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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Hybrid chemical characterization of latent images in EUV resist with 12 nm half-pitch features

With the advancement of high numerical aperture extreme ultraviolet (EUV) lithography, the new platform will enable chipmakers to achieve critical dimensions of 8 nm. However, resist materials face significant challenges in delivering increased sensitivity while managing rising stochastic variations. We aim to develop comprehensive techniques to characterize the chemical profile of latent images, stored in EUV resists after exposure and postexposure baking, which is essential for understanding the origin of stochastic effects. Infrared photo-induced force microscopy (IR PiFM) is a bimodal atomic force microscopy technique combined with an infrared light source, allowing for simultaneous sub-5 nm topographic and chemical characterization within a localized environment. Critical-dimension resonant soft X-ray scatterometry (CD-RSoXS) provides statistical data that reveal structural and chemical information for comparative analysis. For the first time, IR PiFM has been used to chemically map the latent images of EUV resists (after exposure and postexposure baking) at a record high resolution of 12 nm half-pitch, enabling nondestructive analysis of patterns prior to development. Furthermore, CD-RSoXS offers direct experimental observation and comparison of exposed, postexposure baked, and developed patterns, which align with the IR PiFM results. We demonstrate that the IR PiFM technique offers valuable insights into both high spatial resolution and local chemical information simultaneously. In addition, CD-RSoXS provides statistical results that support our main findings. This hybrid metrology approach leverages a multifaceted dataset by combining the most reliable information from each source, which is essential for a comprehensive understanding of the stochastic effects in EUV lithography processes.

O’Reilly, Padraic↗
DOE OSTI2024

Cooled Spray Technology for Particulate Reduction in a Heavy-Duty Engine

Cooled spray (CS) technology passively reduces particulate matter (PM) emissions from diesel engines compared to non-CS-equipped diesel engines. CS inserts are mounted near the injector nozzle and control mixing so that the fuel and air can premix while limiting combustion near fuel-rich zones, thereby reducing the formation of particulate matter. CS components contain no moving parts and could be installed as a retrofit or built into new engines. However, CS technology is early in its development, and further investigations are needed to understand the overall performance implications and practicality of the technology. In this paper, we investigate several important aspects of CS, providing a clearer picture of some challenges and potential benefits of CS. Two alignment techniques are used to characterize measurement ease and bias, namely, an optical alignment and spray-plug impact alignment. While the optical technique facilitates alignment more easily, a bias was measured between the optical and spray-plug techniques, suggesting the optical technique may have insufficient accuracy without additional corrections. We also evaluate the engine performance of a well-aligned and poorly aligned CS insert, compared to the baseline configuration. The poorly aligned insert shows slower combustion than the baseline and mixed overall performance. However, the well-aligned insert shows faster combustion than the baseline and PM emission reduction at most operating conditions, with some conditions showing PM reduction up to 80%. Furthermore, the results of this paper highlight the alignment challenges of CS technology as well as the potential PM reduction benefit of the technology.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Comprehensive characterization of the irradiation effects of glassy carbon

Carbon materials have become increasingly diverse, finding applications in high-temperature and high-radiation environments. Glassy carbon, an allotrope known for its exceptional chemical inertness and desirable mechanical properties. However, understanding neutron irradiation effects in glassy carbon has proven challenging, primarily because of its unique nanopore structure. Here, this study presents a highly detailed microstructural characterization investigation of neutron-induced changes in glassy carbon, revealing how changes in nanopore structure and crystallinity impact the irradiation-induced shrinkage. Aberration-corrected scanning transmission electron microscopy (STEM) reveals pore closure that leads to material densification in the irradiated samples. Dimensional analysis combined with comparison to historical data suggest significant length shrinkage to occur. Neutron and in situ electron irradiation experiments suggest that glassy carbon transforms into so-called carbon onions, supporting the concept of shrinkage saturation. Investigating irradiation temperature effects using STEM, electron energy loss spectroscopy, x-ray diffraction, and Raman spectroscopy revealed partial amorphization at 210 °C–230 °C and preserved order in glassy carbon at 860 °C, coinciding with pore closure. Thermal property measurements were also conducted to assess the effects of densification and other changes in the atomic structure of glassy carbon. The results of this study have broad implications in the deployment of glassy carbon to nuclear environments, based around the observed changes in the thermal properties, and demonstrates the operational window for the onset of densification.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Two-dimensional spin systems in PECVD-grown diamond with tunable density and long coherence for enhanced quantum sensing and simulation

