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We present large-scale atomistic simulations that reveal triple junction (TJ) segregation in Pt-Au nanocrystalline alloys in agreement with experimental observations. While existing studies suggest grain boundary solute segregation as a route to thermally stabilize nanocrystalline materials with respect to grain coarsening, here we quantitatively show that it is specifically the segregation to TJs that dominates the observed stability of these alloys. Our results reveal that doping the TJs renders them immobile, thereby locking the grain boundary network and hindering its evolution. In dilute alloys, it is shown that grain boundary and TJ segregation are not as effective in mitigating grain coarsening, as the solute content is not sufficient to dope and pin all grain boundaries and TJs. Our work highlights the need to account for TJ segregation effects in order to understand and predict the evolution of nanocrystalline alloys under extreme environments.

Understanding the complex temporal and spatial correlations of ions in disordered perovskite oxides is critical to rationalize their functional properties. Here, we provide insights into the longstanding controversy regarding the off-centering of transition metal (TM) ions in the archetypal ferroelectric alloy KTa1-xNbxO3 (KTN). By mapping the full energy (E) and wavevector (Q) dependence of the dynamical structure factor S(Q, E) using neutron scattering, and rationalizing our observations with atomistic simulations leveraging machine learning, we fully resolve the static vs dynamic nature of diffuse scattering sheets, as well as their composition (x) and temperature dependence. Our first-principles simulations, extended with machine-learning molecular dynamics, reproduce both inelastic neutron spectra and diffuse features, and establish how dynamically correlated TM off-centerings couple to phonons, unifying local and collective viewpoints. This study sheds light into an exemplary ferroelectric system and shows the importance of mapping the full S (Q, E) to reveal critical spatiotemporal correlations of atomic disorder from which functional properties emerge. [ABSTRACT FROM AUTHOR]

Understanding the complex temporal and spatial correlations of ions in disordered perovskite oxides is critical to rationalize their functional properties. Here, we provide insights into the longstanding controversy regarding the off-centering of transition metal (TM) ions in the archetypal ferroelectric alloy KTa1-xNbxO3 (KTN). By mapping the full energy (E) and wavevector (Q) dependence of the dynamical structure factor S(Q, E) using neutron scattering, and rationalizing our observations with atomistic simulations leveraging machine learning, we fully resolve the static vs dynamic nature of diffuse scattering sheets, as well as their composition (x) and temperature dependence. Our first-principles simulations, extended with machine-learning molecular dynamics, reproduce both inelastic neutron spectra and diffuse features, and establish how dynamically correlated TM off-centerings couple to phonons, unifying local and collective viewpoints. This study sheds light into an exemplary ferroelectric system and shows the importance of mapping the full S (Q, E) to reveal critical spatiotemporal correlations of atomic disorder from which functional properties emerge. [ABSTRACT FROM AUTHOR]

After the thermal-mechanical processing of Mg alloys, extensive 30°〈0001〉 grain boundaries (GBs) are present in the recrystallized structure, which strongly affects the mechanical properties via interactions with lattice dislocations. In this work, we systematically investigate how the 30°〈0001〉 GBs influence the slip transmission during plastic deformation. We reveal that basal dislocations can be transmuted into its neighboring grain and continue gliding on the basal plane. The prismatic dislocation can transmit the GB remaining on the same Burgers vector. However, a mobile pyramidal c + a dislocation can be absorbed at GBs, initiating the formation of new grain. These findings provide a comprehensive understanding on GB-dislocation interaction in hexagonal close-packed (HCP) metals. [ABSTRACT FROM AUTHOR]

The design of new alloys is a multiscale problem that requires a holistic approach that involves retrieving relevant knowledge, applying advanced computational methods, conducting experimental validations, and analyzing the results, a process that is typically slow and reserved for human experts. Machine learning can help accelerate this process, for instance, through the use of deep surrogate models that connect structural and chemical features to material properties, or vice versa. However, existing datadriven models often target specific material objectives, offering limited flexibility to integrate out-of-domain knowledge and cannot adapt to new, unforeseen challenges. Here, we overcome these limitations by leveraging the distinct capabilities of multiple AI agents that collaborate autonomously within a dynamic environment to solve complex materials design tasks. The proposed physics-aware generative AI platform, AtomAgents, synergizes the intelligence of large language models (LLMs) and the dynamic collaboration among AI agents with expertise in various domains, including knowledge retrieval, multimodal data integration, physics-based simulations, and comprehensive results analysis across modalities. The concerted effort of the multiagent system allows for addressing complex materials design problems, as demonstrated by examples that include autonomously designing metallic alloys with enhanced properties compared to their pure counterparts. Our results enable accurate prediction of key characteristics across alloys and highlight the crucial role of solid solution alloying to steer the development of advanced metallic alloys. Our framework enhances the efficiency of complex multiobjective design tasks and opens avenues in fields such as biomedical materials engineering, renewable energy, and environmental sustainability. [ABSTRACT FROM AUTHOR]

