刘悦｜上海大学｜学者主页

2026

材料领域知识嵌入的分而治之机器学习

杨正伟，刘子图，张王颖，左维，余振垚，邹欣欣，袁浩栋，苏玉凤，施思齐，刘悦

《硅酸盐学报》

DOI

2026

Structure divide-and-conquer: dual graph representation for accurate ionic transport barrier prediction of inorganic compounds

Zhengwei Yang, Linhan Wu, Bing He, Maxim Avdeev, Siqi Shi, Yue Liu

npj Computational Materials

DOI

2026

Beyond Fluorination: A Golden Criterion Guided by Chemical Coordination‐Informed Machine Learning for High‐Voltage Electrolyte Design

Kai Guo, Yaqiao Luo, Z J Yang, W Z Zhang, Yue Liu, Liquan Chen, Da Wang, Siqi Shi

Angewandte Chemie

DOI

2025

A Database of Composition‐Processing‐Performance Parameters for over 400 Inorganic‐Polymer Composite Solid‐State Electrolytes

Pengjin Huang, Zhengwei Yang, Yue Liu, Peijun Yu, Bo Liu, Miao Xu, Maxim Avdeev, Siqi Shi

Advanced Theory and Simulations

DOI

2025

A general framework to govern machine learning oriented materials data quality

Yue Liu, Zhengwei Yang, Xinxin Zou, Yuxiao Lin, Shuchang Ma, Wei Zuo, Zheyi Zou, Hong Wang, Maxim Avdeev, Siqi Shi

Materials Science and Engineering R Reports

DOI

2025

A knowledge acquisition automatizing framework from literature exemplified by Na+ activation energy prediction of NASICON solid-state electrolyte

Yue Liu, Dahui Liu, Zhengwei Yang, Xianyuan Ge, Wenxuan Yao, Jie Wu, Maxim Avdeev, Siqi Shi

Energy storage materials

DOI

2025

Domain knowledge-assisted materials data anomaly detection towards constructing high-performance machine learning models

Yue Liu, Shuchang Ma, Zhengwei Yang, Duo Wu, Yali Zhao, Maxim Avdeev, Siqi Shi

Journal of Materiomics

DOI

2025

Descriptors Divide‐and‐Conquer Enables Multifaceted and Interpretable Materials Structure–Activity Relationship Analysis

Yue Liu, Linhan Wu, Zhengwei Yang, Xinxin Zou, Zheyi Zou, Yuxiao Lin, Maxim Avdeev, Siqi Shi

Advanced Functional Materials

DOI

2024

高质量文本数据驱动的命名实体识别加速镍基单晶高温合金材料知识发现

刘悦，姚文轩，刘大晖，丁琳，杨正伟，刘微，于涛，施思齐

《金属学报》

2023

Auto-MatRegressor材料性能自动预测器:解放材料机器学习“调参师”（英文）

刘悦，王双燕，杨正伟，Maxim Avdeev，施思齐

Science Bulletin

2023

面向材料领域机器学习的数据质量治理

刘悦，马舒畅，杨正伟，邹欣欣，施思齐

《硅酸盐学报》

2023

Auto-MatRegressor: liberating machine learning alchemists

Yue Liu, Shuangyan Wang, Zhengwei Yang, Maxim Avdeev, Siqi Shi

《中国科学通报：英文版》

DOI

2023

Data quantity governance for machine learning in materials science

Yue Liu, Zhengwei Yang, Xinxin Zou, Shuchang Ma, Dahui Liu, Maxim Avdeev, Siqi Shi

National Science Review

DOI

2023

Domain knowledge discovery from abstracts of scientific literature on Nickel-based single crystal superalloys

Yue Liu, Lin Ding, Zhengwei Yang, Xianyuan Ge, DaHui Liu, Wei Liu, Tao Yu, Maxim Avdeev, Siqi Shi

Science China Technological Sciences

DOI

2022

材料领域知识嵌入的机器学习

刘悦，邹欣欣，杨正伟，施思齐

《硅酸盐学报》

2022

融合材料领域知识的数据准确性检测方法

施思齐，孙拾雨，马舒畅，邹欣欣，钱权，刘悦

《无机材料学报》

2022

An automatic descriptors recognizer customized for materials science literature

Yue Liu, Xianyuan Ge, Zhengwei Yang, Shiyu Sun, Dahui Liu, Maxim Avdeev, Siqi Shi

