CN114464264A - Method and device for calculating crystal melting point based on molecular dynamics and storage medium - Google Patents
Method and device for calculating crystal melting point based on molecular dynamics and storage medium Download PDFInfo
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Abstract
The application provides a method and a device for calculating a crystal melting point based on molecular dynamics and a storage medium. Wherein, the method comprises the following steps: obtaining a target crystal structure, and constructing a periodic structure model according to the target crystal structure; generating a plurality of target structure models containing cavities by using the periodic structure model, wherein the volumes of the cavities contained in each target structure model are different; performing molecular dynamics temperature rise simulation on each target structure model to respectively obtain the structural information of each target structure model in a preset temperature range; and obtaining the melting point value of the target crystal structure according to the change state of the structure information of each target structure model in a preset temperature range. According to the technical scheme, the calculation accuracy of the melting point can be improved.
Description
Technical Field
The application belongs to the technical field of computational chemistry, and particularly relates to a molecular dynamics-based crystal melting point calculation method, a molecular dynamics-based crystal melting point calculation device and a storage medium.
Background
At present, molecular dynamics temperature rise simulation methods are mostly adopted when determining the melting point of a crystal substance. The molecular dynamics heating simulation method is used for carrying out continuous or step-type heating simulation on a crystal structure by using a molecular dynamics method, recording the variation of potential energy, kinetic energy, density, root-mean-square displacement and the like of a crystal system in the simulation process, and determining the numerical value of a melting point by positioning the temperature corresponding to the trip point of the variation of the potential energy, the kinetic energy, the density, the root-mean-square displacement and the like along with the temperature variation. However, overheating phenomenon occurs in molecular dynamics temperature rise simulation, so that the calculated melting point result is much higher than the experimental result, namely the accuracy of the calculated result is low.
Disclosure of Invention
In order to solve or partially solve the problems in the related art, the application provides a method and a device for calculating a crystal melting point based on molecular dynamics, and a storage medium, which can improve the calculation accuracy of the melting point.
The first aspect of the present application provides a method for calculating a crystal melting point based on molecular dynamics, comprising:
obtaining a target crystal structure, and constructing a periodic structure model according to the target crystal structure;
generating a plurality of target structure models containing cavities by using the periodic structure model, wherein the volumes of the cavities contained in each target structure model are different;
performing molecular dynamics heating simulation on each target structure model to respectively obtain the structure information of each target structure model in a preset temperature range;
and obtaining the melting point value of the target crystal structure according to the change state of the structure information of each target structure model in the preset temperature range.
Preferably, the method further comprises:
carrying out cell expansion on the periodic structure model to obtain a super-cell periodic structure model;
the generating a plurality of target structure models containing the holes by using the periodic structure model comprises:
and generating a plurality of target structure models containing cavities by using the supercell periodic structure model.
Preferably, the generating a plurality of target structure models including a cavity by using the periodic structure model of the supercell includes:
respectively deleting atoms or molecules with different preset thresholds in the supercell periodic structure model to generate a plurality of target structure models containing cavities;
after the different preset thresholds are sorted according to the sizes, a preset change rule is met between any two adjacent preset thresholds.
Preferably, the method further comprises:
performing structural optimization on each target structure model to respectively obtain the optimized target structure models;
the molecular dynamics heating simulation of each target structure model comprises the following steps:
and performing molecular dynamics temperature rise simulation on each optimized target structure model.
Preferably, the method further comprises:
determining a target force field according to the periodic structure model;
the structural optimization of each target structure model to obtain the optimized target structure model respectively includes:
and performing structural optimization on each target structure model by using a preset algorithm corresponding to the target force field, so that the energy of the target structure model is minimized, and the optimized target structure models are respectively obtained.
Preferably, the structural information includes at least one of a potential energy, a density, an atomic coordinate, and a mean square displacement of the atomic coordinate of the target structure model.
Preferably, the obtaining the melting point value of the target crystal structure according to the change state of the structural information of each target structure model in the preset temperature range includes:
determining a mutation point of the structural information of each target structure model in the preset temperature range according to the change state of the structural information of each target structure model in the preset temperature range;
determining a melting point value of each target structure model according to a temperature value corresponding to the mutation point of each target structure model;
and determining the melting point value of the target crystal structure according to the melting point value of each target structure model.
Preferably, the determining, according to a change state of the structural information of each target structure model within the preset temperature range, a mutation point of the structural information of each target structure model within the preset temperature range includes:
determining a sudden change temperature interval in which the variation of the structural information of each target structure model exceeds a preset variation within the preset temperature range according to the variation state of the structural information of each target structure model within the preset temperature range;
and determining a corresponding mutation point according to the mutation temperature interval of each target structure model.
Preferably, the determining the melting point value of the target crystal structure according to the melting point value of each target structure model comprises:
sequencing the target structure models according to the volume size of the cavity;
determining whether the melting point values of the target structure models in the preset number or the preset proportion in continuous arrangement meet the preset condition or not according to the sequencing result;
and if the target crystal structure exists, determining the melting point value of the target crystal structure according to the continuously arranged melting point values of the target structure models in preset quantity or preset proportion.
Preferably, the determining whether the melting point values of the target structure models in the preset number or the preset proportion in the continuous arrangement satisfy the preset condition according to the sorting result includes:
determining whether the difference value between the melting point values of any two target structure models in the target structure models in a preset quantity or a preset proportion in continuous arrangement is smaller than a first preset value according to the sequencing result; or,
and determining whether the mean square error or the root mean square error between the melting point values of the target structure models in the preset number or the preset proportion in continuous arrangement is smaller than a second preset value according to the sequencing result.
Preferably, the determining the melting point value of the target crystal structure according to the melting point values of the target structure models in the preset number or the preset proportion of the continuous arrangement comprises:
calculating the average melting point value of the melting point values of the target structure models in the preset number or the preset proportion in the continuous arrangement;
determining the average melting point value as the melting point value of the target crystal structure.
