arXiv subjects

Anh D. Phan

Publications and source records attributed to Anh D. Phan.

At least 19 recordsLinked to original sources

arXiv2026

Multiscale Prediction of Polymer Relaxation Dynamics via Computational and Data-Driven Methods

We present a multiscale modeling approach that integrates molecular dynamics simulations, machine learning, and the Elastically Collective Nonlinear Langevin Equation (ECNLE) theory to investigate the glass transition dynamics of polymer systems. The glass transition temperatures (Tg) of four representative polymers are estimated using simulations and machine learning model trained on experimental datasets. These predicted Tg values are used as inputs to the ECNLE theory to compute the temperature dependence of structural relaxation times and diffusion coefficients, and the dynamic fragility. The Tg values predicted from simulations show good quantitative agreement with experimental data. While machine learning tends to slightly overestimate Tg, the resulting dynamic fragility values remain close to experimental fragilities. Overall, ECNLE calculations using these inputs agree well with broadband dielectric spectroscopy results. Our integrated approach provides a practical and scalable tool for predicting the dynamic behavior of polymers, particularly in systems where experimental data are limited.

cond-mat.soft↗

arXiv2025

Predicting Structural Relaxation in Supercooled Small Molecules via Molecular Dynamics Simulations and Microscopic Theory

Understanding and predicting the glassy dynamics of small organic molecules is critical for applications ranging from pharmaceuticals to energy and food preservation. In this work, we present a theoretical framework that combines molecular dynamics simulations and Elastically Collective Nonlinear Langevin Equation (ECNLE) theory to predict the structural relaxation behavior of small organic glass-formers. By using propanol, glucose, fructose, and trehalose as model systems, we estimate the glass transition temperature (Tg) from stepwise cooling simulations and volume-temperature analysis. These computed Tg values are then inserted into the ECNLE theory to calculate temperature-dependent relaxation times and diffusion coefficients. Numerical results agree well with experimental data in prior works. This approach provides a predictive and experimentally-independent route for characterizing glassy dynamics in molecular materials.

cond-mat.soft↗

arXiv2025

Bridging Machine Learning and Glassy Dynamics Theory for Predictive Polymer Modeling

Understanding and predicting the glassy dynamics of polymers remain fundamental challenges in soft matter physics. While the Elastically Collective Nonlinear Langevin Equation (ECNLE) theory has been successful in describing relaxation dynamics, its practical application to polymers depends on a thermal mapping to connect theory with experiment, which in turn requires detailed thermodynamic data. Such data may not be available for chemically complex or newly designed polymers. In this work, we propose a simple approach that integrates machine learning-predicted glass transition temperatures (Tg) with a simplified thermal mapping based on an effective thermal expansion coefficient to overcome these limitations. This approach can provide quantitatively accurate predictions of relaxation dynamics across a broad range of polymers. Rather than replacing the original thermal mapping, our method complements it by trading formal rigor for computational efficiency and broader applicability in high-throughput screening and materials with limited available data. Moreover, we introduce a physically motivated modification to the thermal mapping that resolves discrepancies in the description of low-Tg polymers. Our results establish a generalizable approach for predictive modeling of glassy polymer dynamics and point toward new directions for theory-guided materials discovery.

cond-mat.soft↗

arXiv2025

Machine Learning-Integrated Modeling of Thermal Properties and Relaxation Dynamics in Metallic Glasses

Metallic glasses are a promising class of materials celebrated for their exceptional thermal and mechanical properties. However, accurately predicting and understanding the melting temperature (T_m) and glass transition temperature (T_g) remains a significant challenge. In this study, we present a comprehensive approach that integrates machine learning (ML) models with theoretical methods to predict and analyze these key thermal properties in metallic glasses. Our ML models using distributional data derived from elemental composition-based features obtain high accuracy while minimizing data preprocessing complexity. Furthermore, we explore the correlation between T_m and T_g to elucidate their dependence on alloy composition and thermodynamic behavior. When the T_g value of metallic glasses is known, further analysis using the Elastically Collective Nonlinear Langevin Equation (ECNLE) theory provides a deeper understanding of structural relaxation dynamics. This integrated framework establishes a quantitative description consistent with experimental data and previous works and paves the way for the efficient design and discovery of advanced materials with tailored thermal properties.

