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DOE OSTI2024

A Perspective on the Impact of Group Delay Dispersion in Future Terahertz Wireless Systems

This article discusses the challenges and opportunities of managing group delay dispersion (GDD), and its relation to the performance standards of future sixth-generation (6G) wireless communication systems utilizing terahertz frequency waves. The unique susceptibilities of 6G systems to GDD are described, along with a quantitative description of the sources of GDD, including multipath, rough surface scattering, intelligent reflecting surfaces, and propagation through the atmosphere. An experimental case-study is presented that confirms previous models quantifying the impact of atmospheric GDD. Several GDD manipulation strategies are presented, illustrating their hindered effectiveness in the 6G context. Conversely, some benefits of leveraging GDD to enhance 6G systems, such as improved security and simplified hardware, are also discussed. Finally, a perspective on using photonic GDD control devices is provided, revealing quantitative benefits that may unburden existing equalization schemes. Here, the article argues that GDD will uniquely and significantly impact some 6G systems, but that its careful consideration along with new mitigation strategies, including photonic devices, will help optimize system performance. The conclusion provides a perspective to guide future research in this area.

Strecker, Karl [Oklahoma State University, Stillwa↗

DOE OSTI2026

UCB-GLOBES: An open-access mass spectral database of identified and unidentified atmospheric organic compounds

Chemical characterization of atmospheric organic aerosols using gas chromatography with 70 eV electron ionization mass spectrometry (GC/EI-MS) has been used for decades in advancing molecular marker detection and identification, though primarily through suspect screening and/or targeted analyses. To advance non-targeted analyses of environmental samples, we have catalogued approximately 27 000 mass spectra (MS) of the trimethylsilyl derivatives of semi-volatile organic aerosol (OA) analytes in the open-access University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES). Analytes were observed in ambient samples from the U.S. and the Central Amazon and/or laboratory simulations of secondary OA (SOA) formation. These samples are representative of OA under urban and biomass burning influences as well as SOA derived from biogenic precursors (e.g., isoprene, monoterpenes, sesquiterpenes) and biomass burning intermediates. MS are documented in UCB-GLOBES without regard to known chemical identity, annotated with extensive metadata such as sample source/experimental conditions, any structural information gained from MS analyses, and predicted chemical properties such as average carbon oxidation state and carbon number. UCB-GLOBES MS are compatible for importing into the NIST MS Search program, and we have also provided a Jupyter Notebook for MS visualization and comparisons. We demonstrate the utility of UCB-GLOBES through MS reanalyses of prior analytes observed in ambient data, finding a 20 % reduction in the number of analytes assigned to OA source categories reliant solely on time series correlation and an overall 11 % increase in new MS-based OA source categorization for the Southeast U.S. For 1513 analytes observed previously in the Central Amazon, we found 375 MS matches using UCB-GLOBES vs. 136 MS matches during prior analyses, representing a 14 % gain in newly confirmed or newly categorized OA species. While OA from laboratory oxidation experiments in UCB-GLOBES are highly diverse chemically, on average only 29 % of UCB-GLOBES MS have a mass spectral match to another MS entry in UCB-GLOBES and/or in databases of known compounds (i.e. NIST MS Database, Adams Essential Oil, MANE Flavor and Fragrance Company). This indicates that roughly 70 % of UCB-GLOBES MS are unique thus far, not observed more than once among the laboratory oxidation samples and ambient data in UCB-GLOBES MS. Further, only 18 % can be positively identified using these databases or known authentic standards. This points to a large gap between these laboratory simulations and ambient OA. Overall, the UCB-GLOBES database can be utilized for improving confidence in OA source categorization and/or identification, novel chemical marker discovery, tracking chemical diversity, de novo structure and properties prediction, and improving MS search and matching algorithms. This can ultimately inform future research priorities for the chemical characterization of atmospheric organic samples.

