About

Martin Z. Bazant is the Chevron Professor in Chemical Engineering, Mathematics, and Digital Learning Officer at MIT. His research focuses on chemical engineering, with particular emphasis on the mathematical and computational aspects of the field. As a faculty member, he contributes to the department's mission through his expertise in energy, environment and sustainability, and materials. His role involves advancing understanding in these areas and integrating digital learning into chemical engineering education.

Research topics

• Artificial Intelligence
• Computer Science
• Engineering
• Machine Learning
• Chemistry
• Reliability engineering
• Physical chemistry
• Business
• Materials science
• Nanotechnology
• Physics
• Waste management
• Environmental science
• Political Science
• Metallurgy
• Algorithm
• Environmental economics
• Telecommunications
• Systems engineering
• Structural engineering
• Chemical physics
• Process engineering
• Organic chemistry
• Geometry

Selected publications

• Thermodynamically consistent continuum theory of magnetic particles in high-gradient fields

  Physical Review Fluids · 2026-04-10

  articleOpen access

  Magnetic particles underpin a broad range of technologies, from water purification and mineral processing to bioseparations and targeted drug delivery. The dynamics of magnetic particles in high-gradient magnetic fields—encompassing both their transport and eventual capture—arise from the coupled interplay of field-driven drift, fluid advection, and particle-field feedback. These processes remain poorly captured by existing models relying on empirical closures or discrete particle tracking. Here we present a thermodynamically consistent continuum theory for collective magnetic particle transport and capture in high-gradient fields. The framework derives from a free-energy functional that couples magnetic energy, entropic mixing, and steric interactions, yielding a concentration-dependent susceptibility via homogenization theory. The resulting equations unify magnetism, mass transport, and momentum balances without shut-off criteria, allowing field shielding, anisotropic deposition, and boundary-layer confinement to emerge naturally. Simulations predict canonical capture morphologies—axially aligned plumes, crescent-shaped deposits, and nonlinear shielding—across field strengths and flow regimes, consistent with trends reported in prior experimental and modeling studies. By organizing captured particle mass data into a dimensionless phase diagram based on the Mason number, we reveal three distinct regimes—thermodynamically controlled, transitional, and dynamically controlled. This perspective provides a predictive platform for optimization and extension to 3D geometries, and informing digital twin development for industrial-scale high-gradient magnetic separation processes.

  PublisherDOI

• Author response for "Battery Aging Assessment: From Critical Insights to Enhanced Diagnosis"

  2026-01-20

  peer-review
  PublisherDOI

• Uncovering Electrolyte Transport Mechanisms in Charged MXene Membranes via Continuum Modeling

  ECS Meeting Abstracts · 2025-11-24

  articleSenior author

  MXenes are an emerging class of 2D sheet-like nanomaterials. While analogous to the more well-known graphene , what sets them apart is their unique blend of enhanced stability in aqueous media, near-metallic in-plane electrical conductivity, as well as their ability to sustain a surface charge. Membranes composed of layers of MXenes are, thus, promising candidates for next-generation water purification technologies, with the potential for electrostatically tunable ion transport and separation. Recent experiments by our collaborators confirm that applying a gate voltage to a MXene membrane modulates the resulting transport of electrolytes. Specifically, in a diffusion-driven system, they observe that negative gate voltages lead to lower, saturating ion permeation rates, while positive gate voltages result in higher, increasing permeation rates—a behavior reminiscent of transistors. Additional experiments of the membrane in a pressure-driven system also show that the gate voltage can significantly modulate the magnitude of streaming current. While prior studies on layered 2D-nanomaterial membranes offer qualitative explanations for such phenomena via experiments, a robust, quantitative description grounded in theory continues to remain underdeveloped. To address this gap, we construct a physics-based model of the membrane, capable of accurately predicting its response to an applied gate voltage. Despite the presence of ultrathin nanopores, we adopt a continuum modeling approach, leveraging its unique ability to provide deep physical insights and enable rapid parametric studies. Building on the theory of electrokinetics in nanopores, our work provides the first quantitative look into the physical mechanisms underpinning electrolyte transport in MXene membranes. Figure 1

