CN113160904B - High-throughput calculation method for surface property based on automatic modeling technology - Google Patents

High-throughput calculation method for surface property based on automatic modeling technology Download PDF

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CN113160904B
CN113160904B CN202110284390.XA CN202110284390A CN113160904B CN 113160904 B CN113160904 B CN 113160904B CN 202110284390 A CN202110284390 A CN 202110284390A CN 113160904 B CN113160904 B CN 113160904B
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CN113160904A (en
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张瑞丰
魏博
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Beihang University
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Abstract

The invention discloses a high-throughput computing method for surface properties based on an automatic modeling technology, and belongs to the field of materials. Firstly, obtaining a structure file of a crystal Q to be researched, converting the crystal Q into a unit cell by using the structure file, and analyzing symmetry. Then, the initial basis vector of the crystal Q is converted according to the Miller index specified by the user to obtain a new basis vector matrix corresponding to the new crystal structure G
Figure DDA0002979839870000011
Determining a new basis vector matrix
Figure DDA0002979839870000012
And (4) corresponding atomic coordinates, and filling new basis vectors with atoms of the crystal Q to construct a surface model of the crystal G. And finally, calculating the surface energy and the work function of the constructed new crystal G surface model by adopting DFT. And respectively carrying out high-throughput batch calculation on other crystals with different surface structures of different materials to obtain respective surface energy and work function, and forming a material surface property database. The invention realizes the parallel computation of the surface properties of different surface structures and improves the computation efficiency.

Description

High-throughput calculation method for surface property based on automatic modeling technology
Technical Field
The invention belongs to the field of materials, and particularly relates to a high-throughput computing method for surface properties based on an automatic modeling technology.
Background
The surface energy and work function are two basic physical parameters of a metal surface, and are of great significance for understanding various surface phenomena. Surface energy is defined as the excess free energy of the surface per unit area in a particular crystal plane, and work function is the minimum energy required to move an electron from the surface of an object to a point outside the object, which is understood microscopically to be the energy required to move an electron from the fermi level of the metal to vacuum at 0K. The phenomena described by work function include catalytic behavior, adsorption, surface segregation, surface corrosion, growth rate, and the formation of grain boundaries.
In experiments, work function is usually measured by a Scanning Kelvin Probe Force Microscope (SKPFM), but due to the defects of the SKPFM itself, the result is often inaccurate. The calculation of the surface energy usually requires measuring the surface tension at the melting temperature of the metal, an amount that is difficult to determine experimentally. Therefore, the calculation method based on the first principle of the density functional theory can conveniently and quickly solve the difficulty.
The surface energy and work function calculated by a theoretical method, particularly a density functional method, are effective means for obtaining reasonable results. It was found through search that, although the calculations for the conventional surface energy and work function have been widely applied, these studies are of great significance for understanding the surface properties of metals and guiding experiments. However, these works have only studied some low index facets, such as (111), (110) and (100) facets, and have little focus on other high index crystallographic surfaces. In practice, the crystallographic surfaces are very complex, many crystallographic surfaces are likely to be exposed to air, and different crystallographic planes will play different roles in material applications. For example, aluminum alloys contain some secondary phases to improve their performance, and different secondary phase surfaces have different work functions, which have different effects on galvanic corrosion of the aluminum alloy.
In a chemical catalytic process, the catalytic ability of the catalyst varies from surface to surface, and a high miller index surface may be more active in chemical reactions, and thus, it is far from sufficient to study only a few of the main low indices of a dense surface. The study of other low coordination number surfaces is very essential for the performance of the material, but little has been done for this purpose. Moreover, the calculation of surface properties is crucial to the construction of surface structures, but no direct method is available for constructing crystal surface structures, and only relevant auxiliary software is available, so that the method is time-consuming and labor-consuming. It is therefore necessary, and absent, to explore the properties of the crystal surface using automated modeling techniques.
Disclosure of Invention
The invention provides a high-throughput calculation method of surface properties based on an automatic modeling technology, aiming at solving the defects of the prior art on the surface research of materials.
