130 citations · 389 across the 18 of their papers we have counts for
20 papers
exa-PD: A scalable high-performance workflow for multi-element phase diagram construction
Zhuo Ye, Feng Zhang, Maxim Moraru +4
Exa-PD is a highly parallelizable workflow designed for the construction of multi-element phase diagrams (PDs). It uses standard sampling techniques, molecular dynamics (MD) and Mo…
Structural modulation, physical properties, and electronic band structure of the kagome metal UCrGe
Z. W. Riedel, P. A. E. Murgatroyd, C. S. Kengle +13
The chemical flexibility of the stoichiometry, where an -block element is intercalated in the CoSn structure type, allows for the tuning of flatbands associated with k…
exaPD: A highly parallelizable workflow for multi-element phase diagram (PD) construction
Feng Zhang, Zhuo Ye, Maxim Moraru +4
Phase diagrams (PDs) illustrate the relative stability of competing phases under varying conditions, serving as critical tools for synthesizing complex materials. Reliable phase di…
exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials
Weiyi Xia, Maxim Moraru, Ying Wai Li +1
We present exa-AMD, an open-source, high-performance framework designed for accelerated materials discovery on modern supercomputers. exa-AMD overcomes key computational bottleneck…
exa-AMD: A Scalable Workflow for Accelerating AI-Assisted Materials Discovery and Design
Maxim Moraru, Weiyi Xia, Zhuo Ye +4
exa-AMD is a Python-based application designed to accelerate the discovery and design of functional materials by integrating AI/ML tools, materials databases, and quantum mechanica…
Best of Both Worlds: Enforcing Detailed Balance in Machine Learning Models of Transition Rates
Anjana Anu Talapatra, Anup Pandey, Matthew S. Wilson +4
The slow microstructural evolution of materials often plays a key role in determining material properties. When the unit steps of the evolution process are slow, direct simulation…
High-Throughput Search and Prediction of Layered 4f-Materials
Lin Hou, Ying Wai Li, Christopher Lane
The development of multifunctional devices calls for the discovery of new layered materials with novel electronic properties. f-electron systems naturally host a rich set of compet…
Machine learning potentials with Iterative Boltzmann Inversion: training to experiment
Sakib Matin, Alice Allen, Justin S. Smith +7
Methodologies for training machine learning potentials (MLPs) to quantum-mechanical simulation data have recently seen tremendous progress. Experimental data has a very different c…
Gradient-based Wang-Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space
Weitang Liu, Ying-Wai Li, Yi-Zhuang You +1
The output distribution of a neural network (NN) over the entire input space captures the complete input-output mapping relationship, offering insights toward a more comprehensive…
Reduction of Autocorrelation Times in Lattice Path Integral Quantum Monte Carlo via Direct Sampling of the Truncated Exponential Distribution
Emanuel Casiano-Diaz, Kipton Barros, Ying Wai Li +1
In Monte Carlo simulations, proposed configurations are accepted or rejected according to an acceptance ratio, which depends on an underlying probability distribution and an a prio…
Supervised and Unsupervised Machine Learning of Structural Phases of Polymers Adsorbed to Nanowires
Quinn Parker, Dilina Perera, Ying Wai Li +1
We identify configurational phases and structural transitions in a polymer nanotube composite by means of machine learning. We employ various unsupervised dimensionality reduction…
Machine Learning Assisted Insight to Spin Ice DyTiO
Anjana M Samarakoon, Kipton Barros, Ying Wai Li +8
Complex behavior poses challenges in extracting models from experiment. An example is spin liquid formation in frustrated magnets like DyTiO. Understanding has been hin…
A histogram-free multicanonical Monte Carlo algorithm for the basis expansion of density of states
Ying Wai Li, Markus Eisenbach
We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our a…
Exploring Replica-Exchange Wang-Landau sampling in higher-dimensional parameter space
Alexandra Valentim, Julio C. S. Rocha, Shan-Ho Tsai +4
We considered a higher-dimensional extension for the replica-exchange Wang-Landau algorithm to perform a random walk in the energy and magnetization space of the two-dimensional Is…
Replica-exchange Wang-Landau sampling: Pushing the limits of Monte Carlo simulations in materials sciences
Dilina Perera, Ying Wai Li, Markus Eisenbach +2
We describe the study of thermodynamics of materials using replica-exchange Wang-Landau (REWL) sampling, a generic framework for massively parallel implementations of the Wang-Land…
Scalable replica-exchange framework for Wang-Landau sampling
Thomas Vogel, Ying Wai Li, Thomas Wüst +1
We investigate a generic, parallel replica-exchange framework for Monte Carlo simulations based on the Wang-Landau method. To demonstrate its advantages and general applicability f…
A new paradigm for petascale Monte Carlo simulation: Replica exchange Wang-Landau sampling
Ying Wai Li, Thomas Vogel, Thomas Wüst +1
We introduce a generic, parallel Wang-Landau method that is naturally suited to implementation on massively parallel, petaflop supercomputers. The approach introduces a replica-exc…
Exploring new frontiers in statistical physics with a new, parallel Wang-Landau framework
Thomas Vogel, Ying Wai Li, Thomas Wüst +1
Combining traditional Wang-Landau sampling for multiple replica systems with an exchange of densities of states between replicas, we describe a general framework for simulations on…
A generic, hierarchical framework for massively parallel Wang-Landau sampling
Thomas Vogel, Ying Wai Li, Thomas Wüst +1
We introduce a parallel Wang-Landau method based on the replica-exchange framework for Monte Carlo simulations. To demonstrate its advantages and general applicability for simulati…
Monte Carlo simulations of the HP model (the "Ising model" of protein folding)
Ying Wai Li, Thomas Wüst, David P. Landau
Using Wang-Landau sampling with suitable Monte Carlo trial moves (pull moves and bond-rebridging moves combined) we have determined the density of states and thermodynamic properti…