System and method for determining catalytic properties of chemical compositions.

Abstract

A system for determining catalytic properties of chemical compositions, the system comprising: a catalyst synthesis module configured to synthesise a chemical composition, the catalyst synthesis module being configured to synthesise the chemical composition from one or more of a plurality of predefined base materials and by processing the base materials under one or more of a plurality of processing conditions; a catalyst analysis module configured to analyse the catalytic properties of the synthesised chemical composition under one or more of a plurality of testing conditions and output the analysis results; a control module configured to control the catalyst synthesis module, wherein the control module is configured to determine the base material composition, and processing conditions and / or testing conditions, for a next chemical composition to be synthesised based on the output analysis results from the catalyst testing module for a previous chemical composition.

Description

[0001] SYSTEM AND METHOD FOR DETERMINING CATALYTIC PROPERTIES OF CHEMICAL COMPOSITIONS.

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to systems and methods for determining catalytic properties of chemical compositions, determining processing conditions for forming chemical compositions having target catalytic properties, identifying chemical compositions having target catalytic properties and / or manufacturing chemical compositions having target catalytic properties. In various examples, the properties relate to hydrogen production, carbon dioxide conversion or ammonia synthesis, and respective reverse processes.

[0004] BACKGROUND ART

[0005] There is an increasing need for more effective materials for use in applications including photovoltaics, batteries, super capacitors, and electrocatalysts, to name a few. Of particular intertest are electrocatalysts for the production of hydrogen or conversion of carbon dioxide.

[0006] Investigation of catalyst materials using trial and error methods can be slow and costly and often results in biased and low-quality data. On the other hand, using first principle theoretical calculation methods for modelling catalyst structure and performance, without supporting these models with experimental measurements has not yielded the desired discovery of new catalytic candidates. These methods often necessitate an intricate understanding of catalytic properties prior to predicting novel properties, and the knowledge of the electrocatalytic performance and behaviour on the atomic scale is still absent.

[0007] More recently, the pursuit of potential catalysts through high-throughput experimentation, guided by expert analysis, has similarly failed to produce substantial outcomes in identifying innovative catalysts. These experiments tend to be skewed by limited perceptions of catalytic performance, fixating on specific candidate groups while neglecting unexplored groups within the search domain that might have superior potential. It an object of the present disclosure to at least partially address some of the above problems.

[0008] SUMMARY OF THE INVENTION

[0009] According to an aspect of the disclosure there is provided a system for determining catalytic properties of chemical compositions, the system comprising: a catalyst synthesis module configured to synthesise a chemical composition, the catalyst synthesis module being configured to synthesise the chemical composition from one or more of a plurality of predefined base materials and by processing the base materials under one or more of a plurality of processing conditions; a catalyst analysis module configured to analyse the catalytic properties of the synthesised chemical composition under one or more of a plurality of testing conditions and output the analysis results; a control module configured to control the catalyst synthesis module, wherein the control module is configured to determine the base material composition, and processing conditions and / or testing conditions, for a next chemical composition to be synthesised based on the output analysis results from the catalyst testing module for a previous chemical composition.

[0010] Optionally, the control module is configured to determine the base materials, and processing conditions and / or testing conditions, for the next chemical composition to be synthesised, based on base materials and processing conditions and / or testing conditions, predicted to improve catalytic properties compared to the previous chemical composition, with reference to predetermined target catalytic properties.

[0011] Optionally, the control module is configured to execute a machine learning model configured to predict catalytic properties for a base material composition, and processing conditions and / or testing conditions, in order to determine the base materials and processing conditions and / or testing conditions for the next chemical composition.

[0012] Optionally, the base materials, and processing conditions and / or testing conditions for the next chemical composition are determined based on an acquisition function applied to the output of the machine learning model. Optionally, the machine learning model is trained to output one or more objective values corresponding to catalytic properties based on training data comprising base material composition, full or a subset of processing conditions for synthesis of the catalyst and / or testing conditions, associated catalytic properties derived from experimental measurement.

[0013] Optionally, the machine learning model is refined based on the analysis results through active learning in the process space comprising material composition and processing conditions and / or testing conditions.

[0014] Optionally, the catalytic properties comprise one or more of: reaction product concentration, optionally corresponding to a target current and / or target voltage, reaction product selectivity, reactant conversion percentage and catalyst stability.

[0015] Optionally, the catalytic properties are electrocatalytic and / or photocatalytic properties for Hydrogen production or oxidation, Carbon Dioxide conversion or reduction, and / or Ammonia synthesis or cracking.

[0016] Optionally, the processing conditions comprise one or more of: the different processing steps performed, the order in which different processing steps are performed, processing temperature in each of the relevant processing steps, processing pH temperature in each of the relevant processing steps, processing time in each of the processing steps, liquid flow rate of liquid addition to the sample, the age of chemical components used in the synthesis, the deposition technique used, flow rate of deposition, deposition time, deposition cycle, deposition spin rate, and temperature applied during deposition.

[0017] Optionally, the processing conditions comprise one or more of: the different processing steps performed, the order in which different processing steps are performed, processing temperature in each of the relevant processing steps, processing pH in each of the relevant processing steps, processing pressure in each of the relevant processing steps, revolutions per minute for relevant mixing processes, processing atmosphere in each of the relevant processing steps, processing time in each of the processing steps, liquid flow rate of liquid addition to the sample, the age of chemical components used in the synthesis, the deposition technique used, flow rate of deposition, deposition time, deposition cycle, deposition spin rate, and temperature applied during deposition. Optionally, the base materials comprise a plurality of monometallic or multi-metallic materials.

[0018] Optionally, the base materials are in powder form.

[0019] Optionally, the catalyst synthesis module is configured to mix the one or more base materials with one or more solvents to form a liquid catalyst precursor.

[0020] Optionally, the catalyst synthesis unit is configured to deposit the liquid catalyst precursor onto a conductive substrate to form a test sample.

[0021] Optionally, the deposition of the liquid catalyst precursor is performed by spray coating, doctor blading, electrochemical depositions, dip coating, chemical bathing and / or spin coating.

[0022] Optionally, the deposition of the liquid catalyst precursor is performed by spray coating, doctor blading, electrochemical depositions, dip coating, chemical bathing, spray pyrolysis, drop-casting, sol -gel, chemical vapour deposition and / or spin coating.

[0023] Optionally, catalyst synthesis module is configured to transfer the chemical composition to the catalyst analysis module.

[0024] Optionally, the catalyst synthesis module is configured to operate autonomously under the control of the control unit.

[0025] Optionally, the catalyst analysis module is configured to perform electrolysis using a test sample comprising the synthesised chemical composition deposited on a conductive substrate.