Mass spectrometry↗

DOE OSTI2025

Propane Activation on Pt Electrodes at Room Temperature: Quantification of Adsorbate Identity and Coverage

Abstract C−H bond activation is the first step in manufacturing chemical products from readily available light alkane feedstock and typically proceeds via carbon‐intensive thermal processes. The ongoing emphasis on decarbonization via electrification motivates low‐temperature electrochemical alternatives that could lead to sustainable chemicals production. Platinum (Pt) electrocatalysts have shown activity towards reacting alkanes; however, little is known about propane electrocatalytic activation and conditions suitable for enabling selective oxidation to valuable products. Herein, we utilize a combination of electrochemical mass spectrometry (ECMS) and density functional theory (DFT) calculations to elucidate the potential dependence of propane activation on Pt electrocatalysts. Results show a strong dependence of adsorption on the applied potential in room‐temperature aqueous acidic electrolyte, with a maximum coverage of propane‐derived adsorbates at 0.30 V vs RHE. Using charge deconvolution and deuterated experiments, the mechanism of adsorption was elucidated, and C 3 H 2 * was determined as the average dehydrogenated propane‐derived adsorbate species. DFT calculations further corroborate these results, showing that the formation of deeply dehydrogenated species is energetically accessible at room temperature. The combined theoretical and experimental findings yield insights for selective activation of paraffinic C−H bonds at room temperature, aqueous conditions—a critical step towards decarbonized chemical manufacturing.

Chemistry↗

DOE OSTI2024

Actuating Liquid Crystals Rapidly and Reversibly by Using Chemical Catalysis

Abstract Microtubules and catalytic motor proteins underlie the microscale actuation of living materials, and they have been used in reconstituted systems to harness chemical energy to drive new states of organization of soft matter (e.g., liquid crystals (LCs)). Such materials, however, are fragile and challenging to translate to technological contexts. Rapid (sub‐second) and reversible changes in the orientations of LCs at room temperature using reactions between gaseous hydrogen and oxygen that are catalyzed by Pd/Au surfaces are reported. Surface chemical analysis and computational chemistry studies confirm that dissociative adsorption of H 2 on the Pd/Au films reduces preadsorbed O and generates 1 ML of adsorbed H, driving nitrile‐containing LCs from a perpendicular to a planar orientation. Subsequent exposure to O 2 leads to oxidation of the adsorbed H, reformation of adsorbed O on the Pd/Au surface, and a return of the LC to its initial orientation. The roles of surface composition and reaction kinetics in determining the LC dynamics are described along with a proof‐of‐concept demonstration of microactuation of beads. These results provide fresh ideas for utilizing chemical energy and catalysis to reversibly actuate functional LCs on the microscale.

Chemistry↗

DOE OSTI2025

Generative learning of densities on manifolds

A generative modeling framework is proposed that combines diffusion models and manifold learning to efficiently sample data densities on manifolds. The approach utilizes Diffusion Maps to uncover possible low-dimensional underlying (latent) spaces in the high-dimensional data (ambient) space. Two approaches for sampling from the latent data density are described. The first is a score-based diffusion model, which is trained to map a standard normal distribution to the latent data distribution using a neural network. The second one involves solving an Itô stochastic differential equation in the latent space. Additional realizations of the data are generated by lifting the samples back to the ambient space using Double Diffusion Maps , a recently introduced technique typically employed in studying dynamical system reduction; here the focus lies in sampling densities rather than system dynamics. The proposed approaches enable sampling high dimensional data densities restricted to low-dimensional, a priori unknown manifolds. The efficacy of the proposed framework is demonstrated through a benchmark problem and a material with multiscale structure.

