乔智威

作者: 时间:2023-04-20 点击数:

基本情况:

乔智威,男,工学博士,教授,硕士生导师,博士后合作导师,广东省青年拔尖人才,广州市高层次人才,广州学者A类特聘教授。

职务:化工系系主任,化工食品教工党支部书记,广州大学青年博士学术联谊会理事长

 

联系方式:

E-mail: qzw3140cn@126.com

 

教育经历:

2008/9-2013/9 华南理工大学,化学与化工学院,化学工程专业,获工学博士学位

2011/9-2012/9 美国西北大学,化工系,化学工程专业,联合培养博士生

2004/9-2008/6 华南理工大学,化学与化工学院,化学工程与工艺专业,获工学学士学位

 

工作经历:

2018/2-至今   任广州大学化学化工学院化工系专任教师,硕士生导师,从事教学和科学研究

2013/9-2018/2 分别在华南理工大学制浆造纸工程国家重点实验室、化学与化工学院和新加坡国立大学工程学院化工系从事博士后研究

 

科研方向:

目前主要从事化工材料高通量计算与智能设计。通过计算机分子模拟手段高通量筛选和人工智能技术自动设计新型多孔材料,如金属-有机框架材料(MOFs)、分子筛、聚合物材料等;使用大数据分析建立材料的成分-结构-性能三维关系,并择优进行实验合成。

 

科研项目:

主持科研项目16项:

[16] 广东省人才计划——青年拔尖人才,2020.01-2024.12

[15] 广州市人才计划——广聚英才计划,2021.10-2026.09

[14] 国家自然科学基金项目,面上项目,2020.01-2023.12

[13] 国家自然科学基金项目,面上项目,2017.01-2020.12

[12] 广东省自然科学基金,面上项目,2022.01-2024.12

[11] 广州市科技计划项目,市校(院)联合资助项目,2022.04-2024.03

[10] 广州大学-香港科技大学联合研究合作基金,2022.01-2022.12

[9] 广州市科技计划项目,基础与应用基础研究项目,2021.04-2023.03

[8] 广东省自然科学基金,面上项目,2019.10-2022.09

[7] 广州大学百人计划,科研启动项目,2018.05-2023.05

[6] 广东省自然科学基金,博士启动项目;

[5] 中国博士后科学基金,特别资助;

[4] 中国博士后科学基金,面上项目,一等资助;

[3] 华南理工大学中央高校项目,面上项目;

[2] 华南理工大学中央高校项目,博士启动项目;

[1] 华南理工大学制浆造纸工程国家重点实验室开放基金。

 

教学改革项目、奖项与人才培养:

2023年作为指导老师获第十七届“挑战杯”广东大学生课外学术科技作品竞赛广东省一等奖

2023年新华思政网——广州大学“化工专业实验”课程,主讲教师,累计学习人数 2.7万人

2022年广东省高等教育教学研究和改革项目,人工智能技术在实验教学中有机融入的应用实践研究,项目负责人

2022年广州市高等教育信息化教学课程案例类一等奖,第一完成人

2022年广州大学课程思政项目示范课堂项目,化工专业实验(植物中天然香料的提取及香料成分分析),项目负责人

2022年度广州大学“课程思政”优秀教学案例,一等奖,主讲教师

2022年度广州大学“课程思政”优秀教师

2022年广州大学年度优秀基层教学组织,负责人

2022年广州大学教学改革项目,高校虚拟仿真实验教学项目的分类及界定的研究,项目负责人

2021年广东省一流本科课程“化工专业实验”,课程负责人

2021年广州大学学术新锐

2021年化学工程与工艺专业获批广州大学思政示范专业项目,项目负责人

2020-2021学年度学生课外学术科技活动,优秀指导老师

2021年指导硕士研究生石泽南获广东省优秀学生(研究生阶段)称号

2021年作为指导老师获第十六届“挑战杯”广东大学生课外学术科技作品竞赛广东省三等奖

2021年作为指导老师获第十一届广东大学生材料创新大赛三等奖

2020年国家级一流本科课程——虚拟仿真实验教学一流课程,课程参与人(5/5

2020年教育部化工类专业教学质量与教学改革研究计划项目,“互联网+教育”化工类专业教学新模式的理论与实践探索,项目参与人(3/3

2020年全球“计算材料科学学术新星”提名奖(Finalist for Rising Stars in Computational Materials Science