Journal of Power Sources

DOI

2022

Feature selection method reducing correlations among features by embedding domain knowledge

Yue Liu, Xinxin Zou, Shuchang Ma, Maxim Avdeev, Siqi Shi

Acta Materialia

DOI

2020

Identifying Chemical Factors Affecting Reaction Kinetics in Li-air Battery via ab initio Calculations and Machine Learning

Aiping Wang, Zheyi Zou, Da Wang, Yue Liu, Yajie Li, Junming Wu, Maxim Avdeev, Siqi Shi

Energy storage materials

DOI

2020

Machine learning assisted materials design and discovery for rechargeable batteries

Yue Liu, Biru Guo, Xinxin Zou, Yajie Li, Siqi Shi

Energy storage materials

DOI

2020

An integrated retrieval framework for similar questions: Word-semantic embedded label clustering – LDA with question life cycle

Yue Liu, Aihua Tang, Zhibin Sun, Weize Tang, Fei Cai, Chengjin Wang

Information Sciences

DOI

2020

Predicting creep rupture life of Ni-based single crystal superalloys using divide-and-conquer approach based machine learning

Yue Liu, Junming Wu, Zhichao Wang, Xiao‐Gang Lu, Maxim Avdeev, Siqi Shi, Chong‐Yu Wang, Tao Yu

Acta Materialia

DOI

2019

Predicting the onset temperature (Tg) of Ge Se1− glass transition: a feature selection based two-stage support vector regression method

Yue Liu, Junming Wu, Guang Yang, Tianlu Zhao, Siqi Shi

《中国科学通报：英文版》

DOI

2018

Item life cycle based collaborative filtering

Yue Liu, Fei Cai, Pengfei Ren, Zhizhou Gu

Journal of Intelligent & Fuzzy Systems

DOI

2017

Materials discovery and design using machine learning

Yue Liu, Tianlu Zhao, Wangwei Ju, Siqi Shi

Journal of Materiomics

DOI

2013

Effective Personalized Recommendation using United Auxiliary Domain based Weighted Rating Model in Large-Scale BT Download Datasets

Yue Liu, Binkai Shi -, Guobing Zou, Zhe Xu

Journal of Convergence Information Technology

DOI

刘悦

精选作品

期刊论文

材料领域知识嵌入的分而治之机器学习

Structure divide-and-conquer: dual graph representation for accurate ionic transport barrier prediction of inorganic compounds

Beyond Fluorination: A Golden Criterion Guided by Chemical Coordination‐Informed Machine Learning for High‐Voltage Electrolyte Design

A Database of Composition‐Processing‐Performance Parameters for over 400 Inorganic‐Polymer Composite Solid‐State Electrolytes

A general framework to govern machine learning oriented materials data quality

A knowledge acquisition automatizing framework from literature exemplified by Na+ activation energy prediction of NASICON solid-state electrolyte

Domain knowledge-assisted materials data anomaly detection towards constructing high-performance machine learning models

Descriptors Divide‐and‐Conquer Enables Multifaceted and Interpretable Materials Structure–Activity Relationship Analysis

高质量文本数据驱动的命名实体识别加速镍基单晶高温合金材料知识发现

Auto-MatRegressor材料性能自动预测器:解放材料机器学习“调参师”（英文）

面向材料领域机器学习的数据质量治理

Auto-MatRegressor: liberating machine learning alchemists

Data quantity governance for machine learning in materials science

Domain knowledge discovery from abstracts of scientific literature on Nickel-based single crystal superalloys

材料领域知识嵌入的机器学习

融合材料领域知识的数据准确性检测方法

An automatic descriptors recognizer customized for materials science literature

Feature selection method reducing correlations among features by embedding domain knowledge

Identifying Chemical Factors Affecting Reaction Kinetics in Li-air Battery via ab initio Calculations and Machine Learning

Machine learning assisted materials design and discovery for rechargeable batteries

An integrated retrieval framework for similar questions: Word-semantic embedded label clustering – LDA with question life cycle

Predicting creep rupture life of Ni-based single crystal superalloys using divide-and-conquer approach based machine learning

Predicting the onset temperature (Tg) of Ge Se1− glass transition: a feature selection based two-stage support vector regression method

Item life cycle based collaborative filtering

Materials discovery and design using machine learning

Effective Personalized Recommendation using United Auxiliary Domain based Weighted Rating Model in Large-Scale BT Download Datasets

研究方向