[0026] Optionally, the catalyst analysis module is configured to perform electrolysis on a plurality of test samples comprising the same chemical compositions, in parallel, under respective different testing conditions. Alternatively or additionally, optionally the catalyst analysis module is configured to perform electrolysis on a plurality of test samples comprising different chemical compositions, in parallel, optionally under respective different testing conditions or the same testing conditions.

[0027] Optionally, the testing conditions comprise one or more of: electrolyser components, electrolyte composition, gas concentration in the electrolyte, applied voltage, applied current, electrolyte pH, humidity of gas input, pressure, and temperature.

[0028] Optionally, the testing conditions comprise one or more of: electrolyser components, electrolyte composition, electrolyte concentration, flow rate of electrolyte, gas concentration in the electrolyte, flow rate of gas, concentration of gas, applied voltage, applied current, electrolyte pH, humidity of gas input, humidity of gas output, pressure and temperature.

[0029] Optionally, the catalyst analysis module is further configured to analyse additional properties of the synthesised chemical composition, the base materials and / or intermediate chemical compositions.

[0030] Optionally, the catalyst analysis module is configured to measure product composition and / or concentration during and / or after the electrolysis is performed.

[0031] Optionally, the catalyst analysis module comprises a gas chromatograph-mass spectrometer to measure product composition and / or concentration.

[0032] Optionally, the catalyst analysis module comprises an inductive coupled plasma spectroscopy to measure the catalyst concentration in the electrolyte before, during and / or after the experiment.

[0033] Optionally, the catalyst analysis module is configured to operate autonomously under the control of the control unit.

[0034] Optionally, the catalyst synthesis module comprises a plurality of synthesis work cells, each of the plurality of synthesis work cells being configured to perform one or more processing steps to synthesise the chemical composition, at least a subset of the plurality of synthesis work cells performing optional and / or alternative processing steps, and the control module is configured to control which of the optional and / or alternative synthesis work cells are used to synthesis each chemical composition.

[0035] Optionally, the control unit is further configured to control the order in which synthesis work cells are used to synthesise the chemical composition.

[0036] Optionally, the catalyst analysis module comprises a plurality of analysis work cells, each of the plurality of analysis work cells being configured to perform one or more analysis steps to analyse the chemical composition, at least a subset of the plurality of analysis work cells performing optional and / or alternative analysis steps, and the control module is configured to control which of the optional and / or alternative analysis work cells are used to analyse each chemical composition.

[0037] Optionally, the control unit is further configured to control the order in which analysis work cells are used to analyse the chemical composition.

[0038] Optionally, the control unit is configured to determine a work flow comprising a sequence of processing steps and / or analysis steps performed by one or more synthesis work cells and / or analysis work cells for each chemical composition.

[0039] According to a second aspect of the disclosure, there is provided system for determining catalytic properties of chemical compositions, the system comprising: a modular catalyst synthesis module configured to synthesise a chemical composition from one or more of a plurality of predefined base materials and by processing the base materials under one or more of a plurality of processing conditions, the modular catalyst synthesis module comprising a plurality of synthesis work cells, each of the plurality of synthesis work cells being configured to perform one or more processing steps to synthesise the chemical composition, at least a subset of the plurality of synthesis work cells performing optional and / or alternative processing steps; a catalyst analysis module configured to analyse the catalytic properties of the synthesised chemical composition under one or more of a plurality of testing conditions and output the analysis results; a control module configured to control the catalyst synthesis module, wherein the control module is configured to determine the base material composition, and processing conditions, for synthesising the chemical composition and determine a work flow comprising a sequence of processing steps performed by one or more of the synthesis work cells, the work flow defining which of the optional and / or alternative synthesis work cells are used to synthesis the chemical composition, and / or the order in which the synthesis work cells are used to synthesise the chemical composition.

[0040] Optionally, the control module is configured to determine a work flow, for a next chemical composition to be synthesised based on the output analysis results from the catalyst testing module for a previous chemical composition.

[0041] Optionally, the catalyst analysis module is modular and configured to analyse properties of the synthesised chemical composition, the base materials and / or intermediate chemical compositions, the modular catalyst analysis module comprising a plurality of analysis work cells, each of the plurality of analysis work cells being configured to perform one or more analysis steps, at least a subset of the plurality of analysis work cells performing optional and / or alternative analysis steps, and the work flow determined by the control module further defines which of the optional and / or alternative analysis work cells are used to analyse properties of the synthesised chemical composition, the base materials and / or intermediate chemical compositions and / or the order in which analysis work cells are used to analyse properties of the synthesised chemical composition, the base materials and / or intermediate chemical compositions.

[0042] Optionally, the system is configured to execute a plurality of work flows in parallel to synthesise and analyse a plurality of different chemical compositions.

[0043] Optionally, the chemical composition comprises inorganic nanoparticles.

[0044] Optionally, the system comprises a transfer module configured to transfer the base materials, the chemical composition and / or intermediate chemical compositions between the work cells.

[0045] According to a third aspect of the disclosure, there is provided a method of autonomously determining catalytic properties of chemical compositions, the method comprising: autonomously synthesising a chemical composition, the chemical composition being synthesised from one or more of a plurality of predefined base materials and by processing the base materials under one or more of a plurality of processing conditions; autonomously analysing the catalytic properties of the synthesised chemical composition under one or more of a plurality of testing conditions and outputting the analysis results; controlling the synthesising using a control module 31 configured to determine the base material composition, and processing conditions and / or testing conditions, for a next chemical composition to be synthesised based on the output analysis results from the catalyst testing module for a previous chemical composition.

[0046] According to a fourth aspect of the disclosure, there is provided a method of determining catalytic properties of chemical compositions, the system comprising, the method comprising: autonomously synthesising a chemical composition using a modular catalyst synthesis module configured to synthesise a chemical composition from one or more of a plurality of predefined base materials and by processing the base materials under one or more of a plurality of processing conditions, the modular catalyst synthesis module comprising a plurality of synthesis work cells, each of the plurality of synthesis work cells being configured to perform one or more processing steps to synthesise the chemical composition, at least a subset of the plurality of synthesis work cells performing optional and / or alternative processing steps; autonomously analysing the catalytic properties of the synthesised chemical composition using a catalyst analysis module configured to analyse the catalytic properties of the synthesised chemical composition under one or more of a plurality of testing conditions and output the analysis results; controlling the synthesising using a control module configured to control the catalyst synthesis module, wherein the control module is configured to determine the base material composition, and processing conditions, for synthesising the chemical composition and determine a work flow comprising a sequence of processing steps performed by one or more of the synthesis work cells, the work flow defining which of the optional and / or alternative synthesis work cells are used to synthesis the chemical composition, and / or the order in which the synthesis work cells are used to synthesise the chemical composition.

[0047] According to a fifth aspect of the disclosure, there is provided a method of identifying a chemical composition having target catalytic properties, comprising the method of the third or fourth aspect. According to a sixth aspect of the disclosure, there is provided a method of manufacturing a chemical composition having target catalytic properties, comprising the method of the third or fourth aspect.

