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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

In situ catalyst activation and regeneration enable energy-efficient high-current CO 2 reduction to ethanol-rich C 2+ mixtures

Electrochemical conversion of dissolved CO 2 in bicarbonate electrolytes, i.e., bicarbonate electrolysis, offers distinct advantages over gas diffusion electrode systems by enabling direct utilization of the CO 2 capture electrolyte while bypassing the energy-intensive CO 2 release step. However, bicarbonate electrolysis faces challenges such as CO 2 mass-transfer limitation, local pH-driven CO 2 depletion, and high cathodic potentials. The higher potential often causes catalyst surface reorganization, leading to a gradual loss of active sites and variations in selectivity during CO 2 reduction. Here, we report a directed, in situ activation and regeneration method that allows precatalysts to equilibrate under dynamic (pulsed) electrolysis conditions. We demonstrate in situ activation of a scalable Cu 2 O/Cu mesh that, under short-width (t = 4 s) pulsed electrolysis, provides stable mixed oxidation states of Cu, favoring the formation of an ethanol-rich crude mixture. The pulsed electrolysis waveform, consisting of six distinct segments, is tuned to form Cu + oxides, which are then reduced to generate local alkaline conditions favoring C–C coupling. This synergistic effect results in FEs of 73% for C2+ products and 39% for ethanol at an applied current density of −150 mA cm −2 and a cathodic potential of −1.45 V (vs. RHE). The overall half-cell energy efficiency is ∼30% for C 2+ products. The in situ Raman experiments confirm the role of pCO 2 R in dynamically regenerating Cu+-containing surface species during pulsed operation, thereby steering selectivity towards C 2+ products. A comprehensive multiscale, multiphysics model is developed to investigate the dynamic behavior of copper surface species (Cu, Cu + , and Cu 2+ ) and local microenvironmental conditions during the pCO 2 R. The results reveal that the coexistence of different copper oxidation states, especially the Cu+ intermediate, is critical in steering selectivity towards multicarbon (C 2+ ) products. The dynamic modulation of surface redox states via tailored pulsing strategies favors C–C coupling pathways by inducing localized alkaline conditions and stabilizing reactive intermediates. This work establishes a predictive modeling platform that links pulse waveform design with mechanistic insights into catalyst state evolution and product selectivity. Overall, this study provides valuable insights into the synergistic effect of in situ activation of pre-catalysts and pulsed electrolysis for higher selectivity towards C 2+ products.

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

Comparing multi-source urban flood indicators: satellite, simulation, and citizen-reported data

Urban flooding arises from complex mechanisms, making it challenging to capture accurately with a single detection method. This study evaluates three complementary approaches to detect flooding across three Chicago neighborhoods: (i) Sentinel-1 synthetic aperture radar (SAR), offering weather-independent, high-resolution (10 m) imagery of surface inundation; (ii) the storm water management model (SWMM), simulating combined sewer overflow and drainage performance; and (iii) citizen-generated 311 service requests, capturing observed flooding impacts. By analyzing six storms ranging from severe to mild, we examine how each source uniquely contributes to identifying urban flood events. SAR imagery effectively identifies standing water but can miss brief flooding due to satellite revisit constraints. SWMM provides detailed insights into system-wide drainage behavior yet may underestimate localized street-level flooding. Meanwhile, 311 calls reflect real-world flooding impacts but are vulnerable to underreporting. Statistical overlap analysis highlights chronic flood hotspots repeatedly identified across multiple detection methods, indicating persistent infrastructure and topographic vulnerabilities. Temporal analysis further reveals that while SWMM flooding aligns closely with rainfall peaks, 311 calls typically precede or persist beyond these peaks. Our findings emphasize the value of using satellite observations, hydrological modeling, and resident-reported data in a complementary manner to better interpret patterns in flood timing, severity, and spatial distribution—providing insights that can inform targeted infrastructure improvements and contribute to urban flood resilience planning.

311↗
DOE OSTI2025

Phylogenetic diversity of light-dependent phosphorylation of Thr78 in Rubisco activase

Rubisco activase is an ATP-dependent chaperone that facilitates dissociation of inhibitory sugar phosphates from the catalytic sites of Rubisco during photosynthesis. In Arabidopsis, Rubisco activase is negatively regulated by dark-dependent phosphorylation of Thr78. The prevalence of Thr78 in Rubisco activase was investigated across sequences from 91 plant species, finding that 29 (∼32%) species shared a threonine in the same position. Analysis of seven C3 species with an antibody raised against a Thr78 phospho-peptide demonstrated that this position is phosphorylated in multiple genera. However, light-dependent dephosphorylation of Thr78 was observed only in Arabidopsis. Further, phosphorylation of Thr78 could not be detected in any of the four C4 grass species examined. The results suggest that despite conservation of Thr78 in Rubisco activase from a wide range of species, a regulatory role for phosphorylation at this site is more limited. Furthermore, this provides a case study for how variation in post-translational regulation can amplify functional divergence across the phylogeny of plants beyond what is explained by sequence variation in a metabolically important protein.

