CN117910214A - Material performance optimization method, device, computer equipment and storage medium - Google Patents
Material performance optimization method, device, computer equipment and storage medium Download PDFInfo
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Abstract
The application relates to a material performance optimization method, a material performance optimization device, computer equipment and a storage medium. Belonging to the technical field of material optimization, the method comprises the following steps: acquiring information of each parameter of a material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information. And determining the performance index value of the material to be optimized according to the parameter information of the material to be optimized. And optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model. The method comprises the steps of firstly determining a performance index value of a material to be optimized based on each parameter information of the material to be optimized. Compared with the traditional method for optimizing the performance of the material by only adopting manpower, the method provided by the application can greatly accelerate the efficiency of optimizing the performance of the material and effectively shorten the research and development period of the material.
Description
Technical Field
The present application relates to the technical field of materials, and in particular, to a method and apparatus for optimizing material performance, a computer device, and a storage medium.
Background
The material performance can directly influence the performance of the product, and optimizing the material performance is always one of important research directions in the scientific research field. For example, for lithium battery anode materials, the performance of the lithium battery anode materials can greatly affect the charging performance, discharging performance, service life, and the like of the lithium battery.
The existing research on the performance optimization of the lithium battery cathode material mainly comprises a large number of complex experimental links such as raw material selection, structural design, synthesis, characterization, test and the like. Most of the links are finished manually, a large amount of manpower and material resources are needed to be input, the repeatability and the accuracy of the results are difficult to guarantee due to the influence of a plurality of factors, and the performance improvement effect on the negative electrode material of the lithium battery is poor.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a material performance optimization method, apparatus, computer device, and storage medium that can effectively improve material performance optimization efficiency.
In a first aspect, the present application provides a method of optimizing material properties. The method comprises the following steps:
Acquiring information of each parameter of a material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information;
determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized;
And optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model.
In one embodiment, optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model includes:
based on the material optimization model, determining optimization information of each parameter information of the material to be optimized according to each parameter information and the performance index value of the material to be optimized;
And optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized.
In one embodiment, the optimization information includes a parameter score, and optimizing the performance of the material to be optimized according to the optimization information of each parameter information of the material to be optimized includes:
selecting parameter information to be optimized from the parameter information of the material to be optimized according to the magnitude relation between the parameter scores of the parameter information of the material to be optimized and the corresponding parameter threshold values;
Optimizing the parameter information to be optimized of the material to be optimized so as to optimize the performance of the material to be optimized.
In one embodiment, the optimizing information further includes an optimizing direction, and optimizing parameter information to be optimized of the material to be optimized includes:
And optimizing the parameter information to be optimized of the material to be optimized by adopting the optimization direction of the material to be optimized.
In one embodiment, after optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized, the method further includes:
determining a performance index value of the target material according to the optimized parameter information of the target material;
Determining an index difference value between the performance index value of the target material and the performance index value of the material to be optimized;
and if the index difference is smaller than the difference threshold, optimizing the material optimization model.
In one embodiment, determining the performance index value of the material to be optimized according to the parameter information of the material to be optimized includes:
And determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized based on the performance prediction model.
In one embodiment, the material to be optimized is a lithium battery anode material.
In a second aspect, the application also provides a material performance optimizing device. The device comprises:
The acquisition module is used for acquiring the information of each parameter of the material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information;
The first determining module is used for determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized;
the first optimizing module is used for optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimizing model.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor which when executing the computer program performs the steps of:
Acquiring information of each parameter of a material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information;
determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized;
And optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model.
In a fourth aspect, the present application also provides a computer-readable storage medium. A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
Acquiring information of each parameter of a material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information;
determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized;
And optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model.
In a fifth aspect, the present application also provides a computer program product. Computer program product comprising a computer program which, when executed by a processor, realizes the steps of:
Acquiring information of each parameter of a material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information;
determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized;
And optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model.
The material performance optimization method, the material performance optimization device, the computer equipment and the storage medium acquire the parameter information of the material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information. And determining the performance index value of the material to be optimized according to the parameter information of the material to be optimized. And optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model. The method comprises the steps of firstly determining a performance index value of a material to be optimized based on each parameter information of the material to be optimized. Based on the parameter information and the performance index value of the material to be optimized, the performance of the material to be optimized can be optimized by combining the material optimization model, and compared with the traditional method for optimizing the performance of the material by only adopting manpower, the method can greatly accelerate the performance optimization efficiency of the material and effectively shorten the research and development period of the material.