The high-throughput computing method of the surface property based on the automatic modeling technology comprises the following steps:
the method comprises the following steps: and acquiring a structural file of the crystal Q to be researched by a computer.
The structure file contains the atom type, number and atom coordinates.
Step two: converting the crystal Q into a unit cell by using a structure file of the crystal Q, and analyzing symmetry information of the crystal Q;
the symmetry information comprises space group information, crystallographic point group, crystal system and lattice of the crystal Q; the symmetry information of crystal Q is determined by the atomic coordinates of the unit cell crystal Q.
Step three: an initial basis vector matrix for the crystal Q based on symmetry information of the crystal Q
Figure BDA0002979839850000021
Carrying out conversion to obtain a new basis vector matrix corresponding to the new crystal structure G
Figure BDA0002979839850000022
The specific process of converting the initial basis vectors is as follows:
step 301, the user specifies the miller indices (h, k, l) and assigns the initial basis vectors
Figure BDA0002979839850000023
Conversion to transition vector
Figure BDA0002979839850000024
Figure BDA0002979839850000025
Figure BDA0002979839850000026
Figure BDA0002979839850000027
Wherein, therein
Figure BDA0002979839850000028
Is composed of
Figure BDA0002979839850000029
The transition basis vector of (a) is,
Figure BDA00029798398500000210
is composed of
Figure BDA00029798398500000211
The transition basis vector of (a) is,
Figure BDA00029798398500000212
is composed of
Figure BDA00029798398500000213
M is the least common multiple of h, k and l.
Step 302, using the transition basis vector
Figure BDA00029798398500000214
New basis vector after transformation
Figure BDA00029798398500000215
And
Figure BDA00029798398500000216
Figure BDA00029798398500000217
wherein
Figure BDA00029798398500000218
Means after transformationNew
Figure BDA00029798398500000219
The basis vector is the vector of the vector,
Figure BDA00029798398500000220
indicating the new after transformation
Figure BDA00029798398500000221
And (4) basal vectors.
Step 303, determining new basis vectors
Figure BDA00029798398500000222
And
Figure BDA00029798398500000223
then, select and
Figure BDA00029798398500000224
and
Figure BDA00029798398500000225
the orthogonal shortest lattice vector as the third new basis vector constituting the new crystal structure G
Figure BDA00029798398500000226
The third new vector
Figure BDA00029798398500000227
Comprises the following steps:
Figure BDA00029798398500000228
step 304, by aligning the three new basis vectors
Figure BDA00029798398500000229
And
Figure BDA00029798398500000230
orthogonalizing Graham-Schmidt to obtain Cartesian coordinate systemThe x-y plane is reoriented to the new basis vector to obtain a converted new basis vector matrix
Figure BDA00029798398500000231
Step four: determining a new basis vector matrix
Figure BDA00029798398500000232
And (4) corresponding atomic coordinates, and filling new basis vectors with atoms of the crystal Q to construct a surface model of the crystal G.
The method specifically comprises the following steps:
step 401, determine in
Figure BDA00029798398500000233
And
Figure BDA00029798398500000234
a unit parallelepiped being a new basis vector;
expressed as:
Figure BDA00029798398500000235
t1is composed of
Figure BDA00029798398500000236
Scaling factor, t, of the basis vector construction unit parallelepiped2Is composed of
Figure BDA00029798398500000237
Scaling factor, t, of the basis vector construction unit parallelepiped3Is composed of
Figure BDA00029798398500000238
The base vector construction unit is a scaling coefficient of a parallelepiped;
step 402, determining a supercell completely containing the unit parallelepiped, and obtaining a new surface unit cell of the crystal G through new and old coordinate conversion of atoms in the crystal Q and the crystal G;
first, the origin of the supercellArranged at the vertices of a parallelepiped to define a 3 x 3 matrix
Figure BDA0002979839850000031
Which satisfies
Figure BDA0002979839850000032
Figure BDA0002979839850000033
Is a transposed matrix of the initial basis vectors,
Figure BDA0002979839850000034
then, using the matrix
Figure BDA0002979839850000035
The conversion between the new atom coordinates of the crystal G and the old atom coordinates of the crystal Q is realized;
the new coordinates are then expressed as:
Figure BDA0002979839850000036
wherein the content of the first and second substances,
Figure BDA0002979839850000037
are the original atomic coordinates within the crystal Q,
Figure BDA0002979839850000038
is the atomic coordinate corresponding to the new surface unit cell of crystal G.
