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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

DICER: Data Intensive Computing Environment and Runtime for Evaluating Unprecedented Scale of Geospatial-Temporal Human Mobility Data

With the significant increase in sources and volume of human mobility data through commercial data vendors as well as microsimulation of cities, the scale of geospatial-temporal data to analyze and assess for mobility characterization has grown to the level of Big Data. There are mobility related commercial organizations deploying scalable computing, but often the system architecture, workflow, and intermediate processing components are not fully disclosed in relevant scope. Current research literature has a notable lack of studies demonstrating architectures and workflows for human mobility analytics that are implemented on a TeraByte scale of geospatial-temporal data. In this context, this paper presents a hyperscale-level system solution named DICER (Data Intensive Computing Environment and Runtime) for processing and analytics of geospatial-temporal data at big data scale. Although the cluster computing architecture of DICER with Apache Spark job running on Kubernetes cluster is not new, there are innovations in the workflow, hierarchical processing logic, and a wide range of intermediate preprocessing and mobility metrics calculation. We have performed case studies to validate the effectiveness of DICER system solution by performing detailed analytics and assessment of human mobility microsimulation output at three different scopes and scale, including a usecase with 16.97 TeraByte and 259.2 Billion rows of data. In addition, we have presented another case study of utilizing DICER to perform the same mobility processing and comparative analytics on large-scale commercially available geospatial-temporal data. All these case studies validate the efficiency and usefulness of DICER in computing population mobility characteristics from geospatial-temporal trajectory data at an unprecedented scale (not only just data volume, but also combination of: number of user entities, temporal frequency, spatial resolution, data duration).

De, Debraj↗
DOE OSTI2024

The lifetime risk and impact of vitiligo across sociodemographic groups: a UK population-based cohort study

Abstract Background Vitiligo is an autoimmune skin disorder characterized by depigmented patches of skin, which can have significant psychological impacts. Objectives To estimate the lifetime incidence of vitiligo, overall, by ethnicity and across other sociodemographic subgroups, and to investigate the impacts of vitiligo on mental health, work and healthcare utilization. Methods Incident cases of vitiligo were identified in the Optimum Patient Care Database of primary care records in the UK between 1 January 2004 and 31 December 2020. The lifetime incidence of vitiligo was estimated at age 80 years using modified time-to-event models with age as the timescale, overall and stratified by ethnicity, sex and deprivation. Depression, anxiety, sleep disturbance, healthcare utilization and work-related outcomes were assessed in the 2 years after vitiligo diagnosis and compared with matched controls without vitiligo. The study protocol for this retrospective observational study was registered with ClinicalTrials.gov (NCT06097494). Results In total, 9460 adults and children were newly diagnosed with vitiligo during the study period. The overall cumulative lifetime incidence was 0.92% at 80 years of age [95% confidence interval (CI) 0.90–0.94]. Cumulative incidence was similar in female (0.94%, 95% CI 0.92–0.97) and male patients (0.89%, 95% CI 0.86–0.92). There were substantial differences in lifetime incidence across ethnic groups, listed by Office for National Statistics criteria [Asian 3.58% (95% CI 3.38–3.78); Black 2.18% (95% CI 1.85–2.50); Mixed/multiple 2.03% (95% CI 1.58–2.47); Other 1.05% (95% CI 0.94–1.17); and White 0.73% (95% CI 0.71–0.76)]. Compared with matched controls, people with vitiligo had an increased risk of depression [adjusted odds ratio (aOR) 1.08, 95% CI 1.01–1.15]; anxiety (aOR 1.19, 95% CI 1.09–1.30); depression or anxiety (aOR 1.10, 95% CI 1.03–1.17); and sleep disturbance [adjusted hazard ratio (aHR) 1.15, 95% CI 1.02–1.31]. People with vitiligo also had a greater number of primary care encounters (adjusted incidence rate ratio 1.29, 95% CI 1.26–1.32) and a greater risk of time off work (aHR 1.15, 95% CI 1.06–1.24). There was little evidence of disparities in vitiligo-related impacts across ethnic subgroups. Conclusions Clinicians should be aware of the markedly increased incidence of vitiligo in people belonging to Asian, Black, Mixed/multiple and Other groups. The negative impact of vitiligo on mental health, work and healthcare utilization highlights the importance of monitoring people with vitiligo to identify those who need additional support.

