About

Amir Haji-Akbari is an Associate Professor of Chemical & Environmental Engineering at Yale University. He holds a Ph.D. and M.Sc. from the University of Michigan, Ann Arbor, and a B.Sc. from the University of Tehran. His research broadly focuses on applying modern theoretical and computational tools rooted in thermodynamics and statistical mechanics to study the thermodynamics and kinetics of phase transitions in soft matter systems. His particular focus is on crystallization and aggregation in colloidal, aqueous, and biological systems, including ice formation in the atmosphere, colloidal self-assembly, and protein folding and aggregation. His work involves investigating complex phenomena such as surface freezing in water, ion transport through membranes, and the effects of material flexibility on water evaporation, contributing to a deeper understanding of phase behavior in soft matter and biological systems.

Research topics

• Statistical physics
• Mathematical analysis
• Physics
• Mathematics
• Thermodynamics
• Materials science
• Geometry
• Chemical physics

Selected publications

• Path Dependence in Alchemical Calculations of Water Chemical Potential in Aqueous Electrolytes

  arXiv (Cornell University) · 2026-05-09

  preprintOpen accessSenior author

  Accurate calculation of free energies and their derivatives is central to assessing the thermodynamic stability of molecular and particulate systems across length scales. Yet such quantities can be difficult to compute reliably in strongly interacting systems, such as solutions of ionic species in polar solvents. One important example is the chemical potential of water in aqueous electrolytes, which can be estimated through staged particle insertion by gradually coupling an inserted molecule to its environment. Although the resulting insertion free energy should be independent of the alchemical pathway, the order and manner in which van der Waals and electrostatic interactions are activated can strongly affect convergence and, in some cases, yield inconsistent estimates. Here, we examine this issue by calculating water's chemical potential in aqueous KCl solutions using eight alchemical insertion pathways that differ in the extent and order of van der Waals and Coulombic coupling. We find that concurrently activating these interactions, particularly in fully coupled and partially end-coupled protocols, can produce chemically implausible insertion free energies. These anomalies arise from intermediate states in which the inserted water molecule develops strong electrostatic interactions with a chloride ion before sufficient short-range repulsion has been established. In contrast, pathways that activate short-range van der Waals interactions before electrostatics yield more consistent and chemically plausible estimates. These findings demonstrate that practical alchemical calculations in polar and ionic environments can be highly sensitive to pathway design, underscoring the importance of decoupling short-range and electrostatic interactions in staged insertion alchemical protocols.

  PublisherDOI

• Robustness of Classical Nucleation Theory to Chemical Heterogeneity of Crystal Nucleating Substrates

  Crystal Growth & Design · 2026-02-13

  articleSenior authorCorresponding

  Heterogeneous nucleation is a process wherein extrinsic impurities facilitate crystallization by lowering nucleation barriers and constitutes the dominant mechanism for crystallization in most systems. Classical nucleation theory (cnt) has been remarkably successful in predicting the kinetics of heterogeneous nucleation, even on chemically and topographically nonuniform surfaces, despite its reliance on several restrictive assumptions, such as the idealized spherical-cap geometry of the crystalline nuclei. Here, we employ molecular dynamics simulations and jumpy forward flux sampling to investigate the kinetics and mechanism of heterogeneous crystal nucleation in a model atomic liquid. We examine both a chemically uniform, weakly attractive liquiphilic surface and a checkerboard surface composed of alternating liquiphilic and liquiphobic patches. We find the nucleation rate to retain its canonical temperature dependence predicted by cnt in both systems. Moreover, the contact angles of crystalline nuclei exhibit negligible dependence on the nucleus size and temperature. On the checkerboard surface, nuclei maintain a fixed contact angle through pinning at patch boundaries and vertical growth into the bulk. These findings offer insights into the robustness of cnt in experimental scenarios, where nucleating surfaces often feature active hotspots surrounded by inert or liquiphobic domains.

