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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Insights into the Thermal Expansion of Amorphous Polymers

Here, we investigated the thermal expansion of amorphous polystyrene (PS) and poly(methyl methacrylate) (PMMA) homopolymers using the temperature dependence of spatial electron-density correlations. The strong and broad X-ray interference maxima arising from inter- and intramolecular correlation distances were distinct, maintaining their shape during the heating of the samples to 250 °C. Three maxima characteristic of electron density correlations between the backbones, substituents along the chain, and repeat-units were observed. A remarkable temperature dependence was identified in the largest correlation distances arising from the intermolecular interactions. Based on the temperature dependence of the correlation distances, the coefficients of molecular expansion were very close to the coefficients of thermal expansion. This study provides a simple yet accurate way to correlate macroscopic volume expansions with the molecular expansion obtained from wide-angle X-ray scattering (WAXS) data.

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

Simultaneous Heat and Electricity Storage in a Flow Battery System

This study investigates the dual-storage capability of a redox flow battery (RFB) system, enabling simultaneous storage of heat and electricity within a single platform. Through electrochemical and thermal experiments, we evaluated how heat storage affects battery performance and vice versa using a counterflow heat exchanger integrated in a conventional RFB configuration. The results show that incorporating heat storage had a minimal impact on the electrochemical charging and discharging processes. Further, the heat discharge operated independently of electrochemical storage, confirming that both functions can coexist without interference. The combined system also enhanced overall energy conversion efficiency, demonstrating its potential as an efficient solution for supplying both thermal and electrical energythe two most widely used energy forms.

Electrical energy↗
DOE OSTI2024

Automated Calibration for Rapid Optical Spectroscopy Sensor Development for Online Monitoring

An automated platform has been developed to assist researchers in the rapid development of optical spectroscopy sensors to quantify species from spectral data. This platform performs calibration and validation measurements simultaneously. Real-time, in situ monitoring of complex systems through optical spectroscopy has been shown to be a useful tool; however, building calibration models requires development time, which can be a limiting factor in the case of radiological or otherwise hazardous systems. While calibration time can be reduced through optimized design of experiments, this study approached the challenge differently through automation. The ATLAS (Automated Transient Learning for Applied Sensors) platform used pneumatic control of stock solutions to cycle flow profiles through desired calibration concentrations for multivariate model construction. Additionally, the transients between desired concentrations based on flow calculations were used as validation measurements to understand model predictive capabilities. This automated approach yielded an incredible 76% reduction in model development time and a 60% reduction in sample volume versus estimated manual sample preparation and static measurements. The ATLAS system was demonstrated on two systems: a three-lanthanide system with Pr/Nd/Ho representing a use case with significant overlap or interference between analyte signatures and an alternate system containing Pr/Nd/Ni to demonstrate a use case in which broad-band corrosion species signatures interfered with more distinct lanthanide absorbance profiles. Both systems resulted in strong model prediction performance (RMSEP < 9%). Lastly, ATLAS was demonstrated as a tool to simulate process monitoring scenarios (e.g., column separation) in which models can be further optimized to account for day-to-day changes as necessary (e.g., baseline correction). Ultimately, ATLAS offers a vital tool to rapidly screen monitoring methods, investigate sensor fusion, and explore more complex systems (i.e., larger numbers of species).

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Developing Fluorescence-Based Sensors to Support Rare Earth Element Separation

Rare earth elements (REEs) are essential to most renewable energy technologies. Unfortunately, as we transition to sustainable energy production, the demand for REEs is rapidly growing well beyond current rates of production. As a result, novel means of efficient, scalable, and easily adaptable methods for processing primary and recycle feedstocks are needed. Development and integration of sensors for highly selective in-line monitoring can support more efficient design and testing of such novel separation processes, as well as more cost-effective deployment of those separation flowsheets. Work here will explore the application of fluorescence spectroscopy, a highly sensitive and selective technique, to quantify multiple lanthanides in complex mixtures including known interferents or quenching agents. Results include identification of the optimal excitation wavelength and the limit of detection of various rare earth elements as well as the performance of data-science-based quantification approaches in streams where “unknowns” are present. Overall, the data science tools in conjunction with optical sensor data were able to quantify analytes in the presence of other lanthanides which can be anticipated in the actual industrial stream. Here we include characterization of lanthanides in a microfluidic device similar to those used in new process development. This study demonstrates the capability of utilizing fluorescence spectroscopy to quantify analytes in a complicated solution matrix, suggesting this is a successful approach for in-line monitoring to optimize the separation efficiency in an industrial stream.