Finally, all atoms in the crystal Q are respectively subjected to coordinate conversion to obtain new atomic coordinates corresponding to the crystal G, and the new atomic coordinates are written into the crystal G one by one
Figure BDA0002979839850000039
And (3) obtaining a new surface unit cell of the complete crystal G from the surface structure unit cell.
Step 403, according to the new surface unit cell, edge
Figure BDA00029798398500000310
Expanding cells in the direction until the set surface layer thickness is reached, and increasing a vacuum layer above the surface layer according to the set thickness specified by a user to form a complete surface model.
Step five: the surface energy and work function of the new surface model of the crystal G constructed were calculated using DFT.
The method comprises the following steps:
step 501: using first-principle calculation software to perform surface structure relaxation of the crystal G surface model, judging whether the relaxation degree reaches the set calculation precision, and if so, entering step 502 to perform static calculation; otherwise, continuing to relax the surface structure and recalculating the precision until the requirement of the calculation precision is met.
Step 502: the static calculation includes calculating the surface energy and work function, respectively:
(1) the calculation method of the surface energy comprises the following steps:
Figure BDA00029798398500000311
wherein gamma issSurface energy of crystal G surface structure, EsTotal energy of surface structure of crystal G, EbIs the energy of a single atom in bulk, n is the number of atoms in the surface structure of crystal G, AsIs the surface area of the crystal G surface structure.
(2) The work function calculation method comprises the following steps:
Φ＝Ev-Ef (9)
wherein Φ is a work function of the surface structure; evVacuum level, i.e. the energy of a single electron outside the surface; efThe fermi level, i.e., the energy of a single electron in a surface structure.
Step six: and (4) respectively repeating the steps from the first step to the fifth step in high-flux batch for other crystals with different surface structures of different materials to obtain the surface energy and the work function corresponding to the surface model of each crystal, forming a material surface property database, and screening out the bulk phase material with the optimal surface property.
The invention has the advantages that:
1. the invention relates to a high-throughput calculation method of surface properties based on an automatic modeling technology, which comprises the steps of automatically constructing a material system of a surface structure in a large scale, screening bulk phase materials with excellent surface properties, and has very important guiding significance for the design of anti-corrosion materials and catalysts.
2. The invention relates to a high-throughput computing method of surface properties based on an automatic modeling technology, which realizes modeling of surface structures of specific crystals and any Miller index by utilizing high-throughput computing, realizes parallel computing of the surface properties of different surface structures, and greatly shortens the time for constructing models and computing, which is essential for better measuring the surface properties of materials.
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FIG. 1 is a schematic diagram of a high throughput method of computing surface properties based on automated modeling techniques according to the present invention;
FIG. 2 is a flow chart of the method for high throughput computation of surface properties based on automated modeling techniques of the present invention.
Detailed Description
The present invention is described in detail below with reference to examples and the accompanying drawings.
The invention relates to a high-throughput computing method of surface properties based on an automatic modeling technology, which comprises the steps of reading an initial structure file of a crystal to be researched to judge the symmetry of the crystal, reading a Miller index set by a user and used for constructing a surface, redefining an initial basis vector of a material structure to obtain a new basis vector, and converting the positions of new and old atomic coordinates according to the new basis vector, as shown in figure 1. And then expanding the structure according to the set thickness of the surface layer and the vacuum layer to construct the surface structure of a new crystal, and finally performing DTF high-flux automatic calculation: judging whether the surface relaxation degree reaches the set calculation precision, and if so, performing static calculation; otherwise, the surface structure relaxation is continued. Static calculations include calculating surface energy, which is calculated by reading energy and surface area, and work function, which is calculated by reading fermi level and vacuum level, to determine and compare a series of surface structures with superior properties. Through high-throughput calculation, a database of surface properties of the surface structure of the material is established, and different surfaces with optimal surface properties are screened out.
