CN113311020B - Method for calculating and predicting thermoelectric performance of material based on high-flux first sex principle - Google Patents
Method for calculating and predicting thermoelectric performance of material based on high-flux first sex principle Download PDFInfo
- Publication number
- CN113311020B CN113311020B CN202110597707.5A CN202110597707A CN113311020B CN 113311020 B CN113311020 B CN 113311020B CN 202110597707 A CN202110597707 A CN 202110597707A CN 113311020 B CN113311020 B CN 113311020B
- Authority
- CN
- China
- Prior art keywords
- calculation
- convergence
- optimization
- calculating
- calculated
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N25/00—Investigating or analyzing materials by the use of thermal means
- G01N25/20—Investigating or analyzing materials by the use of thermal means by investigating the development of heat, i.e. calorimetry, e.g. by measuring specific heat, by measuring thermal conductivity
Landscapes
- Chemical & Material Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Electrochemistry (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a method for calculating and predicting thermoelectric properties of a material based on a high-flux first property principle, which comprises the following steps: step 1, performing primary magnetic test calculation on an initial crystal structure of a material so as to obtain magnetic moment information of the material; step 2, carrying out structural optimization calculation on the compound by using a conjugate gradient algorithm or a quasi-Newton algorithm to obtain an optimized unit cell structure, then carrying out calculation and fitting of bulk modulus of the material to obtain bulk modulus information of the corresponding material, and further deducing sound velocity information of the material; and 3, carrying out self-consistent calculation of the material after convergence of the structural optimization calculation, so as to obtain the charge density, the total energy and the magnetic moment of the material. And 4, calculating thermoelectric properties based on the charge density calculated in the step 3.
Description
Technical Field
The invention relates to the field of electrical properties of thermoelectric materials, in particular to a method for calculating and predicting the thermoelectric properties of materials based on a high-flux first property principle.
Background
Materials play an important role in our lives, and innovations in material technology should now also be critical to address urgent social challenges, such as global climate change and more serious pollution. Therefore, development of environmental protection materials such as thermoelectric materials is accelerated. The thermoelectric material is a functional material capable of mutually converting heat energy and electric energy, and can utilize temperature difference to generate electricity and electric energy to exchange heat energy to realize refrigeration, so that various thermoelectric devices are manufactured, and the thermoelectric material is a novel functional environment-friendly material.
We generally use the dimensionless formula zt=s 2 Sigma T/kappa denotes the thermoelectric properties of a material, where S is the Zebeck coefficient of the material, sigma denotes the electrical conductivity of the material, kappa is the thermal conductivity of the material, S 2 The product of σ is called the power factor of the material. Since higher ZT values represent better thermoelectric properties of the material, higher power factors and lower thermal conductivities are required to obtain a material with better thermoelectric properties. Therefore, in the field of thermoelectric materials, it is very important to study the power factor. In addition according to the formula c= (k/p) 1/2 (c represents the sound velocity of the material, ρ is the density of the material, k is the bulk modulus), the material can be usedThe bulk modulus derives the sound velocity of the material. The lower bulk modulus results in a material with a lower acoustic velocity, while a material with a lower acoustic velocity always has a lower thermal conductivity, so acoustic velocity can also serve as a high throughput screening condition for thermoelectric materials, thus finding a material with a higher ZT value.
In general we can optimize the ZT value of a material from two aspects: from the aspect of electric transport performance, the power factor S of the material can be improved 2 Sigma, the thermal conductivity k of the material is reduced in terms of thermal transport. To increase the power factor of the material, the zebach coefficient S and the electrical conductivity σ need to be increased, and the thermal conductivity κ of the material needs to be reduced. However, these parameters are not isolated, but on the one hand the zebesk coefficient of the material is continuously reduced and the conductivity is continuously increased with increasing carrier concentration. On the other hand, the thermal conductivity of the material is influenced by both carrier concentration and lattice phonon, the carrier concentration is increased, the thermal conductivity is also increased, and the effects of the electrical conductivity and the thermal conductivity on ZT values are opposite. It appears that it is difficult to obtain new thermoelectric materials by tuning, so we have created this approach to find new materials with good electrical properties by fast prediction of the power factor and acoustic velocity of the material, selecting a way to directly use high throughput screening.