Arabidopsis↗
DOE OSTI2025

Curvature effects in the reaction-diffusion system governing frontal polymerization

Frontal polymerization is a fast and energy-efficient curing process of thermoset polymers involving the self-sustained propagation of a sharp front that transforms a liquid monomer or gel into a polymer. The temperature, speed, and geometry of the polymerization front are closely intertwined quantities that can affect the curing process and the mechanical properties of the polymer. This work investigates the effect of the front curvature on the front propagation speed based on a reaction-diffusion model. The proposed analytical relations between front speed and curvature are verified by finite element simulations and validated through experiments. The models show that a concave front has a higher front temperature and speed than its convex counterpart. When the curvature of a convex front reaches a critical value, the reaction can no longer be sustained, and the front is quenched. The relation between the speed of a steadily propagating front and its geometry is derived, showing good agreement with experimental observations. This study also provides analytical estimates of the thickness of the polymerization front and insight into the relationship between the front curvature and the kinetics of the exothermic reaction.

42 ENGINEERING↗
DOE OSTI2026

Final SeaQuest Results on the Flavor Asymmetry of the Proton Light-Quark Sea with Proton-Induced Drell-Yan Process

The Fermilab E906/SeaQuest collaboration performed measurements of the Drell-Yan process using 120 GeV proton beams bombarding liquid hydrogen and liquid deuterium targets. A combined analysis of all collected data was performed to obtain the final results for the 𝜎 𝑝⁢𝑑 /2⁢𝜎 𝑝⁢𝑝 Drell-Yan cross section ratio covering the kinematic region of 0.13 < 𝑥 <0.45. The 𝑥 dependencies of $\bar{d}$(𝑥)/$\bar{𝑢}$⁡(𝑥) and $\bar{d}$(𝑥) $-$ $\bar{𝑢}$⁡(𝑥) are extracted from these cross section ratios. It is found that $\bar{d}$(𝑥) is greater than $\bar{𝑢}$⁡(𝑥) over the entire measured 𝑥 range, with improved statistical accuracy compared to previous measurements. The new results on $\bar{d}$(𝑥)/$\bar{𝑢}$⁡(𝑥) and $\bar{d}$(𝑥) $-$ $\bar{𝑢}$⁡(𝑥) are compared to various parton distribution functions and theoretical calculations.

Leung, C. H. [University of Illinois at Urbana-Cha↗
DOE OSTI2026

Miscanthus giganteus Biolistic Transformation Using the Visible RUBY Red Marker Gene to Monitor Transformation Efficiency

Miscanthus × giganteus ( M × g ) is a high-yielding perennial C4 bioenergy crop, but genetic improvement by breeding is constrained by triploid sterility and clonal propagation. Improving genetic transformation methods for M × g would provide opportunities for advantageous trait introgression. Use of an easy to phenotype reporter gene is a promising strategy to improve transformation processes and efficiency. This study presents an efficient novel method for biolistic transformation of inflorescence-derived callus in M × g and demonstrates its efficacy using RUBY, a betalain-based noninvasive reporter that is visible throughout the transformation process. RUBY expression ( Zea mays codon optimized) was visible from callus stage through plantlet development into maturity. RUBY expressing independently transformed plants were confirmed by hygromycin phosphotransferase ELISA and by genomic PCR demonstrating that the RUBY phenotype is sufficient for screening transformants. The Zea mays codon optimized hygromycin selection marker was driven by previously established promoters for Miscanthus, ZmUBI and 2×35S, while the RUBY gene expression was controlled by a known Zea mays C4 promoter, Brachypodium UBI10, newly employed in Miscanthus. The construct containing the 2×35S promoter for hygromycin had a 15.1% transformation efficiency while the ZmUBI promoter had a 20.5% transformation efficiency. This study provides a novel, highly efficient protocol for successful biolistic transformation of M × g for stable expression. This study also demonstrates that RUBY expression can be used as a convenient and powerful monitor of transformation in ongoing and future work to engineer M × g into an improved bioproduct feedstock.

