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At least 91 records · Page 5

Nitrate Reduction Modeling under Acidic Conditions with Late Transition Metals

The electrochemical reduction of nitrate (NO 3 R) to ammonia is a bold yet conceivable way of producing ammonia using renewable electricity. However, serious challenges remain in finding optimal electrocatalysts for the process. An atomistic understanding of the surface energetics behind the NO 3 R is needed in order to design an efficient catalyst. Herein, we combine energetics from density functional theory and microkinetic modeling to demonstrate how surface descriptors can help simplify the search for efficient NO 3 R electrocatalysts. We illustrate the strong correlations between transition-state energetics and O* binding energies for adsorbed nitrate and nitrite on transition metals. For intermediates from NO* and beyond, we compare the benefits of using either the N* or H* binding energies to predict reduction onset potentials. These insights enable us to develop a simple microkinetic model that elucidates the surface coverages of intermediates and the product selectivity of NO 3 R across a range of potentials and transition metals. As a result, we show that the model adequately corroborates with quasi-steady-state rates observed experimentally.

ammonia↗

Design of Atomic Ordering in Mo 2 Nb 2 C 3 T x MXenes for Hydrogen Evolution Electrocatalysis

The need for novel materials for energy storage and generation calls for chemical control at the atomic scale in nanomaterials. Ordered double-transition-metal MXenes expanded the chemical diversity of the family of atomically layered 2D materials since their discovery in 2015. However, atomistic tunability of ordered MXenes to achieve ideal composition-property relationships has not been yet possible. In this study, we demonstrate the synthesis of Mo 2+α Nb 2-α AlC 3 MAX phases (0 ≤ α ≤ 0.3) and confirm the preferential ordering behavior of Mo and Nb in the outer and inner M layers, respectively, using density functional theory, Rietveld refinement, and electron microscopy methods. We also synthesize their 2D derivative Mo 2+α Nb 2-α C 3 T x MXenes and exemplify the effect of preferential ordering on their hydrogen evolution reaction electrocatalytic behavior. In conclusion, this study seeks to inspire further exploration of the ordered double-transition-metal MXene family and contribute composition-behavior tools toward application-driven design of 2D materials.

2D materials↗

Revealing Hot and Long-Lived Metastable Spin States in the Photoinduced Switching of Solvated Metallogrid Complexes with Femtosecond Optical and X-ray Spectroscopies

An atomistic understanding of the photoinduced spin-state switching (PSS) within polynuclear systems of d 4 –d 7 transition metal ion complexes is required for their rational integration into light-driven reactions of chemical and biological interest. However, in contrast to mononuclear systems, the multidimensional dynamics of the PSS in solvated molecular arrays have not yet been elucidated due to the expected complications associated with the connectivity between the metal centers and the strong interactions with the surroundings. Herein, the PSS in a solvated triiron(II) metallogrid complex is characterized using transient optical absorption and X-ray emission spectroscopies on the femtosecond time scale. The complementary measurements reveal the photoinduced creation of energy-rich (hot) and long-lived quintet states, whose dynamics differ critically from their mononuclear congeners. We report this finding opens major prospects for developing novel schemes in solution-phase spin chemistry that are driven by the dynamic PSS process in compact oligometallic arrays.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Uniting Theory and Experiment to Deliver Flexible MOFS for Superior Methane (NG) Storage

The objective of the project was to use previous insights developed through synthesis and quantitative modeling of rigid metal–organic frameworks (MOFs) in an established synergistic theoretical/experimental team to create, modify, and evaluate flexible MOFs (FlexMOFs) for natural gas (NG) storage and release at practically useful pressures and transform the NG storage economy. The goal was reduced pressure absorbed natural gas (ANG) FlexMOF storage at operating pressures less than 100 bar with physisorption exploiting the favorable thermodynamics and kinetics of flexible porous material opening in response to adsorption. Hydrogen behavior in this context was also considered. The specific aim of the project was to design and develop a standard computational modeling methodology for, first, detailed atomistic retrodiction of FlexMOF gating behavior and ultimately prediction of the effects of functionalization and/or substitution on structural transitioning. The project was also geared towards the establishment of the interaction of methane with the framework and binding sites using modeling and the FlexMOF will be both internally and external validated as a SMART metric. This has value to the scientific community both from the obvious standpoint of providing a better understanding of the promising test case systems (CdIF-13 and the MIL-53(Al) series of MOFs), but also in providing an avenue of obtaining insight into these FlexMOF systems in general, which is of particular interest given the tendency of structure-function correlation to lag behind synthesis methodology (making the latter a hit or miss proposition for applications). This gap remains significant for FlexMOF systems whose gate opening behaviors complicate computational examination. The computational methodologies are relatively inexpensive in terms of both money and computational resources enhancing the general viability of these methodologies. The ultimate gain to the public will be in the application of these techniques to design systems for natural gas storage and use to cut down on green-house emissions.

