Michael Probst
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View article: Glyphosate Adsorption on Metal–Organic Framework M<sub>3</sub>(BTC)<sub>2</sub>: Mechanistic Insights and Descriptors for the Adsorption Energy from Density Functional Calculations
Glyphosate Adsorption on Metal–Organic Framework M<sub>3</sub>(BTC)<sub>2</sub>: Mechanistic Insights and Descriptors for the Adsorption Energy from Density Functional Calculations Open
Adsorption-based removal has emerged as an effective strategy for mitigating the harmful impact of glyphosate. Here, the adsorption of glyphosate over the coordinatively unsaturated metal-organic framework (MOF) M3(BTC)2 (M = V, Cr, Mn, Fe…
View article: Accurate classification of materials with elEmBERT: Element embeddings for chemical benchmarks
Accurate classification of materials with elEmBERT: Element embeddings for chemical benchmarks Open
We introduce the elEmBERT model for chemical classification tasks. It is based on deep learning techniques, such as a multilayer encoder architecture. We demonstrate the opportunities offered by our approach on sets of organic, inorganic, …
View article: Molecular dynamics simulations of the sputtering of boron and boron oxide surfaces
Molecular dynamics simulations of the sputtering of boron and boron oxide surfaces Open
Sputtering yields of atoms from boron and boron oxide surfaces as a function of the impact energy of deuterium.
View article: Modelling the Impact of Argon Atoms on a WO3 Surface by Molecular Dynamics Simulations
Modelling the Impact of Argon Atoms on a WO3 Surface by Molecular Dynamics Simulations Open
Machine learning potential energy functions can drive the atomistic dynamics of molecules, clusters, and condensed phases. They are amongst the first examples that showed how quantum mechanics together with machine learning can predict che…
View article: Structure to Property: Chemical Element Embeddings for Predicting Electronic Properties of Crystals
Structure to Property: Chemical Element Embeddings for Predicting Electronic Properties of Crystals Open
We present a new general-purpose machine learning model that is able to predict a variety of crystal properties, including Fermi level energy and band gap, as well as spectral ones such as electronic densities of states. The model is based…
View article: A polarizable valence electron density based force field for high-energy interactions between atoms and molecules
A polarizable valence electron density based force field for high-energy interactions between atoms and molecules Open
High-accuracy molecular force field models suited for hot gases and plasmas are not as abundant as those geared toward ambient pressure and temperature conditions. Here, we present an improved version of our previous electron-density based…
View article: A Polarizable Valence Electron Density Based Force Field for High-Energy Interactions between Atoms and Molecules
A Polarizable Valence Electron Density Based Force Field for High-Energy Interactions between Atoms and Molecules Open
High-accuracy molecular force field models suited for hot gases and plasmas are not as abundant as those geared towards ambient pressure and temperature conditions. Here we present an improved version of our previous electron- density base…
View article: A Polarizable Valence Electron Density Based Force Field for High-Energy Interactions between Atoms and Molecules
A Polarizable Valence Electron Density Based Force Field for High-Energy Interactions between Atoms and Molecules Open
High-accuracy molecular force field models suited for hot gases and plasmas are not as abundant as those geared towards ambient pressure and temperature conditions. Here we present an improved version of our previous electron- density base…
View article: A Simple Electron-Density Based Force Field Model for High-Energy Interactions between Atoms and Molecules
A Simple Electron-Density Based Force Field Model for High-Energy Interactions between Atoms and Molecules Open
In high-energy molecular dynamics or Monte Carlo simulations, standard force fields optimized for simulations at ambient temperatures are inadequate. This is largely because their repulsive parts have been regarded as not very significant,…
View article: Sputtering from rough tungsten surfaces: Data-driven molecular dynamics simulations
Sputtering from rough tungsten surfaces: Data-driven molecular dynamics simulations Open
The sputtering of tungsten surfaces caused by hot plasma particles is an important process in fusion reactors where divertors are typically made of tungsten sheets. In this study, we present a molecular dynamics simulation strategy to inve…
View article: Structure to Property: Machine Learning Methods for Predicting Electronic Properties of Crystals
Structure to Property: Machine Learning Methods for Predicting Electronic Properties of Crystals Open
We present a general-purpose machine learning model for predicting properties of crystals. Specifically, energy of formation, Fermi level energy, band gap, partial charges, and bulk modulus as well as spectral properties, including electro…
View article: A Simple Electron-Density Based Force Field Model for High-Energy Interactions between Atoms and Molecules
A Simple Electron-Density Based Force Field Model for High-Energy Interactions between Atoms and Molecules Open
In high-energy molecular dynamics or Monte-Carlo simulations, standard force fields that are optimised for simulations at ambient temperature are inadequate. This is largely because their repulsive part has been regarded as not very signif…
View article: A Simple Electron-Density Based Force Field Model for High-Energy Interactions between Atoms and Molecules
A Simple Electron-Density Based Force Field Model for High-Energy Interactions between Atoms and Molecules Open
In high-energy molecular dynamics or Monte-Carlo simulations, standard force fields that are optimised for simulations at ambient temperature are inadequate. This is largely because their repulsive part has been regarded as not very signif…
View article: A Simple Electron-Density Based Force Field Model for High-Energy Interactions between Atoms and Molecules
A Simple Electron-Density Based Force Field Model for High-Energy Interactions between Atoms and Molecules Open