CO2 mineralization, a process where CO2 reacts with minerals to form stable carbonates, presents a sustainable approach for CO2 sequestration and mitigation of global warming. While the crucial role of water in regulating CO2 mineralization efficiency is widely acknowledged, a comprehensive understanding of the underlying mechanisms remains elusive. This study employs a combined experimental and atomistic simulation approach to elucidate the intricate mechanisms governing moisture-driven carbonation kinetics of calcium-bearing minerals. A self-designed carbonation reactor equipped with an ultrasonic atomizer is used to meticulously control the water content during carbonation experiments. Grand Canonical Monte Carlo simulations reveal that maximum CO2 uptake occurs at a critical water content where the initiation of capillary condensation significantly enhanced liquid-gas interactions. This phenomenon leads to CO2 adsorption-driven ultrafast carbonation at an optimal moisture content (0.1 to 0.2 g/g, water mass ratio to total wet mass of the mineral). A higher moisture content decimates the carbonation rate by crippling CO2 intake within mineral pores. However, at exceptionally high moisture levels, the carbonation reaction sites shift from internal mesopores to the grain surface. This results in surface dissolution-driven ultrafast carbonation, attributed to the monotonically decreasing free energy of dissolution with increasing surface water thickness, as revealed by metadynamics simulations. This study provides a fundamental and unified understanding of the multifaceted role of water in mineral carbonation, paving the way for optimizing ultrafast CO2 mineralization strategies for global decarbonization efforts. [ABSTRACT FROM AUTHOR]

Abstract Additive manufacturing of metallic parts by Selective Laser Melting (SLM) implies high temperature gradients and small volume of the melt bath. These conditions make the process scales close to those available for state-of-the-art massively parallel atomistic simulations. In the paper, the microscopic mechanisms responsible for the formation of primary microstructure during molten metal solidification are investigated using classical molecular dynamics (CMD). The 316L austenitic stainless steel with face centred cubic lattice, which is widely used in industry including SLM applications was chosen as a material for the CMD simulations. It was shown that solidified material inherits substrate defects and catches new ones, which interact with the solidification front thus producing the primary microstructure. Peculiarities of solidification in different crystallographic directions and solidification front interaction with grain boundaries and newly produced defects (mostly twin boundaries) as well as their formation are under study. Resulting microstructures of virtual samples are compared with those of real samples produced by SLM and analysed by the electron backscatter diffraction (EBSD) method. The comparison shows similarities of EBSD and CMD sample patterns and evidences for the capability of the large-scale atomistic simulations to reproduce main features of the microstructures formed in the metallic SLM additive production.

Polymer nanocomposites have found ubiquitous use across diverse industries, attributable to their distinctive properties and enhanced mechanical performance compared to conventional materials. Elucidating the elastic‐to‐plastic transition in polymer nanocomposites under diverse mechanical loads is paramount for the bespoke design of materials with desired mechanical attributes. In the current work, the elastic‐to‐plastic transition is probed in model systems of polyethylene oxide (PEO) and silica, SiO2, nanoparticles, through detailed atomistic molecular dynamics simulations. This comprehensive, multi‐scale analysis unveils pivotal markers of the elastic‐to‐plastic transition, highlighting the quintessential role of microstructural and regional heterogeneities in density, strain, and stress fields, featuring the polymer‐nanoparticle interphase region. At the atomic level, the behavior of polymer chains interacting with nanoparticle surfaces is traced, differentiating between free and adsorbed chains, and identifying the microscopic origins of the linear‐to‐plastic transition. The mechanical behavior of subregions are characterized within the PEO/SiO2 nanocomposites, focusing on the interphase and bulk‐like polymer areas, probing stress heterogeneities and their decomposition into various force contributions. At the inception of plasticity, a disruption is discerned in isotropy of the polymeric density field, the emergence of low‐density regions, and microscopic voids/cavities within the polymer matrix concomitant with a transition of adsorbed chains to free. The yield strain also emerges as an inflection point in the local versus global strain diagram, demarcating the elastic limit, and the plastic regime shows pronounced strain heterogeneities. The decomposition of the atomic Virial stress into bonded and non‐bonded interactions indicates that the rigidity of the material is primarily governed by non‐bonded interactions, significantly influenced by the volume fraction of the nanoparticle. These findings emphasize the importance of the microstructural and micromechanical environment at the polymer‐nanoparticle interface on the linear‐to‐plastic transition, which is of great importance in the design of nanocomposite materials with advanced mechanical properties. [ABSTRACT FROM AUTHOR]

