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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Prebiotic Membranes and Micelles Do Not Inhibit Peptide Formation During Dehydration

Abstract Cycles of dehydration and rehydration could have enabled formation of peptides and RNA in otherwise unfavorable conditions on the early Earth. Development of the first protocells would have hinged upon colocalization of these biopolymers with fatty acid membranes. Using atomic force microscopy, we find that a prebiotic fatty acid (decanoic acid) forms stacks of membranes after dehydration. Using LC‐MS‐MS (liquid chromatography‐tandem mass spectrometry) with isotope internal standards, we measure the rate of formation of serine dipeptides. We find that dipeptides form during dehydration at moderate temperatures (55 °C) at least as fast in the presence of decanoic acid membranes as in the absence of membranes. Our results are consistent with the hypothesis that protocells could have formed within evaporating environments on the early Earth.

Cohen, Zachary R.↗
DOE OSTI2024

Shortest path network interdiction with asymmetric uncertainty

Abstract This paper considers an extension of the shortest path network interdiction problem that incorporates robustness to account for parameter uncertainty. The shortest path interdiction problem is a game of two players with conflicting agendas and capabilities: an evader, who traverses the arcs of a network from a source node to a sink node using a path of shortest length, and an interdictor, who maximizes the length of the evader's shortest path by interdicting arcs on the network. It is usually assumed that the parameters defining the network are known exactly by both players. We consider the situation where the evader assumes the nominal parameter values while the interdictor uses robust optimization techniques to account for parameter uncertainty or sensor degradation. We formulate this problem as a nonlinear mixed‐integer semi‐infinite bilevel program and show that it can be converted into a mixed‐integer linear program with a second order cone constraint. We use random geometric networks and transportation networks to perform computational studies and demonstrate the unique decision strategies that our variant produces. Solving the shortest path interdiction problem with asymmetric uncertainty protects the interdictor from investing in a strategy that hinges on key interdictions performing as promised. It also provides an alternate strategy that mitigates the risk of these worst‐case possibilities.

Punla‐Green, She'ifa Z.↗
DOE OSTI2025

Impacts of Disulfide‐Containing Monomers in Alternating Diene Metathesis Polymerization

ABSTRACT Among the classes of synthetic polymers, disulfide‐containing structures offer unique opportunities due to their accessibility to redox chemistry that allows for degradation or reversible disulfide formation and exchange under mild conditions. Here, we examine the role of disulfides in olefin metathesis polymerization, specifically alternating diene metathesis (ALTMET) polymerization, for synthesizing unsaturated polyolefins with embedded disulfides. Our synthetic strategy hinged on the use of α,ω‐diacrylate monomers, including those connected by a disulfide unit, via copolymerization by the ALTMET mechanism to yield copolymers containing a range of disulfide content. In addition, the potential impacts of sulfur‐ruthenium interactions on the ALTMET process were investigated spectroscopically, while the degradation of the resultant polymers was affected by mild reducing agents. Overall, this study contributes to the development of degradable synthetic polymers using olefin metathesis methods, with an increased understanding of the potential for further use of disulfide groups in such metathesis reactions.

Lee, Kyoungwon↗
DOE OSTI2026

Ultrabroadband Spacetime Nanoscopy of Terahertz Polaritons in a van der Waals Cavity

Guiding, storing, and processing light at the nanoscale hinges on understanding how polaritons — hybrid quasiparticles of light and matter — propagate and interfere in both space and time. This work introduces a synchrotron-based technique, SYnchrotron SpaceTimE Mapping (SYSTEM), which captures real-time evolution of polariton wave packets with ∼10 nm spatial and sub-100 fs temporal resolution across an ultrabroadband 5–50 THz range. Here, SYSTEM directly visualizes the creation, interference, and decay of multiple high-quality Fabry-Pérot phonon polariton cavity modes in an α-MoO 3 microcavity. These real-space, real-time observations reveal wave-packet dynamics and cavity resonances with record-high quality factors (Q ≈ 100) in the single-digit terahertz regime near 9 THz. SYSTEM thus offers a powerful and broadly applicable platform for probing and engineering ultraslow, deeply subwavelength polaritons, opening new avenues for tailoring light–matter interactions and advancing next-generation THz nanophotonic technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Approximate Recovery and Relative Entropy I: General von Neumann Subalgebras

We prove the existence of a universal recovery channel that approximately recovers states on a von Neumann subalgebra when the change in relative entropy, with respect to a fixed reference state, is small. Our result is a generalization of previous results that applied to type-I von Neumann algebras by Junge at al. [arXiv:1509.07127]. We broadly follow their proof strategy but consider here arbitrary von Neumann algebras, where qualitatively new issues arise. Our results hinge on the construction of certain analytic vectors and computations/estimations of their Araki–Masuda L p norms. We comment on applications to the quantum null energy condition.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Exploring the Potential of Residual Impurities in Germanium Detectors for MeV-Scale Dark Matter Detection

