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DOE OSTI2025

Ruthenium/Carbon Nanocomposites for Efficient Hydrogen Electrocatalysis: Impacts of Halide Residues

Ruthenium has emerged as a promising substitute for platinum toward the hydrogen evolution/oxidation reaction (HER/HOR). Herein, ruthenium/carbon composites are prepared by magnetic induction heating (300 A, 10 s) of RuCl3, RuBr3 or RuI3 loaded on hollow N-doped carbon cages (HNC). The HNC-RuCl3-300A sample consists of Ru nanoparticles (dia. 1.96 nm) and abundant Cl residues. HNC-RuBr3-300A possesses a larger nanoparticle size (≈19.36 nm) and lower content of Br residues. HNC-RuI3-300A contains only bulk-like Ru agglomerates with a minimal amount of I residues, due to reduced Ru-halide bonding interactions. Among these, HNC-RuCl3-300A exhibits the best HER activity in alkaline media, with a low overpotential of only -26 mV to reach 10 mA cm-2, even outperforming Pt/C, and can be used as the cathode catalyst for anion exchange membrane water electrolyzer (along with commercial RuO2 as the anode catalyst), producing 0.5 A cm- 2 at 1.88 V for up to 100 h, a performance markedly better than that with Pt/C. HNC-RuCl3-300A also exhibits the best HOR activity, with a half-wave potential (+18 mV) even lower than that of Pt/C (+35 mV). These activities are ascribed to the combined contributions of small Ru nanoparticles and Ru-to-halide charge transfer that weaken H adsorption.

Yu, Bingzhe↗

DOE OSTI2025

Experimental Pathways for Detecting Double Superionicity in Planetary Ices

The ice giant planets Uranus and Neptune are assumed to contain large amounts of planetary ices such as water, methane, and ammonia. The properties of mixtures of such ices at the extreme pressures and temperatures of planetary interiors are not yet well understood. Ab initio computer simulations have predicted that a number of ices exhibit a hydrogen superionic state and a doubly superionic state. Since the latter state has not yet been generated with experiments, we outline here two possible pathways for reaching and detecting such a state with dynamic compression experiments. Here, we suggest X-ray diffraction as the principal tool for detecting when the material becomes doubly superionic and the sublattice of one of the heavy nuclei melts. That would require a temperature of ~3500 K and pressures greater than ~200 GPa for H 3 NO 4 , which we use as an example material here. Such conditions can be reached with experiments that employ an initial shock that is followed by a ramp compression wave. Alternatively, one may use triple-shock compression because a single shock does not yield sufficiently high densities.

Neptune↗

DOE OSTI2025

Resist! : Sustaining forest carbon sequestration and wood production after insect disturbance

Disturbances from insect pests threaten ecologically and economically important goods and services supplied by forests, including wood production and carbon sequestration. We highlight the factors that influence these services’ resistance, a term quantifying the initial response to disturbance. Insects inflict damage through a range of mechanisms, prompting distinct plant physiological responses that scale to influence ecosystem processes and, with time, goods and services. The degree and timing of tree mortality and defoliation affect the amount of residual vegetation available to support compensatory wood production and influence carbon sequestration by changing rates of detritus-fueled decomposition. Compounding, or sequential, insect attacks may prime a forest for additional disturbance, further eroding wood production and carbon sequestration. Forest management practices that promote biological and structural diversity, and augment or retain limiting biological and nutrient resources, may buffer against the effects of insect pests on wood production and carbon sequestration.

Gough, Christopher M. [Virginia Commonwealth Univ.↗

DOE OSTI2024

Soil water percolation and nutrient fluxes as a function of topographical, seasonal and soil texture variation in Central Amazonia, Brazil

Abstract Understanding soil water dynamics and transport of nutrients is challenging in tropical rainforests due to the uniqueness of several properties related to soils, vegetation and seasonality that make relating patterns found in temperate environments to tropical sites difficult. We address the need for better edaphic characterization in tropical environments by investigating soil water percolation rates and chemistry across topographic, soil texture and seasonal gradients in a mature tropical rainforest in Central Amazonia, Brazil. We utilized a passive wick flux meter (e.g., drainage lysimeter) to directly measure real‐time percolation fluxes at 60‐cm depth, and to sample a suite of chemical species across plateau, slope and valley topographic positions. We found percolation flux volume and chemical exports generally increase with decreasing elevation and clay content, which was lowest in the valley. Daily percolation flux was observed to be 2.39 ± 0.44 in plateau, 3.01 ± 0.50 in slope and 6.16 ± 0.83 mm in valley. Most solutes were present in small amounts of <1 mg L −1 , such as PO₄ 3− , Fe 2+ /Fe 3+ and Mn 2+ ; however, NO 3 − concentrations were >20 mg L −1 , even exceeding 100 mg L −1 in the valley. Based on additional isotopic analysis, we speculate high NO 3 − concentrations are partially an artefact of root decomposition following installation of the flux meters. The empirical relationships we show among percolation volume and nutrient exports under varying topographies and soil textures can improve Earth System Model performance by better constraining ecohydrological relationships to nutrient fluxes, which can in‐turn better illuminate the important factors that govern their behaviour.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Overlapping Schwarz Methods Are Not Anisotropy‐Robust Multigrid Smoothers