Double diffusion maps↗

DOE OSTI2026

Wyoming Trails Carbon Hub (WyoTCH)

The Wyoming Trails Carbon Hub (WyoTCH) project completed a front-end engineering and design (FEED) study for a commercial-scale, open-access carbon dioxide (CO 2 ) transport pipeline in Wyoming under U.S. Department of Energy (DOE) Award DEFE0032347, funded through the Bipartisan Infrastructure Law Carbon Capture Technology Program and administered by the National Energy Technology Laboratory. The project’s approach of designing a multi-source, multi-destination pipeline, rather than a dedicated line serving a single project, would lower the barrier to entry for individual CO 2 projects. The projects would leverage Wyoming's concentrated industrial and power generation CO 2 sources, its existing CO 2 pipeline infrastructure, and its extensive CO 2 storage and utilization capacity. This is the project's final technical report.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2026

Queued Up: 2026 Edition, Characteristics of Power Plants Seeking Transmission Interconnection As of the End of 2025 [Slides]

Electric transmission system operators (ISOs, RTOs, or utilities) require proposed power plants seeking to connect to the transmission grid to undergo a series of impact studies before they can be built. This process establishes what new transmission equipment or upgrades may be needed before a project can connect to the system and assigns the costs of that equipment. The lists of projects in this process are known as “interconnection queues”. In collaboration with https://www.interconnection.fyi. Berkeley Lab compiled, aggregated, and cleaned interconnection queue data from >50 transmission grid operators (7 ISO/RTOs and 50 non-ISO balancing areas), which collectively represent ~98% of currently installed U.S. electric generating capacity.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Simulating hindered grain boundary diffusion using the smoothed boundary method

Abstract Grain boundaries can greatly affect the transport properties of polycrystalline materials, particularly when the grain size approaches the nanoscale. While grain boundaries often enhance diffusion by providing a fast pathway for chemical transport, some material systems, such as those of solid oxide fuel cells and battery cathode particles, exhibit the opposite behavior, where grain boundaries act to hinder diffusion. To facilitate the study of systems with hindered grain boundary diffusion, we propose a model that utilizes the smoothed boundary method to simulate the dynamic concentration evolution in polycrystalline systems. The model employs domain parameters with diffuse interfaces to describe the grains, thereby enabling solutions with explicit consideration of their complex geometries. The intrinsic error arising from the diffuse interface approach employed in our proposed model is explored by comparing the results against a sharp interface model for a variety of parameter sets. Finally, two case studies are considered to demonstrate potential applications of the model. First, a nanocrystalline yttria-stabilized zirconia solid oxide fuel cell system is investigated, and the effective diffusivities are extracted from the simulation results and are compared to the values obtained through mean-field approximations. Second, the concentration evolution during lithiation of a polycrystalline battery cathode particle is simulated to demonstrate the method’s capability.

Materials Science↗

DOE OSTI2024

High‐Loading Lithium‐Sulfur Batteries with Solvent‐Free Dry‐Electrode Processing

Abstract Lithium‐sulfur (Li‐S) batteries, with their high energy density, nontoxicity, and the natural abundance of sulfur, hold immense potential as the next‐generation energy storage technology. To maximize the actual energy density of the Li‐S batteries for practical applications, it is crucial to escalate the areal capacity of the sulfur cathode by fabricating an electrode with high sulfur loading. Herein, ultra‐high sulfur loading (up to 12 mg cm −2 ) cathodes are fabricated through an industrially viable and sustainable solvent‐free dry‐processing method that utilizes a polytetrafluoroethylene binder fibrillation. Due to its low porosity cathode architecture formed by the binder fibrillation process, the dry‐processed electrodes exhibit a relatively lower initial capacity compared to the slurry‐processed electrode. However, its mechanical stability is well maintained throughout the cycling without the formation of electrode cracking, demonstrating significantly superior cycling stability. Additionally, through the optimization of the dry‐processing, a single‐layer pouch cell with a loading of 9 mg cm −2 and a novel multi‐layer pouch cell that uses an aluminum mesh as its current collector with a total loading of 14 mg cm −2 are introduced. To address the reduced initial capacity of dry‐processed electrodes, strategies such as incorporating electrocatalysts or employing prelithiated active materials are suggested.

