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DOE OSTI2025

Testing CP properties of the Higgs boson coupling to τ leptons with heterogeneous graphs

In this paper we explore the possibility of utilizing Deep Learning in measuring the CP properties of the coupling of Higgs boson to τ leptons at the High Luminosity Large Hadron Collider. We employ three Deep Learning (DL) networks, Multi-Layer Perceptron (MLP), Graph Convolution Network (GCN), and Graph Transformer Network (GTN) to enhance signal-to-background separation. The angle between τ lepton decay planes at the detector level is CP-sensitive observables, and we develop Heterogeneous Graphs that integrate diverse node and edge structures to incorporate the CP-sensitive observable efficiently. Using simplified detector simulations we estimate the reconstruction accuracy of the angle between τ lepton planes at the detector level, considering hadronic τ decay modes and standard model backgrounds. With $\sqrt{s}$ = 14 TeV and $\mathcal{L}$ = 100 fb -1 , MLP excludes CP mixing angles above 20° at 68% confidence level (CL), while GCN and GTN achieve exclusions at 90% CL and 95% CL, respectively. The networks also achieve a 3σ significance in excluding a pure CP-odd state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Short–Term Forecasting of Wind Gusts at Airports Across CONUS Using Machine Learning

Short–term forecasting of wind gusts, particularly those of higher intensity, is of great societal importance but is challenging due to the presence of multiple gust generation mechanisms. Wind gust observations from eight high–passenger–volume airports across the continental United States (CONUS) are summarized and used to develop predictive models of wind gust occurrence and magnitude. These short–term (same hour) forecast models are built using multiple logistic and linear regression, as well as artificial neural networks (ANNs) of varying complexity. A suite of 19 upper–air predictors drawn from the ERA5 reanalysis and an autoregressive (AR) term are used. Stepwise procedures instruct predictor selection, and resampling is used to quantify model stability. All models are developed separately for the warm (April–September) and cold (October–March) seasons. Results show that ANNs of 3–5 hidden layers (HLs) generally exhibit higher hit rates than logistic regression models and also improve skill with respect to wind gust magnitudes. However, deeper networks with more HLs increase false alarm rates in occurrence models and mean absolute error in magnitude models due to model overfitting. For model skill, inclusion of the AR term is critical while the majority of the remaining skill derives from wind speeds and lapse rates. A predictive ceiling is also clearly demonstrated, particularly for the strong and damaging gust magnitudes, which appears to be partially due to ERA5 predictor characteristics and the presence of mixed wind climates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Fundamental Superconductivity of Nb films for Quantum Computing Application

Niobium is a widely accepted material for quantum computing device as well as superconducting radio frequency (SRF) technology. Superconducting niobium is a marginal type II superconductor which has a very narrow gap (~20-30 mT) of the mixed state at 2K, even showing the intermediate state (IMS) at the early stage of magnetic vortex penetration. Tremendous progress has been made in understanding the impact of the Nb surface and bulk superconductivities on SRF resonator performance. However, the effect of thin superconducting Nb films for quantum computing applications requires further examination. In this study, we explore the fundamental superconducting properties of various thin Nb films and compare them with respect to the energy relaxation time, T1, measured from superconducting qubit fabricated with these films. The Nb films are fabricated both with or without a surface protective layer that prevents the formation of lossy Nb2O5. Electromagnetic properties are characterized by means of bulk magnetization, electromagnetic transport, and dynamics of surface superconductivity. In addition, analytical electron microscopy is implemented to further connect the superconducting properties to microstructure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Leaching Kinetics of Rare Earth Elements from Fire Clay Seam Coal

Recovery of rare earth elements (REEs) from coal samples collected from the Fire Clay coal seam using diluted mineral acid solutions was investigated. The initial processing step was coal recovery using conventional froth flotation which concentrated the REEs in tailing material resulting in an upgrade to values around 700 ppm on a dry whole mass basis. Leaching experiments were performed on the flotation tailings material using a 1.2 M sulfuric acid solution adjusted to a temperature of 75 °C to study the extractability of REEs from coal material. The effect of particle size, leaching time, leaching temperature, and solid concentration on REE leaching recovery were evaluated. The kinetic data obtained from leaching over a range of temperatures suggested that the leaching process follows the shrinking core model with possibly a mixed control mechanism that may be a result of several heterogenous materials leaching simultaneously. Leaching recovery increased rapidly at the beginning of the reaction then slowed as the system reached equilibrium. The apparent activation energy determined from test data obtained over a range of temperatures using 1 M sulfuric acid was 36 kJ/mol for the first 20 min of reaction time and 27 kJ/mol for the leaching period between 20 and 120 min. The leaching of light REEs during the initial stage was determined to be driven by a chemical reaction, followed by the formation of a product layer, which required lower activation energy in the later stage of leaching. In regards to the heavy REEs, the major mechanism for leaching is desorption and the product layer formation does not affect the heavy REEs significantly.

