AI
Lithium / Sodium
Cathode / Anode
Solid-State
Scale-up
I'm a Research Scientist, Explorer, and Experiencer who aspires to become an Inspirer. My work lies at the intersection of battery materials, clean energy, artificial intelligence, and human-centered innovation.
Driven by the conviction that technology should harmonize ecological balance with individual empowerment, I focus on accelerating the clean energy transition through next-generation battery materials, scalable manufacturing, and AI-enabled energy systems. I bridge fundamental research and industrial implementation by integrating electrochemistry, materials engineering, process development, and data-driven methods.
Building on my experience in battery R&D and industrialization, I am actively advancing AI + Manufacturing and AI + BMS applications—including intelligent process optimization, battery-state estimation such as SOC and SOH, AI model robustness, and battery-system security. This multidisciplinary direction allows me to connect physical battery systems with trustworthy, intelligent decision-making.
University of North Dakota, Grand Forks, ND
May 2023
Guizhou University, Guiyang, China
June 2017
Qingdao University of Science and Technology, Qingdao, China
June 2013
What I’m known for: converting R&D into reproducible, inspectable processes and defensible IP — while leading cross-functional teams across academia and industry.
Coordinated multi-partner roadmaps and helped secure major grants (DOE + state) for battery materials and long-duration storage programs.
Hands-on experience with manufacturing workflows: mixing → coating → drying → calendaring → assembly → formation → testing, plus QC and certification support.
Authored patents and technical reports; recognized for IP strategy and core technology breakthroughs.
Established hands-on capabilities and active development areas are identified separately below.
Glove boxes, grinders, mixers, tube/box/muffle furnaces, jet mills, spray dryers, magnetic separators, compressors, nitrogen generators; slurry prep, coating, drying, calendaring, cutting, ultrasonic/spot/laser welding, electrolyte injection, formation, grading and testing.
Raman, XRD/XRF, SEM/TEM/EDS, XANES, XPS; COMSOL, Aspen Plus, Ansys Fluent, Vensim; Python/MATLAB/C; data analysis with OriginLab/Minitab/MySQL/SPSS.
Currently expanding into AI-enabled battery manufacturing and intelligent battery management through active research projects. Key areas include battery-state estimation, adversarial robustness and security for AI-enabled BMS, data-driven process optimization, and HPC-enabled battery-material manufacturing.
Clean Republic SODO LLC • Grand Forks / Seattle • US
CEM Energy Studies • University of North Dakota • US
Applied electrochemical and process modeling to energy research programs and industry collaborations.
Institute for Energy Studies • University of North Dakota • US
Research on silicon/carbon composite anodes, electrode engineering, and materials characterization.
Clean Republic LLC • ND • US
Sep 2018 – Nov 2020
MICPOWER • China
Apr 2018 – Aug 2018
LFP and NFPP-based cathodes: reproducible synthesis, impurity control, particle engineering, and QC for manufacturing.
From cell to module/system validation: field demonstrations, manufacturing feedback loops, and performance/safety optimization.
Polymer composite solid-state electrolyte materials and manufacturability, including interface considerations and scale-up constraints.
U.S. DOE Genesis Mission (DE-FOA-0003612) • Co-PI
U.S. DOE HPC4EI • PI
DOE-EERE • Co-PI
ND CSEA • Co-PI
Dakota Lithium + SDSMT • Co-PI
Dakota Lithium + MSE, Sci. & Tech.
Selected battery, AI/BMS, and energy-systems work from the August 2026 CV. Citation counts are synchronized with the public Google Scholar profile.
Xin Zhang, Yong Hou.
U.S. Patent Application (2025).
Xin Zhang, et al.
ACS Applied Energy Materials, 2023, 6, 7996–8005.
Xin Zhang, et al.
Electrochimica Acta, 2022, 141329.
B. Ye, Xin Zhang, et al.
Energy Sources, Part B: Economics, Planning, and Policy, 2025, 20(1), 2530518.
M. Lei, Xin Zhang, et al.
2026, under review.
M. Lei, Xin Zhang, et al.
2026, under review.
M. Lei, Xin Zhang, et al.
2026, under review.
M. Lei, Xin Zhang, et al.
ISICN, San Juan, Puerto Rico, USA (2025).
A small collection of tools, games, and digital experiments I’ve built.
Classic tile-based game — form sets, swap tiles, and be the first to empty your rack.
Be the last player to move a token such that only one stack remains.
Generate accessible, publication-ready palettes for scientific visualization.
I’m always working on new ideas — check back later.
For collaborations, consulting, speaking, or hiring conversations — email is best.