Catalyst design system and method based on charge parameter adjustment and adsorption energy joint calculation

Abstract

The invention discloses a catalyst design system and method based on charge parameter adjustment and adsorption energy joint calculation. The catalyst design system comprises a file configuration module, a parameter determination module, a task management module, a carrier optimization module, an NELECT parameter calculation module, an adsorbate optimization module, a thermodynamic calculation module, an adsorption energy calculation module and a task monitoring module. Through a catalyst design system based on charge parameter adjustment and adsorption energy joint calculation, a user can automatically calculate NELECT parameters, and the requirement for manual intervention is reduced. Meanwhile, the catalyst design system can automatically select a proper geometric optimization and adsorption energy calculation method according to the input net charge. Therefore, according to the catalyst design system, the trial and error period and resource consumption are reduced, the risk of inaccurate results caused by manual calculation errors is reduced, the research and development efficiency of the catalyst is greatly improved, and powerful support is provided for practical industrial application of the catalyst.

Description

Technical Field

[0001] The present application relates to the field of catalyst design, and particularly to a catalyst design system and method based on charge parameter adjustment and adsorption energy coupling calculation. Background Art

[0002] Traditional catalyst design methods face various challenges in the process of developing highly efficient catalysts, such as screening processes, trial-and-error cycles, and resource consumption. Specifically, the screening of catalysts usually requires a large number of experiments and theoretical calculations to determine the optimal material structure, composition, and adsorption sites, which is a complex and time-consuming process. In addition, traditional research and development methods rely on a large number of manual operations, such as parameter adjustment, geometric optimization, and adsorption energy calculation, which not only require professional computational chemistry knowledge but also involve cumbersome operations and repeated experimental designs.

[0003] Computational simulation is one of the important research tools in catalytic research, but it still faces many challenges in practical applications. Among them, the reasonable setting of the NELECT parameter is the key, which determines the total number of electrons in the simulation system and thus affects the electronic structure and stability of the system. Usually, the NELECT parameter needs to be manually calculated according to the information in the POSCAR and POSCAR files and pre-set in the INCAR file. However, the manual calculation process of the NELECT parameter for multi-atom systems is very cumbersome and prone to errors, which will inevitably increase the complexity and error rate of the calculation.

[0004] In terms of the calculation of the adsorption energy of the catalyst and adsorbate system, traditional methods are applicable to the case of proximal adsorption of adsorbate small molecules with a net charge of zero. When the net charge of the adsorbate small molecule is not zero, the formula needs to be adjusted. This is due to the influence of periodic boundary conditions, and the charge distribution of the adsorbate and its interaction with the catalyst will change significantly. Therefore, it is necessary to fully consider this charge transfer effect to eliminate the influence of the net charge of the adsorbate on the adsorption energy calculation, so as to ensure more accurate results.

[0005] Therefore, how to simplify and accelerate the geometric optimization and adsorption energy calculation process of catalysts and achieve the rapid screening of highly efficient catalysts has become an urgent problem to be solved in this field. Summary of the Invention

[0006] The present application provides a catalyst design system and method based on charge parameter adjustment and adsorption energy coupling calculation, aiming to simplify and accelerate the geometric optimization and adsorption energy calculation process of catalyst materials.

[0007] To achieve the above object, the present application provides the following technical solutions:

[0008] A catalyst design system based on charge parameter adjustment and adsorption energy coupling calculation, comprising:

[0009] A file configuration module for configuring a script set, a catalyst structure file, and an adsorbate system structure file; the script set includes slab.py, NELECT.py, adsorbate-NELECT.py, far-adsorbate-NELECT.py, thermal.py, binding.py, and far-binding.py; the catalyst structure file is used to characterize the structure of the support material, and the adsorbate system structure file is used to characterize the structure of the adsorbate small molecule;

[0010] A parameter determination module for determining experimental parameters input by the user; the experimental parameters at least include a support material, an adsorbate small molecule, an adsorption site, and a net charge;

[0011] A support optimization module for calling the slab.py script to perform geometric optimization on the support material;

[0012] A NELECT parameter calculation module for calling the NELECT.py script to determine the NELECT parameter matching the net charge and writing the NELECT parameter into the INCAR file;

[0013] An adsorbate optimization module for calling the adsorbate-NELECT.py script and judging whether to call the far-adsorbate-NELECT.py script according to the net charge to perform geometric optimization on the adsorbate system and update the NELECT parameter in the INCAR file;

[0014] A thermodynamics calculation module for calling the thermal.py script to perform thermodynamics analysis on the catalyst and the adsorbate system;

[0015] An adsorption energy calculation module for screening a target script from the binding.py script and the far-binding.py script according to the net charge, calling the target script to determine the adsorption energy calculation result of the adsorbate system, and saving the adsorption energy calculation result to a specified CSV file.

[0016] Optionally, the script set further includes a flow-binding.py script, and the system further includes:

[0017] The task management module is used to call the flow-binding.py script to perform the status management and scheduling of multiple tasks; the multiple tasks include a carrier optimization task, a NELECT parameter calculation task, an adsorbate optimization task, a thermodynamic calculation task, and an adsorption energy calculation task. Among them, the carrier optimization task is assigned to the carrier optimization module, the NELECT parameter calculation task is assigned to the NELECT parameter calculation module, the adsorbate optimization task is assigned to the adsorbate optimization module, the thermodynamic calculation task is assigned to the thermodynamic calculation module, and the adsorption energy calculation task is assigned to the adsorption energy calculation module.

[0018] Optionally, the system further includes:

[0019] The task monitoring module is used to record the key information during the execution of the multiple tasks, detect the running status of the multiple tasks, and when the running status of any task is abnormal, back up and restart the any task.

[0020] Optionally, the types of the adsorbate systems include a first system and a second system. The first system represents that the adsorbate small molecules are located on the carrier material, and the second system represents that the adsorbate small molecules are at a relatively far adsorption distance. The adsorbate optimization module is specifically used for:

[0021] When the net charge is zero, call the adsorbate-NELECT.py script to perform geometric optimization on the adsorbate system; the adsorbate-NELECT.py script is used to perform geometric optimization on the first system;

[0022] When the net charge is not zero, call the adsorbate-NELECT.py script and the far-adsorbate-NELECT.py script to perform geometric optimization on the adsorbate system; the far-adsorbate-NELECT.py script is used to perform geometric optimization on the second system.