We analyze overlapping multiplicative Schwarz methods as smoothers in the geometric multigrid solution of two-dimensional anisotropic diffusion problems. For diffusion equations, it is well known that the smoothing properties of point-wise smoothers, such as Gauss Seidel, rapidly deteriorate as the strength of anisotropy increases. On the other hand, global smoothers based on line smoothing are known to generally provide good smoothing for diffusion problems, independent of the anisotropy strength. Here, a natural question is whether global methods are really necessary to achieve good smoothing in such problems, or whether it can be obtained with locally overlapping block smoothers using sufficiently large blocks and overlap. Through local Fourier analysis and careful numerical experimentation, we show that global methods are indeed necessary to achieve anisotropy-robust smoothing. Specifically, for any fixed block size bounded sufficiently far away from the global domain size, we find that the smoothing properties of overlapping multiplicative Schwarz rapidly deteriorate with increasing anisotropy, irrespective of the amount of overlap between blocks. Moreover, our results indicate that anisotropy-robust smoothing requires blocks of diameter 𝒪⁡(𝜖 −1/2 ) for anisotropy ratio 𝜖 ∈(0,1] .

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

A fast and sensitive size-exclusion chromatography method for plasma extracellular vesicle proteomic analysis

Extracellular vesicles (EVs) carry diverse biomolecules derived from their parental cells, making their components excellent biomarker candidates. However, purifying EVs is a major hurdle in biomarker discovery since current methods require large amounts of samples, are time-consuming and typically have poor reproducibility. Here we describe a simple, fast, and sensitive EV fractionation method using size exclusion chromatography (SEC) on a fast protein liquid chromatography (FPLC) system. Our method uses a Superose 6 Increase 5/150, which has a bed volume of 2.9 mL. The FPLC system and small column size enable reproducible separation of only 50 µL of human plasma in 15 min. To demonstrate the utility of our method, we used longitudinal samples from a group of individuals who underwent intense exercise. A total of 838 proteins were identified, of which, 261 were previously characterized as EV proteins, including classical markers, such as cluster of differentiation (CD)9 and CD81. Quantitative analysis showed low technical variability with correlation coefficients greater than 0.9 between replicates. The analysis captured differences in relevant EV proteins involved in response to physical activity. Our method enables fast and sensitive fractionation of plasma EVs with low variability, which will facilitate biomarker studies in large clinical cohorts.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Determining sulfur speciation in oxidatively crosslinked degradable polymers using sulfur K-edge X-ray absorption spectroscopy

A new family of water-degradable elastic polymers prepared by oxidative crosslinking of the parent polythionolactones shows promise in a broad range of applications, but the compositions of these materials elude conventional analytical methods. Here, in this work, we use sulfur K-edge X-ray absorption spectroscopy to quantify the amounts of thioether, disulfide, sulfone, sulfate ester, and thionoester in each polymer and to rule out the presence of several other functional groups, including sulfonate, thiosulfonate, sulfate, and sulfoxide. We rationalize this speciation as a function of linker flexibility in the context of sulfinyl cycloaddition reactions and propose a mechanism of aggregation for the oxidized polymers. Our results correlate with swelling ratios but not with porosity nor crosslink density measurements, demonstrating the importance of pairing mechanical and chemical techniques when characterizing heterogeneous organic polymers. Finally, we take advantage of the proximity of the gold M 4,5 -edges to the sulfur K-edge to analyze the binding and reactivity of Au(III) with the crosslinked polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Comparative Analyses of Bioequivalence Assessment Methods for In Vitro Permeation Test Data