Preferably, the method further comprises:
if the melting point values of the target structure models in the preset number or the preset proportion which are continuously arranged do not meet the preset condition, generating a larger number of target structure models containing cavities by using the periodic structure models; or generating a plurality of target structure models with smaller volume difference of the cavities by utilizing the periodic structure model; or generating a target structure model with smaller volume difference and more quantity of cavities by using the periodic structure model; or expanding the periodic structure model to generate a larger-size supercell periodic structure model.
In a second aspect, the present application provides a crystal screening method, comprising:
obtaining at least two crystal structures;
performing crystal melting point calculation on the at least two crystal structures by using the molecular dynamics-based crystal melting point calculation method provided by the first aspect of the application to obtain a melting point value of each crystal structure;
and determining a candidate crystal structure from the at least two crystal structures according to the melting point value of each crystal structure.
A third aspect of the present application provides a molecular dynamics-based crystal melting point calculation apparatus, comprising:
an acquisition module for acquiring a target crystal structure;
a construction module for constructing a periodic structure model according to the target crystal structure;
a generating module, configured to generate a plurality of target structure models including cavities by using the periodic structure model, where a volume of the cavity included in each of the target structure models is different;
the processing module is used for performing molecular dynamics heating simulation on each target structure model to respectively obtain the structural information of each target structure model in a preset temperature range;
and the calculation module is used for obtaining the melting point value of the target crystal structure according to the change state of the structural information of each target structure model in the preset temperature range.
The fourth aspect of the present application provides a crystal screening apparatus, comprising:
an acquisition module for acquiring at least two crystal structures;
a calculation module, configured to perform crystal melting point calculation on the at least two crystal structures by using the molecular dynamics-based crystal melting point calculation apparatus according to the third aspect of the present application, so as to obtain a melting point value of each of the crystal structures;
and the determining module is used for determining a candidate crystal structure from the at least two crystal structures according to the melting point value of each crystal structure.
A fifth aspect of the present application provides an electronic device, comprising:
a processor; and
a memory having executable code stored thereon, which when executed by the processor, causes the processor to perform the method for calculating a melting point of a crystal based on molecular dynamics as provided in the first aspect of the present application or the method for screening a crystal as provided in the second aspect of the present application.
A sixth aspect of the present application provides a computer-readable storage medium having stored thereon executable code, which, when executed by a processor of an electronic device, causes the processor to perform the method for calculating a molecular dynamics-based crystal melting point as provided in the first aspect of the present application or the method for screening crystals as provided in the second aspect of the present application.
Compared with the prior art, the beneficial effect of this application is:
by adopting the technical scheme, a series of structural models containing different cavities are established, molecular dynamics simulation heating is carried out on each structural model, the melting point of the crystal structure is determined by analyzing the dynamics simulation result, the overheating phenomenon of the system in the traditional molecular dynamics simulation is overcome, and the calculated melting point result is more accurate; meanwhile, the method is simple, does not need manual intervention, and is easy to realize flow and automation; and the calculation can be parallelized, and the result can be quickly calculated.
Drawings
FIG. 1 is a schematic flow chart of a method for calculating a crystal melting point based on molecular dynamics, provided in an embodiment of the present application;
FIG. 2 is a schematic representation of a benzene crystal structure provided in an example of the present application;
FIG. 3 is a schematic structural diagram of a model of a target structure containing different void sizes for the benzene crystal structure shown in FIG. 2;
FIG. 4 is a graph of density versus simulated temperature for the model of the target structure shown in FIG. 3 with different void sizes;
FIG. 5 is a graph of melting point values versus cavity size for the model of the target structure shown in FIG. 3 containing different cavity sizes;
FIG. 6 is a schematic diagram of a cesium metal crystal structure provided by an embodiment of the present application;
FIG. 7 is a schematic structural diagram of a model of a target structure containing different void sizes for the cesium metal crystal structure shown in FIG. 6;
FIG. 8 is a graph of density versus simulated temperature for the model of the target structure shown in FIG. 7 with different void sizes;
FIG. 9 is a graph of the mean square displacement (rmsd) of the model of the target structure of FIG. 7 with different void sizes as a function of simulated temperature;
FIG. 10 is a graph of melting point values versus cavity size for the model of the target structure shown in FIG. 7 having different cavity sizes;
FIG. 11 is a schematic structural diagram of a device for calculating a melting point of a crystal based on molecular dynamics, provided in an embodiment of the present application;
fig. 12 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While embodiments of the present application are illustrated in the accompanying drawings, it should be understood that the present application may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that although the terms "first," "second," "third," etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless specifically limited otherwise. The technical solutions of the embodiments of the present application are described in detail below with reference to the accompanying drawings.
The embodiment of the application provides a method for calculating a crystal melting point based on a molecular dynamics heating simulation method. As shown in fig. 1, the method may include the steps of:
s110, obtaining a target crystal structure, and constructing a periodic structure model according to the target crystal structure.
The target crystal structure may be a molecular crystal structure or an atomic crystal structure. The target crystal structure may be obtained from a commercially available or published structure database, or from literature, etc., such as from a CSD database. The periodic structure model can be edited and generated by using graphical operation software (such as Material Studio, Mecury, etc.) with an editing function, or edited and modified to a database or a structure building in a document. With knowledge of the position and lattice constant information of the atoms in the target crystal structure, a model of the periodic structure can be built using software editing.
And S120, generating a plurality of target structure models containing the cavities by utilizing the periodic structure model.
Wherein the volumes of the cavities contained in each target structure model are different. The object structure model may include a continuous hollow, and positions of the hollow in different object structure models may overlap, and preferably, the position of the hollow in each object structure model may extend from one short side of the structure model to the opposite short side thereof. The shape of the hollow can be cuboid, cube or other regular or irregular shapes. It is understood that the positions of the holes in different target structure models can also be randomly generated, for example, some hole positions in the target structure models are located at the structure boundary, some hole positions in the target structure models are located in the middle of the structure, and the like, which is not limited herein.