  PublisherDOI

• Unveiling the Morphological Evolution of Li ₂ O ₂ in Li-O ₂ batteries: A Coupled Ion-Electron Transfer (CIET) Based Phase-Field Study

  ECS Meeting Abstracts · 2025-11-24

  article

  Lithium-oxygen batteries (Li-O 2 ) present a compelling prospect for the next generation of batteries owing to their exceptionally high theoretical energy density. [1] However, the current-dependent morphology of Li 2 O 2 has emerged as a primary factor contributing to energy density limitations in Li-O 2 batteries. [2-3] Existing mathematical models grounded in Butler-Volmer kinetics exhibit considerable uncertainties and inaccuracies. [4-5] A more in-depth understanding of the Li 2 O 2 formation process is critical to address the prevailing challenges in Li-O 2 battery technology. In this work, we incorporate recently developed Coupled Ion-Electron Transfer (CIET) theory [6] with a phase-field model to describe the voltage profiles, morphological evolutions, and roles of solvation energy of Li 2 O 2 formation. The CIET-based model provided improved predictions of both voltage profiles and growth patterns compared to BV kinetics, in good agreement with experimental observations. Importantly, our models, for the first time, captures a periodic nucleation-merging-nucleation growing behavior, which is further confirmed by SEM analysis. Furthermore, we identified that increasing solvation reorganization energy can shift the thin-film morphology to higher current densities, enabling enhanced capacity under high-rate conditions. The consistency between model predictions and experimental results validates our approach. This study offers new insights onto the Li 2 O 2 formation mechanism and provides guidance for future Li-O 2 battery design. [1] Bruce, P. G., Freunberger, S. A., Hardwick, L. J., & Tarascon, J.-M. (2012). Nucleation and growth of lithium peroxide in the Li-O2 battery. Nature Materials, 11, 19–29. [2] Read, J. (2002). Characterization of the Lithium/Oxygen Organic Electrolyte Battery. Journal of Electrochemical Society, 149, A1190–A1195. [3] Kraytsberg, A., & Ein-Eli, Y. (2011). Review on Li-air batteries - Opportunities, limitations and perspective. Journal of Power Sources, 196, 886–893. [4] Lau, S., & Archer, L. A. (2015). Nucleation and growth of lithium peroxide in the Li-O 2 battery. Nano Letters, 15(9), 6108–6114. [5] Horstmann, B., Gallant, B., Mitchell, R., Bessler, W. G., Shao-Horn, Y., & Bazant, M. Z. (2013). Rate-dependent morphology of Li2O2 growth in Li-O2 batteries. Journal of Physical Chemistry Letters, 4(24), 4227–4232. [6] Fraggedakis, D.; McEldrew, M.; Smith, R.; Krishnan, Y.; Zhang, Y.; Bai, P.; Chueh, W.; Shao-Horn, Y.; Bazant, M. Z. Theory of Coupled Ion-Electron Transfer Kinetics. J. Chem. Phys. 2020 , 152 , 184703.

  PublisherDOI

• Mechanically induced thermal runaway severity analysis of Li-ion batteries and continuous energy release monitoring