Currently available calculation methods for obtaining thermoelectric properties of materials mostly utilize BoltzTraP program based on constant relaxation time approximation, such as work based on thermoelectric property calculation by Materials Project of university of Massa Medicata, USA 1 . However, the constant relaxation time approximates to only the electronic structure part and the complex scattering term calculation is selected to be ignored, so that the power factor obtained by the calculation method has larger deviation from the actual result. The method is compatible with a TransOpt electric transport calculation program 2 The TransOpt program processes relaxation time based on constant electroacoustic coupling approximation, and considers electroacoustic coupling matrix elements on the whole space energy band as a constant, compared with the constant relaxation time approximation, no extra calculation amount is added, however, scattering correlation of electroacoustic coupling is considered, calculation speed is guaranteed, and prediction accuracy is improved from the aspect of algorithm.
Disclosure of Invention
The invention aims to overcome blindness of experimental trial-and-error method and provides a method for obtaining material electric transport property based on high-flux first property principle calculation. By setting an initial unit cell structure, the automatic flow of the calculation of the electric transport property of the material can be realized, and the operation is simple and quick.
In order to achieve the aim of the invention, the invention adopts the following technical scheme: a method for calculating and obtaining material electrotransport properties based on a high-throughput first sexual principle, comprising the following steps:
step 1, performing primary magnetic test calculation on an initial crystal structure of a material so as to obtain magnetic moment information of the material;
step 2, carrying out structural optimization calculation on the compound by using a conjugate gradient algorithm or a quasi-Newton algorithm to obtain an optimized unit cell structure, then carrying out calculation and fitting of bulk modulus of the material to obtain bulk modulus information of the corresponding material, and further deducing sound velocity information of the material;
and 3, carrying out self-consistent calculation of the material after convergence of the structural optimization calculation, so as to obtain the charge density, the total energy and the magnetic moment of the material.
And 4, calculating thermoelectric properties based on the charge density calculated in the step 3.
Wherein, the step 1 comprises the following steps:
step 1.1, performing magnetic test calculation, wherein the high symmetry K point of the step is set to be 30/a+1, 30/b+1, 30/c+1, a, b and c, and the lattice parameters of the compound are set.
Step 1.2, if the absolute value of the magnetic moment of any atom calculated in this step is greater than 0.02 μb, the parameter "ispin=2" is added to the INCAR file in the following calculation step, otherwise, no modification is made to the INCAR file.
The step 2 comprises the following steps:
and 2.1, performing optimization calculation on the atomic position, shape and volume of the compound. The K point here is set as 30/a+1, 30/b+1, 30/c+1 as above, the convergence criterion of the force is set as per atomBelow is lower than
The energy convergence criterion is 10 -4 eV。
Step 2.2, optimizing the atomic position and the unit cell volume at most five times, and setting parameters as isif=3, ibion=2 and conjugate gradient algorithm. The result of any one optimization of the five times reaches the convergence standard, and the next calculation is performed.
And 2.3, if the convergence standard is not reached after the optimization of the conjugate gradient algorithm for five times, performing optimization calculation of only the atomic positions for five times, wherein the set parameters are ISIF=0, IBRION=1, and the quasi-Newton algorithm. And if the result of any step reaches the convergence standard, performing the next calculation.
If the ten optimizations still do not meet the convergence criteria, we consider the compound as unable to converge, then mark it as "structure optimization not converging" and stop the calculation. If the structural optimization reaches the convergence standard, the optimized structure is subjected to simulated stretching compression of 9 times of material volume, 9 pairs of energy-volume data are obtained through calculation, and Vinet is utilized 3 Fitting the state equation to obtain the bulk modulus of the corresponding material, and finally based on the formula c= (k/ρ) 1/2 The sound velocity of the corresponding material can be obtained.
The step 3 comprises the following steps:
the self-consistent calculation of step 3 is started after convergence of the relaxation calculation, which is mainly done to obtain the charge density, the total energy and the magnetic moment of the material. The K point grids used for self-consistent calculation are 60/a+1, 60/b+1, 60/c+1. Meanwhile, the electron density of state of the material is obtained here based on self-consistent calculation.
