Results 11 to 20 of about 10,388,998 (324)
Methods, progresses, and opportunities of materials informatics
InfoMat, 2023 As an implementation tool of data intensive scientific research methods, machine learning (ML) can effectively shorten the research and development (R&D) cycle of new materials by half or even more.
Chen Li, Kun Zheng
doaj +2 more sources
MaterialsAtlas.org: a materials informatics web app platform for materials discovery and survey of state-of-the-art [PDF]
npj Computational Materials, 2022 The availability and easy access of large-scale experimental and computational materials data have enabled the emergence of accelerated development of algorithms and models for materials property prediction, structure prediction, and generative design of
Jianjun Hu +7 more
doaj +2 more sources
APL Materials, 2016 Our ability to collect “big data” has greatly surpassed our capability to analyze it, underscoring the emergence of the fourth paradigm of science, which is data-driven discovery.
Ankit Agrawal, Alok Choudhary
doaj +2 more sources
The Journal of The Institute of Image Information and Television Engineers, 2023 Materials informatics, data-enabled investigation, is a "fourth paradigm" in materials science research after the conventional empirical approach, theoretical science, and computational research. Materials informatics has two essential ingredients: fingerprinting materials proprieties and the theory of statistical inference and learning.
Yuma Iwasaki
openaire +2 more sources
A framework for materials informatics education through workshops. [PDF]
MRS Bull, 2023 The burgeoning field of materials informatics necessitates a focus on educating the next generation of materials scientists in the concepts of data science, artificial intelligence (AI), and machine learning (ML).
Mannodi-Kanakkithodi A +5 more
europepmc +2 more sources
Materials Informatics for Mechanical Deformation: A Review of Applications and Challenges. [PDF]
Materials (Basel), 2021 In the design and development of novel materials that have excellent mechanical properties, classification and regression methods have been diversely used across mechanical deformation simulations or experiments.
Frydrych K +6 more
europepmc +2 more sources
Journal of Chemical Information and Modeling, 2018 Hanoch Senderowitz, Alexander Tropsha
semanticscholar +6 more sources
Materials informatics platform with three dimensional structures, workflow and thermoelectric applications. [PDF]
Sci Data, 2021 Since the proposal of the “Materials Genome Initiative”, several material databases have emerged and advanced many materials fields. In this work, we present the Materials Informatics Platform with Three-Dimensional Structures (MIP-3d).
Yao M +7 more
europepmc +2 more sources
Materials informatics approach using domain modelling for exploring structure-property relationships of polymers. [PDF]
Sci Rep, 2022 In the development of polymer materials, it is an important issue to explore the complex relationships between domain structure and physical properties. In the domain structure analysis of polymer materials, 1H-static solid-state NMR (ssNMR) spectra can ...
Hara K +4 more
europepmc +2 more sources
Practical application of quantum neural network to materials informatics. [PDF]
Sci Rep, 2023 Quantum neural network (QNN) models have received increasing attention owing to their strong expressibility and resistance to overfitting. It is particularly useful when the size of the training data is small, making it a good fit for materials ...
Hirai H.
europepmc +3 more sources