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Amir Haji-Akbari

Publications and source records attributed to Amir Haji-Akbari.

At least 19 recordsLinked to original sources
arXiv2026

Sensitivity of Nucleation Thermodynamics and Kinetics to the Treatment of Long-Range Interactions

Nucleation rates are exponentially sensitive to the thermodynamic driving force and can therefore depend strongly on the treatment of long-range intermolecular interactions. Here, using the Lennard--Jones (LJ) system as a benchmark, we combine molecular dynamics (MD) simulations, jumpy forward-flux sampling (jFFS), and free-energy calculations to quantify the effect of potential truncation on melting thermodynamics, homogeneous crystal nucleation kinetics, and computational cost. Within the cutoff-radius range $2.5σ\le r_c\le 6σ$, the melting temperature at zero pressure varies by approximately 11%, while the nucleation rate changes by approximately ten orders of magnitude. By invoking classical nucleation theory (CNT), we show that this pronounced kinetic sensitivity originates primarily from cutoff-induced changes in the chemical potential difference between the liquid and crystalline phases. Building on this observation, we develop a CNT-based framework for extrapolating finite-cutoff rates to the full-potential limit and for estimating the expected rate deviations at other cutoff radii and temperatures. These findings also provide a systematic basis for cutoff selection: the optimal cutoff should minimize computational cost while keeping the deviation from the full-potential rate within acceptable bounds. At $kT/ε=0.5$, $r_c=4σ$ provides a reasonable compromise according to these criteria. We further demonstrate that conventional homogeneous tail corrections do not offer a reliable alternative, as they cannot consistently account for the liquid, crystalline, and interfacial environments present during nucleation. Our findings highlight the need to specify and validate the truncation scheme as an integral component of force-field development in simulations of nucleation and other interfacial phase transitions within inhomogeneous environments.

cond-mat.soft↗
arXiv2026

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

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.

physics.chem-ph↗
arXiv2025

Robustness of classical nucleation theory to chemical heterogeneity of crystal nucleating substrates

Heterogeneous nucleation is a process wherein extrinsic impurities facilitate freezing by lowering nucleation barriers and constitutes the dominant mechanism for crystallization in most systems. Classical nucleation theory (\textsc{Cnt}) has been remarkably successful in predicting the kinetics of heterogeneous nucleation, even on chemically and topographically non-uniform 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 comprised of alternating liquiphilic and liquiphobic patches. We find the nucleation rate to retain its canonical temperature dependence predicted by \textsc{Cnt} in both systems. Moreover, the contact angles of crystalline nuclei exhibit negligible dependence on 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 \textsc{Cnt} in experimental scenarios, where nucleating surfaces often feature active hotspots surrounded by inert or liquiphobic domains.

cond-mat.soft↗
arXiv2025

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

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.

cond-mat.stat-mech↗
arXiv2025

The Impact of Hydration Shell Inclusion and Chain Exclusion in the Efficacy of Reaction Coordinates for Homogeneous and Heterogeneous Ice Nucleation

Ice nucleation plays a pivotal role in many natural and industrial processes, and molecular simulations play 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,~\emph{et al.}, \emph{J. Phys. Chem. Lett.}, 15, 1279, {\bf 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 identify distance and $q_6$ 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 $q_6$ 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.

physics.chem-ph↗
arXiv2024

Estimating position-dependent and anisotropic diffusivity tensors from molecular dynamics trajectories: Existing methods and future outlook

Confinement can substantially alter the physicochemical properties of materials by breaking translational isotropy and rendering all physical properties position-dependent. Molecular dynamics (MD) simulations have proven instrumental in characterizing such spatial heterogeneities and probing the impact of confinement on materials' properties. For static properties, this is a straightforward task and can be achieved via simple spatial binning. Such an approach, however, cannot be readily applied to transport coefficients due to lack of natural extensions of autocorrelations used for their calculation in the bulk. The prime example of this challenge is diffusivity, which, in the bulk, can be readily estimated from the particles' mobility statistics, which satisfy the Fokker-Planck equation. Under confinement, however, such statistics will follow the Smoluchowski equation, which lacks a closed-form analytical solution. This brief review explores the rich history of estimating profiles of the diffusivity tensor from MD simulations and discusses various approximate methods and algorithms developed for this purpose. Beside discussing heuristic extensions of bulk methods, we overview more rigorous algorithms, including kernel-based methods, Bayesian approaches, and operator discretization techniques. Additionally, we outline methods based on applying biasing potentials or imposing constraints on tracer particles. Finally, we discuss approaches that estimate diffusivity from mean first passage time or committor probability profiles, a conceptual framework originally developed in the context of collective variable spaces describing rare events in computational chemistry and biology. In summary, this paper offers a concise survey of diverse approaches for estimating diffusivity from MD trajectories, highlighting challenges and opportunities in this area.

