received quantity of feedstock (e.g. each lorry load received from a given upstream source) may be sampled to provide one or more chemical composition analyses 82 before admitting it to a storage silo 110, or alternatively, samples for analysis may be taken direct from the silo. Each batch 101' is associated with one or more analyses 82.

[0291] Conveniently therefore, one chemical composition analysis 82 may be associated with a group 101" of multiple processed batches 101' of feedstock. In this case, for each respective chemical composition analysis 82, the model may be trained on the viscosity data derived from each batch 101' of the group 101" (the method that was used in the illustrated examples), or on a single viscosity data set obtained by averaging the viscosity data sets from all of the batches 101' of that group 101".

[0292] In either case, the model may be trained by identifying common characteristics of the viscosity data of each batch of a group 101" of batches 101' having the same chemical composition analysis 82. Thus, the chemical composition analysis 82 provides a starting point for determining what may be regarded as common characteristics between different viscosity data sets.

[0293] Another approach would be to identify common characteristics of the viscosity data in different viscosity data sets, based only on the viscosity data sets, and then to identifyrelationships between each identified common characteristic and the chemical composition analyses 82 associated therewith.

[0294] Irrespective of the approach taken, the model 80 may be trained by methods well known in the art, wherein each neuron accepts input data and multiplies this by a synaptic weight summed with a bias value. The result is passed to an activation function which is the output signal of the neuron. Back-propagation is used to adjust the weights and biases based on the difference between actual and estimated output.

[0295] Model accuracy

[0296] In tests, it is found that when the ANN model 80 is trained on a data set derived from material obtained from a given upstream process, the model is able to generate the inferred chemical composition of each batch derived from the same upstream process with surprisingly high accuracy and reliability.

[0297] This is the case, even where the model is trained on labelled data wherein each chemical composition analysis 82 is representative of a group 101" of batches from a common source, which vary in composition from batch to batch within the group 101". The data in Figs. 11a and lib, discussed below, was obtained from an ANN model trained in this way, which nevertheless is capable of inferring the composition of each individual batch 101' with high reliability.

[0298] It will be understood that since each group 101" of batches 101' represents a common body of particulate material 102 from a common source, and different groups 101" of batches represent different common bodies of material, or different portions of one common body of material, the variations in composition between batches 101' in a group 101" are generally smaller than the variations in composition between different groups 101".

[0299] The accuracy and reliability of the model 80 is verified in accordance with best practice in the art of Al modelling, by excluding from the training data set the test and process data from a proportion (say about 30%) of the processed material, and then comparing the inferred chemical composition for each batch of the excluded material with the test data for that respective batch. Since the assessment is carried out on batches for which the test and process data have not been previously provided for training the model, this eliminates the possibility of bias that might arise if the assessment were done using data already provided to the model in training.

[0300] Figs. 11a and lib illustrate this robust validation process, wherein each of Figs. 11a and lib shows the same set of data points obtained by X-ray diffraction testing for the proportion of lime (i) as a percentage by weight of the respective sample number S#. The data points are drawnfrom the data set of Fig. 4, but were excluded from the model training data and were used only to test the model output.

[0301] Fig. lib also shows (in a slightly lighter shade) the corresponding data points inferred by the model, based on the sensed viscosity data captured during processing each corresponding batch 101' of the tested material in accordance with the process, and superimposed onto the actual test (ground truth) data show on its own in Fig. 11a. Hence, Fig. lib shows a pair of values (lighter, inferred value; superimposed on darker, test data value) for each sample.

[0302] It can be seen that some of the paired values are identical and so exactly superimposed, while most of the rest lie close together, indicating an accuracy of approximately 85% following extensive training of the model. It is believed that the sensed viscosity data alone provides about 80% accuracy, while the remaining 5% accuracy is achieved by adjusting hyperparameters of the model such as epoch number, loss function type, activation function type and batch size.

[0303] It is believed that further improvement in accuracy may be achievable by including additional data input parameters, which may include any or all of: the first volume of water W1 added during the initial hydration phase Pl; the total volume of water added during the process; the mass of the fluent body 101 and / or the change in mass during the process; and the temperature or change in temperature of the mixture 100 during the first (hydration) phase Pl and optionally also during the second (hydration and carbonatation) phase P2, and further optionally, also during the remaining phases of the process.

