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At least 451 records · Page 25

Intrinsic bulk viscosity of the one-component plasma

The intrinsic bulk viscosity of the one-component plasma (OCP) is computed and analyzed using equilibrium molecular dynamics simulations and the Green-Kubo formalism. It is found that bulk viscosity exhibits a maximum at Γ ≈ 1, corresponding to the condition that the average kinetic energy of particles equals the potential energy at the average interparticle spacing. The weakly coupled and strongly coupled limits are analyzed and used to construct a model that captures the full range of coupling strengths simulated: Γ ≈ 10 –2 –10 2 . Simulations are also run of the Yukawa one-component plasma (YOCP) in order to understand the impact of electron screening. It is found that electron screening leads to a smaller bulk viscosity due to a reduction in the excess heat capacity of the system. Bulk viscosity is shown to be at least an order of magnitude smaller than shear viscosity in both the OCP and YOCP. The generalized frequency-dependent bulk viscosity coefficient is also analyzed. This is found to exhibit a peak near twice the plasma frequency in strongly coupled conditions, which is associated with the oscillatory decay observed in the bulk viscosity autocorrelation function. As a result, the generalized shear and bulk viscosity coefficients are found to have a similar magnitude for ω ≳ 2⁢ω p at strongly coupled conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Heterogeneous flexibility can contribute to chromatin segregation in the cell nucleus

The highly and slightly condensed forms of chromatin, heterochromatin and euchromatin, respectively, segregate in the cell nucleus. Heterochromatin is more abundant in the nucleus periphery. Here, in this work, we study the mechanism of heterochromatin segregation by modeling interphase chromosomes as diblock ring copolymers confined in a rigid spherical shell using molecular dynamics simulations. In our model, heterochromatin and euchromatin are distinguished by their bending stiffnesses only, while an interaction potential between the spherical shell and chromatin is used to model lamin-associated proteins. Our simulations indicate that in the absence of attractive interactions between the nuclear shell and the chromatin, most heterochromatin segregates towards the nuclear interior due to the depletion of less flexible heterochromatin segments from the nuclear periphery. This inverted chromatin distribution, which is opposite to the conventional case with heterochromatin dominating at the periphery, is in accord with experimental observations in rod cells. This “inversion” is also found to be independent of the heterochromatin concentration and chromosome number. The chromatin distribution at the periphery found in vivo can be recovered by further increasing the bending stiffness of heterochromatin segments or by turning on attractive interactions between the nuclear shell and heterochromatin. Our results indicate that the bending stiffness of chromatin could be a contributor to chromosome organization along with differential effects of HP ⁢1⁢𝛼-driven phase segregation and of loop extruders and interactions with the nuclear envelope and topological constraints.

biomolecular & subcellular processes↗

Crystal nucleation rates in one-component Yukawa systems

Nucleation in the supercooled Yukawa system is relevant for addressing current challenges in understanding a range of crystallizing systems including white dwarf (WD) stars. We use both brute force and seeded molecular dynamics simulations to study homogeneous nucleation of crystals from supercooled Yukawa liquids. With our improved approach to seeded simulations, we obtain quantitative predictions of the crystal nucleation rate and cluster size distributions as a function of temperature and screening length. These quantitative results show trends towards fast nucleation with short-ranged potentials. They also indicate that for temperatures T > 0.9⁢T m , where T m is the melt temperature, classical homogeneous nucleation is too slow to initiate crystallization but transient clusters of ~100 particles should be common. As a result, we apply these general results to a typical WD model and obtain a delay of ~0.6 Gyr in the onset of crystallization that may be observable.

36 MATERIALS SCIENCE↗

Machine learning interatomic potential for predicting the thermal properties of uranium nitride

We present a combined computational and experimental investigation of the thermal properties of uranium nitride (UN), focusing on the development of a machine learning interatomic potential (MLIP) using the moment tensor potential framework. The MLIP was trained on density functional theory (DFT) data and validated against various quantities including energies, forces, elastic constants, phonon dispersion, and defect formation energies, achieving excellent agreement with DFT calculations, prior experimental results, and our thermal conductivity measurement. The potential was then employed in molecular dynamics simulations to predict key thermal properties such as melting point, thermal expansion, specific heat, and lattice thermal conductivity. To further assess model accuracy, we fabricated a UN sample and performed new thermal conductivity measurements representative of single-crystal properties, which showed strong agreement with the MLIP predictions. This work confirms the reliability and predictive capability of the developed potential for determining the thermal properties of UN.

