1.1k citations
- University College LondonGB77 papers
- London Centre for NanotechnologyGB57 papers
- Imperial College LondonGB49 papers
- University of CambridgeGB32 papers
- University of Naples Federico IIIT16 papers
- Peking UniversityCN8 papers
- Harvard UniversityUS7 papers
- University of OxfordGB6 papers
- Collaborative Innovation Center of Quantum MatterCN5 papers
- Ewha Womans UniversityKR5 papers
- University of WarwickGB5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
120 papers
Magnetic Ordering in Moiré Graphene Multilayers from a Continuum Hartree+U Approach
Christopher T. S. Cheung, Valerio Vitale, Lennart Klebl +5
Recently, symmetry-broken ground states, such as correlated insulating states, magnetic order and superconductivity, have been discovered in twisted bilayer graphene (tBLG) and twi…
Spectroscopic Signatures of Structural Disorder and Electron-Phonon Interactions in Trigonal Selenium Thin Films for Solar Energy Harvesting
Rasmus S. Nielsen, Axel G. Medaille, Arnau Torrens +7
Selenium is experiencing renewed interest as a elemental semiconductor for a range of optoelectronic and energy applications due to its irresistibly simple composition and favorabl…
Probing the Temporal Response of Liquid Water to a THz Pump Pulse Using Machine Learning-Accelerated Non-Equilibrium Molecular Dynamics
Kit Joll, Philipp Schienbein
Ultrafast, time-resolved spectroscopies enable the direct observation of non-equilibrium processes in condensed-phase systems and have revealed key insights into energy transport,…
Accurate and efficient machine learning interatomic potentials for finite temperature modeling of molecular crystals
Flaviano Della Pia, Benjamin X. Shi, Venkat Kapil +3
As with many parts of the natural sciences, machine learning interatomic potentials (MLIPs) are revolutionizing the modeling of molecular crystals. However, challenges remain for t…
A brief introduction to the diffusion Monte Carlo method and the fixed-node approximation
Alfonso Annarelli, Dario Alfè, Andrea Zen
Quantum Monte Carlo (QMC) methods represent a powerful family of computational techniques for tackling complex quantum many-body problems and performing calculations of stationary…
An accurate and efficient framework for modelling the surface chemistry of ionic materials
Benjamin X. Shi, Andrew S. Rosen, Tobias Schäfer +4
Quantum-mechanical simulations can offer atomic-level insights into chemical processes on surfaces. This understanding is crucial for the rational design of new solid catalysts as…