2020年“高等学校“十三五”规划教材”《化学工程与工艺专业实验》副主编,化学工业出版社

2019年国家级虚拟仿真实验教学项目——《香料紫罗兰酮合成工艺虚拟仿真实验》项目,团队主要成员(5/5

2019年广东省高等教育教学成果二等奖,“虚、实”有机融合的化工类专业实践教学人才培养模式的创新与实践,成果完成人(6/8

2019年广东省教育“双融双创”教师教育教学信息化交流及新媒体新技术教学应用三等奖,成果完成人(3/3

2019年广州市教育教学信息化创新应用,高教组二等奖,成果完成人(3/3

 

主要学术任职

[1] 中国化工学会 过程模拟及仿真专业 青年委员

[2] 化工新材料委员会 常务委员;

[3] 广东省材料研究学会会员;

[4] 国家自然科学基金化学部函审专家;

[5] 《电镀与涂饰》编委;

 

论文一览:

发表科技/教学论文75篇,其中SCI论文72篇,JCR Q1区论文55篇;

IF > 10论文32篇;中国科技期刊(卓越行动计划)论文8篇。

 

代表作论文:

(30) Wenfei Wang#, Lulu Zhang#, Chengzhi Cai, Shuhua Li, Hong Liang, Yufang Wu*, He Zheng*, Zhiwei Qiao*, Machine learning assisted high-throughput computational screening of MOFs for the capture of chemical warfare agents from the air, Separation and Purification Technology, 2023, 325, 124546.

(29) Qiuhong Huang, Xueying Yuan, Lifeng Li, Yaling Yan, Xiao Yang, Wei Wang, Yu Chen, Hong Liang*, Hanyu Gao, Yufang Wu*, Zhiwei Qiao*Machine learning and molecular fingerprint screening of high-performance 2D/3D MOF membranes for Kr/Xe separation, Chemical Engineering Science, 2023, 280, 119031.

(28) Shuya Guo, Xiaoshan Huang, Yizhen Situ, Qiuhong Huang, Kexin Guan, Jiaxin Huang, Wei Wang, Xiangning Bai, Zili Liu, Yufang Wu*, Zhiwei Qiao*Interpretable machine-learning and big data mining to predict gas diffusivity in metal-organic frameworks, Advanced Science, 2023, 2301461.

(27) Xiao Yang#, Qiuhong Huang#, Lulu Zhang, Lifeng Li, Yu Chen, Wei Wang, Hong Liang, Yufang Wu*, He Zheng, Yue Zhao*, Zhiwei Qiao*, Computational screening and machine learning of hydrophobic metal-organic frameworks for removal of chemical warfare agents from air, Applied Materials Today, 2023, 31, 101738.

(26) Dongdong Chen#, Yaling Yan#, Anqi Guo, Valentina Rizzotto, Huarong Lei, Zhiwei Qiao*, Hong Liang, Magdalena Jabłońska, Xiangqiong Jiang, Jiuxing Jiang, Regina Palkovits, Peirong Chen*, Daiqi Ye, Ulrich Simon, Mechanistic insights into the promotion of low-temperature NH3-SCR catalysis by copper auto-reduction in Cu-zeolites, Applied Catalysis B: Environmental, 2023, 322, 122118.

(25) Jinqiao Dong, Lingmei Liu, Chunxia Tan, Qisong Xu, Jiachen Zhang, Zhiwei Qiao, Dandan Chu, Yan Liu, Qun Zhang, Jianwen Jiang, Yu Han*, Anthony P. Davis*, Yong Cui*. Free-standing homochiral 2D monolayers by exfoliation of molecular crystals. Nature, 2022, 602, 606-661.

