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At least 667 records · Page 37

Understanding Differences in Water Adsorption Isotherms: Structural Variations, Force Fields, and Monte Carlo Simulation Approaches

Accurate prediction of water adsorption in micro- and mesoporous materials with hydrophobic pores is essential for the design and characterization of advanced adsorbent materials for separation and energy applications. Here, we assess the reproducibility and consistency of water adsorption isotherms in two microporous all-silica MFI zeolite structures (MFI-K and MFI-O) using two different zeolite force fields and three simulation approaches: grand canonical Monte Carlo (GCMC), Gibbs ensemble Monte Carlo (GEMC), and transition matrix Monte Carlo (TMMC). We demonstrate that consistent treatment of the bulk fluid phase in GCMC and TMMC simulations is critical for reconciling isotherms across methods, and we construct simulation-based equations of state for the TIP4P water model to enable rigorous fugacity-to-pressure conversions. Large shifts in the isotherms are observed for two zeolite force fields developed using different parametrization strategies, with the GCS force field representing implicitly a defect-containing all-silica zeolite, whereas the TraPPE-zeo force field accurately represents an essentially defect-free all-silica zeolite. While water in the van Koningsveld structure of MFI exhibits a first-order phase transition and condensation-like step for adsorption near room temperature, water in the Olson structure of MFI displays continuous adsorption, attributed to differences in the adsorption free energy landscapes. Structural analysis reveals that small geometric variations, particularly Si–O–Si bond angles near the strongest adsorption sites, lead to these substantial differences in adsorption behavior. Furthermore, our results highlight the sensitivity of simulated water adsorption isotherms in hydrophobic frameworks to seemingly small differences in the framework structures, force field parametrization, and simulation approaches.

36 MATERIALS SCIENCE↗

Impact of indirect CP violation on Br( K S → μ + μ – ) ℓ=0

The decay K S → μ + μ – ) ℓ=0 , with the final muon pair in an angular-momentum zero state, is a sensitive probe of short-distance physics. It has recently been shown how to extract this branching ratio from neutral kaon decay data. We point out that the impact of indirect CP violation on the standard-model prediction of this mode, while nominally of order $\vert$ε K $\vert$ ~ 10 -3 , is enhanced by a large amplitude ratio and leads to a shift of the branching ratio Br( K S → μ + μ – ) ℓ=0 by a few percent, depending on the size of a relative phase that can be extracted from data. We also update the standard-model prediction of the short-distance contribution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Activity of Brønsted Acid Sites in UiO-66 for Cyclohexanol Dehydration

Brønsted-acid sites are introduced via –OSO 3 H groups on the coordinatively unsaturated ZrO 2 nodes of UiO-66 metal organic frameworks (MOF). Such groups create strong Brønsted acidic sites that are active for cyclohexanol and ethanol dehydration (in liquid organic phase and gas phase, respectively). The intrinsic activity of Brønsted acid sites at nodes increased by increasing the concentration of sulfur, which is attributed to a shift from isolated µ 3 -OSO 3 H to two groups [(µ 3 -OSO 3 H) 2 ] interacting via hy-drogen bonding. For cyclohexanol dehydration, the relatively low activation enthalpies and negative transition entropies point to an E2 elimination mechanism, similar to dehydration with MFI zeolites in organic solvents. Furthermore, our results, show that the catalytic activity can be manipulated via the functionalization of zirconia nodes of the MOF framework.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electronic Structure of Metallophthalocyanines, MPc (M = Fe, Co, Ni, Cu, Zn, Mg) and Fluorinated MPc

In this work, we compute the electronic structure and optical excitation energies of metal-free and transition-metal phthalocyanines (H2Pc and MPc for M = Fe, Co, Ni, Cu, Zn, Mg) using density functional theory with optimally tuned range-separated hybrid functionals (OT-RSH). We show that the OT-RSH approach provides photoemission spectra in quantitative agreement with experiments as well as optical band gaps within 10% of their experimental values, capturing the interplay of localized d-states and delocalized pi-pi* states for these organometallic compounds. We examine the tunability of MPcs and H 2 Pc through fluorination, resulting in quasi-rigid shifts of the molecular orbital energies by up to 0.7 eV. Our comprehensive data set provides a new computational benchmark for gas-phase phthalocyanines, significantly improving upon other density-functional-theory-based approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic soil columns simulate Arctic redox biogeochemistry and carbon release during changes in water saturation

