1 citations · 3 across the 3 of their papers we have counts for
5 papers
Fine-tuning of universal machine-learning interatomic potentials for high-entropy alloys with application to 2D (Mo,Ta,Nb,W,V)S
Chun Zhou, Hannu-Pekka Komsa
High-entropy alloy (HEA) materials and their two-dimensional counterparts (2D-HEAs) have recently attracted attention due to their tunable properties and catalytic potential, yet t…
Atomic-Scale Quantum Control of Single Spin Defects in a Two-Dimensional Semiconductor
Kwan Ho Au-Yeung, Wantong Huang, Johanna Matusche +15
Individual spin defects in solids are promising building blocks for quantum technologies, but their deterministic creation, individual addressability, and operation near surfaces r…
Massive Discovery of Low-Dimensional Materials from Universal Computational Strategy
Mohammad Bagheri, Ethan Berger, Hannu-Pekka Komsa +1
Low-dimensional materials have attractive properties that drive intense efforts for novel materials discovery. However, experiments are tedious for systematic discovery, and presen…
Resistive switching behaviors in vertically aligned MoS films with Cu, Ag, and Au electrodes
Shuei-De Huang, Touko Lehenkari, Topias Järvinen +4
Neuromorphic computing circuits can be realized using memristors based on low-dimensional materials enabling enhanced metal diffusion for resistive switching. Here, we investigate…
Raman spectra of amino acids and peptides from machine learning polarizabilities
Ethan Berger, Juha Niemelä, Outi Lampela +2
Raman spectroscopy is an important tool in the study of vibrational properties and composition of molecules, peptides and even proteins. Raman spectra can be simulated based on the…