36 - MATERIALS SCIENCE↗

Elastic Screening of Pseudogauge Fields in Graphene

Lattice deformations in graphene couple to the low-energy electronic degrees of freedom as effective scalar and gauge fields. Using molecular dynamics simulations, we show that the optical component of the displacement field, i.e., the relative motion of different sublattices, contributes at equal order as the acoustic component and effectively screens the pseudogauge fields. In particular, we consider twisted bilayer graphene and corrugated monolayer graphene. In both cases, optical lattice displacements significantly reduce the overall magnitude of the pseudomagnetic fields. For corrugated graphene, optical contributions also reshape the pseudomagnetic field and significantly modify the electronic bands near charge neutrality. Previous studies based on continuum elasticity, which ignores this effect, have therefore systematically overestimated the strength of the strain-induced pseudomagnetic field. Furthermore, our results have important consequences for the interpretation of experiments and design of straintronic applications.

36 MATERIALS SCIENCE↗

Dynamic compression and spallation behavior of NbTaTiVZr high-entropy alloy

High-entropy alloys are a new class of materials with promising properties for aerospace and defense applications. The unique behavior of these materials is driven by the complex interactions between dissimilar atoms in a crystal and requires combined theoretical and experimental efforts to unlock their full potential. Here, we evaluate the relationship between the microstructure and the dynamic response of the equiatomic NbTaTiVZr alloy. Specifically, the shock Hugoniot, or equation of state, was measured up to a particle velocity of 0.5 mm μs −1 using gas gun plate impacts. Shock wave profile and incipient spallation experiments were used to characterize wave propagation and damage formation with post-mortem recovery experiments. Molecular dynamics simulations confirm the experimental findings and extend them up to 2.1 mm μs −1 particle velocity. Computational thermodynamic calculation of phase diagram simulations explain details of the material microstructure, which explains the measured strength and experimental damage patterns. Overall, this work provides detailed high-strain-rate characterization of a refractory high-entropy alloy, and more importantly, a framework and demonstration of the utility and necessity of a combined theoretical and experimental approach, outlining the importance of considering processing and manufacturing conditions when evaluating the performance of new materials.

36 MATERIALS SCIENCE↗

Enhancing Biopolyester Backbone Rigidity with an Asymmetric Furanic Monomer

Biobased furanic polyesters can exhibit performance advantages over petroleum-derived polyesters, primarily due to their rigid furan-containing backbones. Herein, we develop two strategies to polymerize methyl 5-hydroxymethyl furanoate to poly(5-hydroxymethyl furanoate) (PHMF), a furan-based polyester with even greater backbone rigidity than poly(ethylene furanoate). Thermal, spectroscopic, and computational investigations of PHMF alongside analogous furan-based and phenyl-based polyesters suggest that the high furan content of PHMF leads to its high glass transition temperature, slow crystallization kinetics, and low amorphous mobility. Molecular dynamics simulations suggest that while the backbone of PHMF is exceptionally rigid, its amorphous phase is denser than its phenyl analog due to noncovalent interchain interactions. Together, these results highlight how asymmetric furan-based monomers can modulate key properties in biobased polyesters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nitrogen: A promising doping strategy for high-performance ovonic threshold switching selectors

The Ovonic Threshold Switching (OTS) selector serves as an essential component in the development of three-dimensional high-density memory integration technology. Nevertheless, the state-of-the-art high-performance OTS materials usually contain toxic elements such as arsenic (As), posing significant risks to both environmental and human health. Nitrogen (N), which belongs to the same group as arsenic (As), has emerged as a highly promising alternative for As doping. However, the underlying mechanisms that govern N-based OTS materials have not yet been extensively investigated. In this study, we delve into the effects of N doping on the structural, bonding, and electronic properties of amorphous GeSe (a-GeNSe) by ab initio molecular dynamics simulations to bridge the knowledge gap. Our findings indicate that upon N doping in a-GeSe, the formation of robust Ge-N bonds, along with N-centered tetrahedral and triangular structures, resulting in the sluggish atomic movement that enhances the thermal stability and endurance of a-GeNSe. The OTS characteristics are significantly influenced by the material’s electronic band structure, and thus the relatively slow performance drift can be attributed to the stabilization of mid-gap states, a result of N doping which effectively slows down the aging process of chalcogenide glass. Moreover, the increased mobility gap in a-GeNSe raises the threshold voltage (V th ), making it more compatible with commercially available phase-change memory materials. Furthermore, our findings reveal the extensive impact of the N element on a typical OTS material and offer valuable perspectives for alternative doping strategies that could potentially supplant As practices.