  Journal of Energy Storage · 2025-08-15 · 1 citations

  article
  PublisherDOI

• Crossover Dynamics of Non-Fickian Ionic Diffusion in Solids

  ArXiv.org · 2025-12-14

  preprintOpen access

  Ionic diffusion in solids is central to energy storage, electronics, and catalysis, yet its chemical origins are difficult to resolve because conventional diffusion models struggle with effects of confinement, crystallographic disorder, lattice distortions, and coupling to electronic or phononic carriers. These challenges are especially pronounced in battery materials, where ionic and electronic motion occur together, complicating interpretation of electrochemical measurements. Here we use tracer exchange as a direct, non-electrochemical probe to reveal distinct ion-transport regimes in the one-dimensional conductor olivine Li_xFePO4 (0 <= x <= 1). Lithium isotope exchange validates single-file diffusion governed by strong ion-ion correlations, where 1D confinement suppresses bypassing and preserves spatial order. Kinetic Monte Carlo simulations and chronoamperometry quantify both Faradaic and non-Faradaic surface exchange, identifying electron transport, rather than Li+ mobility, as the rate-limiting step for electrochemical reaction. In addition, Li-Na exchange exhibits apparent superdiffusion, with rates that increase with Na content. Simulations attribute this behavior to surface-exchange limitations and Na-induced lattice strain that enhances cross-channel Li+ hopping and drives a crossover from 1D to quasi-2D transport. Four-dimensional STEM, in situ synchrotron XRD, X-ray absorption spectroscopy, and Mossbauer spectroscopy confirm that lattice softening and concerted polaron motion contribute to the observed dynamics. These results establish tracer exchange as a powerful tool for probing coupled ion-electron transport and provide chemical insight into how lattice mechanics and multicomponent exchange shape ionic diffusion in solids.

  PublisherOA PDFDOI

• Hierarchical Transmission Line Model (TLM): Impedance of Porous Electrodes Composed of Secondary-Particles

  ECS Meeting Abstracts · 2025-07-11

  articleSenior author

  Tuning the microstructure of porous electrodes is essential for optimizing battery rate capability and cycle life. These electrodes often feature hierarchical structures, where they consist of µm-scale secondary agglomerate particles, which are in turn composed of nm-scale primary particles of the active material, binder, and additives 1 . Multiscale porous electrode models can infer structural and electrochemical properties of the electrodes from impedance measurements, providing a guide rooted in fundamental transport and kinetics 2–4 . Most models are empirical and only at the electrode scale, overlooking species and charge losses within the particles. Hierarchical effects are often approximated using constant phase elements (CPEs) 5,6 . This leads to flawed inference of key electrode parameters from impedance measurements, misinforming microstructure design. While a few studies address the underlying physics more rigorously, such as Huang et al. ’s porous agglomerate transport-reaction model for lithium cobalt oxide (LCO) and lithium nickel manganese cobalt oxide (NMC) chemistries 7,8 , key limitations remain. Typical models do not include 1) electronic potential polarization, 2) solid concentration gradients within the agglomerate, and 3) extension to the electrode scale. Moreover, practical guidelines are needed to identify the dominant limiting phenomena ( i.e. , transport vs. kinetics) under specific operating conditions, at the particle and electrode scale. To bridge these gaps, we propose a fully coupled hierarchical transmission line model (TLM) for impedance analysis of a porous electrode with agglomerate secondary particles. In this work, analytical expressions for the impedance at limiting conditions are derived from physics-based models combining the particle and electrode scales, and they are validated using published impedance datasets for a wide range of cell chemistries. References (1) Wagner, A. C.; Bohn, N.; Geßwein, H.; Neumann, M.; Osenberg, M.; Hilger, A.; Manke, I.; Schmidt, V.; Binder, J. R. Hierarchical Structuring of NMC111-Cathode Materials in Lithium-Ion Batteries: An In-Depth Study on the Influence of Primary and Secondary Particle Sizes on Electrochemical Performance. ACS Appl. Energy Mater. 2020 , 3 (12), 12565–12574. https://doi.org/10.1021/acsaem.0c02494. (2) Wu, B.; Wang, J.; Li, J.; Lin, W.; Hu, H.; Wang, F.; Zhao, S.; Gan, C.; Zhao, J. Morphology Controllable Synthesis and Electrochemical Performance of LiCoO2 for Lithium-Ion Batteries. Electrochimica Acta 2016 , 209 , 315–322. https://doi.org/10.1016/j.electacta.2016.05.085. (3) Singh, A.; Song, J.; Li, W.; Martin, T.; Xu, H.; Finegan, D. P.; Zhu, J. Microstructure-Chemomechanics Relations of Polycrystalline Cathodes in Solid-State Batteries. Extreme Mech. Lett. 2024 , 69 , 102164. https://doi.org/10.1016/j.eml.2024.102164. (4) Lian, H.; Bazant, M. Z. Modeling Lithium Plating Onset on Porous Graphite Electrodes Under Fast Charging with Hierarchical Multiphase Porous Electrode Theory. J. Electrochem. Soc. 2024 , 171 (1), 010526. https://doi.org/10.1149/1945-7111/ad1e3d. (5) Gagneur, L.; Driemeyer-Franco, A. L.; Forgez, C.; Friedrich, G. Modeling of the Diffusion Phenomenon in a Lithium-Ion Cell Using Frequency or Time Domain Identification. Microelectron. Reliab. 2013 , 53 (6), 784–796. https://doi.org/10.1016/j.microrel.2013.03.009. (6) Karden, Eckhard. Using Low Frequency Impedance Spectroscopy for Characterization, Monitoring, and Modeling of Industrial Batteries, Aachener Beiträge des ISEA, Aachen, 2002 . (7) Huang, J.; Ge, H.; Li, Z.; Zhang, J. An Agglomerate Model for the Impedance of Secondary Particle in Lithium-Ion Battery Electrode. J. Electrochem. Soc. 2014 , 161 (8), E3202–E3215. https://doi.org/10.1149/2.027408jes. (8) Huang, J.; Zhang, J. Theory of Impedance Response of Porous Electrodes: Simplifications, Inhomogeneities, Non-Stationarities and Applications. J. Electrochem. Soc. 2016 , 163 (9), A1983. https://doi.org/10.1149/2.0901609jes.

