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Xuning Feng

University of Michigan–Ann Arbor · US
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Area of research
Automotive Engineering · Electrical and Electronic Engineering
Research interest
Research focused on Thermal runaway and Battery (electricity), with related work in Electrolyte, Reliability (semiconductor), SAFER. Notable publications include 'The Application of Data-Driven Methods and Physics-Based Learning for Improving Battery Safety', 'Investigating the thermal runaway features of lithium-ion batteries using a thermal resistance network model', and 'A reliable approach of differentiating discrete sampled-data for battery diagnosis'.
h-index
citations
666
works
10
NIH funding
primary concept
email

Recent publications

Fast-charging lithium-ion batteries require a systems engineering approach
Nature Energy 2025cited by 16position: middledoi
In Situ Fabricated Non‐Flammable Gel Polymer Electrolyte with Stable Interfacial Compatibility for Safer Lithium‐ion Batteries
Small 2025cited by 8position: middledoi
A novel self-adaptive microcapsule mitigating the thermal runaway hazards of lithium-ion batteries
Journal of Energy Storage 2025cited by 6position: middledoi
Explosion limits of binary mixtures of ammonia and additives (hydrogen, natural gas, and diethyl ether)
Fuel 2024cited by 16position: middledoi
Electrolyte induced synergistic construction of cathode electrolyte interphase and capture of reactive free radicals for safer high energy density lithium-ion battery
Journal of Energy Chemistry 2023cited by 35position: middledoi
Thermal runaway modeling of LiNi0.6Mn0.2Co0.2O2/graphite batteries under different states of charge
Journal of Energy Storage 2022cited by 59position: middledoi
Investigating the thermal runaway features of lithium-ion batteries using a thermal resistance network model
Applied Energy 2021cited by 104position: middledoi
Dimensionless normalized concentration based thermal-electric regression model for the thermal runaway of lithium-ion batteries
Journal of Power Sources 2021cited by 39position: lastdoi
The Application of Data-Driven Methods and Physics-Based Learning for Improving Battery Safety
Joule 2020cited by 285position: middledoi
A reliable approach of differentiating discrete sampled-data for battery diagnosis
eTransportation 2020cited by 98position: firstdoi

Grants

No grants ingested yet.

Frequent collaborators

Minggao Ouyang · Tsinghua University6 papers (2020–2025)Li Wang · Chongqing University of Posts and Telecommunications5 papers (2020–2025)Hungjen Hsu · Tsinghua University3 papers (2021–2022)Dongsheng Ren · Tsinghua University3 papers (2020–2022)Xiangming He · Jinan University3 papers (2020–2022)Jie Chen · Tsinghua University3 papers (2021–2022)Jingjing Tong · University of South Carolina2 papers (2023–2025)Xinyu Rui · Tsinghua University2 papers (2021–2022)Yong Peng · Nanchang University2 papers (2023–2025) · 2 papers (2023–2025) · 2 papers (2020–2025)Changyong Jin · Shanghai University2 papers (2020–2021)Bowen Hou · Shihezi University2 papers (2023–2025)Languang Lu · Tsinghua University2 papers (2020–2022)Shichao Zhang · Zhejiang University2 papers (2023–2025)Mengfei Ding · Shandong University2 papers (2023–2025)Chengshan Xu · Tsinghua University2 papers (2021–2025)Caiping Zhang · Guangzhou University of Chinese Medicine2 papers (2021–2022)Jie Liu · Princeton University1 papers (2024–2024)Lu Zhang · Shenyang Medical College1 papers (2024–2024)
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