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

Optical Fiber Sensor with a Hydrophobic Filter Layer for Monitoring Hydrogen under Humid Conditions

Real-time and remote monitoring of hydrogen concentration in underground hydrogen storage reservoirs is crucial to maintaining the integrity and safety of the storage facilities. High humidity in the underground deposits interferes with hydrogen sensors, introducing inaccuracy into the hydrogen sensing measurements. A hydrophobic filter layer over a hydrogen sensing layer on an optical fiber hydrogen sensor was devised to minimize the impact of the humidity on the sensor. The hydrogen sensor coated with a hydrophobic filter layer demonstrated a significant improvement in reliable hydrogen sensing under high humidity conditions (99% RH) without severe baseline drift and reduction of transmission intensity. Finally, the optical fiber hydrogen sensor revamped with the filter layer would enable the reliable measurement of hydrogen concentration under the humid conditions expected in subsurface hydrogen storage facilities.

08 HYDROGEN↗
DOE OSTI2024

Systems-Level Modeling for CRISPR-Based Metabolic Engineering

The CRISPR-Cas system has enabled the development of sophisticated, multigene metabolic engineering programs through the use of guide RNA-directed activation or repression of target genes. To optimize biosynthetic pathways in microbial systems, we need improved models to inform design and implementation of transcriptional programs. Recent progress has resulted in new modeling approaches for identifying gene targets and predicting the efficacy of guide RNA targeting. Genome-scale and flux balance models have successfully been applied to identify targets for improving biosynthetic production yields using combinatorial CRISPR-interference (CRISPRi) programs. Here, the advent of new approaches for tunable and dynamic CRISPR activation (CRISPRa) promises to further advance these engineering capabilities. Once appropriate targets are identified, guide RNA prediction models can lead to increased efficacy in gene targeting. Developing improved models and incorporating approaches from machine learning may be able to overcome current limitations and greatly expand the capabilities of CRISPR-Cas9 tools for metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Spontaneous Formation of Single-Crystalline Spherulites in a Chiral 2D Hybrid Perovskite

In two-dimensional (2D) chiral metal-halide perovskites (MHPs), chiral organic spacers induce structural chirality and chiroptical properties in the metal-halide sublattice. This structural chirality enables reversible crystalline-glass phase transitions in (S-NEA) 2 PbBr 4 , a prototypical chiral 2D MHP where NEA + represents 1-(1-naphthyl)ethylammonium. Here, in this study, we investigate two distinct spherulite states of (S-NEA) 2 PbBr 4 , exhibiting either radial-like or stripe-like banded patterns depending on the annealing conditions of the amorphous film. Despite similarities in optical absorption and photoluminescence, the stripe-like, banded spherulite exhibits higher crystallinity and improved optical transparency compared to those of radial-like spherulite. X-ray nanoprobe measurements reveal tilting-angle modulations in the octahedral plane of stripe-like spherulites, correlating with the film’s surface geometry. Transfer matrix calculations indicate that the optical contrast in stripe-like patterns, seen in bright-field optical microscopy, arises from optical interference effects, differing from the contrast mechanism observed in polymer spherulites. Ultrafast carrier dynamics experiments suggest that the stripe-like spherulites resemble single crystals more closely than radial-like spherulites, while electrical conductivity measurements show enhanced charge carrier transport in stripe-like spherulites. These findings offer insights into MHP spherulite states with a single composition but different morphologies, previously observed only in polymers, highlighting their potential for optoelectronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Photoredox Catalysis with Spin Magnetic Field Effects: A Scheme for Chiral Resolution

Quantities that break both mirror symmetry and time-reversal symmetry, such as the orbital angular momentum, are known to connect molecular chirality with an applied magnetic field. This concept has led to observations such as magneto-chiral dichroism and chirality-induced spin selectivity (CISS). However, being small, these effects often require additional amplification procedures such as flow chemistry to achieve bulk enantioseparation. In this work, we demonstrate how the magnetic field effect on photogenerated radical pairs, which also breaks time-reversal symmetry, can be harnessed for enantiopurification. Fundamental to this process is the collective decay of the singlet and triplet radical-pair states made possible by an applied magnetic field. Because opposite enantiomers exhibit spin-orbit coupling matrix elements of opposite signs, the singlet and triplet decay channels interfere constructively in one enantiomer. Meanwhile, molecules of the other enantiomer are funnelled into the first enantiomer through excited-state chirality inversion, achieving (dynamic kinetic) chiral resolution. Using an axially chiral binaphthyl derivative and a borane photosensitizer as prototype, we predict an appreciable enantiomeric excess (e.e.) of 90% to be possible at steady state, attained within hundreds of milliseconds when irradiated by a laser. Importantly, our analytical results showcase regimes of perfect enantioselectivity (100% e.e.), accessible by further chemical optimization of the photosensitizer for which general strategies are discussed. Altogether, this work illustrates a so-far untapped but powerful control knob for photoredox catalysis based on spin chemistry principles.

