8 citations · 15 across the 13 of their papers we have counts for
14 papers
A Polynomial-Scaling PDE Solver with Entanglement-Basis Tensor Networks
Abhijatmedhi Chotrattanapituk, Michael J. Landry, Chu-Liang Fu +1
We develop a finite element method (FEM) for partial differential equation (PDE) solver based on the entanglement-basis representation introduced in our companion work. By lifting…
Tensor-Network Finite Elements for Analytic Operator Equations
Abhijatmedhi Chotrattanapituk, Michael J. Landry, Chu-Liang Fu +1
Operator equations (OEs) underpin quantitative modeling across science and engineering. Finite-element (FE) methods discretize continuous OEs into finite-dimensional algebraic syst…
Universal Magnetic Structure Prediction from Atomic Coordinates with Near-Experimental Accuracy
Abhijatmedhi Chotrattanapituk, Ryotaro Okabe, Eunbi Rha +6
Magnetic order is a fundamental property of materials, governing collective behavior and enabling a broad range of functionalities. Yet magnetic structure remains difficult to dete…
Tuning chiral anomaly signature in a Dirac semimetal via fast-ion implantation
Manasi Mandal, Eunbi Rha, Abhijatmedhi Chotrattanapituk +13
CdAs is a prototypical Dirac semimetal that hosts a chiral anomaly and thereby functions as a platform to test high-energy physics hypotheses and to realize energy efficien…
Spatiotemporal Mapping of Anisotropic Thermal Transport in GaN Thin Films via Ultrafast X-ray Diffraction
Thanh Nguyen, Chuliang Fu, Mouyang Cheng +17
Efficient thermal management is essential for the reliability of modern power electronics, where increasing device density leads to severe heat dissipation challenges. However, in…
A Foundation Model for Non-Destructive Defect Identification from Vibrational Spectra
Mouyang Cheng, Chu-Liang Fu, Bowen Yu +5
Defects are ubiquitous in solids and strongly influence materials' mechanical and functional properties. However, non-destructive characterization and quantification of defects, es…
AI-driven materials design: a mini-review
Mouyang Cheng, Chu-Liang Fu, Ryotaro Okabe +4
Materials design is an important component of modern science and technology, yet traditional approaches rely heavily on trial-and-error and can be inefficient. Computational techni…
Large Language Model-Guided Prediction Toward Quantum Materials Synthesis
Ryotaro Okabe, Zack West, Abhijatmedhi Chotrattanapituk +5
The synthesis of inorganic crystalline materials is essential for modern technology, especially in quantum materials development. However, designing efficient synthesis workflows r…
Structural Constraint Integration in Generative Model for Discovery of Quantum Material Candidates
Ryotaro Okabe, Mouyang Cheng, Abhijatmedhi Chotrattanapituk +9
Billions of organic molecules are known, but only a tiny fraction of the functional inorganic materials have been discovered, a particularly relevant problem to the community searc…
Ensemble-Embedding Graph Neural Network for Direct Prediction of Optical Spectra from Crystal Structure
Nguyen Tuan Hung, Ryotaro Okabe, Abhijatmedhi Chotrattanapituk +1
Optical properties in solids, such as refractive index and absorption, hold vast applications ranging from solar panels to sensors, photodetectors, and transparent displays. Howeve…
Machine learning detecting Majorana Zero Mode from Zero Bias Peak measurements
Mouyang Cheng, Ryotaro Okabe, Abhijatmedhi Chotrattanapituk +1
Majorana zero modes (MZMs), emerging as exotic quasiparticles that carry non-Abelian statistics, hold great promise for achieving fault-tolerant topological quantum computation. A…
Precise Fermi-level engineering in a topological Weyl semimetal via fast ion implantation
Manasi Mandal, Abhijatmedhi Chotrattanapituk, Kevin Woller +10
The precise controllability of the Fermi level is a critical aspect of quantum materials. For topological Weyl semimetals, there is a pressing need to fine-tune the Fermi level to…
Topological superconductors from a materials perspective
Manasi Mandal, Nathan C. Drucker, Phum Siriviboon +6
Topological superconductors (TSCs) have garnered significant research and industry attention in the past two decades. By hosting Majorana bound states which can be used as qubits t…
Virtual Node Graph Neural Network for Full Phonon Prediction
Ryotaro Okabe, Abhijatmedhi Chotrattanapituk, Artittaya Boonkird +10
The structure-property relationship plays a central role in materials science. Understanding the structure-property relationship in solid-state materials is crucial for structure d…