Abstract The direct detection of MeV-scale dark matter (DM) particles hinges on achieving an exceptionally low-energy detection threshold. Germanium (Ge) detectors, meticulously tailored with precise impurity compositions, hold the potential to enhance sensitivity to energy levels below the sub-electronvolt (sub-eV) range. This study explores the behavior of residual impurities inherent to Ge detectors at helium temperatures, unveiling a captivating freeze-out phenomenon leading to the formation of excited localized states known as dipole states. Using compelling evidence from relative capacitance measurements obtained from two detectors, we elucidate the transition of impurity atoms from free charge states to these dipole states as the temperature drops from 11 to 6.5 K. Our investigation comprehensively covers the intricate formation of these dipole states in bothn-type andp-type impurities. Furthermore, we shed light on the electric field generated by these dipole states, revealing their ability to trap charges and facilitate the creation of cluster dipole states. Confirming findings from previous measurements, we establish that these excited dipole states exhibit a binding energy of less than 10 meV, offering an exceptionally low detection threshold for MeV-scale DM. Building upon this concept, we propose the development of a 1-kg Ge detector with internal charge amplification—an innovative approach poised to surpass electrical noise and enable the detection of MeV-scale DM with unprecedented sensitivity.

Physics↗
DOE OSTI2023

Subtleties in the trainability of quantum machine learning models

A new paradigm for data science has emerged, with quantum data, quantum models, and quantum computational devices. This field, called quantum machine learning (QML), aims to achieve a speedup over traditional machine learning for data analysis. However, its success usually hinges on efficiently training the parameters in quantum neural networks, and the field of QML is still lacking theoretical scaling results for their trainability. Some trainability results have been proven for a closely related field called variational quantum algorithms (VQAs). While both fields involve training a parametrized quantum circuit, there are crucial differences that make the results for one setting not readily applicable to the other. In this work, we bridge the two frameworks and show that gradient scaling results for VQAs can also be applied to study the gradient scaling of QML models. Our results indicate that features deemed detrimental for VQA trainability can also lead to issues such as barren plateaus in QML. Consequently, our work has implications for several QML proposals in the literature. In addition, we provide theoretical and numerical evidence that QML models exhibit further trainability issues not present in VQAs, arising from the use of a training dataset. We refer to these as dataset-induced barren plateaus. These results are most relevant when dealing with classical data, as here the choice of embedding scheme (i.e., the map between classical data and quantum states) can greatly affect the gradient scaling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Grain boundary strain as a determinant of localized sink efficiency

The opportunity to achieve radiation tolerance in crystalline materials hinges on understanding the structure and response of grain boundary sinks to irradiation. A common descriptor of grain boundary efficiency as a defect sink is the denuded zone, which is a defect free zone adjacent to the grain boundary dictated by its ability to absorb radiation induced defects. This descriptor is often used at the mesoscale, which requires an averaging of absorption events. In this paper, we resolve the defect sink efficiency as a function of interfacial strain with respect to grain boundary character, and correlate high levels of grain boundary strain to an enhanced absorption efficiency. Here, we also introduce a key relationship between localized strain in proximity with the grain boundary sink and the variation absorption efficiency associated with these regions, revealing the pitfalls of averaging absorption events along a grain boundary, and presenting a path forward toward improved models for denuded zones and localized grain boundary absorption phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dual aggregation steering in bulk-heterojunction via solvent engineering toward efficient and stable binary organic solar cells

In high-performance organic solar cells (OSCs), efficient charge transport hinges on a well-optimized morphology of the photoactive layer, which depends critically on controlled aggregation and favorable interactions between donor and acceptor materials. In this work, we introduce a cascade solvent system comprising high-boiling-point ethylbenzene (EB) and low-boiling-point chloroform (CF) to finely tune the aggregation behavior of the D18 donor and L8-BO acceptor. The incorporation of EB not only promotes the H-aggregation of D18 and the J-aggregation of L8-BO but also facilitates the formation of ideal nanoscale phase separation, thereby suppressing bimolecular recombination. As a result, devices processed with the EB/CF solvent blend achieve a best power conversion efficiency (PCE) of 19.6 % and enhanced operational stability, outperforming those fabricated with pure CF (17.1 %). In conclusion, this study offers a reliable and effective strategy for optimizing donor and acceptor aggregation, providing a viable pathway toward higher-performance OSCs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Deciphering the structure of Arabidopsis thaliana 5-enol-pyruvyl-shikimate-3-phosphate synthase: An essential step toward the discovery of novel inhibitors to supersede glyphosate

