157 citations · 478 across the 13 of their papers we have counts for
15 papers
The morphology and interface structure of titanium on graphene
Joachim Dahl Thomsen, Wissam A. Saidi, Kate Reidy +4
Titanium (Ti) is an adhesion and contact metal commonly used in nanoelectronics and two-dimensional (2D) materials research. However, when Ti is deposited on graphene (Gr), we obta…
Record Acceleration of the Two-Dimensional Ising Model Using High-Performance Wafer Scale Engine
Dirk Van Essendelft, Hayl Almolyki, Wei Shi +3
The versatility and wide-ranging applicability of the Ising model, originally introduced to study phase transitions in magnetic materials, have made it a cornerstone in statistical…
Exploring the formation of gold/silver nanoalloys with gas-phase synthesis and machine-learning assisted simulations
Quentin Gromoff, Patrizio Benzo, Wissam A. Saidi +6
While nanoalloys are of paramount scientific and practical interests, the main processes leading to their formation are still poorly understood. Key structural features in the allo…
Atomic scale understanding of initial Cu-Ni oxidation from machine-learning accelerated first-principles simulations and in situ TEM experiments
Pandu Wisesa, Meng Li, Matthew T. Curnan +3
The development of accurate methods for determining how alloy surfaces spontaneously restructure under reactive and corrosive environments is a key, long-standing, grand challenge…
Convergence Acceleration in Machine Learning Potentials for Atomistic Simulations
Dylan Bayerl, Christopher M. Andolina, Shyam Dwaraknath +1
Machine learning potentials (MLPs) for atomistic simulations have an enormous prospective impact on materials modeling, offering orders of magnitude speedup over density functional…
Atomistic mechanisms of binary alloy surface segregation from nanoseconds to seconds using accelerated dynamics
Richard B. Garza, Jiyoung Lee, Mai H. Nguyen +6
Although the equilibrium composition of many alloy surfaces is well understood, the rate of transient surface segregation during annealing is not known, despite its crucial effect…
Revisiting Trends in the Exchange Current for Hydrogen Evolution
Timothy T. Yang, Rituja B. Patil, James R. McKone +1
Nørskov and collaborators proposed a simple kinetic model to explain the volcano relation for the hydrogen evolution reaction on transition metal surfaces in such that $ j_0= k_0 f…
Optimization of High Entropy Alloy Catalyst for Ammonia Decomposition and Ammonia Synthesis
Wissam A. Saidi, Waseem Shadid, Götz Veser
The successful synthesis of high entropy alloy (HEA) nanoparticles, a long-sought goal in materials science, opens a new frontier in materials science with applications across cata…
Thermal fluctuations and carrier localization induced by dynamic disorder in MAPbI3 described by a first-principles based tight-binding model
David J. Abramovitch, Wissam A. Saidi, Liang Z. Tan
Halide perovskites are strongly influenced by large amplitude anharmonic lattice fluctuations at room temperature. We develop a tight binding model for dynamically disordered MAPbI…
First-Principles Phonon Quasiparticle Theory Applied to a Strongly Anharmonic Halide Perovskite
Terumasa Tadano, Wissam A. Saidi
Understanding and predicting lattice dynamics in strongly anharmonic crystals is one of the long-standing challenges in condensed matter physics. Here we propose a first-principles…
Response to Comment on "Low-frequency lattice phonons in halide perovskites explain high defect tolerance toward electron-hole recombination"
Weibin Chu, Qijing Zheng, Oleg V. Prezhdo +2
Recently we proposed that defect tolerance in the hybrid perovskites is due to their characteristic low-frequency lattice phonon modes that decrease the non-adiabatic coupling and…
Optimization and Validation of a Deep Learning CuZr Atomistic Potential: Robust Applications for Crystalline and Amorphous Phases with near-DFT Accuracy
Christopher M. Andolina, Philip Williamson, Wissam A. Saidi
We show that a deep-learning neural network potential (DP) based on density functional theory (DFT) calculations can well describe Cu-Zr materials, an example of a binary alloy sys…
End-to-end Symmetry Preserving Inter-atomic Potential Energy Model for Finite and Extended Systems
Linfeng Zhang, Jiequn Han, Han Wang +3
Machine learning models are changing the paradigm of molecular modeling, which is a fundamental tool for material science, chemistry, and computational biology. Of particular inter…
Temperature Dependence of the Energy Levels of Methylammonium Lead Iodide Perovskite from First Principles
Wissam A. Saidi, Samuel Poncé, Bartomeu Monserrat
Environmental effects and intrinsic energy-loss processes lead to fluctuations in the operational temperature of solar cells, which can profoundly influence their power conversion…
Modiffied Schottky emission to explain thickness dependence and slow depolarization in BaTiO nanowires
Y. Qi, J. M. P. Martirez, Wissam A. Saidi +4
We investigate the origin of the depolarization rates in ultrathin adsorbate-stabilized ferroelectric wires. By applying density functional theory calculations and analytic modelin…