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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Interplay of Quantum Size Effect and Tensile Strain on Surface Morphology of β-Sn(100) Islands

The quantum size effect (QSE) and strain effect are two key factors influencing the surface morphology of thin films, which can increase film surface roughness through QSE-induced thickness oscillation and strain-induced island formation, respectively. Surface roughness usually manifests in the early stages of film growth and diminishes beyond a critical thickness. In this work, we employ molecular beam epitaxy (MBE) to grow β-Sn(100) islands with varying thickness N on bilayer graphene-terminated 6H-SiC(0001) substrates. Scanning tunneling microscopy and spectroscopy measurements reveal an inverse surface roughness effect that highlights the interplay of QSE and misfit strain in shaping the surface morphology of β-Sn(100) islands. For N ≤ 10, the islands exhibit flat surfaces, while for N ≥ 26, the island surfaces become corrugated and patterned. For the intermediate range, i.e., 12 ≤ N ≤ 24, both flat and patterned surfaces coexist, with the percentage coverage of the patterned surface oscillating as a function of N. By performing density functional theory calculations, we demonstrate that the unusual surface pattern evolution in our MBE-grown β-Sn(100) islands is a result of the interplay between QSE-induced surface roughing and tensile strain-induced smoothening effect.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Comprehensive framework for assessing and optimizing existing research networks

Conservation, monitoring, and research networks, or collections of ecological research sites unified under a common mission of data collection or a research mission, are essential infrastructure for understanding large landscapes. However, most networks developed opportunistically over decades rather than through systematic design, creating potential limitations in the ability to address conservation challenges across entire regions. We developed a framework to evaluate how well an existing research network represents the environmental conditions its members study and devised an approach to rank sites of priority for strategic expansion. Our approach measures performance through environmental representativeness, geographic coverage, and adequacy for scientific inference and thus optimizes limited monitoring resources to maximize scientific impact. We demonstrated this approach with the U.S. Department of Agriculture (USDA) Forest Service Experimental Forests and Ranges Network (EFRN), a 79‐site network across the United States that grew opportunistically over a century. At the national scale, the network effectively captured high‐biomass forests important for carbon cycle research; 82% of forest biomass was in well‐represented areas. Some areas in Texas, Florida, the Rocky Mountains, and the West Coast had no relevant EFRN sites, which limits the ability to make regional inferences. A fundamental challenge for the EFRN was that sites improving regional extent coverage sometimes provided minimal national benefits, which can create conflicts between local and global priorities. Adding the highest‐ranked candidate site provided a relevant site for 17% of currently poorly represented 1‐km pixel cells nationally, but regional and national site rankings varied considerably due to nested spatial inference. This framework provides quantitative tools for strategic infrastructure decision‐making, ensures that limited monitoring resources maximize conservation impact, and can be applied broadly to address the widespread challenge of optimizing conservation and monitoring networks worldwide.

additional site↗
DOE OSTI2024

Key Insights: Interconnecting Behind-the-Meter Microgrids

This technical brief explores the interconnection challenges and evolving standards associated with behind-the-meter (BTM), facility-scale microgrids. It clarifies key functions related to customer microgrids and backup systems while addressing critical questions regarding certification coverage, operational impacts, customer relationships, and testing requirements for BTM microgrid systems. The document emphasizes the need for updated standards and additional witness testing to ensure safe and effective microgrid operation as well as improved grid integration and compliance with power quality standards.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Fundamental Understanding of “Fresh” Lithium Nucleation and Growth in Sulfide-Based Anode-Free Solid-State Batteries: Effects of Substrate, Current Density, and Li + Supply