cond-mat.mtrl-sci↗

arXiv2025

A Multiscale Approach to Structural Relaxation and Diffusion in Metallic Glasses

Metallic glasses are promising materials with unique mechanical and thermal properties, but their atomic-scale dynamics remain challenging to understand. In this work, we develop a unified approach to investigate the glass transition and structural relaxation in CoCrNi, Zr46Cu46Al8, Zr50Cu40Al10, and Zr64.13Cu15.75Ni10.12Al10 metallic glasses. Molecular dynamics (MD) simulation is employed to analyze the radial distribution function at different temperatures and accurately determine the glass transition temperature. We then combine this temperature with the Elastically Collective Nonlinear Langevin Equation (ECNLE) theory to predict the temperature dependence of the structural relaxation time, tau_alpha(T). By connecting $τ_α(T)$ to the diffusion constant, the ECNLE predictions of tau_alpha(T) can be compared with those calculated from MD simulations or estimated based on the diffusion constant. By combining atomistic simulation with force-level statistical mechanics, our multiscale approach offers deeper insights into relaxation dynamics and diffusion across various timescales. The relationship between the glass transition and the liquidus temperature is elucidated. This study enhances understanding of the glassy dynamics and properties in complex amorphous materials.

cond-mat.mtrl-sci↗

arXiv2024

Toward a Better Understanding of the Photothermal Heating of High-Entropy-Alloy Nanoparticles

We present a theoretical approach, for the first time, to investigate optical and photothermal properties of high-entropy alloy nanoparticles with a focus on FeCoNi-based alloys. We systematically analyze the absorption spectra of spherical nanoparticles composed of pure metals and alloys in various surrounding media. Through comparison with experimental data, we select appropriate dielectric data for the constituent elements to accurately compute absorption spectra for FeCoNi-based high-entropy-alloy nanoparticles. Then, we predict the temperature rise over time within a substrate comprised of Fe nanoparticles exposed to solar irradiation and find quantitative agreement with experimental data for FeCoNi nanoparticles reported in previous studies. The striking similarity between the optical and photothermal behaviors of FeCoNi nanoparticles and their pure iron counterparts suggests that iron nanoparticles can effectively serve as a model for understanding the optical and thermal response of FeCoNi-based alloy nanoparticles. These findings offer a simplified approach for theoretical modeling of complex high-entropy alloys and provide valuable insights into their nanoscale optical behavior.

cond-mat.mtrl-sci↗

arXiv2024

Effect of the Nature of the Solid Substrate on Spatially Heterogeneous Activated Dynamics in Glass Forming Supported Films

We extend the force-level ECNLE theory to treat the spatial gradients of the alpha relaxation time and glass transition temperature, and the corresponding film-averaged quantities, to the geometrically asymmetric case of finite thickness supported films with variable fluid - substrate coupling. The latter typically nonuniversally slows down motion near the solid-liquid interface as modeled via modification of the surface dynamic free energy caging constraints which are spatially transferred into the film, and which compete with the accelerated relaxation gradient induced by the vapor interface. Quantitative applications to the foundational hard sphere fluid and a polymer melt are presented. The strength of the effective fluid-substrate coupling has very large consequences on the dynamical gradients and film-averaged quantities in a film thickness and thermodynamic state dependent manner. The interference of the dynamical gradients of opposite nature emanating from the vapor and solid interfaces is determined, including the conditions for the disappearance of a bulk-like region in the film center. The relative importance of surface-induced modification of local caging versus the generic truncation of the long range collective elastic component of the activation barrier is studied. The conditions for the accuracy and failure of a simple superposition approximation for dynamical gradients in thin films is also determined. The emergence of near substrate dead layers, large gradient effects on film-averaged response functions, and a weak non-monotonic evolution of dynamic gradients in thick and cold films, are briefly discussed. The connection of our theoretical results to simulations and experiments is briefly discussed, as is extension to treat more complex glass-forming systems under nanoconfinement.

cond-mat.soft↗

arXiv2023

Photo-to-heat conversion of broadband metamaterial absorbers based on TiN nanoparticles under laser and solar illumination

We theoretically investigate photothermal heating of ultra-flexible metamaterials, which are obtained by randomly mixing TiN nanoparticles in polydimethylsiloxane (PDMS). Due to the plasmonic properties of TiN nanoparticles, incident light is perfectly absorbed in a broadband range (300-3000 nm) to generate heat within these metamaterials. Under irradiation of an 808 nm near-infrared laser with different intensities, our predicted temperature rises as a function of time agree well with recent experimental data. For a given laser intensity, the temperature rise varies non-monotonically with concentration of TiN nanoparticles because the enhancement of thermal conductivity and absorbed energy as adding plasmonic nanostructures leads to opposite effects on the heating process. When the model is extended to solar heating, photothermal behaviors are qualitatively similar but the temperature increase is less than 13 $K$. Our studies would provide good guidance for future experimental studies on the photo-to-heat conversion of broadband perfect absorbers.

