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Zhenyao Fang

Showing results (1-10 of 12) with videos related to

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Chemistry of Materials : a Publication of the American Chemical Society|March 3, 2025
Leveraging Persistent Homology Features for Accurate Defect Formation Energy Predictions via Graph Neural NetworksZhenyao Fang, Qimin Yan
ACS Nano|October 13, 2025
A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered MaterialsZhenyao Fang, Ting-Wei Hsu, Qimin Yan
Scientific Data|July 2, 2025
Dataset of tensorial optical and transport properties of materials from the Wannier function methodZhenyao Fang, Ting-Wei Hsu, Qimin Yan
Nature Communications|March 1, 2026
Accurate prediction of tensorial spectra using equivariant graph neural networkTing-Wei Hsu, Zhenyao Fang, Arun Bansil, et al.
The Journal of Physical Chemistry Letters|July 18, 2025
Different Charge Transport Mechanisms in Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene Monoflakes and MultiflakesHui Fang, Zhenyao Fang, Anupma Thakur, et al.
Nano Letters|February 3, 2025
Chiral Molecular Magnet Superstructures with Light ControlZhongxuan Wang, Ti Xie, Zhenyao Fang, et al.
Nano Letters|September 16, 2025
Coherent Spins in van der Waals Semiconductor GeS<sub>2</sub> at Ambient ConditionsSumukh Vaidya, Xingyu Gao, Saakshi Dikshit, et al.
Proceedings of the National Academy of Sciences of the United States of America|July 5, 2024
Stabilizing Ti<sub>3</sub>C<sub>2</sub>T<sub></sub> MXene flakes in air by removing confined waterHui Fang, Anupma Thakur, Amirhossein Zahmatkeshsaredorahi, et al.
Journal of the American Chemical Society|July 16, 2025
Planar Defect Layers Template a High-Pressure InBi PolymorphEric A Riesel, Zhenyao Fang, Douglas H Fabini, et al.
Nano Letters|April 24, 2024
Optically Triggered Emergent Mesostructures in Monolayer WS<sub>2</sub>Young-Chul Leem, Zhenyao Fang, Yun-Kyung Lee, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Chemistry of Materials : a Publication of the American Chemical Society|March 3, 2025
Leveraging Persistent Homology Features for Accurate Defect Formation Energy Predictions via Graph Neural NetworksZhenyao Fang, Qimin Yan
ACS Nano|October 13, 2025
A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered MaterialsZhenyao Fang, Ting-Wei Hsu, Qimin Yan
Scientific Data|July 2, 2025
Dataset of tensorial optical and transport properties of materials from the Wannier function methodZhenyao Fang, Ting-Wei Hsu, Qimin Yan
Nature Communications|March 1, 2026
Accurate prediction of tensorial spectra using equivariant graph neural networkTing-Wei Hsu, Zhenyao Fang, Arun Bansil, et al.
The Journal of Physical Chemistry Letters|July 18, 2025
Different Charge Transport Mechanisms in Ti<sub>3</sub>C<sub>2</sub>T<sub><i>x</i></sub> MXene Monoflakes and MultiflakesHui Fang, Zhenyao Fang, Anupma Thakur, et al.
Nano Letters|February 3, 2025
Chiral Molecular Magnet Superstructures with Light ControlZhongxuan Wang, Ti Xie, Zhenyao Fang, et al.
Nano Letters|September 16, 2025
Coherent Spins in van der Waals Semiconductor GeS<sub>2</sub> at Ambient ConditionsSumukh Vaidya, Xingyu Gao, Saakshi Dikshit, et al.
Proceedings of the National Academy of Sciences of the United States of America|July 5, 2024
Stabilizing Ti<sub>3</sub>C<sub>2</sub>T<sub></sub> MXene flakes in air by removing confined waterHui Fang, Anupma Thakur, Amirhossein Zahmatkeshsaredorahi, et al.
Journal of the American Chemical Society|July 16, 2025
Planar Defect Layers Template a High-Pressure InBi PolymorphEric A Riesel, Zhenyao Fang, Douglas H Fabini, et al.
Nano Letters|April 24, 2024
Optically Triggered Emergent Mesostructures in Monolayer WS<sub>2</sub>Young-Chul Leem, Zhenyao Fang, Yun-Kyung Lee, et al.
Pageof 2