The mechanical properties of lignin, an aromatic heteropolymer constituting 20–30% plant biomass, are important to the fabrication and processing of lignin-based sustainable polymeric materials. In this study, atomistic simulations are performed to provide microscopic insights into the mechanics of lignin. Representative samples of miscanthus, spruce, and birch lignin are studied. At room temperature below the glass transition temperature, the stress–strain curves for uniaxial compression and tensile loading are calculated and analyzed. The results show that lignin possesses rigidity with a Young's modulus in the order of GPa and exhibits strain hardening under strong compression. Meanwhile, lignin is brittle and fails through the microscopic mechanism of cavitation and chain pullout under local tensile loading. In addition to the three common lignin samples, minimalist model systems of monodisperse linear chains consisting of only guaiacyl units and β -O-4 linkages are simulated. Systematic variation of the model lignin chain length allows a focused examination of the molecular weight effects. The results show that the molecular weight does not affect the Young's modulus much, but higher molecular weight results in stronger strain hardening under compression. In the range of molecular weight studied, the lignin chains are not long enough to arrest the catastrophic chain pullout, explaining the brittleness of real lignin samples. This work demonstrates that the recently modified CHARMM force fields and the accompanying structural information of real lignin samples properly capture the mechanics of lignin, offering an in silico microscope to explore the atomistic details necessary for the valorizaiton of lignin. [ABSTRACT FROM AUTHOR]

The electrical excitation of spin dynamics in antiferromagnets is important for the development of high-speed spintronic devices with a low power consumption. Here, we present a theoretical study of the spin dynamics generated in the Ni/Cu/Mn2Au/Cu/Ni nanostructure by a perpendicular-to-plane electric current. Our investigation includes atomistic simulations of spin reorientations in a few monolayer antiferromagnetic Mn2Au film and numerical calculations of nonequilibrium spin accumulation in the nanostructure comprising ferromagnetic Ni polarizers with antiparallel magnetizations. This combined approach enables us to quantify the dynamics of Mn magnetic moments induced by the spin-transfer torque created by the spin-polarized charge flow. The calculations show that the direct electric current with the density exceeding some temperature-dependent threshold value gives rise to steady-state auto-oscillations of the Néel vector in the (0 0 1) -oriented Mn2Au nanolayer. As the precession of Mn magnetic moments occurs around an out-of-plane direction strongly deflected from their initial in-plane orientations, the emergence of auto-oscillations should be regarded as the realization of a dynamic spin reorientation transition in the antiferromagnetic crystal. Remarkably, the precession frequency rises with increasing current density J and exceeds 1 THz at J ≈ 1. 4 × 1 0 1 3 A m − 2 , which makes the described antiferromagnetic spin transfer nano-oscillator attractive for device applications. Furthermore, our simulations demonstrate that a picosecond current pulse injected into the Ni/Cu/Mn2Au/Cu/Ni nanostructure can induce a precessional switching of the Néel vector. Depending on the current density and pulse duration, the Néel vector rotates by either 90° or 180° and attains stable orientation along the corresponding 〈 1 1 0 〉 easy axis in the plane of the Mn2Au nanolayer. This feature shows that the Ni/Cu/Mn2Au/Cu/Ni nanostructure could be used as a nonvolatile memory cell with the electrical writing and readout. [ABSTRACT FROM AUTHOR]

Stacking faults (SFs) could be generated in aluminum (Al) via full dislocations extension under extreme stress. However, the extension behavior of the dislocations related to the stress conditions have not been studied comprehensively. In this study, SFs were generated solely under extreme stress condition in coarse–grained Al nanocomposites, where high content of Silicon Carbide nanowires (SiCnw) was introduced as reinforcement. Dislocation extension behaviors under normal and shear stress were predicted using an atomistic approach comparing with experiment methods. The extension ability of full dislocations was studied in terms of complex stress forced on partial dislocations and the relationship between stress condition and the SF width was established by stress analysis. The generated SFs were further proved to offer superb additional strengthening effect for the composites. This study provides a new idea and theory for designing of SF generation in coarse–grained Al based nanocomposites. [ABSTRACT FROM AUTHOR]