[0048] According to a seventh aspect of the disclosure, there is provided a method of determining processing conditions for forming a chemical composition having target catalytic properties, comprising the method of the third or fourth aspect.

[0049] BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Further features of the disclosure will be described below, by way of non-limiting examples and with reference to the accompanying drawings, in which:

[0051] Fig. 1 schematically shows an example system according to the disclosure;

[0052] Fig. 2 is a flow chart showing example process according to the disclosure;

[0053] Fig. 3 schematically shows a further example system according to the disclosure;

[0054] Fig. 4 is a flow chart showing a further example process according to the disclosure.

[0055] DETAILED DESCRIPTION

[0056] Fig. 1 schematically shows an example system 1 according to the disclosure, for determining catalytic properties of chemical compositions, e.g. chemical compositions comprising inorganic nanoparticles. As shown, the system comprises an experimental subsystem 2 and a computer subsystem 3. The experimental subsystem 2 comprises a catalyst synthesis module 21 and a catalyst analysis module 23. The computer subsystem 1 comprises a control module 31.

[0057] The catalyst synthesis module 21 is configured to synthesise a chemical composition. The catalyst synthesis module 21 may be configured to synthesise the chemical composition from one or more of a plurality of predefined base materials. The catalyst synthesis module 21 may be configured to synthesise the chemical composition by processing the base materials under one or more of a plurality of processing conditions. The catalyst synthesis module 21 is configured to mix the one or more base materials with one or more solvents to form a liquid catalyst precursor. The base materials may comprise a plurality of monometallic or multi-metallic materials. The base materials may be formed from a metallic element, or combination or metallic elements, including transition metals and non-transition metals. The base materials may be in powder form, for example. The solvents may include one or more of aqueous solvents e.g. water, hydrochloric acid, sulphuric acid, sodium / potassium hydroxide, sodium / potassium carbonate, organic solvents e.g. ethanol, acetone, isopropyl alcohol, methanol.

[0058] The catalyst synthesis module 21 may comprise a solid handling unit 23 configured to extract samples of the base materials, measure the amount of the samples (e.g. by weight or volume) and load them into a sample container.

[0059] The solid handling unit 23 may comprise one or more base material containers containing the base materials to be extracted. The solid handling unit 23 may comprise one or more robotic arms for manipulating the samples. The solid handling unit 23 may comprise one or more weighing balances for weighing the samples. The solid handling unit 23 may comprise a mixing unit for mixing two or more samples of different base materials together.

[0060] The solid handling unit 23 may comprise one or more dispensing units for dispensing samples from the base material containers, and / or extracting units for extracting samples from the base material containers. The dispensing units and / or extracting units may comprise one or more pumps, for example. The dispensing units may be attached to base material containers, for example. The extracting units may be attached to one or more of the robotic arms, for example.

[0061] The catalyst synthesis module 21 may comprise a liquid handling unit 24 configured to add liquids to the sample, mix the sample and heat and / or cool the sample to form the liquid catalyst precursor. The liquid handling unit 24 may be configured to add liquid solvents and, optionally, further liquids, such as chemical buffers, acids, bases, reducing agents to the sample. The liquid handling unit 24 may comprise one or more liquid containers containing the liquids. The liquid handling unit 24 may comprise one or more robotic arms for manipulating the samples. The liquid handling unit 24 may comprise a heating device (e.g. one or multiple thermocouple temperature devices) for heating and / or cooling the samples. The liquid handling unit 24 may comprise a stirring device for stirring the samples, such as a magnetic stirrer or a shaker.

[0062] The liquid handling unit 24 may comprise one or more dispensing units for dispensing liquids from the liquid containers, and / or extracting units for extracting liquids from the liquid containers. The dispensing units and / or extracting units may comprise one or more pumps, for example. The dispensing units may be attached to the liquid containers, for example. The extracting units may also extract the catalyst in solid form, (known as solute) with the means of vacuum or gravitational filtration process. The extracting units may be attached to one or more of the robotic arms, for example.

[0063] The catalyst synthesis module 21 may be further configured to deposit the liquid catalyst precursor onto a conductive substrate to form a test sample. The conductive substrate may be a gas diffusion electrode or an anionic-cationic bipolar membrane, for example. The conductive substrate may be formed from an electrode material comprising one or more of: indium-doped tin oxide, fluoride doped-tin oxide, glassy carbon, nickel, gold and silver. The liquid catalyst precursor may be deposited as a thin film.

[0064] The catalyst synthesis module 21 may comprise a deposition unit 25 configured to deposit the liquid catalyst precursor onto a conductive substrate to form a test sample. The deposition of the liquid catalyst precursor may be performed by spray coating, spray pyrolysis, doctor blading, electrochemical depositions, dip coating, chemical bathing, dropcasting, sputtering, sol-gel method, chemical vapour deposition, and / or spin coating. Accordingly, the deposition unit 25 may comprise spray coating, spray pyrolysis, doctor blading, electrochemical depositions, dip coating, chemical bathing, drop-casting, sputtering, sol-gel method, chemical vapour deposition, and / or spin coatingequipment. Each of these different equipment for different deposition methods may comprise a work cell as described below. The deposition unit 25 may comprise one or more robotic arms for manipulating the substrate. The deposition unit 25 may comprise one or more robotic arms for manipulating the liquid catalyst precursor. The catalyst synthesis module 21 may be configured to process the base materials under one or more predefined processing conditions. The processing conditions may relate to synthesis of the catalyst precursor or formation of the test sample from the catalyst precursor.

[0065] For example, processing conditions relating to the synthesis of the catalyst precursor may comprise one or more of the processing steps performed, the order in which different processing steps are performed, processing temperature in each of the relevant processing steps, processing pH in each of the relevant processing steps, processing pressure in each of the relevant processing steps, revolutions per minute for relevant mixing processes, processing atmosphere in each of the relevant processing steps, processing time in each of the processing steps, liquid flow rate of liquid addition to the sample, the age of chemical components used in the synthesis, and the synthesis technique used.

[0066] For example, the processing conditions relating to the formation of the test sample from the catalyst precursor may comprise one or more of the deposition technique used, flow rate of deposition, deposition time, deposition cycle, deposition spin rate, deposition height, position (e.g. cartesian coordinate) of the deposition and temperature applied during deposition.

[0067] The catalyst synthesis module 21 may be configured to transfer the chemical composition, now part of the test sample, to the catalyst analysis module 22. This may be performed by one or more robotic arms, for example.