cond-mat.stat-mech↗
arXiv2023

Robust estimation of position-dependent anisotropic diffusivity tensors from stochastic trajectories

Materials under confinement can possess properties that deviate considerably from their bulk counterparts. Indeed, confinement makes all physical properties position-dependent and possibly anisotropic, and characterizing such spatial variations and directionality is an intense area of focus in experimental and computational studies of confined matter. While this task is fairly straightforward for simple mechanical observables, it is far more daunting for transport properties such as diffusivity that can only be estimated from autocorrelations of mechanical observables. For instance, there are well established methods for estimating diffusivity from experimentally observed or computationally generated trajectories in the bulk. No rigorous generalizations of such methods, however, exist for confined systems. In this work, we present two filtered covariance estimators for computing anisotropic and position-dependent diffusivity tensors and validate them by applying them to stochastic trajectories generated according to known diffusivity profiles. These estimators can accurately capture spatial variations spanning over several orders of magnitude and assuming different functional forms. Our approach is also very robust to implementation details such as the localization function and time discretization and performs significantly better than estimators that are solely based on local covariance. Moreover, the kernel function does not have to be localized and can instead belong to a dictionary of orthogonal functions. Therefore, the proposed estimator can be readily used to obtain functional estimates of diffusivity rather than a tabulated collection of pointwise estimates. Nonetheless, the susceptibility of the proposed estimators to time discretization is higher close to hard boundaries. We demonstrate this heightened susceptibility to be common among all covariance-based estimators.

cond-mat.stat-mech↗
arXiv2022

Ideal Conductor Model: An analytical finite-size correction for non-equilibrium molecular dynamics simulations of ion transport through nanoporous membranes

Modulating ion transport through nanoporous membranes is critical to many important chemical and biological separation processes. The corresponding transport timescales, however, are often too long to capture accurately using conventional molecular dynamics (\textsc{Md}). Recently, path sampling techniques such as forward-flux sampling (\textsc{Ffs}) have emerged as attractive alternatives for efficiently and accurately estimating arbitrarily long ionic passage times. Here, we use non-equilibrium \textsc{Md} and \textsc{Ffs} to explore how the kinetics and mechanism of pressure-driven chloride transport through a nanoporous graphitic membrane are affected by its lateral dimensions. We not only find ionic passage times and free energy barriers to decrease dramatically upon increasing the membrane surface area, but also observe an abrupt and discontinuous change in the locus of the transition state. These strong finite size effects arise due to the cumulative effect of the periodic images of the leading ion entering the pore on the distribution of the induced excess charge at the membrane surface in the feed. By assuming that the feed is an ideal conductor, we analytically derive a finite size correction term that can be computed from the information obtained from a single simulation and successfully use it to obtain corrected free energy profiles with no dependence on system size. We then estimate ionic passage times in the thermodynamic limit by assuming an Eyring-type dependence of rates on barriers with a size-independent prefactor. This approach constitutes a universal framework for removing finite size artifacts in molecular simulations of ion transport through nanoporous membranes and biological channel proteins.

cond-mat.stat-mech↗
arXiv2021

How to quantify and avoid finite size effects in computational studies of crystal nucleation: The case of homogeneous crystal nucleation

Finite size artifacts arise in molecular simulations of nucleation when critical nuclei are too close to their periodic images. A rigorous determination of what constitutes too close is, however, a major challenge. Recently, we devised rigorous heuristics for detecting such artifacts based on our investigation of how system size impacts the rate of heterogeneous ice nucleation (Hussain, Haji-Akbari, \emph{J. Chem. Phys.} \textbf{154}, 014108, \textbf{2021}). We identified the prevalence of critical nuclei spanning across the periodic boundary, and the thermodynamic and structural properties of the liquid occupying the inter-image region as indicators of finite size artifacts. Here, we further probe the performance of such heuristics by examining the dependence of homogeneous crystal nucleation rates in the Lennard-Jones liquid on system size. The rates depend non-monotonically on system size and vary by almost six orders of magnitude for the range of system sizes considered here. We confirm that the prevalence of spanning critical nuclei is the primary indicator of finite size artifacts and almost fully explains the observed variations in rate. Proximity, or structuring of the inter-image liquid, however, is not as strong of an indicator due to the fragmented nature of crystalline nuclei. As a result, the dependence of rate on system size is subtle for the systems with a minuscule fraction of spanning critical nuclei. These observations indicate that our heuristics are universally applicable to different modes of nucleation (homogeneous and heterogeneous) in different systems even if they might be overly stringent for homogeneous nucleation,~e.g.,~in the LJ system.