cond-mat.mtrl-sci↗

arXiv2022

Theoretical predictions of melting behaviors of hcp iron up to 4000 GPa

The high-pressure melting diagram of iron is a vital ingredient for the geodynamic modeling of planetary interiors. Nonetheless, available data for molten iron show an alarming discrepancy. Herein, we propose an efficient one-phase approach to capture the solid-liquid transition of iron under extreme conditions. Our basic idea is to extend the statistical moment method to determine the density of iron in the TPa region. On that basis, we adapt the work-heat equivalence principle to appropriately link equation-of-state parameters with melting properties. This strategy allows explaining cutting-edge experimental and ab initio results without massive computational workloads. Our theoretical calculations would be helpful to constrain the chemical composition, internal dynamics, and thermal evolution of the Earth and super-Earths.

cond-mat.mtrl-sci↗

arXiv2022

Screening and collective effects in randomly pinned fluids: A new theoretical framework

We propose a theoretical framework for the dynamics of bulk isotropic hard-sphere systems in the presence of randomly pinned particles and apply this theory to supercooled water to validate it. Structural relaxation is mainly governed by local and non-local activated process. As the pinned fraction grows, a local caging constraint becomes stronger and the long range collective aspect of relaxation is screened by immobile obstacles. Different responses of the local and cooperative motions results in subtle predictions for how the alpha relaxation time varies with pinning and density. Our theoretical analysis for the relaxation time of water with pinned molecules quantitatively well describe previous simulations. In addition, the thermal dependence of relaxation for unpinned bulk water is also consistent with prior computational and experimental data.

cond-mat.soft↗

arXiv2022

Theoretical Insights into Non-Arrhenius Behaviors of Thermal Vacancies in Anharmonic Crystals

Vacancies are prevalent point defects in crystals, but their thermal responses are elusive. Herein, we formulate a simple theoretical model to shed light on the vacancy evolution during heating. Vibrational excitations are thoroughly investigated via moment recurrence techniques in quantum statistical mechanics. On that basis, we carry out numerical analyses for Ag, Cu, and Ni with the Sutton-Chen many-body potential. Our results reveal that the well-known Arrhenius law is insufficient to describe the proliferation of vacancies. Specifically, anharmonic effects lead to a strong nonlinearity in the Gibbs energy of vacancy formation. Our physical picture is well supported by previous simulations and experiments.

cond-mat.mtrl-sci↗

arXiv2022

Confinement effects on the spatially inhomogeneous dynamics in metallic glass films

We develop the Elastically Collective Nonlinear Langevin Equation theory to investigate, for the first time, glassy dynamics in capped metallic glass thin films. Finite-size effects on the spatial gradient of structural relaxation time and glass transition temperature (Tg) are calculated at different temperatures and vitrification criteria. Molecular dynamics is significantly slowed down near rough solid surfaces and the dynamics at location far from the interfaces is sped up. In thick films, the mobility gradient normalized by the bulk value well obeys the double-exponential form since interference effects between two surfaces are weak. Reducing the film thickness induces a strong dynamic coupling between two surfaces and flattens the relaxation gradient. The normalized gradient of the glass transition temperature is independent of vitrification timescale criterion and can be fitted by a superposition function as the films are not ultra-thin. The local fragility is found to remain unchanged with location. This finding suggests that one can use Angell plots of bulk relaxation time and the Tg spatial gradient to characterize glassy dynamics in metallic glass films. Our computational results agree well with experimental data and simulation.

cond-mat.soft↗

arXiv2021

Tailoring Drug Mobility by Photothermal Heating of Graphene Plasmons

We propose a theoretical approach to quantitatively determine the photothermally driven enhancement of molecular mobility of graphene-indomethacin mixtures under infrared laser irradiation. Graphene plasmons absorb incident electromagnetic energy and dissipate them into heat. The absorbed energy depends on optical properties of graphene plasmons, which are sensitive to structural parameters, and concentration of plasmonic nanostructures. By using theoretical model, we calculate temperature gradients of the bulk drug with different concentrations of graphene plasmons. From these, we determine the temperature dependence of structural molecular relaxation and diffusion of indomethacin and find how the heating process significantly enhances the drug mobility.