Eleftheriadou, Viktoria↗
DOE OSTI2024

Kinetics and Mechanism of Ce(IV) Phase Transfer by the Neutral Extractants Tributyl Phosphate and N,N -Di(2-ethylhexyl)isobutyramide

Tributyl phosphate and N,N-di(2-ethylhexyl)isobutyramide (DEHiBA) are uranium-selective extractants that could be used to recover low-enriched uranium from commercial used nuclear fuel. The economic viability of liquid-liquid extraction processes for chemical separations depends on both thermodynamic and kinetic considerations. Here we used microfluidic droplet extraction to measure interfacial phase transfer rate constants for the extraction and stripping of Ce(IV), a non-radioactive actinide surrogate. The Damkohler numbers for each system were calculated and the phase transfer processes were determined to be diffusion-limited under all conditions, contrary to prior studies using constant interface stirred cells and single drop methods. A well-extracted 2:1 DEHiBA/Ce(IV) complex in the organic phase was determined from batch distribution studies, suggesting a different extraction mechanism for Ce(IV) compared with poorly extracted Pu(IV). Finally, phase disengagement rates were found to be rapid in both systems, in agreement with other studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Commercial building HVAC demand flexibility with model predictive control: Field demonstration and literature insights

Model Predictive Control (MPC) for building Heating Ventilation and Air Conditioning (HVAC) systems is beginning to gain traction in the market, with a few controls companies incorporating it into their product offerings. However, it remains difficult to assess whether the energy cost savings are enough to justify the cost of MPC implementation for a particular building, given the limited number of reported demonstrations. For small commercial and residential buildings with relatively uniform systems, standardized approaches can help lower implementation costs. In contrast, for large buildings or district systems, the potential magnitude of cost savings could justify more customized solutions. Estimating the cost-effectiveness of MPC becomes more challenging for medium and large commercial buildings, where a one-size-fits-all solution may not be suitable, and the potential energy cost savings may be insufficient to justify a customized solution. To make MPC technology more appealing, incorporating additional value streams beyond energy efficiency alone can significantly increase its attractiveness. One such revenue stream is demand flexibility, in response to dynamic electricity prices, where MPC can leverage the thermal mass of the building to shift the load and support the grid. Building on an extensive literature review of MPC field studies focused on cost savings and demand flexibility, this paper presents the results of implementing MPC control in a large office building HVAC system in Berkeley, CA. Four different dynamic electricity price profiles were integrated into the MPC objective function to shift building demand while maintaining comfort, and field testing was performed with each price profile across four seasons. The results show potential for 40–65 % demand decrease percentage and up to 61 % annual cost savings compared to the existing rule-based control strategy, under the tested dynamic price scenarios. This paper also presents a sensitivity analysis on the cost savings with respect to the price profile variability, discusses the implementation effort for the price-responsive MPC, and compares the cost savings found in this study to those found in literature on the basis of dynamic price variability, or so-called Electricity Price Relative Standard Deviation.

Zanetti, Ettore↗
DOE OSTI2025

Chelation ion chromatography as an automated, and cost-effective analytical technique for REE determination: method development and applications