36 MATERIALS SCIENCE↗

Cavity-altered superconductivity

Is it feasible to alter the ground-state properties of a material by engineering its electromagnetic environment? Inspired by theoretical predictions, experimental realizations of such cavity-controlled properties without optical excitation are beginning to emerge. Here we devised and implemented a new platform to realize cavity-altered materials. Single crystals of hyperbolic van der Waals (vdW) compounds provide a resonant electromagnetic environment with enhanced density of photonic states and prominent mode confinement. We interfaced hexagonal boron nitride (hBN) with the molecular superconductor κ-(BEDT-TTF) 2 Cu[N(CN) 2 ]Br (κ-ET). The frequencies of infrared hyperbolic modes (HMs) of hBN match the infrared-active carbon–carbon (C=C) stretching molecular resonance of κ-ET implicated in superconductivity. Nano-optical data supported by first-principles molecular Langevin dynamics simulations confirm the presence of resonant coupling between the hBN hyperbolic cavity modes and the C=C stretching mode in κ-ET. Meissner-effect measurements using magnetic force microscopy (MFM) demonstrate a strong suppression of superfluid density near the hBN/κ-ET interface. Non-resonant control heterostructures, including RuCl 3 /κ-ET and hBN/Bi 2 Sr 2 CaCu 2 O 8+x (BSCCO), do not show the pronounced superfluid suppression. These observations suggest that hBN/κ-ET realizes a cavity-altered superconducting ground state. Our work highlights the potential of dark cavities devoid of external photons for engineering electronic ground-state properties of complex quantum materials.

36 MATERIALS SCIENCE↗

Shock Hugoniot calculations using on-the-fly machine learned force fields with ab initio accuracy

We present a framework for computing the shock Hugoniot using on-the-fly machine learned force field (MLFF) molecular dynamics simulations. In particular, we employ an MLFF model based on the kernel method and Bayesian linear regression to compute the free energy, atomic forces, and pressure, in conjunction with a linear regression model between the internal and free energies to compute the internal energy, with all training data generated from Kohn–Sham density functional theory (DFT). We verify the accuracy of the formalism by comparing the Hugoniot for carbon with recent Kohn–Sham DFT results in the literature. In so doing, we demonstrate that Kohn–Sham calculations for the Hugoniot can be accelerated by up to two orders of magnitude, while retaining ab initio accuracy. We apply this framework to calculate the Hugoniots of 14 materials in the FPEOS database, comprising 9 single elements and 5 compounds, between temperatures of 10 kK and 2 MK. We find good agreement with first principles results in the literature while providing tighter error bars. In addition, we confirm that the inter-element interaction in compounds decreases with temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data‐Driven Engineering of Thermostable Collagen‐Mimetic Peptoid Triple Helices

Collagen-mimetic peptides (CMPs) are engineered molecules designed to replicate the triple-helical structure of natural collagen. A repeating x–y-Gly sequence is the defining motif of CMPs and is critical to their triple-helical structure and stability. Substitutions to the residues occupying the x and y positions present a means to modulate the CMP structure and properties. Peptoid residues—N-substituted glycine derivatives—present an attractive potential substitution due to their thermal stability, proteolytic resistance, biocompatibility, and diverse palette of non-natural side chains, but also tend to introduce a high degree of backbone flexibility that can diminish the stability of the triple helix. In this work, we report a computational active learning cycle comprising molecular dynamics simulation, Gaussian process regression, and Bayesian optimization to computationally identify a number of promising peptoid substitutions predicted to stabilize the desired quaternary structure through side chain interactions and produce stable peptoid-based collagen-like triple helices. To experimentally test the computational predictions, a top candidate identified by the screen was synthesized and imaged using scanning electron microscopy to resolve fibril-like bundles consistent with collagen-like triple helices. This work predicts a number of CMP peptoid substitutions capable of forming stable triple-helical structures, presents a generalizable design strategy for engineering desired peptoid structures, and opens new avenues for the design of peptoid-based biomimetic materials.