Thawing Arctic permafrost can induce hydrologic change and alter redox conditions, shifting the balance of soil organic matter (SOM) decomposition. There remains uncertainty about how soil saturation and redox transitions impact dissolved and gas phase carbon fluxes, and efforts to link hydrobiogeochemical processes to ecosystem-scale models are limited. This study evaluates SOM decomposition of Arctic tundra soils using column experiments, water chemistry measurements, microbial community analysis, and a PFLOTRAN reactive transport model. Soil columns from a thermokarst channel (TC) and an upland tundra (UC) were exposed to cycles of saturation and drainage, which controlled carbon emissions. During saturation, an outflow of dissolved organic carbon from the UC soil correlated with elevated reduced iron and decreased pH; during drainage, UC carbon dioxide fluxes were 70% higher than TC fluxes. Intermittent methane release was observed for TC, consistent with higher methanogen abundance. Slower drainage in the TC soil correlated with more subtle biogeochemical changes. PFLOTRAN simulations captured experimental trends in soil carbon fluxes, oxygen concentrations, and water contents. The model was then used to evaluate additional soil water drainage rates. This study emphasizes the importance of considering hydrologic change when evaluating and simulating SOM decomposition in dynamic Arctic tundra environments.

54 ENVIRONMENTAL SCIENCES↗

Unlocking superplasticity in medium and high-entropy alloys

Superplasticity, the capacity of materials to sustain extraordinary tensile elongations at elevated temperatures, underpins a range of advanced metal-forming technologies. Conventionally, it is achieved in fine-grained alloys where deformation is dominated by grain-boundary sliding, accommodated by diffusion and dislocation activity. The advent of medium- and high-entropy alloys (M/HEAs), with their high chemical complexity and unconventional phase stability, offers new pathways to superplastic behavior beyond traditional alloy systems. Although investigated only recently, several M/HEAs already exhibit elongations that rival or exceed those of classical superplastic materials, particularly when ultrafine or metastable microstructures are engineered. Here, we review progress in understanding superplastic deformation in M/HEAs, emphasizing the interplay among composition, initial microstructure, thermomechanical processing, and microstructural evolution during high-temperature deformation. We discuss approaches to generating the fine-grained structures necessary for grain-boundary sliding, including severe plastic deformation and tailored heat treatments. We further highlight dynamic phenomena such as phase transformations, evolving grain-boundary chemistry, and deformation-induced grain refinement that can enhance plasticity in these systems. These mechanisms often shift the balance of deformation processes, enabling large elongations even outside classical criteria. Finally, we outline key challenges for application, including cost, scalability, recyclability, and microstructural stability.

klenam, Desmond [University of the Witwatersrand, ↗

Fluid-like shock compression of dilute polymer nanocomposites

The shock Hugoniot of heterogenous mixtures of discrete particles has been experimentally investigated for porous agglomerates and fluids, while the study of full-density solids has been primarily limited to compressed powders and high-dimensional composites. By dispersing ceria nanoparticles in a polyethylene matrix, we are able to examine the hydrodynamic behavior of a nonporous, heterogenous solid in thermal equilibrium during weak shock compression. Phase-driven discontinuities in the Hugoniot particle velocity–shock velocity (u−D) relationship of pure polyethylene are replicated in the nanocomposites but are shifted to lower velocity and to higher pressure with higher particle concentration. The results are explained using an isothermal, two-velocity fluid model under the hydrodynamic approximation. The model, which assumes a theoretical equation-of-state for ceria and either a low-order or high-order fit to the measured polyethylene Hugoniot, reasonably predicts the Hugoniot for two different polyethylene/ceria nanocomposites. Using the model, the mixture Hugoniot is shown to be insensitive to the Hugoniot of the stiffer constituent when the moduli are sufficiently disparate, while dependence on particle density and volume fraction is preserved through fluid-like motion.