(24) Xiangning Bai, Zenan Shi, Huan Xia, Shuhua Li, Zili Liu, Hong Liang, Zhiting Liu*, Bangfen Wang*, Zhiwei Qiao*, Machine-Learning-Assisted High-Throughput Computational Screening of Metal–Organic Framework Membranes for Hydrogen Separation, Chemical Engineering Journal, 2022, 446, 136783.

(23) Yaling Yan, Zenan Shi, Huilin Li, Lifeng Li, Xiao Yang, Shuhua Li, Hong Liang, Zhiwei Qiao*, Machine learning and in-silico screening of metal–organic frameworks for O2/N2 dynamic adsorption and separation, Chemical Engineering Journal, 2022, 427, 131604.

(22) Xueying Yuan, Lifeng Li, Zenan Shi, Hong Liang, Shuhua Li, Zhiwei Qiao*, Molecular-fingerprint machine-learning-assisted design and prediction for high-performance MOFs for the capture of NMHCs from air, Advanced Powder Materials, 2022, 1, 100026.

(21) Chenghui Zhang, Yongwei Chen*, Houxiao Wu, Huilin Li, Xinyuan Li, Shi Tu, Zhiwei Qiao*, Dongli An, Qibin Xia. Mechanochemical synthesis of a robust cobalt-based metal–organic framework for adsorption separation methane from nitrogen, Chemical Engineering Journal, 2022, 435, 133876.

(20) Aichun Wu, Yuanlin Tang, Xinling Li, Baohua Zhang, Ai-Ju Zhou, Zhiwei Qiao*, Lianpeng Tong*, A Photofunctional Platform of Bis-terpyridine Ruthenium Complex-Linked Coordination Polymers with Structural DiversityJournal of Materials Chemistry A, 2022, 10, 25063-25069.

(19) Zhiwei Qiao*, Lifeng Li, Shuhua Li, Hong Liang, Jian Zhou*, Randall Q. Snurr*, Molecular fingerprint and machine learning to accelerate design of high-performance homochiral metal–organic frameworks, AIChE Journal. 2021, e17352.

(18) Zenan Shi, Xueying Yuan, Yaling Yan, Yuanlin Tang, Junjie Li, Hong Liang, Lianpeng Tong, Zhiwei Qiao*, Techno-Economic Analysis of Metal–Organic Frameworks for Adsorption Heat Pumps/Chillers: From Directional Computational Screening, Machine Learning to Experiment, Journal of Materials Chemistry A, 2021, 9(12): 7656-7666.

(17) Xueying Yuan, Xiaomei Deng, Chengzhi Cai, Zenan Shi, Hong Liang, Shuhua Li, Zhiwei Qiao*, Machine learning and high-throughput computational screening of hydrophobic metal–organic frameworks for capture of formaldehyde from air, Green Energy & Environment, 2021, 6, 759-770.

(16) Jiaxing Wang#, Yaseen Muhammad#, Zhu Gao, Syed Jalil Shah, Shuangxi Nie, Lihan Kuang, Zhongxing Zhao, Zhiwei Qiao*, Zhenxia Zhao*, Implanting Polyethylene Glycol into MIL-101(Cr) as Hydrophobic Barrier for Enhancing Toluene Adsorption under Highly Humid Environment, Chemical Engineering Journal, 2021, 404, 126562.

(15) Hongye Yuan#, Guoliang Liu#, Zhiwei Qiao#, Nanxi Li, Pio John S. Buenconsejo, Shibo Xi, Avishek Karmakar, Mengsha Li, Hong Cai, Stephen John Pennycook, and Dan Zhao*, Solution-Processable Metal-Organic Framework Nanosheets with Variable Functionalities, Advanced Materials, 2021, 33(29): 2101257.