Magnetic properties↗
DOE OSTI2025

Magnetic Blocking in Fluoflavine Radical-Bridged Dilanthanide Complexes

Magnetic exchange coupling is difficult to foster in polynuclear lanthanide (Ln) complexes and poorly understood. While coupling Ln ions through closed-shell ligands is inherently weak due to the contracted 4f orbitals, placing open-shell ligands instead has proven to promote orders of magnitude stronger coupling, giving rise to single-molecule magnets (SMMs) innate to real magnetic memory effect in the case of the anisotropic Ln ions. Notably, the impact of radical bridges with differing oxidation states on magnetic blocking remains unexplored due to lack of Ln SMMs with radicals in two distinct charge states. Herein, the first dilanthanide complexes (Ln = Gd, Dy) containing fluoflavine (flv) bridges, [(Cp* 2 Ln) 2 (μ-flv z )]X, (where X = [Al(OC{CF 3 } 3 ) 4 ] − (z = 1−•), 1-Ln; X = 0 (z = 2−), 2-Ln; X =[K(crypt-222)] + (z = 3−•), 3-Ln) are reported. 1-Ln and 3-Ln, comprising the flv 1−• and flv 3−• radical bridges, were investigated via single-crystal X-ray diffraction (SCXRD), ultraviolet−visible (UV−vis) spectroscopy, Superconducting Quantum Interference Device (SQUID) magnetometry, high-field electron paramagnetic resonance (HF-EPR) spectroscopy and broken-symmetry density functional theory (BS-DFT) calculations. 1-Dy and 3-Dy constitute the first SMMs innate to radicals in two differing oxidation states. 1-Dy exhibits a spin-reversal barrier U eff of 28.36 cm −1 and open magnetic hysteresis loops below 3 K. By contrast, 3-Dy displays a much higher U eff of 143(2) cm −1 and open hysteresis loops until 9.5 K, representing a record for dilanthanide SMMs containing an organic radical bridge. The boost in SMM properties in 3-Dy is attributed to spin-phonon coupling and improved frontier orbital structure. This study paves the way for advanced design strategies of polynuclear Ln SMMs.

Benner, Florian [Michigan State Univ., East Lansin↗
DOE OSTI2026

Advancing Protein Display on Bacterial Spores through an Extensive Survey of Coat Components

The profound stability of bacterial spores makes them a promising platform for biotechnological applications like biocatalysis, bioremediation, drug delivery, etc. However, though the Bacillus subtilis spore is composed of >40 types of proteins, only ∼12 have been explored as fusion carriers for protein display. Here, we assessed the suitability of 33 spore proteins (SPs) as enzyme display carriers by direct allele tagging at native genomic loci. Of the 33 SPs investigated, 26 formed functional fusions with β-glucuronidase (GUS)─a ∼272 kDa homotetramer. This almost triples the number of SPs assessed for enzyme display and doubles the number of functional fusions documented in the literature. We quantitatively assessed 1) SP promoter activation dynamics, 2) GUS activity on spores, 3) surface availability, and 4) protection from thermal and proteolytic degradation. Multicopy expression and pairwise coexpression of the most promising SP-GUS fusions highlighted the complexity of spore structure/assembly and the difficulty in predicting compatibility between different SP fusions. We also assessed the suitability of engineered spores to degrade PET (polyethylene terephthalate) films and found that surface-exposed SPs were most effective. Beyond the broad survey, a key outcome of our work was the identification of SscA (small spore coat assembly protein A) as an effective spore display carrier. SscA supported enzyme activity at least 4-fold higher than any other SP, including the well-established anchor, CotY. We attribute this to its promoter, which demonstrated early and sustained activation relative to other SPs and its small size (∼3 kDa), which likely minimally interferes with enzyme folding, oligomerization, and activity. Labeling and genetic studies, its hydrophobic nature, and low surface availability suggest that SscA assembles within the inner spore coat, which makes it stabilizing and suitable for many biocatalytic applications. Overall, this work serves as a knowledge base to advance the biotechnological utility of B. subtilis spores.