The high-throughput computing method of the surface property based on the automatic modeling technology, as shown in FIG. 2, comprises the following steps:
step one, obtaining a structural file of a crystal Q to be researched through a computer.
Importing a crystal structure file, wherein the structure file comprises atom types, numbers and atom coordinates; and reading the cell information and the atomic coordinate information.
And step two, reading the structure file by using the plug-in program to convert the crystal Q into a unit cell, and analyzing the symmetry of the crystal structure, namely determining the space group information of the crystal Q according to the coordinates of atoms in the unit cell.
And analyzing the symmetry information of the structure according to the atomic coordinates of the crystal, wherein the symmetry information comprises space group information, crystallography point groups, crystal systems and dot matrixes.
The plug-in program package can select spglib software, the spglib software is a computer algorithm for searching the symmetry of a crystal structure, an iterative algorithm is adopted, and space group operation belonging to any space group type is searched by carrying out certain distortion on an input cell structure.
Step three: according to the symmetry information of the space group of the crystal Q, the initial basis vector of the crystal Q is converted according to the Miller index specified by a user, and a new basis vector matrix corresponding to the new crystal structure G is obtained
Figure BDA0002979839850000041
Generally, when constructing a surface structure, the parameters mainly required are the miller index, the thickness of the surface layer and the thickness of the vacuum layer; these parameters are all user-initiated settings. Any crystal plane can be assigned a miller index by three integers (h, k, l). The index of any given plane can be obtained by considering the intersection of that plane with the crystallographic unit cell vectors a, b, c. If the x, y, z plane is a fractional coordinate that intersects the a, b, c coordinate axes, then the Miller index is the smallest integer of the same scale as (1/x, 1/y, 1/z). The essence of the method is to transform the basis vectors of the unit cell model, so that the (001) plane of a new basis is parallel to a required Miller index plane, the transformed basis is two lattice vectors, the third lattice basis vector is orthogonal to the two new basis vectors, and finally, the atom position is redefined according to the new basis through translation transformation.
The specific process of converting the initial basis vectors is as follows:
step 301, the initial basis vector is expressed by the Miller index (h, k, l) of the crystal surface
Figure BDA0002979839850000051
Conversion to transition vector
Figure BDA0002979839850000052
Figure BDA0002979839850000053
Figure BDA0002979839850000054
Figure BDA0002979839850000055
Wherein, therein
Figure BDA0002979839850000056
Is composed of
Figure BDA0002979839850000057
The transition basis vector of (a) is,
Figure BDA0002979839850000058
is composed of
Figure BDA0002979839850000059
The transition basis vector of (a) is,
Figure BDA00029798398500000510
is composed of
Figure BDA00029798398500000511
M is the least common multiple of h, k and l. When there is a 0 value in h, k, l, e.g., (h0l), it corresponds to
Figure BDA00029798398500000512
When there are two 0 values in h, k, l, e.g. (h00), it corresponds to
Figure BDA00029798398500000513
Step 302, using the transition basis vector
Figure BDA00029798398500000514
New basis vector after transformation
Figure BDA00029798398500000515
And
Figure BDA00029798398500000516
Figure BDA00029798398500000517
wherein
Figure BDA00029798398500000518
Indicating the new after transformation
Figure BDA00029798398500000519
The basis vector is the vector of the vector,
Figure BDA00029798398500000520
indicating the new after transformation
Figure BDA00029798398500000521
And (4) basal vectors.