  PublisherDOI

• Pathway-resolved flux decomposition reveals hidden kinetic hierarchy in protein folding

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-23

  articleOpen accessSenior authorCorresponding

  Proteins fold through ensembles of competing pathways, yet the kinetic contribution of each route remains difficult to quantify. Structure-prediction methods such as AlphaFold identify folded endpoints, but do not resolve folding kinetics, pathway heterogeneity, or how flux partitions among competing mechanisms. Here, we introduce a framework that directly decomposes folding flux into pathway-specific kinetic contributions by combining forward-flux sampling with trajectory-level unsupervised learning, avoiding millisecond-scale trajectories, biasing potentials, and \emph{a priori} state discretization. Applied to 2,637 statistically representative folding events of the TC5b variant of Trp-cage, the framework recovers a folding time in near-quantitative agreement with experiments and identifies four pathways distinguished by the ordering of helix formation, hydrophobic collapse, and salt-bridge stabilization. The resulting decomposition shows that structural prevalence is a poor proxy for kinetic importance: the most populated pathways are not the fastest, whereas a rare helix--salt-bridge route is disproportionately efficient and a premature salt bridge produces a frustrated slow route. By assigning statistical weights to competing pathways, this framework links structural evolution to kinetic relevance in biomolecular rare events and reveals how folding landscapes select kinetically important routes from many plausible structural sequences.

  PublisherOA PDFDOI

• Path Dependence in Alchemical Calculations of Water Chemical Potential in Aqueous Electrolytes

  ArXiv.org · 2026-05-09

  articleOpen accessSenior author

  Accurate calculation of free energies and their derivatives is central to assessing the thermodynamic stability of molecular and particulate systems across length scales. Yet such quantities can be difficult to compute reliably in strongly interacting systems, such as solutions of ionic species in polar solvents. One important example is the chemical potential of water in aqueous electrolytes, which can be estimated through staged particle insertion by gradually coupling an inserted molecule to its environment. Although the resulting insertion free energy should be independent of the alchemical pathway, the order and manner in which van der Waals and electrostatic interactions are activated can strongly affect convergence and, in some cases, yield inconsistent estimates. Here, we examine this issue by calculating water's chemical potential in aqueous KCl solutions using eight alchemical insertion pathways that differ in the extent and order of van der Waals and Coulombic coupling. We find that concurrently activating these interactions, particularly in fully coupled and partially end-coupled protocols, can produce chemically implausible insertion free energies. These anomalies arise from intermediate states in which the inserted water molecule develops strong electrostatic interactions with a chloride ion before sufficient short-range repulsion has been established. In contrast, pathways that activate short-range van der Waals interactions before electrostatics yield more consistent and chemically plausible estimates. These findings demonstrate that practical alchemical calculations in polar and ionic environments can be highly sensitive to pathway design, underscoring the importance of decoupling short-range and electrostatic interactions in staged insertion alchemical protocols.

  PublisherOA PDF

• Robustness of Classical Nucleation Theory to Chemical Heterogeneity of Crystal Nucleating Substrates

  Crystal Growth & Design · 2026-02-13

  articleOpen accessSenior authorCorresponding

  Heterogeneous nucleation is a process wherein extrinsic impurities facilitate crystallization by lowering nucleation barriers and constitutes the dominant mechanism for crystallization in most systems. Classical nucleation theory (cnt) has been remarkably successful in predicting the kinetics of heterogeneous nucleation, even on chemically and topographically nonuniform surfaces, despite its reliance on several restrictive assumptions, such as the idealized spherical-cap geometry of the crystalline nuclei. Here, we employ molecular dynamics simulations and jumpy forward flux sampling to investigate the kinetics and mechanism of heterogeneous crystal nucleation in a model atomic liquid. We examine both a chemically uniform, weakly attractive liquiphilic surface and a checkerboard surface composed of alternating liquiphilic and liquiphobic patches. We find the nucleation rate to retain its canonical temperature dependence predicted by cnt in both systems. Moreover, the contact angles of crystalline nuclei exhibit negligible dependence on the nucleus size and temperature. On the checkerboard surface, nuclei maintain a fixed contact angle through pinning at patch boundaries and vertical growth into the bulk. These findings offer insights into the robustness of cnt in experimental scenarios, where nucleating surfaces often feature active hotspots surrounded by inert or liquiphobic domains.