active learning↗

Atomistic Mechanisms of Stress-Dependent Molten Salt Corrosion in NiCr Alloys

Ni-based structural alloys in molten salt environments often experience simultaneous mechanical loading and corrosive attack, yet the mechanisms governing stress-corrosion interactions remain unclear. Prior studies largely emphasize tensile stress, while the role of compressive stress has received limited attention. Here, reactive molecular dynamics simulations are used to investigate the coupled effects of applied strain and corrosion in Ni 0.75 Cr 0.25 exposed to molten FLiNaK at 800 °C. A Σ5(210) grain boundary model is subjected to tensile (+4%) to compressive (−4%) uniaxial strains, and corrosion behavior is evaluated through fluorine adsorption, charge redistribution, and grain boundary evolution. Tensile strain accelerates intergranular corrosion susceptibility by reducing local atomic packing through elastic dilation and increasing excess free volume at the grain boundary, which enhances atomic mobility and salt infiltration. In contrast, compressive strain can suppress corrosion by promoting the formation of a ridge-like surface layer along the grain boundary, limiting salt access to the underlying alloy. These results provide atomistic insight into how stress states influence grain boundary corrosion in molten salts.

36 - MATERIALS SCIENCE↗

Shear Response of Ionizable Polymer Melts at the Crossover from Ionomers to Polyelectrolytes

Nonlinear shear response of polymers is affected by inherent barriers for diffusive motion, including entanglements and topology. In ionizable polymers, ionic clusters further constrain the intrinsic dynamics of the polymers, significantly enhancing their viscosity. Here, using fully atomistic molecular dynamics simulations, the nonlinear shear response of ionizable polymers is presented, across the transition from the ionomer regime where distinctive clusters dominate the structure to the polyelectrolyte regime where clusters percolate, in polystyrene randomly sulfonated with fractions of SO 3 − groups of f = 0.20 and 0.35, in pristine and tetrahydrofuran (THF) swollen polyelectrolyte melts. For f = 0.20, the ionic clusters first fracture into smaller clusters followed by splitting into individual ionic groups and eventually reform. At higher f, the clusters morph in shape but do not break under high shear. At very high shear rates, all of the chains stretch and recoil rapidly. As the shear rate is reduced, some chains stretch and recoil, while others remain largely unaffected by the shear. Macroscopically, for all systems, the shear viscosity displays initially an elastic response, followed by nonlinear shear stress overshoot and, eventually, a steady state. The evolution of viscosity with time and shear reflects that of the ionizable domains.

cluster chemistry↗

Control of Permanent Porosity in Type 3 Porous Liquids via Solvent Clustering

Porous liquids (PLs) are an exciting new class of materials for carbon capture due to their high gas adsorption capacity and ease of industrial implementation. They are composed of sorbent particles suspended in a nonadsorbed solvent, forming a liquid with permanent porosity. While PLs have a vast number of potential compositions based on the number of solvents and sorbent materials available, most of the research has been focused on the selection of the sorbent rather than the solvent. Therefore, PL design criteria on the supramolecular structures of the solvent are explored to create a fundamental understanding of how the solvent enables PL formation for rapid discovery of new PL compositions. Atomistic molecular dynamics simulation of eight solvents with a range of molecular sizes, shapes, and intramolecular bonding was performed, identifying that the shape and size of molecular clusters formed in the solvent are the driving predictor of PL formation rather than the size of the individual solvent molecule. The results demonstrate a significant departure from common approaches to PL formation based on the steric exclusion of solvent molecules from the sorbent via the size of the pore aperture. A modeling and experimental validation study further supports these findings. In conclusion, through this computational material design study, a previously unexplored mechanism in PL formation, solvent–solvent clustering, is identified as a critical factor for the accelerated discovery of liquid phase carbon capture materials.

Carbon capture↗

Controlling Deformation in Al/Ti: How Interface Roughness and Orientation Drive Bimetal Mechanics

The microstructural characteristics and morphology of interfaces in metals can be crucial in governing the initiation of plasticity and early deformation mechanisms under extreme conditions. During high-strain-rate deformation, these interfaces significantly affect dislocation nucleation, twinning, and other mechanisms that directly impact material strength and failure. Despite their importance, a substantial knowledge gap remains between the observed macroscopic material behavior and the underlying role of bimetal interfaces in plasticity initiation. Here, to address this gap, large-scale molecular dynamics simulations are performed on Al/Ti bimetal structures to examine the effect of interface characteristics on the onset of plasticity under uniaxial compression. Specifically, this study investigates how interface roughness (flat vs waveform interfaces) modifies the initiation of plastic events in the microstructure. Atomistic simulations indicate that interface roughness (a microscopic behavior) reduces the stress required for dislocation nucleation, thereby reducing the peak stress relative to a flat interface. For the square interface, the step height strongly influences plasticity initiation by setting the separation of locally flat regions. Varying the interface rotation relative to the loading direction (macroscopic behavior) reveals that the peak stress for both flat and waveform interfaces initially decreases and then increases with rotation, accompanied by a shift in dominant mechanisms—from Al twinning (flat) to interface sliding and Ti-dominated phase transformation and twinning at lower angles. The change in the stress-strain slope during initial compression reflects how rotation alters the resolved shear stress and activates different slip systems. Overall, the study provides valuable insights into the role of bimetal interfaces in controlling plasticity initiation and early deformation pathways for Al/Ti under extreme loading conditions.

