Peter M. Attia
Stanford University
29 Papers
80 Citations
Peter M. Attia is an academic researcher from Stanford University. The author has contributed to research in topics: Computer science & Battery (electricity). The author has an hindex of 13, co-authored 27 publications. Previous affiliations of Peter M. Attia include University of Delaware & Massachusetts Institute of Technology.
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Papers
Data-driven prediction of battery cycle life before capacity degradation
Kristen A. Severson,Peter M. Attia,Norman Jin,Nicholas Perkins,Benben Jiang,Zi Yang,Michael H. Chen,Muratahan Aykol,Patrick Herring,Dimitrios Fraggedakis,Martin Z. Bazant,Stephen J. Harris,Stephen J. Harris,William C. Chueh,Richard D. Braatz +14 more
TL;DR: In this article, a machine learning method was used to predict battery lifetime before the onset of capacity degradation with high accuracy. But, the prediction often cannot be made unless a battery has already degraded significantly.
Closed-loop optimization of fast-charging protocols for batteries with machine learning.
Peter M. Attia,Aditya Grover,Norman Jin,Kristen A. Severson,Todor M. Markov,Yang-Hung Liao,Michael H. Chen,Bryan Cheong,Nicholas Perkins,Zi Yang,Patrick Herring,Muratahan Aykol,Stephen J. Harris,Stephen J. Harris,Richard D. Braatz,Stefano Ermon,William C. Chueh,William C. Chueh +17 more
TL;DR: A closed-loop machine learning methodology of optimizing fast-charging protocols for lithium-ion batteries can identify high-lifetime charging protocols accurately and efficiently, considerably reducing the experimental time compared to simpler approaches.
Review—"Knees" in Lithium-Ion Battery Aging Trajectories
Peter M. Attia,Alexander Bills,Ferran Brosa Planella,Philipp Dechent,Gonccalo dos Reis,Matthieu Dubarry,Paul Gasper,Richard Gilchrist,Samuel Greenbank,David A. Howey,Ouyang Liu,Edwin Khoo,Yuliya Preger,Abhishek S. Soni,Shashank Sripad,Anna G. Stefanopoulou,Valentin Sulzer +16 more
TL;DR: In this article , the authors review prior work on knee degradation in lithium-ion battery aging trajectories and identify key design and usage sensitivities for knees, and discuss challenges and opportunities for knee modeling and prediction.
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Evolution of the Solid–Electrolyte Interphase on Carbonaceous Anodes Visualized by Atomic-Resolution Cryogenic Electron Microscopy
William Huang,Peter M. Attia,Hansen Wang,Sara E. Renfrew,Sara E. Renfrew,Norman Jin,Supratim Das,Zewen Zhang,David T. Boyle,Yuzhang Li,Martin Z. Bazant,Bryan D. McCloskey,Bryan D. McCloskey,William C. Chueh,William C. Chueh,Yi Cui,Yi Cui +16 more
TL;DR: This work image the SEI on carbon black negative electrodes using cryogenic transmission electron microscopy (cryo-TEM) and track its evolution during cycling, finding that a thin, primarily amorphous SEI nucleates on the first cycle, which further evolves into one of two distinct SEI morphologies upon further cycling.
Fluid-enhanced surface diffusion controls intraparticle phase transformations
Yiyang Li,Yiyang Li,Yiyang Li,Hungru Chen,Kipil Lim,Kipil Lim,Haitao D. Deng,Jongwoo Lim,Jongwoo Lim,Dimitrios Fraggedakis,Peter M. Attia,Sang Chul Lee,Norman Jin,Jože Moškon,Zixuan Guan,William E. Gent,Jihyun Hong,Jihyun Hong,Young-Sang Yu,Miran Gaberšček,M. Saiful Islam,Martin Z. Bazant,William C. Chueh,William C. Chueh +23 more
TL;DR: It is shown that lithium migrates along the solid/liquid interface without leaving the particle, whereby charge carriers do not cross the double layer, and establishes fluid-enhanced surface diffusion as a key dial for tuning phase transformation in anisotropic solids.
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