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At least 1,621 records · Page 90

The advancing wave front on a sloping channel covered by a rod canopy following an instantaneous dam break

The drag coefficient Cd for a rigid and uniformly distributed rod canopy covering a sloping channel following the instantaneous collapse of a dam was examined using flume experiments. The measurements included space x and time t high resolution images of the water surface h(x, t) for multiple channel bed slopes So and water depths behind the dam Ho along with drag estimates provided by sequential load cells. Using these data, an analysis of the Saint-Venant equation (SVE) for the front speed was conducted using the diffusive wave approximation. An inferred Cd=0.4 from the h(x, t) data near the advancing front region, also confirmed by load cell measurements, is much reduced relative to its independently measured steady-uniform flow case. This finding suggests that drag reduction mechanisms associated with transients and flow disturbances are more likely to play a dominant role when compared to conventional sheltering or blocking effects on Cd examined in uniform flow. The increased air volume entrained into the advancing wave front region as determined from an inflow–outflow volume balance partly explains the Cd reduction from unity.

Mechanics↗

Design and modeling of indirectly driven magnetized implosions on the NIF

The use of magnetic fields to improve the performance of hohlraum-driven implosions on the National Ignition Facility (NIF) is discussed. The focus is on magnetically insulated inertial confinement fusion, where the primary field effect is to reduce electron-thermal and alpha-particle loss from the compressed hotspot (magnetic pressure is of secondary importance). We summarize the requirements to achieve this state. The design of recent NIF magnetized hohlraum experiments is presented. These are close to earlier shots in the three-shock, high-adiabat (BigFoot) campaign, subject to the constraints that magnetized NIF targets must be fielded at room-temperature, and use ≲1 MJ of laser energy to avoid the risk of optics damage from stimulated Brillouin scattering. We present results from the original magnetized hohlraum platform, as well as a later variant that gives a higher hotspot temperature. In both platforms, imposed fields (at the capsule center) of up to 28 T increase the fusion yield and hotspot temperature. Integrated radiation-magneto-hydrodynamic modeling with the Lasnex code of these shots is shown, where laser power multipliers and a saturation clamp on cross-beam energy transfer are developed to match the time of peak capsule emission and the P2 Legendre moment of the hotspot x-ray image. The resulting fusion yield and ion temperature agree decently with the measured relative effects of the field, although the absolute simulated yields are higher than the data by 2.0−2.7×. The tuned parameters and yield discrepancy are comparable for experiments with and without an imposed field, indicating the model adequately captures the field effects. Self-generated and imposed fields are added sequentially to simulations of one BigFoot NIF shot to understand how they alter target dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Tracking ultrafast non-adiabatic dissociation dynamics of the deuterated water dication molecule

Here, we applied reaction microscopy to elucidate fast non-adiabatic dissociation dynamics of deuterated water molecules after direct photo-double ionization at 61 eV with synchrotron radiation. For the very rare D + + O + + D breakup channel, the particle momenta, angular, and energy distributions of electrons and ions, measured in coincidence, reveal distinct electronic dication states and their dissociation pathways via spin–orbit coupling and charge transfer at crossings and seams on the potential energy surfaces. Notably, we could distinguish between direct and fast sequential dissociation scenarios. For the latter case, our measurements reveal the geometry and orientation of the deuterated water molecule with respect to the polarization vector that leads to this rare 3-body molecular breakup channel. Aided by multi-reference configuration-interaction calculations, the dissociation dynamics could be traced on the relevant potential energy surfaces and particularly their crossings and seams. This approach also unraveled the ultrafast time scales governing these processes.

74 ATOMIC AND MOLECULAR PHYSICS↗

A circuit-generated quantum subspace algorithm for the variational quantum eigensolver

Recent research has shown that wavefunction evolution in real and imaginary time can generate quantum subspaces with significant utility for obtaining accurate ground state energies. Inspired by these methods, we propose combining quantum subspace techniques with the variational quantum eigensolver (VQE). In our approach, the parameterized quantum circuit is divided into a series of smaller subcircuits. The sequential application of these subcircuits to an initial state generates a set of wavefunctions that we use as a quantum subspace to obtain high-accuracy groundstate energies. We call this technique the circuit subspace variational quantum eigensolver (CSVQE) algorithm. By benchmarking CSVQE on a range of quantum chemistry problems, we show that it can achieve significant error reduction in the best case compared to conventional VQE, particularly for poorly optimized circuits, greatly improving convergence rates. Furthermore, we demonstrate that when applied to circuits trapped at local minima, CSVQE can produce energies close to the global minimum of the energy landscape, making it a potentially powerful tool for diagnosing local minima.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Entanglement engineering of optomechanical systems by reinforcement learning