In addition, the sizes of the cavities in different target structure models may be increased in a certain regular manner, for example, in an arithmetic change, an geometric change, and the like. Of course, the size of the cavity in different target structure models may not change regularly, such as by taking a value randomly within a certain range.
In one embodiment, the periodic structure model may be expanded to obtain a periodic structure model of the supercell; and then generating a plurality of target structure models containing the holes by utilizing the supercell periodic structure model.
The lengths of lattice vectors of the superlattice structures obtained after cell expansion may be greater than a first threshold, and the first threshold may be set empirically, for example, the value of the first threshold may be 18 angstroms, 20 angstroms, 22 angstroms, 25 angstroms, or other values. The periodic structure model of the single cell is expanded into a super-cell structure, so that the result is not influenced by the size of the structure model when the subsequent molecular dynamics simulation is carried out on the structure model.
In one embodiment, generating a plurality of target structure models including holes using a periodic structure model of a supercell may include: respectively deleting atoms or molecules with different preset thresholds in the supercell periodic structure model to generate a plurality of target structure models containing cavities;
in this embodiment, part of atoms or molecules in the periodic structure model of the supercell may be deleted to create cavities of different volumes in the structure model, so that a plurality of target structure models containing cavities of a certain volume may be obtained. The target structure model comprises a continuous cavity, and the cavities contained in different target structure models are different in size.
When the target crystal structure is a molecular crystal structure, an integral number of molecules are deleted each time; when the target crystal structure is an atomic-type crystal structure, the number of atoms deleted at a time is related to the stoichiometric ratio of the target crystal structure. For example, the target crystal is ferric oxide (Fe)2O3) Then, the first target structure model may be a void structure formed by deleting two Fe atoms and three O atoms, and at this time, the total number of deleted atoms is 5; the second target structure model can be a cavity structure formed by deleting four Fe atoms and six O atoms, and the total number of the deleted atoms is 10; the third target structure model may be a cavity structure formed by deleting six Fe atoms and nine O atoms, and the total number of atoms deleted is 15; the fourth target structure model may be a void structure formed by deleting eight Fe atoms and twelve O atoms, and the total number of atoms deleted is 20. According to the rule, a plurality of target structure models containing the holes are obtained in sequence, and the ratio of the number of the deleted Fe atoms to the number of the O atoms in each target structure model conforms to the stoichiometric ratio of 2: 3, and in addition, the volume size of the hollow in each target structure model changes in an equal difference mode.
After different preset thresholds are sorted according to sizes, a preset change rule is met between any two adjacent preset thresholds. The preset change rule can be an arithmetic change rule, an geometric change rule and the like. In order to ensure the accuracy of the final result, the number of generated target structure models containing holes may be greater than a second threshold, which may be set empirically, for example, the second threshold may be 5, 6, 8, 10 or other values.
In addition, in order to avoid that the cavity collapse is too large to affect the final result when the subsequent temperature rise simulation is performed on the target structure model, the percentage of the volume size of the cavity in each target structure model to the total volume size of the target structure model should be smaller than a third threshold, and the third threshold may be 28%, 25%, 22%, 20%, or other values.
S130, performing molecular dynamics heating simulation on each target structure model to respectively obtain the structure information of each target structure model in a preset temperature range.
The preset temperature range comprises a lower limit first preset temperature and an upper limit second preset temperature. The first preset temperature may be lower than a lowest possible melting point value of the target crystal structure, and the second preset temperature may be higher than the lowest possible melting point value of the target crystal structure. The lowest possible melting point value for the target crystal structure may be a preset value, or may be found in literature or obtained through past experiments.
The structural information of the target structure model may include, but is not limited to, a variation of at least one of potential energy, density, atomic coordinates, and mean square displacement of atomic coordinates (RMSD) of the target structure model within a preset temperature range. The coordinate change condition of atoms in the preset temperature range can be regarded as a track, and the coordinate change conditions of different atoms can form a track file.
In an embodiment, before performing the molecular dynamics heating simulation on each target structure model, the structure of each target structure model may be optimized to obtain optimized target structure models, so as to perform the molecular dynamics heating simulation on each optimized target structure model.
Wherein, a preset algorithm can be adopted to carry out structural optimization on the target structure model. The structural optimization here may be a process of minimizing the structural energy of the target structural model to obtain a stable structural model.
In an embodiment, when there are a plurality of preset algorithms for structural optimization, a target force field for describing interactions between atoms in the structural model may be determined according to the periodic structural model or the supercell periodic structural model, and then structural optimization is performed on each target structural model by using the preset algorithm corresponding to the target force field, so that energy of the target structural model is minimized, and the optimized target structural models are obtained respectively.
Specifically, the molecules in the periodic structure model or the super-cellular periodic structure model may be input into processing software (such as Antechamber, CGenFF, gmxtop, and other software), and the target force field of the structural model is obtained through calculation, or the target force field of the corresponding structural model is obtained from a literature and/or a public force field database.
In the embodiment of the present application, the implementation of performing a molecular dynamics warming simulation on each target structure model may include: performing initial constant temperature simulation on each target structure model by using an NPT ensemble method, wherein the simulation step number can be set to be a fixed step number (such as 1000000 steps), and the step length is a certain size (such as 1 fs); then, performing molecular dynamics simulation of continuous heating by using an NPT ensemble method, wherein the simulated heating rate is not higher than a preset rate (such as 100K/1500000 steps), and the step length is a certain size (such as 1 fs); and simulating to obtain the change state of result data such as potential energy, density, mean square displacement (RMSD), track file and the like of the target structure model along with the temperature. Wherein the simulation pressure can be set to 1 atmosphere, the simulation starting temperature (first preset temperature) should be lower than the lowest possible melting point value (e.g. 50K), and the ending temperature (second preset temperature) should be higher than the highest possible melting point value (50K).