Glyphosate interferes with plant aromatic metabolism through the inhibition of 5-enol-pyruvyl-shikimate-3-phosphate (EPSP) synthase [EPSPS, EC 2.5.1.19]. For this reason, EPSPS has been extensively studied in a vast array of organisms. This notwithstanding, up to date, the crystal structure of the protein has been solved exclusively in a few prokaryotes, while that of the plant enzyme has been only deduced in silico by similarity. This study aimed at determining the structure of EPSPS from the plant model species Arabidopsis thaliana, which has been cloned, heterologously expressed and affinity-purified. The kinetic properties of the enzyme have been determined, as well as its susceptibility to the inhibition brought about by glyphosate. The crystal structure of the protein has been resolved at high resolution (1.4 Å), showing open conformation of the enzyme, which is the state ready for substrate/inhibitor binding. This provides a framework for the structure-based design of novel EPSPS inhibitors. Surface regions near the active-site cleft entrance or at the interdomain hinge appear promising for inhibitor selectivity, while bound chloride near the active site is a potential placeholder for anionic moieties of future herbicides.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Bayes_Opt-SWMM: A Gaussian process-based Bayesian optimization tool for real-time flood modeling with SWMM

Real-time flood model plays a pivotal role in averting urban flood damage, particularly when there is minimal lead time for preparatory measures. However, urban flood modeling in real-time often contends with inherent uncertainties arising from input data uncertainty and parameter ambiguities. Here this study introduces a real-time calibration (RTC) tool called Bayes_Opt-SWMM, specifically tailored for real-time urban flood modeling and uncertainty optimization. This tool leverages the Gaussian process-based Bayesian optimization algorithm and interfaces seamlessly with the Stormwater Management Model (SWMM). It integrates real-time model forcing data and flood monitoring collected through sensors and gauges which are strategically placed within critical locations of urban drainage systems. Our approach hinges on the Surrogate Model based Uncertainty Optimization (SMUO) concept, providing an avenue for enhancing real-time flood modeling. Bayes_Opt-SWMM runs the optimization process using a surrogate model called Gaussian Process emulator with two inference methods: (1) the Gaussian Process (GP) model and (2) Markov Chain Monte Carlo (MCMC) algorithm in GP model (GP_MCMC). Furthermore, three acquisition functions, namely Expected Improvement (EI), Maximum Probability of Improvement (MPI), and Lower Confidence Bound (LCB), facilitate optimal parameter fitting within the surrogate models. The efficiency of GP-based surrogate models in learning SWMM model parameters, leads to an improved uncertainty quantification and accelerated real-time flood modeling in urban areas. Overall, Bayes_Opt-SWMM emerges as a cost-effective and valuable tool for real-time flood modeling and monitoring, with significant potential for managing intelligent storm water systems in urban environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Ordering in liquid and its heredity impact on phase transformation of Mg-Al-Ca alloys

It is a long-sought goal to achieve desired mechanical properties through tailoring phase formation in alloys, especially for complicated multi-phase alloys. In fact, unveiling nucleation of competitive crystalline phases during solidification hinges on the nature of liquid. Here we employ ab initio molecular dynamics simulations (AIMD) to reveal liquid configuration of the Mg-Al-Ca alloys and explore its effect on the transformation of Ca-containing Laves phase from Al 2 Ca to Mg 2 Ca with increasing Ca/Al ratio (r Ca/Al ). There is structural similarity between liquid and crystalline phase in terms of the local arrangement environment, and the connection schemes of polyhedras. The forming signature of Mg 2 Ca, as hinted by the topological and chemical short-range order originating from liquid, ascends monotonically with increasing r Ca/Al . However, Al 2 Ca crystal-like order increase at first and then decrease at the crossover of r Ca/Al = 0.74, corresponding to experimental composition of phase transition from Al 2 Ca to Mg 2 Ca. The origin of phase transformation across different compositions lies in the dense packing of atomic configurations and preferential bonding of chemical species in both liquid and solid. The present finding provides a feasible scenario for manipulating phase formation to achieve high performance alloys by tailoring the crystal-like order in liquid.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advances and perspectives of hard carbon anode modulated by defect/hetero elemental engineering for sodium ion batteries

Sodium-ion batteries (SIBs) serve as a promising complement to lithium-ion batteries for large-scale energy storage, leveraging the abundance of sodium resources and notable safety advantages. The key advancement in SIB industrialization hinges on identifying a cost-effective and high-performance anode material, similar to the graphite anode in lithium-ion batteries. Hard carbon emerges as prime anode materials for SIBs, boasting high specific capacity, low sodium storage potential, and wide availability. However, practical applications of hard carbon encounters challenges such as low initial Coulombic efficiency (ICE), inadequate long-term cycling stability, and poor rate performance. Recent research has focused on the optimization of hard carbon electrodes through functional design. In this comprehensive review, we have meticulously examined the progress in enhancing sodium storage performance through microstructural modulation within hard carbon, encompassing four pivotal aspects: heteroatom doping, incorporation of oxygen functional groups, surface coating, and intrinsic defect engineering. Progress in implementing these strategies is scrutinized, while the merits and challenges of each defect engineering approach are discussed. In conclusion, this review also looks into forthcoming opportunities and challenges in the practical application process of hard carbon electrodes in SIBs.