  PublisherOA PDFDOI

• The impact of hydration shell inclusion and chain exclusion in the efficacy of reaction coordinates for homogeneous and heterogeneous ice nucleation

  The Journal of Chemical Physics · 2025-04-22 · 2 citations

  articleOpen accessSenior author

  Ice nucleation plays a pivotal role in many natural and industrial processes, and molecular simulations have proven vital in uncovering its kinetics and mechanisms. A fundamental component of such simulations is the choice of an order parameter (OP) that quantifies the progress of nucleation, with the efficacy of an OP typically measured by its ability to predict the committor probabilities. Here, we leverage a machine learning framework introduced in our earlier work [Domingues et al., J. Phys. Chem. Lett. 15, 1279, (2024)] to systematically investigate how key implementation details influence the efficacy of standard Steinhardt OPs in capturing the progress of both homogeneous and heterogeneous ice nucleation. Our analysis identifies distance and q6 cutoffs as the primary determinants of OP performance, regardless of the mode of nucleation. We also examine the impact of two popular refinement strategies, namely chain exclusion and hydration shell inclusion, on OP efficacy. We find neither strategy to exhibit a universally consistent impact. Instead, their efficacy depends strongly on the chosen distance and q6 cutoffs. Chain exclusion enhances OP efficacy when the underlying OP lacks sufficient selectivity, whereas hydration shell inclusion is beneficial for overly selective OPs. Consequently, we demonstrate that selecting optimal combinations of such cutoffs can eliminate the need for these refinement strategies altogether. These findings provide a systematic understanding of how to design and optimize OPs for accurately describing complex nucleation phenomena, offering valuable guidance for improving the predictive power of molecular simulations.

  PublisherOA PDFDOI

• A highly selective and energy efficient approach to boron removal overcomes the Achilles heel of seawater desalination

  Nature Water · 2025-01-20 · 29 citations

  article
  PublisherDOI

• Computational Investigations of Ion Selectivity in Capacitive Deionization from Electronic to Device Scales

  The Journal of Physical Chemistry Letters · 2025-11-24 · 1 citations

  articleCorresponding

  Sustainable water treatment requires selective removal of deleterious ions, such as toxic metals and excess salts, while preserving beneficial minerals. Capacitive deionization (CDI), which is a membrane-free electrochemical desalination technology, offers a tunable alternative for targeted ion separation. Achieving high ion selectivity in CDI is, however, challenging as factors such as ion valence, hydrated radius, and hydration energy influence the preferential electrosorption of different ions into charged porous electrodes, making selectivity outcomes hard to predict and control. Theoretical and computational tools are crucial for understanding the selectivity mechanisms in CDI systems and informing the rational design of new materials and devices. However, these models operate at varying length scales, and integrating the insights gained from different scales into a unified multiscale framework still remains a grand challenge. Here, we overview recent advancements in computational modeling of CDI systems, showing how cross-scale insights can guide the design of next-generation CDI systems.

  PublisherDOI

• Secondary finite-size effects and multi-barrier free energy landscapes in molecular simulations of hindered ion transport