[0023] Optionally, the adsorption energy calculation module is specifically used for:

[0024] Based on the thermodynamic analysis results of the catalyst and the adsorbate system, obtain key energy parameters; the key energy parameters include , , and ;

[0025] When the net charge is zero, it is determined as the target script based on the binding.py script; the binding.py script is used to substitute the key energy parameter into the first formula to calculate the adsorption energy calculation result ; The first formula is ;

[0026] When the net charge is not zero, it is determined as the target script based on the far-binding.py script; the far-binding.py script is used to substitute the key energy parameter into the second formula to calculate the adsorption energy calculation result ; The second formula is 。

[0027] Optionally, the file configuration module is further configured to:

[0028] Construct the catalyst structure file according to the specified first process; the specified first process is: using a three-dimensional modeling process to generate a periodic box corresponding to the carrier material; adding corresponding adsorption sites to the periodic box; determining the structure of the carrier material based on the periodic box with the added adsorption sites; generating the catalyst structure file based on the structure of the carrier material.

[0029] Optionally, the file configuration module is further configured to:

[0030] Construct the adsorbate system structure file according to the specified second process; the specified second process is: using a three-dimensional modeling process to generate the initial structure of the adsorbate small molecule; generating a corresponding pdb file based on the initial structure; using a visualization process to set specified parameters in the pdb file to obtain a visualization file, which represents the molecular system of the initial structure; using a molecular mechanics calculation process to optimize and converge the molecular system to obtain an fchk file; converting the fchk file into a target pdb file; using the three-dimensional modeling process to generate a periodic box corresponding to the molecular system shown in the target pdb file; performing geometric optimization on the periodic box to obtain the optimized structure of the adsorbate small molecule; generating the adsorbate system structure file based on the optimized structure.

[0031] A catalyst design method based on charge parameter adjustment and adsorption energy joint calculation, including:

[0032] Configure a set of scripts, a catalyst structure file, and an adsorbate system structure file; the set of scripts includes the slab.py script, the NELECT.py script, the adsorbate-NELECT.py script, the far-adsorbate-NELECT.py script, the thermal.py script, the binding.py script, and the far-binding.py script; the catalyst structure file is used to characterize the structure of the support material, and the adsorbate system structure file is used to characterize the structure of the adsorbate small molecule;

[0033] Determine the experimental parameters input by the user; the experimental parameters at least include the support material, the adsorbate small molecule, the adsorption site, and the net charge;

[0034] Call the slab.py script to perform geometric optimization on the support material;

[0035] Call the NELECT.py script to determine the NELECT parameter matching the net charge and write the NELECT parameter into the INCAR file;

[0036] Call the adsorbate-NELECT.py script and determine whether to call the far-adsorbate-NELECT.py script according to the net charge, perform geometric optimization on the adsorbate system, and update the NELECT parameter in the INCAR file;

[0037] Call the thermal.py script to perform thermodynamic analysis on the catalyst and the adsorbate system;

[0038] According to the net charge, screen the target script from the binding.py script and the far-binding.py script, call the target script, determine the adsorption energy calculation result of the adsorbate system, and save the adsorption energy calculation result to a specified CSV file.

[0039] A storage medium, the storage medium includes a stored program, wherein the program, when run by a processor, executes the catalyst design method based on charge parameter adjustment and adsorption energy joint calculation.

[0040] An electronic device, including: a processor, a memory, and a bus; the processor is connected to the memory through the bus;

[0041] The memory is used to store a program, and the processor is used to run the program, wherein the program, when run by the processor, executes the catalyst design method based on charge parameter adjustment and adsorption energy joint calculation.

[0042] The catalyst design system based on the joint calculation of charge tuning and adsorption energy provided by this application includes a file configuration module, a parameter determination module, a task management module, a carrier optimization module, a NELECT parameter calculation module, an adsorbate optimization module, a thermodynamics calculation module, an adsorption energy calculation module, and a task monitoring module. Through this catalyst design system, the combination of real-time dynamic regulation of charge state and precise automatic correction technology of the geometric configuration of catalyst-reaction intermediates breaks through the technical bottlenecks in the traditional catalyst design process, such as inaccurate parameter adjustment, low screening efficiency, long trial-and-error cycle, and high resource consumption. By adaptively and automatically selecting a suitable adsorption energy calculation method according to the net charge state, the efficient and accurate prediction of the performance indicators of catalytic materials is realized, significantly improving the catalyst screening efficiency, greatly shortening the R & D cycle, and reducing resource consumption. The automation characteristics and adaptive ability of this catalyst design system enable it to have a wide range of application prospects in many fields such as energy conversion, environmental purification, fine chemical industry, and new material development, and can significantly accelerate the industrialization process of high-performance catalytic materials. Description of the Drawings

[0043] In order to more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0044] Figure 1 It is a schematic diagram of the architecture of a catalyst design system based on the joint calculation of charge tuning and adsorption energy provided by an embodiment of this application;

[0045] Figure 2 It is a schematic diagram of the execution logic of a script provided by an embodiment of this application;

[0046] Figure 3 It is another schematic diagram of the execution logic of a script provided by an embodiment of this application;

[0047] Figure 4 It is yet another schematic diagram of the execution logic of a script provided by an embodiment of this application;

[0048] Figure 5 It is a schematic diagram of a task submission process provided by an embodiment of this application;

[0049] Figure 6 It is a schematic diagram of the process of a catalyst design method based on the joint calculation of charge tuning and adsorption energy provided by an embodiment of this application;

[0050] Figure 7Schematic flowchart of another catalyst design method based on charge parameter adjustment and adsorption energy calculation provided by an embodiment of the present application;

[0051] Figure 8 Adsorption energy histogram provided by an embodiment of the present application. Detailed implementation manners

[0052] Next, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0053] In the present application, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. The term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0054] As Figure 1 shown, it is a schematic architecture diagram of a catalyst design system based on charge parameter adjustment and adsorption energy calculation provided by an embodiment of the present application, including the following modules.