In high-energy molecular dynamics or Monte-Carlo simulations, standard force fields that are optimised for simulations at ambient temperature are inadequate. This is largely because their repulsive part has been regarded as not very signif…
View article: Structure to Property: Chemical Element Embeddings and a Deep Learning Approach for Accurate Prediction of Chemical Properties
Structure to Property: Chemical Element Embeddings and a Deep Learning Approach for Accurate Prediction of Chemical Properties Open
We introduce the elEmBERT model for chemical classification tasks. It is based on deep learning techniques, such as a multilayer encoder architecture. We demonstrate the opportunities offered by our approach on sets of organic, inorganic a…
View article: 2022 Review of Data-Driven Plasma Science
2022 Review of Data-Driven Plasma Science Open
Data-driven science and technology offer transformative tools and methods to science. This review article highlights the latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS), i.e., plasma scie…
View article: Modelling the impact of argon atoms on a tungsten surface
Modelling the impact of argon atoms on a tungsten surface Open
Sputtering from plasma-facing surfaces upon particle impact is an important process in material science. It is especially relevant in the diverter region of fusion devices, which nearly always consist of tungsten. Besides the main plasma c…
View article: Sensing the ortho Positions in C6Cl6 and C6H4Cl2 from Cl2− Formation upon Molecular Reduction
Sensing the ortho Positions in C6Cl6 and C6H4Cl2 from Cl2− Formation upon Molecular Reduction Open
The geometrical effect of chlorine atom positions in polyatomic molecules after capturing a low-energy electron is shown to be a prevalent mechanism yielding Cl2−. In this work, we investigated hexachlorobenzene reduction in electron trans…
View article: Electron-impact ionization cross sections of small molecules containing Fe and Cr <sup>∗</sup>
Electron-impact ionization cross sections of small molecules containing Fe and Cr <sup>∗</sup> Open
We present the electron-impact ionization cross sections (EICSs) of iron and chromium hydrides, nitrides, and oxides. The motivation of this work stems from the fact that chemical sputtering from a steel surface exposed to a hot plasma can…
View article: 2022 Review of Data-Driven Plasma Science
2022 Review of Data-Driven Plasma Science Open
Data science and technology offer transformative tools and methods to science. This review article highlights latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS). A large amount of data and m…
View article: Sputtering and reflection from a beryllium surface: effects of hydrogen isotope mass, impact position and surface binding energy
Sputtering and reflection from a beryllium surface: effects of hydrogen isotope mass, impact position and surface binding energy Open
Atomistic simulations with machine-learned potential energy functions are employed for understanding the mechanisms driving the sputtering of beryllium by low-energy deuterium and tritium atoms and the details of their retention on pristin…
View article: Adsorption and Dehydration Reaction of Ethanol to Ethylene on Isomorphous B, Al, and Ga Substitution of H-ZSM-5 Zeolite: An Embedded ONIOM Study
Adsorption and Dehydration Reaction of Ethanol to Ethylene on Isomorphous B, Al, and Ga Substitution of H-ZSM-5 Zeolite: An Embedded ONIOM Study Open
Dehydration reactions are important in the petroleum and petrochemical industries, especially for the feedstock production. In this work, the catalytic activity of zeolites with different acidities for the dehydration of ethanol to ethylen…
View article: Combinations of density functionals for accurate molecular properties of Be/W/H compounds
Combinations of density functionals for accurate molecular properties of Be/W/H compounds Open
Beryllium and tungsten species can form by plasma-induced erosion of the walls of a fusion reactor. Accurate and fast evaluation of energies and geometries of Be/W/H compounds is needed for direct molecular dynamics of the plasma-wall inte…
View article: Modelling the sputtering and reflection from a beryllium surface: atomistic analysis
Modelling the sputtering and reflection from a beryllium surface: atomistic analysis Open
Sputtering from plasma-facing surfaces upon particle impact can limit the lifetime of components in fusion devices, especially in the diverter region. Atomistic simulations of the processes associated with plasma–wall interactions allow fo…
View article: Electronic structure and reactivity of tirapazamine as a radiosensitizer
Electronic structure and reactivity of tirapazamine as a radiosensitizer Open
Tirapazamine (TP) has been shown to enhance the cytotoxic effects of ionizing radiation in hypoxic cells, thus making it a candidate for a radiosensitizer. This selective behavior is often directly linked to the abundance of O 2 . In this …
View article: Confinement Effect on Heterogeneous Electron Transfer in Aqueous Solutions inside Conducting Nanotubes
Confinement Effect on Heterogeneous Electron Transfer in Aqueous Solutions inside Conducting Nanotubes Open
An Fe 3+/2+ redox couple in conducting single wall carbon nanotubes filled with water molecules is investigated in the framework of the electron transfer theory and with classical molecular dynamics simulations. The diameter of the nanotub…
View article: Sputtering of the beryllium tungsten alloy Be<sub>2</sub>W by deuterium atoms: molecular dynamics simulations using machine learned forces
Sputtering of the beryllium tungsten alloy Be<sub>2</sub>W by deuterium atoms: molecular dynamics simulations using machine learned forces Open
Material erosion and fuel retention will limit the life and the performance of thermonuclear fusion reactors. In this work, sputtering, reflection and retention processes are atomistically modeled by simulating the non-cumulative sputterin…
View article: Iterative training set refinement enables reactive molecular dynamics <i>via</i> machine learned forces
Iterative training set refinement enables reactive molecular dynamics <i>via</i> machine learned forces Open
Reactive self-sputtering from a Be surface is simulated using neural network trained forces with high accuracy. The key in machine learning from DFT calculations is a well-balanced and complete training set of energies and forces obtained …