[0304] In summary, embodiments provide a process and apparatus for batch carbonatation of a fluent pulverulent body (101) in four or five distinct phases (Pl, P2, P3, P4, P5) defined by the varying viscosity profile of the mixture (100), wherein the particles (102) are mixed with water (W) and a carbonic gas (G) and also agglomerated to form seed particles (103) and, optionally, larger pellets (104) within the mixing vessel (20). Process parameters may be adjusted based on the chemical composition and / or sensed viscosity profile of the batch (101'), optionally by means of a machine learning model (80).

[0305] The process in accordance with the second aspect of the invention may include any of the functions described herein as performed by the control system 10 of the apparatus of the first aspect of the invention, irrespective of how those functions are performed (whether by the control system 10 or otherwise.)

[0306] Many further adaptations are possible within the scope of the claims.In the claims, reference numerals and characters are provided in parentheses, purely for ease of reference, and should not be construed as limiting features.

Claims

CLAIMS1. An apparatus for carbonatation of a fluent body (101) of solid particles (102) by reaction with a carbonic gas (G), at least some of the solid particles (102) being dust particles (102');the apparatus being operable to process multiple batches (101') sequentially, each in accordance with a process, wherein each batch (101') is formed from a different said fluent body (101);the apparatus including:a control system (10);a vessel (20) for containing the fluent body (101);a rotor surface (31) arranged within the vessel (20) for rotation about an axis (X31); an actuator (40), operable by the control system (10) to drive the rotor surface (31) in rotation about the axis (X31);a water flow control means (60), operable by the control system (10) to admit water (W) into the vessel to form a mixture (100) with the fluent body (101);a gas flow control means (70), operable by the control system (10) to control a flow of the gas (G) into the vessel (20) at a gas flow rate (G2, G3); anda sensing means (51);wherein the sensing means (51) is arranged to sense a viscosity of the mixture (100) within the vessel (20), and to generate viscosity data (81) as a time series representing the sensed viscosity of the mixture (100) over time, and the control system (10) is arranged to receive the viscosity data from the sensing means (51);wherein the control system (10) is arranged to supply power to the actuator (40), and to operate the water and gas flow control means (60, 70), to process each batch in accordance with the process; wherein, for each batch (101'), the process includes:a first, hydration phase (Pl) including an initial mixing period (Pla); followed by a second, hydration and carbonatation phase (P2); followed bya third, carbonatation phase (P3) having a third phase duration (P31); followed by a fourth, nucleation phase (P4);wherein during the first, hydration phase (Pl):both the fluent body (101) and a first volume of water (Wl) are introduced into the vessel (20), andthe gas flow rate is limited for the initial mixing period (Pla) to not more than a first gas flow rate value (Gl), andthe actuator (40) is operated to drive the rotor surface (31) in rotation, to mix the fluent body (101) and the water (W) to form the mixture (100), andthe viscosity of the mixture (100) defines, over time, a first viscosity profile (VI), wherein the first viscosity profile (VI) defines a progressive increase in viscosity; andwherein the viscosity of the mixture defines a first viscosity peak value (Vvl) following said progressive increase in viscosity of the first viscosity profile (VI); andwherein, after the initial mixing period (Pla), the gas flow rate is increased to a second gas flow rate value (G2), higher than the first gas flow rate value (Gl); andwherein, during the second, hydration and carbonatation phase (P2):a second volume of water (W2) is introduced into the vessel (20), andthe actuator (40) is operated to drive the rotor surface (31) in rotation, to mix the fluent body (101) with the second volume of water (W2); andthe viscosity of the mixture (100) defines, over time, a second viscosity profile (V2), wherein the second viscosity profile (V2) defines a progressive decrease in viscosity to a reduced viscosity value (Vv2), lower than the first viscosity peak value (Vvl); andwherein, during the third, carbonatation phase (P3):the actuator (40) is operated to drive the rotor surface (31) in rotation, to expose fresh surfaces of the mixture (100) for reaction with the gas (G), andthe viscosity of the mixture (100) defines, over time, a third viscosity profile (V3) having a smaller rate of change than each of the first viscosity profile (VI) and the second viscosity profile (V2); and wherein the control system (10) is arranged, after the third phase duration (P31), to terminate the third, carbonatation phase (P3) and initiate the fourth, nucleation phase (P4) by operating the water flow control means (60) to introduce, into the vessel (20), a third volume of water (W3),wherein the third volume of water (W3) is selected to cause a progressive agglomeration of the dust particles (102') to form seed particles (103) during the fourth, nucleation phase (P4); and wherein, during the fourth, nucleation phase (P4):the actuator (40) is operated to drive the rotor surface (31) in rotation, to mix the fluent body (101) with the third volume of water (W3); andthe viscosity of the mixture (100) defines, over time, a fourth viscosity profile (V4), wherein the fourth viscosity profile (V4) defines a progressive increase in viscosity having a greater rate of change than the third viscosity profile (V3) and corresponding to said progressive agglomeration of the dust particles (102') to form seed particles (103).