Bacillus subtilis↗
DOE OSTI2024

Actinide Elemental Ratios of Spent Nuclear Fuel Samples by Resonance Ionization Mass Spectrometry

While resonance ionization mass spectrometry (RIMS) has demonstrated utility in measuring isotopic compositions of elements in complex matrices without the need for chemical separation to remove isobaric interferences, it has had limited application in measuring elemental compositions. The ability to determine elemental compositions via an in situ method like RIMS would be an exceptional asset in spent nuclear fuel analysis, where they are important in assessing reactor histories and whose chemical separation presents a radiological hazard. However, quantitative elemental analysis by RIMS requires special considerations because each element is ionized by its own set of lasers tuned to element specific resonant ionization wavelengths. We present the first comprehensive study of measuring elemental ratios by RIMS in spent nuclear fuel. All actinides produced by neutron capture are enhanced significantly radially from the center to the edge of a fuel pellet. This edge effect is not readily accessible by conventional bulk measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

A Machine Learning Bias Correction on Large–Scale Environment of High–Impact Weather Systems in E3SM Atmosphere Model

Large–scale dynamical and thermodynamical processes are common environmental drivers of high–impact weather systems causing extreme weather events. However, such large–scale environmental conditions often display systematic biases in climate simulations, posing challenges to evaluating high–impact weather systems and extreme weather events. In this paper, a machine learning (ML) approach was employed to bias correct the large–scale wind, temperature, and humidity simulated by the atmospheric component of the Energy Exascale Earth System Model (E3SM) at ~1° resolution. The usefulness of the ML approach for extreme weather analysis was demonstrated with a focus on three high–impact weather systems, including tropical cyclones (TCs), extratropical cyclones (ETCs), and atmospheric rivers (ARs). We show that the ML model can effectively reduce climate bias in large–scale wind, temperature, and humidity while preserving their responses to imposed climate change perturbations. The bias correction is found to directly improve water vapor transport associated with ARs, and representations of thermodynamical flows associated with ETCs. When the bias–corrected large–scale winds are used to drive a synthetic TC track forecast model over the Atlantic basin, the resulting TC track density agrees better with that of the TC track model driven by observed winds. In addition, the ML model insignificantly interferes with the mean climate change signals of large–scale storm environments as well as the occurrence and intensity of three weather systems. This study suggests that the proposed ML approach can be used to improve the downscaling of extreme weather events by providing more realistic large–scale storm environments simulated by low–resolution climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Design and Characterization of the Engineering Model of the Spectrometer Onboard LuSEE‐Night

Abstract The Lunar Surface Electromagnetics Explorer—Night, LuSEE‐Night, is a low‐frequency radio astronomy experiment that will explore the cosmic Dark Ages signal on the radio‐quiet farside of the Moon. The LuSEE‐Night carries a radio frequency spectrometer consisting of a set of antennas, analog and digital processing electronics, and will be launched by NASA's Commercial Lunar Payload Services in 2025. The spectrometer is designed to observe the spectrum of the radio sky in the 0.5−50 MHz band. The engineering model (EM) of the four‐channel spectrometer has been developed. The EM has been characterized for linearity, gain, noise, and their temperature dependence, confirming that the EM meets all the requirements for LuSEE‐Night. Three mitigation techniques have been implemented and verified to suppress self‐induced electromagnetic interference. The flight model of the spectrometer is currently being developed and is scheduled to be shipped to the integration site in early 2024.

Tamura, Emi↗
DOE OSTI2024

Fracture Characterization Via AI‐Assisted Analysis of Temperature Logs

Abstract Fractures control fluid flow, mass transport, and heat transfer in a geothermal reservoir. This makes accurate characterization of fracture networks a prerequisite for optimal design and control of a reservoir's exploitation. We develop a deep‐learning procedure to identify fracture locations via interpretation of temporally and spatially continuous downhole temperature measurements. A long short‐term memory fully convolutional network (LSTM‐FCN) is used both to capture long‐term dependencies in sequential temperature data and to distill local features around fractures. A wellbore and fractured‐reservoir thermal model is established to generate temperature data for network training. The trained LSTM‐FCN exhibits a unique ability to detect multiple fractures intersecting a borehole. We use the LSTM‐FCN algorithm to evaluate the effectiveness of different‐stage wellbore temperature measurements on fracture detection in a complex fractured system. Our experiments reveal that the use of various‐stage temperature information as an input feature set improves the robustness of fracture detection to noise interference. This study indicates the practical feasibility of obtaining accurate fracture‐network reconstructions from temperature signals, at reasonable computational cost.

