Related papers: Interatomic potentials for platinum
Machine learning interatomic potentials (MLIPs) have massively changed the field of atomistic modeling. They enable the accuracy of density functional theory in large-scale simulations while being nearly as fast as classical interatomic…
We utilize the combination of two standard trapping techniques, a magnetic trap and an optical trap in a Raman setup, to propose a versatile and tunable trap for cold atoms. The created potential provides several advantages over…
The package fhi98PP allows one to generate norm-conserving pseudopotentials adapted to density-functional theory total-energy calculations for a multitude of elements throughout the periodic table, including first-row and transition metal…
Axionlike particles (ALPs) can be produced in the Sun, and are considered viable candidates for the cosmological dark matter (DM). It can decay into two photons or interact with matter. We identify new inelastic channels of inverse…
Accuracy of molecular dynamics simulations depends crucially on the interatomic potential used to generate forces. The gold standard would be first-principles quantum mechanics (QM) calculations, but these become prohibitively expensive at…
New EAM potentials for the ternary palladium-silver-hydrogen system are developed by extending a previously developed palladium-hydrogen potential. The ternary potentials accurately capture the heat of mixing and structural properties…
Pentadiamond is a recently proposed new carbon allotrope consisting of a network of pentagonal rings where both sp$^2$ and sp$^3$ hybridization are present. In this work we investigated the mechanical and electronic properties, as well as,…
Preparing realistic atom-scale models of amorphous silicon (a-Si) is a decades-old condensed matter physics challenge. Herein, we combine the Activation Relaxation Technique nouveau (ARTn) to a Moment Tensor Potential (MTP) to generate…
Choice of appropriate force field is one of the main concerns of any atomistic simulation that needs to be seriously considered in order to yield reliable results. Since, investigations on mechanical behavior of materials at micro/nanoscale…
The development of efficient and cost-effective bifunctional electrocatalysts for hydrogen-related technologies is crucial for the transition to sustainable energy. In this work, we present Pt@ZrO2 as a high-performance ceramic-based…
Machine-learning potentials for materials, namely the moment tensor potentials (MTPs), were validated using experimental EXAFS spectra for the first time. The MTPs for four metals (bcc W and Mo, fcc Cu and Ni) were obtained by the active…
We analyze in this article the magneto-resistance ratio of finite and infinite iridium and platinum chains. Our calculations, that are based on a combination of non equilibrium Green function techniques and density functional theory,…
We demonstrate a novel class of trapping potentials, time-averaged adiabatic potentials (TAAP) which allows the generation of a large variety of traps and waveguides for ultracold atoms. Multiple traps can be coupled through controllable…
A novel embedded atom method (EAM) potential for the Xi-phases of Al-Pd-Mn has been determined with the force-matching method. Different combinations of analytic functions were tested for the pair and transfer part. The best results are…
Interatomic potentials provide a means to simulate extended length and time scales that are outside the reach of ab initio calculations. The development of an interatomic potential for a particular material requires the optimization of the…
Microscopy of polymer electrolyte membranes that have undergone operation under fuel cell conditions, have revealed a well defined band of platinum in the membrane. Here, we propose a physics based model that captures the mechanism of…
Machine learning interatomic potentials (MLPs) are a promising technique for atomic modeling. While high accuracy and small errors are widely reported for MLPs, an open concern is whether MLPs can accurately reproduce atomistic dynamics and…
Motivated by recent chemical attempts at assembling halogen-bridged transition-metal complexes within a nanotube, we model and characterize a platinum-halide triangular prism in terms of a Peierls-Hubbard Hamiltonian. Based on a…
We derive the exact analytic form of the potential experienced by a magnetic dipole trapped between two infinite parallel superconducting plates using the method of image dipoles, providing a benchmark for numerical methods and a foundation…
We demonstrate how machine-learning based interatomic potentials can be used to model guest atoms in host structures. Specifically, we generate Gaussian approximation potential (GAP) models for the interaction of lithium atoms with…