RUBY↗
DOE OSTI2025

Upgrading biocrude oil into sustainable aviation fuel using zeolite-supported iron-molybdenum carbide nanocatalysts

Food waste is an underdeveloped source for production of sustainable aviation fuel (SAF). Now, there is no certified conversion process of food waste for SAF by American Society for Testing and Materials (ASTM). We report the use of zeolite-supported molybdenum carbide nanocatalysts in upgrading biocrudes, produced from food wastes through HTL, into SAF precursors. Our data show a complete removal of oxygen from the biocrude through hydrodeoxygenation and a higher heating value of 46.5 MJ/kg, which is comparable to that of Jet A (46.1 MJ/kg). The prescreening tests (tier alpha and beta) show the average carbon number of the distillation cut (150° to 230°C) of upgraded fuel is 10.6, close to the value of 11.4 for average conventional jet fuel, and the specifications of properties including surface tension, viscosity, heating value, flash point, and freezing point were found to meet the standards of SAF. The metal carbide nanocatalysts were reusable in upgrading tests, and the activity of deoxygenation was retained.

10 SYNTHETIC FUELS↗
DOE OSTI2025

Resourceful and economical designing of fermentation medium for lab and commercial strains of yeast from alternative feedstock: ‘transgenic oilcane’

Sugarcane plant engineered to accumulate lipids in its vegetative tissue is being developed as a new bioenergy crop. The new crop would be a source of juice, oil, and cellulosic sugars. However, limited tolerance of industrially recognized yeasts towards inhibitors generated during the processing of lignocellulosic biomass to produce fermentable sugars is a major challenge in developing scalable processes for second-generation drop-in fuel production. To this end, hydrolysates generated from engineered sugarcane—‘oilcane’ bagasse contain added phenolics and fatty acids that further restrict the growth of fermenting microorganisms and necessitate nutrient supplementation and/or detoxification of hydrolysate which makes the fermentation process expensive. Herein, we propose a resourceful and economical approach for growing lab and commercial strains of S. cerevisiae on unrefined cellulosic sugars aerobically and fermentatively.

09 BIOMASS FUELS↗
DOE OSTI2026

Multi-trait multi-environment genomic prediction strategies for Miscanthus sacchariflorus

Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (G×E×T) and (2) two single-trait multi-environment (STME) models (with and without G×E interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.

genomic prediction (GP)↗
DOE OSTI2025

An Image-Plane Approach to Gravitational Lens Modeling of Interferometric Data

Strong gravitational lensing acts as a cosmic telescope, enabling the study of the high-redshift universe. Astronomical interferometers, such as the Atacama Large Millimeter/submillimeter Array (ALMA), have provided high-resolution images of strongly lensed sources at millimeter and submillimeter wavelengths. To model the mass and light distributions of lensing and source galaxies from strongly lensed images, strong lens modeling for interferometric observations is conventionally performed in the visibility space, which is computationally expensive. In this paper, we implement an image-plane lens modeling methodology for interferometric dirty images by accounting for noise correlations. We show that the image-plane likelihood function produces accurate model values when tested on simulated ALMA observations with an ensemble of noise realizations. We also apply our technique to ALMA observations of two sources selected from the South Pole Telescope survey, comparing our results with previous visibility-based models. Our model results are consistent with previous models for both parametric and pixelated source-plane reconstructions. We implement this methodology for interferometric lens modeling in the open-source software package lenstronomy.

Zhang, Nan [Illinois U., Urbana (main)] (ORCID:000↗
DOE OSTI2026

On-Detector Machine Learning for Beam-Induced Background Rejection at a 10 TeV Muon Collider

A 10 TeV Muon Collider is a compelling candidate for a future energy-frontier facility, offering unprecedented opportunities to explore the fundamental laws of particle physics. Muon decays in the collider ring produce intense beam-induced background (BIB) that can overwhelm detector occupancy and exceed readout bandwidth constraints. We investigate the potential of on-detector Machine Learning for BIB rejection in the vertex detector, exploiting pixel cluster shapes to distinguish background from collision products. We study three classes of lightweight neural-network architectures, and evaluate their implementation feasibility using high-level synthesis. Selected architectures achieve 88 to 90% data reduction at 99% signal efficiency, while requiring hardware resources compatible with potential ASIC implementation. These results demonstrate the potential of performing substantial BIB rejection directly in the pixel readout, providing a strategy for meeting the tracker readout requirements at a future Muon Collider.

Abadjiev, Daniel [Chicago U.]↗
DOE OSTI2025

2D Multivariate‐Metal‐Organic Frameworks (2D‐M 2 OF) for High Yield Ammonia Synthesis from Nitrate

Ammonia synthesis from nitrate offers a promising approach for both nitrate removal and nitrogen recycling. In this study, a series of 2D multivariate-metal-organic frameworks (M 2 OFs) is synthesized, incorporating transition metals such as Co, Ni, Mn, and Ag to enhance these processes. These M 2 OFs exhibit remarkable ammonia production performance, with the highest performance achieved using the quaternary structure exceeding a current density of 1 A cm −2 at −0.8 V vs RHE, with an ammonia Faradic efficiency (F.E.) of ≈90%, and a yield rate of 68 mg h −1 cm −2 . Our findings reveal that the synergy among different metal centers in M 2 OFs provides a new efficient reaction pathway for nitrate reduction via surface hydrogen co-adsorption, a mechanism not attainable with single-metal MOFs.

