collaborators

5 papers

cond-mat.mtrl-sci2021

Properties of α-Brass Nanoparticles II: Structure and Composition

Jan Weinreich, Martín Leandro Paleico, Jörg Behler

Nanoparticles have become increasingly interesting for a wide range of applications, because in principle it is possible to tailor their properties by controlling size, shape and c…

physics.comp-ph2020

A Bin and Hash Method for Analyzing Reference Data and Descriptors in Machine Learning Potentials

Martín Leandro Paleico, Jörg Behler

In recent years the development of machine learning (ML) potentials (MLP) has become a very active field of research. Numerous approaches have been proposed, which allow to perform…

physics.chem-ph2020

Global Optimization of Copper Clusters at the ZnO(10-10) Surface Using a DFT-based Neural Network Potential and Genetic Algorithms

Martín Leandro Paleico, Jörg Behler

The determination of the most stable structures of metal clusters supported at solid surfaces by computer simulations represents a formidable challenge due to the complexity of the…

physics.chem-ph2020

A flexible and adaptive grid algorithm for global optimization utilizing basin hopping Monte Carlo

Martín Leandro Paleico, Jörg Behler

Global optimization is an active area of research in atomistic simulations, and many algorithms have been proposed to date. A prominent example is basin hopping Monte Carlo, which…

physics.chem-ph2020

Properties of -Brass Nanoparticles I: Neural Network Potential Energy Surface

Jan Weinreich, Anton Römer, Martín Leandro Paleico +1

Binary metal clusters are of high interest for applications in heterogeneous catalysis and have received much attention in recent years. To gain insights into their structure and c…