Understanding the electrochemical extraction and deposition of lithium (Li) from cathode is crucial for advancing anode-free solid-state batteries (AFSSBs). Herein, cryo-transmission electron microscopy (cryo-TEM) and electrochemical studies are employed to investigate how current collector surface properties, current densities, and cathode loadings influence the morphology of fresh electrochemically deposited Li and the electrochemical performance in sulfide-based AFSSBs. Cryo-TEM reveals that Cu current collectors induce irregular, dendritic Li deposits due to their lithiophobic nature and reactivity with Li 5.4 PS 4.4 Cl 1.6 (LPSC), while Ni and Au facilitate more uniform, planar-like Li growth. The morphology of the deposited Li also depends on current density: higher rates produce smaller, porous particles versus larger, denser deposits at lower rates. Importantly, for the first time, we discovered that low cathode loadings lead to poor cycling stability due to insufficient Li + supply for complete anode coverage, contrary to conventional solid-state batteries with preloaded Li metal anodes. This finding establishes a design principle where adequate cathode Li + reservoirs are essential for anode interface stability in AFSSBs. Overall, this work elucidates the interplayed effect of current collectors, current densities, and cathode loadings on Li morphology and cycle stability, offering fundamental insights into cathode-derived Li behavior and practical guidelines for optimizing AFSSBs performance through nucleation control and interface engineering.

25 ENERGY STORAGE↗
DOE OSTI2026

Product-promoted acetylene cyclotrimerization to benzene on Ag(111)

Acetylene cyclotrimerization to benzene on Ag(111) has recently been found to be 100% selective. However, it requires monolayer coverages, limiting its practical application due to the high pressure required to attain this surface coverage of acetylene near room temperature. Here, we show that co-adsorbed benzene, the reaction product, promotes cyclotrimerization at submonolayer acetylene coverages without compromising the 100% selectivity of Ag(111) via temperature-programmed desorption experiments. Scanning tunneling microscopy and density functional theory (DFT) calculations elucidate the origin of this effect whereby attractive acetylene–benzene interactions locally compress acetylene domains. DFT calculations further illustrate how co-adsorbed benzene reduces the transition-state energy for formation of the key C 4 intermediate, making cyclotrimerization competitive with desorption. Together, these findings reveal how product-reactant interactions can enhance C–C coupling.

Acetylene cyclotrimerization↗
DOE OSTI2024

Microstructural Passivation of Patterned Al 2 O 3 Back Contacts on CdS/CdTe Solar Cells

Abstract Patterned aluminum oxide (Al 2 O 3 ) back contact on cadmium telluride (CdTe) solar cells can effectively mitigate the loss of the majority carriers while retaining the passivation benefits for minority carriers. This study investigates the impact of the point‐contact geometry on cell performance, where the spacing of the microholes is systematically varied at a constant microhole diameter (≈16 µm). Microhole arrays are created on an evaporated Al 2 O 3 layer (≈30 nm) on CdTe using laser‐beam lithography and selective wet etching processes. Comparative analysis indicates a significant decrease in fill factor (FF) and short‐circuit current ( I SC ) when the contact fraction falls below 30%, likely due to the Al 2 O 3 barrier impeding majority carriers. Above this fraction, FF and I SC are comparable to those of baseline CdTe cells without Al 2 O 3 . Open‐circuit voltage ( V OC ) shows a gradual decrease as Al 2 O 3 coverage is reduced but exhibits a slight increase (<15 mV) when the contact fraction exceeds 30%. Cathodoluminescence (CL) characterization reveals that significantly improved radiative recombination occurs within the CdTe grain bulk with Al 2 O 3 , whereas this effect on grain boundaries is minimal. The findings imply complex local carrier dynamics in the patterned back‐contact region, closely tied to the microstructural properties of CdTe‐based solar cells.

Roy, Etee Kawna↗
DOE OSTI2025

Status of the development and testing of in-vessel and ECH-protection components for the ITER low-field side reflectometer

The ITER Low-Field Side Reflectometer (LFSR) is a critical diagnostic system designed to measure edge electron density profiles, fluctuations, and plasma rotation in ITER. This paper presents the latest developments in the design, testing, and validation of key in-vessel and Electron Cyclotron Heating (ECH) protection components. The LFSR antenna array has been optimized to provide robust coverage over expected plasma vertical displacements and a Doppler measurement for plasma rotation. Further, a comprehensive assessment of a 170-GHz diffraction grating and a novel stray-ECH power monitor demonstrates effectiveness in mitigating the impact of stray ECH power on sensitive microwave electronics. Additionally, an advancement in anti-reflective technology for millimeter waves significantly improves transmission of LFSR's vacuum window while meeting ITER's stringent safety and operational requirements. These results support the continued integration of LFSR into ITER, ensuring its diagnostic capabilities remain resilient under reactor-relevant conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Pseudomonas aeruginosa Adhesion and Biofilm Formation on Poly(l-lysine)-Tethered Hydrogels: Synergistic Effect of Substrate Stiffness and Positive Charge Density