03 NATURAL GAS↗

Irradiation-Induced Structural Disorder and Its Influence on the Mechanical Response of Polycrystalline MoS2

Molybdenum disulfide (MoS2) thin films are widely used as dry-film lubricants and protective coatings in aerospace and other radiation-exposed environments. Conventional synthesis routes produce polycrystalline films whose grain boundaries and other native defects cause their mechanical and tribological behavior to differ substantially from that of ideal single crystals. Under irradiation, these films progressively evolve from polycrystalline structures, composed of layered MoS2 grains, into highly disordered and eventually amorphous structures, altering both their tribological performance and mechanical integrity. Here, we employ reactive atomistic simulations to investigate irradiation-driven structural evolution in bulk polycrystalline MoS2. Using controlled primary knock-on atom (PKA) events, we characterize the progressive transition from a polycrystalline microstructure to an amorphous network by tracking defect accumulation and structural disorder. We then establish how this transition modifies the dominant deformation mechanisms and the temperature-dependent tensile response. Specifically, irradiation suppresses interlayer sliding and delamination, mechanisms which facilitate the deformation of the pristine polycrystal, resulting in defect-induced hardening. Broadly, our results establish direct process–structure–property relationships linking irradiation-induced defect accumulation, microstructural evolution, deformation mechanisms, and mechanical behavior, providing an atomistic framework for understanding the structural integrity and long-term reliability of irradiated MoS2 coatings.

Moore, Daniel [Sandia National Laboratories (SNL)]↗

Multiscale Molecular Dynamics Simulations: Accelerating Conformational Sampling of Biomolecular Systems by Iterating All-Atom and Coarse-Grained Simulations

We developed the atomistic-coarse-grained multiscale MD simulation method in the OpenMM simulation package by iterating between the all-atom (AA) and coarse-grained (CG) MD simulations to enhance the sampling of biomolecular conformations. As the free energy surfaces are flattened during CG MD simulations, we can accelerate the transitions between different low-energy conformations. The AA-CG-AA cycles are repeated, facilitating the accelerated sampling of biomolecular conformations at a CG level, while the finer atomistic interactions are refined with AA simulators.

Do, Hung Nguyen↗

Utilizing Oxygen Redox in Layered Cathode Materials from Multiscale Perspective

We report in high-capacity layered oxide cathode materials, utilization of lattice oxygen as a redox center is considered to be one of the most promising approaches to overcome the capacity limitation set by conventional transition metal redox centers. However, rapid material degradation is often associated with oxygen oxidation, leading to formidable challenges in utilizing oxygen redox. Further mechanistic understanding of the oxygen activities thus becomes critical to better control oxygen redox reactions. This review summarizes recent advances for investigating oxygen redox reactions in cathode materials from a multiscale perspective, i.e., from the atomistic level to the microstructure regime. First the mechanistic aspects of oxygen redox and the consequences of this reaction on various electrode degradation pathways during battery operation (e.g., oxygen loss, transition metal migration, irreversible phase transition), relating structural changes at the crystallographic scale to those at the macro scale, are discussed. Then recent developments based on atomic and microstructure modifications that are promising for improving the reversibility of oxygen redox reaction or mitigating the harmful processes arising from oxidation of the oxygen centers under high operating voltage are recounted. The analysis is concluded with a commentary on further research directions toward optimizing the oxygen activity for high-capacity charge storage.