[0068] The catalyst analysis module 22 may be configured to perform electrolysis using the test sample comprising the synthesised chemical composition deposited on the conductive substrate and to analyse the catalytic properties of the synthesised chemical composition under one or more of a plurality of testing conditions and output the analysis results. For example, the catalyst synthesis module 22 may be configured to measure product composition and / or concentration. These may be measured before, during and / or after the electrolysis is performed. The catalyst analysis module 22 may be configured to perform one or more of electrocatalytic Hydrogen production, Carbon Dioxide reduction, and photovoltaic conversion, and / or reverse processes. Accordingly, the catalytic properties may correspond to one or more of these catalytic processes.

[0069] The catalyst analysis module 22 may comprise an electrolyser unit 26 to perform the electrolysis. The electrolyser unit 26 may be configured to receive the test sample and form an electrolyser using the test sample, e.g. as an electrode within the electrolyser. The electrolyser may comprise electrodes and an electrolyte. The electrolyser unit 26 may comprise a potentiostat for controlling electrode voltage. The electrolyser unit 26 may further comprise a temperature control means, e.g. comprising a heater, for controlling the temperature of the electrolyser.

[0070] The catalyst analysis module 22 may be configured to perform electrolysis on a plurality of test samples in parallel. The plurality of test samples may comprise the same chemical compositions, under respective different testing conditions. Alternatively, or additionally, the plurality of test samples may comprise respectively different chemical compositions, under the same testing conditions.

[0071] The electrolyser unit 26 may be configured to control the testing conditions for each test sample. For example, the testing conditions may comprise one or more of electrolyser components, electrolyser stack, electrolyte composition, electrolyte concentration, flow rate of electrolyte, gas concentration in the electrolyte, flow rate of gas, concentration of gas, applied voltage, applied current (e.g. of either direct or alternating current), electrolyte pH, humidity of gas input, humidity of gas output, pressure, and temperature.

[0072] The catalyst analysis module 22 may further comprise a measurement unit 27 for measuring catalytic performance. The measurement unit 27 may comprise a gas chromatograph-mass spectrometer to measure product composition and / or concentration, and / or an inductively coupled plasma to measure the catalyst decomposition, for example.

[0073] The measurements obtained by the catalyst analysis module 22 may be provided to the control module 31 for further analysis. Catalytic properties may be determined based on the obtained measurement. The catalytic properties may comprise one or more of reaction product concentration, optionally corresponding to a target current and / or target voltage, reaction product selectivity, reactant conversion percentage and catalyst stability.

[0074] The control module 31 may be configured to control the catalyst synthesis module 21 and / or the catalyst analysis module 22. The catalyst synthesis module 21 and / or the catalyst analysis module 22 may be is configured to operate autonomously under the control of the control module 31. The control module 31 may comprise one or more experimental subsystem control units 33 configured to control the modules forming the experimental subsystem. The experimental subsystem control units 33 may be configured to execute one or more machine learning algorithms configured to control the modules forming the experimental subsystem based on base material compositions for the test samples, and processing conditions and / or testing conditions, determined by the control module 31.

[0075] Additionally, the one or more experimental subsystem control units 33 may receive as input metadata relating to the modules forming the experimental subsystem. This metadata may allow the experimental subsystem control units 33 to perform feedback control based on the metadata. Accordingly, the metadata may comprise metadata corresponding to the processing or test conditions. With regard to physical manipulation, e.g. by robotic arms, data collected by cameras, position sensors and / or motions sensors may be used.

[0076] The control module 31 may comprise a prediction unit 32 configured to determine the base material composition, and one or both of the processing conditions and the testing conditions, for a next chemical composition to be synthesised based on the output results from the catalyst testing module for a previous chemical composition. The prediction unit 32 may be configured to determine the base materials, and processing conditions and / or testing conditions, for the next chemical composition to be synthesised, based on base materials and processing conditions and / or testing conditions, predicted to improve catalytic properties compared to the previous chemical composition, with reference to predetermined target catalytic properties.

[0077] The prediction unit 32 may be configured to execute a machine learning model configured to predict catalytic properties for a base material composition, and processing conditions and / or testing conditions, in order to determine the base materials and processing conditions for the next chemical composition. The machine learning model may be random forest regression model, or Bayesian neural network, for example.

[0078] The machine learning model may be trained to output one or more objective values corresponding to catalytic properties based on training data comprising base material composition, full or a subset of processing conditions for synthesis of the catalyst and / or testing conditions, associated catalytic properties derived from experimental measurement.

[0079] The machine learning model may be periodically refined based on the results from the catalyst analysis module 22, e.g. through active learning in the process space comprising material composition and processing conditions and / or testing conditions. The results may be from the measurement unit and / or the electrolyser unit and may relate to the base materials, chemical compositions and / or intermediate chemical compositions.

[0080] The initial base material composition, processing conditions and the testing conditions may be selected randomly or based on an initial prediction by the control module 31, e.g. the prediction unit 32.

[0081] The control module 31, e.g. the prediction unit 32, may be configured to iteratively change one or more of the base material compositions, the processing conditions and the testing conditions, for subsequent experiments. The system may be configured to operate in an iterative cycle of synthesis and analysis until a predefined condition is met. The predefined condition may be convergence of the catalytic properties of the chemical composition to a predefined set of catalytic properties. The base materials, and processing conditions and / or testing conditions for the next chemical composition are determined based on an acquisition function applied to the output of the machine learning model. The acquisition function may determine the exploration of the process space comprising material composition and processing conditions and / or testing conditions.

[0082] Fig. 2 is a flow diagram showing an example process according to the disclosure. In Step SI, initial base material composition, processing conditions and testing conditions are selected. In step S2, a liquid catalyst precursor is synthesised from the base materials, solvents and additives by the solid handling unit 23 and liquid handling unit 24 of the synthesis module. In Step S3, the liquid catalyst precursor is deposited as a thin film on a conductive substrate by the deposition unit 25 of the synthesis module to form a test sample. In Step S4, the test sample is integrated into an electrolyser by the electrolyser unit 26 of the analysis module and electrolysis is performed. In Step S5, catalytic performance is measured by the measurement unit 27 of the analysis module. In Step S6, measurements are provided to the control module 31, together with data regarding the base material composition, processing and test conditions. In Step S7, the machine learning model is updated based on the measurements and data received. In Step S8, the control unit determines whether the catalytic properties correspond to predefined desired properties. If so, the process ends. If not, the process continues to Step S9. In Step S9, subsequent base material composition, processing conditions and testing conditions are determined by the control unit. The processes then return to Step S2.

[0083] The experimental subsystem 2, e.g. one or both of the catalyst synthesis module 21 and the catalyst analysis module 22, may comprise a plurality of work cells, e.g. synthesis work cells and analysis work cells respectively. The work cells are modular hardware units configured to perform specific functions within the experimental subsystem 2, and the catalyst synthesis module 21 and the catalyst analysis module 22 respectively.

