Zobrazeno 1 - 10
of 232
pro vyhledávání: '"Rupp Matthias"'
Machine-learning interatomic potentials (MLPs) are fast, data-driven surrogate models of atomistic systems' potential energy surfaces that can accelerate ab-initio molecular dynamics (MD) simulations by several orders of magnitude. The performance of
Externí odkaz:
http://arxiv.org/abs/2409.13390
Publikováno v:
The Journal of Chemical Physics 161(6): 060401, 2024
A survey of the contributions to the Journal of Chemical Physics' Special Topic on Software for Atomistic Machine Learning.
Externí odkaz:
http://arxiv.org/abs/2406.19750
Autor:
Sumaria, Vaidish, Rawal, Takat B., Li, Young Feng, Sommer, David, Vikoren, Jake, Bondi, Robert J., Rupp, Matthias, Prasad, Amrit, Prasad, Deeptanshu
The photoconversion of CO$_2$ to hydrocarbons is a sustainable route to its transformation into value-added compounds and, thereby, crucial to mitigating the energy and climate crises. CuPt nanoparticles on TiO$_2$ surfaces have been reported to show
Externí odkaz:
http://arxiv.org/abs/2402.08884
Data-driven engineering refers to systematic data collection and processing using machine learning to improve engineering systems. Currently, the implementation of data-driven engineering relies on fundamental data science and software engineering sk
Externí odkaz:
http://arxiv.org/abs/2307.05584
The Green-Kubo (GK) method is a rigorous framework for heat transport simulations in materials. However, it requires an accurate description of the potential-energy surface and carefully converged statistics. Machine-learning potentials can achieve t
Externí odkaz:
http://arxiv.org/abs/2303.14434
Autor:
Schulze Simon, Cortese Bruno, Rupp Matthias, de Croon Mart H.J.M., Hessel Volker, Couet Julien, Lang Jürgen, Klemm Elias
Publikováno v:
Green Processing and Synthesis, Vol 2, Iss 5, Pp 381-395 (2013)
For the first time the anionic polymerization of 1,3-butadiene (Bd) is successfully transferred from semi-batch into a continuous microfluidic setup with comparable product properties. The molecular weight distribution described by the polydispersity
Externí odkaz:
https://doaj.org/article/073666f8d9394559b46c2c216088665a
Publikováno v:
In Composites Part A January 2025 188
Publikováno v:
Journal of Cheminformatics, Vol 4, Iss Suppl 1, p P33 (2012)
Externí odkaz:
https://doaj.org/article/c3133851a4c64746888842f7da425a06
Autor:
Rupp Matthias
Publikováno v:
Journal of Cheminformatics, Vol 3, Iss Suppl 1, p O8 (2011)
Externí odkaz:
https://doaj.org/article/05c458e31a114650a155c474e90d92e7
All-atom dynamics simulations are an indispensable quantitative tool in physics, chemistry, and materials science, but large systems and long simulation times remain challenging due to the trade-off between computational efficiency and predictive acc
Externí odkaz:
http://arxiv.org/abs/2110.00624