Drawings
FIG. 1 is an application environment diagram of a material performance optimization method provided in this embodiment;
FIG. 2 is a flow chart of a first material property optimization method according to the present embodiment;
FIG. 3 is a schematic flow chart of optimizing the performance of the material to be optimized according to the present embodiment;
FIG. 4 is a schematic flow chart of optimizing a material optimization model according to the present embodiment;
FIG. 5 is a flow chart of a second method for optimizing material properties according to the present embodiment;
FIG. 6 is a block diagram of a material performance optimizing apparatus according to the present embodiment;
fig. 7 is an internal structural diagram of the computer device provided in the present embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in FIG. 1. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing acquired data of the abnormal data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of optimizing material properties.
In one embodiment, a method for optimizing material properties is provided, as shown in FIG. 2, comprising the steps of:
s201, acquiring information of each parameter of the material to be optimized.
The material to be optimized refers to an optimization object of which the material performance needs to be optimized and improved, and the material to be optimized in the application can be a negative electrode material of a lithium battery. The parameter information refers to related parameter information of the material to be optimized, and comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information.
Optionally, in this embodiment, the original information of the material to be optimized is first obtained. And acquiring physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information of the material to be optimized according to the original information. And taking the physical parameter information, the chemical parameter information, the preparation process parameter information and the performance parameter information as the parameter information of the material to be optimized.
In this embodiment, an alternative implementation manner of obtaining the original information of the material to be optimized is: summarizing attribute items of the material to be optimized from a document, a database and theoretical calculation simulation results based on molecular dynamics simulation, a first sexual principle and a density functional theory, and taking information corresponding to each attribute item as original information.
According to the original information, the physical parameter information, the chemical parameter information, the preparation process parameter information and the performance parameter information of the material to be optimized are obtained by the following alternative embodiments: the original information is pre-processed in advance in a manner including, but not limited to, one or more of data cleansing, normalization and normalization. The data cleaning process means deleting irrelevant data and repeated data in the original data set, screening out data irrelevant to the mining subject, and processing missing values, abnormal values and the like. The normalization processing refers to converting dimensionless data into dimensionless data through transformation. The normalization processing refers to normalization processing of data, and improves reliability and accuracy of the data by eliminating redundancy, errors and inconsistencies in the data.
The physical parameter information includes, but is not limited to, the density, hardness, specific surface area and other parameter information of the material to be optimized.
Chemical parameter information includes, but is not limited to, elemental composition, chemical bond structure, molecular formula, lattice constant, crystal symmetry, and the like.
The preparation process parameter information includes, but is not limited to, synthesis temperature, preparation time, raw material proportion, impurity content information during preparation and the like. The impurity content information comprises information such as metal element content, nonmetallic element content, doping proportion and the like.
The performance parameter information refers to parameter information related to the performance of the material to be optimized, including but not limited to electrochemical activity, reversibility, conductivity, thermodynamic stability, particle size, porosity, and the like.
S202, determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized.
Wherein, the performance index refers to a numerical value used for representing the performance of the material to be optimized, and generally, the higher the performance index value is, the better the performance of the material to be optimized is represented.
An alternative implementation manner of this embodiment is as follows: according to the information of each parameter, determining the index value of each parameter, carrying out fusion processing on the index value of each parameter, and taking the value obtained after the fusion processing as the performance index value of the material to be optimized. The fusion process may take one of, but not limited to, summation, weighted summation, and product. The index value of each parameter may be determined by: and determining the score of each parameter index of each parameter according to the parameter index of each parameter, and finally fusing the scores of the parameter indexes to obtain the index value of each parameter. For example, taking physical parameter information as an example, obtaining the score of the density index, the score of the hardness index and the score of the specific surface area index of the physical parameter, and finally adding the scores of the several indexes to obtain the index value of the physical parameter.
Another alternative implementation of this embodiment is: and determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized based on the performance prediction model. Specifically, each parameter information of the material to be optimized is input into a performance prediction model, and a performance index value of the material to be optimized is determined. The performance prediction model is a model capable of mapping the performance of a material based on the parameter information of the material, and adopts, but is not limited to, convolutional Neural Network (CNN), cyclic neural network (RNN), long-term short-term memory network (LSTM), transformer coding, and the like. And training the original model by adopting sample parameters, continuously carrying out parameter optimization, and finally training to obtain the performance prediction model.
S203, optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model.