Step 303, determining new basis vectors
Figure BDA00029798398500000522
And
Figure BDA00029798398500000523
then, select and
Figure BDA00029798398500000524
and
Figure BDA00029798398500000525
the orthogonal shortest lattice vector as the third new basis vector constituting the new crystal structure G
Figure BDA00029798398500000526
The third new vector
Figure BDA00029798398500000527
Comprises the following steps:
Figure BDA00029798398500000528
step 304, by aligning the three new basis vectors
Figure BDA00029798398500000529
And
Figure BDA00029798398500000530
performing Graham-Schmidt orthogonalization, reorienting an x-y plane of a Cartesian coordinate system to a new basis vector to obtain a matrix formed by the converted new basis vector
Figure BDA00029798398500000531
Step four: determining a new basis vector matrix
Figure BDA00029798398500000532
Corresponding atomic coordinates, using the crystal Q as the formerAnd filling new basis vectors to construct a surface model of the crystal G.
The method specifically comprises the following steps:
step 401, determining new basis vectors
Figure BDA00029798398500000533
And
Figure BDA00029798398500000534
a bounding cell parallelepiped;
expressed as:
Figure BDA00029798398500000535
t1is composed of
Figure BDA00029798398500000536
Scaling factor, t, of the basis vector construction unit parallelepiped2Is composed of
Figure BDA00029798398500000537
Scaling factor, t, of the basis vector construction unit parallelepiped3Is composed of
Figure BDA00029798398500000538
The base vector construction unit is a scaling coefficient of a parallelepiped;
step 402, determining a supercell completely containing the unit parallelepiped, and obtaining a new surface unit cell of the crystal G through new and old coordinate conversion of atoms in the crystal Q and the crystal G;
first, the origin of the supercell is set at the vertex of the parallelepiped, and a 3 × 3 matrix is set
Figure BDA0002979839850000061
Which satisfies
Figure BDA0002979839850000062
Figure BDA0002979839850000063
Is a transposed matrix of the initial basis vectors,
Figure BDA0002979839850000064
then, using the matrix
Figure BDA0002979839850000065
Implementing a transformation between the new coordinates and the old coordinates of the atom, the new coordinates are expressed as:
Figure BDA0002979839850000066
wherein the content of the first and second substances,
Figure BDA0002979839850000067
are the original atomic coordinates within the crystal Q,
Figure BDA0002979839850000068
is the atomic coordinate corresponding to the new surface unit cell of crystal G.
Finally, all atoms in the crystal Q are respectively subjected to coordinate conversion to obtain new atomic coordinates corresponding to the crystal G, and all atoms are subjected to one-by-one conversion
Figure BDA0002979839850000069
Write by
Figure BDA00029798398500000610
And (3) obtaining a new surface unit cell of the complete crystal G from the surface structure unit cell.
Step 403, according to the new surface unit cell, edge
Figure BDA00029798398500000611
Expanding cells in the direction until the set surface layer thickness is reached, and then increasing a vacuum layer above the surface layer according to the set thickness specified by a user to form a complete surface model.
Step five: the surface energy and work function of the new surface model of the crystal G constructed were calculated using DFT.
A user issues a batch processing instruction, a plurality of surface models can be constructed in a high-throughput and large-batch mode at the same time and copied into POSCAR, built-in calculation auxiliary files INCAR, KPOINTS and POTCAR are added, the surface structure is optimized through DFT, and the calculated energy property is read for calculating the surface energy and the work function.
The calculating step comprises:
step 501: calculating through a first principle, performing surface structure relaxation of the crystal G surface model, judging whether the relaxation degree reaches a set calculation precision, and if so, entering step 502 to perform static calculation; otherwise, continuing to relax the surface structure and recalculating the precision until the requirement of the calculation precision is met.
Step 502: the static calculation includes calculating the surface energy and work function, respectively:
the surface energy is calculated by reading the energy and surface area, and the work function is calculated by reading the fermi level and the vacuum level.