Rare earth elements (REEs), as critical minerals, have important uses in modern energy and technologies, yet are vulnerable to potential supply chain disruptions. To establish domestic REE supply chain, efficient REE detection methods for resource characterization and mineral processing will be needed to accelerate innovations for domestic REE recovery. This study developed a rapid, novel, and cost-effective for REE detection method using ion chromatography (IC) for aqueous samples. Various REE-targeted eluent gradients and post-column agent compositions were tested on the chelation ion chromatography (CIC) with UV-vis detector for optimal separation and quantification of REEs within approximately 20 min. The single-channel pump to deliver the post-column solution to UV-vis detector was replaced with a 4-channel gradient pump, to increase operation and maintenance efficiencies. After method optimization, resulting calibration curves for more than ten REEs achieved high coefficients of determination (R2>0.999) and low relatively standard deviations (below 3.24%), demonstrating sub-ppm level detection limits (0.0897 to 0.1149 mg/L). The reliability of the CIC method was validated through comparison with inductively coupled plasma mass spectrometry (ICP-MS), showing strong agreement in REE recovery from certified standards. The impact of metal ions and salts on REE recovery using CIC was also systematically investigated. CIC consistently exhibited reliable performance in the presence of salt solutions such as NaCl and Na₂SO₄ (up to 10,000 mg/L). Our study also found the presence of high concentrations of Al ions (at 10,000 mg/L) significantly influenced REE determination, and elevated concentrations of Ca ions affected the recovery of specific REEs, including La, Ce, and Pr. The CIC method was further tested on REE-containing eluents from solvent extraction tests out of fly ash leachates. REE detection from these real processing fluids were reported to achieve 90% to 100% recovery rate from our IC method, compared to ICP-MS results. This study underscores the potential of CIC as a reliable and efficient alternative for REE determination in complex matrices. It also highlights the importance of minimizing select interfering metal ions in solutions to ensure accurate results. The REE CIC method presents a promising, low-maintenance, salt-tolerant, and cost-effective alternative to traditional analytical methods for REE analysis.

detection of rare earth elements (REE)↗
DOE OSTI2025

Regional-scale soil carbon predictions can be enhanced by transferring global-scale soil–environment relationships

Accurate modelling and mapping soil organic carbon are crucial for supporting soil health restoration and climate change mitigation at both regional and global scales. However, regional soil predictions often suffer from data scarcity and high prediction uncertainty. Utilizing a pre-trained global-to-regional soil carbon predictive model can be a potential solution to address this challenge. Despite its promise, how to construct and apply the global-scale model to enhance regional-scale soil carbon mapping remains largely unexplored. Here, we propose the Global Soil Carbon Pre-trained Model (GSoilCPM), a deep-learning-based domain adaptative model, to enhance regional-scale soil carbon predictions. Based on large amount of environmental covariate data and 106,167 soil samples across the globe, we verify our hypothesis of the effectiveness of this 'global-to-regional' modelling strategy. The pre-trained model can be then transferred and fine-tuned to bridge the regional- and global-scale soil–environment relationships. We applied and validated this modelling strategy in four regional-scale study areas, three in the Northern Hemisphere and one in the Southern Hemisphere, each with distinct environmental background. Compared to traditional modelling approaches as a baseline, four case studies all demonstrated significant improvement in prediction accuracy across diverse environments and varying data availabilities. The average percentage improvement across all regions is 10.93% (absolute values decreased by 1.20 g kg−1 averagely) in MAE and 29.04% (absolute values increased by 0.10 averagely) in CCC. The applicability and future horizons of using GSoilCPM were further discussed. We further reveal that regions with fewer soil samples or lower baseline accuracy benefit more from the pre-trained global model. Our findings highlight the advantages of leveraging the generalized knowledge from global models to enhance specifically localized soil modelling, positioning a potential paradigm shift in digital soil mapping, and far-reaching implications for soil monitoring and land management.

Deep learning↗
DOE OSTI2025

Bonneville Dam Powerhouse 2 Gatewell Improvement Post Construction Evaluation (Final Report)