S140, obtaining the melting point value of the target crystal structure according to the change state of the structure information of each target structure model in a preset temperature range.
In the embodiment of the application, the mutation point of the structural information of each target structure model in the preset temperature range can be determined according to the change state of the structural information of each target structure model in the preset temperature range; determining a melting point value of each target structure model according to a temperature value corresponding to the mutation point of each target structure model; and determining the melting point value of the target crystal structure according to the melting point value of each target structure model.
In an embodiment, the determining, according to the change state of the structural information of each target structure model within the preset temperature range, the abrupt change point of the structural information of each target structure model within the preset temperature range may include: determining a sudden change temperature interval in which the variation of the structural information of each target structure model exceeds a preset variation within a preset temperature range according to the variation state of the structural information of each target structure model within the preset temperature range; and determining a corresponding mutation point according to the mutation temperature interval of each target structure model.
Specifically, a curve of the structural information of each target structure model changing with temperature may be drawn, and it is determined whether there is a large variation of the structural information in a certain temperature interval in the curve, data of the structural information in the temperature interval is in a descending trend with temperature rise, and a variation between a maximum value and a minimum value of the structural information exceeds a preset variation, and if there is a variation, the temperature interval is determined to be a sudden change temperature interval. Further, the intermediate temperature of the abrupt temperature interval may be determined as an abrupt point of the target structure model, and a temperature value corresponding to the abrupt point may be used as a melting point value of the target structure model. According to the method, the mutation point and the melting point value of each target structure model can be determined.
In an embodiment, determining the melting point value of the target crystal structure from the melting point value of each target structure model may include: sequencing the target structure models according to the size of the cavity; determining whether the melting point values of the target structure models in the preset number or the preset proportion which are continuously arranged meet the preset condition or not according to the sequencing result; and if the target crystal structure exists, determining the melting point value of the target crystal structure according to the melting point values of the target structure models which are continuously arranged in preset quantity or in preset proportion.
The preset number may be 3 or more than 3, and the preset ratio may be 1/2, 3/5, 2/3 or other values.
Specifically, the determining whether there is an embodiment in which the melting point values of the target structure models in the preset number or the preset ratio, which are continuously arranged, satisfy the preset condition according to the sorting result may include: and determining whether the difference value between the melting point values of any two target structure models in the target structure models with the preset quantity or the preset proportion continuously arranged is smaller than a first preset value according to the sequencing result. The difference value may be an absolute difference value or a ratio value.
Or, according to the sorting result, determining whether the mean square error or the root mean square error between the melting point values of the target structure models in the preset number or the preset proportion in the continuous arrangement is smaller than a second preset value.
In addition, if the melting point values of the target structure models which are continuously arranged in preset quantity or in preset proportion do not meet the preset conditions, a larger quantity of target structure models containing cavities can be generated by utilizing the periodic structure models or the supercell periodic structure models; or generating a plurality of target structure models with smaller volume difference of the cavities by utilizing the periodic structure model or the supercell periodic structure model; or generating a target structure model with smaller volume difference and more quantity of cavities by using the periodic structure model or the supercell periodic structure model; or expanding the periodic structure model to generate a larger-size supercell periodic structure model.
In an embodiment, determining the melting point value of the target crystal structure according to a preset number or a preset ratio of melting point values of the target structure models arranged in series may include: calculating the average melting point value of the melting point values of the target structure models in the preset number or the preset proportion; the average melting point value is determined as the melting point value of the target crystal structure.
Specifically, a melting point value variation curve (melting point value-cavity volume size) of the target structure models with different cavity volume sizes may be drawn, and it may be determined whether a relatively flat region where the melting point value varies with the increase of the cavity exists in the curve (for example, a difference between an average melting point value in the region and a melting point value of any single target structure model in the region is smaller than a first preset value, such as 15K, or a difference between melting point values of any two target structure models in the region is smaller than 15K, or a mean square error or a root mean square error between a melting point value of one target structure model in the region and melting point values of other target structure models is smaller than a second preset value). If present, the average melting point value within the interval may be calculated and used as the final melting point value for the target crystal structure. If not, the process returns to step S120 to establish a periodic structure model of the supercell with larger size or a target structure model with a larger number of voids with smaller void volume difference, and continues to perform the molecular dynamics simulation calculation in steps S130 and S140 to re-determine the melting point value of the target crystal structure.
The following will explain in detail with reference to specific examples.
Taking the melting point of benzene crystals as an example.
Model: the benzene crystal periodic structure primitive cell obtained from the CSD database contains 4 benzene molecules, the side length of the primitive cell is respectively 7.39 angstroms, 9.42 angstroms and 6.81 angstroms, and the primitive cell is in an orthorhombic structure. The periodic structure model of benzene crystals is shown in FIG. 2.
According to the steps, the periodic structure model of the benzene crystal is firstly expanded from the original unit cell model to form a 6 x 3 x 4 supercell periodic structure model, and the supercell periodic structure model comprises 288 benzene molecules.
Secondly, constructing holes to obtain a series of target structure models containing the holes; the cavities are generated by a method of directly deleting molecules at corresponding positions and numbers in the supercell periodic structure model, and the sizes of the cavities in the target structure model containing the cavities are respectively 8, 16, 24, 32, 40 and 48 benzene molecules. The shape of the cavity in the target structure model tends to be a cuboid, and the maximum cavity size is 16.7% of the total volume. The model of the target structure containing different void sizes is shown in FIG. 3. The model is a 0-hole structural model, the 0-hole structural model is a supercell periodic structural model obtained by cell expansion from an original unit cell periodic structural model, (b) is an 8-molecule hole target structural model, (c) is a 16-molecule hole target structural model, (d) is a 24-molecule hole target structural model, (e) is a 32-molecule hole target structural model, (f) is a 40-molecule hole target structural model, and (g) is a 48-molecule hole target structural model.