58 GEOSCIENCES↗

DOE OSTI2023

Extraction Kinetics of Rare Earth Elements from Ion-Adsorbed Underclays

Citric acid has been identified as an environmentally sustainable organic acid capable of leaching up to ~30% of easily accessible REEs from underclay material. An analysis of the leaching profiles was performed to discern the reaction rates, extraction efficiencies, and potential leaching mechanisms of REEs and cations of interest from ion-adsorbed underclays. The initial leaching stage follows a slow intraparticle diffusion mechanism followed by a second stage controlled by a mixed diffusion regime. The leaching profiles of Ca and P were similar to those of REEs, suggesting that REEs are most likely derived from mineral surfaces such as hydroxyapatite or crandallite rather than predominately from underclays. Fitting to a modified diffusion control model found diffusion-controlled leaching to be the primary mechanism whereas non-diffusive mechanisms made up about 22% of the extracted REEs. Gangue cations associated with underclays had less non-diffusive leaching than REE species, indicating that their leaching kinetics may be dominated by diffusion from within the material or potentially from product layer formation. Fitting to Boyd plots further indicated that REEs were leached following intraparticle diffusion control. These results have important implications for the development of more efficient and sustainable methods for extracting REEs or critical minerals from alternative feedstocks.

Prem, Priscilla↗

DOE OSTI2023

Fundamental Superconductivity of Nb films for Quantum Computing Application

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Using optical fibers to examine thermal mixing of liquid sodium in a pool-type geometry

Sodium fast reactors (SFR) are poised to be a leading candidate for the next generation of commercial nuclear reactor deployment. Companies are commissioning designs for SFR increasing the need for experimental and computational analysis to improve the economics and safety of these reactors. Analysis of SFR behavior during reactor transients directly informs the understanding of reactor safety. Particularly, investigating the thermal transients associated with the reactor loss of flow transient allows for informed design decisions to be made regarding reactor safety. During loss of flow transients the flow rate of the coolant is significantly reduced, but not necessarily stopped. The reduction in flow rate results in coolant temperatures exiting the reactor core that can be drastically different than the coolant in upper pool. When these different temperature fluids interact, thermally stratified layers can form causing cyclic thermal fatigue on the reactor vessel potentially leading to pre-material failure. Past experimental studies have lacked high resolution temperature measurements. This research focuses on demonstrating the reliability of novel techniques for acquiring high resolution temperature measurements in a scaled liquid sodium facility. Tests are conducted that simulate postulated loss of flow transients and provide unprecedented spatial temperature distribution measurements.

42 ENGINEERING↗

DOE OSTI2021

Effects of Surface and Top Wind Shear on the Spatial Organization of Marine Stratocumulus-Topped Boundary Layers

Typically, the convective nature of Stratocumulus topped boundary layers (STBL) involves the motion of updrafts and downdrafts, driven by surface fluxes and radiative cooling, respectively. The balance between shear and buoyant forcings at the surface can determine the organization of updrafts between cellular and roll structures. We investigate the effect of varying shear at the surface and top of the STBL using Large Eddy Simulations, taking DYCOMS II RF01 as a base case. We focus on spatial identification of the following features: coherent updrafts and downdrafts, and observe how they are affected by varying shear. Stronger surface shear organizes the updrafts in rolls, causes less well-mixed thermodynamic profiles, and decreases cloud fraction and liquid water path (LWP). Stronger top shear also decreases cloud fraction and LWP more than surface shear, by thinning the cloud from the top. Features with stronger top than surface shear are associated with a net downward momentum transport and show early signs of decoupling. Classifying updrafts and downdrafts based on their vertical span and horizontal size confirms the dominance of tall objects spanning the whole STBL. Tall objects occupy 30% of the volume in the STBL, while short ones occupy less than 1%. For updraft and downdraft fluxes, these tall objects explain 65% of the vertical velocity variance and 83% of the buoyancy flux, on average. Stronger top shear also weakens the contribution of downdrafts to the turbulent fluxes and tilts the otherwise vertical development of updrafts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Two-dimensional simulations of internal gravity waves in a $\mathrm{5M_⊙}$ zero-age-main-sequence model

