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   Articles with "materials data" as a keyword



Concepts for a Semantically Accessible Materials Data Space: Overview over Specific Implementations in Materials Science

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recommendations! Published in 2024 at "Advanced Engineering Materials"

DOI: 10.1002/adem.202401092

Abstract: This article describes advancements in the ongoing digital transformation in materials science and engineering. It is driven by domain‐specific successes and the development of specialized digital data spaces. There is an evident and increasing need… read more here.

Keywords: materials data; science; concepts semantically; materials science ... See more keywords

Materials data validation and imputation with an artificial neural network

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recommendations! Published in 2018 at "Computational Materials Science"

DOI: 10.1016/j.commatsci.2018.02.002

Abstract: Abstract We apply an artificial neural network to model and verify material properties. The neural network algorithm has a unique capability to handle incomplete data sets in both training and predicting, so it can regard… read more here.

Keywords: data validation; materials data; network; artificial neural ... See more keywords

Materials data specification: Methods and use cases

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recommendations! Published in 2019 at "Computational Materials Science"

DOI: 10.1016/j.commatsci.2019.109086

Abstract: Abstract With the extremely fast development of Materials Genome Initiative (MGI) and Materials Informatics (MI), expressing materials data formally, semantically and scientifically is urgently demanded. According to the features of materials data, we proposed a… read more here.

Keywords: specification methods; materials data; use cases; methods use ... See more keywords

Data-driven microstructural optimization of Ag-Bi-I perovskite-inspired materials

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recommendations! Published in 2025 at "Npj Computational Materials"

DOI: 10.1038/s41524-025-01701-7

Abstract: Microstructural design is crucial yet challenging for thin-film semiconductors, creating barriers for new materials to achieve practical applications in photovoltaics and optoelectronics. We present the Daisy Visual Intelligence Framework (Daisy), which combines multiple AI models… read more here.

Keywords: materials data; inspired materials; perovskite inspired; synthesis ... See more keywords

CSIML: a cost-sensitive and iterative machine-learning method for small and imbalanced materials data sets

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recommendations! Published in 2024 at "Chemistry Letters"

DOI: 10.1093/chemle/upae090

Abstract: Materials science research benefits from the powerful machine-learning (ML) surrogate models, but it is also limited by the implicit requirement for sufficiently big and balanced data distribution for ML. In this paper, we propose a… read more here.

Keywords: materials data; data sets; small imbalanced; machine learning ... See more keywords