Entanglement is fundamental to quantum information science and technology, yet controlling and manipulating entanglement—so-called entanglement engineering—for arbitrary quantum systems remains a formidable challenge. There are two difficulties: the fragility of quantum entanglement and its experimental characterization. We develop a model-free deep reinforcement-learning (RL) approach to entanglement engineering, in which feedback control together with weak continuous measurement and partial state observation is exploited to generate and maintain desired entanglement. We employ quantum optomechanical systems with linear or nonlinear photon–phonon interactions to demonstrate the workings of our machine-learning-based entanglement engineering protocol. In particular, the RL agent sequentially interacts with one or multiple parallel quantum optomechanical environments, collects trajectories, and updates the policy to maximize the accumulated reward to create and stabilize quantum entanglement over an arbitrary amount of time. The machine-learning-based model-free control principle is applicable to the entanglement engineering of experimental quantum systems in general.

97 MATHEMATICS AND COMPUTING↗

Temperature effects of ion irradiation on the nanostructural features in ductile-phase-toughened tungsten composites

Ductile-phase toughened tungsten (DPT W) composites have emerged as promising candidates for load-bearing components behind the plasma-facing tungsten armor in fusion reactors due to their enhanced thermomechanical properties. This study focuses on a composite consisting of W particles embedded in a ductile NiFeW solution matrix, hot-rolled to a thickness reduction of 87% (87R DPT W). Sequential irradiations with Ni2+ and He+ ions were performed to identical doses and helium concentrations at room temperature (RT) and 1273 K. Irradiation at RT produced no discernible nanostructural features due to the immobility of mono-vacancies, whereas cavity formation was observed at 973 K. At 1273 K, the W phase exhibited larger cavities, reduced cavity number density, and lower volumetric swelling compared to 973 K. Notably, nanosized NiFeW precipitates formed within the W phase at 1273 K, a phenomenon absent at 973 K. A new phase of cubic (NiFe)6W6C was also observed at the interphase boundary. In contrast, the NiFeW matrix showed no nanostructural changes at 1273 K, likely due to cavity dissociation. Separate irradiations at 1273 K indicated that Ni2+ ions induced precipitate formation in the W phase, while He+ ions exclusively caused cavity formation. The microstructure of 87R DPT W irradiated at RT and subsequently annealed at 1273 K closely resembled that of material irradiated directly at 1273 K. Like oxide-dispersion-strengthened steels, the observed nanoparticle-embedded W can inhibit dislocation propagation, potentially delaying the ductile-to-brittle transition temperature. These findings highlight the potential of NiFeW nanoparticle-reinforced W composites as irradiation-resistant materials for fusion reactors.

Jiang, Weilin (ORCID:0000000183028313)↗

Finite-element-based simulations of electrodes for CO 2 cascade reduction reactions

The multielectron reduction of CO 2 to liquid fuels could be a path to scalable energy storage, but reaching this goal requires major advances in catalysis and systems engineering. Cascade catalysis, which couples sequential reactions without isolating intermediates, has emerged as a promising route to enhance selectivity and efficiency in CO 2 reduction (CO 2 R). In this review, we examine how finite-element-based simulations of continuum model [finite element method (FEM)] approaches are being used to analyze and guide CO 2 R cascade systems. We first outline the fundamentals of cascade catalysis and recent advances in catalytic materials (metallic, molecular, and hybrid architectures). We then focus on FEM developments at the electrode and device scales, emphasizing how these models capture transport phenomena, local microenvironments, and geometry-dependent effects. To clarify design principles, we present case studies of cascade electrodes organized in systems without and with integrated semiconductors. We further emphasize the integration of FEM with multiscale frameworks (density functional theory, molecular dynamics, kinetic Monte Carlo) and its role in bridging atomic-level insights with device-level performance. Finally, we identify current limitations and future prospects, including improved boundary conditions, coupling with operando experiments, and machine learning-accelerated model development. Together, these insights provide design principles for next-generation CO 2 R cascade systems for efficient solar fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗

Experimental evidence of disordered crystalline premixing in sputter-deposited Ni(V)/Al multilayers

The sputter deposition of alternating layers of Ni(V) and Al forms a reactive multilayer known to undergo self-propagating formation reactions when ignited. The sequential deposition process leads to nanometer-scale premixing of reactants at each included interface, which ultimately affects multilayer exothermicity. This work performs the direct measurement of a disordered face-centered cubic (FCC) solid solution premixed phase at the interfaces of Ni(V)/Al multilayers via scanning transmission electron microscopy. The crystallinity of the observed phase differs from previously reported a priori predictions of an amorphous interlayer. The disordered FCC phase retains its symmetry after annealing for 16 h at 135 ± 5 °C, but the lattice parameter shifts consistently with an Al-rich composition. The existence of a crystalline premix in Ni(V)/Al is attributed to the electronic contribution to the entropy of crystallization. The importance of electronic entropy to the phase formation of energetic materials motivates its inclusion when constructing digital twins for atomistic kinetics and ignition sensitivity.

Crystal structure↗

Phosphorus chemistry in plant charcoal: interplay between biomass composition and thermal condition

Background Vegetation fire may change Phosphorus (P) cycling in terrestrial ecosystems through converting biomass into fire residues. Aim The aim of this study was to understand the chemistry and mobility of P in fire residues to help reveal P thermochemistry during biomass burning and post-fire P cycling. Methods A combination of sequential extraction, liquid 31P NMR and P K-edge XANES was used to obtain quantitative P speciation and explain P solubilisation behaviours of charcoal. Key results Despite varying diverse P species existing in raw biomass, only two P structural moieties – orthophosphate and pyrophosphate – were identified in charcoal. However, relative abundance of pyrophosphate differs greatly among charcoal samples from different biomass types, ranging between 0 and 40% of total extractable P. Although P K-edge XANES data indicates abundant soluble phosphate minerals, most P (70–90%) is likely occluded physically in the charcoal. The bicarbonate-extractable P (the Olsen-P) varies significantly and cannot be explained by surface P concentration or elemental stoichiometry alone. Conclusion and implications The results suggest the importance of starting biomass P speciation (i.e. molecular structure and complexation environment) and thermal conditions in controlling P speciation and availability in charcoal. The different P chemistry between charcoal and ash suggests the importance of fire types and severity in disturbing the P cycle.

Forestry↗

Radiation damage and dose limits in serial synchrotron crystallography at cryo- and room temperatures

Radiation damage limits the accuracy of macromolecular structures in X-ray crystallography. Cryogenic (cryo-) cooling reduces the global radiation damage rate and, therefore, became the method of choice over the past decades. The recent advent of serial crystallography, which spreads the absorbed energy over many crystals, thereby reducing damage, has rendered room temperature (RT) data collection more practical and also extendable to microcrystals, both enabling and requiring the study of specific and global radiation damage at RT. Here, we performed sequential serial raster-scanning crystallography using a microfocused synchrotron beam that allowed for the collection of two series of 40 and 90 full datasets at 2- and 1.9-Å resolution at a dose rate of 40.3 MGy/s on hen egg white lysozyme (HEWL) crystals at RT and cryotemperature, respectively. The diffraction intensity halved its initial value at average doses ( D 1/2 ) of 0.57 and 15.3 MGy at RT and 100 K, respectively. Specific radiation damage at RT was observed at disulfide bonds but not at acidic residues, increasing and then apparently reversing, a peculiar behavior that can be modeled by accounting for differential diffraction intensity decay due to the nonuniform illumination by the X-ray beam. Specific damage to disulfide bonds is evident early on at RT and proceeds at a fivefold higher rate than global damage. The decay modeling suggests it is advisable not to exceed a dose of 0.38 MGy per dataset in static and time-resolved synchrotron crystallography experiments at RT. This rough yardstick might change for proteins other than HEWL and at resolutions other than 2 Å.