[0055] File configuration module 100, parameter determination module 200, task management module 300, carrier optimization module 400, NELECT parameter calculation module 500, adsorbate optimization module 600, thermodynamic calculation module 700, adsorption energy calculation module 800, and task monitoring module 900.

[0056] The file configuration module 100 is used to configure the script set, the catalyst structure file, and the adsorbate system structure file; the script set includes the flow-binding.py script, the slab.py script, the NELECT.py script, the adsorbate-NELECT.py script, the far-adsorbate-NELECT.py script, the thermal.py script, the binding.py script, and the far-binding.py script; the catalyst structure file is used to characterize the structure of the carrier material, and the adsorbate system structure file is used to characterize the structure of the adsorbate small molecule.

[0057] In some examples, the file configuration module 100 can pre-build a task directory, build a Support / directory under the task target, upload the flow-binding.py script, the slab.py script, the NELECT.py script, the adsorbate-NELECT.py script, the far-adsorbate-NELECT.py script, the thermal.py script, the binding.py script, and the far-binding.py script to the Support / directory, and grant each script the corresponding executable permission.

[0058] In some examples, the script set also includes auxiliary scripts such as the backup.sh script, the getE.sh script, the getG.sh script, the r2t.sh script, and the rcheck.sh script.

[0059] In some examples, the file configuration module 100 can also build a bin / directory under the task target, upload the backup.sh script, the getE.sh script, the getG.sh script, the r2t.sh script, and the rcheck.sh script to the bin / directory, grant each script the corresponding executable permission, and pre-compile the code in each script.

[0060] Optionally, the file configuration module 100 is further used to: build the catalyst structure file according to the specified first process; the specified first process is: use a three-dimensional modeling process to generate the periodic box corresponding to the carrier material; add corresponding adsorption sites to the periodic box; determine the structure of the carrier material based on the periodic box with added adsorption sites; generate the catalyst structure file based on the structure of the carrier material.

[0061] In some examples, the three-dimensional modeling process can be the Materials Studio software.

[0062] In some examples, the VASP software based on plane wave basis set for calculations can also be used to perform geometric optimization on the periodic box corresponding to the carrier material.

[0063] In some examples, the VESTA software can also be used to add corresponding adsorption sites in the periodic box.

[0064] In some examples, the file format of the catalyst structure file is a cif file. Uploading the catalyst structure file to the Support / directory can achieve the configuration of the catalyst structure file.

[0065] Optionally, the file configuration module 100 is further configured to: construct an adsorbate system structure file according to a specified second process; the specified second process is: generate an initial structure of an adsorbate small molecule using a three-dimensional modeling process; generate a corresponding pdb file based on the initial structure; use a visualization process to set specified parameters in the pdb file to obtain a visualization file, where the visualization file represents the molecular system of the initial structure; use a molecular mechanics calculation process to optimize and converge the molecular system to obtain an fchk file; convert the fchk file into a target pdb file; generate a periodic box corresponding to the molecular system shown in the target pdb file using a three-dimensional modeling process; perform geometric optimization on the periodic box to obtain an optimized structure of the adsorbate small molecule; generate an adsorbate system structure file based on the optimized structure.

[0066] In some examples, the visualization process can be the gauss view software, the file format of the visualization file can be a gif file, the molecular mechanics calculation process can be the Gaussian16 software, and the file format of the adsorbate system structure file can be an xyz coordinate file.

[0067] In some examples, the initial structure of the adsorbate small molecule can be constructed in Materials Studio software, or the initial structure of the adsorbate small molecule can be obtained with the help of PubChem software, and the initial structure is converted into a pdb file through Materials Studio software. Then, the.pdb file is opened with the help of gauss view software, and the corresponding task type, molecular net charge, electronic multiplicity, and the content of parts such as the calculation environment, resources, methods, and basis sets are set to generate the corresponding gif file. The molecular system is optimized and converged by Gaussian16 software based on the atomic basis set. The obtained fchk file is opened with gauss view software, converted into a pdb file and then imported into Materials Studio software. After adding a periodic box identical to the carrier material to the molecular system, it is exported as a cif file. With the help of VASP software, the molecular system is geometrically optimized again in the Support / directory, and then the optimized CONTCAR structure (a specific form of the optimized structure) is exported, and the CONTCAR structure is converted into an xyz coordinate file through VESTA software and also uploaded to the Support / directory, and the configuration of the adsorbate system structure file can be completed.

[0068] The parameter determination module 200 is used to determine the experimental parameters input by the user; the experimental parameters at least include the carrier material, the adsorbate small molecule, the adsorption site, the net charge, and the number of top-layer atoms of the catalyst to be released.

[0069] In some examples, the user can obtain experimental parameters such as the name of the carrier material, the name of the adsorbate small molecule, the adsorption site, the net charge, and the number of top-layer atoms of the catalyst to be released through the command line. If the experimental parameters input by the user are incomplete, the parameter determination module 200 will also display an error prompt and exit the experimental task.

[0070] The task management module 300 is used to call the flow-binding.py script to perform the status management and scheduling work of multiple tasks; the multiple tasks include the carrier optimization task, the NELECT parameter calculation task, the adsorbate optimization task, the thermodynamic calculation task, and the adsorption energy calculation task. Among them, the carrier optimization task is assigned to the carrier optimization module, the NELECT parameter calculation task is assigned to the NELECT parameter calculation module, the adsorbate optimization task is assigned to the adsorbate optimization module, the thermodynamic calculation task is assigned to the thermodynamic calculation module, and the adsorption energy calculation task is assigned to the adsorption energy calculation module.

[0071] In some examples, the task management module 300 uses the SLURM scheduling system to achieve queuing, submission, monitoring, and status feedback of each task.

[0072] In some examples, the task management module 300 uses the enumeration type TASK_STATUS to manage the status of each task, such as "not executed", "in progress", "completed", "failed", etc., to ensure that the status of the task can be tracked during the task execution process.