Moore, Nathan W. [Sandia National Laboratories (SN↗

Ab Initio modeling of Near-Edge EELS spectra for chemisorbed molecules

Abstract Electron energy loss spectroscopy (EELS) has recently been applied to probe chemisorbed molecules on metal nanostructures, but a fundamental understanding of the correlation between these spectra and the electronic structures of the adsorbates has been limited. We report here on the insights afforded by time-dependent density functional theory to decipher the energy loss near edge structure (ELNES) of EELS spectra associated with chemisorption. These first-principles calculations simulate the ELNES-EELS spectra for chemisorbed CO on various facets of Au and Pt. Computational predictions of key signatures such as the ‘red shift’ and reductions in the peak intensity of the 2 π * and 6 σ * peaks, as compared to free CO in the gas phase, are validated in comparison to experimentally collected EELS spectra. These signatures are revealed to arise from changes in the electronic structure in terms of unoccupied density of states associated with the chemisorption process. They are consistent with a Blyholder model that incorporates donation and back-donation of electrons. They are also characteristic of the chemisorption process, such as the choice of metal, site of adsorption and the coverage and distribution of adsorbates. Our simulations thus provide guidelines for the use of ELNES-EELS to characterize the atomic structure and adsorption property of nanostructured surfaces and facilitate the development of advanced nanomaterials for catalytic applications.

Materials Science↗

SCGSR Final Report

Dual phase noble liquid time projection chambers (TPCs) have an unprecedented sensitivity towards dark matter searches and neutrinos, owing to their ability to detect single electrons. When a particle deposits energy into one of these detectors, electrons are released and drifted into a gaseous region of high electric field. In the gas, the electrons are accelerated to produce extra light into what is called an S2 pulse. This light is far easier to detect than the current induced from a single electron. The two widely used elements for noble liquid detectors are Xe and Ar. Xe has a larger chance of being hit by neutrinos or dark matter, but ends with a lower (i.e. harder to detect) energy when struck. However, Ar light is hard to reflect and detect due to its short wavelength which is absorbed by most materials. While one may use TPB to re-emit this light at a longer wavelength, spatial variations of TPB thickness can smear the amount of re-emitted light, and thus cause a poor S2 energy resolution and spatial resolution. Furthermore, a single electron pulse in Ar is spread over a much longer time than one in Xe, which makes it harder to identify single electrons in Ar. The goal of Xe doping is to combine the best aspects of Ar with the best aspects of Xe. More specifically, this means a detector with a larger yield of photons and electrons produced per energy deposition, an ability to collect more of the light given by those signals, and a narrower pulse from the electron signal. During this project, we developed and operated a detector that can overcome the thermodynamic challenges of Xe doping – namely, preventing Xe from freezing. In the first experimental run during this award period, we found that we can achieve at least 5% of Xe in LAr, and measure the Xe concentration in the gas. In the second run, we installed our detector and saw the first S2 pulses in a dual phase Xe doped LAr TPC. With the data we took, we quantified the effect of Xe doping on the detectability of wavelength-shifted light produced in a Xe doped Ar mixture, as well as the single electron pulse shape. While the Ar light has successfully been wavelength shifted, we learned that much to our surprise, Xe doping actually makes the S2 pulse wider before it makes it narrower.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Bayesian Exploration and Surrogate Emulation of Nonlinear Beam-Response Geometry in the LBNF Beamline