Systems of spins engineered with tunable density and reduced dimensionality enable a number of advancements in quantum sensing and simulation. Defects in diamond, such as nitrogen-vacancy (NV) centers and substitutional nitrogen (P1 centers), are particularly promising solid-state platforms to explore. However, the ability to controllably create coherent, two-dimensional spin systems and characterize their properties, such as density, depth confinement, and coherence, is an outstanding materials challenge. We present a refined approach to engineer dense (≳1 ppm ∙ nm), 2D nitrogen, and NV layers in diamond using delta-doping during plasma-enhanced chemical vapor deposition epitaxial growth. We employ both traditional materials techniques, e.g., secondary ion mass spectrometry, alongside NV spin decoherence-based measurements to characterize the density and dimensionality of the P1 and NV layers. We find P1 densities of 5–10 ppm ∙ nm, NV densities between 1 and 3.5 ppm ∙ nm tuned via electron irradiation dosage, and depth confinement of the spin layer down to 1.6 nm. We also observe high (up to 0.74) ratios of NV to P1 centers and reproducibly long NV coherence times, dominated by dipolar interactions with the engineered P1 and NV spin baths.

36 MATERIALS SCIENCE↗
NASA NTRS2017

Role of Forcing Uncertainty and Background Model Error Characterization in Snow Data Assimilation

Accurate specification of the model error covariances in data assimilation systems is a challenging issue. Ensemble land data assimilation methods rely on stochastic perturbations of input forcing and model prognostic fields for developing representations of input model error covariances. This article examines the limitations of using a single forcing dataset for specifying forcing uncertainty inputs for assimilating snow depth retrievals. Using an idealized data assimilation experiment, the article demonstrates that the use of hybrid forcing input strategies (either through the use of an ensemble of forcing products or through the added use of the forcing climatology) provide a better characterization of the background model error, which leads to improved data assimilation results, especially during the snow accumulation and melt-time periods. The use of hybrid forcing ensembles is then employed for assimilating snow depth retrievals from the AMSR2 (Advanced Microwave Scanning Radiometer 2) instrument over two domains in the continental USA with different snow evolution characteristics. Over a region near the Great Lakes, where the snow evolution tends to be ephemeral, the use of hybrid forcing ensembles provides significant improvements relative to the use of a single forcing dataset. Over the Colorado headwaters characterized by large snow accumulation, the impact of using the forcing ensemble is less prominent and is largely limited to the snow transition time periods. The results of the article demonstrate that improving the background model error through the use of a forcing ensemble enables the assimilation system to better incorporate the observational information.

assimilation↗
DOE OSTI2022

Machine‐Learning Spectral Indicators of Topology

Abstract Topological materials discovery has emerged as an important frontier in condensed matter physics. While theoretical classification frameworks have been used to identify thousands of candidate topological materials, experimental determination of materials’ topology often poses significant technical challenges. X‐ray absorption spectroscopy (XAS) is a widely used materials characterization technique sensitive to atoms’ local symmetry and chemical bonding, which are intimately linked to band topology by the theory of topological quantum chemistry (TQC). Moreover, as a local structural probe, XAS is known to have high quantitative agreement between experiment and calculation, suggesting that insights from computational spectra can effectively inform experiments. In this work, computed X‐ray absorption near‐edge structure (XANES) spectra of more than 10 000 inorganic materials to train a neural network (NN) classifier that predicts topological class directly from XANES signatures, achieving F 1 scores of 89% and 93% for topological and trivial classes, respectively is leveraged. Given the simplicity of the XAS setup and its compatibility with multimodal sample environments, the proposed machine‐learning‐augmented XAS topological indicator has the potential to discover broader categories of topological materials, such as non‐cleavable compounds and amorphous materials, and may further inform field‐driven phenomena in situ, such as magnetic field‐driven topological phase transitions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evidence of Alpha Radiolysis in the Formation of a Californium Nitrate Complex