The step 4 comprises the following steps:
based on the charge density calculated in the step 3, electric transport property calculation is performed based on a TransOpt program, wherein denser Brillouin zone high symmetry K points are adopted and are set to 240/a+1, 240/b+1 and 240/c+1. In the electric transport calculation process, deformation potential and Young's modulus are respectively 3eV and 100GPa, and the calculation temperature is 700K.
The beneficial effects are that: compared with the prior art, the technical scheme of the invention has the following beneficial technical effects:
1. the method overcomes the defect of the traditional trial-and-error method, saves resources and time, is calculated based on the high-flux first property principle, and can automatically realize the calculation of the material electric transport property by giving an initial crystal structure.
2. The method does not involve experiments and use chemical products in the whole process, does not generate chemical pollution, and accords with the environment-friendly concept; and the method is simple to operate, low in cost, easy to realize and suitable for popularization and application.
3. According to the method, the thermoelectric performance of the material can be predicted in advance through the calculation result, samples meeting the requirements are selected for experimental verification, the experimental time and resources can be saved, the experimental efficiency is improved, the guidance effect is achieved, and blindness is avoided.
4. Four electron state densities with different smoothness degrees are adopted, and the track contribution of different elements can be displayed more intuitively.
5. The method is compatible with a TransOpt electric transport calculation program, and for the first-principle high-flux electric transport calculation, the calculation speed is ensured, and the accuracy of a calculation result is increased.
6. Different structure optimization strategies are adopted, and the calculation time is reduced.
Drawings
FIG. 1 is a flow chart of the calculation of the method.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples.
Embodiment one:
the method for calculating and obtaining the material electric transport property based on the high-flux first sex principle comprises the following steps:
step 1, a simple magnetic test calculation is performed on the initial cubic system Fe1Nb1Sb1 with the space group number of 216.
Step 1.1, lattice constants of Fe1Nb1Sb1 are respectively
The high symmetry K point of this step is set to 8 x 8.
Step 1.2, through magnetic test calculation, the magnetic moment of Fe1Nb1Sb1 is found to be 0.0015 mu B, and belongs to a nonmagnetic compound, and no parameter of 'ISPIN=2' is added in an INCAR input file calculated next.
Step 2, carrying out structure optimization calculation on the compound by using a conjugate gradient algorithm or a quasi-Newton algorithm to obtain an optimized unit cell structure;
step 2.1, the high symmetry K point of this step is still set to 8 x 8, the convergence criterion of the force is
The energy convergence criterion is 10 -4 eV。
And 2.2, firstly setting optimization parameters of ISIF=3 and IBRION=2, performing optimization calculation on the structure of Fe1Nb1Sb1 by using a conjugate gradient algorithm, finally reaching convergence standard, and ending the optimization calculation. Based on the optimized structure, the volume modulus is calculated to obtain 9 pairs of energy-volume parameters, the volume modulus of Fe1Nb1Sb1 is 165.625GPa after being fitted by using a Vinet state equation, and the sound velocity prediction result is 1792m/s.
And 3, after the structure optimization calculation is converged, self-consistent calculation is started, so that the charge density and the total energy of Fe1Nb1Sb1 are obtained. The self-consistent calculated high symmetry K point is set to 15 x 15.
And 4, carrying out electric transport calculation after the calculation is completed, wherein in the electric transport calculation process of Fe1Nb1Sb1, the K point is set to 58 x 58. Finally, the n-type maximum power factor of Fe1Nb1Sb1 is calculated to be 51 x 10 -4 W/mK 2 The p-type maximum power factor is 33 x 10 -4 W/mK 2
Embodiment two:
this step is substantially the same as the above embodiment, with the particular feature that:
in this embodiment, a method for obtaining the electrotransport property of a material based on the high-flux first sexual principle is calculated as follows:
step 1, a simple magnetic test calculation was performed on Pb4Te4 of the initial cubic system, space group number 62.
Step 1.1, lattice constants of Pb4Te4 are respectively
The high symmetry K point of this step is set to 4 x 7 x 5.