Main-sequence intermediate-mass stars present a radiative envelope that supports internal gravity waves (IGWs). Excited at the boundary with the convective core, IGWs propagate towards the stellar surface and are suspected to impact physical processes such as rotation and chemical mixing. Using the fully compressible time-implicit code MUSIC, we study IGWs in two-dimensional simulations of a zero-age-main-sequence 5 solar mass star model up to 91 percent of the stellar radius with different luminosity and radiative diffusivity enhancements. Our results show that low-frequency waves excited by core convection are strongly impacted by radiative effects as they propagate. This impact depends on the radial profile of radiative diffusivity which increases by almost 5 orders of magnitude between the centre of the star and the top of the simulation domain. In the upper layers of the simulation domain, we observe an increase of the temperature. Our study suggests that this is due to heat added in these layers by IGWs damped by radiative diffusion. We show that non-linear effects linked to large amplitude IGWs may be relevant just above the convective core. Both these effects are intensified by the artificial enhancement of the luminosity and radiative diffusivity, with enhancement factors up to 10 4 times the realistic values. Our results also highlight that direct comparison between numerical simulations with enhanced luminosity and observations must be made with caution. Finally, our work suggests that thermal effects linked to the damping of IGWs could have a non-negligible impact on stellar structure.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Appealing sheath‐core spun high‐performance composite carbon molecular sieve membranes

Abstract Carbon molecular sieve (CMS) membranes are attractive candidates to meet requirements for challenging gas separations. The added ability to maintain such intrinsic properties in an asymmetric morphology with a structure that we term a “Pseudo Wheel+Hub & Spoke” asymmetric form offers new opportunities. For CMS membrane, specifically, the structure provides both selective layer support and low flow resistance even for high feed pressures and fluxes in CO 2 removal from natural gas. This capability is unavailable to even rigid glassy polymers due to the much higher modulus of CMS materials. Combining precursor asymmetric hollow fiber formation and optimized pyrolysis creates a defect free CMS proof‐of‐concept membrane for this application. Facile formation of the sheath‐core spun precursor with a 6FDA‐DAM sheath and Matrimid® core also avoids the need to seal defects before or after the carbonization of the precursors. The composite CMS membrane shows CO 2 /CH 4 (50 : 50) mixed gas feed with an attractive CO 2 /CH 4 selectivity of 64.3 and CO 2 permeance of 232 GPU at 35 °C. A key additional benefit of the approach is reduction in use of the more costly high performance 6FDA‐DAM in a composite sheath‐core CMS membrane with the “Pseudo Wheel+Hub & Spoke” structure.

Cao, Yuhe↗

DOE OSTI2026

Predicting Particle-Size Distributions in Fuel-Cell Inks

Prediction of the catalyst-activated carbon particle sizes of fuel-cell inks remains a critical challenge in enhancing the performance and durability of fuel cells. The performance and structural integrity of the catalyst layers in the cell depend not only on the properties of the ionomer, but also on the carbon supports that host the catalyst. To investigate how these carbon aggregate structures form, we present a model that calculates the cooperative size distributions of ionomer and carbon aggregates in various water/alcohol mixtures and compares those results to available experimental data. Aggregation of both the suspended ionomers and the carbon particles is interwoven as the carbon aggregation depends heavily on the ionic strength of its environment, namely protons dissociating from the ionomer’s sulfonic-acid-group side chains. We demonstrate that the surrounding mixed solvent as well as Nafion TM binder concentration strongly influence the degree of aggregation for carbon particles. The validated model provides a framework for exploring aggregation under a wide range of conditions for various electrochemical-technology inks.

Srivastav, Harsh [University of California, Berkel↗

DOE OSTI2025

Remote-sensing detectability of airborne Arctic dust

Remote-sensing (RS)-based estimates of Arctic dust are oftentimes overestimated due to a failure in separating out the dust contribution from that of spatially homogeneous clouds or low-altitude cloud-like plumes. A variety of illustrations are given with a particular emphasis on questionable claims of using brightness temperature differences (BTDs) as a signature indicator of Arctic dust transported from mid-latitude deserts or generated by local Arctic sources. While there is little dispute about the presence of both Asian and local dust across the Arctic, the direct RS detectability of airborne dust, as ascribed to satellite (MODIS and AVHRR) measurements of significantly negative brightness temperature differences at 11 and 12 µm (BTD 11–12 ), has been misrepresented in certain cases. While it is difficult to account for all examples of strongly negative BTD 11–12 values in the Arctic, it is unlikely that airborne dust plays a significant role. One much more likely contributor would be water clouds in the Arctic inversion layer. The RS detectability of the impact of Arctic dust (notably due to Arctic dust from local sources) can, however, be of significance. Sustained dust deposition can substantially decrease (visible to shortwave IR) snow and ice reflectance albedo (pan-chromatic reflectance) and the signal measured by satellite sensors. Significantly negative BTD 11–12 values would, however, only represent a limited area near the drainage basin sources according to our event-level case studies. The enhanced ice-nucleating particle (INP) role of local Arctic dust can, for example, induce significant changes in the properties of low-level mixed-phase clouds (cloud optical depth changes <~ 1) that can readily be detected by active and passive RS instruments. It is critical that the distinction between the RS detectability of airborne Arctic dust versus the RS detectability of the impacts of that dust be understood if we are to appropriately parameterize, for example, the radiative forcing influence of dust in this climate-sensitive region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