ABSTRACT For topical, dermatological drug products, an in vitro option to determine bioequivalence (BE) between test and reference products is recommended. In particular, in vitro permeation test (IVPT) data analysis uses a reference‐scaled approach for two primary endpoints, cumulative penetration amount (AMT) and maximum flux ( J max ), which takes the within donor variability into consideration. In 2022, the Food and Drug Administration (FDA) published a draft IVPT guidance that includes statistical analysis methods for both balanced and unbalanced cases of IVPT study data. This work presents a comprehensive evaluation of various methodologies used to estimate critical parameters essential in assessing BE. Specifically, we investigate the performance of the FDA draft IVPT guidance approach alongside alternative empirical and model‐based methods utilizing mixed‐effects models. Our analyses include both simulated scenarios and real‐world studies. In simulated scenarios, empirical formulas consistently demonstrate robustness in approximating the true model, particularly in effectively addressing treatment–donor interactions. Conversely, the effectiveness of model‐based approaches heavily relies on precise model selection, which significantly influences their results. The research emphasizes the importance of accurate model selection in model‐based BE assessment methodologies. It sheds light on the advantages of empirical formulas, highlighting their reliability compared to model‐based approaches and offers valuable implications for BE assessments. Our findings underscore the significance of robust methodologies and provide essential insights to advance their understanding and application in the assessment of BE, employed in IVPT data analysis.

Leon, Sami↗

DOE OSTI2024

Large-Volume Injection and Assessment of Reference Standards for n -Alkane δD and δ 13 C Analysis via Gas Chromatography Isotope Ratio Mass Spectrometry

Compound-specific stable isotope analysis of hydrogen (δD) and carbon (δ 13 C) in organic compounds is a valuable tool in biogeochemical research. A key limitation of this method is the relatively large amount of sample required to achieve desirable precision. We developed a large-volume (20 μL) injection method that allows for high throughput analysis of less concentrated samples and tested it for δ 13 C and δD measurements of n-alkanes. We also conducted a comparison of reference standards and assessed several methods to normalize and correct n-alkane δD and δ13C measurements. The mean precision of the δD method based on 233 environmental n-alkane samples (two to three replications per sample) is 4.0‰ (1σ, estimated from the weighted mean of the pooled unbiased standard deviations) and 0.46‰ (1σ) for δ 13 C from 37 environmental samples (two to three replications per sample). The evaluation of reference standards shows that the use of n-alkane standards with large offsets in δD values in adjacent n-alkane chains can lead to biases in measurement correction. The large-volume injection method shows good reproducibility of δ 13 C and δD measurements of n-alkanes and reduces the required sample concentration by about 80%. We propose that for δD measurements, a reference standard set should be used in which each reference standard has a limited range of δD values and no adjacent n-alkane chains, to minimize memory effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Surface analysis insight note: Illustrating the effect of adventitious contamination on Pt photoemission peak intensities

Adventitious carbon contaminations are not only omnipresent and used for charge referencing of XPS spectra but also can alter the apparent presence of the element peaks that span over the large spectral window of binding energies. This Insight note describes the effect of an adventitious contamination layer on Pt and presents, in brief, the approach whereby the component spectra are derived for ion beam cleaned Pt samples that can then utilize linear mathematics to peak fit said spectra thus quantifying the amount of each component including that assigned to the contamination itself of Pt metal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Machine Learning Discrimination and Ultrasensitive Detection of Fentanyl Using Gold Nanoparticle-Decorated Carbon Nanotube-Based Field-Effect Transistor Sensors

The opioid overdose crisis is a global health challenge. Fentanyl, an exceedingly potent synthetic opioid, has emerged as a leading contributor to the surge in opioid-related overdose deaths. The surge in overdose fatalities, particularly due to illicitly manufactured fentanyl and its contamination of street drugs, emphasizes the urgency for drug-testing technologies that can quickly and accurately identify fentanyl from other drugs and quantify trace amounts of fentanyl. In this paper, gold nanoparticle (AuNP)-decorated single-walled carbon nanotube (SWCNT)-based field-effect transistors (FETs) are utilized for machine learning-assisted identification of fentanyl from codeine, hydrocodone, and morphine. The unique sensing performance of fentanyl led to use machine learning approaches for accurate identification of fentanyl. Employing linear discriminant analysis (LDA) with a leave-one-out cross-validation approach, a validation accuracy of 91.2% is achieved. Meanwhile, density functional theory (DFT) calculations reveal the factors that contributed to the enhanced sensitivity of the Au-SWCNT FET sensor toward fentanyl as well as the underlying sensing mechanism. Finally, fentanyl antibodies are introduced to the Au-SWCNT FET sensor as specific receptors, expanding the linear range of the sensor in the lower concentration range, and enabling ultrasensitive detection of fentanyl with a limit of detection at 10.8 fg mL –1 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Effect of Entropic Constraints on the Thermodynamics of Molecular Adsorption in Nano‐Porous Materials