The material optimization model is a trained neural network model for optimizing material performance, and is not limited to Convolutional Neural Networks (CNNs), cyclic neural networks (RNNs) and the like.
Optionally, in this embodiment, each parameter information and performance index value of the material to be optimized may be input into a material optimization model, an optimization direction is given by the material optimization model, and the performance of the material to be optimized is optimized based on the optimization direction.
According to the material performance optimization method, the parameter information of the material to be optimized can be obtained; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information. And determining the performance index value of the material to be optimized according to the parameter information of the material to be optimized. And optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model. The method comprises the steps of firstly determining a performance index value of a material to be optimized based on each parameter information of the material to be optimized. Based on the parameter information and the performance index value of the material to be optimized, the performance of the material to be optimized can be optimized by combining the material optimization model, and compared with the traditional method for optimizing the performance of the material by only adopting manpower, the method can greatly accelerate the performance optimization efficiency of the material and effectively shorten the research and development period of the material.
In one embodiment, in order to improve the material performance optimization effect, as shown in fig. 3, an alternative implementation manner in S203 includes:
s301, based on a material optimization model, determining optimization information of each parameter information of the material to be optimized according to each parameter information and the performance index value of the material to be optimized.
The optimization information refers to optimization suggestion information for each parameter information, and mainly comprises a parameter score and/or an optimization direction.
An alternative implementation manner of this embodiment is as follows: in this embodiment, each parameter information and performance index value of the material to be optimized are input to the material optimization model, and the material optimization model outputs the parameter scores of each parameter information.
Another alternative implementation of this embodiment is: in this embodiment, each parameter information and performance index value of the material to be optimized are input to the material optimization model, and the material optimization model outputs the optimization direction of each parameter information.
Yet another alternative implementation of this embodiment is: in this embodiment, each parameter information and performance index value of the material to be optimized are input to the material optimization model, and the material optimization model outputs the parameter scores and the optimization directions of each parameter information.
S302, optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized.
An alternative implementation manner of this embodiment is as follows: if the optimization information is the parameter score, the parameter information to be optimized is selected from the parameter information of the material to be optimized according to the magnitude relation between the parameter score of the parameter information of the material to be optimized and the corresponding parameter threshold. Optimizing the parameter information to be optimized of the material to be optimized so as to optimize the performance of the material to be optimized.
Another alternative implementation of this embodiment is: if the optimization information is the optimization direction, optimizing the parameter information according to the optimization direction of the parameter information of the material to be optimized, and further optimizing the performance of the material to be optimized.
Yet another alternative implementation of this embodiment is: if the optimization information comprises the parameter scores and the optimization directions, the parameter information to be optimized is selected from the parameter information of the material to be optimized according to the magnitude relation between the parameter scores of the parameter information of the material to be optimized and the corresponding parameter threshold values. And optimizing the parameter information to be optimized of the material to be optimized by adopting the optimization direction of the material to be optimized. Specifically, firstly, according to the magnitude relation between the parameter score of each parameter information and the parameter threshold value, selecting the parameter information to be optimized (i.e. the parameter to be optimized), then selecting the optimization direction corresponding to the parameter information to be optimized from the optimization directions of the materials to be optimized, and optimizing the parameter information to be optimized based on the optimization direction corresponding to the parameter information to be optimized.
The parameter threshold is a judging condition for determining whether each parameter information belongs to the parameter information to be optimized. The parameter values of some parameter information are smaller than the parameter threshold value, and the parameter values of some parameter information are larger than the parameter threshold value, so that the parameter information belongs to the parameter information to be optimized.
In this embodiment, based on a material optimization model, optimization information of each parameter information of a material to be optimized is determined according to each parameter information and a performance index value of the material to be optimized. And optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized, so that the performance optimization of the material to be optimized can be realized quickly.
In one embodiment, to continuously optimize the performance of a material optimization model during use, as shown in FIG. 4, an alternative implementation of a material performance optimization method includes:
S401, determining a performance index value of the target material according to the optimized parameter information of the target material.
The target material is a material formed by optimizing a material to be optimized.
Optionally, in this embodiment, each parameter information of the target material obtained by optimization is input to a performance prediction model, and a performance index value of the target material is output by the performance prediction model.
S402, determining an index difference value between the performance index value of the target material and the performance index value of the material to be optimized.
The index difference value refers to a difference value between a performance index value of the target material and a performance index value of the material to be optimized.
