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RESEARCH PAPER · Fuel · 2022

Mapping between Density of States and Energy Band Gap for Bismuth-Based Semiconductors Via Machine Learning Prediction

Yang Ling, Zhengxin Chen, Site Li, Yunxiao Guan, Min Shi, Jun Yue Zhu, Zhihai Cheng, Jiang Wu, Chaojie Yin, Mengjie Bai

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Mapping between Density of States and Energy Band Gap for Bismuth-Based Semiconductors Via Machine Learning PredictionOriginalConstructing a link between multivariate titanium-based semiconductor band gaps and chemical formulae based on machine learning5Electronic properties prediction enhancement of 36 ternary III-IB-VI alloys using a deep feed-forward neural network1Properties of manganese (III) oxide (Mn 2 O 3 ) catalyst for use in Fe-air batteries0Machine learning-based prediction of nonlinear optical rectification in GaAs/AlGaAs tetrapod core/shell quantum dots under pressure and central hydrogenic impurity effects12Application of Machine Learning in Predicting the Properties of Two-Dimensional Semiconductor Materials3Advances in Bi-MOF-based heterostructures for CO2 photoconversion: Mechanistic insights, charge dynamics, and structure-function correlations0

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  1. Constructing a link between multivariate titanium-based semiconductor band gaps and chemical formulae based on machine learning

    Materials Today Communications · 2023-05-24

    Jiawei Li, Zhengxin Chen, Jiang Wu, Jia Horng Lin, Ping He, Rui Zhu, Cheng Peng, Hai Feng Zhang, Wenhao Li, Xu Fang, Hongtao Shen

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  2. Electronic properties prediction enhancement of 36 ternary III-IB-VI alloys using a deep feed-forward neural network

    Materials Today Communications · 2024-05-01

    Parisa Mohammadi, Alireza Kokabi, Hamid Reza Shahdoosti, Shoeib Babaee Touski

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  3. Properties of manganese (III) oxide (Mn 2 O 3 ) catalyst for use in Fe-air batteries

    MATEC Web of Conferences · 2025-01-01

    Edwine Matlou, Tshegofatso M. Phaahla, Phuti Esrom Ngoepe, Khomotso Portia Maenetja

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  4. Machine learning-based prediction of nonlinear optical rectification in GaAs/AlGaAs tetrapod core/shell quantum dots under pressure and central hydrogenic impurity effects

    Materials Science in Semiconductor Processing · 2025-09-03

    Nabil Zeiri, Ayoub Ed-Dahmouny, David B. Hayrapetyan, Pınar BAŞER, Ahmed Sali, Mohamed E. El Sayed, A. Samir, C.A. Duque

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  5. Application of Machine Learning in Predicting the Properties of Two-Dimensional Semiconductor Materials

    Nanomaterials · 2026-05-22

    Jie Yang, Lingli Tang, Yunlong Wang, Jie Wen, Wenyuan Chen

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  6. Advances in Bi-MOF-based heterostructures for CO2 photoconversion: Mechanistic insights, charge dynamics, and structure-function correlations

    Journal of Energy Chemistry · 2026-10-01

    Anchal Panwar, Naveen Thakur, Vatika Soni, Akshay Chawla, Pankaj Raizada, Pardeep Singh, Pankaj Thakur, Chaudhery Mustansar Hussain, Aftab Aslam Parwaz Khan, Sonu Sonu

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