Modifications to vertical barrier screens (VBS) and the addition of concrete corbels to improve passage conditions for juvenile salmonids in the gatewells of Bonneville Dam’s second powerhouse (B2) were completed prior to the 2024 passage season. To evaluate the effectiveness of those modifications, PNNL carried out a post construction evaluation to contrast fish condition and mortality between two turbine unit operational ranges within the peak efficiency range. A block-treatment study design was implemented in 2024 to contrast descaling and mortality of juvenile salmonids sampled in the juvenile fish facility following exposure to turbine operations (middle versus upper 1% peak efficiency range) during spring and summer passage periods. In spring, 1.96% of juvenile salmonids sampled during mid-1% operations were descaled and 0.46% were mortalities. Of those sampled during upper 1% unit operations in spring, 2.90% were descaled and 0.95% were mortalities. Although these differences appeared to be meaningful, substantial exceedances of the upper 1% limit occurred during two treatment blocks of the spring study period. Fish collected during the upper 1% treatment of these two blocks experienced substantially higher rates of descaling and mortality compared to those collected during mid-1% treatments. Censoring these two upper 1% samples from the spring study period resulted in upper 1% descaling and mortality rates that were statistically similar to those from the mid-1% treatment. During the summer study period, 0.99% of juveniles sampled during mid-1% operations were descaled and 0.33% suffered mortality; these rates were significantly lower than the descaling (2.80%) and mortality (1.73%) rates observed during upper 1% treatments. Comparing the results from the 2024 study to those from the historical (2008–2013) baseline of unmodified units revealed that the descaling and mortality rates observed during upper 1% operations in spring 2024 were near the upper end of the historic range observed for mid-1% operations. Spring 2024 upper 1% descaling and mortality rates were below, or well below the median of historical mid and upper 1% (combined) rates, which suggests that the modifications have had a positive effect. Summer 2024 upper 1% descaling and mortality rates were at or above the top of the range of historical mid 1% and above or well above the median of historical mid and upper 1% (combined) rates. It is important to keep in mind that 2024 is a single year when considering these comparisons. Additional study could help confirm these results or seek a level of operation that achieves the desired outcomes for fish.

13 HYDRO ENERGY↗
DOE OSTI2025

Correlated dynamic disorder, octahedral tilts, and acoustic phonon softening in CsSnBr 3 and CsPbBr 3

Metal halide perovskites (MHPs) have emerged as highly promising materials for optoelectronic applications, with all-inorganic MHPs presenting enhanced stability compared to their hybrid counterparts. Here, in this study, we investigate the atomic dynamics and structural fluctuations in single crystals of CsSnBr⁢ 3 and CsPbBr⁢ 3 through systematic inelastic neutron scattering (INS) measurements as a function of temperature. Our experiments are compared with first-principle simulations, augmented with large-scale molecular dynamics modeling, based on machine-learned neural network potentials. Through both INS and simulations, we find quasi-elastic diffuse rods in reciprocal space in both compounds, originating from fluctuating planar domains featuring correlated tilts of Br octahedron. The diffuse rods exhibit a slow, overdamped dynamic process, modulated across 𝑸 space, reflecting the strong lattice anharmonicity of the inorganic framework. We do not find evidence for dynamic off-centering of the Sn 2+ ions besides phonon vibrations at the center of the Br octahedron. These results offer valuable insights into the unusual anharmonic atomic dynamics and intricate correlated structural distortions in MHPs, which will be critical for rationalizing and further tailoring their thermal and optoelectronic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Direction-specific enhanced diffusion of CO 2 in chiral hexagonal boron nitride nanotubes

To meet performance requirements, the next generation of gas separation membranes will need both high gas permeability and selectivity, attainable if we could coax adsorbates to minimize random Brownian motion and produce direction-specific diffusion along a desired axis. In this atomistic modeling study, we detail how direction-specific diffusion of CO 2 can be achieved in chiral hexagonal boron nitride nanotubes (hBNNTs) by means of a non-Knudsen diffusion mechanism. Our findings detail how this mechanism of diffusion is driven by interactions with the tube walls and enables the CO 2 molecules to diffuse along the nanotube’s z-axis with minimized collisions and directional changes. hBNNTs with chiral indices exhibit CO 2 diffusion rates faster than non-chiral tubes of comparable and larger diameters. Of the hBNNTs studied, a (7,3) tube appears to be ideally sized (3.7 Å radius) exhibiting CO 2 diffusion that is 3.4 times faster than diatomic N 2 . Applying this mechanism of diffusion to hypothetical sheet membranes prepared with aligned chiral (7,3) hBNNTs results in membranes with a calculated CO 2 /N 2 permselectivity of 170 and a CO 2 permeability limit of nearly 1.35 ×10 7 Barrer, readily surpassing the Robeson upper bound for CO 2 /N 2 separations.