LDRD 22A1059-068FP Tailoring the Properties of Multi-Phase Materials Through the Use of Correlative Microscopy and Machine Learning - Poster

High strength alloys with good ductility, hardness, and toughness are needed to meet stringent design requirements for extreme environments. One complication in this pursuit is the evidence that metals rarely exhibit both high strength and good fracture toughness as the underlying mechanisms work in opposition. An exception to this behavior is found in multiphase alloys that form complex microstructures of mixed phases with variable grain sizes and shapes that provide increased fracture toughness by the arrangement of their constituent elements. We propose to explore this phenomenon using state-of-the-art machine learning (ML) techniques in a new and novel manner to identify and correlate the critical microstructural features in a Titanium-10Vanadium-2Iron-3Aluminum (Ti-10V-2Fe-3Al) alloy that is reported to exhibit high strength and fracture toughness. Additionally, we will employ multiple, complementary characterization techniques such as optical microscopy, electron backscatter diffraction (EBSD), energy dispersive spectroscopy (EDS) and scanning electron microscopy to provide multi-layer, quantitative ground truth measures of the microstructures. This data will be used to train a Convolutional Neural Network (CNN) in a semi-supervised environment to identify key microstructural features such as ? platelet dimensions and locations and ?/? phase boundaries and correlate those features with the strength and toughness. Here the ? and ? nomenclature refers to hexagonal close pack (hcp) and body center cubic (bcc) crystal structures, respectively. Previous work has focused on popular alloys and typically used one characterization technique. This research is focused on a promising titanium alloy, uses multiple complimentary characterization tools to provide precise microstructural information and correlates to improved fracture toughness. The resulting ML tool can be trained for additional microstructural features, different alloy(s), and or target mechanical properties.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Influence of Concentration Gradients on Electroconvection at a Cation-Exchange Membrane Surface

Membrane-based systems, such as electrodialysis, play an important role in desalination and industrial separation processes. Electrodialysis uses alternating anion- and cation-exchange membranes with a perpendicular electric field to generate concentrated and diluate streams from a feed solution. It is known that under overlimiting current conditions, reduced charge and mass transfer at the membrane interface leads to regions of high ion depletion generating instability and vortices termed electroconvection. While electroconvective mixing is known to directly impact the separation efficiency of electrodialysis, the influence of ion concentration gradients across the membrane experienced in a functional electrodialysis system is not known. Here, we report the influence of ion concentration gradients across a cation exchange membrane (Nafion) that is both aligned with and opposed to the applied electric field. Experiments were conducted by coflowing NaCl solutions of different concentrations (0.1–100 mM) on each side of the membrane, and electroconvection was visualized with a fluorescence dye (Rhodamine 6G). Here, we obtained concentration profiles from fluorescence image data and systematically measured the thickness of the depletion boundary layer d BL under different conditions. We found smaller d BL values at a higher flow rate both with and without concentration gradients. Our results show that electroconvection is enhanced when the electric field is opposite to the direction of the concentration gradient.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Impact of Interposer Microstructure on Ionic Transport in Liquid-Phase Bicarbonate Electrolysis

The electrochemical reduction of CO 2 (CO 2 RR) is a potentially scalable approach for converting captured carbon dioxide into value-added products. Conventional gas-phase electrolysis systems can suffer from carbonate crossover, which limits the efficiency of the system. Liquid-phase (bi)carbonate electrolysis using bipolar membrane electrode assemblies (BPMMEA) has emerged as a promising alternative. The interposer layer, a porous mass-transport material between the BPM and the catalyst, is an essential component of the MEA, as it allows evolved CO 2 to reach the catalyst surface for reaction. In the absence of this layer, evolved CO 2 generated by the pH swing process at the BPM can be converted back into (bi)carbonate (CO 2 recapture) due to the high bulk pH. Thus, clear design guidelines are needed to maximize CO 2 conversion, minimize CO 2 recapture in the catholyte, and improve energy efficiency. Here, the transport properties of the interposer are systematically characterized by X-ray tomography and symmetric-cell impedance spectroscopy to quantify porosity, tortuosity, and the resulting MacMullin number. We then examine the correlation between these material properties and the electrolyzer performance. We focus on characterizing two commercial porous membrane filters, mixed cellulose ester (MCE) and poly(ether sulfone) (PES).

