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At least 73 records · Page 4

Screening of bimetallic electrocatalysts for water purification with machine learning

Electrocatalysis provides a potential solution to NO 3 - pollution in wastewater by converting it to innocuous N 2 gas. However, materials with excellent catalytic activity are typically limited to expensive precious metals, hindering their commercial viability. Here, in response to this challenge, we have conducted the most extensive computational search to date for electrocatalysts that can facilitate NO 3 - reduction reaction, starting with 59 390 candidate bimetallic alloys from the Materials Project and Automatic-Flow databases. Using a joint machine learning- and computation-based screening strategy, we evaluated our candidates based on corrosion resistance, catalytic activity, N 2 selectivity, cost, and the ability to synthesize. We found that only 20 materials will satisfy all criteria in our screening strategy, all of which contain varying amounts of Cu. Our proposed list of candidates is consistent with previous materials investigated in the literature, with the exception of Cu–Co and Cu–Ag based compounds that merit further investigation.

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Chemical reactivity under collective vibrational strong coupling

Recent experiments of chemical reactions in optical cavities have shown great promise to alter and steer chemical reactions, but still remain poorly understood theoretically. In particular, the origin of resonant effects between the cavity and certain vibrational modes in the collective limit is still subject to active research. In this paper, we study the unimolecular dissociation reactions of many molecules, collectively interacting with an infrared cavity mode, through their vibrational dipole moment. We find that the reaction rate can slow down by increasing the number of aligned molecules, if the cavity mode is resonant with a vibrational mode of the molecules. We also discover a simple scaling relation that scales with the collective Rabi splitting, to estimate the onset of reaction rate modification by collective vibrational strong coupling and numerically demonstrate these effects for up to 10 4 molecules.

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Probing time-resolved plasma-driven solution electrochemistry in a falling liquid film plasma reactor: Identification of HO$^−_2$ as a plasma-derived reducing agent

Many applications involving plasma–liquid interactions depend on the reactive processes occurring at the plasma–liquid interface. In this article, we report on a falling liquid film plasma reactor allowing for in situ optical absorption measurements of the time-dependence of the ferricyanide/ferrocyanide redox reactivity, complemented with ex situ measurement of the decomposition of formate. We found excellent agreement between the measured decomposition percentages and the diffusion-limited decomposition of formate by interfacial plasma-enabled reactions, except at high pH in thin liquid films, indicating the involvement of previously unexplored plasma-induced liquid phase chemistry enabled by long-lived reactive species. We also determined that high pH facilitates a reduction-favoring environment in ferricyanide/ferrocyanide redox solutions. In situ conversion measurements of a 1:1 ferricyanide/ferrocyanide redox mixture exceed the measured ex situ conversion and show that conversion of a 1:1 ferricyanide/ferrocyanide mixture is strongly dependent on film thickness. We identified three dominant processes: reduction faster than ms time scales for film thicknesses >100 µm, •OH-driven oxidation on time scales of <10 ms, and reduction on 15 ms time scales for film thickness <100 µm. We attribute the slow reduction and larger formate decomposition at high pH to HO$^−_2$ formed from plasma-produced H 2 O 2 enabled by the high pH at the plasma–liquid interface as confirmed experimentally and by computed reaction rates of HO$^−_2$ with ferricyanide. Overall, this work demonstrates the utility of liquid film reactors in enabling the discovery of new plasma-interfacial chemistry and the utility of atmospheric plasmas for electrodeless electrochemistry.

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Physics through the 1990s: Atomic, molecular and optical physics

The volume presents a program of research initiatives in atomic, molecular, and optical physics. The current state of atomic, molecular, and optical physics in the US is examined with respect to demographics, education patterns, applications, and the US economy. Recommendations are made for each field, with discussions of their histories and the relevance of the research to government agencies. The section on atomic physics includes atomic theory, structure, and dynamics; accelerator-based atomic physics; and large facilities. The section on molecular physics includes spectroscopy, scattering theory and experiment, and the dynamics of chemical reactions. The section on optical physics discusses lasers, laser spectroscopy, and quantum optics and coherence. A section elucidates interfaces between the three fields and astrophysics, condensed matter physics, surface science, plasma physics, atmospheric physics, and nuclear physics. Another section shows applications of the three fields in ultra-precise measurements, fusion, national security, materials, medicine, and other topics.