Step 1.2, through magnetic test calculation, the magnetic moment of Pb4Te4 is found to be 0 mu B, and belongs to nonmagnetic compounds.
Step 2.1, the high symmetry K point of this step is still set to 4×7×5, the convergence criterion of the force is
The energy convergence criterion is 10 -4 eV。
Step 2.2, firstly setting optimization parameters of 'isif=3 and ibrion=2', and performing structural optimization calculation on Pb4Te4 by using a conjugate gradient algorithm, wherein convergence criteria are not reached after five times. Based on the optimized structure, the calculation of the bulk modulus is carried out, the calculated result is fitted by using a Vinet state equation, the bulk modulus of Pb4Te4 is found to be 38.4GPa, and the sound velocity prediction result is calculated to be 425m/s.
And 2.3, setting optimization parameters as ISIF=0 and IBRION=1, and re-optimizing by using a quasi-Newton algorithm to reach convergence standard.
And 3, setting the self-consistent high-symmetry K point to be 7×14×10.
And 4, carrying out electric transport calculation after the calculation is completed, wherein in the electric transport calculation process of Pb4Te4, the K point is set to 26 x 53 x 37. Finally, the n-type maximum power factor of Pb4Te4 is calculated to be 143 x 10 -4 W/mK 2 The p-type maximum power factor is 264 x 10 -4 W/mK 2
The method of the embodiment can overcome the defect of the traditional trial-and-error method, saves resources and time, calculates based on the first sexual principle, and can obtain a calculation result by inputting an initial crystal structure, thereby being convenient and quick. According to the method, through theoretical calculation, samples meeting the requirements are selected for experimental verification, so that the experimental time and resources can be saved, the experimental efficiency is improved, the guidance effect is achieved, and blindness is avoided.
Table 1 shows the predicted power factor and sound velocity for a portion of n-type material at 700K
| name | PF max (10 -4 W/mK 2 ) | Sound Velocity(m/s) | Space group |
| MIP3D-22204-In4O6 | 537.461 | 1867.23 | 167 |
| MIP3D-26335-Na2S4Sb2 | 484.24 | 864.223 | 12 |
| MIP3D-18728-Ga1O6Sb1Sr2 | 480.713 | 1958.26 | 225 |
| MIP3D-7091-Bi2Na2Se4 | 479.012 | 608.282 | 141 |
| MIP3D-10126-Cd2O6Sn2 | 477.884 | 1784.89 | 148 |
| MIP3D-22206-In4O8Zn2 | 465.678 | 1824.67 | 227 |
| MIP3D-10020-Cd2Ga4O8 | 450.081 | 1988.79 | 227 |
| MIP3D-10059-Cd2In4O8 | 448.407 | 1619.45 | 227 |
| MIP3D-3015-As2Hg1O6 | 446.493 | 1974.93 | 162 |
| MIP3D-28773-Pb4S4 | 429.262 | 345.611 | 64 |
| MIP3D-28725-Pb2S2 | 424.768 | 420.434 | 39 |
| MIP3D-20220-H2In2O4 | 424.362 | 1937.24 | 31 |
| MIP3D-28244-O8Sn2Zn4 | 421.637 | 1993.93 | 227 |
| MIP3D-7593-Br2O2Sb2 | 421.545 | 1010.46 | 129 |
| MIP3D-3056-As2Li2Se4 | 420.154 | 753.418 | 9 |
| MIP3D-7090-Bi2Na2S4 | 412.919 | 781.572 | 141 |
| MIP3D-27989-O6Sn2Sr2 | 404.667 | 1810.49 | 74 |
| MIP3D-26078-N4Zn6 | 397.329 | 1680.36 | 194 |
| MIP3D-22189-In4Mg2O8 | 390.845 | 1881.84 | 227 |
| MIP3D-3018-As2Hg2O6 | 366.547 | 1104.15 | 162 |
| MIP3D-18913-Ga2O4Rb2 | 364.891 | 1234.83 | 227 |
| MIP3D-21971-In2Li2O4 | 364.236 | 1816.56 | 141 |
| MIP3D-6191-Ba3Br2In2O5 | 363.498 | 990.659 | 139 |