Well-characterized complexes of transplutonium elements are scarce because of the experimental challenges of working with these elements and the rarity of the isotopes. This leads to a lack of structural and spectroscopic data needed to understand the nature of chemical bonds in these compounds. In this work, the synthesis of Cf(DOPO q ) 2 (NO 3 )(py) (DOPO q =2,4,6,8-tetra-tert-butyl-1-oxo-1H-phenoxazin-9-olate; py=pyridine) is reported, in which the nitrate anion is hypothesized to form through the α-radiolysis-induced reaction of pyridine and/or the ligand. Here, computational analysis of the electronic structure of the complex reveals that the Cf III –ligand interactions are largely ionic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Nanocomposite Materials for Radionuclide Sequestration from Groundwater Environments

The half-lives of radionuclides range from fractions of a second to billions of years. Since no practical method of altering radioactive decay exists, and since exposure to either the energy emitted from radioactive decay or chemical properties of radionuclides poses dire health risks, radioactive materials must be segregated and controlled. The capture, treatment, and disposition of radioactive materials remain an extraordinary challenge. In here, we focus our attention on the synthesis and characterization of a unique class of nanocomposite materials that have potential for removal of radionuclide contamination. Specifically, we report a simple approach to decorate the surface of iron-based (Fe/FexOy) material with various nano-catalysts. Specifically, copper (Cu), tin (Sn), and silver (Ag) nanoparticles were prepared through two different reduction approaches, namely, citrate and cetyltrimethylammonium bromide (CTAB) methods, on the iron-based material surface. All samples were characterized by a variety of analytical tools, which included scanning electron microscopy (SEM), electron-dispersive X-ray microanalysis (EDS), and EDS mapping to elucidate materials’ morphology as well as nano-catalysts’ loading and location on the iron-based structures.

Hunyadi Murph, Simona E.↗
DOE OSTI2025

Inducible flippase-mediated metabolic engineering of Rhodosporidium toruloides for enhanced 3-hydroxypropionic acid production from corn stover hydrolysate

Rhodosporidium toruloides has gained increasing interests as a promising non-model host organism to produce a wide range of bioproducts from lignocellulosic biomass. Increasing the bioproduct titers, rates, and yields remains a challenge, largely due to a lack of robust and well-characterized genetic tools in this host. Here we developed an inducible flippase (FLP) and flippase recognition target (FRT) system that enables genetic manipulations without the need for additional selection markers. Synthetic inducible promoters were established, enabling regulation of FLP expression and efficient antibiotic marker removal. Leveraging this system, we engineered a strain to optimize 3-hydroxypropionic acid (3HP) production. Over four rounds of iterative genomic editing to resolve pathway bottlenecks, we achieved a 3HP titer of 69.4 g/L in fed-batch fermentation - the highest level reported in yeast from lignocellulosic hydrolysates. The engineered high 3HP producing strain offers a robust platform for sustainable bio-based chemical production from lignocellulosic feedstocks.

3-hydroxypropionic acid↗
DOE OSTI2024

Multistage Stochastic optimization for mid-term integrated generation and maintenance scheduling of cascaded hydroelectric system with renewable energy uncertainty

The uncertainties resulting from the escalating penetration of renewable energy resources pose severe challenges to the efficient operation of modern power systems. Hydroelectricity is characterized by its flexibility, controllability, and reliability, and thus becomes one of the most ideal energy resources to hedge against such uncertainties. This paper studies the mid-term integrated generation and maintenance scheduling of a cascaded hydroelectric system (CHS) consisting of multiple cascaded reservoirs and hydroelectric units. To precisely describe the mid-term water regulation policies, the hydraulic coupling relationship and water-energy nexus of CHS are incorporated into the proposed optimization model. The uncertainties of natural water inflow and the power outputs of wind/solar energy generation are taken into consideration and captured via a stochastic process modeled by a scenario tree. A multistage stochastic optimization (MSO) approach is developed to coordinate the complementary operations of multiple energy resources, by optimizing the mid-term water resource management, generation scheduling, and maintenance scheduling of CHS. The proposed MSO model is formulated as a large-scale mixed-integer linear program that presents significant computational intractability. To address this issue, a tailored Benders decomposition algorithm is developed. Two real-world case studies are conducted to demonstrate the capability and characteristics of the proposed model and algorithm. The computational results show that the proposed MSO model can exploit the flexibility of hydroelectricity to efficiently respond to variable wind and solar power, and reserve water resources for the generation in peak months to reduce the consumption of fossil fuel. Furthermore, the proposed solution approach also exhibits promising computational efficiency when handling large-scale models.