Next-generation long-baseline neutrino experiments aim to achieve multi-MW proton beam power while reducing accelerator-induced systematic uncertainties. At Fermilab, the LBNF beamline is designed for 1.2 MW operation with PIP-II and is upgradeable to 2.4 MW. DUNE will probe the three-flavor neutrino paradigm and search for CP violation, requiring precise neutrino-flux normalization and improved control of accelerator-related uncertainties. Within the LBNF beamline, the System for On-Axis Neutrino Detection (SAND) will constrain flux uncertainties using precision near-detector measurements, while the Muon Monitor System (MuMS) will provide beamline diagnostics sensitive to the proton beam, target, and horn configuration. However, the pion phase space relevant for DUNE depends simultaneously on many correlated parameters, including beam centroid, beam width, horn current and alignment, target position, optics shifts, and radiation-induced changes. Consequently, MuMS observables exhibit nonlinear and coupled responses that are difficult to characterize using traditional one-parameter scans. To address this challenge, we are developing a Bayesian Exploration framework coupled to physics-informed surrogate emulators trained on Geant4 beamline simulations. Gaussian-process emulators provide both fast predictions and uncertainty estimates, enabling adaptive selection of new simulation points in beam-parameter space. As an initial demonstration, we construct surrogate emulators for MuMS response observables using a verified simulation campaign spanning proton-beam steering conditions. The emulators reproduce the simulated dependence of MuMS centroid and gradient observables while providing predictive uncertainties, and serve as the foundation for future multidimensional exploration including beam width, horn current, and additional beamline parameters. This work establishes a framework for uncertainty-aware beam monitoring, adaptive simulation campaigns, and rapid beam-response inference for future DUNE operations.

Ganguly, Sudeshna [Fermilab] (ORCID:00000003163482↗

Probing the Boundary between Classical and Quantum Mechanics by Analyzing the Energy Dependence of Single-Electron Scattering Events at the Nanoscale

The relation between the energy-dependent particle and wave descriptions of electron–matter interactions on the nanoscale was analyzed by measuring the delocalization of an evanescent field from energy-filtered amplitude images of sample/vacuum interfaces with a special aberration-corrected electron microscope. The spatial field extension coincided with the energy-dependent self-coherence length of propagating wave packets that obeyed the time-dependent Schrödinger equation, and underwent a Goos–Hänchen shift. The findings support the view that wave packets are created by self-interferences during coherent–inelastic Coulomb interactions with a decoherence phase close to Δφ = 0.5 rad. Due to a strictly reciprocal dependence on energy, the wave packets shrink below atomic dimensions for electron energy losses beyond 1000 eV, and thus appear particle-like. Consequently, our observations inevitably include pulse-like wave propagations that stimulate structural dynamics in nanomaterials at any electron energy loss, which can be exploited to unravel time-dependent structure–function relationships on the nanoscale.

36 MATERIALS SCIENCE↗

Symmetry instability induced by topological phase transitions

The symmetry-topology interplay dictates how to define order parameters and classify material ordered phases. However, current understanding of this interplay has been predominately approached from a one-sided perspective, with topological states being classified within the constraints imposed by specific fixed symmetries. Here, in this study, we complete this full circle by demonstrating spontaneous symmetry breaking that results from a periodic alteration of topological phases induced by light in a centrosymmetric Dirac material ZrTe 5 . The distinguishing feature is the observation of robust correlation and striking anomalies in the fluence and temperature dependence of key transport parameters. First, both shift current 𝐽 𝑠 and displacement current 𝐽 𝑑 , arising from interband transition and infrared phonon driving, respectively, along with charge carrier pumping, exhibit similar behaviors. Second, they all peak at similar low pump fluence, followed by a subsequent reduction as the fluence further increases. This behavior cannot be explained by conventional energetically allowed, direct excitations. Third, all the three observables exhibit anomalies when they approach the topological phase transition temperature. These results highlight the unique low-energy pumping behaviors in ZrTe 5 , characterized by reversible fluence dependence and a “hinge-like” interaction that connects various electronic and lattice observables, including phonons, charge carriers, and currents. Our findings, supported by model analysis, provide key insights into the fragility of crystalline (inversion) and time-reversal symmetries during the dynamics of topological phase transitions. This fragility drives spontaneous symmetry breaking, evidenced by the synchronized emergence of off-resonant infrared phonons and broken-symmetry photocurrents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Bonding and Acidity of the Formal Hydride in the Prototypical Au 9 (PPh 3 ) 8 H 2+ Nanocluster

