Zobrazeno 1 - 10
of 411
pro vyhledávání: '"Hammer, Bjørk"'
Autor:
Pitfield, Joe, Brix, Florian, Tang, Zeyuan, Slavensky, Andreas Møller, Rønne, Nikolaj, Christiansen, Mads-Peter Verner, Hammer, Bjørk
Universal potentials open the door for DFT level calculations at a fraction of their cost. We find that for application to systems outside the scope of its training data, CHGNet\cite{deng2023chgnet} has the potential to succeed out of the box, but ca
Externí odkaz:
http://arxiv.org/abs/2407.14288
Publikováno v:
J. Chem. Phys. 161, 014713 (2024)
We introduce an atomistic classifier based on a combination of spectral graph theory and a Voronoi tessellation method. This classifier allows for the discrimination between structures from different minima of a potential energy surface, making it a
Externí odkaz:
http://arxiv.org/abs/2407.13471
Reliable uncertainty measures are required when using data based machine learning interatomic potentials (MLIPs) for atomistic simulations. In this work, we propose for sparse Gaussian Process Regression type MLIP a stochastic uncertainty measure aki
Externí odkaz:
http://arxiv.org/abs/2407.12525
Publikováno v:
J. Chem. Phys. 159, 024123 (2023)
Global optimization of atomistic structure rely on the generation of new candidate structures in order to drive the exploration of the potential energy surface (PES) in search for the global minimum energy (GM) structure. In this work, we discuss a t
Externí odkaz:
http://arxiv.org/abs/2402.18338
We present a generative diffusion model specifically tailored to the discovery of surface structures. The generative model takes into account substrate registry and periodicity by including masked atoms and $z$-directional confinement. Using a rotati
Externí odkaz:
http://arxiv.org/abs/2402.17404
The use of machine learning (ML) in chemical physics has enabled the construction of interatomic potentials having the accuracy of ab initio methods and a computational cost comparable to that of classical force fields. Training an ML model requires
Externí odkaz:
http://arxiv.org/abs/2305.15846
Determination of crystal structures of nanocrystalline or amorphous compounds is a great challenge in solid states chemistry and physics. Pair distribution function (PDF) analysis of X-Ray or neutron total scattering data has proven to be a key eleme
Externí odkaz:
http://arxiv.org/abs/2209.01358
Autor:
Rønne, Nikolaj, Christiansen, Mads-Peter V., Slavensky, Andreas Møller, Tang, Zeyuan, Brix, Florian, Pedersen, Mikkel Elkjær, Bisbo, Malthe Kjær, Hammer, Bjørk
Publikováno v:
J. Chem. Phys. 157, 174115 (2022)
We describe a local surrogate model for use in conjunction with global structure search methods. The model follows the Gaussian approximation potential (GAP) formalism and is based on a the smooth overlap of atomic positions descriptor with sparsific
Externí odkaz:
http://arxiv.org/abs/2208.09273
Autor:
Tang, Zeyuan, Simonsen, Frederik Doktor S., Jaganathan, Rijutha, Palotás, Julianna, Oomens, Jos, Hornekær, Liv, Hammer, Bjørk
Publikováno v:
A&A 663, A150 (2022)
Fragmentation is an important decay mechanism for polycyclic aromatic hydrocarbons (PAHs) under harsh interstellar conditions and represents a possible formation pathway for small molecules such as H2, C2H2, C2H4. Our aim is to investigate the dissoc
Externí odkaz:
http://arxiv.org/abs/2205.07705
Autor:
Tang, Zeyuan, Hammer, Bjørk
Publikováno v:
J. Chem. Phys. 156, 134703 (2022)
Dimerization of polycyclic aromatic hydrocarbons (PAHs) is an important, yet poorly understood, step in the on-surface synthesis of graphene (nanoribbon), soot formation, and growth of carbonaceous dust grains in the interstellar medium (ISM). The on
Externí odkaz:
http://arxiv.org/abs/2204.05635