2. An apparatus according to claim 1, wherein the control system (10) includes a chemical kinetics control subsystem (12) including an algorithm based on a set of equations representing chemical reactions occurring within the mixture (100) during the process;the chemical kinetics control subsystem (12) being arranged:to receive an indication of a chemical composition of each batch (101'), and then, based on the indication, to define at least one parameter value of the process by means of the algorithm, and thento adjust the process, for the respective batch (101'), in accordance with the defined parameter value.

3. An apparatus according to claim 1, wherein the control system (10) is arranged, while processing a respective batch (101'):to define at least one parameter value of the process, based at least on the viscosity data generated while processing the respective batch (101'); and thento adjust the process, for the respective batch (101'), in accordance with the defined parameter value.

4. An apparatus according to claim 1, wherein the control system (10) is arranged, while processing a respective batch (101'):after the first, hydration phase (Pl), to define at least one parameter value of the process, based on the first viscosity profile (VI) of the respective batch (101') obtained during the first, hydration phase (Pl); and then,after the first, hydration phase (Pl), to adjust the process, for the respective batch (101'), in accordance with the defined parameter value.

5. An apparatus according to claim 4, wherein the control system (10) includes a machine learning control subsystem (11), the machine learning control subsystem (11) including a machine learning model (80);the machine learning model (80) being arranged to generate, based on the first viscosity profile (VI) of the respective batch (101'), inferred characteristics of the respective batch (101'); andthe defined parameter value is based on the inferred characteristics.

6. An apparatus according to claim 5, wherein the machine learning model (80) is based on a training data set including the viscosity data (81) or averaged said viscosity data (81) generated by processing, with an instance of the apparatus, each of a plurality of said batches (101') in accordance with the process.

7. An apparatus according to claim 5, wherein the inferred characteristics represent a chemical composition of the respective batch (101').

8. An apparatus according to claim 7, wherein the control system (10) includes a chemical kinetics control subsystem (12) including an algorithm based on a set of equations representing chemical reactions occurring within the mixture (100) during the process;the chemical kinetics control subsystem (12) being arranged:to receive the inferred characteristics from the machine learning control subsystem (11), and thento define the parameter value based on the inferred characteristics.

9. An apparatus according to claim 7 or claim 8, wherein the machine learning model (80) is based on a training data set (81, 82) including:the viscosity data (81) or averaged said viscosity data (81) generated by processing, with an instance of the apparatus, each of a plurality of said batches (101') in accordance with the process, and,for each respective one (101') of the plurality of batches, or for each respective one of a plurality of groups (101") of batches (101') of the plurality of batches (101'), a chemical composition analysis (82) representative of that respective one (101') or group (101") of the plurality of batches (101').

10. An apparatus according to any one of claims 4 - 9, wherein the control system (10) is arranged to further adjust the process for the respective batch, while processing the respective batch (101'), based at least on the viscosity data generated, subsequent to the first, hydration phase (Pl), while processing the respective batch (101').

11. An apparatus according to any of claims 2 - 10, wherein the at least one parameter value includes the third phase duration (P31).

12. An apparatus according to any of claims 2 - 11, wherein the at least one parameter value includes the second volume of water (W2).

13. An apparatus according to claim 12, wherein the at least one parameter value includes: a supplementary volume determination as to whether or not at least one supplementary volume of water (Wsl, Ws2) is to be introduced into the vessel (20) during the third, carbonatation phase (P3); and, responsive to a positive supplementary volume determination, during the third, carbonatation phase (P3), an addition of the at least one supplementary volume of water (Wsl, Ws2) into the vessel (20).

