Please use this identifier to cite or link to this item: doi:10.22028/D291-39958
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Title: Toward a Li-Ion Battery Ontology Covering Production and Material Structure
Author(s): Mutz, Marcel
Perovic, Milena
Gümbel, Philip
Steinbauer, Veit
Taranovskyy, Andriy
Li, Yunjie
Beran, Lisa
Käfer, Tobias
Dröder, Klaus
Knoblauch, Volker
Kwade, Arno
Presser, Volker
Werth, Dirk
Kraus, Tobias
Language: English
Title: Energy technology : generation, conversion, storage, distribution
Volume: 11
Issue: 5
Publisher/Platform: Wiley
Year of Publication: 2023
Free key words: battery production
battery research
cell production
data structures
electrode production
ontology
axonomy
DDC notations: 540 Chemistry
Publikation type: Journal Article
Abstract: An ontology for the structured storage, retrieval, and analysis of data on lithium-ion battery materials and electrode-to-cell production is presented. It provides a logical structure that is mapped onto a digital architecture and used to visualize, correlate, and make predictions in battery production, research, and development. Materials and processes are specified using a predetermined terminology; a chain of unit processes (steps) connects raw materials and products (items) of battery cell production. The ontology enables the attachment of analytical methods (characterization methods) to items. Workshops and interviews with experts in battery materials and production processes are conducted to ensure that the structure is conformable both for industrial-scale and laboratory-scale data generation and implementation. Raw materials and intermediate products are identified and defined for all steps to the final battery cell. Steps and items are defined based on current standard materials and process chains using terms that are in common use. Alternative structures and the connection of the ontology to other existing ontologies are discussed. The contribution provides a pragmatic, accessible way to unify the storage of materials-oriented lithium-ion battery production data. It aids the linkage of such data with domain knowledge and the automation of data analysis in production and research.
DOI of the first publication: 10.1002/ente.202200681
URL of the first publication: https://onlinelibrary.wiley.com/doi/10.1002/ente.202200681
Link to this record: urn:nbn:de:bsz:291--ds-399585
hdl:20.500.11880/35978
http://dx.doi.org/10.22028/D291-39958
ISSN: 2194-4296
2194-4288
Date of registration: 16-Jun-2023
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Chemie
NT - Materialwissenschaft und Werkstofftechnik
Professorship: NT - Prof. Dr. Tobias Kraus
NT - Prof. Dr. Volker Presser
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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