Then, simulation calculation: the interaction between molecules in the benzene crystal was described using an opls-aa force field. Energy minimization calculation is firstly carried out on each target structure model by using gromacs software, then the optimized target structure model is relaxed for 1000000 steps at the temperature of 200K, then the temperature is continuously raised from 200K to 400K, and the number of simulated temperature raising steps is 4000000 steps. The time step length in the relaxation and heating processes is 1fs, and the ensemble method is NPT.
Simulation results are as follows: and analyzing the temperature and density data of the system in the temperature rise simulation process to obtain the melting point value of each target structure model. The simulated temperature versus density relationship is shown in fig. 4, and the melting point values of the target structure model containing different voids are obtained. In fig. 4, (a) shows a state of change in density of the structural model under 0-molecule cavity with temperature, (b) shows a state of change in density of the structural model under 8-molecule cavity with temperature, (c) shows a state of change in density of the structural model under 16-molecule cavity with temperature, (d) shows a state of change in density of the structural model under 24-molecule cavity with temperature, (e) shows a state of change in density of the structural model under 32-molecule cavity with temperature, (f) shows a state of change in density of the structural model under 40-molecule cavity with temperature, and (g) shows a state of change in density of the structural model under 48-molecule cavity with temperature.
During the simulation, the density decreased with increasing temperature. During melting, the density of the system suddenly drops, and the temperature of the middle point of the sudden change section can be taken as the melting point value. When the volume of the cavity in the model is large, under the pressure coupling effect of the NPT ensemble, atoms near the cavity part in part of the model cannot support the original structure, so that the cavity collapses, and at this time, the model volume may suddenly decrease below the melting point temperature. However, in this example, the density suddenly rises and is far from the melting point when the cavity collapses, and the judgment of the melting point value is not affected.
Finally, the magnitude of the melting point results was plotted as a function of the void volume size, as shown in FIG. 5. It can be seen that the melting point result of the simulation calculation is 340K for the structural model without the cavity (i.e. the structural model with the cavity size of 0), which is much higher than the experimental result, and there is a serious overheating phenomenon. After the cavities are added, the melting point of the crystal begins to decrease along with the increase of the size of the cavities, when the size of the cavities is in the range of 15-40 molecules, the calculated melting point result does not significantly decrease along with the increase of the cavities, the difference between the melting point values is less than 10K, and when the melting point value hardly changes along with the size of the cavities (the size of the cavities is 30-40 molecules), the calculated average melting point value is very close to the experimental value represented by a dotted line. Therefore, compared with the traditional molecular dynamics simulation method (the melting point value obtained under the 0 cavity), the technical scheme of the application has the advantage that the calculation accuracy of the melting point is remarkably improved.
Taking the melting point of cesium metal as an example.
Model: the cesium metal crystal is in a body-centered cubic structure, the unit cell side length is 6.14 angstroms, and the cesium crystal primitive cell structure is shown in fig. 6.
Firstly, cells are expanded by a unit cell periodic structure model to form a 20 x 10 supercell periodic structure model, and the supercell periodic structure model comprises 4000 cesium atoms.
And secondly, constructing holes, wherein the holes are generated by directly deleting atoms at corresponding positions and numbers in the periodic structure model of the supercell, and the holes in the target structure model containing the holes are respectively 100, 200, 300, 400, 500, 600, 700 and 800 cesium atoms in size. The shape of the cavity in the target structure model tends to be a cuboid, and the maximum cavity size is 20% of the total volume. The model of the target structure containing different vacancy sizes is shown in FIG. 7 below. The model is a 0-hole structure model, which is a supercell periodic structure model obtained by expanding an original unit cell periodic structure model, (b) a 100-atom hole target structure model, (c) a 200-atom hole target structure model, (d) a 300-atom hole target structure model, (e) a 400-atom hole target structure model, (f) a 500-atom hole target structure model, (g) a 600-atom hole target structure model, (h) a 700-atom hole target structure model, and (i) an 800-atom hole target structure model.
And (3) simulation calculation: eam force field was used to describe the interaction between cesium atoms, and molecular dynamics simulations were performed on each of the above target structure models using lammps software. Firstly, energy minimization calculation is carried out on a target structure model, then the optimized target structure model is relaxed for 1000000 steps at the temperature of 250K, then the temperature is continuously raised from 250K to 400K, and the number of simulated temperature raising steps is 3000000 steps. The time step length in the relaxation and heating processes is 1fs, and the ensemble method is NPT.
Simulation results are as follows: and analyzing the temperature and density data of the system in the temperature rise simulation process to obtain the melting point value of each target structure model. The simulated temperature versus density relationship is shown in FIG. 8 below. In fig. 8, (a) shows a state of change in density of the structural model under 0 atomic void with temperature, (b) shows a state of change in density of the structural model under 100 atomic void with temperature, (c) shows a state of change in density of the structural model under 200 atomic void with temperature, (d) shows a state of change in density of the structural model under 300 atomic void with temperature, (e) shows a state of change in density of the structural model under 400 atomic void with temperature, (f) shows a state of change in density of the structural model under 500 atomic void with temperature, (g) shows a state of change in density of the structural model under 600 atomic void with temperature, (h) shows a state of change in density of the structural model under 700 atomic void with temperature, and (i) shows a state of change in density of the structural model under 800 atomic void with temperature.
During the simulation, the density decreased with increasing temperature. During melting, the density of the system suddenly drops, and the temperature of the middle point of the sudden change section can be taken as the melting point value. When the volume of the cavity in the model is large, under the pressure coupling effect of the NPT ensemble, atoms near the cavity part in part of the model cannot support the original structure, so that the cavity collapses, and at this time, the model volume may suddenly decrease below the melting point temperature. When the temperature at which the voids collapse is close to the melting temperature, the process of collapse may merge with the process of sudden drop in density of the system, resulting in only a small drop in density after a sudden rise in density. The melting temperature at this time can be regarded as the temperature at the end of collapse.