CO2↗
DOE OSTI2025

Virocell Necromass Provides Limited Plant Nitrogen and Elicits Rhizosphere Metabolites That Affect Phage Dynamics

Bacteriophages impact soil bacteria through lysis, altering the availability of organic carbon and plant nutrients. However, the magnitude of nutrient uptake by plants from lysed bacteria remains unknown, partly because this process is challenging to investigate in the field. In this study, we extend ecosystem fabrication (EcoFAB 2.0) approaches to study plant-bacteria-phage interactions by comparing the impact of virocell (phage-lysed) and uninfected 15 N-labelled bacterial necromass on plant nitrogen acquisition and rhizosphere exometabolites composition. We show that grass Brachypodium distachyon derives some nitrogen from amino acids in uninfected Pseudomonas putida necromass lysed by sonication but not from virocell necromass. Additionally, the bacterial necromass elicits the formation of rhizosphere exometabolites, some of which (guanosine), alongside tested aromatic acids ( p -coumaric and benzoic acid), show bacterium-specific effects on bacteriophage-induced lysis when tested in vitro. The study highlights the dynamic feedback between virocell necromass and plants and suggests that root exudate metabolites can impact bacteriophage infection dynamics.

Brachypodium↗
DOE OSTI2024

Enhancing carbon dioxide capture under humid conditions by optimizing the pore surface structure

Metal–organic frameworks (MOFs) exhibit significant potential for mitigating carbon emissions due to their high porosity and tunability. Despite numerous reports on CO 2 capture by MOF sorbents, a common challenge is their poor selectivity for CO 2 over water. Moreover, in-depth studies are much needed to elucidate the relationships among the pore surface structure, hydrophobicity, and CO 2 uptake capacity/selectivity. In this work, we investigate the factors influencing CO 2 adsorption capacity and selectivity under humidity in a series of isoreticular pillar-layer structures, Ni 2 (L) 2 (dabco) (L = bdc, ndc, adc). Our study shows that increasing ligand conjugation not only results in increased hydrophobicity, decreased pore size and BET surface area, but also leads to the change of primary binding sites of water molecules and higher binding energy of CO 2 , all of which contribute to largely increased CO 2 uptake capacity under humid conditions. Additionally, increasing ligand conjugation and consequently hydrophobicity slow down and reduce competitive water adsorption drastically. Notably, the MOF made of ligand with the highest conjugation, Ni 2 (adc) 2 (dabco), exhibits significantly enhanced CO 2 adsorption in N 2 /CO 2 binary mixtures under relatively high humidity (50% RH), with an increase of ~31% and ~36% for the composition of 15/85 and 50/50, respectively, compared to dry conditions. An experimental FTIR study and DFT theoretical calculations confirm that H 2 O occupies different primary binding site in Ni 2 (bdc) 2 (dabco) and Ni 2 (adc) 2 (dabco), and under humid conditions a higher binding energy of CO 2 is achieved with preferential H 2 O/CO 2 co-adsorption in Ni 2 (adc) 2 (dabco), potentially creating additional adsorption sites for CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Nanoscopic Titanium Dioxide Overlayers Improve the Durability of Porphyrin Molecular Electrocatalysts while Maintaining Molecular Structure and Redox Activity