[0073] In a possible implementation manner, the specific process of the carrier optimization task can be: check whether the directory for carrier optimization exists, and automatically create it if it does not exist; submit the carrier optimization job (which can be implemented by calling the slab.py script) and monitor the status of the carrier optimization job; check whether the key output file (such as the OUTCAR file) exists and contains a preset success flag, and if the condition is not met, call the backup script and resubmit the carrier optimization job until the requirements are met.

[0074] In a possible implementation manner, the specific process of the adsorbate optimization task can be: by calling the adsorbate-NELECT.py script, combine, translate, and layer the adsorbate with the carrier material in a predetermined target directory and generate a VASP input file; when the net charge is not equal to zero, by additionally calling the far-adsorbate-NELECT.py script, perform adsorbate geometry optimization at an adjusted adsorption distance in a predetermined target directory (with a "far-" prefix) and generate the corresponding VASP input file.

[0075] In a possible implementation manner, the specific process of the thermodynamic calculation task can be: submit a job in a specified thermodynamic calculation directory (for example, by calling the thermal.py script and the r2t.sh script), and confirm the completion of the calculation by detecting keywords such as "Total CPU time" in the OUTCAR file; start an automatic backup and resubmission process when the task is abnormal.

[0076] In a possible implementation manner, the specific process of the adsorption energy calculation task can be: based on the output file generated in the adsorbate geometry optimization stage, determine the binding energy calculation method according to the net charge. When the net charge is equal to zero, call the binding.py script to determine the adsorption energy calculation result. When the net charge is not equal to zero, call the far-binding.py script to determine the adsorption energy calculation result, and save the adsorption energy calculation result to a CSV file for subsequent data statistics and comparison.

[0077] The carrier optimization module 400 is used to call the slab.py script to perform geometric optimization on the carrier material.

[0078] In some examples, the carrier optimization module 400 is responsible for performing carrier optimization tasks (by calling the slab.py script). If a corresponding carrier optimization job is already running in the target directory, the slab.py script will skip the carrier optimization task; if the carrier optimization job has been completed, it will check and execute the necessary post-processing steps to ensure the smooth progress of the carrier optimization task.

[0079] The NELECT parameter calculation module 500 is used to call the NELECT.py script to determine the NELECT parameters matching the net charge and write the NELECT parameters into the INCAR file.

[0080] In some examples, as shown in Figure 2 the execution logic of the NELECT.py script can be as follows: (1) Read the experimental parameters (including the carrier material, the name of the adsorbate small molecule, and the net charge) from the command line; (2) Obtain the path where the NELECT.py script is located; (3) Check whether the POSCAR and POSCAR files exist and read the content in the POSCAR file; (4) Calculate the numerical value of the NELECT parameter based on the "ZVAL" in the POSCAR, the "count" of each atom in the POSCAR file, and the net charge number (net_charge); (5) Write the numerical value of the NELECT parameter into the INCAR file and then perform the subsequent adsorbate optimization task.

[0081] In a possible implementation, the NELECT parameter calculation module 500 can use the pymatgen library to read the element information (such as the ZVAL value and the number of atoms) in the POTCAR and POSCAR files and calculate the corresponding NELECT based on the element information.

[0082] The adsorbate optimization module 600 is used to call the adsorbate-NELECT.py script and determine whether to call the far-adsorbate-NELECT.py script based on the net charge, perform geometric optimization on the adsorbate system, and update the NELECT parameter in the INCAR file.

[0083] Optionally, the types of adsorbate systems include a first system and a second system. The first system represents that the adsorbate small molecules are located on the carrier material, and the second system represents that the adsorbate small molecules are at a relatively long adsorption distance. The adsorbate optimization module 600 is specifically configured to: when the net charge is zero, call the adsorbate-NELECT.py script to perform geometric optimization on the adsorbate system; the adsorbate-NELECT.py script is used to perform geometric optimization on the first system; when the net charge is not zero, call the adsorbate-NELECT.py script and the far-adsorbate-NELECT.py script to perform geometric optimization on the adsorbate system; the far-adsorbate-NELECT.py script is used to perform geometric optimization on the second system.

[0084] In some examples, the adsorbate-NELECT.py script is responsible for binding the adsorbate small molecules to the carrier material, performing surface stratification and adsorbate translation on the adsorbate small molecules and the carrier material, generating corresponding VASP input files, and calling the NELECT.py script to update the NELECT parameter in the INCAR.

[0085] In some examples, the far-adsorbate-NELECT.py script is responsible for implementing geometric optimization of the adsorbate at a relatively long adsorption distance, automatically adjusting the translation distance of the adsorbate, and achieving geometric optimization of the adsorbate at the adjusted adsorption distance in a predetermined target directory (with a "far-" prefix), generating corresponding VASP input files, and simultaneously updating the NELECT parameter in the INCAR file.

[0086] The thermodynamic calculation module 700 is used to call the thermal.py script to perform thermodynamic analysis of the catalyst and the adsorbate system.

[0087] In some examples, the thermodynamic calculation module 700 is used to submit a thermodynamic calculation job to complete the thermodynamic analysis of the catalyst and the adsorbate system. It can also confirm whether the thermodynamic analysis is completed by checking the "Total CPU time" information in the OUTCAR file, and resubmit or perform a backup according to the status of the thermodynamic calculation job.

[0088] The adsorption energy calculation module 800 is used to screen the target script from the binding.py script and the far-binding.py script according to the net charge, call the target script to determine the adsorption energy calculation result of the adsorbate system, and save the adsorption energy calculation result to a specified CSV file.

[0089] Optionally, the adsorption energy calculation module 800 is specifically configured to: obtain key energy parameters based on the thermodynamic analysis results of the catalyst and adsorbate system; the key energy parameters include , , and ; when the net charge is zero, based on the binding.py script, it is determined as the target script; the binding.py script is used to substitute the key energy parameters into the first formula to calculate the adsorption energy calculation result ; the first formula is ; when the net charge is not zero, based on the far-binding.py script, it is determined as the target script; the far-binding.py script is used to substitute the key energy parameters into the second formula to calculate the adsorption energy calculation result ; the second formula is .

[0090] In some examples, represents the magnitude of the adsorption energy, represents the energy magnitude of the first system, represents the energy magnitude of the support material, represents the energy magnitude of the adsorbate small molecule, represents the energy magnitude of the second system.

