Ontological representation of experiments in electrochemistry and synthetic chemistry

Presentation given at the Ontologies4Chem Workshop 2025.Abstract: This talk presented a high-level abstraction model designed for the ontological representation of chemical experiments. Using two distinct and complex use cases, high-throughput electrochemical testing and automated organic synthesis, the presenters demonstrated how this model can capture diverse experimental scenarios. The primary goal is to engage the audience in a discussion to identify and address common challenges, as well as to pinpoint any gaps or weaknesses in the model.

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Publication Details

Journal
Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)
Published
2025-11-12
DOI
https://doi.org/10.5281/zenodo.18016880
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00
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article

Ontological representation of experiments in electrochemistry and synthetic chemistry

Alexei A. Lapkin, Daniel Willimetz, Jürgen Schumacher, Zhang Shuyuan
Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)
Machine Learning in Materials Science
article

Ontological representation of experiments in electrochemistry and synthetic chemistry

Alexei A. Lapkin, Daniel Willimetz, Jürgen Schumacher, Zhang Shuyuan
article en

Abstract

Presentation given at the Ontologies4Chem Workshop 2025.Abstract: This talk presented a high-level abstraction model designed for the ontological representation of chemical experiments. Using two distinct and complex use cases, high-throughput electrochemical testing and automated organic synthesis, the presenters demonstrated how this model can capture diverse experimental scenarios. The primary goal is to engage the audience in a discussion to identify and address common challenges, as well as to pinpoint any gaps or weaknesses in the model.

Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences)
University of Cambridge (GB), Fraunhofer Institute for Algorithms and Scientific Computing (DE), Fraunhofer Institute for Solar Energy Systems (DE), ZHAW Zurich University of Applied Sciences (CH)
Openalex Percentile: Top 46%
Machine Learning in Materials Science
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Ontological representation of experiments in electrochemistry and synthetic chemistry — Alexei A. Lapkin, Daniel Willimetz, et al. · Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences) (2025) | TGRS Research Map | TGRS