Atomic structure optimization

Patent metadata

Field	Value
Publication number	US-10078735-B2
Application number	US-201514928615-A
Country	US
Kind code	B2
Filing date	Oct 30, 2015
Priority date	Oct 30, 2015
Publication date	Sep 18, 2018
Grant date	Sep 18, 2018

Abstract

Electronic design automation modules simulate the behavior of structures and materials at atomic scale with parameters or a configuration that varies across iterative transformations.

First claim

The invention claimed is:

1. A system comprising:
an EDA tool transforming a model of an atomic structure into a final state to determine a plurality of ab initio characteristics of the atomic structure, comprising:
a control module causing a set of one or more ab initio modules to perform a plurality of iterative transformations to determine the plurality of ab initio characteristics of an atomic structure, the plurality of iterative transformations including:
a first iterative transformation with a first k-mesh resolution, the first iterative transformation responsive to the control module by transforming the model of the atomic structure into a first intermediate state of the model of the atomic structure; and
a second iterative transformation with a second k-mesh resolution, the second k-mesh resolution being higher than the first k-mesh resolution, the second iterative transformation responsive to the control module by transforming a previously determined intermediate state of the model of the atomic structure into the final state of the model of the atomic structure.

2. The system of claim 1 , wherein the first k-mesh resolution is a single gamma point.

3. The system of claim 1 , wherein the first k-mesh resolution is a 2×2×2 k-mesh.

4. The system of claim 1 , wherein the first and the second iterative transformations are performed with a supercell having any of (i) at least 64 atoms and (ii) at least 63 atoms and a vacancy.

5. The system of claim 1 , wherein the first and the second iterative transformations inform the plurality of ab initio characteristics including a defect structure and a migration path of the defect.

6. The system of claim 1 , wherein an iterative transformation of any of the plurality of iterative transformations yields atomic forces of the atomic structure.

7. The system of claim 1 , wherein different iterative transformations of the plurality of iterative transformations change one or more positions of one or more atoms of the atomic structure as inputs.

8. The system of claim 1 , wherein the plurality of ab initio characteristics of the atomic structure includes a plurality of atomic coordinates of a plurality of constituent atoms in a unit cell of the atomic structure.

9. The system of claim 1 , wherein the plurality of ab initio characteristics of the atomic structure includes a minimum energy of a unit cell of the atomic structure.

10. The system of claim 1 , wherein the first and second sets of solutions inform the plurality of ab initio characteristics including any of formation energy of defects, migration energy of defects, entropy of defect formation, entropy of defect migration, defect concentration, and defect diffusivity.

11. The system of claim 1 , wherein the set of one or more ab initio modules includes at least two modules, a first one of the modules performing atomic structure relaxation based on a conjugate gradient minimization and a second one of the modules performing atomic structure relaxation based on quasi-Newton minimization,
and wherein in causing the set of one or more ab initio modules to perform the plurality of iterative transformations the control module indicates which of the ab initio modules is to perform the first iterative transformation and which of the ab initio modules is to perform the second iterative transformation.

12. The system of claim 11 , wherein in causing the set of one or more ab initio modules to perform the plurality of iterative transformations the control module causes the first iterative transformation to be performed using the first module and causes the second iterative transformation to be performed using the second module.

13. The system of claim 11 , wherein in causing the set of one or more ab initio modules to perform the plurality of iterative transformations the control module provides atomic structure in a first state as input to a selected one of the ab initio modules and receives back atomic structure in a second state as transformed by the selected ab initio module.

14. The system of claim 13 , wherein the atomic structure provided by the control module to the second module is in the state in which the control module received the atomic structure back from the first module.

15. The system of claim 1 , wherein the first k-mesh resolution has either a single gamma point in a Brillouin zone of the atomic structure or a 2×2×2 k-mesh in the Brillouin zone of the atomic structure.

16. A computer executed method of transforming a model of an atomic structure into a final state to determine a plurality of ab initio characteristics of the atomic structure, comprising:
the computer causing a set of one or more ab initio modules to perform a plurality of iterative transformations to determine the plurality of ab initio characteristics of an atomic structure, including:
the computer causing a first iterative transformation of the atomic structure with a first k-mesh resolution, the first iterative transformation responsive to at control module by transforming the model of the atomic structure into a first intermediate state of the model of the atomic structure; and
the computer causing a final iterative transformation with a final k-mesh resolution, the final k-mesh resolution being higher than the first k-mesh resolution, the final iterative transformation responsive to the control module by transforming a previously determined intermediate state of the model of the atomic structure into the final state of the model of the atomic structure.

17. The method of claim 16 , wherein the first k-mesh resolution is a single gamma point.

18. The method of claim 16 , wherein the first k-mesh resolution is a 2×2×2 k-mesh.

19. The method of claim 16 , wherein the first and the second iterative transformations are performed with a supercell having any of (i) at least 64 atoms and (ii) at least 63 atoms and a vacancy.

20. The method of claim 16 , wherein the first and the second iterative transformations inform the plurality of ab initio characteristics including a defect structure and a migration path of the defect.

21. The method of claim 16 , wherein an iterative transformation of any of the plurality of iterative transformations yields atomic forces of the atomic structure.

22. The method of claim 16 , wherein different iterative transformations of the plurality of iterative transformations change one or more positions of one or more atoms of the atomic structure as inputs.

23. The method of claim 16 , wherein the plurality of ab initio characteristics of the atomic structure includes a plurality of atomic coordinates of a plurality of constituent atoms in a unit cell of the atomic structure.

24. The method of claim 16 , wherein the plurality of ab initio characteristics of the atomic structure includes a minimum energy of a unit cell of the atomic structure.

25. The method of claim 16 , wherein the first and second sets of solutions inform the plurality of ab initio characteristics including any of formation energy of defects, migration energy of defects, entropy of defect formation, entropy of defect migration, defect concentration, and defect diffusivity.

26. The method of claim 16 , wherein the computer causes the first iterative transformation to be performed using conjugate gradient minimization, and the final iterative transformation to be performed using quasi-Newton minimization.

27. The meth

Assignees

• Synopsys Inc

Inventors

• Lee Kyuho
• Oh Yong-Seog
• Kumar Ashutosh
• Balasingam Pratheep

Classifications

• G06F30/20

  Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title

• G16C10/00 Primary

  Computational theoretical chemistry, i.e. ICT specially adapted for theoretical aspects of quantum chemistry, molecular mechanics, molecular dynamics or the like · CPC title

• G06F17/18

  for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title

• G06F19/701 Primary

  Physics · mapped topic