Yang, Xiaoyu↗
DOE OSTI2025

Optoelectronic polymer memristors with dynamic control for power-efficient in-sensor edge computing

Abstract As the demand for edge platforms in artificial intelligence increases, including mobile devices and security applications, the surge in data influx into edge devices often triggers interference and suboptimal decision-making. There is a pressing need for solutions emphasizing low power consumption and cost-effectiveness. In-sensor computing systems employing memristors face challenges in optimizing energy efficiency and streamlining manufacturing due to the necessity for multiple physical processing components. Here, we introduce low-power organic optoelectronic memristors with synergistic optical and mV-level electrical tunable operation for a dynamic “control-on-demand” architecture. Integrating signal sensing, featuring, and processing within the same memristors enables the realization of each in-sensor analogue reservoir computing module, and minimizes circuit integration complexity. The system achieves 97.15% fingerprint recognition accuracy while maintaining a minimal reservoir size and ultra-low energy consumption. Furthermore, we leverage wafer-scale solution techniques and flexible substrates for optimal memristor fabrication. By centralizing core functionalities on the same in-sensor platform, we propose a resilient and adaptable framework for energy-efficient and economical edge computing.

Optics↗
DOE OSTI2026

Dynamically tunable membrane metasurfaces for infrared spectroscopy and strong light-matter interactions

Mid-infrared spectroscopy enables biochemical sensing by identifying vibrational molecular fingerprints, but it faces limitations in instrumentation portability and analytical sensitivity. Optical metasurfaces with strong mid-infrared photonic resonances provide an attractive solution towards on-chip spectrometry and sensitive molecular detection, yet their static nature hinders their anticipated impact. Here, we introduce and demonstrate dynamically tunable silicon membrane metasurfaces exhibiting high-Q transmissive resonances in the fingerprint region. By harnessing silicon’s thermo-optical properties, we achieve continuous modulation of coupling-induced transparency (CIT) modes that emerge upon the interference of quasi-bound states in the continuum (q-BICs) and surface lattice modes (SLMs). We measure a spectral tuning rate of 0.06 cm −1 K −1 by continuously sweeping the sharp CIT resonances over a 23.5 cm −1 spectral range across a temperature range of 300–700 K. In the current proof‑of‑concept implementation, the dynamic transmission control enables non-contact chemical analysis of polymer films by detecting characteristic absorption bands of polystyrene (1450 and 1492 cm −1 ) and poly(methyl methacrylate) (1730 cm −1 ) without requiring conventional spectrometers. When analyte molecules fill the metasurface-generated photonic cavities, we demonstrate vibrational strong coupling between the poly(methyl methacrylate)’s carbonyl band and the CIT mode, manifested in a Rabi splitting of ~43 cm −1 . Our results establish a new photonic platform that unites spectral precision, strong field enhancement, and reconfigurability, offering diverse potential for compact mid-infrared spectroscopy, molecular sensing, and programmable polaritonic photonics.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Low-energy electronic structure in the unconventional charge-ordered state of ScV6Sn6

Abstract Kagome vanadates A V 3 Sb 5 display unusual low-temperature electronic properties including charge density waves (CDW), whose microscopic origin remains unsettled. Recently, CDW order has been discovered in a new material ScV 6 Sn 6 , providing an opportunity to explore whether the onset of CDW leads to unusual electronic properties. Here, we study this question using angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy (STM). The ARPES measurements show minimal changes to the electronic structure after the onset of CDW. However, STM quasiparticle interference (QPI) measurements show strong dispersing features related to the CDW ordering vectors. A plausible explanation is the presence of a strong momentum-dependent scattering potential peaked at the CDW wavevector, associated with the existence of competing CDW instabilities. Our STM results further indicate that the bands most affected by the CDW are near vHS, analogous to the case of A V 3 Sb 5 despite very different CDW wavevectors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Emergent flat band and topological Kondo semimetal driven by orbital-selective correlations

Flat electronic bands are expected to show proportionally enhanced electron correlations, which may generate a plethora of novel quantum phases and unusual low-energy excitations. They are increasingly being pursued in d-electron-based systems with crystalline lattices that feature destructive electronic interference, where they are often topological. Such flat bands, though, are generically located far away from the Fermi energy, which limits their capacity to partake in the low-energy physics. Here we show that electron correlations produce emergent flat bands that are pinned to the Fermi energy. We demonstrate this effect within a Hubbard model, in the regime described by Wannier orbitals where an effective Kondo description arises through orbital-selective Mott correlations. Moreover, the correlation effect cooperates with symmetry constraints to produce a topological Kondo semimetal. Our results motivate a novel design principle for Weyl Kondo semimetals in a new setting, viz.d-electron-based materials on suitable crystal lattices, and uncover interconnections among seemingly disparate systems that may inspire fresh understandings and realizations of correlated topological effects in quantum materials and beyond.

74 ATOMIC AND MOLECULAR PHYSICS↗