Optionally, in this embodiment, a result obtained by subtracting the performance index value of the material to be optimized from the performance index value of the target material is used as an index difference between the performance index value of the target material and the performance index value of the material to be optimized.
S403, if the index difference value is smaller than the difference value threshold value, optimizing the material optimization model.
The difference threshold is a boundary value for judging whether the index difference meets the corresponding condition.
Optionally, in this embodiment, if the index difference is smaller than the difference threshold, training the material optimization model by using the sample data is continued, and model parameters of the material optimization model are adjusted to optimize the material optimization model.
In this embodiment, the performance index value of the target material is determined according to the optimized parameter information of the target material. And determining an index difference value between the performance index value of the target material and the performance index value of the material to be optimized. And if the index difference is smaller than the difference threshold, optimizing the material optimization model. That is, the material optimization model in this embodiment can be used to assist the user in optimizing the material properties. Based on the optimized result (i.e. the performance index value of the target material), the performance of the material optimization model can be verified in reverse, if the optimized performance does not reach the standard (i.e. the index difference value is smaller than the difference threshold value), the performance of the material optimization model is required to be improved, the material optimization model is optimized if the user requirement cannot be met at present, and based on the embodiment, a complementary and mutually promoted relationship is formed between the material performance improvement and the material optimization model, so that the intelligent development of the material research direction is further promoted.
In one embodiment, as shown in fig. 5, an alternative implementation of a material performance optimization method includes:
S501, acquiring information of each parameter of the material to be optimized. Wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information. The material to be optimized is a lithium battery anode material.
S502, determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized based on the performance prediction model.
S503, based on the material optimization model, determining optimization information of each parameter information of the material to be optimized according to each parameter information and the performance index value of the material to be optimized. Wherein the optimization information includes a parameter score and an optimization direction.
S504, selecting parameter information to be optimized from the parameter information of the material to be optimized according to the magnitude relation between the parameter scores of the parameter information of the material to be optimized and the corresponding parameter threshold values.
S505, optimizing parameter information to be optimized of the material to be optimized by adopting the optimization direction of the material to be optimized so as to realize optimization of the performance of the material to be optimized.
S506, determining the performance index value of the target material according to the optimized parameter information of the target material.
S507, determining an index difference value between the performance index value of the target material and the performance index value of the material to be optimized.
And S508, if the index difference value is smaller than the difference value threshold value, optimizing the material optimization model.
In this embodiment, transaction association information of a target transaction may be obtained; the transaction association information comprises transaction entity information, transaction relation information, entity attribute information and relation attribute information; constructing an original transaction knowledge graph of the target transaction according to the transaction association information; according to the method, the risk identification result of the target transaction is determined according to the original transaction knowledge graph and the historical transaction records between two transaction entities in the transaction entity information, the original transaction knowledge graph of the target transaction is firstly constructed according to the transaction association information, and the risk identification result is finally determined according to the historical transaction records between the original transaction knowledge graph and the two transaction entities in the transaction entity information.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a material performance optimization device for realizing the above related material performance optimization method. The implementation of the solution provided by the device is similar to that described in the above method, so the specific limitations in one or more embodiments of the material performance optimization device provided below may be referred to above as limitations of the material performance optimization method, and will not be described herein.
In one embodiment, as shown in fig. 6, there is provided a material property optimizing apparatus 1 comprising: an acquisition module 10, a first determination module 20 and a first optimization module 30, wherein:
An acquisition module 10, configured to acquire information of each parameter of a material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information; the material to be optimized is a lithium battery anode material.
A first determining module 20, configured to determine a performance index value of the material to be optimized according to each parameter information of the material to be optimized;
The first optimizing module 30 is configured to optimize the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimizing model.
In one embodiment, the first optimization module 30 in fig. 6 above is further specifically configured to:
based on the material optimization model, determining optimization information of each parameter information of the material to be optimized according to each parameter information and the performance index value of the material to be optimized;
And optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized.
In one embodiment, the first optimization module 30 in fig. 6 above is further specifically configured to:
selecting parameter information to be optimized from the parameter information of the material to be optimized according to the magnitude relation between the parameter scores of the parameter information of the material to be optimized and the corresponding parameter threshold values;
Optimizing the parameter information to be optimized of the material to be optimized so as to optimize the performance of the material to be optimized.
In one embodiment, the first optimization module 30 in fig. 6 above is further specifically configured to:
And optimizing the parameter information to be optimized of the material to be optimized by adopting the optimization direction of the material to be optimized.