14. An apparatus according to claim 13, wherein the at least one supplementary volume of water includes at least two supplementary volumes of water (Wsl, Ws2), the supplementary volumes of water (Wsl, Ws2) being introduced into the vessel (20) sequentially in temporally spaced relation.

15. An apparatus according to claim 14, wherein the at least one parameter value includes the or each supplementary volume of water (Wsl, Ws2).

16. An apparatus according to any of claims 2 - 15, wherein the control system (10) is arranged, while processing a respective batch (101'):to make an additional volume determination, based on at least the fourth viscosity profile (V4), as to whether or not at least one additional volume of water (Wai, Wa2, Wa3, Wa4, Wa5) is to be introduced into the vessel (20) during the fourth, nucleation phase (P4); and,responsive to a positive additional volume determination, during the fourth, nucleation phase (P4), after a delay period following the introduction of the third volume of water (W3), to introduce the at least one additional volume of water (Wai, Wa2, Wa3, Wa4, Wa5) into the vessel (20).

17. An apparatus according to claim 16, wherein the at least one additional volume of water includes at least two additional volumes of water (Wai, Wa2, Wa3, Wa4, Wa5), the additional volumes of water (Wai, Wa2, Wa3, Wa4, Wa5) being introduced into the vessel (20) sequentially in temporally spaced relation.

18. An apparatus according to claim 17, wherein the control system (10) is arranged to determine the or each additional volume of water (Wai, Wa2, Wa3, Wa4, Wa5) based on at least the viscosity data generated while processing the respective batch (101').

19. An apparatus according to claim 1, wherein the control system (10) is arranged to operate the water flow control means (60) to introduce the second volume of water (W2) into the vessel (20), during the second, hydration and carbonatation phase (P2), responsive to sensing a reduction in a rate of saidprogressive increase in viscosity of the first viscosity profile (VI), or responsive to sensing the first viscosity peak value (Vvl), or responsive to sensing the decrease in viscosity from the first viscosity peak value (Vvl).

20. An apparatus according to claim 1, wherein the control system (10) is arranged to increase the gas flow rate, at or near a beginning of the fourth, nucleation phase (P4), to a third gas flow rate value (G3), higher than the second gas flow rate value (G2).

21. An apparatus according to claim 1, wherein the control system (10) is arranged to terminate the fourth, nucleation phase (P4) by discharging the mixture (100) from the vessel (20).

22. An apparatus according to claim 1, wherein the fourth viscosity profile (V4) defines a progressive increase in viscosity to a second viscosity peak value (Vv3), higher than the first viscosity peak value (Vvl); andthe control system (10) is arranged to supply power to the actuator (40), and to operate the water and gas flow control means (60, 70), to define, following the fourth, nucleation phase (P4), a fifth, pelletisation phase (P5);wherein, during the fifth, pelletisation phase (P5):the actuator (40) is operated to drive the rotor surface (31) in rotation, to cause a further, progressive agglomeration of the particles (102) to form pellets (104), the pellets (104) being larger than the seed particles (103); andthe pellets (104) increase progressively in size; andthe viscosity of the mixture (100) defines, over time, a fifth viscosity profile (V5a, V5b), wherein a moving average (V5a', V5b') of the fifth viscosity profile (V5a, V5b) has a smaller rate of change than the fourth viscosity profile (V4).

23. An apparatus according to claim 22, wherein, during the fifth, pelletisation phase (P5), the control system (10) is arranged to operate the actuator (40):at a first period speed or power (A2) for a first time period (P5a), and then, after the first time period (P5a),at a second period speed or power (Al), lower than the first period speed or power (A2), for a second time period (P5b).

24. An apparatus according to claim 22 or claim 23, wherein the control system (10) is arranged to operate the gas flow control means (70) to maintain a flow of the gas (G) into the vessel (20) to react with the mixture (100) during the fifth, pelletisation phase (P5).

25. An apparatus according to claim 1, wherein the sensing means (51) is arranged to sense variations in power supplied to the actuator (40), the power being arranged to vary responsive to a varying torque reaction of the mixture (100) at the rotor surface (31).