Source record↗

Robo-line storage: Low latency, high capacity storage systems over geographically distributed networks

Rapid advances in high performance computing are making possible more complete and accurate computer-based modeling of complex physical phenomena, such as weather front interactions, dynamics of chemical reactions, numerical aerodynamic analysis of airframes, and ocean-land-atmosphere interactions. Many of these 'grand challenge' applications are as demanding of the underlying storage system, in terms of their capacity and bandwidth requirements, as they are on the computational power of the processor. A global view of the Earth's ocean chlorophyll and land vegetation requires over 2 terabytes of raw satellite image data. In this paper, we describe our planned research program in high capacity, high bandwidth storage systems. The project has four overall goals. First, we will examine new methods for high capacity storage systems, made possible by low cost, small form factor magnetic and optical tape systems. Second, access to the storage system will be low latency and high bandwidth. To achieve this, we must interleave data transfer at all levels of the storage system, including devices, controllers, servers, and communications links. Latency will be reduced by extensive caching throughout the storage hierarchy. Third, we will provide effective management of a storage hierarchy, extending the techniques already developed for the Log Structured File System. Finally, we will construct a protototype high capacity file server, suitable for use on the National Research and Education Network (NREN). Such research must be a Cornerstone of any coherent program in high performance computing and communications.

Katz, Randy H.↗

Controlled Reaction Dynamics of Binary Hexafluorides to Explore New Chemical Signatures

Conclusions • Successfully halted the UF6 hydrolysis reaction and trapped intermediate complexes • Simple alcohol instead of water leads to shifting of bands in UF6 likely from change in matrix effects • MoF6 reaction shows some potential for methyl group being present in structure of intermediates • Future work with bulkier R-groups will hopefully reveal further information as to the reaction pathway and intermediate structure via kinetics and peak shifting

Dorris, Austin L. [Savannah River National Laborat↗

Large-scale atomistic model construction of subbituminous and bituminous coals for solvent extraction simulations with reactive molecular dynamics

Large-scale atomistic models for complex polycyclic aromatic hydrocarbon systems help understand the chemical properties and behaviors of complex feedstocks such as coal or petroleum. However, the development and utilization of large-scale models remain limited due to the difficulty in achieving the varied structural characteristics necessary to capture stochastic nature of these feedstocks. Here we demonstrate a systematic workflow to construct stochastic molecular systems from a broad analytical suite: high-resolution transmission electron microscopy (HRTEM), carbon-13 nuclear magnetic resonance spectroscopy ( 13 C NMR), laser desorption ionization mass spectroscopy (LDI-MS), and elemental analysis. We present a model construction and analysis utility of a new Python-based module. We selected one subbituminous and three high-volatile bituminous coals to construct large-scale models (~40,000 atoms). The constructed models were utilized to examine the affinity for solvent extraction (naphthalene or tetralin) and the effect of structural properties (e.g., aromatic cluster size, functional groups, and cross-linking) in reactive molecular dynamics simulations. Complex chemical reactions were monitored with bond order transitions, intermediates formation, and mass distributions. Reactive molecular dynamics simulations suggest a plausible chemical extraction process and products for the complex fossil feedstocks. The results indicated that radical formations with bond breaking of bridging oxygens and carbons were required at high temperatures to facilitate hydrogeneration and extraction of gas molecules from radical-free molecules. We observed that aliphatic chains of tetralin were easily decomposed and combined with radicals to form small size of molecules with aryl bonding, mainly increasing molecules in the 500–1000 Da, while naphthalene had little impact on chemical extraction process.

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Graph characterization of higher-order structure in atmospheric chemical reaction mechanisms

Atmospheric chemical reactions play an important role in air quality and climate change. While the structure and dynamics of individual chemical reactions are fairly well understood, the emergent properties of the entire atmospheric chemical system, which can involve many different species that participate in many different reactions, are not well described. In this work, we leverage graph-theoretic techniques to characterize patterns of interaction (“motifs”) in three different representations of gas-phase atmospheric chemistry, termed “chemical mechanisms.” These widely used mechanisms, the master chemical mechanism, the GEOS-Chem mechanism, and the Super-Fast mechanism, vary dramatically in scale and application, but they all generally aim to simulate the abundance and variability of chemical species in the atmosphere. This motif analysis quantifies the fundamental patterns of interaction within the mechanisms, which are directly related to their construction. For example, the gas-phase chemistry in the very small Super-Fast mechanism is entirely composed of bimolecular reactions, and its motif distribution matches that of an individual bimolecular reaction well. The larger and more complex mechanisms show emergent motif distributions that differ strongly from any specific reaction type, consistent with their complexity. The proposed motif analysis demonstrates that while these mechanisms all have a similar design goal, their higher-order structure of interactions differs strongly and thus provides a novel set of tools for exploring differences across chemical mechanisms.