36 MATERIALS SCIENCE↗

Experimental and Computational Insights into the Structural Dynamics of the Fc Fragment of IgG1 Subtype from Biosimilar VEGF‐Trap

The constant fragment (Fc) of the immunoglobulin G1 (IgG1) subtype is increasingly recognized as a crucial scaffold in the development of advanced therapeutics due to its enhanced specificity, efficacy, and extended half‐life. A prime example is VEGF‐Trap (Aflibercept), a recombinant fusion protein that merges the Fc region of the IgG1 subtype with the binding domains of vascular endothelial growth factor receptors (VEGFR)‐1 and VEGFR‐2. The Fc region's role in N‐glycosylation is particularly important, as it significantly influences protein stability. Herein, the first near‐physiological temperature structures of the N‐glycan‐bound Fc fragment of IgG1 subtype from a biosimilar VEGF‐Trap are presented, determined using the SPring‐8 Angstrom Compact free electron LAser (SACLA) and the Turkish Light Source (Turkish DeLight). Comparative analysis with cryogenic structures, including existing data, reveals alternate conformations within the glycan‐binding pocket. Furthermore, molecular dynamics simulations indicate the presence of a high degree of structural plasticity, explaining how the protein adapts its structure through conformational changes. The observed structural fluctuations/conformational changes demonstrate the effect of N‐glycans on protein stability. These findings offer new insights into the molecular basis of Fc‐mediated functions and provide valuable information for the design of next‐generation therapeutics.

60 APPLIED LIFE SCIENCES↗

Physics-informed machine learning exploration of Na storage mechanisms in disordered carbon

Sodium-ion batteries are a cost-effective, sustainable alternative to lithium-ion systems for large-scale energy storage. However, optimizing sodium storage in carbon-based anodes with microstructural complexity and atomic disorder remains a major challenge. The intrinsic inhomogeneity of these materials produces diverse local environments, making it difficult for conventional methods to predict and control ion dynamics. Hard carbon (HC) anodes, composed of ranges of ordered-to-disordered graphitic and amorphous nanodomains, offer tunable ion storage and rate capacity, yet rationale design remains a challenge due to poorly understood correlation between local atomic feature and ion transport mechanism. Here, to address this challenge, we introduce a data-driven framework that integrates validated machine-learned interatomic potentials, large-scale molecular dynamics simulations, and machine learning to elucidate sodium transport mechanisms as a function of carbon and sodium loading densities. By computing per-ion structural descriptors and applying unsupervised learning, we identify distinct diffusion modes governed by microscopic features. Supervised analysis and correlation mapping then establish quantitative links between these transport regimes and processing variables such as bulk carbon density and sodium content. This physics-informed approach establishes quantitative structure–transport relationships and offers actionable design principles for engineering high-performance HC anodes.

Data-driven framework↗

Structure-Based Design of Small-Molecule Inhibitors of Human Interleukin-6

Human Interleukin-6 (hIL-6) is a pro inflammatory cytokine that binds to its receptor, IL-6Rα followed by binding to gp130 and subsequent dimerization to form a hexamer signaling complex. As a critical inflammation mediator, hIL-6 is associated with a diverse range of diseases and monoclonal antibodies in clinical use that either target IL-6Rα or hIL-6 to inhibit signaling. Here, we perform high-throughput structure-based computational screening using ensemble docking for small-molecule antagonists for which the target conformations were taken from 600 ns long molecular dynamics simulations of the apo protein. Prior knowledge of the contact sites from binary complex studies and experimental work was incorporated into the docking studies. The top 20 scoring ligands from the in silico studies after post analysis were subjected to in vitro functional assays. Among these compounds, the ligand with the second-highest calculated binding affinity experimentally showed an ~84% inhibitory effect on IL6-induced STAT3 reporter activity at 10 μM concentration. This finding may pave the way for designing small-molecule inhibitors of hIL-6 of therapeutic significance.

Human Interleukin-6↗