Qiangfeng Xiao | Energy conversion | Best Researcher Award

Prof Dr. Qiangfeng Xiao | Energy conversion | Best Researcher Award

Professor at Tongji University, China

Dr. Qiangfeng Xiao is a professor at Tongji University, China, with extensive experience in energy storage and conversion materials. He earned his Ph.D. in Chemical Engineering from UCLA in 2010 and has over 50 peer-reviewed publications, 10 patents, and 18 pending patents. Prior to Tongji, he worked at GM’s R&D Center, focusing on lithium-ion and fuel cell technologies. His research includes high-energy Li metal batteries, solid-state electrolytes, and advanced anodes and cathodes. Dr. Xiao is also a reviewer for top journals and a member of several professional societies, recognized for his innovation and contributions to the field.

Professional Profiles

Education

Ph.D. in Chemical Engineering, University of California, Los Angeles (UCLA), 2010. M.S. in Materials Science, Tsinghua University, Beijing, China, 2003. B.S. in Chemical Engineering, Qingdao University, Qingdao, China, 2000

Professional Experience

1. Tongji University, Professor (2018-Present) Leading projects on high-energy Li metal batteries, solid-state electrolytes, and advanced anodes and cathodes. 2. General Motors (GM) Team Leader, Cross-lab Collaboration (2017) Developed high-performance, lightweight surface coatings and vibration dampers for vehicle body panels and battery packs. Senior Researcher, Global Propulsion System (2017-2018) Conducted postmortem analysis of EV battery failures. Before his tenure at Tongji University, Dr. Xiao worked at the General Motors (GM) Research & Development Center for 8 years. Energy conversion

Qualifications

US permanent resident Extensive industrial experience in R&D, particularly in the development of lithium-ion batteries and fuel cells Expertise in the design and hands-on fabrication of 1Ah pouch cells Postmortem analysis of EV batteries In-situ characterization techniques for lithium-ion batteries, including In-situ XRD, TEM, and DEMS Development of technology roadmaps for EV batteries Experience in developing high-energy batteries (500 Wh/kg) Comprehensive knowledge of the industrial process of lithium-ion battery development and production Deep understanding of cell design and chemistry Proficiency in battery pack structure and analysis of cell state within packs Skilled in drafting and securing patent applications Experience in funding application and management Highly self-motivated and innovative. Energy conversion

Research Interests

Dr. Xiao’s research focuses on the design and synthesis of materials for energy storage and conversion applications. His significant contributions include: High-energy rechargeable Li metal 500 Wh/kg batteries F-containing electrolytes for Li anode Sulfides, Garnets, polymers, and their composite-based solid-state electrolytes High-capacity, long-life Si anodes Li-rich manganese-based cathodes Ni-rich single crystal cathodes High-power liquid fuel cells. Energy conversion

Research Focuse

Dr. Qiangfeng Xiao’s research primarily focuses on advanced materials for energy storage and conversion technologies. His work spans the design and synthesis of hierarchical nanowire composites, graphene-based ultrafast charge-discharge cathodes, and high-energy density lithium-ion supercapacitors. He has contributed significantly to the development of silicon and graphene-based anodes, as well as innovative coatings for lithium metal anodes. Dr. Xiao also explores biomimetic ionic channels in metal-organic frameworks for lithium-ion electrolytes and regenerative polysulfide-scavenging layers for lithium-sulfur batteries. His research innovations consistently aim at enhancing energy storage capacity, improving cycling life, and advancing materials for next-generation batteries and supercapacitors. Energy conversion

Publications

  1. In-situ Construction of Polyelectrolyte/Polyzwitterion Coacervate Framework for High-Performance Silicon Anodes, Publication date: 2024.
  2. High-voltage ether-based electrolytes for lithium metal batteries via synergy between the solvent and additive, Publication date: 2024.
  3. Boosting borohydride oxidation kinetics by manipulating hydrogen evolution and oxidation through octahedral Pt-Ni/C for high-performance direct borohydride fuel cells, Publication date: 2024.
  4. Investigation of non-precious metal cathode catalysts for direct borohydride fuel cells, Publication date: 2024.
  5. High-performance precious metal-free direct ammonia fuel cells endowed by Co-doped Ni4Cu1 anode catalysts, Publication date: 2023.
  6. Regulating cathode‐electrolyte interphase by confining functional aluminum compound within Ni‐rich cathodes,Publication date: 2023.
  7. High-performance zinc-air batteries enabled by hybridizing atomically dispersed FeN2 with Co3O4 nanoparticles, Publication date: 2023.
  8. Optimization of the cathode catalyst layer for boosting direct ammonia fuel cell performance by orthogonal tests, Publication date: 2023.
  9. Recent Progress on Nanomodification Applied in Anodes of Rechargeable Li Metal Batteries, Publication date: 2023.
  10. Prefabrication of a Lithium Fluoride Interfacial Layer to Enable Dendrite-Free Lithium Deposition, Publication date: 2023.
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Xu Xu | AI Energy Science | Best Researcher Award