Infections associated with antibacterial-resistant Pseudomonas aeruginosa (P. aeruginosa) are the major cause of morbidity and mortality of patients, presenting one of the greatest therapeutic challenges for treatment of community-acquired and nosocomial infections. To develop antimicrobial hydrogel coatings to control the adhesion and subsequent biofilm formation of P. aeruginosa, we have used photo-cross-linked poly(ethylene glycol) diacrylate (PEGDA) hydrogels with varied cross-linking densities and covalently grafted poly(l-lysine) (PLL) at different weight compositions (ϕ PLL ). Both surface stiffness and positive charge density of the hydrogels were efficiently tuned over a broad range to investigate their effects on two main strains of P. aeruginosa, PA01 and PA14. We found that both number and viability of attached cells were positively correlated with the hydrogel stiffness, leading to thicker and larger coverage of cell colonies at 72 h postseeding on the stiffer substrates. The dependence of both PA01 and PA14 strains on ϕ PLL , however, was nonmonotonic. Positive charges from dissociated amine groups in the grafted PLL chains significantly promoted initial adhesion and proliferation of both strains at low ϕ PLL and developed into the thickest biofilms on the stiffest hydrogels grafted with ϕ PLL of 1–2%. Nevertheless, on the softest hydrogels grafted with PLL at high ϕ PLL of 7–10%, the bacteria no longer attached or survived. These results not only improved our fundamental understanding of bacteria-material interactions but also provided a series of PLL-grafted PEGDA hydrogels with controlled stiffness and positive charge density as ideal surface coating materials to prevent bacterial infections.

bacteria↗
DOE OSTI2025

Fallowed agricultural lands dominate anthropogenic dust sources in California

Air pollution remains a major problem in many parts of California, significantly impacting public health and regional climate. However, the contribution of anthropogenic dust from agricultural sources, among major pollutants in California’s semi-arid Central Valley, remains largely unclear. Here, we used the Cropland Data Layer from the U.S. Department of Agriculture to identify crop types and land use/cover and leveraged satellite-derived estimates of major dust events between 2008 and 2022 over California. We identified fallowed land—an unplanted agricultural land parcel—as a key anthropogenic dust source in California. Specifically, we find that the Central Valley accounts for about 77% of total fallowed land areas in California, where they are associated with about 88% of major anthropogenic dust events. We also find that the geographic coverage of these fallowed lands expanded between 2008 and 2022 with associated increasing anthropogenic dust activities. Additionally, these anthropogenic dust activities are sensitive to the drought severity over the fallowed lands, with potential cumulative effects on downstream dust burden during prolonged multi-year drought conditions. Overall, our results have important implications for public health, including increased risk for Valley fever and for regional climates, such as increases in extreme precipitation and snowmelt over the Sierra Nevada.

Climate sciences↗
DOE OSTI2024

Quantification of heterogeneity in human CD8 + T cell responses to vaccine antigens: an HLA-guided perspective

Vaccines have historically played a pivotal role in controlling epidemics. Effective vaccines for viruses causing significant human disease, e.g., Ebola, Lassa fever, or Crimean Congo hemorrhagic fever virus, would be invaluable to public health strategies and counter-measure development missions. Here, we propose coverage metrics to quantify vaccine-induced CD8 + T cell-mediated immune protection, as well as metrics to characterize immuno-dominant epitopes, in light of human genetic heterogeneity and viral evolution. Proof-of-principle of our approach and methods are demonstrated for Ebola virus, SARS-CoV-2, and Burkholderia pseudomallei (vaccine) proteins.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Sticking Coefficients of Fusion Reactor Impurities from Molecular Dynamics Simulations for the Design of Cryopumps