13 HYDRO ENERGY↗
DOE OSTI2022

Friction stir welding and self-ion irradiation effects on microstructure and mechanical properties changes within oxide dispersion strengthened steel $\mathrm{MA956}$

We report the joining process for oxide dispersion strengthened (ODS) alloys remains a key challenge facing the nuclear community. The microstructure and mechanical properties were characterized in the base material and friction stir welded ODS MA956 irradiated with 5 MeV Fe 2+ ions from 400 to 500°C up to 25 dpa. Nanoindentation was performed to assess changes in hardness and yield stress, and the dispersed barrier hardening (DBH) model was applied to described results. A combination of scanning transmission electron microscopy (STEM) and atom probe tomography (APT) were used to assess evolution of the microstructure including dispersoids, network dislocations and dislocation loops, nanoclusters, and solid solution concentrations. Overall, softening was observed as a result of increased dose, which was exacerbated at 500°C. The formation and coarsening of new dispersoids was noted while nanoclusters tended to dissolve in the base material, and were not observed in the stir zone. Solute nanocluster evolution was identified as a primary driver of the changes in mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Engineered Nanoporous Frameworks for Adsorption Cooling Applications

The energy demand for traditional vapor-compressed technology for space cooling continues to soar year after year due to global warming and the increasing human population’s need to improve living and working conditions. Thus, there is a growing demand for eco-friendly technologies that use sustainable or waste energy resources. Here this review discusses the properties of various refrigerants used for adsorption cooling applications followed by a brief discussion on the thermodynamic cycle. Next, sorbents traditionally used for cooling are reviewed to emphasize the need for advanced capture materials with superior properties to improve refrigerant sorption. The remainder of the review focus on studies using engineered nanoporous frameworks (ENFs) with various refrigerants for adsorption cooling applications. The effects of the various factors that play a role in ENF–refrigerant pair selection, including pore structure/dimension/shape, morphology, open-metal sites, pore chemistry and possible presence of defects, are reviewed. Next, in-depth insights into the sorbent–refrigerant interaction, and pore filling mechanism gained through a combination of characterization techniques and computational modeling are discussed. Finally, we outline the challenges and opportunities related to using ENFs for adsorption cooling applications and provide our views on the future of this technology.

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

Thermal Weight Determination and Interstate Coupling in State-Averaged ADAPT-VQE

Characterizing electronic thermal states at low temperatures is an important but challenging task in quantum chemistry and condensed matter physics, making it a prime candidate for a useful application in quantum computing. One of the most successful methods for state preparation on quantum computers is the Adaptive, Problem-Tailored (ADAPT) Variational Quantum Eigensolver (VQE), which has recently been generalized to treat excited states within a state-averaged framework as well as Gibbs states. In this work, we introduce Helmholtz-Optimized Thermal (HOT) ADAPT-VQE, an ancilla-free strategy for preparing Gibbs states that directly minimizes the Helmholtz free energy by targeting the dominant eigenstates of the thermal ensemble. We demonstrate the usefulness of HOT-ADAPT-VQE by predicting the free energy of two model systems with strongly correlated ground states: (1) the Fe 2+ cation in a magnetic field and (2) a [Cu 2 O 7 ] 10– fragment of the Mott insulator La 2 CuO 4 . Our results demonstrate that HOT-ADAPT-VQE significantly improves upon Gibbs-state estimates from multistate variants of ADAPT-VQE, often with substantially shallower quantum circuits, making it a promising candidate for thermal-state calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Using In Situ High-Energy X-ray Diffraction to Quantify Electrode Behavior of Li-Ion Batteries from Extreme Fast Charging

