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陆

陆文聪 (Wencong Lu)

shanghai university邮箱:wclu@shu.edu.cn

H指数:46

被引数:7,627

个人简介

现任理学院副院长。1986年获北京清华大学物理化学及仪器分析专业学士学位，1991年获上海科技大学物理化学专业硕士学位，1999年获中科院上海冶金研究所材料物理和化学专业博士学位。历任上海大学助教（1986－1992年）、讲师（1992－1996年）、副教授（1996年－2002年）、教授（2002年－）、博士生导师（2004年－）。曾任理学院化学系副主任、党委组织部副部长。

教育背景

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工作经历

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荣誉奖项

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A Problem-Setup-Centric Framework for Mixed-Variable Chemical Formulation Optimization with Customized Constraints

以问题-设定为中心的框架，用于具有定制化约束的混合变量化学配方优化

IF3.2

2026-08-010

OA

Creating Gallium-based alloys with the lowest melting point via reverse design Approach

通过逆向设计方法制备具有最低熔点的镓基合金

Acta Materialia

IF9.3

2025-09-250

PRE

Accelerated discovery of lead-free solder alloys with enhanced creep resistance via complementary machine learning strategy

通过互补的机器学习策略加速发现具有增强的抗蠕变性的无铅焊料合金

JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T

IF6.6

2024-09-011

OAAI

Accelerated discovery of Magnesium-based amorphous alloys through a property-driven active learning strategy

JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T

IF6.6

2024-09-010

OAAI

Inverse Design of Low-Resistivity Ternary Gold Alloys via Interpretable Machine Learning and Proactive Search Progress

IF3.2

2024-07-220

OAAI

The mastery of details in the workflow of materials machine learning

NPJ COMPUTATIONAL MATERIALS

IF11.9

2024-07-021

OA

Inverse design of Bulk metallic glasses with reduced glass transform temperatures via Target-Optimal inverse projection

COMPUTATIONAL MATERIALS SCIENCE

IF3.3

2024-02-010

PRE

Discovery Precision: An effective metric for evaluating performance of machine learning model for explorative materials discovery

发现精度: 用于评估探索性材料发现的机器学习模型性能的有效指标

COMPUTATIONAL MATERIALS SCIENCE

IF3.3

2024-01-017

PRE

Target-directed discovery for low melting point alloys via inverse design strategy

JOURNAL OF ALLOYS AND COMPOUNDS

IF6.3

2024-01-013

PRE

Accelerating the discovery of N-annulated perylene organic sensitizers via an interpretable machine learning model

JOURNAL OF MOLECULAR STRUCTURE

IF4.7

2024-01-014

PRE

Interpretable machine learning assisted multi-objective optimization design for small molecule hole transport materials

JOURNAL OF ALLOYS AND COMPOUNDS

IF6.3

2023-12-013

PRE

OCPMDM 2.0: An intelligent solution for materials data mining

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

IF3.8

2023-12-013

PRE

MIC-SHAP: An ensemble feature selection method for materials machine learning

Mic-shap: 一种面向材料机器学习的集成特征选择方法

MATERIALS TODAY COMMUNICATIONS

IF4.5

2023-12-0118

PRE

Accelerated Design for High-Entropy Alloys Based on Machine Learning and Multiobjective Optimization

JOURNAL OF CHEMICAL INFORMATION AND MODELING

IF5.3

2023-09-266

PRE

Machine Learning-Directed Fast and High-Throughput Acquisition of High-Efficiency Microwave Absorbents From Infinite Design Space

面向机器学习的从无限设计空间快速高通量获取高效微波吸收剂

ADVANCED FUNCTIONAL MATERIALS

IF19

2023-08-249

OA

Machine Learning Combined with Weighted Voting Regression and Proactive Searching Progress to Discover ABO3-δ Perovskites with High Oxide Ionic Conductivity

机器学习结合加权投票回归和主动搜索发现具有高氧化物离子电导率的ABO3-δ 钙钛矿的进展

JOURNAL OF PHYSICAL CHEMISTRY C

IF3.2

2023-08-186

PRE

Machine learning assisted classification of post-treatment amines for increasing the stability of organic-inorganic hybrid perovskites

MATERIALS TODAY COMMUNICATIONS

IF4.5

2023-06-011

PRE

Feature Selection in Machine Learning for Perovskite Materials Design and Discovery

用于钙钛矿材料设计和发现的机器学习中的特征选择

IF3.2

2023-04-1620

OAAI

Small data machine learning in materials science

材料科学中的小数据机器学习

NPJ COMPUTATIONAL MATERIALS

IF11.9

2023-03-25180

OAAI

Rational design of ZL003-based organic dyes for highly efficient dye-sensitized solar cells: Influence of alkynyl group and n-spacers on photovoltaic performance

JOURNAL OF MOLECULAR STRUCTURE

IF4.7

2022-12-019

PRE