Chemistry↗

DOE OSTI2026

Final Technical Report for DE-SC0022206

This project developed foundational genetic, genomic, and epigenetic tools for anaerobic fungi (Neocallimastigomycota), a group of microorganisms with exceptional natural abilities to deconstruct lignocellulosic biomass. Efficient biomass deconstruction remains a major barrier to economical production of renewable fuels, chemicals, and materials from agricultural and forestry residues. The project sought to enable mechanistic studies and future engineering of anaerobic fungi by improving genomic resources, establishing methods for gene expression, and investigating epigenetic regulation of biomass-degrading pathways. Major accomplishments included generation of the first chromosome-scale genome assemblies for multiple anaerobic fungal species, providing publicly available genomic resources that support both engineering and fundamental biological research. The project established the first reproducible system for heterologous gene expression in anaerobic fungi and identified genomic features and mobile genetic elements that may support future development of stable transformation technologies. In parallel, the project demonstrated direct conversion of untreated lignocellulosic biomass into fuels and specialty chemicals through a fungal-yeast bioprocess and identified anaerobic fungal enzymes with utility for metabolic engineering. The research also revealed that epigenetic regulation plays an important role in controlling fungal gene expression and enzyme production, identifying potential strategies for enhancing biomass degradation. Collectively, this work established anaerobic fungi as a tractable emerging platform for bioenergy and biomanufacturing research, generated valuable public resources, trained the next generation of researchers, and advanced DOE-BER goals related to predictive biology, sustainable bioprocessing, and the circular bioeconomy.

Solomon, Kevin [University of Delaware] (ORCID:000↗

DOE OSTI2025

Glauber’s Salt Composites for HVAC Applications: A Study on the Use of the T-History Method with a Modified Data Evaluation Methodology

Phase change materials (PCMs) can be utilized in buildings for peak load shifting in air conditioning systems, and the use of salt hydrate-based PCMs can reduce the cost of thermal energy storage devices. Glauber’s salt is an economical salt hydrate PCM with a melting point of around 32 °C. However, the desired melting range typically falls between 18 and 22 °C for building air conditioning applications. Although many researchers have characterized Glauber’s salt and its composites with modified melting points, enthalpy–temperature curves for composites of Glauber’s salt and NaCl are unavailable. In this study, we report the melting and solidification enthalpy–temperature curves for two different composites of Glauber’s salt and NaCl with a melting point of 21 °C obtained by the T-history method. Both composites contain NaCl to suppress the melting point, borax to reduce supercooling, and sodium polyacrylate as a thickener to enhance cyclic stability. The first composite with 12 wt.% NaCl demonstrated 139 kJ·kg−1 of latent heat of fusion, and the second composite with 9 wt.% NaCl demonstrated 171 kJ·kg−1. Both the composites have high volumetric energy densities compared to their organic counterparts with similar melting points.

Chemistry↗

DOE OSTI2026

In-Situ Visualization of a Growing Brittle Crack in Aluminum Oxynitride Using Synchrotron X-Rays and the Double-Cleavage Drilled Compression Geometry

Brittle fracture is difficult to study in situ due to the speed of a growing crack and the often-catastrophic nature of failure in brittle materials. As a result, the influence of microstructural considerations, such as orientation, grain boundary locations, and strain field, on the crack path remains poorly understood. Presented in this study is a method addressing this knowledge gap, which utilizes the double-cleavage drilled compression geometry to achieve quasi-stable fracture in aluminum oxynitride (AlON). Synchrotron X-ray micro-computed tomography is used to characterize the crack shape and length, while high-energy diffraction microscopy provides information on the strains, orientations, and shapes of grains in the microstructure surrounding the crack tip. During testing, the crack grew in discrete and irregular jumps while the fracture toughness falls within reported ranges. The crack in AlON is found to have no greater tendency to crack intergranularly as compared to transgranularly, and grains which are cracked transgranularly do not display a trend in orientation or stress when compared to those around which the crack followed a grain boundary. The high resolution of the crack path and microstructural data provides a path forward for modeling and understanding 3D brittle fracture.

