Screening solid state ionic conductors for high ionic conductivity

US9904772B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9904772-B2
Application numberUS-201414536506-A
CountryUS
Kind codeB2
Filing dateNov 7, 2014
Priority dateDec 2, 2013
Publication dateFeb 27, 2018
Grant dateFeb 27, 2018

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Abstract

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Non-normal statistics applied to diffusivity calculations accelerate screening of ionic conductors for electrochemical devices such as electric storage batteries, fuel cells, and sensors. Displacements of atomic species within a crystalline structure for a candidate ionic conductor material are analyzed using a Skellam distribution optionally combined with Gaussian noise to calculate values for the standard deviation, upper error bound, and lower error bound for predicted values of diffusivity (D). When the predicted values of D have sufficient statistical precision, the diffusivity calculation is terminated and the calculated diffusivity is compared to a threshold value of diffusivity. When the threshold has been exceeded, the candidate ionic conductor may be listed as a preferred good conductor. When the calculated diffusivity fails to exceed the threshold, the material may be listed as a poor conductor and may be eliminated from further consideration.

First claim

Opening claim text (preview).

What is claimed is: 1. A high ionic conductivity solid state screen method, comprising: receiving a crystal structure selection for an inorganic material; receiving a threshold value selection for diffusivity; calculating, by a processor, a displacement of a selected atomic species in the inorganic material relative to the crystal structure; calculating, by the processor, an estimate of diffusivity from a Skellam distribution of the displacement; comparing the estimate of diffusivity to the threshold value selection for diffusivity; identifying the inorganic material as a preferred material when the estimate of diffusivity is greater than or equal to the threshold value selection for diffusivity; and providing an indication specifying whether the inorganic material is the preferred material. 2. The method of claim 1 , wherein the calculating the displacement comprises a molecular dynamics simulation. 3. The method of claim 1 , wherein the calculating the displacement comprises an ab initio molecular dynamics simulation. 4. The method of claim 1 , wherein the calculating the displacement comprises a Monte Carlo simulation. 5. The method of claim 1 , further comprising determining a value for statistical significance of the estimate of diffusivity, wherein the calculating the displacement continues until the value for statistical significance of the estimate of diffusivity is less than or equal to a threshold value of statistical significance. 6. The method of claim 1 , wherein the Skellam distribution is combined with Gaussian noise. 7. The method of claim 1 , wherein the threshold value for diffusivity corresponds to a preferred minimum value of electrical conductivity of the inorganic material. 8. The method of claim 1 , further comprising receiving a temperature selection greater than or equal to 500 Kelvin for calculating the value of diffusivity. 9. The method of claim 1 , further comprising issuing a warning notification when the calculating an estimate of diffusivity indicates that both the selected atomic species and the crystal structure are in motion relative to a stationary reference. 10. The method of claim 1 , further comprising: calculating, by the processor, an upper bound for diffusivity; calculating, by the processor, a lower bound for diffusivity; determining, by the processor, a value of convergence for diffusivity from the upper bound and the lower bound; and comparing, by the processor, the estimate of diffusivity to the threshold value of diffusivity when the value of convergence corresponds to at least 95 percent confidence in the value of diffusivity. 11. The method of claim 1 , further comprising calculating a credible interval of diffusivity from the Skellam distribution of the displacement. 12. A high ionic conductivity solid state screening apparatus comprising: a processor; and a memory coupled to the processor, the memory including instructions executable by the processor to: receive a crystal structure selection for an inorganic material; receive a threshold value selection for diffusivity; calculate a displacement of a selected atomic species in the inorganic material relative to the crystal structure; calculate an estimate of diffusivity from a Skellam distribution of the displacement; compare the estimate of diffusivity to the threshold value selection for diffusivity; identify the inorganic material as a preferred material when the estimate of diffusivity is greater than or equal to the threshold value selection for diffusivity; and provide an indication specifying whether the inorganic material is the preferred material. 13. The apparatus of claim 12 , wherein the calculation of the displacement is performed by a molecular dynamics simulation. 14. The apparatus of claim 12 , wherein the calculation of the displacement is performed by an ab initio molecular dynamics simulation. 15. The apparatus of claim 12 , wherein the calculation of the displacement is performed by a Monte Carlo simulation. 16. The apparatus of claim 12 , the instructions further comprising: determine a value for statistical significance of the estimate of diffusivity; and continue the calculating the displacement continues until the value for statistical significance of the estimate of diffusivity is less than or equal to a threshold value of statistical significance. 17. The apparatus of claim 12 , wherein the Skellam distribution is combined with Gaussian noise. 18. The apparatus of claim 12 , wherein the threshold value for diffusivity corresponds to a preferred minimum value of electrical conductivity of the inorganic material. 19. The apparatus of claim 12 , the instructions further comprising issue a warning notification when the calculating an estimate of diffusivity indicates that both the selected atomic species and the crystal structure are in motion relative to a stationary reference. 20. The apparatus of claim 12 , the instructions further comprising: calculate an upper bound for diffusivity; calculate a lower bound for diffusivity; determine a value of convergence for diffusivity from the upper bound and the lower bound; and compare the estimate of diffusivity to the threshold value of diffusivity when the value of convergence corresponds to at least 95 percent confidence in the value of diffusivity. 21. A non-transitory computer readable storage medium including instructions executable by a processor comprising the steps of: receiving a crystal structure selection for an inorganic material; receiving a threshold value selection for diffusivity; calculating a displacement of a selected atomic species in the inorganic material relative to the crystal structure; calculating an estimate of diffusivity from a Skellam distribution of the displacement; comparing the estimate of diffusivity to the threshold value selection for diffusivity; identifying the inorganic material as a preferred material when the estimate of diffusivity is greater than or equal to the threshold value selection for diffusivity; and providing an indication specifying whether the inorganic material is the preferred material.

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Classifications

  • Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells (H01M10/60 takes precedence) · CPC title

  • G06F19/704Primary

    Physics · mapped topic

  • Solid electrolytes · CPC title

  • G16C20/30Primary

    Prediction of properties of chemical compounds, compositions or mixtures · CPC title

  • Energy storage using batteries · CPC title

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What does patent US9904772B2 cover?
Non-normal statistics applied to diffusivity calculations accelerate screening of ionic conductors for electrochemical devices such as electric storage batteries, fuel cells, and sensors. Displacements of atomic species within a crystalline structure for a candidate ionic conductor material are analyzed using a Skellam distribution optionally combined with Gaussian noise to calculate values for…
Who is the assignee on this patent?
Samsung Electronics Co Ltd, Massachusetts Inst Technology
What technology area does this patent fall under?
Primary CPC classification G06F19/704. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Feb 27 2018 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 3 related publications on this page (citations in our corpus or others sharing the same primary CPC).