36 MATERIALS SCIENCE↗

Selective reduction of CO to acetaldehyde with CuAg electrocatalysts

Electrochemical CO reduction can serve as a sequential step in the transformation of CO 2 into multicarbon fuels and chemicals. In this study, we provide insights on how to steer selectivity for CO reduction almost exclusively toward a single multicarbon oxygenate by carefully controlling the catalyst composition and its surrounding reaction conditions. Under alkaline reaction conditions, we demonstrate that planar CuAg electrodes can reduce CO to acetaldehyde with over 50% Faradaic efficiency and over 90% selectivity on a carbon basis at a modest electrode potential of −0.536 V vs. the reversible hydrogen electrode. The Faradaic efficiency to acetaldehyde was further enhanced to 70% by increasing the roughness factor of the CuAg electrode. Density functional theory calculations indicate that Ag ad-atoms on Cu weaken the binding energy of the reduced acetaldehyde intermediate and inhibit its further reduction to ethanol, demonstrating that the improved selectivity to acetaldehyde is due to the electronic effect from Ag incorporation. These findings will aid in the design of catalysts that are able to guide complex reaction networks and achieve high selectivity for the desired product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimizing immunization protocols to elicit broadly neutralizing antibodies

Significance The global health burden could be substantially alleviated by the creation of universal vaccines against highly mutable pathogens like HIV and influenza. Broadly neutralizing antibodies (bnAbs) are encouraging targets for such vaccines, because they can bind to diverse strains of these pathogens. BnAbs typically develop only after the immune system has been exposed to many mutated versions of a pathogen, and then too in few people and low numbers. Thus, sequentially administering multiple different pathogen-like proteins is a promising strategy to elicit bnAbs through vaccination. However, it remains unclear how best to design/administer these proteins. We explore this using physics-based simulations and provide mechanistic insights into antibody evolution that could guide creation of universal vaccines against highly mutable pathogens.

Sprenger, Kayla G.↗

Hierarchical supramolecular assembly of a single peptoid polymer into a planar nanobrush with two distinct molecular packing motifs

Significance The preparation of hierarchical biomimetic nanostructures remains a challenging task. Bioinspired peptoid polymers offer a promising opportunity to encode assembly information within the component chains. Here, we report a one-pot preparation of planar nanobrush structures from poly(ethyleneglycol)- block -poly( N -octylglycine) based on tuning the interplay of crystallization and solvophobicity. Each nanobrush assembly is composed of two distinct structural domains, which form sequentially by control of the solution temperature, and contain distinct molecular packing motifs. Micellar intermediates first assemble into linear arrays at elevated temperature in a mesophase state, followed by lateral, crystallization-driven growth in a living manner upon cooling. Precise control over the nanobrush dimensions could be achieved. The structural tunability and excellent biocompatibility of polypeptoids offer great potential for nanomaterials inaccessible previously.

36 MATERIALS SCIENCE↗

Nonadiabatic coupling of the dynamical structure to the superconductivity in YSr 2 Cu 2.75 Mo 0.25 O 7.54 and Sr 2 CuO 3.3

A crucial issue in cuprates is the extent and mechanism of the coupling of the lattice to the electrons and the superconductivity. Here we report Cu K edge extended X-ray absorption fine structure measurements elucidating the internal quantum tunneling polaron (iqtp) component of the dynamical structure in two heavily overdoped superconducting cuprate compounds, tetragonal YSr 2 Cu 2.75 Mo 0.25 O 7.54 with superconducting critical temperature, T c = 84 K and hole density p = 0.3 to 0.5 per planar Cu, and the tetragonal phase of Sr 2 CuO 3.3 with T c = 95 K and p = 0.6. In YSr 2 Cu 2.75 Mo 0.25 O 7.54 changes in the Cu-apical O two-site distribution reflect a sequential renormalization of the double-well potential of this site beginning at T c , with the energy difference between the two minima increasing by ~6 meV between T c and 52 K. Sr 2 CuO 3.3 undergoes a radically larger transformation at T c , >1-Å displacements of the apical O atoms. The principal feature of the dynamical structure underlying these transformations is the strongly anharmonic oscillation of the apical O atoms in a double-well potential that results in the observation of two distinct O sites whose Cu–O distances indicate different bonding modes and valence-charge distributions. The coupling of the superconductivity to the iqtp that originates in this nonadiabatic coupling between the electrons and lattice demonstrates an important role for the dynamical structure whereby pairing occurs even in a system where displacements of the atoms that are part of the transition are sufficiently large to alter the Fermi surface. The synchronization and dynamic coherence of the iqtps resulting from the strong interactions within a crystal would be expected to influence this process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The pathway for coenzyme M biosynthesis in bacteria