Gorske, Sara F.↗

DOE OSTI2026

Hierarchical low Pt-loading “core-shell” electrocatalysts for the oxygen reduction reaction in fuel cells

The sluggish kinetics of the oxygen reduction reaction (ORR) hinder cost-effective polymer electrolyte fuel cells (PEFCs), which rely on scarce, expensive platinum-based electrocatalysts (ECs). Here, we present a novel synthesis method for ORR ECs achieving exceptional platinum utilization. The design features a hierarchical “multi-carbon” support comprising carbon nanoparticles interacting with graphene nanoplatelets as the “core”, encapsulated by a porous carbon nitride (CN) “shell”. This configuration promotes strong core/shell interactions and a bimodal active site distribution, consisting of chemically dispersed Pt and Ni single-atom complexes and PtNix alloy nanoclusters embedded in the CN shell. These advantages enable high activity and durability, achieving an ORR activity of 1.6 A mgPt−1 at 0.9 V vs. RHE-an order of magnitude higher than Pt/C (0.17 A mgPt−1). A proof-of-concept PEFC demonstrates a specific power of 12.0 kW gPt−1 at 0.60 V. This approach offers a significant step toward more efficient and sustainable PEFC technologies.

Pagot, Gioele [University of Padova, Italy]↗

DOE OSTI2026

Treatment of Lagoon Dairy Manure Wastewater via Iron Electrocoagulation, Microfiltration, and Adsorption

Dairy manure wastewater generated by flushing barn cow waste contains nutrients, pathogens, and organic and inorganic contaminants. This study utilized a process consisting of iron electrocoagulation (Fe-EC), microfiltration (MF), and activated carbon (AC) adsorption to treat farm wastewater and explore the reclamation of clean water for irrigation and livestock consumption. Significant removal (>99.9%) of chemical oxygen demand (COD), total organic carbon (TOC), phosphorus (P), turbidity, and microorganisms, as well as ions including magnesium, calcium, sulfur, and silica was achieved by the combined EC-MF-AC process. Specifically, a charge loading of ∼37,500 C/L in a continuous-flow EC configuration, followed by MF, achieved more than 95% removal of TOC and COD. Characterization of produced flocs and foam via scanning-electron microscopy with energy-dispersal spectroscopy and Fourier transform infrared spectroscopy confirmed the removal of ions, including calcium, sulfur, and silica. A key finding was the electrocatalytic conversion of nitrogen species to ammonia gas through the intermediate reduction of nitrate/nitrite, which led to ∼60% total nitrogen (TN) removal. AC treatment further improved TN removal to ∼70%. The Fe-EC process also eradicated >99.9% of bacteria. Preliminary process cost assessment, based on recycled materials for EC electrodes, showed significant cost savings (∼2 times) compared to commercial electrodes.

Dutta, Swapnamoy [ORNL]↗

DOE OSTI2026

TRACE Input Modernization

This work presents a Tom’s Obvious Minimal Language (TOML)-based representation of input for the US Nuclear Regulatory Commission’s TRAC/RELAP Advanced Computational Engine (TRACE) thermal hydraulics code. Implemented using the Workbench Analysis Sequence Processor (WASP), the approach maps traditional TRACE input structures to a hierarchical format composed of named parameters, typed values, and native data collections. The resulting representation preserves TRACE’s existing modeling capabilities while providing a modern, structured interface for model development and management. WASP further extends TOML through a file import directive that supports modular model composition and reusable input organization. In addition, WASP provides extended array data entry convenience with various data repeat and interpolation capabilities. Examples of the new TOML syntax are provided for major TRACE input categories, including hydraulic components, heat structures, control systems, and trip logic. The TOML representation establishes a foundation for improved validation, tooling, automation, and model maintainability while remaining compatible with existing TRACE workflows. To facilitate migration to the TOML-based input format, the TRACE executable now supports conversion of native TRACE input into an intermediate JSON representation. A Python utility subsequently transforms the JSON data into an equivalent TOML model. Lastly, the TRACE executable now supports execution using TOML-formatted input.