cond-mat.soft↗
arXiv2021

Role of Nanoscale Interfacial Proximity in Contact Freezing in Water

Contact freezing is a mode of atmospheric ice nucleation in which a collision between a dry ice nucleating particle (INP) and a water droplet results in considerably faster heterogeneous nucleation. The molecular mechanism of such enhancement is, however, still a mystery. While earlier studies had attributed it to collision-induced transient perturbations, recent experiments point to the pivotal role of nanoscale proximity of the INP and the free interface. By simulating heterogeneous nucleation of ice within INP-supported nanofilms of two model water-like tetrahedral liquids, we demonstrate that such nanoscale proximity is sufficient for inducing rate increases commensurate with those observed in contact freezing experiments, but only if the free interface has a tendency to enhance homogeneous nucleation. Water is suspected of possessing this latter property, known as surface freezing propensity. Our findings therefore establish a connection between surface freezing propensity and kinetic enhancement during contact nucleation. We also observe that faster nucleation proceeds through a mechanism markedly distinct from classical heterogeneous nucleation, involving the formation of hourglass-shaped crystalline nuclei that conceive at either interface, and that have a lower free energy of formation due to the nanoscale proximity of the interfaces and the modulation of the free interfacial structure by the INP. In addition to providing valuable insights into the physics of contact nucleation, our findings can assist in improving the accuracy of heterogeneous nucleation rate measurements in experiments, and in advancing our understanding of ice nucleation on nonuniform surfaces such as organic, polymeric and biological materials.

cond-mat.soft↗
arXiv2021

How to Quantify and Avoid Finite Size Effects in Computational Studies of Crystal Nucleation: The Case of Heterogeneous Ice Nucleation

Computational studies of crystal nucleation can be impacted by finite size effects, primarily due to unphysical interactions between crystalline nuclei and their periodic images. It is, however, not always feasible to systematically investigate the sensitivity of nucleation kinetics and mechanism to system size due to large computational costs of nucleation studies. Here, we use jumpy forward flux sampling to accurately compute the rates of heterogeneous ice nucleation in the vicinity of square-shaped model structureless ice nucleating particles (INPs) of different sizes, and identify three distinct regimes for the dependence of rate on the INP dimension, $L$. For small INPs, the rate is a strong function of $L$ due to artificial spanning of critical nuclei across the periodic boundary. Intermediate-sized INPs, however, give rise to the emergence of non-spanning 'proximal` nuclei that are close enough to their periodic images to fully structure the intermediary liquid. While such proximity can facilitate nucleation, its effect is offset by the higher density of the intermediary liquid, leading to artificially small nucleation rates overall. The critical nuclei formed at large INPs are neither spanning nor proximal. Yet, the rate is a weak function of $L$, with its logarithm scaling linearly with $1/L$. The key heuristic emerging from these observations is that finite size effects will be minimal if critical nuclei are neither spanning nor proximal, and if the intermediary liquid has a region that is structurally indistinguishable from the supercooled liquid under the same conditions.

cond-mat.stat-mech↗
arXiv2020

Induced Charge Anisotropy: a Hidden Variable Affecting Ion Transport through Membranes

The ability of semipermeable membranes to selectively impede the transport of undesirable solutes is key to many applications. Yet, obtaining a systematic understanding of how membrane structure affects selectivity remains elusive due to the insufficient spatiotemporal resolution of existing experimental techniques, and the inaccessibility of relevant solute transport timescales to conventional molecular simulations. Here, we utilize jumpy forward-flux sampling to probe the transport of sodium and chloride ions through a graphitic membrane with sub-nm pores. We find chlorides to traverse the pore at rates over two orders of magnitude faster than sodiums. We also identify two major impediments to the transport of both ion types. In addition to the partial dehydration of the leading ion, its traversal induces charge anisotropy at its rear, which exerts a net restraining force on the ion. Charge anisotropy is therefore a crucial hidden variable controlling the kinetics of ion transport through nanopores.

cond-mat.soft↗
arXiv2019

Studying Rare Events using Forward-Flux Sampling: Recent Breakthroughs and Future Outlook

Rare events are processes that occur upon the emergence of unlikely fluctuations. Unlike what their name suggests, rare events are fairly ubiquitous in nature, as the occurrence of many structural transformations in biology and material sciences is predicated upon crossing large free energy barriers. Probing the kinetics and uncovering the molecular mechanisms of possible barrier crossings in a system is critical to predicting and controlling its structural and functional properties. Due to their activated nature, however, rare events are exceptionally difficult to study using conventional experimental and computational techniques. In recent decades, a wide variety of specialized computational techniques-- known as advanced sampling techniques-- have been developed to systematically capture improbable fluctuations relevant to rare events. In this perspective, we focus on a technique called forward flux sampling (Allen~\emph{et al.,}~\emph{J. Chem. Phys.}, {\bf 124}: 024102, 2006), and overview its recent methodological variants and extensions. We also provide a detailed overview of its application to study a wide variety of rare events, and map out potential avenues for further explorations.