Additive manufacturing of metallic parts by Selective Laser Melting (SLM) implies high temperature gradients and small volume of the melt bath. These conditions make the process scales close to those available for state-of-the-art massively parallel atomistic simulations. In the paper, the microscopic mechanisms responsible for the formation of primary microstructure during molten metal solidification are investigated using classical molecular dynamics (CMD). The 316L austenitic stainless steel with face centred cubic lattice, which is widely used in industry including SLM applications was chosen as a material for the CMD simulations. It was shown that solidified material inherits substrate defects and catches new ones, which interact with the solidification front thus producing the primary microstructure. Peculiarities of solidification in different crystallographic directions and solidification front interaction with grain boundaries and newly produced defects (mostly twin boundaries) as well as their formation are under study. Resulting microstructures of virtual samples are compared with those of real samples produced by SLM and analysed by the electron backscatter diffraction (EBSD) method. The comparison shows similarities of EBSD and CMD sample patterns and evidences for the capability of the large-scale atomistic simulations to reproduce main features of the microstructures formed in the metallic SLM additive production. [ABSTRACT FROM AUTHOR]

Atomistic simulations are conducted to investigate the tensile properties and deformation mechanisms of the gradient nano-grained (GNG) structure of face-centered-cubic (FCC) Al0.3CrFeCoNi HEAs, and comparisons are made with the homogeneous nano-grained (HNG) counterparts. Our computations show that the GNG Al0.3CrFeCoNi HEA primarily undergoes three typical deformation stages, i.e. linear elastic, plastic yielding and plastic flow stages, and the plastic deformation mechanism of GNG structure is dominated by the dislocation slip and stacking faults multiplication. The GNG structure possesses an obvious higher flow strength compared to the HNG counterpart, showing the extra strengthening effect. The strengthen mechanism is attributed to the tensile strain partitioning between the large grains and small grains, which causes hetero-deformation induced stress and higher dislocation density and thus strengthening the GNG structure. With the increase of temperature, the Young's modulus, yielding strength and flow strength of GNG and HNG structures all exhibit a clear decreased trend. Increasing strain rate leads to the increase of the Young's modulus and yielding strength of GNG and HNG structures. In particular, no extra strengthening effect is observed from the GNG structure at higher temperature or higher strain rate. Such a scenario can be attributed to the more dislocation slips, stacking faults and grain boundary activities in the small grains, which makes them to accommodate significant tensile strain. These findings provide deeper insights into the deformation mechanisms of GNG HEAs and offer guidance to design heterogeneous HEA structures. [ABSTRACT FROM AUTHOR]

Polymer nanocomposites are characterized by heterogeneous mechanical behavior and performance, which is mainly controlled by the interaction between the nanofiller and the polymer matrix. Optimizing their material performance in engineering applications requires understanding how both the temperature and strain rate of the applied deformation affect mechanical properties. This work investigates the effect of strain rate and temperature on the mechanical properties of poly(ethylene oxide)/silica (PEO/SiO2) nanocomposites, revealing their behavior in both the melt and glassy states, via atomistic molecular dynamics simulations and continuum models. In the glassy state, the results indicate that Young's modulus increases by up to 99.7% as the strain rate rises from 1.0 × 10−7 fs−1 to 1.0 × 10−4 fs−1, while Poisson's ratio decreases by up to 39.8% over the same range. These effects become even more pronounced in the melt state. Conversely, higher temperatures lead to an opposing trend. A local, per-atom analysis of stress and strain fields reveals broader variability in the local strain of the PEO/SiO2 nanocomposites as temperature increases and/or the deformation rate decreases. Both interphase and matrix regions lose rigidity at higher temperatures and lower strain rates, blurring their distinctiveness. The results of the atomistic simulations concerning the elastic modulus and Poisson's ratio are in good agreement with the predictions of the Richeton–Ji model. Additionally, these findings can be leveraged to design advanced polymer composites with tailored mechanical properties and could optimize structural components by enhancing their performance under diverse engineering conditions. [ABSTRACT FROM AUTHOR]

Objective: The present study investigates the production of mebendazole nanocrystal formulations by wet media milling. Significance: Nanocrystal formulations are expected to enhance the dissolution properties of mebendazole, which possesses poor solubility, highly dependent on crystal polymorphism. Methods: A Box-Behnken design was employed to study the effects of formulation and process variables on the nanocrystal size and ζ-potential. The optimal nanosuspensions were solidified by spay-drying and freeze-drying with and without mannitol, and the effects of the drying method on the reconstitution of the nanosuspension was studied. Additionally, their physicochemical properties were determined, while the mechanism of fracture and stabilizer adsorption were investigated by atomistic simulations. Results: Poloxamer 407 is the most suitable stabilizer, while the bead size, milling speed, and stabilizer content significantly affect the diameter. The ζ-potential is affected by the stabilizer concentration depending on bead size. Energy-vector diagrams revealed a slip plane in the lattice of form C, while molecular dynamics simulations revealed strong interactions between stabilizer and crystal surface. Both drying processes induce polymorphic transformation to form A, which, however, can be partially prevented by the addition of mannitol in freeze-drying, at the expense of suspension redispersibility. The spray-dried nanosuspensions exhibited substantially enhanced dissolution profile compared to neat mebendazole, probably due to reduction of particle size, despite transformation to the unfavorable form A. Conclusions: Nanocrystal formulations exhibited significant dissolution enhancement, while experimental design and atomistic simulations provided useful insights into the mechanism of their formation and stability. [ABSTRACT FROM AUTHOR]

