92 citations
- Université Paris-SudFR7 papers
- Centre National de la Recherche ScientifiqueFR6 papers
- Columbia UniversityUS5 papers
- Laboratoire de Physique Théorique et Modèles StatistiquesFR5 papers
- Bogolyubov Institute for Theoretical PhysicsUA4 papers
- University of ViennaAT4 papers
- William & MaryUS4 papers
- Flatiron Institute2 papers
- Utrecht UniversityNL2 papers
- Aalborg UniversityDK1 paper
- Ames National LaboratoryUS1 paper
- City College of New YorkUS1 paper
25 papers
Utilizing SciPy and other open source packages to provide a powerful API for materials manipulation in the Schrödinger Materials Suite
Alexandr Fonari, Farshad Fallah, Michael Rauch
The use of several open source scientific packages in the Schrödinger Materials Science Suite will be discussed. A typical workflow for materials discovery will be described, discu…
Finding the temperature window for atomic layer deposition of ruthenium metal via efficient phonon calculations
Alexandr Fonari, Simon D. Elliott, Casey N. Brock +3
We investigate the use of first principles thermodynamics based on periodic density functional theory (DFT) to examine the gas-surface chemistry of an oxidized ruthenium surface re…
Universal sectors of two-dimensional Carrollian CFTs
Ankit Aggarwal, Arjun Bagchi, Stephane Detournay +3
We revisit modular invariance in two-dimensional Carrollian conformal field theories from a geometric perspective. Focusing on the characters of the induced and highest-weight repr…
Unified description of cuprate superconductors by fractionalized electrons emerging from integrated analyses of photoemission spectra and quasiparticle interference
Shiro Sakai, Youhei Yamaji, Fumihiro Imoto +6
Electronic structure of high-temperature superconducting cuprates is studied by analyzing experimental data independently obtained from two complementary spectroscopies, one, quasi…
Scalable Training of Neural Network Potentials for Complex Interfaces Through Data Augmentation
In Won Yeu, Annika Stuke, Jon L. pez-Zorrilla +5
Artificial neural network (ANN) potentials enable highly accurate atomistic simulations of complex materials at unprecedented scales. Despite their promise, training ANN potentials…
Robust and effective ab initio molecular dynamics simulations on the GPU cloud infrastructure using the Schrödinger Materials Science Suite
Alexandr Fonari, Garvit Agarwal, Subodh C. Tiwari +3
Ab initio Born-Oppenheimer molecular dynamics (AIMD) is a valuable method for simulating physico-chemical processes of complex systems, including reactive systems, and for training…