A cryopump can be utilized as an impurity removal component of a direct internal recirculation (DIR) system for the fusion fuel cycle. The DIR facilitates a low fuel inventory by continuously pumping unburnt fuel while removing impurities from the fusion exhaust stream. A cryopump can target multiple impurity species by maintaining a temperature lower than the gas triple-point temperature that promotes desublimation. The desublimation/condensation of gases in cryopumps can be characterized by the sticking coefficient, which is defined as the probability for a gas particle to stick to a (cryo-)surface upon collision. The sticking coefficient is one of the important design/operation parameters for cryopumps, and it depends on a variety of surface and gas properties. Here, in this study, molecular dynamics simulations were utilized to estimate the sticking coefficients of typical fusion gas impurity species N 2 , CO 2 , and CH 4 over a Cu surface for a range of gas temperatures and surface coverages. The molecular dynamics study showed that the sticking coefficients for gases decrease with an increase in gas temperature. The presence of a single full monolayer of condensate on the metallic surface showed an adverse effect on the sticking of gases; however the sticking improved with two full monolayers of condensate on the surface. The sticking of gases over the mixed condensate on a surface was more favorable than the condensate of the same species for N 2 and CH 4 , with an exception for CO 2 , which showed a decrease in sticking over the mixed condensate.

cryopump↗
DOE OSTI2024

Cosmological Constraints from Combining Photometric Galaxy Surveys and Gravitational Wave Observatories

Spatial variations in survey properties due to selection effects generate substantial systematic errors in large-scale structure measurements in optical galaxy surveys on very large scales. On such scales, the statistical sensitivity of optical surveys is also limited by their finite sky coverage. By contrast, gravitational wave (GW) sources appear to be relatively free of these issues, provided the angular sensitivity of GW experiments can be accurately characterized. We quantify the expected cosmological information gain from combining the forecast LSST 3$\times$2pt analysis (combination of three 2-point correlations of galaxy density and weak lensing shear fields) with the large-scale auto-correlation of GW sources from proposed next-generation GW experiments. We find that in $\Lambda$CDM and $w$CDM models, there is no significant improvement in cosmological constraints from combining GW with LSST 3$\times$2pt over LSST alone, due to the large shot noise for the former; however, this combination does enable a $\sim6\%$ constraint on the linear galaxy bias of GW sources. More interestingly, the optical-GW data combination provides tight constraints on models with primordial non-Gaussianity (PNG), due to the predicted scale-dependent bias in PNG models on large scales. Assuming that the largest angular scales that LSST will probe are comparable to those in Stage III surveys ($\ell_{\rm min}\sim50$), the inclusion of next-generation GW measurements could improve constraints on the PNG parameter $f_{\rm NL}$ by up to a factor of $\simeq6.6$ compared to LSST alone, yielding $\sigma(f_{\rm NL})=8.5$. These results assume the expected capability of a network of Einstein Telescope-like GW observatories, with a detection rate of $10^6$ events/year. We investigate the sensitivity of our results to different assumptions about future GW detectors as well as different LSST analysis choices.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Impact of Domain Knowledge on the Property Prediction of Specialized Machine Learning Models

Developing transferable machine learning models is trending in data-driven materials research. However, how to apply such models to a specific research domain remains unclear. Here, in this work, we choose high-entropy materials as a platform with a specialized data set containing 145,323 DFT-relaxed materials. This data set is used to explore the role of domain-specific knowledge in training effective models. Our tests with three representative graph neural network architectures indicate the model complexity has much smaller influence on performance than the data itself. Specifically, the consideration of low-energy atomic ordering, structures with diverse elemental coverage, and high-order interactions significantly influences the model performance. We also find that domain knowledge-driven sampling can greatly enhance unsupervised learning techniques. This research highlights that developing specialized data sets is more beneficial than further complicating deep learning architectures. Additionally, physics-inspired sampling algorithms are crucially needed for better machine learning models for a specific materials research domain.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Photovoltaic and Cost Analysis for Winston-Salem, North Carolina

This study assesses the feasibility of solar installations at various sites in Winston-Salem, focusing on factors such as solar resource availability, electricity costs, and rooftop area for photovoltaic systems. The analysis begins by estimating daily energy requirements based on annual electricity use, followed by adjusting for seasonal and operational fluctuations. Using regional solar data from the National Solar Radiation Database (NSRDB), we calculate average peak sun hours to determine effective system sizing. A parametric approach using the System Advisor Model (SAM) refines this sizing process, incorporating a safety margin of 1.2 to address demand peaks. Each PV system is designed to fit available rooftop space, and a coverage threshold of 70% is identified as optimal for maximizing cost savings and sustainability. This threshold allows installations to meet substantial energy demands, supporting energy resilience and enhancing economic returns.