cond-mat.mes-hall↗

arXiv2021

Toward a better understanding of activation volume and dynamic decoupling of glass-forming liquids under compression

We theoretically investigate physical properties of the pressure-induced activation volume and dynamic decoupling of ternidazole, glycerol, and probucol by the Elastically Collective Nonlinear Langevin Equation theory. Based on the predicted temperature dependence of activated relaxation under various compression, the activation volume is determined to characterize effects of pressure on molecular dynamics of materials. We find that the decoupling of the structural relaxation time of compressed systems from their bulk uncompressed value is governed by the power-law rule. The decoupling exponent exponentially grows with pressure below 2 GPa. The decoupling exponent and activation volume are intercorrelated and have a connection with the differential activation free energy. We numerically and mathematically analyze relationships among these quantities to explain many results in previous experiments and simulations.

cond-mat.soft↗

arXiv2021

Impact of high pressure on reversible structural relaxation of metallic glass

We theoretically investigate the temperature dependence of the reversible structural relaxation time and diffusion constant of metallic glasses under pressure. The compression not only changes the glassy dynamics, but also generates a metastable state along with a higher-energy state where the system can rejuvenate. The relaxation times for forward and backward transitions in this two-state system are nearly identical and much faster than the relaxation time without accounting for barrier-recrossing. At ambient pressure, the expected irreversible relaxation process is recovered, and our numerical results agree well with prior experimental results. An increase of pressure has a minor effect on the relaxation time and diffusion constant that one computes without considering the influence of the metastable state, but it leads to a large reduction of the reversible relaxation time computed upon taking the metastable state into account. The presence of external compression is also shown to trigger a fragile-to-strong crossover in metallic glasses.

cond-mat.mtrl-sci↗

arXiv2021

Theoretical Model for the High-Pressure Melting Process of MgO with the B1 Structure

MgO is an abundant mineral in the rocky mantle of terrestrial planets, but its melting behaviors remain enigmatic. Here we introduce a simple theoretical model to investigate the B1-liquid transition of MgO up to 370 GPa. Vibrational free energies of B1-MgO are fully computed by the moment recurrence technique in quantum statistical physics. On that basis, we associate the melting temperature with the isothermal bulk modulus via the work-heat equivalence principle. This strategy allows us to quantitatively explain recent experimental data. Our numerical analyses would yield insights into planetary dynamics and evolution.

cond-mat.mtrl-sci↗

arXiv2020

Efficient Analytical Approach for High-Pressure Melting Properties of Iron

Iron represents the principal constituent of the Earth's core, but its high-pressure melting diagram remains ambiguous. Here we present a simple analytical approach to predict the melting properties of iron under deep-Earth conditions. In our model, anharmonic free energies of the solid phase are directly determined by the moment expansion technique in quantum statistical mechanics. This basis associated with the Lindemann criterion for a vibrational instability can deduce the melting temperature. Moreover, we correlate the thermal expansion process with the shear response to explain a discontinuity of atomic volume, enthalpy, and entropy upon melting. Our numerical calculations are quantitatively consistent with recent experiments and simulations. The obtained results would improve understanding of the Earth's structure, dynamics, and evolution.

cond-mat.mtrl-sci↗

arXiv2020

Cooperative nanoparticle self-assembly and photothermal heating in a flexible plasmonic metamaterial

We theoretically investigate equilibrium behaviors and photothermal effects of a flexible plasmonic metamaterial composed of aramid nanofibers and gold nanoparticles. The fiber matrix is considered as an external field to reconfigure a nanoparticle assembly. We find that the heating process tunes particle-particle and fiber-particle interactions, which alter adsorption of nanoparticles on fiber surfaces or clustering in pore spaces. Thus, it is possible to control the nanoparticle self-assembly by laser illumination. Gold nanoparticles strongly absorb radiations and efficiently dissipate absorbed energy into heat. By solving the heat transfer equation associated with an effective medium approximation, we calculate the spatial temperature rise. Remarkably, our theoretical results quantitatively agree with prior experiments. This indicates that we can ignore plasmonic coupling effects induced by particle clustering. Effects of the laser spot size and intensity on the photothermal heating are also discussed.

cond-mat.mes-hall↗