Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry. [PDF]
Chem Sci, 2023 The rapid growth of materials chemistry data, driven by advancements in large-scale radiation facilities as well as laboratory instruments, has outpaced conventional data analysis and modelling methods, which can require enormous manual effort.
Anker AS +3 more
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Editorial for "Materials Chemistry" Sections on Molecules. [PDF]
Molecules, 2020 Materials chemistry has been one of the most talked-about areas of materials research over the past decades [...
Marrocchi A.
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The "Materials Chemistry" Section of Molecules: A Multidisciplinary Environment for Materials-Based Researches. [PDF]
Molecules, 2020 The “Materials Chemistry” Section of Molecules is an open access place for the dissemination of theoretical and experimental studies related to the chemical approaches to materials-based problems [...
Cirillo G.
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Editorial for "Materials Chemistry" Section, in Journal Molecules. [PDF]
Molecules, 2020 Dear colleagues and friends, it is a great pleasure to summarize the most significant successes achieved during 2019 in the “Materials Chemistry” Section (https://www [...
Malucelli G.
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Synthesis and stability of switchable CO2-responsive foaming coupled with nanoparticles
iScience, 2022 Summary: CO2-responsive foaming has been drawing huge attention due to its unique switching characteristics in academic research and industrial practices, whereas its stability remains questionable for further applications.
Songyan Li +5 more
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Quantum materials with strong spin-orbit coupling : challenges and opportunities for materials chemists [PDF]
, 2021 ASG acknowledges funding through an EPSRC Early Career Fellowship EP/T011130/1.Spin-orbit coupling is a quantum effect that can give rise to exotic electronic and magnetic states in the compounds of the 4d and 5d transition metals. Exploratory synthesis,
Gibbs, Alexandra +2 more
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Olympus, enhanced: benchmarking mixed-parameter and multi-objective optimization in chemistry and materials science [PDF]
, 2023 Experiment planning algorithms are a required component of autonomous platforms for scientific discovery. Selecting a suitable optimization algorithm for a novel application is an important yet difficult choice a researcher has to make based on past ...
Alán, Aspuru-Guzik +6 more
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Benchmarking Graph Neural Networks for Materials Chemistry [PDF]
, 2021 Graph neural networks (GNNs) have received intense interest as a rapidly expanding class of machine learning models remarkably well-suited for materials applications.
Eric, Juarez +3 more
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Outstanding Reviewers for Materials Chemistry Frontiersin 2019 [PDF]
, 2020 We would like to take this opportunity to highlight the Outstanding Reviewers forMaterials Chemistry Frontiersin 2019, as selected by the editorial team for their significant contribution to the ...
Pucci, Andrea +11 more
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Clip-off Chemistry: Synthesis by Programmed Disassembly of Reticular Materials [PDF]
, 2021 Bond-breaking is an essential process in natural and synthetic chemical transformations. Accordingly, the ability for researchers to strategically dictate which bonds in a given system are broken translates to greater synthetic control, as historically ...
Judith, Juanhuix +10 more
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