[0091] In a possible implementation, the adsorption energy calculation module 800 can obtain the thermodynamic analysis results of the catalyst and adsorbate system from the OUTCAR file.

[0092] In some examples, as shown in Figure 3 , the execution logic of the binding.py script can be: (1) read experimental parameters from the command line; (2) obtain the paths where each file (such as each OUTCAR file) is located; (3) read from the OUTCAR file in the optimized adsorbate directory; read and respectively from the OUTCAR files in the optimized support and catalyst system directories; calculate using the first formula and output it in CSV format.

[0093] In some examples, as shown in Figure 4As shown in the figure, the execution logic of the far-binding.py script can be as follows: (1) Run the far-binding.py script when the net charge is not 0; (2) Read the experimental parameters from the command line; (3) Obtain the paths where each file (such as each OUTCAR file) is located; (4) Read and from the OUTCAR files in the catalytic system directories of the optimized proximal adsorption (i.e., the first system) and distal adsorption (i.e., the second system) respectively; (5) Calculate using the second formula and output it in CSV format.

[0094] The task monitoring module 900 is used to record the key information during the execution of multiple tasks, detect the running status of multiple tasks, and when the running status of any task is abnormal, back up and restart any task.

[0095] In some examples, the task monitoring module 900 includes a log recording unit, a status detection unit, and a backup and resubmission process unit.

[0096] In a possible implementation manner, the log recording unit is used to record the key information during the submission, execution, monitoring, and retry of each task. Specifically, the key information includes but is not limited to the task submission time, status information, error prompt, and retry situation.

[0097] In a possible implementation manner, the status detection unit is used to parse the SLURM job queue and the key output files, and real-time feedback the running status of each task. The so-called job can be understood as the process obtained by instantiating the task.

[0098] In a possible implementation manner, the backup and resubmission process unit is used to automatically call the backup script and resubmit the job when a task exception is detected, ensuring the reliability and robustness of the overall process.

[0099] In some examples, the monitoring process of the task monitoring module 900 for the carrier optimization task can be summarized as follows: (1) Detect whether the target directory for carrier optimization exists. If not, call the preset script to create the target directory; (2) Use the Shell script (or the rcheck.sh script) to detect the preset success flag in the OUTCAR file; (3) When it is detected that the carrier optimization task fails or the output file does not meet the expectations, call the backup script (such as the backup.sh script) for backup and resubmit the carrier optimization job until the preset retry times are reached or the carrier optimization task is successfully completed.

[0100] In some examples, the task monitoring module 900 implements the submission process of each task, which can be seen in Figure 5 as shown.

[0101] It should be emphasized that through the catalyst design system based on charge parameter adjustment and adsorption energy coupling calculation shown in this application, users can efficiently and accurately complete tasks such as geometric optimization, adsorption energy calculation, and thermodynamic analysis of catalysts. The following goals are specifically achieved: (1) Automatically calculate and adjust the NELECT parameter: The system can automatically calculate the NELECT parameter and adjust this NELECT parameter according to the net charge of different systems, avoiding the cumbersome process of manual calculation and setting; (2) Automatically select the adsorption energy calculation method: According to the net charge situation of the adsorbate, the system can automatically select the calculation method of adsorption energy to ensure the correct selection of the calculation formula; (3) Automated task management and error handling: The system can automatically submit calculation tasks, monitor the task progress, and automatically perform backup and resubmission processes when the task fails to ensure the smooth progress of the calculation task; (4) Improve calculation efficiency and accuracy: Through the automated workflow, manual intervention is reduced, human errors are avoided, and the calculation efficiency and the accuracy of the results are improved.

[0102] Based on the above-mentioned various modules, the catalyst design system based on charge parameter adjustment and adsorption energy coupling calculation can greatly simplify the R & D process of catalysts, significantly shorten the R & D cycle, effectively reduce the calculation error rate, greatly improve the catalyst screening efficiency, and through automated task management, accurately calculate the NELECT parameter and adsorption energy, and then automatically select the calculation method according to the net charge, and can improve the calculation accuracy and efficiency of catalyst design, thereby accelerating the development and industrial application of catalysts.

[0103] As Figure 6 shown, it is a schematic flowchart of a catalyst design method based on charge parameter adjustment and adsorption energy coupling calculation provided by an embodiment of this application, including the following steps.

[0104] S601: Configure the script set, catalyst structure file, and adsorbate system structure file.

[0105] Among them, the script set includes the slab.py script, NELECT.py script, adsorbate-NELECT.py script, far-adsorbate-NELECT.py script, thermal.py script, binding.py script, and far-binding.py script; the catalyst structure file is used to characterize the structure of the carrier material, and the adsorbate system structure file is used to characterize the structure of the adsorbate small molecule.

[0106] S602: Determine the experimental parameters input by the user.

[0107] Among them, the experimental parameters at least include the carrier material, adsorbate small molecule, adsorption site, and net charge.

[0108] S603: Call the slab.py script to perform geometric optimization on the carrier material.

[0109] S604: Call the NELECT.py script to determine the NELECT parameter matching the net charge and write the NELECT parameter to the INCAR file.

[0110] S605: Call the adsorbate-NELECT.py script and determine whether to call the far-adsorbate-NELECT.py script based on the net charge, perform geometric optimization on the adsorbate system, and update the NELECT parameter in the INCAR file.

[0111] S606: Call the thermal.py script to perform thermodynamic analysis on the catalyst and adsorbate system.

[0112] S607: Screen the target script from the binding.py script and the far-binding.py script according to the net charge, call the target script, determine the adsorption energy calculation result of the adsorbate system, and save the adsorption energy calculation result to the specified CSV file.

[0113] It should be noted that during the process of configuring the script set, the catalyst structure file, and the adsorbate system structure file, it involves the construction of the directory structure (i.e., the task directory), the construction of the structure of the catalyst carrier material (i.e., creating the catalyst structure file), and the construction of the structure of the adsorbate small molecule (i.e., creating the adsorbate system structure file).