  PublisherDOI

• Theory of ultrafast conductance modulation in electrochemical protonic synapses by multiphase polarization

  ArXiv.org · 2025-07-31

  preprintOpen accessSenior author

  Three-terminal electrochemical ionic synapses (EIoS) have recently attracted interest for in-memory computing applications. These devices utilize electrochemical ion intercalation to modulate the ion concentration in the channel material. The electrical conductance, which is concentration dependent, can be read separately and mapped to a non-volatile memory state. To compete with other random access memory technologies, linear and symmetric conductance modulation is often sought after, properties typically thought to be limited by the slow ion diffusion timescale. A recent study by Onen et al.[1] examining protonic EIoS with a tungsten oxide (WO3) channel revealed that this limiting timescale seemed irrelevant, and linear conductance modulation was achieved over nanosecond timescales, much faster than the bulk ion diffusion. This contrasts with previous studies that have shown similar conductance modulation with pulse timescales of milliseconds to seconds. Understanding the phenomena behind these conductance modulation properties in EIoS systems remains a crucial question gating technological improvements to these devices. Here, we provide a theoretical explanation that demonstrates how linearity and symmetry arise from consistent control over the electrolyte-WO3 interface. Comparing these past works, changes in the WO3 channel crystallinity were identified, affecting material thermodynamics and revealing that the device achieving nanosecond pulse timescales underwent phase separation. Coupling of electric field polarizatino and increased electron conductivity in high-concentration filaments, the reaction environment at the gate electrode can be controlled, resulting in ideal conductance modulation within the diffusion-limited regime. This work highlights the potential for phase-separating systems to overcome the traditional diffusion barriers that limit EIoS performance.