  ArXiv.org · 2025-08-10

  preprintOpen accessSenior author

  Ion transport through nanoscale channels and pores is pivotal to numerous natural processes and industrial applications. Experimental investigation of the kinetics and mechanisms of such processes is, however, hampered by the limited spatiotemporal resolution of existing experimental techniques. While molecular simulations have become indispensable for unraveling the underlying principles of nanoscale transport, they also suffer from some important technical limitations. In our previous works, we identified strong polarization-induced finite-size effects in molecular dynamics simulations of hindered ion transport, caused by spurious long-range interactions between the traversing ion and the periodic replicates of other ions. To rectify these artifacts, we introduced the Ideal Conductor/Dielectric Model (\textsc{Icdm}), which treats the system as a combination of conductors and dielectrics, and constructs an analytical correction to the translocation free energy profile. Here, we investigate some limitations of this model. Firstly, we propose a generalized approach based on Markov State models that is capable of estimating translocation timescales in the thermodynamic limit for free energy profiles with multiple comparable barriers. Second, we identify a new category of polarization-induced finite-size effects, which significantly alter the spatial distribution of non-traversing ions in smaller systems. These secondary effects cannot be corrected by the ICDM model and must be avoided by selecting sufficiently large system sizes. Additionally, we demonstrate through multiple case studies that finite-size artifacts can reverse expected trends in ion transport kinetics. Our findings underscore the necessity for careful selection of system sizes and the judicious application of the \textsc{Icdm} model to rectify residual finite-size artifacts.

  PublisherOA PDFDOI

• Secondary Finite-Size Effects and Multibarrier Free Energy Landscapes in Molecular Simulations of Hindered Ion Transport

  The Journal of Physical Chemistry B · 2025-10-23 · 2 citations

  articleSenior authorCorresponding

  Ion transport through nanoscale channels and pores is pivotal to numerous natural processes and industrial applications. Experimental investigation of the kinetics and mechanisms of such processes is, however, hampered by the limited spatiotemporal resolution of existing experimental techniques. While molecular simulations have become indispensable for unraveling the underlying principles of nanoscale transport, they all suffer from some important technical limitations. In our previous works, we identified strong polarization-induced finite-size effects in molecular dynamics simulations of hindered ion transport, caused by spurious long-range interactions between the traversing ion and the periodic replicates of other ions. To rectify these artifacts, we introduced the ideal conductor/dielectric model (Icdm), which treats the system as a combination of conductors and dielectrics and constructs an analytical correction to the translocation free energy profile. Here, we investigate some limitations of this model. First, we propose a generalized approach based on Markov state models that is capable of estimating translocation time scales in the thermodynamic limit for free energy profiles with multiple comparable barriers. Second, we identify a new category of polarization-induced finite-size effects, which significantly alter the spatial distribution of nontraversing ions in smaller systems. These secondary effects cannot be corrected by the Icdm model and must be avoided by selecting sufficiently large system sizes. Additionally, we demonstrate through multiple case studies that finite-size artifacts can spuriously reverse expected trends in ion transport kinetics. Our findings underscore the necessity for careful selection of system sizes and the judicious application of the Icdm model to rectify residual finite-size artifacts.

  PublisherDOI

Recent grants

• CAREER: Computational Design and Optimization of Operationally Robust Crystal Nucleating Materials via Surface Nano-Patterning

  NSF · $521k · 2018–2024

• Computational Design of Ultraselective Desalination Membranes using Molecular Simulations and Path Sampling Techniques

  NSF · $332k · 2021–2023

Frequent coauthors

• Pablo G. Debenedetti

  Princeton University

  18 shared

• Sharon C. Glotzer

  13 shared

• Michael Engel

  Friedrich-Alexander-Universität Erlangen-Nürnberg

  10 shared

• Sarwar Hussain

  Yale University

  9 shared

• Tiago S. Domingues

  Yale University

  7 shared

• Ronald R. Coifman

  5 shared

• Betül Uralcan

  Yale University

  5 shared

• Menachem Elimelech

  Yale University

  4 shared

Education

• Ph.D., Department of Chemical Engineering

  University of Michigan

  2012

• M. Sc., Mathematics

  University of Michigan

  2009

• M. Sc., Chemical Engineering

  University of Michigan

  2006

• B. Sc., Biotechnology

  University of Tehran

  2003

Awards & honors

• Sloan Research Fellowship (2025)
• Yale Ackerman Award (2023)
• AIChE COMSEF Young Investigator Award (2019)
• NSF CAREER Award (2018)
• Distinguished Young Scholars' Seminar Series, University of…