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Qimin Yan

Showing results (1-10 of 36) 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
The Journal of Physical Chemistry Letters|November 12, 2019
Chemisorption Can Reverse Defect-Defect Interaction on Heterogeneous Catalyst SurfacesLiping Yu, Adrienn Ruzsinszky, Qimin Yan
Nature Communications|May 26, 2017
Negative Poisson's ratio in 1T-type crystalline two-dimensional transition metal dichalcogenidesLiping Yu, Qimin Yan, Adrienn Ruzsinszky
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
Advanced Materials (Deerfield Beach, Fla.)|January 10, 2024
The Case for a Defect Genome InitiativeQimin Yan, Swastik Kar, Sugata Chowdhury, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|October 16, 2023
Bilayer Kagome Borophene with Multiple van Hove SingularitiesQian Gao, Qimin Yan, Zhenpeng Hu, et al.
Nature Communications|March 1, 2026
Accurate prediction of tensorial spectra using equivariant graph neural networkTing-Wei Hsu, Zhenyao Fang, Arun Bansil, et al.
Nature Communications|January 26, 2022
Antisite defect qubits in monolayer transition metal dichalcogenidesJeng-Yuan Tsai, Jinbo Pan, Hsin Lin, et al.
Nano Letters|March 21, 2020
Hierarchically 3D Porous Ag Nanostructures Derived from Silver Benzenethiolate Nanoboxes: Enabling CO<sub>2</sub> Reduction with a Near-Unity Selectivity and Mass-Specific Current Density over 500 A/gSasitha C Abeyweera, Jie Yu, John P Perdew, et al.
Pageof 4

Showing results (1-10 of 36) with videos related to

Sort By:
Pageof 4
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
The Journal of Physical Chemistry Letters|November 12, 2019
Chemisorption Can Reverse Defect-Defect Interaction on Heterogeneous Catalyst SurfacesLiping Yu, Adrienn Ruzsinszky, Qimin Yan
Nature Communications|May 26, 2017
Negative Poisson's ratio in 1T-type crystalline two-dimensional transition metal dichalcogenidesLiping Yu, Qimin Yan, Adrienn Ruzsinszky
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
Advanced Materials (Deerfield Beach, Fla.)|January 10, 2024
The Case for a Defect Genome InitiativeQimin Yan, Swastik Kar, Sugata Chowdhury, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)|October 16, 2023
Bilayer Kagome Borophene with Multiple van Hove SingularitiesQian Gao, Qimin Yan, Zhenpeng Hu, et al.
Nature Communications|March 1, 2026
Accurate prediction of tensorial spectra using equivariant graph neural networkTing-Wei Hsu, Zhenyao Fang, Arun Bansil, et al.
Nature Communications|January 26, 2022
Antisite defect qubits in monolayer transition metal dichalcogenidesJeng-Yuan Tsai, Jinbo Pan, Hsin Lin, et al.
Nano Letters|March 21, 2020
Hierarchically 3D Porous Ag Nanostructures Derived from Silver Benzenethiolate Nanoboxes: Enabling CO<sub>2</sub> Reduction with a Near-Unity Selectivity and Mass-Specific Current Density over 500 A/gSasitha C Abeyweera, Jie Yu, John P Perdew, et al.
Pageof 4