Abstract Gas separation is a critical industrial process that consumes a significant amount of energy due to the widely used techniques that are currently employed. Adsorptive materials—such as metal–organic frameworks (MOFs)—show promise as an energy‐efficient alternative. Of particular current interest are novel, temperature‐dependent separation processes in MOFs, such as the recently reported separation of ternary isomeric hydrocarbon mixtures within one and the same material. However, the mechanisms of these highly desirable separations remain poorly understood. Herein, through a combination of ab initio simulations and statistical mechanics, it is shown that the temperature dependence is the result of a constraint on the guest molecule's entropic degrees of freedom when loaded into the MOF, caused by the fortuitous tight fitting of the guest inside the pore. While the framework applies to all molecular adsorption in porous media, it is essential for the description of large molecules in small pores, which is demonstrated here using the separation of C6 isomers in Ca(H 2 tcpb) as a test case. The developed framework and analysis not only reveal the reason why separation occurs but also predict the temperatures at which it takes place, thus opening the door to newly designed MOFs with tailor‐made precision.

Chemistry↗

DOE OSTI2025

Efficient Perovskite Solar Cells Achieved via Rapid Photonic Annealing of all Stacking Layers: Unveiling the Crystallization Energy Window

In this study, we report high-performance perovksite solar cells (PSCs) with rapid photonic annealing (RPA) of all stacking layers, enabled by ultraviolet (UV) light-emitting diode (LED) sources, to replace lengthy and energy-intensive thermal annealing (TA). The UV-LED annealing technique allows for layer-specific annealing, where the selected light source provides a precise UV wavelength for maximizing the amount of light absorption by the target layer. The disparity in optical absorption between the target layer and the underlying films allows the stack of the underlying films to remain relatively unaffected, making this process ideal for heating sensitive substrates. Along with a systematic investigation into the layer-specific annealing mechanism of RPA, the results demonstrated that this UV-LED-based photonic annealing of all stacking layers (7 s for perovskite absorber) can produce PSCs with the power conversion efficiency (PCE) of over 23%, the highest reported among optically annealed PSCs. Moreover, the RPA device retains over 80% of the initial PCE over 1000 h under continuous 1 sun illumination at 55 °C and 30%–60% relative humidity (RH), while TA control device drops to 50% of its initial efficiency. Furthermore, these findings represent significant strides toward achieving rapid, cost-effective, and scalable manufacturing of commercial perovskite photovoltaics (PV).

14 SOLAR ENERGY↗

DOE OSTI2024

Unusual Electrical Conductivity Enhancement in Stable n‐Type Carbon Nanotube Networks

Organic molecule-doped n-type single-walled carbon nanotube (SWCNT) networks are promising candidates for advanced energy applications, such as flexible thermoelectrics and photovoltaics. Yet charge transport in n-type SWCNTs is limited by two factors: i) charge localization impeding inter-tube transport caused by disordered mesostructure of randomly oriented SWCNTs and ii) reduction of charge carrier concentration driven by oxidation. Herein, studied the relationship between the mesostructure and thermoelectric properties of n-type SWCNTs obtained by surfactant-functionalization and polymer-dopant grafting. Surprisingly, the electrical conductivity of the polymer-doped SWCNTs keeps increasing with increasing polymer content, even after the saturation of carrier concentration, resulting in 12x higher conductivity on polymer-doping compared to surfactant-functionalization. While hopping transport typically dominates in disordered systems, it is shown that a bridging effect from the polymer causes unusual band-like conduction in polymer-doped SWCNTs. Additionally, since surfactants are essential to prevent oxidation and retain n-type over a long duration, shows that SWCNTs obtained through a dual-functionalization strategy using both polymer-dopant and surfactant, demonstrates a long-term stable high n-type thermoelectric power factor, when the surfactant amount is carefully controlled. Besides thermoelectrics, the findings are of general interest to developing stable and conductive n-type SWCNTs for various energy and electronic applications.