The atoms in the crystal structure vibrate back and forth near the equilibrium position before unmelted, when the atoms are not far from the equilibrium position. When the crystal melts, atoms leave equilibrium positions and begin to diffuse to other positions. The reaction process is shown on the rmsd curve, namely, when the structure is in a crystal state, the rmsd value is small and rises slowly along with the rise of temperature; when the structure melts, the rmsd increases rapidly as the simulation progresses, and the higher the temperature, the faster the particles diffuse, and thus the higher the rmsd value increases. Before and after the crystal melts, there is a significant jump in the rmsd value, by means of which the temperature at melting can be determined.
The rmsd of the target structure models containing different void sizes as a function of temperature is shown in FIG. 9. In fig. 9, (a) shows a change state of rmsd with temperature of the 0-atom-cavity lower structure model, (b) shows a change state of rmsd with temperature of the 100-atom-cavity lower structure model, (c) shows a change state of rmsd with temperature of the 200-atom-cavity lower structure model, (d) shows a change state of rmsd with temperature of the 300-atom-cavity lower structure model, (e) shows a change state of rmsd with temperature of the 400-atom-cavity lower structure model, (f) shows a change state of rmsd with temperature of the 500-atom-cavity lower structure model, (g) shows a change state of rmsd with temperature of the 600-atom-cavity lower structure model, (h) shows a change state of rmsd with temperature of the 700-atom-cavity lower structure model, and (i) shows a change state of rmsd with temperature of the 800-atom-cavity lower structure model. It can be seen from fig. 9 that the melting point determined by the rmsd jump is the same size as the melting point determined by the density jump, and that both methods are in good agreement.
Finally, the magnitude of the melting point results was plotted as a function of the void volume size, as shown in FIG. 10. Therefore, the melting point result of the structural model of the 0 cavity is much higher than the experimental result by simulation calculation, and serious overheating phenomenon exists. After the holes are added, the calculation result of the melting point of the cesium metal crystal is firstly reduced along with the size of the holes, then basically does not change along with the increase of the holes, the difference between the values of the melting points is small, and in the range of 300-800 atoms with the melting point hardly changing along with the number of the holes, the average value result of the melting point is basically consistent with the experimental value represented by the curve. Therefore, compared with the traditional molecular dynamics simulation method (the melting point value obtained under the 0 cavity), the technical scheme of the application has the advantage that the calculation accuracy of the melting point is remarkably improved.
By adopting the technical scheme, a series of structural models containing different cavities are established, molecular dynamics simulation heating is carried out on each structural model, the melting point of the crystal structure is determined by analyzing the dynamics simulation result, the overheating phenomenon of the system in the traditional molecular dynamics simulation is overcome, and the calculated melting point result is more accurate; meanwhile, the method is simple, does not need manual intervention, and is easy to realize flow and automation; and the calculation can be parallelized, and the result can be quickly calculated.
The embodiment of the application also provides a crystal screening method, which comprises the following steps:
s1, obtaining at least two crystal structures;
s2, calculating the crystal melting points of the at least two crystal structures by using the method for calculating the crystal melting points based on molecular dynamics, which is improved in the foregoing embodiment, to obtain the melting point value of each crystal structure;
and S3, determining candidate crystal structures from the at least two crystal structures according to the melting point value of each crystal structure.
By adopting the method, the melting point values of a plurality of crystal structures can be quickly and accurately calculated, and the melting point values of the crystal structures are sequenced to determine the size relationship of the melting point values of the crystal structures, so that candidate crystal structures with required melting points can be quickly selected in subsequent application.
The embodiment of the present application further provides a device for calculating a crystal melting point based on molecular dynamics, which can be used to perform the method for calculating a crystal melting point based on molecular dynamics provided in the foregoing embodiment. As shown in fig. 11, the apparatus may include:
an acquisition module 1110 for acquiring a target crystal structure;
a building module 1120 for building a periodic structure model from the target crystal structure;
a generating module 1130, configured to generate a plurality of target structure models including holes by using the periodic structure model, where the holes included in each of the target structure models have different volumes;
the processing module 1140 is configured to perform molecular dynamics heating simulation on each target structure model to obtain structure information of each target structure model in a preset temperature range;
a calculating module 1150, configured to obtain a melting point value of the target crystal structure according to a change state of the structure information of each target structure model within a preset temperature range.
Optionally, the apparatus shown in fig. 11 may further include:
the cell expanding module is used for expanding the periodic structure model to obtain a super-cell periodic structure model;
accordingly, the generating module 1130 can be specifically configured to generate a plurality of target structure models including holes by using the periodic structure model of the supercell.
Optionally, the generating module 1130 deletes atoms or molecules with different preset thresholds in the supercell periodic structure model, respectively, to generate a plurality of target structure models including voids; after different preset thresholds are sorted according to sizes, a preset change rule is met between any two adjacent preset thresholds.
Optionally, the apparatus shown in fig. 11 may further include:
the optimization module is used for carrying out structural optimization on each target structure model to respectively obtain the optimized target structure models;
accordingly, the processing module 1140 may be specifically configured to perform a molecular dynamics warming simulation for each optimized target structure model.
Optionally, the apparatus shown in fig. 11 may further include:
the determining module is used for determining a target force field according to the periodic structure model;
the optimization module may be specifically configured to perform structural optimization on each target structure model by using a preset algorithm corresponding to the target force field, so as to minimize energy of the target structure model and obtain the optimized target structure models respectively.
Wherein the structural information may include, but is not limited to, at least one of potential energy, density, atomic coordinates, and mean square displacement of atomic coordinates of the target structural model.
