1985年生于山西省忻州，康奈尔大学访问学者。围绕纳米粉末的设计与合成、能源转换电催化剂与二次电池材料、人工智能辅助材料设计、新型粉末冶金材料等国际前沿方向开展研究。共发表SCI论文90余篇，被引1600余次，h因子23。以第一作者、通讯作者在J Am Chem Soc、Adv Mater、Adv Energy Mater、Adv Funct Mater、ACS Nano、Energy Storage Mater、Scripta Mater等国际期刊发表30余篇，2篇ESI高倍引论文，3篇封面文章，单篇最高影响因子32.086，总被引用1876次，单篇最高引用243次。授权20余项发明专利，获得过2017年中国有色金属工业技术发明一等奖、北京科技大学优秀博士后、北京科技大学优秀博士论文、2022年第八届中国国际“互联网+”大学生创新创业大赛（北京赛区复赛）优秀指导教师等荣誉。
主持国家自然科学青年基金、北京市自然科学面上基金、北京市自然科学青年基金、中国博士后科学基金等9项课题，参与国家863计划、国家自然基金重点项目、国家重点研发计划等10余项国家级课题和企业横向课题。现为Angew. Chem. Int. Ed.、Adv. Energy Mater.、Adv Funct Mater、Nano-Micro Lett、Mater Sci Eng C、Int J Hydrogen Energ、Ceram Int等多个国际期刊的审稿人。指导学生获第七届中国国际“互联网+”大学生创新创业大赛银奖、2022年第八届中国国际“互联网+”大学生创新创业大赛北京赛区复赛产业命题赛道一等奖、二等奖。协助讲授研究生课程《先进陶瓷材料》，指导2021年本科生校级创新创业项目（SRTP），获2022年北京科技大学材料科学与工程学院优秀本科生导师称号。与剑桥大学、康奈尔大学、北京大学等国内外名校有良好合作关系。学生培养方面，尊重学生人格和个人兴趣，注重激发学生科研热情，培养学生良好科研习惯，鼓励学生树立科研志向、继续深造，教学相长，多名学生在学期间获得国家奖学金等奖励，毕业后在国内重点高校任教，欢迎报考硕士、博士学位的优秀学子邮件联系。
纳米粉末的设计和合成
电催化剂
离子电池与空气电池
粉末冶金
机器学习/人工智能辅助材料设计
部分第一/通讯作者论文
1. Yong Wang, Yongzhi Zhao, Luan Liu, Wanjun Qin, Sijia Liu, Juping Tu, Yadong Liu, Yunpu Qin, Jianfang Liu, Haoyang Wu, Deyin Zhang, Aimin Chu, Baorui Jia*, Xuanhui Qu, Mingli Qin*, Junmin Xue*. Facet Engineering and Pore Design Boost Dynamic Fe Exchange in Oxygen Evolution Catalysis to Break the Activity–Stability Trade-Off. Journal of the American Chemical Society, 2023.
2. Yongzhi Zhaoξ, Zili Zhangξ, Luan Liu, Yong Wang, Tong Wu, Wanjun Qin, Sijia Liu, Baorui Jia*, Haoyang Wu, Deyin Zhang, Xuanhui Qu, Genggeng Qi, Emmanuel P. Giannelis, Mingli Qin*, Shaojun Guo. S and O Co-Coordinated Mo Single Sites in Hierarchically Porous Tubes from Sulfur–Enamine Copolymerization for Oxygen Reduction and Evolution[J]. Journal of the American Chemical Society, 2022, 144(45): 20571-20581.
3. Yong Wang, Yongzhi Zhao, Luan Liu, Wanjun Qin, Sijia Liu, Juping Tu, Yunpu Qin, Jianfang Liu, Haoyang Wu, Deyin Zhang, Aimin Chu, Baorui Jia*, Xuanhui Qu, Mingli Qin*. Mesoporous single crystals with Fe-rich skin for ultra-low overpotential in oxygen evolution catalysis. Advanced Materials. 2022. DOI: 10.1002/adma.202200088
4. Yongzhi Zhaoξ, Haoyang Wuξ, Yong Wang, Luan Liu, Wanjun Qin, Sijia Liu, Jianfang Liu, Yunpu Qin, Deyin Zhang, Aimin Chu, Baorui Jia*, Xuanhui Qu, Mingli Qin*. Sulfur coordination engineering of molybdenum single-atom for dual-functional oxygen reduction/evolution catalysis[J]. Energy Storage Materials, 2022, 50: 186-195.
5. Luan Liu, Yan Wang, Yongzhi Zhao, Yong Wang, Zili Zhang, Tong Wu, Wanjun Qin, Sijia Liu, Baorui Jia*, Haoyang Wu, Deyin Zhang, Xuanhui Qu, Manish Chhowalla*, Mingli Qin*. Ultra-high Pt-mass-activity hydrogen evolution catalyst electrodeposited from bulk Pt. Advanced Functional Materials, 2022: 2112207.