[0084] The synthesis work cells may be configured to perform one or more processing steps to synthesise the chemical composition. The analysis work cells may be configured to perform one or more analysis steps to analyse the chemical composition, the base materials and / or intermediate chemical compositions.

[0085] For example, hardware units and / or sub-units forming the solid handling unit 23, liquid handling unit 24, deposition unit 25, electrolyser unit 26 and measurement unit 27 described above may form one or more work cells. Hardware units and / or sub-units configured to transfer the base materials, intermediate chemical compositions or the chemical composition from one work cell to another, as described above may form submodules of a transfer module. The transfer module may be configured to transfer the base materials, intermediate chemical compositions and / or the chemical composition between the work cells.

[0086] At least some of the work cells may perform optional and / or alternative functions. At least a subset of the plurality of synthesis work cells may perform optional and / or alternative processing steps. At least a subset of the plurality of analysis work cells may perform optional and / or alternative analysis steps.

[0087] The control module may be configured to control which of the optional and / or alternative synthesis work cells are used to synthesis each chemical composition. Alternatively, or additionally, the control module may be configured to control which of the optional and / or alternative analysis work cells are used to analyse each chemical composition. The control unit may be further configured to control the order in which synthesis work cells and / or analysis work cells are used to synthesis or analyse the chemical composition.

[0088] The control unit may be configured to determine a work flow comprising a sequence of processing steps and / or analysis steps performed by one or more synthesis work cells and / or analysis work cells for each chemical composition. The control unit may also be configured to control parameters of operation for each work cell. Accordingly, appropriate work cells can be selected and used to synthesis a chemical composition under the required processing conditions and analyse the chemical composition, the base materials and / or intermediate chemical compositions as required.

[0089] Accordingly, the optional and / or alternative work cells and / or the parameters of operation for each work cell (regardless of whether they are optional and / or alternative work cells) may define a parameter space for synthesising chemical compositions. The system thus enables dynamic synthesis of chemical compositions dependent on the parameter space that needs to be explored to synthesis a chemical composition required to meet one or more target properties.

[0090] Fig. 3 schematically shows a further example system 1 according to the disclosure, for determining catalytic properties of chemical compositions. As shown, the system comprises an experimental subsystem 2 and a computer subsystem 3. The experimental subsystem 2 comprises a catalyst synthesis module 21 comprising a plurality of work cells.

[0091] As shown, the plurality of work cells may comprise one or more of: an automated dosing work cell 41, a microwave synthesis work cell 42, a spray pyrolysis work cell 43, and an electrochemical deposition work cell 47. The automated dosing work cell 41 automates the precise measurement and mixing of base materials to prepare chemical compositions for synthesis or deposition. It involves the use of automated systems to accurately dose the required amounts of each base material, liquid or solid. These materials are then mixed under controlled conditions to ensure homogeneity. The prepared chemical composition is consistent and ready for further processing, whether it be for synthesis in a microwave work cell or deposition in a spray pyrolysis or electrochemical deposition work cell.

[0092] The microwave synthesis work cell 42 utilizes microwave radiation to heat and synthesize chemical compounds. The intermediary chemical composition, which is a partially processed material, is subjected to microwave energy. The microwaves cause rapid heating of the material, leading to chemical reactions that finalize the composition. The result is a finalized chemical composition that is uniform and ready for the next step. This preparation might include processes like crimping / decrimping, vial capping / recapping, filtration, centrifugation, or mixing with other liquid compounds depending on the next step.

[0093] The spray pyrolysis work cell 43 is used to deposit a thin film of the chemical composition onto a conductive substrate. The chemical composition is first dissolved or suspended in a solution, typically a solvent. The solution is then atomized into fine droplets and sprayed onto a heated conductive substrate. As the droplets reach the hot surface, they undergo pyrolysis, converting the precursor solution into a solid film. The result is a uniform, thin film of the desired chemical composition on the substrate ready for testing.

[0094] The electrochemical deposition work cell 47 uses electrochemical processes to deposit a material onto a conductive substrate. The substrate is immersed in an electrolyte solution containing the material to be deposited. By applying an electric current, ions of the material are reduced and deposited onto the substrate. The result is a layer of material that is electrochemically bonded to the substrate. This final chemical composition is then ready for testing.

[0095] The experimental subsystem 2 further comprises a catalyst analysis module 22, comprising a plurality of work cells. As shown the plurality of work cells may comprise an ultraviolet-visible spectroscopy work cell 44, an x-ray fluorescence work cell 45, and a parallel electrolyser work cell 46.

[0096] The experimental sub-system 2 may further comprise a transfer module, not shown, but the function of which is denoted by arrows between work cells in Fig.3.

[0097] The computer subsystem comprises a control module 31 comprising a prediction unit 32 and an experimental work flow control unit 34 and. The experimental work flow control unit is configured to determine a work flow comprising a sequence of processing steps and / or analysis steps performed by one or more synthesis work cells and / or analysis work cells for each chemical composition. The work flow control unit 34 may further determine operating parameters for each of the work cells in the work flow. The work flow is determined based on the output of the prediction unit 32, e.g. the output base materials and processing conditions.

[0098] The catalyst synthesis module 21 may be configured to synthesise the chemical composition by processing the base materials under one or more of a plurality of processing conditions corresponding to the parameter space defined by the work cells of the determined work flow.

[0099] For example, the catalyst synthesis module 21 may be configured to mix the one or more base materials with one or more solvents to form a liquid catalyst precursor utilizing one or more preparation work cells, such as the automated dosing module 41. The preparation work cells are work cells for preparing the liquid catalyst precursor, e.g. those forming the solid handling unit 23 and liquid handling unit 24.

[0100] The catalyst synthesis module 21 may be further configured to deposit the liquid catalyst precursor onto a conductive substrate to form a test sample by utilizing deposition work cells e.g. the coupled spray pyrolysis work cell 42 and the electrochemical deposition work cell 47. The deposition work cells are for forming a test sample from the liquid catalyst, e.g. those forming the deposition unit 25.

[0101] Processing conditions relating to the synthesis of the catalyst precursor by the preparation work cells may comprise one or more of: the different processing steps performed, the order in which different processing steps are performed, processing temperature in each of the relevant processing steps, processing pH temperature in each of the relevant processing steps, processing pressure in each of the relevant processing steps, revolutions per minute for relevant mixing processes, processing atmosphere in each of the relevant processing steps, processing time in each of the processing steps, liquid flow rate of liquid addition to the sample, the age of chemical components used in the synthesis, the synthesis technique used, the deposition technique used, flow rate of deposition, deposition time, deposition cycle, deposition spin rate, and temperature applied during deposition.

[0102] For example, the processing conditions relating to the formation of the test sample from the catalyst precursor using the deposition work cells may comprise on or more of: the deposition technique used, flow rate of deposition, deposition time, deposition cycle, deposition spin rate, deposition height, position (e.g. cartesian coordinate) of the deposition and temperature applied during deposition.

