Simulation scaling with dft and non-dft
US-2015088473-A1 · Mar 26, 2015 · US
US9858365B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9858365-B2 |
| Application number | US-201414523135-A |
| Country | US |
| Kind code | B2 |
| Filing date | Oct 24, 2014 |
| Priority date | Oct 24, 2013 |
| Publication date | Jan 2, 2018 |
| Grant date | Jan 2, 2018 |
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A method for modeling a material at least partially-defined by atomic information includes, for each of a plurality of configurations of the material, determining energy moments for a density of states of the respective configuration of the material, and generating a tight binding Hamiltonian matrix for the respective configuration of the material. The method further includes, for each of the plurality of configurations of the material, forming a tight binding model of the configuration of the material by resolving a linking of (i) the energy moments for the density of states of the material to (ii) the tight binding Hamiltonian matrix for the material. Still further the method includes, based on the tight binding models for each of the configurations of the material, forming an environmentally-adapted tight binding model.
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What is claimed: 1. A method for modeling a material at least partially-defined by atomic information, the method comprising: for each of a plurality of configurations of the material: determining, by a linking module of a computing system, energy moments for a density of states of the respective configuration of the material; generating, by the linking module, a tight binding Hamiltonian matrix for the respective configuration of the material, wherein the tight binding Hamiltonian matrix is at least partially expressed in terms of one or more tight binding parameters; forming, by the linking module, a tight binding model of the configuration of the material by resolving a linking of (i) the energy moments for the density of states of the material to (ii) the tight binding Hamiltonian matrix for the material, wherein the tight binding model includes determined values of the one or more tight binding parameters, based on the tight binding models for each of the configurations of the material, forming an environmentally-adapted tight binding model, wherein the environmentally-adapted tight binding model models the material for environmentally-dependent variations in the atomic information of the material. 2. The method of claim 1 , wherein the environmentally-dependent variations in the atomic information of the material comprise variations (i) in interatomic distances in the material, (ii) in atomic-coordinations in the material, (iii) in alloy concentrations in the material, (iv) in strain in the material, (v) in angular momentum of occupied states in the material, (vi) in dimension of the periodicity in the material, or (vii) in surface passivation atoms in the material. 3. The method of claim 2 , wherein the environmentally-dependent variations are represented at least partially in the plurality of configurations of the materials, wherein each of the plurality of configurations of the material defines a variation of the atomic information different than that defined by any other of the plurality of configurations. 4. The method of claim 1 , wherein the density of states is an angular momentum resolved local density of states. 5. The method of claim 1 , wherein generating the tight binding Hamiltonian matrix for the respective configuration of the material includes forming the tight binding Hamiltonian matrix as a symbolic tri-diagonalized matrix, wherein components of the symbolic tri-diagonalized matrix are expressed in terms of the one or more tight binding parameters. 6. The method of claim 5 , wherein forming the tight binding model by resolving the linking of (i) the energy moments for the density of states of the material to (ii) the tight binding Hamiltonian matrix for the material elements includes forming a series of expressions linking the energy moments to components of the symbolic tri-diagonalized matrix. 7. The method of claim 6 , wherein forming the tight binding model further includes collectively solving the series of expressions to obtain the one or more tight binding parameters. 8. The method of claim 6 , wherein the series of expressions is a system of non-linear equations. 9. The method of claim 1 , wherein forming an environmentally-adapted tight binding model includes fitting the one or more tight binding parameters for the plurality of configurations of the materials to one or more model functions. 10. The method of claim 1 , wherein the material is either one or a suitable combination of the following classes of materials: a semiconductor, a binary semiconductor alloy, a target or ternary semiconductor alloy, a metal/semiconductor heterostructure, a metal-dielectric-semiconductor nanostructure, an insulator-dielectric nanostructure, a metal-dielectric nanostructure, or a metal-metal nanostructure. 11. A method of a modeling a macroscopic material, the method comprising: applying the method of claim 1 to microscopic material as the material at least partially-defined by the atomic information, the microscopic material being formed of no more than 100 atoms; and scaling the environmentally-adapted tight binding model of the microscopic material into the macroscopic material. 12. The method of claim 11 , wherein the microscopic material is formed of no more than 50 atoms, no more than 10 atoms, or no more than 2 atoms. 13. The method of claim 11 , wherein the microscopic material is either one or a suitable combination of the following classes of materials: a 111-V semiconductor material, a group IV semiconductor material, a metal, a polymer, or an insulator. 14. A non-transitory computer-readable storage medium having stored thereon a set of instructions that specially configure a computing device such that, when executed by one or more processors, the instructions cause the computing device to: for each of a plurality of configurations of a material: determine energy moments for a density of states of the respective configuration of the material; generate a tight binding Hamiltonian matrix for the respective configuration of the material, wherein the tight binding Hamiltonian matrix is at least partially expressed in terms of one or more tight binding parameters; form a tight binding model of the configuration of the material by resolving a linking of (i) the energy moments for the density of states of the respective configuration of the material to (ii) the tight binding Hamiltonian matrix for the respective configuration of the material, wherein the tight binding model includes determined values of the one or more tight binding parameters, based on the tight binding models for each of the configurations of the material, form an environmentally-adapted tight binding model, wherein the environmentally-adapted tight binding model models the material for environmentally-dependent variations in the atomic information of the material. 15. The non-transitory computer-readable storage medium of claim 14 , wherein generating the tight binding Hamiltonian matrix for the respective configuration of the material includes: generating the tight binding Hamiltonian matrix as a symbolic matrix, wherein components of the symbolic matrix include the one or more tight binding parameters; recursively converting the symbolic matrix to a tri-diagonalized symbolic matrix. 16. The non-transitory computer-readable storage medium of claim 14 , wherein the one or more right binding parameters include an on-site energy parameter. 17. The non-transitory computer-readable storage medium of claim 14 , wherein the one or more right binding parameters include one or more two-center integral parameters. 18. A system comprising: a storage mechanism to store data indicative of a tight binding model, wherein the tight binding model is configured to model properties of a material at least partially-defined by atomic information; one or more processors; and one or more non-transitory memories coupled to the one or more processors, wherein the one or more non-transitory memories include computer executable instructions stored therein that specially configure the one or more processors such that, when executed by the one or more processors, the computer executable instructions cause a computer device to: determine energy moments for a density of states of the material, generate a tight binding Hamiltonian matrix for the material, wherein the tight binding Hamiltonian matrix is at least partially expressed in terms of one or more tight binding parameters, form a tight binding model of the material by resolving a linking of (i) the energy moments for the d
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