14 SOLAR ENERGY↗
DOE OSTI2026

A Joint Search for Muon Neutrino Disappearance with the Short-Baseline Neutrino Program Using the SPINE Deep Learning-Based Reconstruction Package

We present the status of a joint search for muon neutrino disappearance in the Booster Neutrino Beam at Fermilab using the Short-Baseline Neutrino (SBN) Program's two-detector configuration, SBND and ICARUS. Charged-current interactions consistent with muon neutrinos and containing only a muon and at least one proton in the final state are reconstructed and selected using the SPINE deep learning-based particle reconstruction package. To exploit proton multiplicity information and enhance sensitivity to modeling effects, the selected sample is partitioned into exclusive channels with exactly one reconstructed proton and with more than one reconstructed proton. Comprehensive systematic uncertainties from the neutrino flux, interaction, and detector response are incorporated into the analysis, and the coverage of these systematic uncertainty models is validated using data from both detectors, including checks of near-far consistency in key kinematic and topology-sensitive observables. This analysis is intended for inclusion in SBN's first oscillation result.

Mueller, Justin [Fermilab]↗
DOE OSTI2025

Carbene Functionalization of Monolayer Tungsten Disulfide for Enhanced Quantum Emission

Semiconducting two-dimensional (2D) transition metal dichalcogenides (TMDs) are promising materials for an array of applications, ranging from conventional field-effect transistors, photodetectors, and light-emitting diodes to their more recent use in quantum photonic technologies. Chemical functionalization of 2D TMDs with organic ligands and adlayers provides an additional means for customizing their electronic and optical properties. While many pathways have been reported for the chemical functionalization of 2D TMDs, their frequent reliance on solution-based methods results in limited control over adlayer thickness and coverage, thus hindering utility in high-performance applications. Here, in this study, we describe the vapor-phase functionalization of a 2D TMD with carbene ligands, specifically tungsten disulfide (WS 2 ) with N-heterocyclic carbenes (NHCs), resulting in molecularly smooth, thin, and uniform adlayers. Reacting NHCs with monolayer WS 2 reduces the broad photoluminescence background observed at cryogenic temperatures by 58%, which facilitates the detection of single-photon emitters from strained monolayer WS 2 , as indicated by second order correlation values ( g (2) ) as low as 0.17 ± 0.07. Chemical characterization coupled with density functional theory calculations suggests that the NHC adlayer has a dual defect-passivation and doping effect on monolayer WS 2 that results in enhanced single-photon emission. Overall, this study establishes vapor-phase carbene functionalization as a homogeneous surface modification scheme for tailoring the quantum emission properties of semiconducting 2D TMDs.

N-heterocyclic carbenes↗
DOE OSTI2024

Modeling Diurnal and Annual Ethylene Generation from Solar-Driven Electrochemical CO 2 Reduction Devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards achieving net-negative carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Here, using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimental CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. We simulated diurnal product outputs with and without the effects of ambient temperature to determine gaseous product temperature sensitivity. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne/yr at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

Yap, Kyra M. K.↗
DOE OSTI2024

Field Validation of Cloud Properties Sensor Field Campaign Report

The purpose of this campaign is to deploy Aerodyne Research Inc.’s extended wavelength cloud optical properties sensor (TWST-EN) in an operationally relevant environment with co-located, validated sensors. The Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) observatory is ideal for this deployment because of the variety of operational sensors that can measure some of the same cloud properties using different modalities. While cloud property sensors have long existed, they tend to be costly to produce and maintain. Our sensor measures absolute spectral radiance in the two bands and will retrieve cloud optical depth (COD), droplet effective radius, and thermodynamic phase. Our prototype is built predominantly from off-the-shelf components and uses uncooled spectrometers. A lower-cost, easy-to-use sensor such as this could allow deployment at many more sites for greater spatial coverage. Analysis and retrieval algorithm development using the data from this deployment has been a central technical objective of our U.S. Department of Energy Small Business Innovative Research (SBIR) Phase 2 contract (DE-SC0020473: Low-Cost Shortwave Spectroradiometer for Retrieval of Cloud Properties).

54 ENVIRONMENTAL SCIENCES↗