Modular Ontology-Driven Data Capturing for Machine Learning-Assisted Supported Catalytically Active Metal Solutions Design

Employing the modular ontology modelling approach to capture experimental data from various researchers. The data is used for machine learning training for SCLAMS catalyst discovery.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-14
DOI
https://doi.org/10.5281/zenodo.17409409
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00
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article

Modular Ontology-Driven Data Capturing for Machine Learning-Assisted Supported Catalytically Active Metal Solutions Design

Zenodo (CERN European Organization for Nuclear Research)
Machine Learning in Materials Science
article

Modular Ontology-Driven Data Capturing for Machine Learning-Assisted Supported Catalytically Active Metal Solutions Design

article en

Abstract

Employing the modular ontology modelling approach to capture experimental data from various researchers. The data is used for machine learning training for SCLAMS catalyst discovery.

Zenodo (CERN European Organization for Nuclear Research)
Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 57%
Machine Learning in Materials Science
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Modular Ontology-Driven Data Capturing for Machine Learning-Assisted Supported Catalytically Active Metal Solutions Design · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS