# Periodic table-based compositional descriptors for accelerating electrochemical material discovery: Li-ion conductors and oxygen evolution electrocatalysts

https://mdr.nims.go.jp/datasets/c7ec772e-9300-42ee-aabf-b07b43d54cc5

## File

- [Periodic table-based compositional descriptors for accelerating electrochemical material discovery  Li-ion conductors and oxygen evolution electrocata.pdf](https://mdr.nims.go.jp/filesets/d4038a42-ac89-4cbf-a66d-e737b0ae22ad/download) ([Detail](https://mdr.nims.go.jp/filesets/d4038a42-ac89-4cbf-a66d-e737b0ae22ad.md))

## Id

c7ec772e-9300-42ee-aabf-b07b43d54cc5

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2025-06-17T08:01:45.334875Z

## Updated at

2025-06-18T03:30:21.619329Z

## Published at

2025-06-18T03:20:15.181608Z

## Doi

https://doi.org/10.48505/nims.5536

## First published url

https://doi.org/10.1080/27660400.2025.2513218

## Date published

2025-12-31

## Recorded date published

2025-12-31

## Resource type

journal_article

## Manuscript type

accepted_manuscript

## Collection



## Title

- title: 'Periodic table-based compositional descriptors for accelerating electrochemical
    material discovery: Li-ion conductors and oxygen evolution electrocatalysts'
  title_type: original
  lang: en

## Description

- description: "The discovery of high-performance electrochemical materials is essential
    for advancing sustainable energy technologies, yet conventional approaches are
    often limited by trial-and-error experimental processes, time-consuming computations
    and the need for detailed structural data. To address these challenges, we introduce
    a periodic table-based compositional descriptor, referred to as the periodic descriptor.
    Unlike existing methods, our periodic descriptor only requires chemical formulas,
    making it straightforward and versatile while supporting reversible design, which
    allows direct conversion between descriptors and chemical compositions. \r\nWe
    applied this approach to two critical applications: fast Li-ion conductors for
    solid-state electrolytes and platinum-group metal (PGM)-free oxygen evolution
    reaction (OER) electrocatalysts for water electrolysis. In the case of Li-ion
    conductors, our model identified both known materials and new candidates, including
    anti-fluorite structures that exhibit high ionic conductivity at 600-700 K—significantly
    lower than that of traditional anti-fluorite compounds like Li₂S and Li₂Se. For
    electrocatalysts, we identified Fe0.1Co0.1Cu0.1Ag0.1W0.6 oxide, which showed electrochemical
    performance comparable to the benchmark PGM catalyst RuO₂ but at a lower overpotential.\r\nThe
    periodic descriptor demonstrates high predictive accuracy while maintaining low
    dimensionality, simplifying both the discovery and optimization of materials.
    This work not only establishes a scalable, efficient framework for material exploration
    but also highlights the potential for accelerating breakthroughs in green energy
    solutions, such as next-generation batteries and green hydrogen production, ultimately
    contributing to carbon neutrality."
  description_type: abstract
  lang: und

## Creator

- name: Yen-Ju Wu
  role: author
  orcid: https://orcid.org/0000-0003-2647-3407
- name: Yibin Xu
  role: author
  orcid: https://orcid.org/0000-0001-8600-8748
- name: Lei Fang
  role: author
  orcid: https://orcid.org/0000-0003-4706-0521
- name: Wenqin Peng
  role: author
- name: Ken Sakaushi
  role: author
  orcid: https://orcid.org/0000-0003-4797-9087
- name: Meiqi Zhang
  role: author
- name: Masao Arai
  role: author
  orcid: https://orcid.org/0000-0003-0088-5649
- name: Yukinori Koyama
  role: author
  orcid: https://orcid.org/0000-0002-7090-4430

## Contact agent



## Publisher

organization: Informa UK Limited

## Managing organization



## Keyword

- subject: Solid electrolyte
  schema: not_defined
- subject: ionic conductor
  schema: not_defined
- subject: electrocatalyst
  schema: not_defined
- subject: energy storage
  schema: not_defined
- subject: descriptor
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: 'Science and Technology of Advanced Materials: Methods'
  issn: '27660400'

## Conference



## Related item



## Funding

- identifier: JPMXP1122712807
  funder_name: Ministry of Education, Culture, Sports, Science and Technology
- identifier: JPMJPF2016
  funder_name: Center of Innovation Program
- identifier: Materials Open Platform for All Solid-State Batter
  funder_name: National Institute for Materials Science
- funder_name: Advanced Battery Collaboration

## 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



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## Custom property



## Fileset

- id: d4038a42-ac89-4cbf-a66d-e737b0ae22ad
  filename: Periodic table-based compositional descriptors for accelerating electrochemical
    material discovery  Li-ion conductors and oxygen evolution electrocata.pdf
  content_type: application/pdf
  size: 6747265
  md5: b729a84388376aba09e2cf0cb76826b5

## Thumbnail

fileset_id: d4038a42-ac89-4cbf-a66d-e737b0ae22ad
filename: Periodic table-based compositional descriptors for accelerating electrochemical
  material discovery  Li-ion conductors and oxygen evolution electrocata.pdf