25 ENERGY STORAGE↗

Effect of Nanoconfinement on NMR Relaxation of Heptane in Kerogen from Molecular Simulations and Measurements

Kerogen-rich shale reservoirs will play a key role during the energy transition, yet the effects of nanoconfinement on the NMR relaxation of hydrocarbons in kerogen are poorly understood. Here, we use atomistic MD simulations to investigate the effects of nanoconfinement on the 1H NMR relaxation times T 1 and T 2 of heptane in kerogen. In the case of T 1 , we discover the important role of confinement in reducing T 1 by ~3 orders of magnitude from that of bulk heptane, in agreement with measurements of heptane dissolved in kerogen from the Kimmeridge Shale, without any models or free parameters. In the case of T 2 , we discover that confinement breaks spatial isotropy and gives rise to residual dipolar coupling which reduces T 2 by ~5 orders of magnitude from the value for bulk heptane. We use the simulated T 2 to calibrate the surface relaxivity and thence predict the pore-size distribution of the organic nanopores in kerogen, without additional experimental data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Selected magnetoelectrical phonon stiffening in Cr 2 ⁢O 3

A thorough understanding of lattice dynamics, particularly how they couple with spin through spin-phonon interactions, is crucial for pioneering new spin-caloritronic applications. Here, despite extensive studies on Cr 2 ⁢O 3 , the origin of nonlinear thermal expansions and the unusual stiffening of optical phonon modes is still elusive. Through inelastic neutron scattering and atomistic calculations, we found that these behaviors can be attributed to the renormalization of electron states owing to the magnetic transition, and we ruled out the effects from thermal expansion, phonon anharmonicity, magnetostriction, or electron-phonon interactions. Importantly, our quantitative modeling suggests that the common belief that dynamic spin-phonon interactions are the origin of anomalous phonon energy stiffening in magnetic compounds does not apply in Cr 2 ⁢O 3 .

DFT+U↗

Computational Modeling and Experimental Characterization of Martensitic Transformations in Nicoal for Self-Sensing Materials

Fundamental changes to aero-vehicle management require the utilization of automated health monitoring of vehicle structural components. A novel method is the use of self-sensing materials, which contain embedded sensory particles (SP). SPs are micron-sized pieces of shape-memory alloy that undergo transformation when the local strain reaches a prescribed threshold. The transformation is a result of a spontaneous rearrangement of the atoms in the crystal lattice under intensified stress near damaged locations, generating acoustic waves of a specific spectrum that can be detected by a suitably placed sensor. The sensitivity of the method depends on the strength of the emitted signal and its propagation through the material. To study the transition behavior of the sensory particle inside a metal matrix under load, a simulation approach based on a coupled atomistic-continuum model is used. The simulation results indicate a strong dependence of the particle's pseudoelastic response on its crystallographic orientation with respect to the loading direction and suggest possible ways of optimizing particle sensitivity. The technology of embedded sensory particles will serve as the key element in an autonomous structural health monitoring system that will constantly monitor for damage initiation in service, which will enable quick detection of unforeseen damage initiation in real-time and during onground inspections.

Wallace, T. A.↗

A molecular dynamics study of laser-excited gold

The structural evolution of laser-excited systems of gold has previously been measured through ultrafast MeV electron diffraction. However, there has been a long-standing inability of atomistic simulations to provide a consistent picture of the melting process, leading to large discrepancies between the predicted threshold energy density for complete melting, as well as the transition between heterogeneous and homogeneous melting. We make use of two-temperature classical molecular dynamics simulations utilizing three highly successful interatomic potentials and reproduce electron diffraction data presented by Mo et al. [Science 360, 1451–1455 (2018)]. We recreate the experimental electron diffraction data, employing both a constant and temperature-dependent electron–ion equilibration rate. In all cases, we are able to match time-resolved electron diffraction data, and find consistency between atomistic simulations and experiments, only by allowing laser energy to be transported away from the interaction region. This additional energy-loss pathway, which scales strongly with laser fluence, we attribute to hot electrons leaving the target on a timescale commensurate with melting.