| MIP3D-21972-In2Li2O4 | 362.336 | 1813.72 | 141 |
| MIP3D-10267-Cd4O8Sn2 | 356.92 | 1528.88 | 227 |
| MIP3D-6199-Ba3Cl2In2O5 | 356.362 | 1081.12 | 139 |
Table 2 shows the power factor and sound velocity prediction results for a portion of p-type material at 700K
| name | PF max (10 -4 W/mK 2 ) | Sound Velocity(m/s) | Space group |
| MIP3D-28772-Pb4S4 | 514.193 | 352.979 | 36 |
| MIP3D-20513-H6Mg2Os1 | 413.021 | 1651.99 | 225 |
| MIP3D-5242-Ba1Ca3O4 | 380.052 | 1421.39 | 221 |
| MIP3D-5829-Ba2F8Sn2 | 350.13 | 822.474 | 129 |
| MIP3D-28775-Pb4Te4 | 286.776 | 425.522 | 62 |
| MIP3D-19176-Ga9K3 | 274.863 | 527.064 | 119 |
| MIP3D-28773-Pb4S4 | 248.484 | 345.611 | 64 |
| MIP3D-19180-Ga9Rb3 | 246.432 | 460.605 | 119 |
| MIP3D-1393-Al1H6In1Rb2 | 246.419 | 523.211 | 225 |
| MIP3D-167-Ag1Ba2Sb1 | 231.943 | 359.453 | 225 |
| MIP3D-5249-Ba1Ce1O3 | 230.342 | 1512.94 | 221 |
| MIP3D-16879-F4O4W2 | 227.381 | 1872.69 | 26 |
| MIP3D-24322-Li5S4Sb1 | 225.377 | 914.996 | 71 |
| MIP3D-17309-F6Sn2 | 220.445 | 1135.23 | 225 |
| MIP3D-24362-Li8Mg4Si4 | 213.229 | 1110.34 | 215 |
| MIP3D-28725-Pb2S2 | 211.446 | 420.434 | 39 |
| MIP3D-9262-Ca2H4 | 206.204 | 1119.59 | 194 |
| MIP3D-11414-Cl8Si4 | 205.121 | 941.185 | 19 |
| MIP3D-2947-As2Er2O2Zn2 | 202.25 | 1183.09 | 129 |
| MIP3D-2966-As2F2Sr2Zn2 | 201.326 | 857.303 | 129 |
| MIP3D-10162-Cd2S2 | 201.03 | 947.595 | 59 |
| MIP3D-6565-Be2Na2Sb2 | 197.021 | 680.235 | 194 |
| MIP3D-3122-As2O2Y2Zn2 | 193.922 | 1318.95 | 129 |
| MIP3D-23119-La2Na2O4 | 193.49 | 1389.42 | 141 |
| MIP3D-30153-Se2Zr1 | 192.521 | 1031.3 | 164 |
| MIP3D-20207-H2He2Li2 | 191.206 | 614.102 | 36 |
In summary, in the method for obtaining thermoelectric properties of materials based on the high-flux first principle of calculation, the high-flux calculation is utilized to perform magnetic test on the materials, then perform structural optimization calculation, if the numerical value after structural optimization reaches the convergence standard, stretch and compress the structure after structural optimization to obtain different energy-volume data, the Vinet state equation is utilized to perform fitting to obtain the bulk modulus of the corresponding materials so as to obtain the sound velocity of the materials, materials with lower heat conductivity can be indirectly screened out, then the self-consistency and electron state density calculation are performed on the compounds, and finally the thermoelectric properties of the materials are further calculated by using the TransOpt program, so that the power factor of the more accurate materials is obtained. By predicting the power factor and the sound velocity of the material, the discovery of potentially novel thermoelectric materials is facilitated.
The embodiments of the method according to the present invention are described above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes may be made according to the purposes of the invention, so long as the method according to the present invention meets the purposes of the present invention, and the principle and concept of a method for calculating and predicting thermoelectric performance of a material based on the high-throughput first principle of the present invention, all fall within the scope of protection of the present invention.