cond-mat.stat-mech↗
arXiv2018

Thermodynamically Driven Assemblies and Liquid-liquid Phase Separations in Biology

The sustenance of life depends on the high degree of organization that prevails through different levels of living organisms, from subcellular structures such as biomolecular complexes and organelles to tissues and organs. The physical origin of such organization is not fully understood, and even though it is clear that cells and organisms cannot maintain their integrity without consuming energy, there is growing evidence that individual assembly processes can be thermodynamically driven and occur spontaneously due to changes in thermodynamic variables such as intermolecular interactions and concentration. Understanding the phase separation \emph{in vivo} requires a multidisciplinary approach, integrating the theory and physics of phase separation with experimental and computational techniques. This paper aims at providing a brief overview of the physics of phase separation and its biological implications, with a particular focus on the assembly of membraneless organelles. We discuss the underlying physical principles of phase separation from its thermodynamics to its kinetics. We also overview the wide range of methods utilized for experimental verification and characterization of phase separation of membraneless organelles, as well as the utility of molecular simulations rooted in thermodynamics and statistical physics in understanding the governing principles of thermodynamically driven biological self-assembly processes.

cond-mat.soft↗
arXiv2018

Forward-Flux Sampling with Jumpy Order Parameters

Forward-flux sampling (FFS) is a path sampling technique that has gained increased popularity in recent years, and has been used to compute rates of rare event phenomena such as crystallization, condensation, hydrophobic evaporation, DNA hybridization and protein folding. The popularity of FFS is not only due to its ease of implementation, but also because it is not very sensitive to the particular choice of an order parameter. The order parameter utilized in conventional FFS, however, still needs to satisfy a stringent smoothness criterion in order to assure sequential crossing of FFS milestones. This condition is usually violated for order parameters utilized for describing aggregation phenomena such as crystallization. Here, we present a generalized FFS algorithm for which this smoothness criterion is no longer necessary, and apply it to compute homogeneous crystal nucleation rates in several systems. Our numerical tests reveal that conventional FFS can sometimes underestimate the nucleation rate by several orders of magnitude.

cond-mat.stat-mech↗
arXiv2017

Forward Flux Sampling Calculation of Homogeneous Nucleation Rates from Aqueous NaCl Solutions

We used molecular dynamics simulations and the path sampling technique known as forward flux sampling to study homogeneous nucleation of NaCl crystals from supersaturated aqueous solutions at 298 K and 1 bar. Nucleation rates were obtained for a range of salt concentrations for the Joung-Cheatham NaCl force field combined with the SPC/E water model. The calculated nucleation rates are significantly lower than available experimental measurements. The estimates for the nucleation rates in this work do not rely on classical nucleation theory, but the pathways observed in the simulations suggest that the nucleation process is better described by classical nucleation theory than an alternative interpretation based on Ostwald's step rule, in contrast to some prior simulations of related models. In addition to the size of NaCl nucleus, we find that the crystallinity of a nascent cluster plays an important role in the nucleation process. Nuclei with high crystallinity were found to have higher growth probability and longer lifetimes, possibly because they are less exposed to hydration water.

physics.chem-ph↗
arXiv2015

Thermodynamic and Kinetic Anisotropies in Octane Thin Films

Confinement breaks the translational symmetry of materials. Such symmetry breaking can be used to obtain configurations that are not otherwise accessible in the bulk. Here, we explore the effect of substrate-liquid interactions on the induced thermodynamic and kinetic anisotropies. We consider n-octane nanofilms that are in contact with substrates with varying degrees of attraction. Complete freezing of octane nanofilms is observed at low temperatures, while at intermediate temperatures, a frozen monolayer emerges at both interfaces. By carefully inspecting the profiles of translational and orientational relaxation times, we confirm that the translational and orientational degrees of freedom are decoupled at these frozen monolayers. At sufficiently high temperatures, however, free interfaces and solid-liquid interfaces close to loose substrates undergo pre-freezing, characterized by mild peaks in several thermodynamic quantities. Two distinct dynamic regimes are observed. The dynamics is accelerated in the vicinity of loose substrates, while sticky substrates decelerate dynamics, sometimes by as much as two orders of magnitude. These two distinct dynamical regimes have been previously by us [JCP 141: 024506, 2014] for a model atomic glass-forming liquid. We also confirm the existence of two correlations proposed in the above-mentioned work in solid-liquid subsurface regions of octane films, i.e., a correlation between density and normal stress, and between atomic translational relaxation time and lateral stress. Finally, we inspect the ability of different regions of a film to explore the potential energy landscape, and observe no noticeable difference between the free surface and the bulk. This is unlike the films of model atomic glass formers that tend to sample their respective landscape more efficiently at free surfaces.

cond-mat.stat-mech↗