Molecular catalysts, such as metalated porphyrins, are attractive cocatalysts for photocatalytic water splitting owing to their potential to simultaneously catalyze target reactions at their metal center, extend charge-separated-state lifetimes, and accumulate the requisite charge for product formation. However, porphyrin catalysts, like most molecular catalysts, are often limited by poor stability associated with demetalation, inactivation by undesired bonding (e.g., O2 coordination/redox/dimerization), and detachment from electrode supports or semiconducting photoabsorbers. In this study, nanoscopic titanium dioxide (TiO2) overlayers, deposited by atomic layer deposition (ALD), are demonstrated to encapsulate cobalt(III) meso-tetra(4-carboxyphenyl) porphyrin chloride (CoTCPP) molecular catalysts and thereby improve their adhesion to electrode surfaces over a wide range of electrode potentials spanning from -1.0 V vs RHE to +1.8 V vs RHE. Through analysis of Raman and ultraviolet-visible spectroscopy, it was confirmed that the metalloporphyrin structure was maintained when the surface-bound CoTCPP was encapsulated by 10 - 250 ALD cycles (~2 - 18 nm thick) of TiO2. Additional characterization of CoTCPP catalysts before and after electrochemical measurements reveals that up to 97% of the encapsulated CoTCPP remains tethered to the electrode surface after chronoamperometry tests under hydrogen evolution reaction (HER) conditions, compared to <36% for unencapsulated CoTCPP. This study also shows that encapsulated CoTCPP molecules remain partially redox active for overlayers up to 8 nm, which can also attenuate undesired redox mediator back reactions like ferricyanide reduction.

08 HYDROGEN↗
DOE OSTI2024

A Review on Solid State Batteries: Life Cycle Perspectives

This report briefly reviews the characteristics of solid-state batteries (SSBs) and the life-cycle analysis (LCA) studies that have been completed for SSBs. Compared with conventional lithium-ion batteries (LIBs), SSBs offer improved safety and potentially higher energy density — both enabled by replacing liquid electrolytes with solid electrolytes and using lithium metal anodes. Several challenges impede the commercialization of SSBs, primarily related to the stability of the interface between the solid electrolyte and the electrodes. Several options are under consideration for SSB electrolyte and cathode chemistries. As a result, the production processes for these components and the corresponding battery packs are still under development and can differ significantly from those used for conventional LIB pack production. A robust comparison of SSBs with LIBs through LCA is important to analyze the environmental benefits and challenges associated with this alternative battery system. While the literature provides only a few LCA studies focused on SSBs, with significant uncertainty in their life-cycle inventories (LCIs), those studies collectively suggest that solid electrolyte manufacturing is the major environmental hotspot, followed by cathode and anode production.

25 ENERGY STORAGE↗
DOE OSTI2026

Validation of the DESI DR2 Ly⁢ 𝛼 BAO analysis using synthetic datasets

The second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI), containing data from the first three years of observations, doubles the number of Lyman-α (Ly α) forest spectra in DR1 and it provides the largest dataset of its kind. To ensure a robust validation of the baryonic acoustic oscillation (BAO) analysis using Ly α forests, we have made significant updates compared to DR1 to both the mocks and the analysis framework used in the validation. In particular, we present CoLoRe-QL, a new set of Lyα mocks that use a quasilinear input power spectrum to incorporate the nonlinear broadening of the BAO peak. Here, we have also increased the number of realizations used in the validation to 400, compared to the 150 realizations used in DR1. Finally, we present a detailed study of the impact of quasar redshift errors on the BAO measurement, and we compare different strategies to mask damped Lyman-α absorbers in our spectra. The BAO measurement from the Ly α dataset of DESI DR2 is presented in a companion publication.

Casas, L. [Institut de Física d’Altes Energies (IF↗
DOE OSTI2025

Validation of the DESI DR2 Ly$\alpha$ BAO analysis using synthetic datasets

The second data release (DR2) of the Dark Energy Spectroscopic Instrument (DESI), containing data from the first three years of observations, doubles the number of Lyman-$\alpha$ (Ly$\alpha$) forest spectra in DR1 and it provides the largest dataset of its kind. To ensure a robust validation of the Baryonic Acoustic Oscillation (BAO) analysis using Ly$\alpha$ forests, we have made significant updates compared to DR1 to both the mocks and the analysis framework used in the validation. In particular, we present CoLoRe-QL, a new set of Ly$\alpha$ mocks that use a quasi-linear input power spectrum to incorporate the non-linear broadening of the BAO peak. We have also increased the number of realisations used in the validation to 400, compared to the 150 realisations used in DR1. Finally, we present a detailed study of the impact of quasar redshift errors on the BAO measurement, and we compare different strategies to mask Damped Lyman-$\alpha$ Absorbers (DLAs) in our spectra. The BAO measurement from the Ly$\alpha$ dataset of DESI DR2 is presented in a companion publication.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