Claims (1)
1. A method for calculating a predicted material thermoelectric property based on a high-throughput first sexual principle, the method comprising the steps of:
step 1, using VASP calculation software, firstly using default calculation parameters of the software to perform magnetic test calculation on an initial compound crystal structure, and finally obtaining material magnetic moment information;
step 2, carrying out structural optimization calculation on the compound by using a conjugate gradient algorithm or a quasi-Newton algorithm to obtain an optimized unit cell structure, then carrying out calculation and fitting of bulk modulus of the material to obtain bulk modulus information of the corresponding material, and further deducing sound velocity information of the material;
step 3, after the structure optimization calculation reaches convergence, self-consistent calculation is started, so that the charge density, the total energy and the magnetic moment of the material are obtained;
step 4, calculating the electric transport property based on the charge density calculated in the step 3;
the step 1 comprises the following steps:
step 1.1, performing magnetic test calculation by using VASP software, obtaining unit cell side lengths a, b and c of a calculated material when the calculation is performed, setting high symmetry K points of the calculated material in a three-dimensional space to be 30/a+1, 30/b+1 and 30/c+1, and finally performing the calculation according to the default calculation parameters of the VASP;
step 1.2, if the absolute value of the magnetic moment of any atom calculated in step 1.1 is greater than 0.02 μb, adding the parameter ispin=2 to the vacp calculation control parameter file INCAR in the following calculation steps 2,3,4, otherwise, not modifying the INCAR file;
the step 2 comprises the following steps:
step 2.1, carrying out volume optimization calculation in step 2.2 on the atomic position, shape and volume of the compound by using VASP calculation software, and if the optimization result in step 2.2 does not meet the requirements, carrying out optimization calculation in step 2.3; the symmetry K points calculated for the structural optimization of the material are also related to the unit cell side length, set to 30/a+1, 30/b+1, 30/c+1, and the convergence criterion for the forces of the final material is set to be lower than that of each atom
The energy convergence criterion of the material is 10 -4 eV；
Step 2.2, optimizing the atomic position and the unit cell volume of the material for at most five times, namely, calculating the stress tensor of the material when VASP calculation is carried out, and simultaneously changing the primitive shape and the volume of the material, so that the calculation parameters in the step are set to allow the ion position of the material to be changed, the unit cell volume and the unit cell shape ISIF=3, the structure optimization method IBRION=2, and the calculation result of any one of the five times reaches the convergence standard by utilizing the conjugate gradient algorithm, so as to carry out the calculation in the step 3;
step 2.3 if the five conjugate gradient algorithm is optimized without reaching each atom below
The energy of the material is less than 10 -4 Performing optimization calculation of only atomic positions for five times according to convergence criteria of eV, and performing calculation in step 3 in order to optimize the atomic positions in the calculation process, wherein the calculation parameter setting parameters are ISIF=0, the structure optimization method IBRION=1, namely, the calculation result of any one of the five times reaches the convergence criteria by utilizing a quasi-Newton algorithm;
step 2.4, if ten times of optimization are carried out and still the convergence criterion is not met, the compound is considered to be incapable of converging, then the compound is marked as the structure optimization is not converged, and the calculation is stopped; if the structural optimization reaches the convergence standard, carrying out simulated stretching compression on the optimized structure for 9 times of material volumes, obtaining 9 pairs of energy-volume data through calculation, fitting by using a Vinet state equation to obtain the volume modulus of the corresponding material, and finally carrying out the process based on the formula c= (k/ρ) 1/2 Obtaining the sound velocity of the corresponding material;
the step 3 comprises the following steps:
step 3.1, judging the material subjected to structure optimization, if the optimized structure reaches that each atom is lower than