[0103] The catalyst analysis module 2 may be configured to analyse the intrinsic catalytic properties of the synthesised chemical and output the analysis results e.g. utilizing the ultraviolet-visible spectroscopy work cell 44 or the x-ray Fluorescence work cell 45, as well as the performance of the catalytic properties of the test sample, e.g. utilizing the parallel electrolyser work cell 46.

[0104] The transfer module, the functions of which are denoted by the arrows between the work cells in Fig. 3, may comprise one or more of: a robotic arm, a robotic arm on a linear range extender, a mobile robot or a human-in-the-loop. The transfer module's primary function is to transfer the required inputs and collect the outputs from each of the work cells.

[0105] Two alternative example work flows are shown in Fig. 3. A first workflow, is shown by transfer module steps A, B, C, D, and E. The prediction unit 32 predicted the base material composition, the processing conditions and the testing conditions. The experimental work flow control unit 34 then determined a work flow first requiring the automated dosing work cell 41, then the microwave reactor work cell 5, followed by the ultraviolet-visible spectroscopy work cell 44, then the spray pyrolysis work cell 43, completed by the parallel electrolyser work cell 46. A second workflow, is shown by transfer module steps G, H, I and J. The prediction unit 32 has predicted a different base material composition, alternative processing conditions and testing conditions. This secondary workflow was planned by experimental workflow control unit 34, utilizing the automated dosing work cell 41, the electrochemical deposition work cell 47, the x-ray Fluorescence work cell 45, followed by the parallel electrolyser work cell 46.

[0106] Multiple work flows may be executed in parallel, i.e. simultaneously. For example, both the above first and second work flows may be executed in parallel.

[0107] In step F, electrolysis measurements and / or other data from the catalysis analysis module 22 may be provided to the control module 31.

[0108] At least some of the work cells may be selectively coupled to the system, e.g. interchangeable. In other words, work cells that are not required for a given experiment or set of experiments may be uncoupled and removed from the system, and recoupled within the system when they are required. Alternatively, each of the different work cells may be permanently coupled within the system. For example, the electrodeposition work cell 47 may be selectively coupled, as required by the work flow GHU in Fig. 3.

[0109] Fig. 4 is a process flow diagram showing the high-level process according to the disclosure. In step S21, initial base material composition, processing conditions, and testing conditions are selected. In Step S22, the reaction pathway (corresponding to the processing conditions) needed to reach the selected composition is determined based on the available parameter space. Step S23 identifies available work cells (both uncoupled and coupled) for the reaction pathways, which serves as input to Step S22.

[0110] In Step S24, the system determines if an uncoupled work cell is required to carry out the synthesis and characterization route. If an uncoupled work cell is required, the process advances to Step S25. If not, the process continues to Step S26, where a liquid catalyst precursor is synthesized from the base materials, solvents, and additives by a preparation work cell of the catalyst synthesis module. Step S27 assesses whether intrinsic analysis of the liquid precursor is necessary based on the testing conditions determined by the control modules prediction unit. If yes, the process moves to Step S28, where one or more work cells within the catalyst analysis module performs intrinsic analysis of the liquid precursor. If intrinsic analysis is not required, the process proceeds to Step S29, where the liquid catalyst precursor is deposited as a thin film on a conductive substrate by one or more works cells within the deposition unit of the catalyst synthesis module, forming a test sample.

[0111] In Step S30, intrinsic analysis of the nanomaterial coating (corresponding to the chemical composition) is evaluated. If intrinsic analysis is required by the testing conditions determined by the control modules prediction unit, the process advances to Step S31, where a work cell within the catalyst analysis module performs this analysis. If not, the process moves to Step S32, where the test sample is integrated into an electrolyser work cell the of the catalyst analysis module, and electrolysis is performed.

[0112] Step S33 involves measuring the catalytic performance of the sample of the catalyst analysis module. Step S34 then determines whether intrinsic analysis of the used nanomaterial coating is necessary based on the testing conditions determined by the control modules prediction unit. If yes, one or more work cells within the catalyst analysis module performs this intrinsic analysis in Step S35. If not, data regarding the composition, processing, and testing conditions, along with performance measurements, are translated to the control module in Step S36.

[0113] In Step S37, the machine learning model of the prediction unit 32 is updated based on the measurements and data received. In Step S38, the control module checks if the catalytic properties meet predefined target properties. If the desired properties are achieved, the process ends. If not, the process continues to Step S39, where subsequent base material compositions, processing conditions, and testing conditions are determined. The process then returns to Step S22, where a new iteration begins.

[0114] The use of machine learning enables smarter selection of experiments based on the predefined goals, e.g. target properties. This may enable less exhaustive, more economic, searching for new catalysts. The machine learning module employs a random forest regression approach to develop a predictive model. This model learns from experimental data generated during electrocatalyst synthesis and testing, identifying correlations and patterns. Using the random forest model, the machine learning module selects candidate compositions for synthesis and testing. This approach ensures a diverse and unbiased exploration of the compositional space, minimizing the risk of overlooking promising candidates. As the system progresses through successive iterations of synthesis, testing, and prediction, the machine learning module continually refines its predictive model. This iterative process enhances the accuracy of predictions, resulting in increasingly efficient candidate selection.

[0115] The experimental apparatus facilitates high throughput, precise and controlled synthesis and testing of electrocatalysts. The solid handling unit 23 uses robotic arms, precise pumps, and weighing balances, to accurately loads, weighs, and mixes solid powder samples. This ensures consistent and reproducible catalyst formulations. The liquid handling unit 24 is equipped with sample containers, a thermocouple heating / cooling plate, a magnetic stirrer, and liquid pumps, to accurately mix, stir, and heat / cool liquid precursor samples. This contributes to the reproducibility of catalyst synthesis. Employing techniques like spray coating, doctor blading and spin coating, uniformly deposits liquid precursors onto conductive substrates. This yields catalyst thin films with precise compositions and thickness. The electrolyser module enables concurrent testing of multiple catalysts. This parallelized setup accelerates experimentation throughput. The gas chromatograph-mass spectrometer measures product composition and concentration postelectrocatalysis, providing insights into reaction pathways and catalytic efficiency. The inductively coupled plasma spectrometer measures the concentration of the catalyst in the electrolyte which indicates the decomposition of catalyst during electrolysis experiment.