Optionally, the calculating module 1150 may include:
the first determining unit is used for determining a mutation point of the structural information of each target structure model in a preset temperature range according to the change state of the structural information of each target structure model in the preset temperature range;
the second determining unit is used for determining the melting point value of each target structure model according to the temperature value corresponding to the catastrophe point of each target structure model;
and the third determining unit is used for determining the melting point value of the target crystal structure according to the melting point value of each target structure model.
Optionally, the first determining unit may be specifically configured to determine, according to a change state of the structural information of each target structure model in a preset temperature range, a sudden change temperature interval in which a change amount of the structural information of each target structure model exceeds a preset change amount in the preset temperature range; and determining a corresponding mutation point according to the mutation temperature interval of each target structure model.
Optionally, the third determining unit may be specifically configured to sort the multiple target structure models according to the sizes of the cavities; determining whether the melting point values of the target structure models in the preset number or the preset proportion which are continuously arranged meet the preset condition or not according to the sequencing result; and if the target crystal structure exists, determining the melting point value of the target crystal structure according to the melting point values of the target structure models which are continuously arranged in preset quantity or in preset proportion.
If the melting point values of the target structure models which are continuously arranged in the preset number or in the preset proportion do not meet the preset condition, the generation module 1130 may generate a larger number of target structure models containing cavities by using the periodic structure models; or generating a plurality of target structure models with smaller volume difference of the cavities by utilizing the periodic structure model; or generating a target structure model with smaller volume difference and more quantity of cavities by utilizing the periodic structure model; or expanding the periodic structure model to generate a larger-size supercell periodic structure model.
Optionally, the determining, by the third determining unit, whether there is an implementation manner in which the melting point values of the target structure models in the preset number or the preset ratio, which are continuously arranged, satisfy the preset condition according to the sorting result may include: determining whether the difference value between the melting point values of any two target structure models in the target structure models with the preset quantity or the preset proportion in continuous arrangement is smaller than a first preset value or not according to the sequencing result; or, according to the sorting result, determining whether the mean square error or the root mean square error between the melting point values of the target structure models in the preset number or the preset proportion in the continuous arrangement is smaller than a second preset value.
Optionally, the third determining unit may determine the melting point value of the target crystal structure according to the melting point values of the target structure models which are continuously arranged in the preset number or in the preset ratio, where the embodiment of determining the melting point value of the target crystal structure may include: calculating the average melting point value of the melting point values of the target structure models in the preset number or the preset proportion; the average melting point value is determined as the melting point value of the target crystal structure.
According to the device, a series of structural models containing different cavities are established, molecular dynamics simulation heating is carried out on each structural model, the melting point of the crystal structure is determined by analyzing the dynamics simulation result, the overheating phenomenon of a system in the traditional molecular dynamics simulation is overcome, and the calculated melting point result is more accurate; meanwhile, the method is simple, does not need manual intervention, and is easy to realize flow and automation; and the calculation can be parallelized, and the result can be quickly calculated.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
The embodiment of the application also provides a crystal screening device which can be used for executing the crystal screening method provided by the embodiment. Specifically, the apparatus may include:
an acquisition module for acquiring at least two crystal structures;
a calculation module, configured to perform crystal melting point calculation on the at least two crystal structures by using the molecular dynamics-based crystal melting point calculation apparatus provided in the foregoing embodiment, so as to obtain a melting point value of each crystal structure;
and the determining module is used for determining a candidate crystal structure from the at least two crystal structures according to the melting point value of each crystal structure.
The embodiment of the present application further provides an electronic device, which can be used to perform the method for calculating the crystal melting point and/or the method for screening crystals based on molecular dynamics provided in the foregoing embodiments. As shown in fig. 12, the electronic device 1200 includes a memory 1210 and a processor 1220.
The Processor 1220 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 1210 may include various types of storage units, such as system memory, Read Only Memory (ROM), and permanent storage. Wherein the ROM may store static data or instructions for the processor 1220 or other modules of the computer. The persistent storage device may be a read-write storage device. The persistent storage may be a non-volatile storage device that does not lose stored instructions and data even after the computer is powered off. In some embodiments, the persistent storage device employs a mass storage device (e.g., magnetic or optical disk, flash memory) as the persistent storage device. In other embodiments, the permanent storage may be a removable storage device (e.g., floppy disk, optical drive). The system memory may be a read-write memory device or a volatile read-write memory device, such as a dynamic random access memory. The system memory may store instructions and data that some or all of the processors require at runtime. In addition, memory 1210 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (e.g., DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), magnetic and/or optical disks, as well. In some embodiments, memory 1210 may include a removable storage device that is readable and/or writable, such as a Compact Disc (CD), a digital versatile disc read only (e.g., DVD-ROM, dual layer DVD-ROM), a Blu-ray disc read only, an ultra-dense disc, a flash memory card (e.g., SD card, min SD card, Micro-SD card, etc.), a magnetic floppy disc, or the like. Computer-readable storage media do not contain carrier waves or transitory electronic signals transmitted by wireless or wired means.
The memory 1210 has stored thereon executable code that, when processed by the processor 1220, may cause the processor 1220 to perform some or all of the methods described above.
Furthermore, the method according to the present application may also be implemented as a computer program or computer program product comprising computer program code instructions for performing some or all of the steps of the above-described method of the present application.
Alternatively, the present application may also be embodied as a computer-readable storage medium (or non-transitory machine-readable storage medium or machine-readable storage medium) having executable code (or a computer program or computer instruction code) stored thereon, which, when executed by a processor of an electronic device (or server, etc.), causes the processor to perform part or all of the various steps of the above-described method according to the present application.
Having described embodiments of the present application, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or improvements to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (17)
1. A method for calculating a crystal melting point based on molecular dynamics, comprising:
obtaining a target crystal structure, and constructing a periodic structure model according to the target crystal structure;
generating a plurality of target structure models containing cavities by using the periodic structure model, wherein the volumes of the cavities contained in each target structure model are different;
performing molecular dynamics heating simulation on each target structure model to respectively obtain the structure information of each target structure model in a preset temperature range;
and obtaining the melting point value of the target crystal structure according to the change state of the structure information of each target structure model in the preset temperature range.