CO2 electrolysis↗

DOE OSTI2022

Ruddlesden–Popper Perovskites with Narrow Phase Distribution for Air-Stable Solar Cells

2D Ruddlesden-Popper perovskites have risen to prominence as stable and efficient photovoltaic materials because of their structural diversity, rich photophysics, and low moisture ingression. However, thin films processed from stoichiometric precursor solutions possess a broad phase distribution of different number of inorganic layers with random crystal orientation, crippling device performance. The effect of methylammonium chloride (MACI) and 3-amino4-phenolsulfonic acid (APSA) on the fabrication of perpendicularly oriented (PEA) 2 MA 4 Pb 5 I 16 films with narrow phase distribution using antisolvent and hot-casting processing techniques is investigated. MACI plays a critical role in suppressing parasitic n ≤ 2 and 3D-like phases. APSA performs the dual function of trap passivation and further narrowing phase polydispersity through strong coordination with Pb 2+ . Ex situ grazing-incident wide-angle X-Ray scattering (GIWAXS) and ultrafast spectroscopic characterization reveal uniformly mixed-phase distribution with disordered orientation in antisolvent treated films, while additive-assisted hot-casting treatment results in oriented, reverse-graded phase distribution, i.e., small-n on the film surface and large-n at the bottom. Arising thin films enable efficient p-i-n solar cells with an efficiency of 14.34%, and a V oc of 1.20 V, retaining 96% initial efficiency after 1440 h under ambient conditions (RH = 50-60%) without encapsulation.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Predictions of delafossite-hosted honeycomb and kagome phases

Delafossites, typically denoted by the formula ABO 2 , are a class of layered materials that exhibit a wide range of electronic and optical properties. Recently, the idea of modifying these delafossites into ordered kagome or honeycomb phases via strategic doping has emerged as a potential way to tailor these properties. In this study, we use high-throughput density functional theory calculations to explore many possible candidate kagome and honeycomb phases by considering dopants selected from the parent compounds of known ternary delafossite oxides from the inorganic crystal structure database. Here our results indicate that while A-site in existing delafossites can host a limited range of elemental specifies, and display a low propensity for mixing or ordering, the oxide sub-units in the BO 2 much more readily admit guest species. Our study identifies four candidate B-site kagome and fifteen candidate B-site honeycombs with a formation energy more than 50 meV f.u. −1 below other competing phases. The ability to predict and control the formation of these unique structures offers exciting opportunities in materials design, where innovative properties can be engineered through the selection of specific dopants. A number of these constitute novel correlated metals, which may be of interest for subsequent efforts in synthesis. These novel correlated metals may have significant implications for quantum computing, spintronics, and high-temperature superconductivity, thus inspiring future experimental synthesis and characterization of these proposed materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Large spatiotemporal variability in aerosol properties over central Argentina during the CACTI field campaign

Abstract. Few field campaigns with extensive aerosol measurements have been conducted over continental areas in the Southern Hemisphere. To address this data gap and better understand the interactions of convective clouds and the surrounding environment, extensive in situ and remote sensing measurements were collected during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign conducted between October 2018 and April 2019 over the Sierras de Córdoba range of central Argentina. This study describes measurements of aerosol number, size, composition, mixing state, and cloud condensation nuclei (CCN) collected on the ground and from a research aircraft during 7 weeks of the campaign. Large spatial and multiday variations in aerosol number, size, composition, and CCN were observed due to transport from upwind sources controlled by mesoscale to synoptic-scale meteorological conditions. Large vertical wind shears, back trajectories, single-particle measurements, and chemical transport model predictions indicate that different types of emissions and source regions, including biogenic emissions and biomass burning from the Amazon and anthropogenic emissions from Chile and eastern Argentina, contribute to aerosols observed during CACTI. Repeated aircraft measurements near the boundary layer top reveal strong spatial and temporal variations in CCN and demonstrate that understanding the complex co-variability of aerosol properties and clouds is critical to quantify the impact of aerosol–cloud interactions. In addition to quantifying aerosol properties in this data-sparse region, these measurements will be valuable to evaluate predictions over the midlatitudes of South America and improve parameterized aerosol processes in local, regional, and global models.

54 ENVIRONMENTAL SCIENCES↗