Results 11 to 20 of about 2,666,070 (302)
Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting
Nature Communications, 2021 In machine learning approaches relevant for chemical physics and material science, neural network potentials can be trained on the experimental data. The authors propose a training method applying trajectory reweighting instead of direct backpropagation ...
Stephan Thaler, Julija Zavadlav
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Multiscale modeling of respiration [PDF]
IEEE Engineering in Medicine and Biology Magazine, 2009 A multiscale mathematical model was developed to distinguish responses of external and cellular respiration to exercise of moderate intensity. The simulation shows that the characteristic MRTs of external and cellular respiration are similar even when a transit delay exists between the tissue cells and the lungs.
Haiying, Zhou +3 more
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Deep multiscale model learning [PDF]
Journal of Computational Physics, 2020 The objective of this paper is to design novel multi-layer neural network architectures for multiscale simulations of flows taking into account the observed data and physical modeling concepts. Our approaches use deep learning concepts combined with local multiscale model reduction methodologies to predict flow dynamics.
Yating Wang +4 more
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Multiscale Modeling of Electrochemical Reactions and Processes
, 2021 Multiscale Modeling of Electrochemical Reactions and Processes is a practical guide to multiscale computational methodologies. It offers a holistic understanding of the impact of reaction conditions on the overall performance of electrolyzers, fuel cells,
Wang, Yun
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Multiscale modeling for biologists [PDF]
WIREs Systems Biology and Medicine, 2009 AbstractBiomedical research frequently involves performing experiments and developing hypotheses that link different scales of biological systems such as, for instance, the scales of intracellular molecular interactions to the scale of cellular behavior and beyond to the behavior of cell populations. Computational modeling efforts that aim at exploring
Martin, Meier-Schellersheim +2 more
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A Quantitative Molecular Orbital Perspective of the Chalcogen Bond
ChemistryOpen, 2021 Invited for this month's cover are the groups of Prof. Dr. Teodorico C. Ramalho (Federal University of Lavras and University Hradec Kralove) and Prof. Dr. F. Matthias Bickelhaupt (Vrije Universiteit Amsterdam and Radboud University).
Lucas deAzevedo Santos +4 more
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Dynamic pressure variations in the lower crust caused by localized fluid-induced weakening
Communications Earth & Environment, 2022 Localized very high pressure mineral assemblages can be explained by local pressure gradients up to an order of magnitude greater than lithostatic pressure, according to a numerical visco-elasto-plastic model of fluid-induced mechanical ...
Evangelos Moulas +2 more
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B‐DNA Structure and Stability: The Role of Nucleotide Composition and Order
ChemistryOpen, 2022 Invited for this month's cover are the groups of Célia Fonseca Guerra at the Vrije Universiteit Amsterdam and Leiden University, Giampaolo Barone from the Università degli Studi di Palermo, and F.
Celine Nieuwland +4 more
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Multiscale modeling of glioblastoma [PDF]
Translational Cancer Research, 2018 As reviewed in the Editorial “ Targeting glioblastoma stem- cells: a recurrent challenge in neuro-oncology ” (1), we recently developed a 3D mathematical model of glioblastoma multiforme (GBM) progression and response to therapy (2). The development of the model necessarily required assumptions to be made about which key biological processes to ...
Yan, Huaming +7 more
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Process-Structure-Properties-Performance Modeling for Selective Laser Melting
Metals, 2019 Selective laser melting (SLM) is a promising manufacturing technique where the part design, from performance and properties process control and alloying, can be accelerated with integrated computational materials engineering (ICME).
Tatu Pinomaa +5 more
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