Bimetallic nanoclusters have a wide range of uses, and Re-W has been shown to be a catalyst due to its good properties, so it is crucial to study Re-W nanoclusters at the microscopic scale in order to obtain better-performing Re-W nanoclusters. This research investigates the diffusion and structural modification of Re on the surfaces of W nanoclusters at high temperatures. The EAM potential function is employed in this work to explain the interaction between Re and W, and the LAMMPS (large-scale atom/polar massively parallel simulation) package is used for the simulation. We observed the diffusion phenomenon in our investigation by depositing Re atoms on the surface of the W nanoclusters. The findings demonstrate that there are differences in the exchange energy barriers between the Re and W atoms at various locations. At the intersection of the faces, the more (110) faces there are, the lower the exchange energy barrier between the Re and W atoms. During diffusion, the mechanisms of vacancy formation and migration were investigated. The results of the analysis demonstrate that the formation and migration of these vacancies are facilitated by the presence of Re atoms. Furthermore, we noticed that the lattice structure changed throughout the entire deposition process. This observation offers a theoretical direction for producing Re-W bimetallic nanoclusters with a little lattice distortion. [ABSTRACT FROM AUTHOR]

Currently, clear guidance is not available for determining the minimum practical chain lengths needed for achieving reasonable convergence when performing atomistic simulations of common synthetic polymers. Here, we analyze a collection of polymers, including polypropylene (PP), polyethylene naphthalate (PEN), polyethylene terephthalate (PET), polyethylene glycol (PEG), poly(methyl methacrylate) (PMMA), polystyrene (PS), and polyvinyl chloride (PVC), with chain lengths varying from 5 to 240 repeat units. We exclusively focus on solvated polymer systems, and we report the convergence of several characteristic properties, such as radial distribution functions (RDFs), surface area per repeat unit (SASA/N), ratio of mean squared end-to-end distance to mean squared radius of gyration ($\displaystyle{{\left\langle {R^2} \right\rangle } \over {\left\langle {R_g^2 } \right\rangle }}$ 〈 R 2 〉 〈 R g 2 〉 ), and surface electrostatic potential distributions. Based on these data, we propose a general relationship for identifying minimum practical chain lengths for performing atomistic simulations of solvated linear synthetic polymers, which is based on the SASA/N. [ABSTRACT FROM AUTHOR]

Energy transfer in small nano-sized systems can be very different from that in their macroscopic counterparts due to reduced dimensionality, interaction with surfaces, disorder, and large fluctuations. Those ingredients may induce non-diffusive heat transfer that requires to be taken into account on small scales. We provide an overview of the recent advances in this field from the points of view of nonequilibrium statistical mechanics and atomistic simulations. We summarize the underlying basic properties leading to violations of the standard diffusive picture of heat transport and its universal features, with some historical perspective. We complete this scenario by illustrating also the effects of long-range interaction and integrability on non-diffusive transport. Then we discuss how all of these features can be exploited for thermal management, rectification and to improve the efficiency of energy conversion. We conclude with a review on recent achievements in atomistic simulations of anomalous heat transport in single polymers, nanotubes and two-dimensional materials. A short account of the existing experimental literature is also given.

Metallic alloys often form phases--known as solid solutions--in which chemical elements are spread out on the same crystal lattice in an almost random manner. The tendency of certain chemical motifs to be more common than others is known as chemical short-range order (SRO), and it has received substantial consideration in alloys with multiple chemical elements present in large concentrations due to their extreme configurational complexity (e.g., high-entropy alloys). SRO renders solid solutions "slightly less random than completely random," which is a physically intuitive picture, but not easily quantifiable due to the sheer number of possible chemical motifs and their subtle spatial distribution on the lattice. Here, we present a multiscale method to predict and quantify the SRO state of an alloy with atomic resolution, incorporating machine learning techniques to bridge the gap between electronic-structure calculations and the characteristic length scale of SRO. The result is an approach capable of predicting SRO length scale in agreement with experimental measurements while comprehensively correlating SRO with fundamental quantities such as local lattice distortions. This work advances the quantitative understanding of solid-solution phases, paving the way for the rigorous incorporation of SRO length scales into predictive mechanical and thermodynamic models. [ABSTRACT FROM AUTHOR]