6. Mingli Qin*, Shumei Li, Yongzhi Zhao, Cheng‐Yen Lao, Zili Zhang, Luan Liu, Fei Fang, Haoyang Wu, Baorui Jia*, Zhiwei Liu, Wei (Alex) Wang*, Ye Liu, Xuanhui Qu. Unprecedented synthesis of holey 2D layered double hydroxide nanomesh for enhanced oxygen evolution. Advanced Energy Materials. 2019, 9(1): 1803060.
7. Baorui Jia, Qiyao Yu, Yongzhi Zhao, Mingli Qin*, Wei Wang*, Zhiwei Liu, Cheng-Yen Lao, Ye Liu, Haoyang Wu, Zili Zhang, Xuanhui Qu. Bamboo-like hollow tubes with MoS2/N-doped-C interfaces boost potassium-ion storage. Advanced Functional Materials. 2018, 8: 3409-3418.
8. Mingli Qin*,ξ, Zili Zhangξ, Yongzhi Zhao, Luan Liu, Baorui Jia*, Kun Han, Haoyang Wu, Ye Liu, Lijun Wang, Xin Min, Kai Xi, Cheng‐Yen Lao, Wei (Alex) Wang*, Xuanhui Qu, Ramachandran Vasant Kumar. Optimization of von-Mises-stress distribution in mesoporous α-Fe2O3/C hollow bowls synergistically boosts gravimetric/volumetric capacity and high-rate stability in alkali-ion batteries. Advanced Functional Materials, 2019: 1902822.
9. Zili Zhangξ, Baorui Jiaξ, Luan Liu, Yongzhi Zhao, Haoyang Wu, Mingli Qin,* Kun Han, Wei Alex Wang,* Kai Xi, Lin Zhang, Genggeng Qi, Xuanhui Qu, Ramachandran Vasant Kumar. Hollow multihole carbon bowls: a stress-release structure design for high-stability and high-volumetric-capacity potassium ion batteries. ACS Nano, 2019, 13, 11363.
10. Luan Liu, Yongzhi Zhao, Yong Wang, Zili Zhang, Jia Liu, Tong Wu, Wanjun Qin, Sijia Liu, Baorui Jia*, Haoyang Wu, Deyin Zhang, Xuanhui Qu, Kai Xi, Mingli Qin*. Single-Atom Co Doped in Ultrathin WO3 Arrays for the Enhanced Hydrogen Evolution Reaction in a Wide pH Range[J]. ACS Applied Materials & Interfaces, 2021, 13(45): 53915-53924.
11. Xue Jiang*ξ, Yongzhi Zhaoξ, Jianfang Liuξ, Baorui Jia*, Xuanhui Qu, and Mingli Qin*. Machine Learning Captures Synthetic Intuitions for Hollow Nanostructures[J]. ACS Applied Nano Materials, 2022.
12. Xue Jiangξ, Yong Wangξ, Baorui Jia*, Xuanhui Qu, and Mingli Qin*. Using Machine Learning to Predict Oxygen Evolution Activity for Transition Metal Hydroxide Electrocatalysts[J]. ACS Applied Materials & Interfaces, 2022, 14(36): 41141-41148.
13. Baorui Jia, Yongzhi Zhao, Mingli Qin*, Wei Wang*, Zhiwei Liu, Cheng-Yen Lao, Qiyao Yu, Ye Liu, Haoyang Wu, Zili Zhang, Xuanhui Qu. Multirole organic-induced scalable synthesis of a mesoporous MoS2-monolayer/carbon composite for high-performance lithium and potassium storage. Journal of Materials Chemistry A. 2018, 6: 11147-11153.
14. Baorui Jia*, Mingli Qin*, Shumei Li, Zili Zhang, Huifeng Lu, Pengqi Chen, Haoyang Wu, Xin Lu, Lin Zhang, Xuanhui Qu. The synthesis of mesoporous single crystal Co(OH)2 nanoplate and its topotactic conversion to dual-pore mesoporous single crystal Co3O4. ACS Applied Materials & Interfaces, 2016, 8: 15582-15590.
15. Baorui Jia*, Mingli Qin*, ZiLi Zhang, Shumei Li, Deyin Zhang, Haoyang Wu, Lin Zhang, Xin Lu, Xuanhui Qu. Hollow porous VOx/C nanoscrolls as high-performance anodes for lithium-ion batteries. ACS Applied Materials & Interfaces, 2016, 8: 25954-25961.
16. Zili Zhang, Mingli Qin*, Baorui Jia*, Hongzhou Zhang, Xuanhui Qu. Facile synthesis of novel bowl-like hollow carbon spheres by combination of hydrothermal carbonization and soft templating. Chemical Communications, 2017.
17. Xue Jiangξ, Baorui Jiaξ, Guofei Zhang, Cong Zhang∗, Xin Wang, Ruijie Zhang∗, Haiqing Yin∗, Xuanhui Qu, Yong Song, Lan Su, Zhenli Mi, Lei Hu, Han Ma. A strategy combining machine learning and multiscale calculation to predict tensile strength for pearlitic steel wires with industrial data. Scripta Materialia, 2020, 186: 272-277.