26. An apparatus according to claim 1 or claim 25, wherein the control system (10) is arranged to supply power to the actuator (40) to operate the actuator (40) to drive the rotor surface (31) in rotation at a substantially constant speed (A2) during at least a part of the process.

27. An apparatus according to any one of claims 1 - 26, wherein the dust particles (102') include at least one of: fly ash, air pollution control residue (APCR), cement kiln dust (CKD), and cement bypass dust (CBD).

28. A process for carbonatation of a fluent body (101) of solid particles (102) by reaction with a carbonic gas (G), at least some of the solid particles (102) being dust particles (102'), by means of an apparatus;the apparatus including:a vessel (20) for containing the fluent body (101), anda rotor surface (31) arranged within the vessel (20) for rotation about an axis (X31); the apparatus being operable to process multiple batches (101') sequentially, each in accordance with the process, wherein each batch (101') is formed from a different said fluent body (101);the process including, for each respective batch (101'):mixing the fluent body (101) with water (W), in the vessel (20), to form a mixture (100); providing a flow of the gas (G) into the vessel (20) at a gas flow rate (G2, G3); and sensing a viscosity of the mixture (100) within the vessel (20) to generate viscosity data as a time series representing the sensed viscosity of the mixture (100) over time;the process further including, for each respective batch (101'):a first, hydration phase (Pl) including an initial mixing period (Pla); followed by a second, hydration and carbonatation phase (P2); followed bya third, carbonatation phase (P3) having a third phase duration (P31); followed by a fourth, nucleation phase (P4);wherein during the first, hydration phase (Pl):both the fluent body (101) and a first volume of water (Wl) are introduced into the vessel (20), andthe gas flow rate is limited for the initial mixing period to not more than a first gas flow rate value (Gl), andthe rotor surface (31) is driven in rotation, to mix the fluent body (101) and the water (W) to form the mixture (100), andthe viscosity of the mixture (100) defines, over time, a first viscosity profile (VI), wherein the first viscosity profile (VI) defines a progressive increase in viscosity; andwherein the viscosity of the mixture (100) defines a first viscosity peak value (Vvl) following said progressive increase in viscosity of the first viscosity profile (VI); andwherein, after the initial mixing period (Pla), the gas flow rate is increased to a second gas flow rate value (G2), higher than the first gas flow rate value (Gl); andwherein, during the second, hydration and carbonatation phase (P2):a second volume of water (W2) is introduced into the vessel (20), andthe rotor surface (31) is driven in rotation, to mix the fluent body (101) with the second volume of water (W2); andthe viscosity of the mixture (100) defines, over time, a second viscosity profile (V2), wherein the second viscosity profile (V2) defines a progressive decrease in viscosity to a reduced viscosity value (Vv2), lower than the first viscosity peak value (Vvl); andwherein, during the third, carbonatation phase (P3):the rotor surface (31) is driven in rotation, to expose fresh surfaces of the mixture (100) for reaction with the gas (G), andthe viscosity of the mixture (100) defines, over time, a third viscosity profile (V3) having a smaller rate of change than each of the first viscosity profile (VI) and the second viscosity profile (V2); and wherein, after the third phase duration (P31), the third, carbonatation phase (P3) is terminated, and the fourth, nucleation phase (P4) is initiated, by introducing, into the vessel (20), a third volume of water (W3), wherein the third volume of water (W3) is selected to cause a progressive agglomeration of the dust particles (102') to form seed particles (103) during the fourth, nucleation phase (P4); andwherein, during the fourth, nucleation phase (P4):the rotor surface (31) is driven in rotation, to mix the fluent body (101) with the third volume of water (W3); andthe viscosity of the mixture (100) defines, over time, a fourth viscosity profile (V4), wherein the fourth viscosity profile (V4) defines a progressive increase in viscosity having a greater rate of changethan the third viscosity profile (V3) and corresponding to said progressive agglomeration of the dust particles (102') to form seed particles (103).

29. A process according to claim 28, wherein the dust particles (102') form at least 40% of the solid particles (102) of the fluent body (101) by weight.

30. A process according to claim 28 or 29, wherein the dust particles (102') include at least one of: fly ash, air pollution control residue (APCR), cement kiln dust (CKD), and cement bypass dust (CBD).

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