[0114] In a possible implementation, the process of constructing the directory structure can be as follows: Construct a Support / directory under the task directory, and upload the flow-binding.py script, slab.py script, adsorbate-NELECT.py script, far-adsorbate-NELECT.py script, NELECT.py script, thermal.py script, binding.py script, and far-binding.py script to the Support / directory and grant the corresponding executable permissions. At the same time, upload the backup.sh script, getE.sh script, getG.sh script, r2t.sh script, and rcheck.sh script to the bin / directory of the home directory, grant executable permissions to the files, and the code in these scripts can be pre-compiled.

[0115] In a possible implementation, the process of constructing the structure of the catalyst support material can be as follows: construct the structure of the target support in the MaterialsStudio software. Since this invention mainly uses the VASP software based on plane wave basis sets to perform geometric optimization, it is necessary to determine the size of the material periodic box. After construction, export the cif file. At the same time, the VESTA software can be used to determine the corresponding adsorption sites. Upload the cif file of the support to the Support / directory to complete the preparation of the support material.

[0116] In a possible implementation, the process of constructing the structure of the adsorbate small molecule can be as follows: First, construct the structure of the target adsorbate in the MaterialsStudio software, or obtain the structure of the target adsorbate with the help of the PubChem software, and convert the initial molecular system into a pdb file through the Materials Studio software. Then open the pdb file in the gauss view software and set the corresponding task type, molecular net charge, electronic multiplicity, and the content of parts such as the calculation environment, resources, methods, and basis sets to generate the corresponding gif file. Optimize and converge the molecular system through the Gaussian16 software based on atomic basis sets. The obtained fchk file is opened in the gauss view software, converted into a pdb file and then imported into the Materials Studio software. After adding the same periodic box as the support material to the molecular system, export it as a cif file. With the help of the VASP software, perform geometric optimization on the molecular system again in the Support / directory, then export the optimized CONTCAR structure, and convert it into an xyz coordinate file through the VESTA software, which is also uploaded to the Support / directory to complete the preparation of the adsorbate small molecule.

[0117] In some examples, after completing the configuration script set, the catalyst structure file, and the adsorbate system structure file, the operating environment of the catalyst design system based on charge tuning and adsorption energy joint calculation (such as the Python environment) can be activated. Enter the command: "python flow-binding.py; support material; adsorbate small molecule; adsorption site; net charge" (the input variable of the number of top-layer atoms of the catalyst to be released can be determined in the script in advance) in the command line to start a series of automated calculations, and multiple adsorbates can be submitted simultaneously in this process.

[0118] In some examples, after completing the adsorption energy calculation, the adsorption energy calculation results in the specified CSV file can be used for processing and plotting. At the same time, different adsorption sites can be selected according to the adsorption energy calculation results, or different support material structures can be constructed to conduct experiments again.

[0119] In a possible implementation, the processes shown in S601 - S607 can also be summarized as Figure 7 the following steps: constructing the structures of the catalyst support and the adsorbate small molecules; inputting relevant parameters, including the material name, adsorbate name, adsorption site, net charge, and the number of released top-layer atoms; performing geometric optimization on the support material; calculating the value of the NELECT parameter according to the net charge to achieve dynamic parameter adjustment; performing geometric optimization on the system of the adsorbate adsorbed on the support material; whether the net charge is 0; if the net charge is 0, then perform thermodynamic calculations to conduct a thermodynamic analysis of the catalyst and adsorbate system, and use a method to calculate the adsorption energy; if the net charge is not 0, perform geometric optimization on the system of the adsorbate at a relatively far adsorption distance, and use a method to calculate the adsorption energy; output the adsorption energy data in the CSV file format.

[0120] Based on the processes shown in S601 - S607 above, the application of the catalyst design system based on charge parameter adjustment and joint calculation of adsorption energy can effectively simplify and accelerate the geometric optimization and adsorption energy calculation processes of catalyst materials, greatly improving the research and development efficiency of catalysts.

[0121] In a possible implementation, for the operation and usage method of the catalyst design system based on charge parameter adjustment and joint calculation of adsorption energy, the realized catalyst experiment process can be referred to the following Examples 1 - 4.

[0122] Example 1 is as follows: The hydrogen oxalate ion adsorbs in a horizontal form at the Fe atomic site on the iron single-atom support. With the help of the catalyst design system based on charge parameter adjustment and joint calculation of adsorption energy, geometric optimization is respectively performed on the catalyst support and the overall catalytic system after adsorption, and at the same time, calculations such as thermodynamic free energy correction and adsorption energy are carried out, as Figure 8 shown. The specific implementation steps are as follows, Steps 1 - 3.

[0123] Step 1: First, construct the Fe-N4 single-atom (SA) material on a carbon substrate in the Materials Studio software, place it in a box with ABC being 25.5651, 17.2200, and 35.0000 respectively, export it as the Fe-SA.cif file, and upload it to the Support / directory.

[0124] Step 2: Construct the molecular structure of hydrogen oxalate (HC2O4-) in Materials Studio software, export it as a pdb file. In Gaussian View software, set the net charge of the system to -1. At the same time, select the UB3LYP hybrid functional and the DEF2TZVP triple zeta basis set. After supplementing the remaining parameters, export it as an HC2O4.gif file. Optimize the molecule using Gaussian16 software and obtain the HC2O4.fchk file through conversion. Open the HC2O4.fchk file in Gaussian View software, convert it to a pdb file and then import it into Materials Studio software. Add a periodic box to the molecular system that is the same as the carrier material, that is, the ABC sizes of the box are 25.5651, 17.2200, and 35.0000. Then export it as an HC2O4.cif file and upload it to the Support / directory. Use VASP software to geometrically optimize the hydrogen oxalate molecule again, then export the optimized CONTCAR structure and convert it to an HC2O4.xyz coordinate file using VESTA software, and also upload it to the Support / directory.