2. The method of claim 1, further comprising:
carrying out cell expansion on the periodic structure model to obtain a super-cell periodic structure model;
the generating a plurality of target structure models containing the holes by using the periodic structure model comprises:
and generating a plurality of target structure models containing cavities by using the supercell periodic structure model.
3. The method of claim 2, wherein generating a plurality of target structure models containing holes using the periodic structure model of the supercell comprises:
respectively deleting atoms or molecules with different preset thresholds in the supercell periodic structure model to generate a plurality of target structure models containing cavities;
after the different preset thresholds are sorted according to the sizes, a preset change rule is met between any two adjacent preset thresholds.
4. The method of claim 1, further comprising:
performing structural optimization on each target structure model to respectively obtain the optimized target structure models;
the molecular dynamics heating simulation of each target structure model comprises the following steps:
and performing molecular dynamics temperature rise simulation on each optimized target structure model.
5. The method of claim 4, further comprising:
determining a target force field according to the periodic structure model;
the structural optimization of each target structure model to obtain the optimized target structure model respectively includes:
and performing structural optimization on each target structure model by using a preset algorithm corresponding to the target force field, so that the energy of the target structure model is minimized, and the optimized target structure models are respectively obtained.
6. The method of claim 1, wherein the structural information comprises at least one of a potential energy, a density, an atomic coordinate, and a mean square displacement of an atomic coordinate of the target structural model.
7. The method according to any one of claims 1 to 6, wherein the obtaining the melting point value of the target crystal structure according to the change state of the structural information of each target structure model in the preset temperature range comprises:
determining a mutation point of the structural information of each target structure model in the preset temperature range according to the change state of the structural information of each target structure model in the preset temperature range;
determining a melting point value of each target structure model according to a temperature value corresponding to the mutation point of each target structure model;
and determining the melting point value of the target crystal structure according to the melting point value of each target structure model.
8. The method according to claim 7, wherein the determining the mutation point of the structural information of each target structure model in the preset temperature range according to the change state of the structural information of each target structure model in the preset temperature range comprises:
determining a sudden change temperature interval in which the variation of the structural information of each target structure model exceeds a preset variation within the preset temperature range according to the variation state of the structural information of each target structure model within the preset temperature range;
and determining a corresponding mutation point according to the mutation temperature interval of each target structure model.
9. The method of claim 7, wherein determining the melting point value of the target crystal structure from the melting point values of each of the target structure models comprises:
sequencing the target structure models according to the volume size of the cavity;
determining whether the melting point values of the target structure models in the preset number or the preset proportion in continuous arrangement meet the preset condition or not according to the sequencing result;
and if the target crystal structure exists, determining the melting point value of the target crystal structure according to the continuously arranged melting point values of the target structure models in preset quantity or preset proportion.
10. The method according to claim 9, wherein the determining whether the melting point values of the target structure models in a preset number or a preset proportion in a continuous arrangement satisfy a preset condition according to the sorting result comprises:
determining whether the difference value between the melting point values of any two target structure models in the target structure models in a preset quantity or a preset proportion in continuous arrangement is smaller than a first preset value according to the sequencing result; or,
and determining whether the mean square error or the root mean square error between the melting point values of the target structure models in the preset number or the preset proportion in continuous arrangement is smaller than a second preset value according to the sequencing result.
11. The method of claim 9, wherein determining the melting point value of the target crystal structure according to the predetermined number or ratio of the melting point values of the target structure model in the consecutive arrangement comprises:
calculating the average melting point value of the melting point values of the target structure models in the preset number or the preset proportion in the continuous arrangement;
determining the average melting point value as the melting point value of the target crystal structure.
12. The method of claim 9, further comprising:
if the melting point values of the target structure models in the preset number or the preset proportion which are continuously arranged do not meet the preset condition, generating a larger number of target structure models containing cavities by using the periodic structure models; or generating a plurality of target structure models with smaller volume difference of the cavities by utilizing the periodic structure model; or generating a target structure model with smaller volume difference and more quantity of cavities by using the periodic structure model; or expanding the periodic structure model to generate a larger-size supercell periodic structure model.
13. A crystal screening method, comprising:
obtaining at least two crystal structures;
performing a crystal melting point calculation on the at least two crystal structures using the method of any one of claims 1-12 to obtain a melting point value for each of the crystal structures;
and determining a candidate crystal structure from the at least two crystal structures according to the melting point value of each crystal structure.
14. A molecular dynamics-based crystalline melting point calculation apparatus, comprising:
an acquisition module for acquiring a target crystal structure;
a construction module for constructing a periodic structure model according to the target crystal structure;
a generating module, configured to generate a plurality of target structure models including cavities by using the periodic structure model, where a volume of the cavity included in each of the target structure models is different;
the processing module is used for performing molecular dynamics heating simulation on each target structure model to respectively obtain the structural information of each target structure model in a preset temperature range;
and the calculation module is used for obtaining the melting point value of the target crystal structure according to the change state of the structural information of each target structure model in the preset temperature range.
15. A crystal screening apparatus, comprising:
an acquisition module for acquiring at least two crystal structures;
a calculation module for performing crystal melting point calculations on the at least two crystal structures using the apparatus of claim 14 to obtain a melting point value for each of the crystal structures;
and the determining module is used for determining a candidate crystal structure from the at least two crystal structures according to the melting point value of each crystal structure.
16. An electronic device, comprising:
a processor; and
a memory having executable code stored thereon, which when executed by the processor, causes the processor to perform the method of any one of claims 1-13.
17. A computer-readable storage medium having stored thereon executable code, which when executed by a processor of an electronic device, causes the processor to perform the method of any one of claims 1-13.
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