Abstract The role of hydrogen atoms as surface ligands on metal nanoclusters is of profound importance but remains difficult to directly study. While hydrogen atoms often appear to be incorporated formally as hydrides, evidence suggests that they donate electrons to the cluster's delocalized superatomic orbitals and may consequently behave as acidic protons that play key roles in synthetic or catalytic mechanisms. Here we directly test this assertion for the prototypical Au 9 (PPh 3 ) 8 H 2+ nanocluster, formed by addition of a hydride to the well‐characterized Au 9 (PPh 3 ) 8 3+ . Using gas‐phase infrared spectroscopy, we were able to unambiguously isolate Au 9 (PPh 3 ) 8 H 2+ and Au 9 (PPh 3 ) 8 D 2+ , revealing an Au−H stretching mode at 1528 cm −1 that shifts to 1038 cm −1 upon deuteration. This shift is greater than the maximum expected for a typical harmonic potential, suggesting a potential governing cluster‐H bonding that has some square‐well character consistent with the hydrogen nucleus behaving as a metal atom in the cluster core. Complexing this cluster with very weak bases reveals a redshift of 37 cm −1 in the Au−H vibration, consistent with those typically seen for moderately acidic groups in gas phase molecules and providing an estimate of the acidity of Au 9 (PPh 3 ) 8 H 2+ , at least with regard to its surface reactivity.

Hernández, Hanna Morales↗

Experimental Investigation of a Phase Change Material Charged Serpentine Heat Exchanger with Louvered Fins

Phase change material heat exchangers (PCM-HX) can be used as a latent heat thermal energy storage (LHTES) component in heat pump applications to further enhance the efficiency of a heat pump as well as to yield financial savings by peak-load shifting. In this paper, a low-cost commercially available aluminum serpentine heat exchanger with louvered fins was experimentally investigated to check its thermal performance as a PCM-HX. A transparent rectangular box fabricated from acrylic plates served as a PCM container. Two cameras were used to capture the phase change process of the PCM on the front and top sides of the container during the experiment. A total of 88 installed temperature sensors throughout the test setup and a mass flow meter enabled a quantitative analysis of the PCM-HX as well. The energy balance deviation between the estimated theoretical and experimentally calculated PCM storage was ±14% considering the often-neglected heat loss and thermal mass of the PCM-HX. PCM temperature profiles, charge and discharge rates, and energy densities under different test conditions were also investigated.

42 ENGINEERING↗

Bonding and Acidity of the Formal Hydride in the Prototypical Au 9 (PPh 3 ) 8 H 2+ Nanocluster

The role of hydrogen atoms as surface ligands on metal nanoclusters is of profound importance but remains difficult to directly study. While hydrogen atoms often appear to be incorporated formally as hydrides, evidence suggests that they donate electrons to the cluster's delocalized superatomic orbitals and may consequently behave as acidic protons that play key roles in synthetic or catalytic mechanisms. Here we directly test this assertion for the prototypical Au 9 (PPh 3 ) 8 H 2+ nanocluster, formed by addition of a hydride to the well-characterized Au 9 (PPh 3 ) 8 3+ . Using gas-phase infrared spectroscopy, we were able to unambiguously isolate Au 9 (PPh 3 ) 8 H 2+ and Au 9 (PPh 3 ) 8 D 2+ , revealing an Au–H stretching mode at 1528 cm –1 that shifts to 1038 cm –1 upon deuteration. This shift is greater than the maximum expected for a typical harmonic potential, suggesting a potential governing cluster-H bonding that has some square-well character consistent with the hydrogen nucleus behaving as a metal atom in the cluster core. Complexing this cluster with very weak bases reveals a redshift of 37 cm –1 in the Au–H vibration, consistent with those typically seen for moderately acidic groups in gas phase molecules and providing an estimate of the acidity of Au 9 (PPh 3 ) 8 H 2+ , at least with regard to its surface reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hadron Storage Ring Transition Crossing for Yellow Only Configuration

The Electron Ion Collider (EIC) Hadron Storage Ring (HSR) has undergone many iterations. This technical note captures the progress made on transition crossing in the HSR studies for the yellow only configuration. Being heavily dependent on the phase advance per cell, the hsr-au-trans-8786phi-071725 optics was used where the phase advances per arc cell are 87°, horizontal and 85°, vertical. These phase advances were chosen to aid in the cancellation of the β and η waves generated during the jump and to minimize the tune shift. The total change in the γ T is 1 unit as prescribed. This technical note will describe the process in which HSR will jump transition with the assumption that longitudinal dynamics will be handled similar to the Relativistic Heavy Ion Collider (RHIC).

