activity
20192023
most citedMachine Learning on Neutron and X-Ray Scattering

124 citations · 388 across the 15 of their papers we have counts for

collaborators

15 papers

cond-mat.mtrl-sci2023

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…

cond-mat.mtrl-sci2023★ 3 cited

Sustainability-Driven Exploration of Topological Material

Artittaya Boonkird, Nathan Drucker, Manasi Mandal +9

Topological materials are at the forefront of quantum materials research, offering tremendous potential for next-generation energy and information devices. However, current investi…

physics.app-ph2023★ 72 cited

Current-induced deterministic switching of van der Waals ferromagnet at room temperature

Shivam N. Kajale, Thanh Nguyen, Corson A. Chao +4

Recent discovery of emergent magnetism in van der Waals magnetic materials (vdWMM) has broadened the material space for developing spintronic devices for energy-efficient computati…

cond-mat.mtrl-sci2023

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…

cond-mat.dis-nn2023★ 1 cited

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…

cond-mat.mtrl-sci2022★ 1 cited

Panoramic mapping of phonon transport from ultrafast electron diffraction and machine learning

Zhantao Chen, Xiaozhe Shen, Nina Andrejevic +11

One central challenge in understanding phonon thermal transport is a lack of experimental tools to investigate mode-based transport information. Although recent advances in computa…

cond-mat.mtrl-sci2021★ 21 cited

Elucidating proximity magnetism through polarized neutron reflectometry and machine learning

Nina Andrejevic, Zhantao Chen, Thanh Nguyen +7

Polarized neutron reflectometry is a powerful technique to interrogate the structures of multilayered magnetic materials with depth sensitivity and nanometer resolution. However, r…

cond-mat.str-el2021★ 32 cited

Electronic properties of correlated kagomé metals AVSb(A = K, Rb, Cs): A perspective

Thanh Nguyen, Mingda Li

Following the discovery of a new family of kagomé prototypical materials with structure AVSb (A = K, Rb, Cs), there has been heightened interest in studying the correlation…

cond-mat.str-el2021

Fluctuation-driven, topology-stabilized order in a correlated nodal semimetal

Nathan C. Drucker, Thanh Nguyen, Fei Han +19

The interplay between strong electron correlation and band topology is at the forefront of condensed matter research. As a direct consequence of correlation, magnetism enriches top…

cond-mat.mtrl-sci2021★ 124 cited

Machine Learning on Neutron and X-Ray Scattering

Zhantao Chen, Nina Andrejevic, Nathan Drucker +8

Neutron and X-ray scattering represent two state-of-the-art materials characterization techniques that measure materials' structural and dynamical properties with high precision. T…

cond-mat.mtrl-sci2021★ 4 cited

Topological Signatures in Nodal Semimetals through Neutron Scattering

Thanh Nguyen, Yoichiro Tsurimaki, Ricardo Pablo-Pedro +5

Topological nodal semimetals are known to host a variety of fascinating electronic properties due to the topological protection of the band-touching nodes. Neutron scattering, desp…

cond-mat.mtrl-sci2020★ 6 cited

Signature of Many-Body Localization of Phonons in Strongly Disordered Superlattices

Thanh Nguyen, Nina Andrejevic, Hoi Chun Po +17

Many-body localization (MBL) has attracted significant attention due to its immunity to thermalization, role in logarithmic entanglement entropy growth, and opportunities to reach…

cond-mat.dis-nn2020★ 34 cited

Machine learning spectral indicators of topology

Nina Andrejevic, Jovana Andrejevic, B. Andrei Bernevig +7

Topological materials discovery has emerged as an important frontier in condensed matter physics. While theoretical classification frameworks have been used to identify thousands o…

cond-mat.mes-hall2019

Spectroscopic Signatures of Nonlocal Interfacial Coupling in Superconducting FeSe/SrTiO3 Heterostructures

Nina Andrejevic, Fei Han, Thanh Nguyen +10

The mechanism of enhanced superconductivity in the one unit-cell (1UC) FeSe film on a SrTiO3 (STO) substrate has stimulated significant research interest but remains elusive. Using…

cond-mat.mes-hall2019★ 90 cited

Quantized Thermoelectric Hall Effect Induces Giant Power Factor in a Topological Semimetal

Fei Han, Nina Andrejevic, Thanh Nguyen +14

Thermoelectrics are promising by directly generating electricity from waste heat. However, (sub-)room-temperature thermoelectrics have been a long-standing challenge due to vanishi…