THERMS Technology Commercialization Fund Final Report

The technology commercialization fund assisted with the design and development of an intermediate scale packed be thermal energy storage system. Presented in this final report is the design, testing, and modeling of a 100 kWh th radial packed-bed. Air is used as a heat transfer fluid and 3/8” pea gravel is used as the storage medium. Testing has demonstrated the formation of a thermocline within the packed-bed. An air charging temperature of 450 °C was achieved resulting in a charging power of 26.5 kWh th . The radial packed-bed was charged for 5 hours and discharged for 5 hours. Minimal temperature variation was observed at the bottom, middle, and top axial locations of the radial packed-bed which suggests that buoyancy and hydrodynamics in the injection well had a minimal effect on the uniformity of air flow through the bed during charging and discharging. This indicates that the forced convection in a radial direction is dominating the flow regime compared to the buoyancy. The findings of this study suggest an increased air duct diameter through the air heater will increase the charging temperature and increase air mass flow through the system. Increased mass flow through the packed-bed is hypothesized to shorten the thermocline length. Modeled and measured results are compared, and it is here determined that a more comprehensive CFD model will aid in the understanding of air flow and thermocline evolution within the packed-bed.

25 ENERGY STORAGE↗
DOE OSTI2025

Imaging Photonic Resonances within an All‐Dielectric Metasurface via Photoelectron Emission Microscopy

Dielectric metasurfaces, through volume‐type photonic resonances, enable precise control of light‐matter interactions for applications including imaging, holography, and sensing. The application space of dielectric metasurfaces has extended from infrared to visible wavelengths by incorporating high refractive index materials, such as titanium dioxide (TiO 2 ). Understanding the fundamental and fabrication limits for these applications requires metrology with nanoscale resolution, sensitivity to electromagnetic fields within the meta‐atom volume, and far‐field excitation. In this work, photoelectron emission microscopy (PEEM) is used to image field distributions of photonic resonances in a TiO 2 metasurface excited with far‐field, visible‐wavelength illumination. The local volumetric field variations within the meta‐atoms are analyzed as a function of illumination angle and polarization by comparing photoelectron images to finite‐difference time‐domain simulations. This study determines the inelastic mean free path of very low‐energy (<1 eV) photoelectrons to be 35 ± 10 nm, which is comparable to the meta‐atom height thereby highlighting PEEM sensitivity to resonances within the volume. Additionally, the simulations reveal high sensitivity of PEEM images to an in‐plane component of the illumination k ‐vector. These results demonstrate that photoelectron imaging with subwavelength resolution offers unique advantages for examining light‐matter interactions in volume‐type (as opposed to surface) photonic modes within dielectric nanophotonic structures.

electron inelastic mean free path↗
DOE OSTI2026

Mechanistic insights into low-temperature oxidation of carbon fibers: Influence of hydrogen defects and crystallite size

Although oxidation mechanisms have been exhaustively studied for graphite, similar analyses of carbon fibers are comparatively sparse. Most prior work has focused on quantifying weight loss or assessing protective surface coatings designed to slow oxidation. The use of optical spectroscopic techniques for oxidation analyses is comparatively unexplored, but such techniques could provide an early indicator of fiber oxidation that would undermine carbon fiber performance. Here, in this work, we applied Raman spectroscopy to study oxidation-induced spectral alterations in 16 carbon fiber types from 7 manufacturers oxidized at 300 °C for 72 h, 400 °C for 8 h, and 500 °C for 1 h. We connect these results with structural properties of the carbon fibers obtained through wide-angle X-ray scattering, identifying a linear dependence between the reactivity of carbon fibers and the crystallite size of the unperturbed fibers. We then demonstrate that substituted hydrogen defects are likely removed from the fiber surface during oxidation and use the relative defect concentration to predict the Raman spectral change as a function of temperature and time, assuming Arrhenius behavior.

Carbon fiber↗