Results 11 to 20 of about 522,455 (311)
Choosing the right molecular machine learning potential. [PDF]
Chem Sci, 2021 Quantum-chemistry simulations based on potential energy surfaces of molecules provide invaluable insight into the physicochemical processes at the atomistic level and yield such important observables as reaction rates and spectra.
Pinheiro M +4 more
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Machine Learning Potential for Serpentines
Journal of Geophysical Research: Machine Learning and ComputationSerpentines are layered hydrous magnesium silicates (MgO⋅SiO2⋅H2O) formed through serpentinization, a geochemical process that significantly alters the physical property of the mantle.
Hongjin Wang +2 more
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Machine learning potential predictor of idiopathic pulmonary fibrosis [PDF]
Frontiers in GeneticsIntroductionIdiopathic pulmonary fibrosis (IPF) is a severe chronic respiratory disease characterized by treatment challenges and poor prognosis.
Chenchun Ding +8 more
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Machine Learning a General-Purpose Interatomic Potential for Silicon [PDF]
Physical Review X, 2018 The success of first-principles electronic-structure calculation for predictive modeling in chemistry, solid-state physics, and materials science is constrained by the limitations on simulated length scales and timescales due to the computational cost ...
Albert P. Bartók +3 more
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Lifelong Machine Learning Potentials
Journal of Chemical Theory and Computation, 2023 Journal of Chemical Theory and Computation, 19 (12)
Marco Eckhoff, Markus Reiher
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Machine learning potential era of zeolite simulation. [PDF]
Chem Sci, 2022 The machine learning atomic simulation will usher the research of zeolite, as other complex materials, into a new era featuring the easy access to zeolite functionalities predicted from theory.
Ma S, Liu ZP.
europepmc +3 more sources
Modeling Groundwater Potential Using Machine Learning Models [PDF]
پژوهشهای آبخیزداری, 2023 IntroductionFinding the potential of groundwater resources is one of the basic principles in water resources management. The aim of this research is to determine the potential of groundwater using support vector machine learning (SVM) models as well as ...
Ahmad Salamat +2 more
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Machine Learning of Reactive Potentials
Annual Review of Physical Chemistry, 2023 In the past two decades, machine learning potentials (MLPs) have driven significant developments in chemical, biological, and material sciences. The construction and training of MLPs enable fast and accurate simulations and analysis of thermodynamic and kinetic properties.
Yinuo Yang +4 more
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Machine Learning Techniques for the Design and Optimization of Polymer Composites: A Review [PDF]
E3S Web of Conferences, 2023 Polymer composites are employed in a variety of applications due to their distinctive characteristics. Nevertheless, designing and optimizing these materials can be a lengthy and resourceintensive process for low cost and sustainable materials.
Maniraj J. +7 more
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Machine-learning potential of a single pendulum
Physical Review E, 2022 Reservoir Computing offers a great computational framework where a physical system can directly be used as computational substrate. Typically a "reservoir" is comprised of a large number of dynamical systems, and is consequently high-dimensional. In this work, we use just a single simple low-dimensional dynamical system, namely a driven pendulum, as a ...
Swarnendu Mandal +2 more
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