(1) The calculation method of the surface energy comprises the following steps:
after the surface structure energy is obtained through a first principle based on a density functional theory, a numerical value of the surface energy is obtained through the following formula (8):
Figure BDA00029798398500000612
wherein gamma issSurface energy of crystal G surface structure, EsTotal energy of surface structure of crystal G, EbIs the energy of a single atom in bulk, n is the number of atoms in the surface structure of crystal G, AsIs the surface area of the crystal G surface structure.
The calculated surface energy can be used to judge the activity of the surfaces with different miller indexes, i.e. the higher the surface energy of a surface, the more active the surface is, which is important for analysis such as corrosion, catalysis, surface adsorption, etc.
(2) The work function calculation method comprises the following steps:
reading Fermi level and vacuum level from the result of the first principle calculation based on the density functional theory, and further obtaining the value of work function:
Φ＝Ev-Ef (9)
wherein Φ is a work function of the surface structure; evVacuum level, i.e. the energy of a single electron outside the surface; efThe fermi level, i.e., the energy of a single electron in a surface structure.
Different surface structures have different work functions and will have different effects on the galvanic corrosion and catalytic ability of the material.
Step six: and respectively repeating the first step to the fifth step on a plurality of other crystals with different surface structures of different materials to obtain a surface model, and performing high-flux batch calculation to obtain respective surface energy and work function to form a material surface property database.
And screening the material with the optimal surface property from the material surface property structure library.
Different surface structures have different work functions and will have different effects on the galvanic corrosion and catalytic ability of the material.
In general, density functional theory is a very efficient way to calculate surface energy and work function. And a surface structure library is established in large batch according to the crystal structure, high-flux search is carried out, the surface energy and the work function of different atomic layer thicknesses of different surface structures are calculated, a material surface property structure library is established, and a material with the optimal surface property is screened out, so that the material strength prediction is favorable for providing reasonable guidance for experiments.

Claims (4)

1. A high-throughput computing method of surface properties based on an automatic modeling technology is characterized by comprising the following steps:
the method comprises the following steps: aiming at a crystal Q to be researched, converting the crystal Q into a unit cell by using a structure file of the crystal Q, and analyzing symmetry;
step two: initial basis vector matrix for crystal Q according to user specified Miller index
Figure FDA0003535434310000011
Carrying out conversion to obtain a basis vector matrix of the new crystal G
Figure FDA0003535434310000012
Step three: determining basis vector matrices
Figure FDA0003535434310000013
Corresponding atomic coordinates, and filling the basis vector matrix with atoms of crystal Q
Figure FDA0003535434310000014
Constructing a surface model of the crystal G;
the method specifically comprises the following steps:
first, a new basis vector is determined
Figure FDA0003535434310000015
And
Figure FDA0003535434310000016
a bounding cell parallelepiped;
expressed as:
Figure FDA0003535434310000017
t1is composed of
Figure FDA0003535434310000018
Scaling factor, t, of the basis vector construction unit parallelepiped2Is composed of
Figure FDA0003535434310000019
Scaling factor, t, of the basis vector construction unit parallelepiped3Is composed of
Figure FDA00035354343100000110
The base vector construction unit is a scaling coefficient of a parallelepiped;
then, determining a supercell completely containing the unit parallelepiped, and obtaining a new surface unit cell through the new and old coordinate transformation of atoms in the two crystals;
the method specifically comprises the following steps: setting the origin of the supercell at the vertex of the parallelepiped, and setting a 3X 3 matrix
Figure FDA00035354343100000111
Which satisfies
Figure FDA00035354343100000112
Figure FDA00035354343100000113
A transposed matrix of the initial basis vectors; by means of a matrix
Figure FDA00035354343100000114
And realizing the conversion between the new atomic coordinates of the crystal G and the old atomic coordinates of the crystal Q, wherein the conversion formula is as follows:
Figure FDA00035354343100000115
wherein the content of the first and second substances,
Figure FDA00035354343100000116
are the original atomic coordinates within the crystal Q,
Figure FDA00035354343100000117
is the atomic coordinate corresponding to the new surface unit cell of the crystal G;
in the same way, all atoms in the crystal Q are respectively subjected to coordinate conversion to obtain new coordinates of atoms corresponding to the crystal G, and the new coordinates are written into the crystal G one by one
Figure FDA00035354343100000118
Obtaining a new surface unit cell of the complete crystal G from the surface structure unit cell;
finally, according to the new surface unit cell, edge
Figure FDA00035354343100000119
Expanding cells in the direction until the set surface layer thickness is reached, and then increasing a vacuum layer above the surface layer according to the set thickness specified by a user to form a complete surface model;
step four: calculating the surface energy and work function of the constructed new surface model by adopting DFT;
the method specifically comprises the following steps: firstly, judging whether the surface structure of a crystal G surface model is loose or not, and if so, performing static calculation; otherwise, continuing to perform surface structure relaxation and recalculating the precision until the requirement of the calculation precision is met;
step five: and (4) repeating the step one to the step four to obtain the surface energy and the work function of each corresponding crystal by high-flux batch calculation for other crystals with different surface structures of different materials, forming a material surface property database, and screening the material with the optimal surface property.
