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Massachusetts Institute of Technology

Physical Models and Statistical Methods for Understanding Electrochemical Kinetics

Abstract

dc:description.abstract

Decarbonization of the global economy in order to limit rapid global surface temperature growth is a critical industrial and societal challenge for the next several decades. Yet, several sectors of the economy remain stubbornly difficult to decarbonize, such as commodity chemicals production, cement and steel manufacturing, and synthetic fertilizer synthesis, to name only a few. Emerging efforts to decarbonize these processes rely on electrochemical techniques, which use emissions-free sources of electricity to drive relevant chemical reactions. Much remains to be understood about the fundamentals of electrochemical kinetics, hampering efforts to rationally engineer decarbonized electrochemical processes. This thesis develops new physical models and applies rigorous statistical methods towards developing a more complete understanding of electrochemical kinetics. The physical models I develop are grounded in the framework of classical statistical mechanics. In Chapter 2, I develop an extension to the classical Marcus kinetic theory of electron transfer that accounts for diffusive transport effects in the electrochemical double layer. In Chapter 3, I advance a simple physical explanation for why the reorganization energy, a key parameter in Marcus theory, exhibits marked attenuation upon approach to a constant potential electrode surface. Finally, in Chapter 4, I apply molecular dynamics simulations of the electrochemical double layer (EDL) to evaluate the fidelity of continuum theoretical predictions of electrostatic potential variation in the EDL. The statistical methods I report in this thesis leverage relatively straightforward mathematical approaches to modernize classical electrochemical analyses. In Chapter 5, I show how applying a Bayesian analysis technique to Tafel slope analysis can correct subjective human biases in literature-reported analyses of CO2 electroreduction data. Finally, in Chapter 6, I develop a new electrochemical analysis technique based on analysis of weakly nonlinear current response to a medium-amplitude oscillating voltage signal, which can serve as a complementary technique to cyclic voltammetry, a more traditional approach to electrochemical characterization.

Degree

thesis:*
Name thesis:degree_name
Doctoral
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Chemical Engineering
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Limaye, Aditya Madan
Advisor dc:contributor.advisor
  • Willard, Adam P.

Rights

dc:rights
Statement dc:rights
  • In Copyright - Educational Use Permitted
  • Copyright MIT

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/144690
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/144690

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Limaye, Aditya Madan. Physical Models and Statistical Methods for Understanding Electrochemical Kinetics. Massachusetts Institute of Technology, 2022. https://hdl.handle.net/1721.1/144690