25 ENERGY STORAGE↗
DOE OSTI2026

Electrochemical dynamics of imidazolium ionic liquids at graphene electrodes for energy storage applications

Electric double layer capacitors (EDLCs) are prominent energy storage systems that constitute the foundation of more reliable and sustainable energy infrastructures. Modern EDLCs often incorporate ionic liquids (ILs) as a key component in their electrolytes, leveraging the high electrochemical stability of ILs to enhance device performance. The performance and functionality of these capacitors also hinge on the interfacial behavior of ILs at electrode surfaces, which remain insufficiently understood. Here, we performed synchrotron infrared nanospectroscopy (SINS) in combination with density functional theory (DFT) calculations to investigate the electric double layers (EDLs) of three imidazolium-based ILs in a custom-designed graphene liquid cell. This approach revealed new insights into the dynamics of IL EDLs and the underpinning factors originating from the IL structures. Variations in anion size and structure were found to tune the ILs’ ability to form EDLs with compact and closely-correlated ion arrangements, which are critical for enhancing their capacitive performance. These findings highlight the intricate interactions between ions governed by their structures and charge behaviors, which underscores the opportunities for targeted design of IL-based electrolytes to optimize EDLC functionality.

Electric double layers↗
DOE OSTI2023

CdTe-based thin film photovoltaics: Recent advances, current challenges and future prospects

Cadmium telluride (CdTe)-based cells have emerged as the leading commercialized thin film photovoltaic technology and has intrinsically better temperature coefficients, energy yield, and degradation rates than Si technologies. More than 30 GW peak (GWp) of CdTe-based modules are installed worldwide, multiple companies are in production, modules are shipping at up to 18.6% efficiency, and lab cell efficiency is above 22%. We review developments in the science and technology that have occurred over approximately the past decade. These achievements were enabled by manufacturing innovations and scaling module production, as well as maximizing photocurrent through window layer optimization and alloyed CdSe x Te 1-x (CST) absorbers. Improved chlorine passivation processes, film microstructure, and serendipitous Se defect passivation significantly increased minority carrier lifetime. Efficiencies >22% have been realized for both Cu and As doped CST-based cells. The path to further efficiency gains hinges primarily on increasing open circuit voltage (V oc ) and fill factor (FF) through innovations in materials, fabrication methods, and device stacks. Replacing the longstanding Cu doping with As doping is resulting in better module stability and is being translated to large-scale production. To realize 25% efficiency and >1 V V oc , research and development is needed to increase the minority carrier lifetime beyond 100 ns, reduce grain boundary and interface recombination, and tailor band diagrams at the front and back interfaces. Many of these goals have been realized separately however combining them together using scalable manufacturing approaches has been elusive to date. We review these achievements and outstanding opportunities for this remarkable photovoltaic technology.

14 SOLAR ENERGY↗
DOE OSTI2023

Ab initio quantum dynamics of plasmonic charge carriers

Surface plasmons respond strongly to electric fields and generate energetic (hot) charge carriers that can be used in optoelectronic devices. However, utilization of hot carriers has to outcompete fast carrier relaxation in metals. Often, the reported efficiencies of nanoscale devices based on plasmon excitations are low and the mechanisms of device operation remain inconsistent within the field. Further developments hinge on fundamental understanding of the nature and kinetics of plasmon decay processes. In this work, we provide an overview of time domain ab initio modeling of hot carrier dynamics, demonstrating that atomistic details of the surface structure of plasmonic materials, and their chemical interaction with semiconducting and molecular charge acceptors and substrates, play key roles in governing the dynamics pathways. Considered case studies represent various dynamics channels and illustrate solar energy and optoelectronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Electronic Structure-Based Descriptors for Oxide Properties and Functions

The transition from fossil fuels to renewable energy requires the development of efficient and cost-effective energy storage technologies. A promising way forward is to harness the energy of intermittent renewable sources, such as solar and wind, to perform (electro)catalytic reactions to generate fuels, thus storing energy in the form of chemical bonds. Furthermore, current catalysts rely on the use of expensive, rare, or geographically localized elements, such as platinum. Widespread adoption of new (electro)catalytic technologies hinges on the discovery and development of materials containing earth-abundant elements, which can efficiently catalyze an array of (electro)chemical reactions.

Adsorption↗