The energy of the material is less than 10 -4 The convergence criterion of eV starts to calculate in the step 3; />
Step 3.2, taking the unit cell side lengths a, b and c of the calculated material, setting the high symmetry K point of the calculated material in the three-dimensional space as 60/a+1, 60/b+1 and 60/c+1, and calculating by using VASP;
step 3.3, setting the energy convergence criterion to 10 in the calculation parameter file -4 In the process of calculating VASP, if the energy of the material reaches the convergence condition, the calculation is completed to obtain the charge density, the total energy and the magnetic moment of the material;
the step 4 comprises the following steps:
step 4.1, judging whether the step 3 reaches 10 -4 If reaching the convergence standard, performing VASP calculation by using the charge density calculated in the step 3, firstly obtaining the unit cell side lengths a, b and c of the calculated material, setting high symmetry K points of the Brillouin zone, specifically 240/a+1, 240/b+1 and 240/c+1, and setting the energy convergence standard as 10 in a calculation parameter file -4 eV, next, VASP calculation;
step 4.2, if the calculation result of step 4.1 reaches 10 -4 And (3) invoking a TransOpt program based on the calculation result of the step according to the energy convergence standard of eV, adopting a deformation potential and Young modulus method, respectively setting the deformation potential to 3eV and the Young modulus to 100GPa, calculating the temperature to 700K, and calculating the electric transport property to finally obtain the calculation result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110597707.5A CN113311020B (en) | 2021-05-31 | 2021-05-31 | Method for calculating and predicting thermoelectric performance of material based on high-flux first sex principle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110597707.5A CN113311020B (en) | 2021-05-31 | 2021-05-31 | Method for calculating and predicting thermoelectric performance of material based on high-flux first sex principle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113311020A CN113311020A (en) | 2021-08-27 |
| CN113311020B true CN113311020B (en) | 2023-05-05 |
Family
ID=77376244
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110597707.5A Active CN113311020B (en) | 2021-05-31 | 2021-05-31 | Method for calculating and predicting thermoelectric performance of material based on high-flux first sex principle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113311020B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114397420B (en) * | 2021-12-17 | 2023-12-12 | 西安近代化学研究所 | Determination method for compression potential energy of layered stacked energetic compound molecular crystals |
| CN114912296A (en) * | 2022-06-14 | 2022-08-16 | 上海大学 | Method for calculating and screening Peltier active refrigeration material |
| CN116813345A (en) * | 2023-07-14 | 2023-09-29 | 西安科技大学 | Strontium potassium niobate ceramic with high thermoelectric performance and construction method thereof |
| CN117476117B (en) * | 2023-12-27 | 2024-04-23 | 宁德时代新能源科技股份有限公司 | Method for predicting initial magnetic moment in crystal structure |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111062134A (en) * | 2019-12-18 | 2020-04-24 | 哈尔滨工业大学 | Screening method of functional material element with optical, electric and thermal properties |
| CN111581847A (en) * | 2020-05-25 | 2020-08-25 | 长沙理工大学 | Design method of embedded thermoelectric device for road and embedded thermoelectric power generation road surface thereof |
| JP2021033964A (en) * | 2019-08-29 | 2021-03-01 | トヨタ自動車株式会社 | Saturation magnetization prediction method and saturation magnetization prediction simulation program |
| CN112786123A (en) * | 2021-03-03 | 2021-05-11 | 沈阳大学 | Screening efficient AB2O4Theoretical method of spinel semiconductor photocatalytic material |
Family Cites Families (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104679965A (en) * | 2015-03-25 | 2015-06-03 | 湖北工业大学 | Method for forecasting thermoelectric conversion power factors of bismuth telluride through WIEN2K software |
| CN106771706B (en) * | 2016-11-22 | 2019-10-25 | 武汉理工大学 | A kind of method of the thermoelectric material of quick screenability optimization |
| CN108365087A (en) * | 2018-01-31 | 2018-08-03 | 许昌学院 | A kind of preparation process based on the surfaces MnAs Half-metallic |
| CN110188429B (en) * | 2019-05-20 | 2020-01-31 | 北京应用物理与计算数学研究所 | th principle calculation method and system for electrical/thermal conductivity of f-containing electronic metal |
| CN110210103B (en) * | 2019-05-27 | 2020-11-27 | 北京工业大学 | Multi-scale simulation method for mechanical behavior of multiphase composite material |