(14) Yaling Yan#, Lulu Zhang#, Shuhua Li, Hong Liang, Zhiwei Qiao*, Adsorption behavior of metal-organic frameworks: From single simulation, high-throughput computational screening to machine learning, Computational Materials Science, 2021, 193, 110383.

(13) Zhiwei Qiao, Yaling Yan, Yaxing Tang, Hong Liang, and Jianwen Jiang*, Metal–Organic Frameworks for Xylene Separation: From Computational Screening to Machine Learning,

Journal of Physical Chemistry C, 2021, 125, 7839-7848.

(12) Zenan Shi, Hong Liang, Wenyuan Yang, Jie Liu, Zili Liu, Zhiwei Qiao*, Machine learning and in silico discovery of metal-organic frameworks: Methanol as a working fluid in adsorption-driven heat pumps and chillers, Chemical Engineering Science, 2020, 214, 115430.

(11) Yongwei Chen, Houxiao Wu, Yinuo Yuan, Daofei Lv, Zhiwei Qiao*, Dongli An, Xuanjun Wu, Hong Liang, Zhong Li, Qibin Xia*, Highly rapid mechanochemical synthesis of a pillar-layer metal-organic framework for efficient CH4/N2 separation, Chemical Engineering Journal, 2020, 385, 123836.

(10) Zenan Shi, Wenyuan Yang, Xiaomei Deng, Chengzhi Cai, Yaling Yan, Hong Liang, Zili Liu, Zhiwei Qiao*, Machine-learning-assisted high-throughput computational screening of high performance metal–organic frameworks, Molecular Systems Design & Engineering, 2020, 5, 725-742.

(9) 蔡铖智#, 李丽凤#, 邓小梅, 李树华, 梁红, 乔智威*. 基于机器学习和高通量计算筛选金属有机框架的甲烷/乙烷/丙烷分离性能. 化学学报, 2020, 78(5): 427-436.

(8) Houxiao Wu, Yongwei Chen, Wenyuan Yang, Daofei Lv, Yinuo Yuan, Zhiwei Qiao*, Hong Liang, Zhong Li, Qibin Xia*, Ethane-selective behavior achieved on a nickel-based MOF: Impact of pore effect and hydrogen bonds, Industrial & Engineering Chemistry Research, 2019, 58, 10516.

(7) Zhiwei Qiao, Anthony K. Cheetham, Jianwen Jiang*, Identifying the best metal–organic frameworks and unravelling different mechanisms for the separation of pentane isomers, Molecular Systems Design & Engineering, 2019, 4, 609.

(6) Zhiwei Qiao, Qisong Xu, Jianwen Jiang*, Computational screening of hydrophobic metal-organic frameworks for the separation of H2S and CO2 from natural gas, Journal of Materials Chemistry A, 2018, 6, 18898.

(5) Zhiwei Qiao, Qisong Xu, Jianwen Jiang*, High-throughput computational screening of metal-organic framework membranes for upgrading of natural gas, Journal of Membrane Science, 2018, 551, 47.

(4) 杨文远, 梁红, 乔智威*. 高通量筛选金属-有机框架:分离天然气中的硫化氢和二氧化碳. 化学学报, 2018, 76, 785.

(3) Zhiwei Qiao, Chunwang Peng, Jian Zhou, Jianwen Jiang*, High-throughput computational screening of 137953 metal-organic frameworks for membrane separation of CO2/N2/CH4 mixture, Journal of Materials Chemistry A, 2016, 4, 15904.

(2) Zhiwei Qiao, Kang Zhang, Jianwen Jiang*, In silico screening of 4764 computation-ready, experimental metal-organic frameworks for CO2 separation, Journal of Materials Chemistry A, 2016, 4(6), 2105.

(1) Zhiwei Qiao, Ariana Torres-Knoop, David Dubbeldam, David Fairen Jimenez, Jian Zhou*, Randall Q. Snurr*, Advanced Monte Carlo simulations of the adsorption of chiral alcohols in a homochiral metal-organic framework, AIChE Journal, 2014, 60(6), 2324.

 

 

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