  PublisherOA PDFDOI

• Theory of Electric Field Driven Phase-Separation: Applications to Nanosecond Linear Conductance Modulation in 3-Terminal EC RAM

  ECS Meeting Abstracts · 2025-07-11

  articleSenior author

  The need for increased computational efficiency for deep learning applications has led to interest in in-memory computing. One promising example is three-terminal synaptic transistors with ion or proton intercalation mechanisms [1,2], which have been studied for their CMOS compatibility and fast switching times. These systems are typically thought to be limited by the ion diffusion time τ diffusion =L 2 /D. Interestingly, a recent study by Onen, et. al. [2] has shown that linear conductance modulation can be achieved at the nanosecond timescale for proton intercalation into tungsten oxide (WO 3 ), far quicker than the bulk ion diffusion timescale. This surprising finding opens new questions how the conductance state can be modulated order of magnitudes faster than the expected physical transport timescales. Here we present a theoretical explanation for this phenomenon where the applied electric field polarizes the drives spontaneous material phase-separation, even when the bulk concentration is outside the binodal stability gap. In this regime, the intercalation of ions goes directly to translation of the phase boundary. Our theory predicts that conductance modulation can occur on the 10 ns timescale, consistent with experimental observations [2], and shows that the induced phase separation leads to a fixed reaction environment at the gate electrode. This stable environment enables linear conductance modulation with pulse number. We then compare these model results to solid solution amorphous WO 3 , where we demonstrate how 1s relaxation times are needed to get similar linear conductance modulation. Finally, under a simplified model, we construct a map relating diffusion, reaction, and pulse-length timescales to whether phase-separation can be induced, providing design principles for selecting materials for ion-based EC RAM devices. Onen, Murat, et al. "Nanosecond protonic programmable resistors for analog deep learning." Science 377 . 6605 (2022): 539-543. Cui, Jinsong, et al. "CMOS-compatible electrochemical synaptic transistor arrays for deep learning accelerators." Nature Electronics 6.4 (2023): 292-300. Tian, Huanhuan, Ju Li, and Martin Z. Bazant. "Multiphase Polarization in Ion‐Intercalation Nanofilms: General Theory Including Various Surface Effects and Memory Applications." Advanced Functional Materials 33.23 (2023): 2213621.

  PublisherDOI

• Author response for "Modeling Single-Crystal Electrodes as a Network of Primary Particles"

  2025-09-30

  peer-review
  PublisherDOI

Recent grants

• Mathematical Modeling of Induced-Charge Electrokinetics

  NSF · $288k · 2007–2010

• FRG: Collaborative Research: Mathematical Modeling of Rechargeable Batteries

  NSF · $725k · 2009–2012

• EAGER/Collaborative Research: New Concept of Sorption Hysteresis and Disjoining Pressure in Concrete and Other Adsorbent Microporous Solids

  NSF · $90k · 2011–2013

• Mathematical Modeling of Rechargeable Batteries

  NSF · $44k · 2009–2010

Frequent coauthors

• Armand Ajdari

  Centre National de la Recherche Scientifique

  72 shared

• Richard D. Braatz

  Massachusetts Institute of Technology

  48 shared

• Alexei A. Kornyshev

  48 shared

• William C. Chueh

  SLAC National Accelerator Laboratory

  45 shared

• Peng Bai

  China Aerodynamics Research and Development Center

  41 shared

• Brian D. Storey

  Toyota Research Institute

  38 shared

• Grigorios A. Pavliotis

  36 shared

• Dimitrios Fraggedakis

  36 shared

Labs

• MIT ChemEPI

Education

• Ph.D., Mechanical Engineering

  Massachusetts Institute of Technology

  1991

• M.S., Mechanical Engineering

  Massachusetts Institute of Technology

  1987

• B.S., Mechanical Engineering

  University of California, Berkeley

  1985

Awards & honors

• Member of the National Academy of Engineering (2025)
• Electrochemical Society Fellow (2023)
• Inaugural President, International Electrokinetics Society (…
• MIT Information Systems and Technology (IS&T) Infinite Mile…
• MITx Prize for Teaching and Learning in MOOCs (2019)