Multivalency represents an appealing option to modulate selectivity in enzyme inhibition and transform moderate glycosidase inhibitors into highly potent ones. The rational design of multivalent inhibitors is however challenging because global affinity enhancement relies on several interconnected local mechanistic events, whose relative impact is unknown. So far, the largest multivalent effects ever reported for a non‐polymeric glycosidase inhibitor have been obtained with cyclopeptoid‐based inhibitors of Jack bean α‐mannosidase (JBα‐man). Here, we report a structure‐activity relationship (SAR) study based on the top‐down deconstruction of best‐in‐class multivalent inhibitors. This approach provides a valuable tool to understand the complex interdependent mechanisms underpinning the inhibitory multivalent effect. Combining SAR experiments, binding stoichiometry assessments, thermodynamic modelling and atomistic simulations allowed us to establish the significant contribution of statistical rebinding mechanisms and the importance of several key parameters, including inhitope accessibility, topological restrictions, and electrostatic interactions. Our findings indicate that strong chelate‐binding, resulting from the formation of a cross‐linked complex between a multivalent inhibitor and two dimeric JBα‐man molecules, is not a sufficient condition to reach high levels of affinity enhancements. The deconstruction approach thus offers unique opportunities to better understand multivalent binding and provides important guidelines for the design of potent and selective multiheaded inhibitors. [ABSTRACT FROM AUTHOR]

This research article examines the effects of atomic ordering on the structural and ferroelectric properties of (Ba, Sr) TiO3 solid solutions. Using density functional theory and molecular dynamics simulations, the study investigates how the concentration and ordering of Sr atoms influence local polarization, phase stability, and field-induced switching. The results demonstrate that atomic ordering impacts the Curie temperature, polarization, and stability of ferroelectric phases. This study contributes to our understanding of how atomic ordering affects material properties and offers insights into optimizing ferroelectric phases and functional properties in nanostructures. The document also provides additional information, references, and access to supporting data for further exploration. [Extracted from the article]

This research article examines the effects of atomic ordering on the structural and ferroelectric properties of (Ba, Sr) TiO3 solid solutions. Using density functional theory and molecular dynamics simulations, the study investigates how the concentration and ordering of Sr atoms influence local polarization, phase stability, and field-induced switching. The results demonstrate that atomic ordering impacts the Curie temperature, polarization, and stability of ferroelectric phases. This study contributes to our understanding of how atomic ordering affects material properties and offers insights into optimizing ferroelectric phases and functional properties in nanostructures. The document also provides additional information, references, and access to supporting data for further exploration. [Extracted from the article]

Designing hydrogen-resistant Ni-based alloys from the perspective of the Ni/graphene interface (NGI) provides the potential to increase hydrogen trapping away from potential fracture paths. Nonetheless, numerous essential mechanisms of hydrogen penetration behaviors in the Ni-graphene nanocomposites are presently not well understood. Here we investigate the influence of Ni/graphene interfaces (NGIs) on the behavior of hydrogen diffusion and trapping in their vicinity using atomistic simulations. Hydrogen diffusion is competitively affected by elevated temperatures and NGIs. The difference in the mean square displacement for hydrogen between the composites and pure Ni can be of two orders of magnitude, highlighting the sluggish diffusion in the composites. As NGIs reduce hydrogen formation energy and diffusion barrier, hydrogen prefers to migrate towards the interfaces. Hydrogen readily forms sp3 C–H bonds with C atoms, thereby impeding its detachment from graphene and subsequent entry into a non-diffusible state. Results of the study will contribute to the use of Ni–graphene nanocomposites as hydrogen-resistant materials for nuclear reactors.

Through atomistic simulations, we uncover the dynamic properties of the Cantor alloy under shock-loading conditions and characterize its equation-of-state over a wide range of densities and pressures along with spall strength at ultra-high strain rates. Simulation results reveal the role of local phase transformations during the development of the shock wave on the alloy's high spall strength. The simulated shock Hugoniot results are in remarkable agreement with experimental data, validating the predictability of the model. These mechanistic insights along with the quantification of dynamical properties can drive further advancements in various applications of this class of alloys under extreme environments.