2D-M2OF↗
DOE OSTI2025

Field–scale evaluation of ecosystem service benefits of bioenergy switchgrass

Purpose-grown perennial herbaceous species are nonfood crops specifically cultivated for bioenergy production and have the potential to secure bioenergy feedstock resources while enhancing ecosystem services. This study assessed soil greenhouse gas emissions (CO 2 and N 2 O), nitrate (NO 3 -N) leaching reduction potential, evapotranspiration (ET), and water-use efficiency (WUE) of bioenergy switchgrass (Panicum virgatum L.) in comparison to corn (Zea mays L.). The study was conducted on field-scale plots in Urbana, IL, during the 2020–2022 growing seasons. Switchgrass was established in 2020 and urea-fertilized at 56 kg N ha –1 year –1 . Corn management followed best management practices for the US Midwest, including no-till and 202 kg N ha –1 year –1 fertilization, applied as urea–ammonium nitrate (32%). Our results showed lower direct N 2 O emissions in switchgrass compared to corn. Although soil CO 2 emissions did not differ significantly during the establishment year, emissions in subsequent years were over 50% higher in switchgrass than in corn, likely due to increased belowground biomass, which was over five times higher in switchgrass. Nitrate-N leaching decreased as the switchgrass stand matured, reaching 80% lower than in corn by the third year. Differences in ET and WUE between corn and switchgrass were not significant; however, results indicate a trend toward reduced WUE in switchgrass under drought, driven by lower aboveground biomass production. Our study demonstrates that switchgrass can be implemented at a commercial scale without negatively impacting the hydrological cycle, while potentially reducing N losses through nitrate-N leaching and soil N 2 O emissions, and enhancing belowground C storage.

09 BIOMASS FUELS↗
DOE OSTI2026

Nonequilibrium defect-phase nanostructures stabilized by irradiation in undersaturated Ni-Si nanocrystalline alloy

Nanocrystalline thin films of the undersaturated alloy Ni-8.5 at% Si were subjected to 2 MeV Ti irradiation at temperatures ranging from 450˚C to 550˚C. Correlative microscopy combining transmission electron microscopy (TEM), scanning-TEM and atom probe tomography (APT revealed that large dose irradiation at 450˚C of samples with initial grain sizes below 100 nm stabilized a novel nanostructure which surprisingly contained three co-existing phases, the γ face-centered-cubic (FCC) matrix, γ' L12 ordered precipitates on intragranular dislocation loops and Ni 31 Si 12 precipitates at triple junctions (TJs). In contrast, irradiation at 550˚C and irradiation of larger grain-size samples at 450˚C only produced a γ-γ' two-phase coexistence. Analysis of the three-phase nanostructure and phase field simulations indicates that radiation-induced segregation is most pronounced at TJs, thus triggering the formation of Ni 31 Si 12 precipitates. These incoherent precipitates, in turn, are expected to stabilize the grain size under irradiation. The results are generalized using the concept of driven defect-phases. It is suggested that the stabilization of driven defect-phases may impart radiation resilience by providing localized relaxation modes to the microstructure evolution during and after temporary perturbations in irradiation conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electrosynthesis of high purity ethylene using high-index facet Cu 2 O nanocrystals electrocatalyst

Electrochemical CO 2 reduction reaction (eCO2RR) to multi-carbon (C 2+ ) products with copper-based catalysts is often limited by poor selectivity. This challenge arises from the concurrent formation of various intermediates, dictated by the atomic arrangement and electronic properties of surface atoms. In this study, we found that copper (I) oxide (Cu 2 O) nanocrystals with 50 facets (50F-NC), predominantly featuring (211) facets that offers high density of under-coordinated sites, demonstrate superior ethylene (C 2 H 4 ) selectivity of 92% ± 2 with an overall current density of 212 mA/cm 2 at -650 mV vs RHE. Furthermore, after one month of storage in a 1 M KOH electrolyte, this catalyst demonstrated a C 2 H 4 Faradaic efficiency of 87% highlighting its stabile structure under strong alkaline environments. Here, operando electrochemical Raman spectroscopy revealed enhanced CO* intermediate coverage on the 50F-NC catalyst, correlating with improved C-C coupling. SEM, TEM, and XPS analyses, along with DFT calculations, suggested that Cu sites on the (211) facet of 50F-NC and those at the Cu/Cu 2 O interface formed in-situ due to the surface reconstruction during the reaction, are likely active sites for effective C-C coupling and sustained high-rate C 2 H 4 production.

Cu nano particle↗