# Open electrolyte database generated via an automated molecular dynamics simulation framework

https://mdr.nims.go.jp/datasets/f8e08eb0-70c0-464f-8637-dbf0c7871102

## File

- [s41524-026-02093-y (1).pdf](https://mdr.nims.go.jp/filesets/d789338f-2e85-4a4d-b2cd-bd151eb74985/download) ([Detail](https://mdr.nims.go.jp/filesets/d789338f-2e85-4a4d-b2cd-bd151eb74985.md))

## Id

f8e08eb0-70c0-464f-8637-dbf0c7871102

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2026-09-21T01:37:06.375642Z

## Updated at

2026-09-24T00:16:02.066501Z

## Published at

2026-09-24T01:41:50.440304Z

## Doi



## First published url

https://doi.org/10.1038/s41524-026-02093-y

## Date published

2026-04-20

## Recorded date published



## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Open electrolyte database generated via an automated molecular dynamics simulation
    framework
  title_type: original
  lang: en

## Description

- description: Modern battery technologies demand electrolytes that simultaneously
    deliver multiple functions tailored to diverse applications. Achieving such multi-objective
    optimization remains fundamentally challenging, as many key electrolyte properties
    are intrinsically in competition. Data-driven approaches provide a systematic
    route to navigating the vast compositional space of electrolyte systems; however,
    their effectiveness critically depends on the availability of comprehensive datasets
    that capture not only descriptors derived from isolated molecular structures and
    properties but also structural and physicochemical characteristics of electrolytes
    as integrated solutions. Here, we report an open electrolyte database comprising
    approximately 5600 electrolyte formulations, generated using a fully automated,
    high-throughput molecular dynamics simulation framework. The dataset spans diverse
    combinations of solvents, salts, and concentrations, and provides unified descriptions
    of electrolyte structures and physicochemical properties. To facilitate data exploration
    and utilization, we implement a web-based graphical user interface (https://oedb.jp)
    that enables interactive browsing and comparison of electrolyte compositions together
    with their associated descriptors, while also making the database accessible to
    LLM-based agents for data reference. This Open Electrolyte Database for Batteries
    (OEDB) establishes a foundation for data-driven electrolyte design grounded in
    structure–property relationships at the electrolyte level.
  description_type: abstract
  lang: und

## Creator

- name: Kou Nakamura
  role: author
- name: Norio Takenaka
  role: author
- name: Masatoshi Hanai
  role: author
- name: Yuna Oikawa
  role: author
- name: Ryo Tamura
  role: author
  orcid: https://orcid.org/0000-0002-0349-358X
  organization: National Institute for Materials Science
- name: Koji Tsuda
  role: author
  orcid: https://orcid.org/0000-0002-4288-1606
  organization: National Institute for Materials Science
- name: Masanobu Nakayama
  role: author
- name: Junichiro Shiomi
  role: author
- name: Atsuo Yamada
  role: author

## Contact agent



## Publisher

organization: Springer Science and Business Media LLC

## Managing organization



## Keyword

- subject: electrolyte database
  schema: not_defined
- subject: AI
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by-nc-nd/4.0/
  date_licensed: 2026-06-19

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: npj Computational Materials
  issn: '20573960'
  volume: '12'
  issue: '1'
  article_number: '215'

## Conference



## Related item



## Funding

- identifier: JPMXP1121467561
  funder_name: Ministry of Education, Culture, Sports, Science and Technology

## 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: d789338f-2e85-4a4d-b2cd-bd151eb74985
  filename: s41524-026-02093-y (1).pdf
  content_type: application/pdf
  size: 2633273
  md5: 243bd5b6d67ebe76389e5ed0d32709c4

## Thumbnail

fileset_id: d789338f-2e85-4a4d-b2cd-bd151eb74985
filename: s41524-026-02093-y (1).pdf