| CN110218888B (en) * | 2019-06-20 | 2021-05-04 | 电子科技大学 | Novel Zintl-phase thermoelectric material and preparation method thereof |
| CN111785831A (en) * | 2020-06-23 | 2020-10-16 | 武汉理工大学 | Promote In2Se3Method for multivalued storage characteristics of phase change material |
-
2021
- 2021-05-31 CN CN202110597707.5A patent/CN113311020B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2021033964A (en) * | 2019-08-29 | 2021-03-01 | トヨタ自動車株式会社 | Saturation magnetization prediction method and saturation magnetization prediction simulation program |
| CN111062134A (en) * | 2019-12-18 | 2020-04-24 | 哈尔滨工业大学 | Screening method of functional material element with optical, electric and thermal properties |
| CN111581847A (en) * | 2020-05-25 | 2020-08-25 | 长沙理工大学 | Design method of embedded thermoelectric device for road and embedded thermoelectric power generation road surface thereof |
| CN112786123A (en) * | 2021-03-03 | 2021-05-11 | 沈阳大学 | Screening efficient AB2O4Theoretical method of spinel semiconductor photocatalytic material |
Non-Patent Citations (2)
| Title |
|---|
| Sirui Feng.Quasi-industrially Produced Large-area Microscale Graphene Flakes Assembled Film with Extremely High Thermoelectric Power Factor.《Nano Energy》.2019,全文. * |
| 邹纯鹏.BiCuChO（Ch=Se,S）热电性能的第一性原理研究.《工程科技Ⅰ辑》.2021,全文. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113311020A (en) | 2021-08-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113311020B (en) | Method for calculating and predicting thermoelectric performance of material based on high-flux first sex principle | |
| Sahai et al. | Adaptive coarse graining method for energy transfer and dissociation kinetics of polyatomic species | |
| Lu et al. | Data mining-aided materials discovery and optimization | |
| Xu et al. | Direction dependent thermal conductivity of monolayer phosphorene: Parameterization of Stillinger-Weber potential and molecular dynamics study | |
| Yuan et al. | Parameter extraction of solar cell models using chaotic asexual reproduction optimization | |
| Zakharchenko et al. | Self-consistent screening approximation for flexible membranes: Application to graphene | |
| Lian et al. | Optimal sensor placement for large structures using the nearest neighbour index and a hybrid swarm intelligence algorithm | |
| Feng et al. | Electronic structure as a guide in screening for potential thermoelectrics: Demonstration for half-Heusler compounds | |
| CN107341301B (en) | Method for predicting wettability between defect-introduced graphene and metal | |
| Miyamoto et al. | Meniscus and beam halo formation in a tandem-type negative ion source with surface production | |
| Yang et al. | Dual adaptive sampling and machine learning interatomic potentials for modeling materials with chemical bond hierarchy | |
| Garcia et al. | Computational screening of magnetocaloric alloys | |
| Wang et al. | Mutation particle swarm optimization (M-PSO) of a thermoelectric generator in a multi-variable space | |
| CN113362902A (en) | Method for simulating displacement damage of ternary compound semiconductor based on molecular dynamics | |
| Yuan et al. | Antibonding induced anharmonicity leading to ultralow lattice thermal conductivity and extraordinary thermoelectric performance in CsK 2 X (X= Sb, Bi) | |
| Yue et al. | Methodology for determining the electronic thermal conductivity of metals via direct nonequilibrium ab initio molecular dynamics | |
| CN116994677A (en) | Electric transport performance high-flux calculation method based on deformation potential approximation | |
| Rodin et al. | Microscopic theory of ionic motion in solids | |
| CN113536661B (en) | TFET device structure optimization and performance prediction method based on neural network | |
| Huang et al. | First-principles based deep neural network force field for molecular dynamics simulation of N–Ga–Al semiconductors | |
| Zhang et al. | Accessing the thermal conductivities of Sb 2 Te 3 and Bi 2 Te 3/Sb 2 Te 3 superlattices by molecular dynamics simulations with a deep neural network potential | |
| CN114462178A (en) | Design method of wearable two-dimensional asymmetric material with high thermoelectric conversion efficiency | |
| Verreck et al. | 3D TCAD model for poly-Si channel current and variability in vertical NAND flash memory | |
| Zhang et al. | Tuning the lattice thermal conductivity of Sb 2 Te 3 by Cr doping: a deep potential molecular dynamics study | |
| Lu et al. | Adaptive genetic algorithm-based design of gamma-graphyne nanoribbon incorporating diamond-shaped segment with high thermoelectric conversion efficiency |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |