Richard D. Braatz

Massachusetts Institute of Technology (MIT)

SCHOLARLY PAPERS

4

DOWNLOADS

268

TOTAL CITATIONS

1

Scholarly Papers (4)

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1.

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 (562,508)

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

2.

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 83 (590,903)

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

3.

Developing Ultra-High Concentration Formulations of Human Immune Globulins Through Spray Drying and Suspension Formation

Number of pages: 36 Posted: 22 May 2024
Jayprakash Yadav, Francesco Civati, Shihab Uddin, Wenchuan Ma, Andreas Liebminger, Wolfgang Teschner, Guillaume André, Bernhardt L. Trout, Richard D. Braatz and Allan S. Myerson
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Massachusetts Institute of Technology (MIT) and affiliation not provided to SSRN
Downloads 60 (700,583)

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Spray drying, immune globulins, formulation, viscosity, rheology

4.

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

Downloads 35 (870,197)
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 20 (1,047,533)
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 15 (1,107,309)

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