carbon nanotubes↗

DOE OSTI2026

Healable Coatings as a Mechanism to Repair Leading Edge Erosion in Wind Energy

Wind turbine blades are highly engineered structures designed to face temperature extremes and high winds. However, erosion of the blade's leading edge and subsequent repair remains a significant and costly challenge for the wind energy industry. Repair of these leading edges can lead to large amounts of downtime for the turbine and significant operational inefficiencies. In this work, the strength of adhesion and healing ability of a commercially available vitrimer (Mallinda's VITRIMAX) was compared to that of a thermoplastic resin, which has previously been demonstrated in wind energy applications (Arkema's Elium) to evaluate their efficacy as surface coatings for wind turbine blades, particularly their leading edges. Vitrimers are a class of inherently reprocessable thermosets, and it was theorized that vitrimer-based leading edge coatings could enable more robust and efficient wind turbine blades with decreased operational downtime and safer maintenance practices. It was found that the VITRIMAX adhered better to the wind blades' surfaces than both the manufacturer's paint and Elium, with increases in pull-off strength of adhesion ranging from 24% to 83% above that of the original paint. Furthermore, the VITRIMAX adhered strongly to the underlying composite of each blade with strength of adhesion values increasing in ranges from 42% to 97% above that of the original paint. Finally, the vitrimer coating showed an 88% decrease in surface roughness compared to end-of-life blade materials, and initial healing demonstrations in which coatings were manually scratched and subsequently healed exhibited an ~84.5% decrease in scratch depths.

Hubbard, Amber [ORNL]↗

DOE OSTI2025

Evaluation of common trap types for capturing wild pigs

Abstract Wild pigs ( Sus scrofa ) are one of the most ecologically harmful invasive vertebrates globally. Due to their negative impacts, wild pig populations are managed via trapping, yet studies investigating various trap designs have been limited in duration, location, and number of trappers. Using data from professional trappers across the southeastern U.S., we evaluated the performance of 3 wild pig trap types (corral, drop, passive net), and the effect of forage season (barren, green‐up, masting) on trapping success. Specifically, we compared trap effectiveness (estimated proportion of targeted wild pigs caught per capture event), trap night effort (number of days to first catch), and the amount of bait and time used per individual take over the lifetime of each trap location across the 3 trap types and forage seasons. Across >850 capture events by 31 trappers, all 3 trap types evaluated were effective at capturing entire social groups of wild pigs. Few differences were observed among trap types, although drop traps in masting season captured a greater estimated proportion of wild pigs per capture event compared to other trap type‐season combinations. Our data also revealed that passive net traps required slightly more bait/wild pig captured than drop traps but there was no difference in the time/wild pig captured among traps. Our findings demonstrate that when operated by wildlife professionals, multiple designs of wild pig traps can be effective at removing targeted groups of wild pigs. Further, our results offer insights regarding the performance of wild pig trap types across seasons that can be used to inform wild pig trapping programs.

Taylor, Charles R. [Warnell School of Forestry and↗

DOE OSTI2025

Machine Learning in the Context of Laser-Induced Breakdown Spectroscopy

The integration of machine learning (ML) with Laser-Induced Breakdown Spectroscopy (LIBS) has revolutionized the analytical capabilities of LIBS. The combi-nation of both methods enables more accurate and efficient data analysis. While LIBS itself is a powerful technique for elemental analysis, the vast amount of spectral data it generates can be hard to interpret. Machine learning addresses these challenges by leveraging algorithms that can learn from data, identify patterns, and make predictions without explicit programming for the interpretation of each specific task. In LIBS application, ML techniques are used to enhance various analytical processes. For example, ML algorithms can classify materials based on their spectral fingerprints, predict the concentration of elements in a sample, and identify underlying patterns within complex datasets. Here, this application improves the precision of LIBS analyses while significantly reducing the time required for data processing and interpretation. In this chapter, the fundamental concepts of ML will be discussed first. Following this, the process of data splitting and the importance of feature selection will be examined. Several machine learning methods will then be closely examined, exploring how each can benefit LIBS analysis and highlighting their respective advantages and shortcomings. This structured approach will provide a comprehensive understanding of the integration of ML in the context of LIBS analysis.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Inscribing geodesic circles on the face of the superstratum

Abstract We use families of circular null geodesics as probes of a family of microstate geometries, known as (1,0, n) superstrata. These geometries carry a left-moving momentum wave and the behavior of some of the geodesic probes is very sensitive to this background wave. The left-moving geodesics behave like BPS particles and so can be placed in circular orbits anywhere in the geometry and actually “float” at fixed radius and angle in the three-dimensional “capped BTZ” geometry. The right-moving geodesics behave like non-BPS particles. We show that they provide a simple geometric characterization of the black-hole bound: when the momentum charge of the geometry is below this bound, such geodesics can be placed anywhere, but exceeding the bound, even by a small amount, means these geodesics are restricted to the deep interior of the geometry. We also show that for left-moving string probes, the tidal forces remain comparable with those of global AdS 3 . Nevertheless, for some of these probes, the “bumps” in the geometry induce an oscillatory mass term and we discuss how this can lead to chaotic scrambling of the state of the string.

Physics↗