Zobrazeno 1 - 10
of 322
pro vyhledávání: '"Mueller, Tim"'
This paper introduces the Chemical Environment Modeling Theory (CEMT), a novel, generalized framework designed to overcome the limitations inherent in traditional atom-centered Machine Learning Force Field (MLFF) models, widely used in atomistic simu
Externí odkaz:
http://arxiv.org/abs/2310.18552
Conventional control of fluid systems does not consider system-wide knowledge for optimising energy efficient operation. Distributed control of fluid systems combines reliable local control of components while using system-wide cooperation to ensure
Externí odkaz:
http://arxiv.org/abs/2212.08450
Autor:
Hernandez, Alberto, Mueller, Tim
In recent years there has been great progress in the use of machine learning algorithms to develop interatomic potential models. Machine-learned potential models are typically orders of magnitude faster than density functional theory but also orders
Externí odkaz:
http://arxiv.org/abs/2210.15124
Autor:
Peters, Adam B., Wang, Chuhong, Zhang, Dajie, Hernandez, Alberto, Nagle, Dennis C., Mueller, Tim, Spicer, James B.
Ultra-high-temperature ceramics (UHTCs) are optimal structural materials for applications that require extreme temperature resilience, resistance to chemically aggressive environments, wear, and mechanical stress. Processing UHTCs with laser-based ad
Externí odkaz:
http://arxiv.org/abs/2208.02041
Autor:
Peters, Adam B., Zhang, Dajie, Hernandez, Alberto, Wang, Chuhong, Nagle, Dennis C., Mueller, Tim, Spicer, James B.
Selective laser reaction sintering techniques (SLRS) techniques were investigated for the production of near net-shape non-oxide ceramics including SiC, Si$_3$N$_4$, and HfC/SiC composites that might be compatible with prevailing powder bed fusion ad
Externí odkaz:
http://arxiv.org/abs/2208.00054
Autor:
Alsayed Kassem, Jamila, Müller, Tim, Esterhuyse, Christopher A., Kebede, Milen G., Osseyran, Anwar, Grosso, Paola
Publikováno v:
In Future Generation Computer Systems April 2025 165
Publikováno v:
Phys. Rev. Materials 5, 013803 (2021)
Kinetic Monte Carlo models parameterized by first principles calculations are widely used to simulate atomic diffusion. However, accurately predicting the activation energies for diffusion in substitutional alloys remains challenging due to the wide
Externí odkaz:
http://arxiv.org/abs/2009.12474
Publikováno v:
Comp Mater Sci, 110100 (2020)
Computational modeling of the properties of crystalline materials has become an increasingly important aspect of materials research, consuming hundreds of millions of CPU-hours at scientific computing centres around the world each year, if not more.
Externí odkaz:
http://arxiv.org/abs/1907.13610
The length and time scales of atomistic simulations are limited by the computational cost of the methods used to predict material properties. In recent years there has been great progress in the use of machine learning algorithms to develop fast and
Externí odkaz:
http://arxiv.org/abs/1904.01095
Publikováno v:
In Journal of Building Engineering 1 June 2023 68