Pyramidal dislocations in magnesium (Mg) and other hexagonal close-packed metals play an important role in accommodating plastic strains along the c-axis. Bulk single crystal Mg only presents very limited plasticity in c-axis compression, and this behavior was attributed to out-of-plane dissociation of pyramidal dislocations onto the basal plane and resulted in an immobile dislocation configuration. In contrast, other simulations and experiments reported in-plane dissociation of pyramidal dislocations on their slip planes. Thus, the core structure and mode of dissociation of pyramidal dislocations are still not well understood. To better understand the dissociation behavior of pyramidal dislocations in Mg at room temperature, in this work, atomistic simulations were conducted to investigate four types of pyramidal dislocations at 300 K: edge and screw Py-I on {101¯1}, edge and screw Py-II on {112¯2} by using a modified embedded atom method (MEAM) potential for Mg and anisotropic elasticity dislocation model. The results show that when energy minimization was performed before relaxation, in-plane dissociation of edge dislocations on respective pyramidal plane could be obtained at room temperature for all four types of dislocation. Without energy minimization, the edge dislocations dissociated out-of-plane onto the basal plane. Calculations of potential energy and hydrostatic stress of individual atoms at the edge dislocation core show that the extraordinarily high energy and atomic stresses in the as-constructed dislocation structures caused the out-of-plane dissociation onto the basal plane. The core structures of all four types of pyramidal dislocation after in-plane dissociation were analyzed by computing the distribution of the Burgers vector.

Despite uranium dioxide (UO2) being a widely used nuclear fuel, fuel performance models rely extensively on empirical correlations of material behavior, leveraging the historical operating experience of UO2. Mechanistic models that consider an atomistic understanding of the processes governing fuel performance (such as fission gas release and creep) will enable a better description of fuel behavior under non-prototypical conditions such as in new reactor concepts or for modified UO2 fuel compositions. To this end, molecular dynamics simulation is a powerful tool for rapidly predicting physical properties of proposed fuel candidates. However, the reliability of these simulations depends largely on the accuracy of the atomic forces. Traditionally, these forces are computed using either a classical force field (FF) or density functional theory (DFT). While DFT is relatively accurate, the computational cost is burdensome, especially for f-electron elements, such as actinides. By contrast, classical FFs are computationally efficient but are less accurate. For these reasons, we report a new accurate machine learning interatomic potential (MLIP) for UO2 that provides high-fidelity reproduction of DFT forces at a similar low cost to classical FFs. We employ an active learning approach that autonomously augments the DFT training data set to iteratively refine the MLIP. To further improve the quality of our predictions, we utilize transfer learning to retrain our MLIP to higher-accuracy DFT+U data. We validate our MLIPs by comparing predicted physical properties (e.g., thermal expansion and elastic properties) with those from existing classical FFs and DFT/DFT+U calculations, as well as with experimental data when available.

Molecular chaperones, a family of proteins of which Hsp90 and Hsp70 are integral members, form an essential machinery to maintain healthy proteomes by controlling the folding and activation of a plethora of substrate client proteins. This is achieved through cycles in which Hsp90 and Hsp70, regulated by task‐specific co‐chaperones, process ATP and become part of a complex network that undergoes extensive compositional and conformational variations. Despite impressive advances in structural knowledge, the mechanisms that regulate the dynamics of functional assemblies, their response to nucleotides, and their relevance for client remodeling are still elusive. Here, we focus on the glucocorticoid receptor (GR):Hsp90:Hsp70:co‐chaperone Hop client‐loading and the GR:Hsp90:co‐chaperone p23 client‐maturation complexes, key assemblies in the folding cycle of glucocorticoid receptor (GR), a client strictly dependent upon Hsp90/Hsp70 for activity. Using a combination of molecular dynamics simulation approaches, we unveil with unprecedented detail the mechanisms that underpin function in these chaperone machineries. Specifically, we dissect the processes by which the nucleotide‐encoded message is relayed to the client and how the distinct partners of the assemblies cooperate to (pre)organize partially folded GR during Loading and Maturation. We show how different ligand states determine distinct dynamic profiles for the functional interfaces defining the interactions in the complexes and modulate their overall flexibility to facilitate progress along the chaperone cycle. Finally, we also show that the GR regions engaged by the chaperone machinery display peculiar energetic signatures in the folded state, which enhance the probability of partial unfolding fluctuations. From these results, we propose a model where a dynamic cross‐talk emerges between the chaperone dynamics states and remodeling of client‐interacting regions. This factor, coupled to the highly dynamic nature of the assemblies and the conformational heterogeneity of their interactions, provides the basis for regulating the functions of distinct assemblies during the chaperoning cycle. [ABSTRACT FROM AUTHOR]