Extreme fast charging (XFC, =15 min charging time) of Li-ion batteries (LIBs) has been proposed as an immediate target to increase the commercial appeal of electric vehicles. However, XFC of LIBs is associated with the degradation of battery performance and safety concerns. Quantitative and simultaneous characterization of various components during cell degradation represents a major experimental challenge. In this work, we outline a methodology for the use of spatially resolved, high-energy X-ray diffraction as a quantitative, in situ method of mapping the degradation of LIBs. We use this approach to study the battery cell capacity loss, both locally (mm scale) and globally over the entire cell (cm scale). Specifically, our workflow allows us to quantify the total amount of plated Li on the anode, as well as its spatial correlation to the structural properties of the anode and cathode. The method complements existing optical methods to resolve the spatial heterogeneity of local degradation mechanisms such as Li plating and provides simultaneous insights into concomitant anode state-of-charge variability. We apply it to commercially relevant single-layer pouch cells with the graphite anode and the LiNi 0.5 Mn 0.3 Co 0.2 O 2 cathode. Our results show that Li plating occurs heterogeneously on the graphite anode and that it is spatially correlated to the extent of anode lithiation. In this work, we anticipate that the described workflow will allow for understanding multiscale degradation in energy-storage devices beyond LIBs, where quantitative analysis at a local and global length scale can be performed without the necessity to tear down the device, due to the applicability of high-energy X-rays to probe in situ degradation.

25 ENERGY STORAGE↗
DOE OSTI2022

Amazonian terrestrial water balance inferred from satellite-observed water vapor isotopes

Atmospheric humidity and soil moisture in the Amazon forest are tightly coupled to the region’s water balance, or the difference between two moisture fluxes, evapotranspiration minus precipitation (ET-P). However, large and poorly characterized uncertainties in both fluxes, and in their difference, make it challenging to evaluate spatiotemporal variations of water balance and its dependence on ET or P. Here, we show that satellite observations of the HDO/H 2 O ratio of water vapor are sensitive to spatiotemporal variations of ET-P over the Amazon. When calibrated by basin-scale and mass-balance estimates of ET-P derived from terrestrial water storage and river discharge measurements, the isotopic data demonstrate that rainfall controls wet Amazon water balance variability, but ET becomes important in regulating water balance and its variability in the dry Amazon. Changes in the drivers of ET, such as above ground biomass, could therefore have a larger impact on soil moisture and humidity in the dry (southern and eastern) Amazon relative to the wet Amazon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Enhancing spectroscopy and microscopy with emerging methods in photon correlation and quantum illumination

Quantum optics has led to important advancements in our ability to prepare and detect correlations between individual photons. Its principles are increasingly translated into nanoscale characterization tools, furthering methods in spectroscopy, microscopy and metrology. Here, in this Review, we discuss the rapid progress in this field driven by advanced technologies of single-photon detectors and quantum-light sources, including time-resolved single-photon counting cameras, superconducting nanowire single-photon detectors and entangled photon sources of increasing brightness. We emphasize emerging applications in super-resolution microscopy, measurements below classical noise limits and photon-number-resolved spectroscopy—a powerful paradigm for the characterization of nanoscale electronic materials. We conclude by discussing key technological challenges and future opportunities in materials science and bionanophotonics alike.

Tsao, Chieh [University of California, Berkeley, C↗
DOE OSTI2023

VIPIR: A High-Throughput Drop-Weight Impact Instrument for Imaging the Initiation and Propagation of Reactions in Energetic Materials

Characterizing the handling safety and sensitivity of explosives has been a challenging area of study for over 60 years. Historically one of the most accessible and widely utilized experiments has been the drop-weight impact test, which involves dropping a weight on a small sample sandwiched between two anvils. Because this experiment generally only utilizes sound thresholds to determine whether or not a sample reacted, the physical and chemical properties governing sensitivity remain convolved. Better understanding of chemical and material characteristics is needed to give the chemistry and engineering communities a predictive tool to determine the handling sensitivity of explosives prior to pursuing expensive and potentially hazardous synthesis and formulation operations. Here, we are developing a high throughput drop tower instrument capable of imaging the deformation and flow of energetic materials during impact and the resulting thermal ignition and propagation events. This instrument is based on previous designs but has been modified for higher throughput and tailorable modifications in the future. Herein, we present key design features that enable high-speed visible and thermal imaging of explosive initiation by sub-shock impacts, as well as preliminary results in which ignition sites were observed in an erythritol tetranitrate sample.

47 OTHER INSTRUMENTATION↗