2. The method for high-throughput calculation of surface properties based on automated modeling techniques according to claim 1, wherein said configuration file contains atomic species, numbers and atomic coordinates.
3. The method for high-throughput calculation of surface properties based on automatic modeling technology according to claim 1, wherein the specific process of basis vector transformation in the second step is as follows:
step 201, the initial basis vector is expressed by the Miller index (h, k, l) of the crystal surface
Figure FDA0003535434310000021
Conversion to transition vector
Figure FDA0003535434310000022
Figure FDA0003535434310000023
Figure FDA0003535434310000024
Figure FDA0003535434310000025
Wherein, therein
Figure FDA0003535434310000026
Is composed of
Figure FDA0003535434310000027
The transition basis vector of (a) is,
Figure FDA0003535434310000028
is composed of
Figure FDA0003535434310000029
The transition basis vector of (a) is,
Figure FDA00035354343100000210
is composed of
Figure FDA00035354343100000211
M is the least common multiple of h, k and l;
step 202, using the transition basis vector
Figure FDA00035354343100000212
New basis vector after transformation
Figure FDA00035354343100000213
And
Figure FDA00035354343100000214
Figure FDA00035354343100000215
wherein
Figure FDA00035354343100000216
Indicating the new after transformation
Figure FDA00035354343100000217
The basis vector is the vector of the vector,
Figure FDA00035354343100000218
indicating the new after transformation
Figure FDA00035354343100000219
Base vector;
step 203, determining new basis vectors
Figure FDA00035354343100000220
And
Figure FDA00035354343100000221
then, select and
Figure FDA00035354343100000222
and
Figure FDA00035354343100000223
the orthogonal shortest lattice vector as the third new basis vector constituting the new crystal structure G
Figure FDA00035354343100000224
The third new vector
Figure FDA00035354343100000225
Comprises the following steps:
Figure FDA00035354343100000226
step 204, by aiming three new basis vectors
Figure FDA00035354343100000227
And
Figure FDA00035354343100000228
performing Graham-Schmidt orthogonalization, reorienting an x-y plane of a Cartesian coordinate system to a new basis vector to obtain a matrix formed by the converted new basis vector
Figure FDA00035354343100000229
4. The method for high-throughput calculation of surface properties based on automatic modeling technique as claimed in claim 1, wherein in step four, the static calculation includes work function and surface energy;
the surface energy calculation formula is:
Figure FDA00035354343100000230
wherein gamma issSurface energy of surface structure, EsTotal energy of surface structure, EbIs the energy of a single atom in the bulk phase, n is the number of atoms in the surface structure, AsSurface area of the surface structure;
the work function calculation formula is:
Φ＝Ev-Ef
wherein Φ is a work function of the surface structure; evVacuum level, i.e. the energy of a single electron outside the surface; efThe fermi level, i.e., the energy of a single electron in a surface structure.
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