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Chemo‐Mechanical Coupling in Hydrogels: Dynamics in the Diffusion‐Limited Regime

Hydrogels are characterized by substantial volume changes in response to external stimuli, making them promising candidates for developing smart materials with enhanced adaptability and responsiveness. By integrating chemical reactions, hydrogels acquire dynamic and tunable responsiveness to external stimuli through chemo‐mechanical coupling, expanding their potential in emerging applications. However, capturing their transient behavior remains challenging due to the complex interplay of chemical reactions, solvent transport, and polymer network deformation. Classical theories capture equilibrium swelling but fail to describe time‐dependent phenomena. To address this, a time‐dependent continuum model is developed that explicitly couples these processes. Volume phase transition in hydrogels with homogeneous chemical reactions is investigated, then the effects of reaction kinetics on these transitions are analyzed. The coupling of these mechanisms is further explored through a study of transient mechanical instabilities. To illustrate the impact of distinct reaction and diffusion timescales, a photo‐active gripper is studied for robotic applications. Finally, a photo‐active microswimmer that exhibits non‐reciprocal motion is proposed to highlight the solvent diffusion for locomotion at the micro‐ and nano‐ scales. The work establishes that transient dynamics of chemo‐mechanical hydrogels generate functions not accessible by steady state models and provides a predictive platform for designing adaptive materials in emerging applications.

chemo-mechanical coupling↗

Isolating Chemical Reaction Mechanism as a Variable with Reactive Coarse-Grained Molecular Dynamics: Step-Growth versus Chain-Growth Polymerization

Here we present a general approach to isolate chemical reaction mechanism as an independently controllable variable across chemically distinct systems. Modern approaches to reduce the computational expense of molecular dynamics simulations often group multiple atoms into a single “coarse-grained” interaction site, which leads to a loss of chemical resolution. In this work we convert this shortcoming into a feature and use identical coarse-grained models to represent molecules that share nonreactive characteristics but react by different mechanisms. As a proof of concept, we use this approach to simulate and investigate distinct, yet similar, trifunctional isocyanurate resin formulations that polymerize by either chain- or step-growth. Because the underlying molecular mechanics of these models are identical, all emergent differences are a function of the reaction mechanism only. We find that the microscopic morphologies resemble related all-atom simulations and that simulated mechanical testing reasonably agrees with experiment.

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Efficient fully-coherent quantum signal processing algorithms for real-time dynamics simulation

Simulating the unitary dynamics of a quantum system is a fundamental problem of quantum mechanics, in which quantum computers are believed to have significant advantage over their classical counterparts. One prominent such instance is the simulation of electronic dynamics, which plays an essential role in chemical reactions, non-equilibrium dynamics, and material design. These systems are time-dependent, which requires that the corresponding simulation algorithm can be successfully concatenated with itself over different time intervals to reproduce the overall coherent quantum dynamics of the system. In this paper, we quantify such simulation algorithms by the property of being fully-coherent: the algorithm succeeds with arbitrarily high success probability 1 − δ while only requiring a single copy of the initial state. Here we subsequently develop fully-coherent simulation algorithms based on quantum signal processing (QSP), including a novel algorithm that circumvents the use of amplitude amplification while also achieving a query complexity additive in time t, ln(1/δ), and ln(1/ϵ) for error tolerance ϵ: $Θ‖\mathscr{H}‖|t|+ln(1/ϵ)+ln(1/δ)$. Furthermore, we numerically analyze these algorithms by applying them to the simulation of the spin dynamics of the Heisenberg model and the correlated electronic dynamics of an H2 molecule. Since any electronic Hamiltonian can be mapped to a spin Hamiltonian, our algorithm can efficiently simulate time-dependent ab initio electronic dynamics in the circuit model of quantum computation. Accordingly, it is also our hope that the present work serves as a bridge between QSP-based quantum algorithms and chemical dynamics, stimulating a cross-fertilization between these exciting fields.

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Energy and chemical reaction. I

Reagent translational energy effect on dynamics of ionic and atomic reactions, using nuclear recoil and chemical accelerator methods

Wolfgang, R.↗

Modeling prebiotic chemistries with quantum accuracy at classical costs

Molecular Dynamics (MD) simulations using classical force-fields are commonly employed in numerous scientific investigations. However, many natural processes involve bond breaking and quantum forces. This complexity is compounded by the presence of multiple competing length and timescales. For example, accurately modeling the thermodynamics and dynamics of a chemical reaction requires accounting for the concerted movements of numerous solvent molecules and ions with their own fast or slow timescales. While widely used static Density Functional Theory (DFT) calculations at 0 temperature can be beneficial for such investigations, they do not account for dynamics, and lack precision in describing the molecular environments. They particularly fail at correct, rigorous treatments of finite-temperature fluctuations, and thus generalization to experimentally relevant conditions. In PNAS Benayad et al develop a scalable, generalizable approach for designing Neural Network Potentials (NNPs) that can handle chemical reactivity in solvated systems with quantum accuracy at classical costs. Specifically, they study phosphoester bond formation and rupture, which is fundamentally relevant to the Phosphorus-Oxygen bond formation central to life, and especially for the RNA world hypothesis. The framework developed here has the potential to generalize to different chemical reactions of energy and biological relevance.