[0125] Step 3: Enter the Support / directory and start pymatgen. Set the adsorption site on the single iron atom. Given that the atomic number of the Fe atom is 1, the adsorption site is 0. Then enter the command "python flow-binding.py Fe-SA HC2O4 0 -1" in the command line in this directory to start the automated workflow calculation. Thus, from the generated Eads.csv file, it can be obtained that the energy of the single iron atom carrier is -1535.64 eV, the total energy of the system where the hydrogen oxalate ion is adsorbed horizontally on the Fe atom adsorption site of the carrier is -1587.25 eV, the adsorption energy is -1.03 eV, and at the same time, the free energy correction value of 0.80 eV can also be obtained, and the total energy of the system when the hydrogen oxalate ion is adsorbed distally is -1586.21 eV, etc.

[0126] Example 2: Take the adsorption of hydrogen oxalate ions on the Fe atom site of an iron cluster (AC) carrier. Use the automated workflow system to geometrically optimize the catalyst carrier and the overall catalytic system after adsorption respectively, and at the same time perform calculations on parts such as thermodynamic free energy correction and adsorption energy, as Figure 8 shown.

[0127] In Example 2, the Fe atom number of the selected adsorption site is 15, and the adsorption site is 14. Then, from the generated Eads.csv file, it can be obtained that the energy of the iron cluster carrier is -1613.24 eV, the total energy of the system where the hydrogenoxalate ion is adsorbed on the Fe atom adsorption site of the carrier in a horizontal form is -1665.80 eV, the adsorption energy is -1.99 eV, and at the same time, the free energy correction value of 0.79 eV can also be obtained. The total energy of the system when the hydrogenoxalate ion is adsorbed distally is -1663.80 eV and other data.

[0128] It should be noted that the construction of the carrier (i.e., the adsorbed small molecule), the geometric optimization of the adsorbed small molecule, and the startup method of the catalyst design system based on charge tuning and adsorption energy calculation in Example 2 refer to the steps shown in Example 1.

[0129] Example 3: With the hydrogenoxalate ion adsorbed on the Fe single-atom site of the iron single atom and iron cluster carrier, the automated workflow system is used to geometrically optimize the catalyst carrier and the overall catalytic system after adsorption respectively, and at the same time, calculate the thermodynamic free energy correction and adsorption energy and other parts, as Figure 8 shown.

[0130] In Example 3, the Fe atom number of the selected adsorption site is 16, and the adsorption site is 15. Then, from the generated Eads.csv file, it can be obtained that the energy of the iron single atom and iron cluster carrier is -1589.82 eV, the total energy of the system where the hydrogenoxalate ion is adsorbed on the Fe atom adsorption site of the carrier in a horizontal form is -1642.83 eV, the adsorption energy is -2.49 eV, and at the same time, the free energy correction value of 0.79 eV can also be obtained. The total energy of the system when the hydrogenoxalate ion is adsorbed distally is -1640.34 eV and other data.

[0131] It should be noted that the construction of the carrier (i.e., the adsorbed small molecule), the geometric optimization of the adsorbed small molecule, and the startup method of the catalyst design system based on charge tuning and adsorption energy calculation in Example 3 refer to the steps shown in Example 1.

[0132] Example 4: With the hydrogenoxalate ion adsorbed on the Fe cluster site of the iron single atom and iron cluster carrier, the automated workflow system is used to geometrically optimize the catalyst carrier and the overall catalytic system after adsorption respectively, and at the same time, calculate the thermodynamic free energy correction and adsorption energy and other parts, as Figure 8 shown.

[0133] In Example 4, the Fe atom number of the selected adsorption site is 15, and the adsorption site is 14. Then, from the generated Eads.csv file, it can be obtained that the energy of the single Fe atom and the Fe cluster carrier is -1589.82 eV. The total energy of the system where the hydrogenoxalate ion is adsorbed on the Fe atom adsorption site of the carrier in a horizontal form is -1642.35 eV, the adsorption energy is -1.99 eV, and at the same time, the free energy correction value of 0.82 eV can also be obtained. The total energy of the system when the hydrogenoxalate ion is adsorbed distally is -1640.36 eV and other data.

[0134] It should be noted that for the construction of the carrier and the adsorbed small molecule, the geometric optimization of the adsorbed small molecule, and the startup method of the catalyst design system based on charge tuning and adsorption energy calculation in Example 4, refer to the steps shown in Example 1.

[0135] As shown in the above various embodiments, through the catalyst design system based on charge tuning and adsorption energy calculation, users can automatically calculate the NELECT parameter and reduce the need for manual intervention. At the same time, the catalyst design system can automatically select appropriate geometric optimization and adsorption energy calculation methods according to the input net charge. Therefore, the catalyst design system reduces the trial-and-error cycle and resource consumption, reduces the risk of inaccurate results caused by manual calculation errors, greatly improves the research and development efficiency of catalysts, and provides strong support for the actual industrial application of catalysts.

[0136] This application also provides a computer-readable storage medium. The computer-readable storage medium includes a stored program, wherein the program executes the catalyst design method based on charge tuning and adsorption energy calculation provided in this application.

[0137] This application also provides an electronic device, including: a processor, a memory, and a bus. The processor is connected to the memory through the bus. The memory is used to store the program, and the processor is used to run the program, wherein when the program runs, it executes the catalyst design method based on charge tuning and adsorption energy calculation provided in this application.

[0138] In addition, the functions described above in the embodiments of this application can be at least partially executed by one or more hardware logic components. For example, without limitation, the exemplary types of hardware logic components that can be used include: Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), Application Specific Standard Product (ASSP), System on Chip (SOC), Complex Programmable Logic Device (CPLD), and so on.

[0139] Although several specific implementation details are included in the above description, these should not be construed as limiting the scope of the present application. Certain features described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, the various features described in the context of a single embodiment can also be implemented separately or in any suitable sub-combination in multiple embodiments.

[0140] The above description is only a preferred embodiment of the present application and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosure concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the present application.