Mercaptoethane sulfonate or coenzyme M (CoM) is the smallest known organic cofactor and is most commonly associated with the methane-forming step in all methanogenic archaea but is also associated with the anaerobic oxidation of methane to CO 2 in anaerobic methanotrophic archaea and the oxidation of short-chain alkanes in Syntrophoarchaeum species. It has also been found in a small number of bacteria capable of the metabolism of small organics. Although many of the steps for CoM biosynthesis in methanogenic archaea have been elucidated, a complete pathway for the biosynthesis of CoM in archaea or bacteria has not been reported. Here, we present the complete CoM biosynthesis pathway in bacteria, revealing distinct chemical steps relative to CoM biosynthesis in methanogenic archaea. The existence of different pathways represents a profound instance of convergent evolution. The five-step pathway involves the addition of sulfite, the elimination of phosphate, decarboxylation, thiolation, and the reduction to affect the sequential conversion of phosphoenolpyruvate to CoM. The salient features of the pathway demonstrate reactivities for members of large aspartase/fumarase and pyridoxal 5'-phosphate–dependent enzyme families.

59 BASIC BIOLOGICAL SCIENCES↗

Data assimilation in operator algebras

We develop an algebraic framework for sequential data assimilation of partially observed dynamical systems. In this framework, Bayesian data assimilation is embedded in a nonabelian operator algebra, which provides a representation of observables by multiplication operators and probability densities by density operators (quantum states). In the algebraic approach, the forecast step of data assimilation is represented by a quantum operation induced by the Koopman operator of the dynamical system. Moreover, the analysis step is described by a quantum effect, which generalizes the Bayesian observational update rule. Projecting this formulation to finite-dimensional matrix algebras leads to computational schemes that are i) automatically positivity-preserving and ii) amenable to consistent data-driven approximation using kernel methods for machine learning. Moreover, these methods are natural candidates for implementation on quantum computers. Applications to the Lorenz 96 multiscale system and the El Niño Southern Oscillation in a climate model show promising results in terms of forecast skill and uncertainty quantification.

97 MATHEMATICS AND COMPUTING↗

Strong, ductile, and hierarchical hetero-lamellar-structured alloys through microstructural inheritance and refinement

The strength−ductility trade-off exists ubiquitously, especially in brittle intermetallic-containing multiple principal element alloys (MPEAs), where the intermetallic phases often induce premature failure leading to severe ductility reduction. Hierarchical heterogeneities represent a promising microstructural solution to achieve simultaneous strength−ductility enhancement. However, it remains fundamentally challenging to tailor hierarchical heterostructures using conventional methods, which often rely on costly and time-consuming processing. Here, we report a multiscale microstructural inheritance and refinement strategy to process “structural hierarchy precursors” in as-cast heterogeneous Al 0.7 CoCrFeNi MPEAs, which lead directly to a hierarchical hetero-lamellar structure (HLS) after simple rolling and annealing. Interestingly, it takes only 10 min of annealing time, two orders of magnitude less than that required to render the state-of-the-art properties during conventional processing of Al 0.7 CoCrFeNi, for us to achieve record-high strength−ductility combinations via the hierarchical HLS design that sequentially stimulates multiple unusual deformation and reinforcement mechanisms. In particular, the HLS-enabled high hetero-deformation-induced (HDI) internal stress triggers profuse <111>-type dislocations on over five independent slip systems in the supposedly brittle intermetallic phase and activates extensive stacking faults (SFs) and nanotwinning in the adjoining soft phase with a rather high SF energy. These unexpected, dynamically reinforcing hetero-deformation mechanisms across multiple length scales facilitate high sustained HDI strain hardening, along with a salient microcrack-mediated extrinsic ductilization effect, suggesting that the proposed microstructural inheritance and refinement strategy provides an efficient, fast, and low-cost approach to overcome the strength−ductility trade-off in a broad range of structural materials.

Science & Technology - Other Topics↗