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Controlled Reaction Dynamics of Binary Hexafluorides to Explore New Chemical Signatures

Uranium hexafluoride (UF6 ) is a key compound in the nuclear fuel cycle. • Many enrichment technologies utilize UF6 due to its advantageous properties: • Fluorine (F) has only one isotope of major abundance. • UF6 is a solid at room temperature but has a high (~70 torr) vapor pressure. • There is significant knowledge regarding the chemical processing of UF6 . • UF6 readily hydrolyzes when released to the atmosphere. • Despite significant advances in UF6 processing, the fundamental chemistry governing reaction with UF6 is still poorly understood.

Dorris, Austin L. [Savannah River National Laborat↗

Development of a Computational Chemical Vapor Deposition Model: Applications to Indium Nitride and Dicyanovinylaniline

A computational chemical vapor deposition (CVD) model is presented, that couples chemical reaction mechanisms with fluid dynamic simulations for vapor deposition experiments. The chemical properties of the systems under investigation are evaluated using quantum, molecular and statistical mechanics models. The fluid dynamic computations are performed using the CFD-ACE program, which can simulate multispecies transport, heat and mass transfer, gas phase chemistry, chemistry of adsorbed species, pulsed reactant flow and variable gravity conditions. Two experimental setups are being studied, in order to fabricate films of: (a) indium nitride (InN) from the gas or surface phase reaction of trimethylindium and ammonia; and (b) 4-(1,1)dicyanovinyl-dimethylaminoaniline (DCVA) by vapor deposition. Modeling of these setups requires knowledge of three groups of properties: thermodynamic properties (heat capacity), transport properties (diffusion, viscosity, and thermal conductivity), and kinetic properties (rate constants for all possible elementary chemical reactions). These properties are evaluated using computational methods whenever experimental data is not available for the species or for the elementary reactions. The chemical vapor deposition model is applied to InN and DCVA. Several possible InN mechanisms are proposed and analyzed. The CVD model simulations of InN show that the deposition rate of InN is more efficient when pulsing chemistry is used under conditions of high pressure and microgravity. An analysis of the chemical properties of DCVA show that DCVA dimers may form under certain conditions of physical vapor transport. CVD simulations of the DCVA system suggest that deposition of the DCVA dimer may play a small role in the film and crystal growth processes.

Cardelino, Carlos↗

CO 2 Adsorption and Hydrogenation on Inverse InO x /Cu(111) Catalysts: Active Role of the Oxide–Metal Interface

The direct conversion of carbon dioxide (CO 2 ) into methanol via hydrogenation is essential for industrial applications. Recent studies on catalysts that contain an inverse oxide/metal configuration have shown very good catalytic performance for the CO 2 hydrogenation to methanol process. Here, in this study, we investigated the behavior of indium oxide-Cu(111) interfaces under pure CO 2 and CO 2 /H 2 mixtures using synchrotron-based ambient-pressure X-ray photoelectron spectroscopy (AP-XPS). Initially, a single layer of copper oxide (Cu x O) was grown on the Cu(111) surface by controlled oxidation. On this surface, indium was deposited at room temperature. Oxygen atoms transferred from Cu x O/Cu(111) to the indium metal upon deposition, forming In-O-Cu bonds and active interfaces. Although Cu(111) is not very active for the binding and activation of CO 2 , the formed InO x -Cu(111) interfaces had no problem adsorbing and dissociating the molecule at room temperature. Reaction of CO 2 with H 2 on InO x -Cu(111) yielded surface-bound H 3 CO, CO 2 δ− , CO 3 , and CH x species that are typical intermediates in the production of methanol and other oxygenates. The InO x -Cu(111) interface underwent dynamic chemical changes under reaction conditions, forming In-Cu alloys at low indium coverages (< 0.05 monolayer), while at higher indium coverages a mixture of an In-Cu and InO x was detected in XPS. These findings indicate that InO x /In-Cu interfaces can play a key role in processes aimed at the trapping and valorization of CO 2 .

36 MATERIALS SCIENCE↗

Femtosecond intramolecular rearrangement of the CH 3 NCS radical cation

Strong-field ionization, involving tunnel ionization and electron rescattering, enables femtosecond time-resolved dynamics measurements of chemical reactions involving radical cations. Here, we compare the formation of CH 3 S + following the strong-field ionization of the isomers CH 3 SCN and CH 3 NCS. The former involves the release of neutral CN, while the latter involves an intramolecular rearrangement. Here, we find the intramolecular rearrangement takes place on a single picosecond timescale and exhibits vibrational coherence. Density functional theory and coupled-cluster calculations on the neutral and singly ionized species help us determine the driving force responsible for intramolecular rearrangement in CH 3 NCS. Our findings illustrate the complexity that accompanies radical cation chemistry following electron ionization and demonstrate a useful tool for understanding cation dynamics after ionization.

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