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Nanoscale
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May 18, 2026
High throughput generation of high-<i>zT</i> thermoelectrics with precise stoichiometric controls
Yuelin Wang, Chengquan Zhong, Jingzi Zhang, et al.
Nanoscale
|
November 10, 2023
Data-driven machine learning prediction of glass transition temperature and the glass-forming ability of metallic glasses
Jingzi Zhang, Mengkun Zhao, Chengquan Zhong, et al.
Nanoscale
|
June 18, 2025
Enhancing perovskite solar cell efficiency and stability: a multimodal prediction approach integrating microstructure, composition, and processing technology
Wajeeha Rahman, Chengquan Zhong, Haotian Liu, et al.
Nanoscale
|
June 19, 2023
Accurate and efficient machine learning models for predicting hydrogen evolution reaction catalysts based on structural and electronic feature engineering in alloys
Jingzi Zhang, Yuelin Wang, Xuyan Zhou, et al.
ACS Applied Materials & Interfaces
|
October 25, 2024
Enhancing Superconductor Critical Temperature Prediction: A Novel Machine Learning Approach Integrating Dopant Recognition
Chengquan Zhong, Yuelin Wang, Yanwu Long, et al.
ACS Applied Materials & Interfaces
|
June 16, 2023
Deep Generative Model for Inverse Design of High-Temperature Superconductor Compositions with Predicted <i>T</i><sub>c</sub> > 77 K
Chengquan Zhong, Jingzi Zhang, Xiaoting Lu, et al.
ACS Applied Materials & Interfaces
|
March 31, 2026
Machine Learning-Guided Discovery of High-Performance Perovskite Solar Cells via Cluster Analysis and Experimental Validation
Wajeeha Rahman, Chengquan Zhong, Jingzi Zhang, et al.
ACS Applied Materials & Interfaces
|
March 20, 2025
Inverse Design of High-Performance Thermoelectric Materials via a Generative Model Combined with Experimental Verification
Yanwu Long, Chengquan Zhong, Xiaojing Ma, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|
June 22, 2026
Advancing the Design of High-Efficiency Printable Hole-Conductor-Free Mesoscopic Perovskite Solar Cells Through Machine Learning
Hao Meng, Jingzi Zhang, Xu Zhu, et al.
ACS Omega
|
June 15, 2026
Machine Learning for Superconductor Discovery: From Data-Driven Insights to Accelerated Design
Jingzi Zhang, Chengquan Zhong, Cailu Xiao, et al.
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Search research articles
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Showing results (1-10 of 10) with videos related to
Sort By:
Page
of 1
Nanoscale
|
May 18, 2026
High throughput generation of high-<i>zT</i> thermoelectrics with precise stoichiometric controls
Yuelin Wang, Chengquan Zhong, Jingzi Zhang, et al.
Nanoscale
|
November 10, 2023
Data-driven machine learning prediction of glass transition temperature and the glass-forming ability of metallic glasses
Jingzi Zhang, Mengkun Zhao, Chengquan Zhong, et al.
Nanoscale
|
June 18, 2025
Enhancing perovskite solar cell efficiency and stability: a multimodal prediction approach integrating microstructure, composition, and processing technology
Wajeeha Rahman, Chengquan Zhong, Haotian Liu, et al.
Nanoscale
|
June 19, 2023
Accurate and efficient machine learning models for predicting hydrogen evolution reaction catalysts based on structural and electronic feature engineering in alloys
Jingzi Zhang, Yuelin Wang, Xuyan Zhou, et al.
ACS Applied Materials & Interfaces
|
October 25, 2024
Enhancing Superconductor Critical Temperature Prediction: A Novel Machine Learning Approach Integrating Dopant Recognition
Chengquan Zhong, Yuelin Wang, Yanwu Long, et al.
ACS Applied Materials & Interfaces
|
June 16, 2023
Deep Generative Model for Inverse Design of High-Temperature Superconductor Compositions with Predicted <i>T</i><sub>c</sub> > 77 K
Chengquan Zhong, Jingzi Zhang, Xiaoting Lu, et al.
ACS Applied Materials & Interfaces
|
March 31, 2026
Machine Learning-Guided Discovery of High-Performance Perovskite Solar Cells via Cluster Analysis and Experimental Validation
Wajeeha Rahman, Chengquan Zhong, Jingzi Zhang, et al.
ACS Applied Materials & Interfaces
|
March 20, 2025
Inverse Design of High-Performance Thermoelectric Materials via a Generative Model Combined with Experimental Verification
Yanwu Long, Chengquan Zhong, Xiaojing Ma, et al.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|
June 22, 2026
Advancing the Design of High-Efficiency Printable Hole-Conductor-Free Mesoscopic Perovskite Solar Cells Through Machine Learning
Hao Meng, Jingzi Zhang, Xu Zhu, et al.
ACS Omega
|
June 15, 2026
Machine Learning for Superconductor Discovery: From Data-Driven Insights to Accelerated Design
Jingzi Zhang, Chengquan Zhong, Cailu Xiao, et al.
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of 1