Lefebvre, Robert A. [Oak Ridge National Laboratory↗

DOE OSTI2025

Microbial Enrichments Contribute to Characterization Of Desert Tortoise Gut Microbiota

Abstract Desert tortoises play ecologically significant roles, including plant seed dispersal and mineral cycling, and yet little is known about microbial members that are critical to their gut and overall health. Tortoises consume recalcitrant plant material, which their gut microbiota degrades and converts into usable metabolites and nutrients for the tortoise. Findings from tortoise gut microbiomes may translate well into biotechnological applications as these microbes have evolved to efficiently degrade recalcitrant substrates and generate useful products. In this study, we cultivated microbial communities from desert tortoise fecal samples following a targeted anaerobic enrichment for microbes involved in deconstruction and utilization of plant biomass. We employed 16S rRNA amplicon sequencing to compare cultivated communities to initial fecal source material and found high abundances of Firmicutes and Bacteroidota typically associated with biomass deconstruction in all cultivated samples. Significantly decreased microbial diversity was observed in the cultivated microbial communities, yet several key taxa thrived in lignocellulose enrichments, includingLachnospiraceaeandEnterococcus. Additionally, cultivated communities produced short-chain fatty acids under anaerobic conditions, and their growth and metabolic output provide evidence of their viability in the initial fecal communities. Overall, this study adds to the limited understanding of reptilian herbivore microbiota, and offers a path towards biotechnological translation based on the ability of the cultivated communities to convert lignocellulose directly to acetate, propionate, and butyrate.

Environmental Sciences & Ecology↗

DOE OSTI2025

High-throughput micro-scale bandgap mapping for perovskite-inspired materials with complex composition space

Abstract To realize the full promise of high-throughput experimental workflows, the rate of sample synthesis must be matched by that of characterization. Of growing interest are contactless optical techniques that can rapidly measure material homogeneity and properties. Here, we present a hyperspectral imaging method to measure local optical bandgap distributions within samples, utilizing spatially-resolved reflectance spectra coupled with automated data analysis. We collect approximately one million optical bandgap data across the compositional space of Cs 3 (Bi x Sb 1-x ) 2 (Br y I 1-y ) 9 perovskite-inspired materials. Our results show non-monotonic bandgap variations (i.e., bandgap bowing) along six composition gradient sequences, in addition to identifying samples with multiple bandgaps in statistics. High-throughput transient absorption spectroscopy reveals that within these compositions, the depletion of the ground state carriers to excited states occurred at discrete energy levels with independent carrier dynamics, consistent with the bandgap observation and indicative of phase separation. This work demonstrates the potential for rapid optical measurements to assess material quality and homogeneity in a high-throughput experimental setting, supporting screening and recipe optimization of optoelectronic material candidates with desired carrier dynamics and optical properties.

Science & Technology - Other Topics↗

DOE OSTI2025

Detecting Magnon-phonon coupling in yttrium iron garnet with variable temperature STEM-EELS

Magnons, quanta of spin wave excitations in magnetically ordered materials, have been identified as candidates for several potentially transformative technologies in recent years. Macroscopic techniques, such as neutron scattering or Raman spectroscopy, can be used to identify and analyze magnons, but provide relatively delocalized information about the sample. Understanding how the bonding and local structure of a material interacts with, and influences, the magnon population in a material is a crucial step toward the ability to produce any real-world application utilizing magnons. By leveraging the combined spatial resolution of scanning transmission electron microscopy (STEM) and the energy resolution of monochromated electron energy-loss spectroscopy (EELS) nanoscale analysis of magnons can be performed. While the weak interaction of magnons with the electron beam makes magnon EELS challenging on reasonable timescales, magnon-phonon coupling can be leveraged to understand magnons through their effect on the more easily measured phonons. Here, we examine yttrium iron garnet (YIG) flakes, and demonstrate non-linear, temperature-dependent shifts in the phonon frequencies, consistent with previously described magnon-phonon coupling effects. The ability to measure the temperature-dependence of vibrational frequencies with high precision in individual nanoscale flakes, demonstrates the ability to study magnon-phonon coupling in the STEM with unprecedented spatial resolution.

Reifsnyder, Alexander [ORNL]↗