# Toward the Atomic-Level Analysis of Ground-State Electronic Structures of Solid Materials via Prediction from Core-Loss Spectra: A Computational Study in Si

https://mdr.nims.go.jp/datasets/f985fead-b571-4be9-8096-a52da0bb8065

## File

- [takahara-et-al-2024-toward-the-atomic-level-analysis-of-ground-state-electronic-structures-of-solid-materials-via.pdf](https://mdr.nims.go.jp/filesets/fc4789c7-e738-4821-9a44-14642f1ca119/download) ([Detail](https://mdr.nims.go.jp/filesets/fc4789c7-e738-4821-9a44-14642f1ca119.md))

## Id

f985fead-b571-4be9-8096-a52da0bb8065

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-09-10T21:50:50.389105Z

## Updated at

2024-10-02T03:30:19.232951Z

## Published at

2024-10-02T03:30:19.507679Z

## Doi



## First published url

https://doi.org/10.1021/acs.jpcc.4c02818

## Date published

2024-08-15

## Recorded date published

2024-8-15

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: 'Toward the Atomic-Level Analysis of Ground-State Electronic Structures of
    Solid Materials via Prediction from Core-Loss Spectra: A Computational Study in
    Si'
  title_type: original
  lang: en

## Description

- description: Local electronic structure in the ground state is essential for understanding
    the stability and properties of materials. Core-loss spectroscopy using electron
    or X-ray provides insights into the local electronic structure, but directly observable
    information is limited to the partial density of state (PDOS) of the conduction
    band at the excited state. To overcome this limitation, we developed a machine
    learning (ML) approach by creating a database of Si-K core-loss spectra and corresponding
    ground-state PDOS for various silicon structures. Using this database, we constructed
    an ML model capable of predicting the atom-specific ground-state PDOS of the valence
    and conduction bands from Si-K edges. Our model demonstrated the ability of the
    ML to extract the complex correlation between ground-state PDOS and Si-K edges.
    This study provides crucial insights into achieving atomic-level analysis of ground-state
    electronic structures, paving the way for a deeper understanding of stability
    and properties of materials.
  description_type: abstract
  lang: und

## Creator

- name: Izumi Takahara
  role: author
- name: Fumihiko Uesugi
  role: author
  orcid: https://orcid.org/0000-0003-3346-4218
  organization: National Institute for Materials Science
- name: Koji Kimoto
  role: author
  orcid: https://orcid.org/0000-0002-3927-0492
  organization: National Institute for Materials Science
- name: Kiyou Shibata
  role: author
- name: Teruyasu Mizoguchi
  role: author

## Contact agent



## Publisher

organization: American Chemical Society (ACS)

## Managing organization



## Keyword

- subject: Machine learning
  schema: not_defined
- subject: ELNES
  schema: not_defined
- subject: XANES
  schema: not_defined
- subject: PDOS
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by/4.0/

## Other identifier(s)



## Data origin



## Embargo



## Journal

- title: The Journal of Physical Chemistry C
  issn: '19327447'
  volume: '128'
  issue: '32'
  start_page: 13500
  end_page: 13507

## Conference



## Related item



## Funding

- funder_name: New Energy and Industrial Technology Development Organization
- identifier: JP-MJCR1993
  funder_name: Core Research for Evolutional Science and Technology
- identifier: 24K08016
  funder_name: Japan Society for the Promotion of Science
- identifier: 24KJ0939
  funder_name: Japan Society for the Promotion of Science
- identifier: JP19H05787
  funder_name: Japan Society for the Promotion of Science

## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



## Specific property for specimen



## Process for specimen treatment



## Computational method



## Energy level/transition state



## Software



## Custom property



## Fileset

- id: fc4789c7-e738-4821-9a44-14642f1ca119
  filename: takahara-et-al-2024-toward-the-atomic-level-analysis-of-ground-state-electronic-structures-of-solid-materials-via.pdf
  content_type: application/pdf
  size: 3558821
  md5: 12473ab5aa7e84c397d1a777343f27d6

## Thumbnail

fileset_id: fc4789c7-e738-4821-9a44-14642f1ca119
filename: takahara-et-al-2024-toward-the-atomic-level-analysis-of-ground-state-electronic-structures-of-solid-materials-via.pdf