43 PARTICLE ACCELERATORS↗

Burn severity and vegetation type control phosphorus concentration, molecular composition, and mobilization

Shifting phosphorus (P) dynamics after wildfires can have cascading impacts from terrestrial to aquatic environments. However, it is unclear whether shifts in P composition or P concentration are responsible for changes in P dynamics post-fire. We used laboratory leaching experiments of Douglas fir forest and sagebrush shrubland chars to examine how the potential mobility of P compounds is influenced by different burn severities. Burning produced a 6.9- and 29-fold increase in particulate P mobilization but a 3.8- and 30.5-fold decrease in aqueous P released for Douglas fir forest and sagebrush shrubland, respectively. The mechanisms driving particulate- and dissolved-phase P compound mobilization were contrasting. Phosphorus compound mobilization in the particulate phase was controlled by solid char total P concentrations, while the aqueous phase was driven by solubility changes of molecular species. Nuclear magnetic resonance (NMR) and X-ray absorption near-edge structure (XANES) on the solid chars indicated that organic orthophosphate monoester and diester species were thermally mineralized to inorganic P moieties with burning in both vegetation types, which decreases P solubility. This coincided with the production of calcium- and magnesium-bound inorganic P compounds. With increasing burn severity there were systematic shifts in P concentration and composition – higher-severity chars mobilized P compounds in the particulate phase, although the magnitude of change was vegetation-specific. Our results indicate a post-fire transformation to both the composition of the solid charred material and how P compounds are mobilized, which may influence its environmental cycling and fate.

31P solution-state NMR↗

Adaptive machine learning for time-varying systems: low dimensional latent space tuning

Machine learning (ML) tools such as encoder-decoder convolutional neural networks (CNN) can represent incredibly complex nonlinear functions which map between combinations of images and scalars. For example, CNNs can be used to map combinations of accelerator parameters and images which are 2D projections of the 6D phase space distributions of charged particle beams as they are transported between various particle accelerator locations. Despite their strengths, applying ML to time-varying systems, or systems with shifting distributions, is an open problem, especially for large systems for which collecting new data for re-training is impractical or interrupts operations. Particle accelerators are one example of large time-varying systems for which collecting detailed training data requires lengthy dedicated beam measurements which may no longer be available during regular operations. We present a novel method of adaptive ML for time-varying systems. Our approach is to map very high (N ≈ 100k) dimensional inputs (a combination of scalar parameters and images) into the low dimensional (N ≈ 2) latent space at the output of the encoder section of an encoder-decoder CNN. We then actively tune the low dimensional latent space-based representation of complex system dynamics by the addition of an adaptively tuned feedback vector directly before the decoder sections builds back up to our image-based high-dimensional phase space density representations. This method allows us to learn correlations within and to quickly tune the characteristics of incredibly large parameter space systems and to track their evolution in real time based on feedback without massive new data sets for re-training. We demonstrate that our method can accurately predict and track the phase space of charged particle beams at various locations in a particle accelerator by adaptively adjusting in real-time while the unknown input beam distribution of the accelerator is changing in shape, charge, and offset and while the RF system of the accelerator itself is also changing in an unpredictable way. For FACET-II we demonstrate that such an approach has the potential to use transverse deflecting cavity and energy spread spectrum beam measurements to accurately predict 2D projections of the 6D phase space of the electron beam at the plasma wakefield acceleration interaction point where such diagnostics are unavailable.

47 OTHER INSTRUMENTATION↗