[0116] The experimental apparatus supports high-throughput, precise, and controlled synthesis and testing of electrocatalysts. Work cells within the catalyst synthesis module made up of instrumentation to execute processes such as vial crimping / decrimping, vial capping / decapping, liquid handling, solid handling, centrifugation, vortex mixing, ultrasonic dispersion and emulsification, heating, sample manipulation, cooling, filtration, glass ampule / pin preparation, high-shear homogenization, evaporation, weighing, and shaking, ensure consistent catalyst formulations. Techniques such as spray coating, spray pyrolysis, doctor blading, electrochemical depositions, dip coating, chemical bathing, dropcasting, sputtering, sol-gel method, chemical vapour deposition, and / or spin coating deposit liquid precursors uniformly onto conductive substrates, yielding catalyst thin films with precise compositions and thicknesses. The parallel electrolyser work cell enables concurrent testing of multiple catalysts, accelerating experimental throughput. The gas chromatograph-mass spectrometer measures product composition and concentration postelectrocatalysis, while the inductively coupled plasma spectrometer assesses catalyst decomposition by measuring its concentration in the electrolyte.

[0117] The system of the present disclosure may address challenges with existing automated systems such as limited flexibility and parameter space, as automated systems typically lack the adaptability of human researchers and are fixed in location. This restricts the range of experiments and can lead to a narrow exploration of potential materials. Additionally, developing and integrating new features into autonomous systems is time-consuming, slowing down the discovery process and limiting responsiveness to new insights or unexpected results.

[0118] The data management and analysis facilitate data acquisition, organization, and interpretation of data. Data is captured and organized during the synthesis and testing processes. This structured repository of information ensures systematic tracking and analysis of catalyst performance trends. Aided by acquired data, the machine learning algorithm conducts sophisticated analysis of catalytic performance. The machine learning algorithm compares experimental results against predefined boundary conditions and targeted catalytic properties, supporting informed decision-making for subsequent experiments.

[0119] The invention's iterative process promotes continuous improvement and optimization. The iterative cycle commences with the machine learning module selecting candidate compositions for synthesis. These candidates undergo controlled synthesis, electrochemical testing, and analysis. The resulting data informs the module's predictive model, guiding the selection of subsequent candidates. With each iteration, the machine learning module's predictive model becomes increasingly accurate. The module fine-tunes its predictions based on newly acquired data, gradually narrowing down optimal electrocatalyst compositions. Accordingly, the integration of machine learning algorithms and advanced experimental techniques offers the following advantages:

[0120] • Acceleration of Discovery: The system's parallelized setup, rapid synthesis, and data-driven predictions significantly expedite the electrocatalyst discovery process, enabling researchers to explore a vast compositional space efficiently.

[0121] • Enhanced Exploration: Unbiased candidate selection and comprehensive analysis ensure thorough exploration of catalyst compositions, reducing the risk of overlooking high-performing materials.

[0122] • High-Quality Data: The systematic data acquisition and analysis mechanisms yield high-quality, structured data, enabling robust conclusions and insights into catalyst behaviour.

[0123] • Informed Decision-Making: The machine learning module's predictions empower researchers to make informed decisions about the next set of experiments, optimizing resource utilization.

[0124] • Iterative Learning: The iterative nature of the system encourages continuous learning and improvement. The machine learning module refines its predictive model with each iteration, leading to increasingly accurate predictions and higher-quality catalyst discoveries.

Claims

CLAIMS1. A system for determining catalytic properties of chemical compositions, the system comprising: a catalyst synthesis module configured to synthesise a chemical composition, the catalyst synthesis module being configured to synthesise the chemical composition from one or more of a plurality of predefined base materials and by processing the base materials under one or more of a plurality of processing conditions; a catalyst analysis module configured to analyse the catalytic properties of the synthesised chemical composition under one or more of a plurality of testing conditions and output the analysis results; a control module configured to control the catalyst synthesis module, wherein the control module is configured to determine the base material composition, and processing conditions and / or testing conditions, for a next chemical composition to be synthesised based on the output analysis results from the catalyst testing module for a previous chemical composition.

2. The system of claim 1, wherein the control module is configured to determine the base materials, and processing conditions and / or testing conditions, for the next chemical composition to be synthesised, based on base materials and processing conditions and / or testing conditions, predicted to improve catalytic properties compared to the previous chemical composition, with reference to predetermined target catalytic properties.

3. The system of any preceding claim, wherein the control module is configured to execute a machine learning model configured to predict catalytic properties for a base material composition, and processing conditions and / or testing conditions, in order to determine the base materials and processing conditions and / or testing conditions for the next chemical composition.

4. The system of claim 3, wherein the base materials, and processing conditions and / or testing conditions for the next chemical composition are determined based on an acquisition function applied to the output of the machine learning model.

5. The system of claim 3 or 4, wherein the machine learning model is trained to output one or more objective values corresponding to catalytic properties based on training data comprising base material composition, full or a subset of processing conditions for synthesis of the catalyst and / or testing conditions, associated catalytic properties derived from experimental measurement.

6. The system of any one of claims 3 to 5, wherein the machine learning model is refined based on the analysis results through active learning in the process space comprising material composition and processing conditions and / or testing conditions.

7. The system of any preceding claim, wherein the catalytic properties comprise one or more of: reaction product concentration, optionally corresponding to a target current and / or target voltage, reaction product selectivity, reactant conversion percentage and catalyst stability.

8. The system of any preceding claim, wherein the catalytic properties are electrocatalytic and / or photocatalytic properties for Hydrogen production or oxidation, Carbon Dioxide conversion or reduction, and / or Ammonia synthesis or cracking.

9. The system of any preceding claim, wherein the processing conditions comprise one or more of: the different processing steps performed, the order in which different processing steps are performed, processing temperature in each of the relevant processing steps, processing pH in each of the relevant processing steps, processing pressure in each of the relevant processing steps, revolutions per minute for relevant mixing processes, processing atmosphere in each of the relevant processing steps, processing time in each of the processing steps, liquid flow rate of liquid addition to the sample, the age of chemical components used in the synthesis, the deposition technique used, flow rate of deposition, deposition time, deposition cycle, deposition spin rate, and temperature applied during deposition.

10. The system of any preceding claim, wherein the base materials comprise a plurality of monometallic or multi-metallic materials.

11. The system of any preceding claim, wherein the base materials are in powder form.

12. The system of any preceding claim, wherein the catalyst synthesis module is configured to mix the one or more base materials with one or more solvents to form a liquid catalyst precursor.

13. The system of any preceding claim, wherein the catalyst synthesis unit is configured to deposit the liquid catalyst precursor onto a conductive substrate to form a test sample.

14. The system of claim 13, wherein the deposition of the liquid catalyst precursor is performed by spray coating, doctor blading, electrochemical depositions, dip coating, chemical bathing, spray pyrolysis, drop-casting, sol-gel, chemical vapour deposition and / or spin coating.

15. The system of any preceding claim, wherein catalyst synthesis module is configured to transfer the chemical composition to the catalyst analysis module.

16. The system of any preceding claim, wherein the catalyst synthesis module is configured to operate autonomously under the control of the control unit.