Assist Prof Dr. Xu Xu | AI Energy Science | Best Researcher Award

PHD at Hong Kong Polytechnic University, China

Xu Xu is an Assistant Professor at Xi’an Jiaotong-Liverpool University’s Department of Electrical and Electronic Engineering, School of Advanced Technology. With a PhD from Hong Kong Polytechnic University, his expertise lies in power system optimization, renewable energy integration, and the application of artificial intelligence in smart grids. Xu has garnered recognition for his work, including awards like Best Oral Presentation at the 3rd International Conference on Power and Electrical Engineering. He actively contributes to academic service, serving on committees such as the IEEE IAS Industrial and Commercial Power System Asia Technical Program Committee.

Professional Profiles

Education

Hong Kong Polytechnic University Hong Kong SAR PhD in Electrical Engineering 2016/09-2019/09

Work Experience

Xi’an Jiaotong-Liverpool University Suzhou, China Assistant Professor in Department of Electrical and Electronic Engineering, School of Advanced Technology 2022/04-Present Nanyang Technological University Singapore Research Fellow in Rolls-Royce@NTU Corporate Laboratory with School of Electrical and Electronic Engineering 2021/01-2022/02 University of Hong Kong Hong Kong SAR Research Assistant I in Department of Electrical and Electronic Engineering 2020/09-2020/12 Hong Kong Polytechnic University Hong Kong SAR Postdoctoral Fellow in Department of Electrical Engineering 2019/10-2020/09

Research Interests

Power system optimization, Renewable energy generation and integration, Application of artificial intelligence in smart grids.

Academic Services

Technical Program Committee Member, 2021 IEEE IAS Industrial and Commercial Power System Asia Technical Program Committee, Session Chair in Topic of Power System Planning, 2020 IEEE IAS Industrial and Commercial Power System Asia Technical Program Committee

Research Focus

Xu Xu’s research focuses on advancing home energy management through innovative methods such as multi-agent reinforcement learning. His work, published in prestigious journals like IEEE Transactions on Smart Grid and Applied Energy, explores optimizing photovoltaic hosting capacity and integrating renewable energy sources into distribution networks. Additionally, he investigates game-theoretic approaches for residential PV panel planning and develops data-driven strategies for electricity trading and energy sharing mechanisms in residential clusters. Xu Xu’s interdisciplinary approach combines expertise in electrical engineering, renewable energy, and artificial intelligence to address challenges in sustainable energy systems, making significant contributions to the field of smart grids and energy management.

Publications

  1. Data-driven assisted real-time optimal control strategy of submerged arc furnace via intelligent energy terminals considering large-scale renewable energy utilization, Publication date: 2024.
  2. Cooperative multi-agent deep reinforcement learning based decentralized framework for dynamic renewable hosting capacity assessment in distribution grids, Publication date: 2023.
  3. Generative adversarial network assisted stochastic photovoltaic system planning considering coordinated multi-timescale volt-var optimization in distribution gridsPublication date: 2023.
  4. Robust proactive power smoothing control of PV systems based on deep reinforcement learning, Publication date: 2023.
  5. Autonomous input voltage sharing control and triple phase shift modulation method for ISOP-DAB converter in DC microgrid: A multiagent deep reinforcement learning-based method. Publication date: 2022.
  6. Coordinated current and voltage unbalance mitigation in networked microgrids with aggregated PV systemsPublication date: 2022.
  7. Collaborative Control Framework of Multiple Electric Springs for Frequency Stabilization and Distribution Loss Reduction in Microgrids, Publication date: 2022.
  8. Adaptive Distributed Graph Model for Multiple-Line Outage Identification in Large-Scale Power SystemPublication date: 2022.
  9. Optimal Unified Power Flow Controller Planning in Transmission Grids with Uncertainty Consideration, Publication date: 2020.
  10. Data-driven-based dynamic pricing method for sharing rooftop photovoltaic energy in a single apartment building, Publication date: 2020.
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