36 MATERIALS SCIENCE↗

Multiscale Modeling of Vinyl-Addition Polynorbornenes: The Effect of Stereochemistry

Vinyl-addition polynorbornenes are candidates for designing high-performance polymers due to unique characteristics, which include a high glass transition temperature associated with a rigid backbone. Recent studies have established that the processability and properties of these polymers can be fine-tuned by using targeted substitutions. However, synthesis with different catalysts results in materials with distinct properties, potentially due to the presence of various stereoisomers that are difficult to quantify experimentally. Herein, we develop all-atom models of polynorbornene oligomers based on classical force fields and density functional theory. To establish the relationship between chemical architecture, chain conformations, and melt structure, we perform detailed molecular dynamics simulations with the fine-tuned atomistic force field and propose simpler coarse-grained descriptions to address the high molecular weight limit. All-atom simulations of oligomers suggest high glass transition temperatures in the range of 550–600 K. In the melt state (800 K), meso chains form highly rigid extended coils (C∞≈11) with amorphous structural characteristics similar to the X-ray diffraction data observed in the literature. In contrast, simulations with racemo chains predict highly helical tubular chain conformations that could promote assembly into crystalline structures.

Polymer Science↗

Computational Prediction of Coiled–Coil Protein Gelation Dynamics and Structure

Protein hydrogels represent an important and growing biomaterial for a multitude of applications, including diagnostics and drug delivery. We have previously explored the ability to engineer the thermoresponsive supramolecular assembly of coiled–coil proteins into hydrogels with varying gelation properties, where we have defined important parameters in the coiled–coil hydrogel design. Using Rosetta energy scores and Poisson–Boltzmann electrostatic energies, we iterate a computational design strategy to predict the gelation of coiled–coil proteins while simultaneously exploring five new coiled–coil protein hydrogel sequences. Provided this library, we explore the impact of in silico energies on structure and gelation kinetics, where we also reveal a range of blue autofluorescence that enables hydrogel disassembly and recovery. As a result of this library, we identify the new coiled–coil hydrogel sequence, Q5, capable of gelation within 24 h at 4 °C, a more than 2-fold increase over that of our previous iteration Q2. The fast gelation time of Q5 enables the assessment of structural transition in real time using small-angle X-ray scattering (SAXS) that is correlated to coarse-grained and atomistic molecular dynamics simulations revealing the supramolecular assembling behavior of coiled–coils toward nanofiber assembly and gelation. This work represents the first system of hydrogels with predictable self-assembly, autofluorescent capability, and a molecular model of coiled–coil fiber formation.

36 MATERIALS SCIENCE↗

Low-energy electronic structure of perovskite and Ruddlesden-Popper semiconductors in the Ba-Zr-S system probed by bond-selective polarized x-ray absorption spectroscopy, infrared reflectivity, and Raman scattering

Chalcogenides in perovskite and the related layered Ruddlesden-Popper crystal structures ( chalcogenide perovskites for brevity) are an exciting family of semiconductors but remain experimentally little studied. Chalcogenide perovskites share crystal structures and some physical properties with ionic compounds such as oxide and halide perovskites, but the metal-chalcogen bonds responsible for semiconducting behavior are substantially more covalent than in these more-studied perovskites. In this study, we use complementary experimental and theoretical methods to study how the mixed ionic-covalent Zr-S bonds support the electronic structure and physical properties of perovskite BaZrS 3 and Ruddlesden-Popper Ba 3 Zr 2 S 7 . We apply theoretical methods to assign features of experimentally measured x-ray absorption spectroscopy (XAS) to particular orbital transitions, enabling a clear physical interpretation of angle-dependent, polarized XAS data measured on single-crystal samples, and an atomistic view of the covalent bonding network that facilitates charge transport. Polarized Raman measurements identify signatures of crystalline anisotropy in Ba 3 Zr 2 S 7 and enable the first assignments of mode symmetry in this material. Infrared reflectivity reveals electronic transport properties that augur well for the use of chalcogenide perovskites in optoelectronic and energy-conversion technologies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing

Neuromorphic computing inspired by mammalian intelligence aims to emulate the nonlinear dynamics of biological neurons and synapses to achieve fast, low-energy, and highly efficient information processing. Brain-inspired computing relies on the design and discovery of materials exhibiting nonlinear current–voltage profiles, frequently underpinned by electronic state transitions, to achieve spiking neurons and dynamically tunable synapses. A signature challenge in the design of artificial neurons is controlling the steepness of first-order transitions in active elements, as abrupt transitions are at risk of driving unstable voltage and temperature oscillations, which result in catastrophic device failure. A critical knowledge gap is the lack of structure–function correlations mapping the composition and atomistic structure of crystalline solids to nonlinear dynamical response characteristics. Here, we address the key question of how modification of atomistic structure correlates with alteration of neuron-like functionality. Constructing oscillator circuits from millimeter-scale single crystals enables high-resolution atomic structure solutions, which we use to demonstrate that the selective positioning of Pb cations modifies charge ordering along a one-dimensional CuxV2O5 framework even at low insertion stoichiometries, thereby providing an atom-precise design parameter for damping first-order transitions. We use temperature-variant X-ray diffraction and X-ray spectroscopy to elucidate the suppression of Cu-ion shuttling based on the precise positioning of Pb ions in seven-coordinated tunnel interstitial sites as the mechanistic basis for transition broadening, thus bridging a critical gap between statistical mechanics and quantum chemical descriptions of phase transitions. Such mechanistic understanding thus paves the way to site-selective modification strategies for modulating the sharpness of first-order transitions, with an exemplary demonstration here in tuning neuronal signal processing.

Crystal structure↗

Impurity induced confinement effects in size-separated Mn-doped CsPbCl 3 nanocrystals

Beyond quantum confinement, impurity doping of semiconductor nanocrystals (NCs) offers a degree of control over their optical and electronic properties, which are of interest for potential applications. Manganese (Mn)-doped CsPbCl 3 NCs, for example, show synergistic effects in the visible, with large enhancements in both blue (exciton) and red (dopant) emission over a narrow range of dopant concentration. Although Mn concentration is the primary parameter, NC size offers an additional degree of control over the number of dopants per NC. Size-resolved CsPbCl 3 NCs prepared in the limit of strong Mn doping highlight the emergence of defective NCs with deviations from anticipated confinement trends. In conclusion, the transition correlates with a redshift and increase in the amplitude of dopant emission, and we discuss these observations in the context of atomistic simulations of Ruddlesden-Popper defects in CsPbCl 3 .

36 MATERIALS SCIENCE↗

Kinetics of Carbon Condensation in Detonation of High Explosives: First-Order Phase Transition Theory Perspective

We report the kinetics of carbon condensation, or carbon clustering, in detonation of carbon-rich high explosives is modeled by solving a system of rate equations for concentrations of carbon particles. Unlike previous efforts, the rate equations account not only for the aggregation of particles but also for their fragmentation in a thermodynamically consistent manner. Numerical simulations are performed, yielding the distribution of particle concentrations as a function of time. In addition to that, analytical expressions are obtained for all the distinct steps and regimes of the condensation kinetics, which facilitates the analysis of the numerical results and allows one to study the sensitivity of the kinetic behavior to the variation of system parameters. The latter is important because the numerical values of many parameters are not reliably known at present. The theory of the kinetics of first-order phase transitions is found adequate to describe the general kinetic trends of carbon condensation, as described by the rate equations. Such physical phenomena and processes as the coagulation, nucleation, growth, and Ostwald ripening are observed, and their dependence on various system parameters is studied and reported. It is believed that the present work will become useful when analyzing the present and future results for the kinetics of carbon condensation, obtained from experiments or atomistic simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiscale, mechanistic modeling of cesium transport in silicon carbide for TRISO fuel performance prediction

Understanding cesium (Cs) transport in TRistructural ISOtropic (TRISO) particle fuel is crucial for predicting fission product release in high-temperature reactors. However, current challenges include significant scatter in diffusivity data and unexplained temperature-dependent diffusion regimes in the silicon carbide layer. This study addresses these challenges by developing a multiscale, mechanistic Cs transport model integrating atomistic simulations and phase field modeling. Our model quantifies temperature and grain size effects on Cs diffusivity, attributing experimentally observed regimes to a transition from bulk-dominated diffusivity at high temperatures to grain boundary-dominated diffusivity at lower temperatures. The model, validated against diffusion measurements and advanced gas reactor (AGR)-1 and AGR-2 post-irradiation fission product release data, enhances the predictive capability of the BISON fuel performance code. This study advances our understanding of Cs release from TRISO particles and its dependence on temperature and silicon carbide grain size, with implications for the safety and efficiency of high-temperature nuclear reactors.

BISON↗