Martin Z. Bazant

Massachusetts Institute of Technology (MIT) - Department of Chemical Engineering

77 Massachusetts Avenue, Room 66-350

Cambridge, MA 02139

United States

  • Massachusetts Institute of Technology (MIT) - Department of Chemical Engineering

SCHOLARLY PAPERS

5

DOWNLOADS

527

TOTAL CITATIONS

4

Scholarly Papers (5)

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1.

Large-Deformation Plasticity and Fracture Behavior of Pure Lithium Under Various Stress States

Number of pages: 38 Posted: 11 Nov 2020
Tobias Sedlatschek, Junhe Lian, Wei Li, Menglei Jiang, Tomasz Wierzbicki, Martin Z. Bazant and Juner Zhu
Department of Mechanical Engineering, Massachusetts Institute of Technology, Aalto University - Advanced Manufacturing and Materials, Massachusetts Institute of Technology (MIT) - Department of Mechanical Engineering, Department of Materials Science and Engineering, Massachusetts Institute of Technology, Department of Mechanical Engineering, Massachusetts Institute of Technology, Massachusetts Institute of Technology (MIT) - Department of Chemical Engineering and Massachusetts Institute of Technology (MIT) - Department of Mechanical Engineering
Downloads 261 (235,157)
Citation 3

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Pure lithium, Lithium-metal battery, Mechanical properties, microstructure, Plasticity, Fracture

2.

Nonlinear Local Identifiability Analysis of Multiphase Porous Electrode Theory-Based Battery Models: A Lithium Iron Phosphate Case Study

Number of pages: 15 Posted: 24 Jan 2023
Giacomo Galuppini, Marc D. Berliner, Daniel A. Cogswell, Debbie Zhuang, Martin Z. Bazant and Richard D. Braatz
Massachusetts Institute of Technology (MIT), affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Massachusetts Institute of Technology (MIT) - Department of Chemical Engineering and Massachusetts Institute of Technology (MIT)
Downloads 90 (569,057)

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Lithium-ion batteries, Lithium Iron Phosphate, Multiphase Porous Electrode Theory, parameter estimation, Identifiability Analysis

3.

Efficient Computation of Safe, Fast Charging Protocols for Multiphase Lithium-Ion Batteries: A Lithium Iron Phosphate Case Study

Number of pages: 16 Posted: 18 Mar 2023
Giacomo Galuppini, Marc D. Berliner, Huada Lian, Debbie Zhuang, Martin Z. Bazant and Richard D. Braatz
Massachusetts Institute of Technology (MIT), affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Massachusetts Institute of Technology (MIT) - Department of Chemical Engineering and Massachusetts Institute of Technology (MIT)
Downloads 86 (585,188)

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lithium-ion batteries, Lithium Iron Phosphate, Multiphase Porous Electrode Theory, Fast charging, Charging Protocols, Optimal Control

4.

Application of Finite Gaussian Process Distribution of Relaxation Times on Sofc Electrodes

Number of pages: 24 Posted: 29 Jan 2023
Nicholas J. Williams, Conor Osborne, Ieuan Seymour, Martin Z. Bazant and Stephen Skinner
Imperial College London, affiliation not provided to SSRN, Imperial College London, Massachusetts Institute of Technology (MIT) - Department of Chemical Engineering and Imperial College London
Downloads 53 (750,065)

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Gaussian process, Inverse problem, DRT, EIS, SOFC

5.

Improving Diagnostics and Prognostics of Implantable Cardioverter Defibrillator Batteries with Interpretable Machine Learning Models

Downloads 37 (864,768)
Citation 1

Improving Diagnostics and Prognostics of Implantable Cardioverter Defibrillator Batteries with Interpretable Machine Learning Models

Number of pages: 20 Posted: 25 Mar 2024
Giacomo Galuppini, Qiaohao Liang, Prabhakar A. Tamirisa, Jeffrey A. Lemmerman, Melani G. Sullivan, Michael J. M. Mazack, Partha M. Gomadam, Martin Z. Bazant and Richard D. Braatz
Massachusetts Institute of Technology (MIT), Massachusetts Institute of Technology (MIT), Medtronic (Minneapolis), Medtronic (Minneapolis), Medtronic (Minneapolis), Medtronic (Minneapolis), Medtronic (Minneapolis), Massachusetts Institute of Technology (MIT) - Department of Chemical Engineering and Massachusetts Institute of Technology (MIT)
Downloads 21 (1,051,131)
Citation 1

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Batteries, Defibrillators, Machine Learning, Generalized Additive Models, Diagnostics, Prognostics.

Improving Diagnostics and Prognostics of Implantable Cardioverter Defibrillator Batteries with Interpretable Machine Learning Models

Number of pages: 19 Posted: 22 Jan 2024
Giacomo Galuppini, Qiaohao Liang, Prabhakar A. Tamirisa, Jeffrey A. Lemmerman, Melani G. Sullivan, Michael J. M. Mazack, Partha M. Gomadam, Martin Z. Bazant and Richard D. Braatz
Massachusetts Institute of Technology (MIT), Massachusetts Institute of Technology (MIT), Medtronic (Minneapolis), Medtronic (Minneapolis), Medtronic (Minneapolis), Medtronic (Minneapolis), Medtronic (Minneapolis), Massachusetts Institute of Technology (MIT) - Department of Chemical Engineering and Massachusetts Institute of Technology (MIT)
Downloads 16 (1,111,876)

Abstract:

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Batteries, Defibrillators, Machine learning, Generalized Additive Models, Diagnostics, Prognostics