Claims

1. A catalyst design system based on the joint calculation of charge tuning parameters and adsorption energy, characterized in that include: File configuration module, used to configure script set, catalyst structure file and adsorbate architecture file; The script set includes a slab.py script, a NELECT.py script, an adsorbate-NELECT.py script, a far-adsorbate-NELECT.py script, a thermal.py script, a binding.py script, and a far-binding.py script; the catalyst structure file is used to characterize the structure of the support material, and the adsorbate system structure file is used to characterize the structure of the adsorbate small molecule; A parameter determination module is used to determine the experimental parameters input by the user; the experimental parameters include at least the carrier material, adsorbate small molecules, adsorption sites, and net charge; A carrier optimization module is used to call the slab.py script to perform geometric optimization on the carrier material; A NELECT parameter calculation module, configured to call the NELECT.py script, determine NELECT parameters that match the net charge, and write the NELECT parameters into an INCAR file; an adsorbate optimization module, configured to call the adsorbate-NELECT.py script and determine whether to call the far-adsorbate-NELECT.py script based on the net charge, perform geometry optimization on the adsorbate system, and update the NELECT parameters in the INCAR file; A thermodynamic calculation module, used to call the thermal.py script to perform thermodynamic analysis of the catalyst and adsorbate system; An adsorption energy calculation module is used to screen a target script from the binding.py script and the far-binding.py script according to the net charge, call the target script, determine the adsorption energy calculation result of the adsorbate system, and save the adsorption energy calculation result to a specified CSV file.

2. The system according to claim 1, wherein The script set further includes a flow-binding.py script, and the system further includes: A task management module is used to call the flow-binding.py script to perform state management and scheduling of multiple tasks; the multiple tasks include carrier optimization tasks, NELECT parameter calculation tasks, adsorbate optimization tasks, thermodynamic calculation tasks, and adsorption energy calculation tasks, wherein the carrier optimization task is assigned to the carrier optimization module, the NELECT parameter calculation task is assigned to the NELECT parameter calculation module, the adsorbate optimization task is assigned to the adsorbate optimization module, the thermodynamic calculation task is assigned to the thermodynamic calculation module, and the adsorption energy calculation task is assigned to the adsorption energy calculation module.

3. The system according to claim 2, wherein The system further comprises: The task monitoring module is used to record key information of the multiple tasks during execution, detect the running status of the multiple tasks, and back up and restart any task when the running status of any task is abnormal.

4. The system according to claim 1, wherein The types of the adsorbate systems include a first system and a second system. The first system characterizes that the adsorbate small molecules are located on the carrier material, and the second system characterizes that the adsorbate small molecules are at a relatively far adsorption distance. The adsorbate optimization module is specifically configured to: When the net charge is zero, call the adsorbate-NELECT.py script to perform geometric optimization on the adsorbate system; the adsorbate-NELECT.py script is used to perform geometric optimization on the first system; When the net charge is not zero, call the adsorbate-NELECT.py script and the far-adsorbate-NELECT.py script to perform geometric optimization on the adsorbate system; the far-adsorbate-NELECT.py script is used to perform geometric optimization on the second system.

5. The system according to claim 1, wherein The adsorption energy calculation module is specifically configured to: Obtain key energy parameters based on the thermodynamic analysis results of the catalyst and the adsorbate system; the key energy parameters include , , and ; When the net charge is zero, determine the target script based on the binding.py script; The binding.py script is used to substitute the key energy parameters into the first formula to calculate the adsorption energy calculation result ; The first formula is ; When the net charge is non-zero, it is determined as the target script based on the far-binding.py script; the far-binding.py script is used to substitute the key energy parameter into the second formula to calculate the adsorption energy calculation result ; the second formula is .

6. The system according to claim 1, characterized in that, The file configuration module is further configured to: Construct the catalyst structure file according to the specified first process; the specified first process is: use the three-dimensional modeling process to generate the periodic box corresponding to the carrier material; add the corresponding adsorption sites to the periodic box; Determine the structure of the carrier material based on the periodic box with the added adsorption sites; Generate the catalyst structure file based on the structure of the carrier material.

7. The system according to claim 1, characterized in that The file configuration module is further configured to: Construct the adsorbate system structure file according to the specified second process; the specified second process is: use the three-dimensional modeling process to generate the initial structure of the adsorbate small molecule; Generate the corresponding pdb file based on the initial structure; Use the visualization process to set the specified parameters in the pdb file to obtain a visualization file, and the visualization file characterizes the molecular system of the initial structure; Use the molecular mechanics calculation process to optimize and converge the molecular system to obtain an fchk file; convert the fchk file to a target pdb file; Use the three-dimensional modeling process to generate the periodic box corresponding to the molecular system shown in the target pdb file; Perform geometric optimization on the periodic box to obtain the optimized structure of the adsorbate small molecule; Generate the adsorbate system structure file based on the optimized structure.

8. A catalyst design method based on the joint calculation of charge tuning parameters and adsorption energy, characterized in that, Include: A configuration script set, a catalyst structure file, and an adsorbate system structure file; The script set includes the slab.py script, the NELECT.py script, the adsorbate-NELECT.py script, the far-adsorbate-NELECT.py script, the thermal.py script, the binding.py script, and the far-binding.py script; the catalyst structure file is used to characterize the structure of the carrier material, and the adsorbate system structure file is used to characterize the structure of the adsorbate small molecule; Determine the experimental parameters input by the user; the experimental parameters at least include a carrier material, an adsorbate small molecule, an adsorption site, and a net charge; Call the slab.py script to perform geometric optimization on the carrier material; Call the NELECT.py script to determine the NELECT parameter matching the net charge and write the NELECT parameter into the INCAR file; Call the adsorbate-NELECT.py script and determine whether to call the far-adsorbate-NELECT.py script according to the net charge, perform geometric optimization on the adsorbate system, and update the NELECT parameter in the INCAR file; Call the thermal.py script to perform thermodynamic analysis on the catalyst and adsorbate system; According to the net charge, screen the target script from the binding.py script and the far-binding.py script, call the target script, determine the calculation result of the adsorption energy of the adsorbate system, and save the calculation result of the adsorption energy to a specified CSV file.

9. A storage medium, characterized in that, The storage medium includes a stored program, wherein the program, when run by a processor, executes the catalyst design method based on charge parameter adjustment and adsorption energy joint calculation according to claim 8.

10. An electronic device, characterized in that, Comprising: A processor, a memory, and a bus; The processor is connected to the memory through the bus; The memory is used to store a program, and the processor is used to run the program, wherein the program, when run by the processor, executes the catalyst design method based on charge parameter adjustment and adsorption energy joint calculation according to claim 8.

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