# Automatic extraction of materials and properties from superconductors scientific literature

https://mdr.nims.go.jp/datasets/9970d39a-ccfc-406c-bb80-9ca1ac64d864

## File

- [Automatic extraction of materials and properties from superconductors scientific literature.pdf](https://mdr.nims.go.jp/filesets/9ea32845-e04c-4108-abdb-fcfab7bb1740/download) ([Detail](https://mdr.nims.go.jp/filesets/9ea32845-e04c-4108-abdb-fcfab7bb1740.md))

## Id

9970d39a-ccfc-406c-bb80-9ca1ac64d864

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2023-06-21T07:59:54.095865Z

## Updated at

2024-01-05T13:12:53.173860Z

## Published at

2023-12-26T23:30:15.716534Z

## Doi



## First published url

https://doi.org/10.1080/27660400.2022.2153633

## Date published

2023-12-31

## Recorded date published

2023-12-31

## Resource type

journal

## Manuscript type

vor

## Collection



## Title

- title: Automatic extraction of materials and properties from superconductors scientific
    literature
  title_type: original
  lang: en

## Description

- description: The automatic extraction of materials and related properties from the
    scientific literature is gaining attention in data-driven materials science (Materials
    Informatics). In this paper, we discuss Grobid-superconductors, our solution for
    automatically extracting superconductor material names and respective properties
    from text. Built as a Grobid module, it combines machine learning and heuristic
    approaches in a multi-step architecture that supports input data as raw text or
    PDF documents. Using Grobid-superconductors, we built SuperCon2, a database of
    40,324 materials and properties records from 37,700 papers. The material (or sample)
    information is represented by name, chemical formula, and material class, and
    is characterized by shape, doping, substitution variables for components, and
    substrate as adjoined information. The properties include the Tc superconducting
    critical temperature and, when available, applied pressure with the Tc measurement
    method.
  description_type: abstract
  lang: en

## Creator

- name: Luca Foppiano
  role: author
  orcid: https://orcid.org/0000-0002-6114-6164
  organization: NIMS
  department: MaDIS
- name: Pedro Baptista Castro
  role: author
  orcid: https://orcid.org/0000-0001-8673-2840
  organization: NIMS
  department: MANA
- name: Pedro Ortiz Suarez
  role: author
  orcid: https://orcid.org/0000-0003-0343-8852
  organization: University of Mannheim
  department: Data and Web Science Group
- name: Kensei Terashima
  role: author
  orcid: https://orcid.org/0000-0003-0375-3043
  organization: NIMS
  department: MANA
- name: Yoshihiko Takano
  role: author
  orcid: https://orcid.org/0000-0002-1541-6928
  organization: NIMS
  department: MANA
- name: Masashi Ishii
  role: author
  orcid: https://orcid.org/0000-0003-0357-2832
  organization: NIMS
  department: MaDIS

## Contact agent



## Publisher

organization: Tayor & Francis

## Managing organization



## Keyword

- subject: Materials informatics
  schema: not_defined
- subject: superconductors
  schema: not_defined
- subject: machine learning
  schema: not_defined
- subject: NLP
  schema: not_defined
- subject: TDM
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: 'SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS: METHODS'
  issn: '27660400'
  volume: '3'
  issue: '1'
  start_page: 2153633
  end_page: 2153633
  article_number: '2153633'

## Conference



## Related item

- title: 'SuperCon 2 dataset     '
  identifier: https://mdr.nims.go.jp/concern/datasets/4q77fv540
  identifier_type: URI
  relation_type: documents
  related_item_type: dataset

## Funding



## 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: 9ea32845-e04c-4108-abdb-fcfab7bb1740
  filename: Automatic extraction of materials and properties from superconductors
    scientific literature.pdf
  content_type: application/pdf
  size: 9024364
  md5: 7094fa53b1ad5aace260cae5d9636c59

## Thumbnail

fileset_id: 9ea32845-e04c-4108-abdb-fcfab7bb1740
filename: Automatic extraction of materials and properties from superconductors scientific
  literature.pdf