In one embodiment, the material property optimizing apparatus 1 in fig. 6 above further includes:
the second determining module is used for determining a performance index value of the target material according to the optimized parameter information of the target material;
the third determining module is used for determining an index difference value between the performance index value of the target material and the performance index value of the material to be optimized;
and the second optimization module is used for optimizing the material optimization model if the index difference value is smaller than the difference value threshold value.
In one embodiment, the first determining module 20 in fig. 6 above is further specifically configured to:
And determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized based on the performance prediction model.
The various modules in the material performance optimization apparatus described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store data related to the target transaction. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of optimizing material properties.
It will be appreciated by those skilled in the art that the structure shown in FIG. 7 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
Acquiring information of each parameter of a material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information;
determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized;
And optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model.
In one embodiment, the processor when executing the computer program further performs the steps of: based on a material optimization model, optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized, including:
based on the material optimization model, determining optimization information of each parameter information of the material to be optimized according to each parameter information and the performance index value of the material to be optimized;
And optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized.
In one embodiment, the processor when executing the computer program further performs the steps of: the optimization information comprises parameter scores, optimizes the performance of the material to be optimized according to the optimization information of each parameter information of the material to be optimized, and comprises the following steps:
selecting parameter information to be optimized from the parameter information of the material to be optimized according to the magnitude relation between the parameter scores of the parameter information of the material to be optimized and the corresponding parameter threshold values;
Optimizing the parameter information to be optimized of the material to be optimized so as to optimize the performance of the material to be optimized.
In one embodiment, the processor when executing the computer program further performs the steps of: the optimization information further comprises an optimization direction, and the optimization of the parameter information to be optimized of the material to be optimized comprises the following steps:
And optimizing the parameter information to be optimized of the material to be optimized by adopting the optimization direction of the material to be optimized.
In one embodiment, the processor when executing the computer program further performs the steps of: after optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized, the method further comprises the following steps:
determining a performance index value of the target material according to the optimized parameter information of the target material;
Determining an index difference value between the performance index value of the target material and the performance index value of the material to be optimized;
and if the index difference is smaller than the difference threshold, optimizing the material optimization model.
In one embodiment, the processor when executing the computer program further performs the steps of: according to each parameter information of the material to be optimized, determining a performance index value of the material to be optimized comprises the following steps:
And determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized based on the performance prediction model.
In one embodiment, the processor when executing the computer program further performs the steps of: the material to be optimized is a lithium battery cathode material.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
Acquiring information of each parameter of a material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information;
determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized;
And optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model.
In one embodiment, the computer program when executed by the processor further performs the steps of: based on a material optimization model, optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized, including:
based on the material optimization model, determining optimization information of each parameter information of the material to be optimized according to each parameter information and the performance index value of the material to be optimized;
And optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized.
In one embodiment, the computer program when executed by the processor further performs the steps of: the optimization information comprises parameter scores, optimizes the performance of the material to be optimized according to the optimization information of each parameter information of the material to be optimized, and comprises the following steps:
selecting parameter information to be optimized from the parameter information of the material to be optimized according to the magnitude relation between the parameter scores of the parameter information of the material to be optimized and the corresponding parameter threshold values;
Optimizing the parameter information to be optimized of the material to be optimized so as to optimize the performance of the material to be optimized.
In one embodiment, the computer program when executed by the processor further performs the steps of: the optimization information further comprises an optimization direction, and the optimization of the parameter information to be optimized of the material to be optimized comprises the following steps:
And optimizing the parameter information to be optimized of the material to be optimized by adopting the optimization direction of the material to be optimized.
In one embodiment, the computer program when executed by the processor further performs the steps of: after optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized, the method further comprises the following steps:
determining a performance index value of the target material according to the optimized parameter information of the target material;
Determining an index difference value between the performance index value of the target material and the performance index value of the material to be optimized;
and if the index difference is smaller than the difference threshold, optimizing the material optimization model.
In one embodiment, the computer program when executed by the processor further performs the steps of: according to each parameter information of the material to be optimized, determining a performance index value of the material to be optimized comprises the following steps:
And determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized based on the performance prediction model.
In one embodiment, the computer program when executed by the processor further performs the steps of: the material to be optimized is a lithium battery cathode material.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:
Acquiring information of each parameter of a material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information;
determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized;
And optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on the material optimization model.