17. The system of any preceding claim, wherein the catalyst analysis module is configured to perform electrolysis using a test sample comprising the synthesised chemical composition deposited on a conductive substrate.

18. The system of any preceding claim, wherein the catalyst analysis module is configured to perform electrolysis on a plurality of test samples comprising the same chemical compositions, in parallel, under respective different testing conditions, or perform electrolysis on a plurality of test samples comprising different chemical compositions, in parallel, optionally under different respective different testing conditions.

19. The system of any preceding claim, wherein the testing conditions comprise one or more of: electrolyser components, electrolyte composition, electrolyte concentration, flow rate of electrolyte, gas concentration in the electrolyte, flow rate of gas, concentration ofgas, applied voltage, applied current, electrolyte pH, humidity of gas input, humidity of gas output, pressure and temperature.

20. The system of any preceding claim, wherein the catalyst analysis module is further configured to analyse additional properties of the synthesised chemical composition, the base materials and / or intermediate chemical compositions.

21. The system of any preceding claim, wherein the catalyst analysis module is configured to measure product composition and / or concentration during and / or after the electrolysis is performed.

22. The system of any preceding claim, wherein the catalyst analysis module comprises a gas chromatograph-mass spectrometer to measure product composition and / or concentration.

23. The system of any preceding claim, wherein the catalyst analysis module comprises an inductive coupled plasma spectroscopy to measure the catalyst concentration in the electrolyte before, during and / or after the experiment.

24. The system of any preceding claim, wherein the catalyst analysis module is configured to operate autonomously under the control of the control unit.

25. The system of any preceding claim, wherein: the catalyst synthesis module comprises a plurality of synthesis work cells, each of the plurality of synthesis work cells being configured to perform one or more processing steps to synthesise the chemical composition, at least a subset of the plurality of synthesis work cells performing optional and / or alternative processing steps, and the control module is configured to control which of the optional and / or alternative synthesis work cells are used to synthesis each chemical composition.

26. The system of claim 25, wherein the control unit is further configured to control the order in which synthesis work cells are used to synthesise the chemical composition.

27. The system of any preceding claim, wherein:the catalyst analysis module comprises a plurality of analysis work cells, each of the plurality of analysis work cells being configured to perform one or more analysis steps to analyse the chemical composition, at least a subset of the plurality of analysis work cells performing optional and / or alternative analysis steps, and the control module is configured to control which of the optional and / or alternative analysis work cells are used to analyse each chemical composition.

28. The system of claim 27, wherein the control unit is further configured to control the order in which analysis work cells are used to analyse the chemical composition.

29. The system of claim 28, optionally when dependent on claim 26, wherein the control unit is configured to determine a work flow comprising a sequence of processing steps and / or analysis steps performed by one or more synthesis work cells and / or analysis work cells for each chemical composition.

30. A system for determining catalytic properties of chemical compositions, the system comprising: a modular catalyst synthesis module configured to synthesise a chemical composition from one or more of a plurality of predefined base materials and by processing the base materials under one or more of a plurality of processing conditions, the modular catalyst synthesis module comprising a plurality of synthesis work cells, each of the plurality of synthesis work cells being configured to perform one or more processing steps to synthesise the chemical composition, at least a subset of the plurality of synthesis work cells performing optional and / or alternative processing steps; a catalyst analysis module configured to analyse the catalytic properties of the synthesised chemical composition under one or more of a plurality of testing conditions and output the analysis results; a control module configured to control the catalyst synthesis module, wherein the control module is configured to determine the base material composition, and processing conditions, for synthesising the chemical composition and determine a work flow comprising a sequence of processing steps performed by one or more of the synthesis work cells, the work flow defining which of the optional and / or alternative synthesis work cells are used to synthesis the chemical composition, and / or the order in which the synthesis work cells are used to synthesise the chemical composition.

31. The system of claim 30, wherein the control module is configured to determine a work flow, for a next chemical composition to be synthesised based on the output analysis results from the catalyst testing module for a previous chemical composition.

32. The system of claim 30 or 31, wherein the catalyst analysis module is modular and configured to analyse properties of the synthesised chemical composition, the base materials and / or intermediate chemical compositions, the modular catalyst analysis module comprising a plurality of analysis work cells, each of the plurality of analysis work cells being configured to perform one or more analysis steps, at least a subset of the plurality of analysis work cells performing optional and / or alternative analysis steps, and the work flow determined by the control module further defines which of the optional and / or alternative analysis work cells are used to analyse properties of the synthesised chemical composition, the base materials and / or intermediate chemical compositions and / or the order in which analysis work cells are used to analyse properties of the synthesised chemical composition, the base materials and / or intermediate chemical compositions.

33. The system of any one of claims 30 to 32, wherein the system is configured to execute a plurality of work flows in parallel to synthesise and analyse a plurality of different chemical compositions.

34. The system of any preceding claim, wherein the chemical composition comprises inorganic nanoparticles.

35. The system of any one of claims 25 to 34 comprising a transfer module configured to transfer the base materials, the chemical composition and / or intermediate chemical compositions between the work cells.

36. A method of autonomously determining catalytic properties of chemical compositions, the method comprising: autonomously synthesising a chemical composition, the chemical composition being synthesised from one or more of a plurality of predefined base materials and by processing the base materials under one or more of a plurality of processing conditions;autonomously analysing the catalytic properties of the synthesised chemical composition under one or more of a plurality of testing conditions and outputting the analysis results; controlling the synthesising using a control module configured to determine the base material composition, and processing conditions and / or testing conditions, for a next chemical composition to be synthesised based on the output analysis results from the catalyst testing module for a previous chemical composition.

37. A method of determining catalytic properties of chemical compositions, the system comprising, the method comprising: autonomously synthesising a chemical composition using a modular catalyst synthesis module configured to synthesise a chemical composition from one or more of a plurality of predefined base materials and by processing the base materials under one or more of a plurality of processing conditions, the modular catalyst synthesis module comprising a plurality of synthesis work cells, each of the plurality of synthesis work cells being configured to perform one or more processing steps to synthesise the chemical composition, at least a subset of the plurality of synthesis work cells performing optional and / or alternative processing steps; autonomously analysing the catalytic properties of the synthesised chemical composition using a catalyst analysis module configured to analyse the catalytic properties of the synthesised chemical composition under one or more of a plurality of testing conditions and output the analysis results; controlling the synthesising using a control module configured to control the catalyst synthesis module, wherein the control module is configured to determine the base material composition, and processing conditions, for synthesising the chemical composition and determine a work flow comprising a sequence of processing steps performed by one or more of the synthesis work cells, the work flow defining which of the optional and / or alternative synthesis work cells are used to synthesis the chemical composition, and / or the order in which the synthesis work cells are used to synthesise the chemical composition.

38. A method of identifying a chemical composition having target catalytic properties, comprising the method of claim 36 or 37.

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