714 citations
- Oak Ridge National LaboratoryUS284 papers
- University of Tennessee at KnoxvilleUS71 papers
- Frantsevich Institute for Problems in Materials ScienceUA39 papers
- Institute of PhysicsPL38 papers
- National Academy of Sciences of UkraineUA35 papers
- Argonne National LaboratoryUS20 papers
- University of FloridaUS16 papers
- Vanderbilt UniversityUS15 papers
- V.E. Lashkaryov Institute of Semiconductor PhysicsUA14 papers
- Chinese Academy of SciencesCN10 papers
- Lawrence Berkeley National LaboratoryUS10 papers
- National Institute of Standards and TechnologyUS9 papers
286 papers
Direct observation of ultrafast defect-bound and free exciton dynamics in defect-engineered WS monolayers
Tae Gwan Park, Xufan Li, Kyungnam Kang +7
Defects in two-dimensional transition metal dichalcogenides (TMDCs) broadly affect their optical and electronic properties. Directly capturing the ultrafast processes of exciton tr…
Rapid synthesis of dual-element isotope-enriched alpha-MoO3 crystals by reactive vapor transport
Ryan W. Spangler, Jacob M. Shusterman, Anton V. Ievlev +3
In this work, we develop a rapid reactive vapor transport technique to efficiently utilize limited isotopically pure precursors, particularly gaseous 18O2, and synthesize mm-scale,…
Raman Digital Twin of Monolayer Janus Transition Metal Dichalcogenides
Johnathan Kowalski, Liangbo Liang
Monolayer transition metal dichalcogenides (TMDs) are a key class of two-dimensional (2D) materials with broad technological potential. Their Janus counterparts exhibit unique prop…
Curiosity Driven Exploration to Optimize Structure-Property Learning in Microscopy
Aditya Vatsavai, Ganesh Narasimha, Yongtao Liu +5
Rapidly determining structure-property correlations in materials is an important challenge in better understanding fundamental mechanisms and greatly assists in materials design. I…
Deciphering the Scattering of Mechanically Driven Polymers using Deep Learning
Lijie Ding, Chi-Huan Tung, Bobby G. Sumpter +2
We present a deep learning approach for analyzing two-dimensional scattering data of semiflexible polymers under external forces. In our framework, scattering functions are compres…
Deep learning with reflection high-energy electron diffraction images to predict cation ratio in SrTiO thin films
Sumner B. Harris, Patrick T. Gemperline, Christopher M. Rouleau +2
Machine learning (ML) with in situ diagnostics offers a transformative approach to accelerate, understand, and control thin film synthesis by uncovering relationships between synth…