High-Throughput Exploration of Evolutionary Structural Materials

While experimental high-throughput and computational methods exist for the development of functional materials, structural materials are still being developed on the base of experience, stepwise prediction and punctual support of computational models. As a result, many major breakthroughs have been...

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Bibliographic Details
Published inJournal of heat treatment and materials : HTM = Zeitschrift für Werkstoffe, Wärmebehandlung, Fertigung Vol. 73; no. 1; pp. 3 - 12
Main Authors Ellendt, N., Mädler, L.
Format Journal Article
LanguageEnglish
Published De Gruyter 14.02.2018
Subjects
Descriptor
Deskriptor
Framework
High-Throughput
Hochdurchsatz
Konstruktionswerkstoff
Konzept
Machine Learning
Maschinelles Lernen
Structural Material
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Summary:While experimental high-throughput and computational methods exist for the development of functional materials, structural materials are still being developed on the base of experience, stepwise prediction and punctual support of computational models. As a result, many major breakthroughs have been and still are achieved by coincidence under non-intuitive conditions. Experimental high throughput methods allow to explore large process windows where no prediction is possible due to lack of existent data. This work proposes the high throughput method “Farbige Zustände” as a novel approach for the experimental exploration of structural materials. New methods for sample synthesis, treatment and characterization are developed as well as computational methods for ad-hoc data analysis, search and experiment planning.
ISSN:1867-2493
2194-1831
DOI:10.3139/105.110345