The exceptional strength of nanolaminates is attributed to the influence of their fine stratification on the movement of dislocations. Through atomistic simulations, the impact of interfacial structure on the dynamics of an edge dislocation, which is compelled to move within a nanoscale layer of a nanolaminate, is examined for three different nanolaminates. In this study, we model confined layer slip in three structures: nanolaminated Ag and two types of Ag/Cu nanolaminates. We find that the glide motion is jerky in the presence of incoherent interfaces characterized by distinct arrays of misfit dislocations. In addition, the glide planes exhibit varying levels of resistance to dislocation motion, where planes with intersection lines that coincide with misfit dislocation lines experience greater resistance than planes without such intersection lines. [ABSTRACT FROM AUTHOR]

Size plays an important role on the deformation mechanism of nanopillars. With decreasing size, many FCC nanopillars exhibit dislocation starvation which is responsible for their high strength. However, many details about the dislocation starvation like how often it occurs, and how much is its contribution to the total plastic strain, are still elusive. Similarly, the size below which the dislocation starvation occurs is not clearly established. In this context, atomistic simulations have been performed on the compression of <110> Cu nanopillars with size (d) ranging from 5 to 21.5 nm. Molecular dynamics (MD) simulation results indicate that the nanopillars deform by the slip of extended dislocations and exhibit dislocation starvation mainly at small sizes (<20 nm). The frequency of the occurrence of dislocation starvation is highest in small-sized nanowires and it decreases with increasing size. Above the size of 20 nm, no dislocation starvation has been observed. Furthermore, we define the dislocation starvation strain and based on this, it has been shown that the contribution of the dislocation starvation to the total plastic strain decreases from 70% in small-sized nanopillars to below 5% in large-sized pillars. The present results suggest that dislocation starvation is a dominant phenomenon in small-sized nanopillars. [ABSTRACT FROM AUTHOR]

This study employs molecular dynamics simulations to explore nanoscale friction behaviour as a function of varying loading and sliding speeds on a developed top-layer articular cartilage contact interface atomistic model. To investigate nanotribological behaviour, sliding speed variations on the normal force, friction force, non-bonded interaction energy and interface temperature is obtained at the inter-cartilage interface. Analysis conducted at high velocity in a simplified tissue-like hydrated environment revealed ice-like dynamic smooth sliding behaviour of protein chains when cartilage interfaces are even 3.8 Å apart. With an increase in velocity, the coefficient of friction (COF) increases significantly in a hydrated environment. Additionally, at lower loads, the effect of sliding velocity is more pronounced than at higher loads. However, results show that articular cartilage adapts to higher load and speed sliding conditions exhibiting lower friction (COF-0.03–1.17) by means of interfacial water rearrangements and protein side-chain non-bonded interactions reducing heavy shear deformation. This is attributed to an alteration in the load-bearing and friction mechanism owing to water rearrangement and adsorption at nanoconfined biointerfaces. This study provides mechanistic insights into friction mechanisms at the cartilage interface which could lead to wear-like conditions under physiological sliding contact conditions, thereby facilitating the design of better implants. [ABSTRACT FROM AUTHOR]

Through atomistic simulations, we uncover the dynamic properties of the Cantor alloy under shock-loading conditions and characterize its equation-of-state over a wide range of densities and pressures along with spall strength at ultra-high strain rates. Simulation results reveal the role of local phase transformations during the development of the shock wave on the alloy's high spall strength. The simulated shock Hugoniot results are in remarkable agreement with experimental data, validating the predictability of the model. These mechanistic insights along with the quantification of dynamical properties can drive further advancements in various applications of this class of alloys under extreme environments. The spall behavior of Cantor alloys is mediated by a strain-rate dependent, reversible FCC-to-HCP phase transition mechanism during shock loading endowing them with high spall strength compared to conventional alloys. [ABSTRACT FROM AUTHOR]

This paper investigates the interaction of edge dislocations with voids in concentrated solid solution alloys (CSAs) using atomistic simulations. The simulation setup consists of edge dislocations with different periodicity lengths and a periodic array of voids as obstacles to dislocation motion. The critical resolved shear stress (CRSS) for dislocation motion is determined by static simulations bracketing the applied shear stress. The results show that shorter dislocation lengths and the presence of voids increase the CRSS for dislocation motion. The dislocation–void interaction is found to follow an Orowan-like mechanism, where partial dislocation arms mutually annihilate each other to overcome the void. Solute strengthening produces a 'friction stress' that adds to the Orowan stress. At variance with classical theories of solute pinning, this stress must be considered a function of the dislocation line length, in line with the idea that geometrical constraints synergetically enhance the pinning action of solutes. Modifying the equation by Bacon, Kocks and Scattergood for void strengthening to account for the solute hardening in CSAs allows one to quantitatively predict the CRSS in the presence of voids and its dependency on void spacing. The predictions show good agreement with the simulation data without invoking any fit parameters. [ABSTRACT FROM AUTHOR]