In one embodiment, the computer program when executed by the processor further performs the steps of: based on a material optimization model, optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized, including:
based on the material optimization model, determining optimization information of each parameter information of the material to be optimized according to each parameter information and the performance index value of the material to be optimized;
And optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized.
In one embodiment, the computer program when executed by the processor further performs the steps of: the optimization information comprises parameter scores, optimizes the performance of the material to be optimized according to the optimization information of each parameter information of the material to be optimized, and comprises the following steps:
selecting parameter information to be optimized from the parameter information of the material to be optimized according to the magnitude relation between the parameter scores of the parameter information of the material to be optimized and the corresponding parameter threshold values;
Optimizing the parameter information to be optimized of the material to be optimized so as to optimize the performance of the material to be optimized.
In one embodiment, the computer program when executed by the processor further performs the steps of: the optimization information further comprises an optimization direction, and the optimization of the parameter information to be optimized of the material to be optimized comprises the following steps:
And optimizing the parameter information to be optimized of the material to be optimized by adopting the optimization direction of the material to be optimized.
In one embodiment, the computer program when executed by the processor further performs the steps of: after optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized, the method further comprises the following steps:
determining a performance index value of the target material according to the optimized parameter information of the target material;
Determining an index difference value between the performance index value of the target material and the performance index value of the material to be optimized;
and if the index difference is smaller than the difference threshold, optimizing the material optimization model.
In one embodiment, the computer program when executed by the processor further performs the steps of: according to each parameter information of the material to be optimized, determining a performance index value of the material to be optimized comprises the following steps:
And determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized based on the performance prediction model.
In one embodiment, the computer program when executed by the processor further performs the steps of: the material to be optimized is a lithium battery cathode material.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high density embedded nonvolatile memory, resistive random access memory (ReRAM), magneto-resistive random access memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric memory (Ferroelectric Random Access Memory, FRAM), phase change memory (PHASE CHANGE memory, PCM), graphene memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in various forms such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), etc. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
1. A method of optimizing material properties, the method comprising:
Acquiring information of each parameter of a material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information;
Determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized;
And optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on a material optimization model.
2. The method according to claim 1, wherein optimizing the performance of the material to be optimized based on the parameter information and the performance index value of the material to be optimized based on the material optimization model comprises:
Based on a material optimization model, determining optimization information of each parameter information of the material to be optimized according to each parameter information and performance index value of the material to be optimized;
And optimizing the performance of the material to be optimized according to the optimization information of the parameter information of the material to be optimized.
3. The method according to claim 2, wherein the optimization information includes parameter scores, and the optimizing the performance of the material to be optimized according to the optimization information of each parameter information of the material to be optimized includes:
Selecting parameter information to be optimized from the parameter information of the material to be optimized according to the magnitude relation between the parameter scores of the parameter information of the material to be optimized and the corresponding parameter threshold values;
And optimizing the parameter information to be optimized of the material to be optimized so as to optimize the performance of the material to be optimized.
4. A method according to claim 3, wherein the optimization information further includes an optimization direction, and the optimizing the parameter information to be optimized of the material to be optimized includes:
And optimizing the parameter information to be optimized of the material to be optimized by adopting the optimization direction of the material to be optimized.
5. The method according to claim 2, wherein after optimizing the performance of the material to be optimized according to the optimization information of the respective parameter information of the material to be optimized, the method further comprises:
determining a performance index value of the target material according to the optimized parameter information of the target material;
determining an index difference value of the performance index value of the target material and the performance index value of the material to be optimized;
and if the index difference value is smaller than a difference value threshold value, optimizing the material optimization model.
6. The method according to claim 1, wherein determining the performance index value of the material to be optimized according to the parameter information of the material to be optimized comprises:
and determining the performance index value of the material to be optimized according to the parameter information of the material to be optimized based on the performance prediction model.
7. The method according to any one of claims 1-6, wherein the material to be optimized is a lithium battery anode material.
8. A material property optimizing apparatus, the apparatus comprising:
The acquisition module is used for acquiring the information of each parameter of the material to be optimized; wherein each parameter information comprises at least one of physical parameter information, chemical parameter information, preparation process parameter information and performance parameter information;
the first determining module is used for determining a performance index value of the material to be optimized according to the parameter information of the material to be optimized;
the first optimization module is used for optimizing the performance of the material to be optimized according to the parameter information and the performance index value of the material to be optimized based on a material optimization model.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the material property optimization method of any one of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the material property optimization method of any one of claims 1 to 7.
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