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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Learning interpretable surface elasticity properties from bulk properties via neural network equation learners

Surface elasticity is central to understanding the mechanics and stability of surfaces and interfaces. It is characterized by quantities such as surface tension, residual surface stress, and surface stiffness. However their analytical expressions are typically difficult to derive from atomistic data, and depend strongly on modeling choices. This work presents a neural network-based equation learner which combines customized activation functions and connection-based pruning to discover parsimonious, closed-form equations for surface elasticity from atomistic simulations. Applying the method to seven face-centered cubic (FCC) metals, our equation learner uncovers interpretable equations that describe both low-Miller index and high-Miller index surface properties, capturing long-tail property distributions accurately. The discovered expressions are decoupled into two components: a universal, geometry-driven orientation function, and material-specific baseline coefficients. We find that lower-order properties such as surface tension are fundamentally geometry dependent, while higher-order properties such as surface stress and elasticity show more complex geometry and material dependence. We also relate material dependent coefficients to bulk properties, forming a clear map from bulk material properties to surface elasticity. Overall, this approach demonstrates that interpretable neurosymbolic machine learning can bridge the gap between atomistic simulations and physical laws, enabling the discovery of generalizable structure–property relationships for materials science phenomena such as surface elasticity.

Equation learning↗
DOE OSTI2021

Performance Analysis and Limiting Parameters of Cross-flow Membrane-based Liquid-desiccant Air Dehumidifiers

We report that to dehumidify a humid air stream, existing air conditioning (AC) systems substantially overcool the outdoor humid air below its dew point, thereby significantly reducing energy efficiency. Directly capturing humidity, membrane-based liquid-desiccant dehumidification systems separate sensible and latent cooling (SSLC) loads and thus offer a promising pathway for a high-performance AC solution. Design of an energy-efficient SSLC-AC system, however, rests largely on detailed understating of the dehumidification process. While some studies have identified the dehumidification process mainly depends on membrane characteristics, other studies have argued that the process is limited by desiccant liquid or alternatively air thermo-hydraulic physics for typical humid climate conditions. The present study examines performance and physics of the membrane-based liquid-desiccant dehumidification process over a wide range of climate conditions through a novel 3D, two-phase, multi-species CFD model. Decoupling the thermodynamic and hydraulic effects, the study reveals that the dehumidification rate is a linear function of the water vapor pressure potential ($J=α ΔP$) summarizing the system's thermodynamic state. The slope of the curve (i.e., α) depends on hydraulic transport characteristics of the membrane pores, air stream, and desiccant solution. More importantly, it was found that the air dehumidification process is mainly limited by the air-side transport physics for thin liquid-desiccant films and commonly used porous superhydrophobic membranes. Additionally, results show that, depending on ambient/desiccant conditions and physical dehumidifier characteristics, energy effectiveness and dehumidification rate vary from 13 to 34% and from 0.13 to 1.4 g m -2 s -1 , respectively. Therefore, the present study allows to efficiently design future SSLC-based AC systems exhibiting high performance energy metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Electrochemically active surface area controls HER activity for Fe x Ni 100–x films in alkaline electrolyte

We report the synthesis and electrocatalytic activity of Fe x Ni 100-x electrochemically deposited films were investigated. Films were evaluated for the hydrogen evolution reaction (HER) in alkaline media with respect to composition and electrochemically active surface area (ECSA). Results demonstrate that films of higher or equal Fe content had an ECSA tenfold greater than films with higher Ni. When normalized by geometric surface area, Fe 50 Ni 50 films required the lowest overpotential of -390 mV to reach a current density of -10 mA cm -2 . However, when normalized by the ECSA, intrinsic HER activity increases as Ni content increases. Tafel slope, ECSA, microscopy, and impedance spectroscopy analyses allow a decoupled analysis of surface area versus activity effects on overall measured HER activity. Furthermore, these analyses collectively demonstrate that the increase in electrocatalytic activity is attributed to the increase in ECSA and not to an enhancement in the intrinsic activity by Fe and Ni component interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Rates and reversibility of CO 2 hydrogenation on Cu-based catalysts

Kinetics of reaction pathways involved in the conversion of CO 2 to methanol and CO on Cu/ZnO/Al 2 O 3 are resolved using in situ chemical titration, steady-state kinetic measurements, and mathematical formalisms for reversibility to probe salient species governing methanol selectivity and yield during CO 2 hydrogenation. Across a range of H 2 :CO 2 = 1:1 to H 2 :CO 2 = 80.5:1, active site density determined from in situ chlorine uptake remained invariant; hence, observed trends in rates can be interpreted as only arising from reaction kinetics and not from changing active site density. Kinetic and thermodynamic contributions to rates are decoupled to evaluate forward and reverse rates of methanol synthesis and reverse water-gas shift (RWGS) reactions. These kinetic analyses show that the forward rates of methanol synthesis exhibit persistent first order dependence on hydrogen pressure and are inhibited by water more significantly than the forward rates of RWGS. In contrast, the reverse rates of methanol synthesis and RWGS are both inhibited by H 2 . Consequently, without any modifications to the Cu/ZnO/Al 2 O 3 catalyst formulation, methanol selectivity can be increased to > 80% by increasing inlet H 2 partial pressure and methanol yield can be enhanced by ~20% by adding water adsorbents even under conditions far from equilibrium. Here, the kinetic treatments presented herein demonstrate a dearth of H* species during catalysis, provide thermodynamic constraints precluding sequential RWGS and CO hydrogenation as the pathway for methanol synthesis, reveal P H2 and P H2O as salient in determining methanol selectivity and yield by impacting both the forward and reverse rates of CO 2 hydrogenation on Cu/ZnO/Al 2 O 3 , and explicate the fundamentals of novel sorption-enhanced methanol synthesis, which not only alleviates equilibrium constraints but also alters the intrinsic rate at which the system approaches equilibrium.

42 ENGINEERING↗
DOE OSTI2022

Modeling multiple scattering transient of an ultrashort laser pulse by spherical particles

The multiple scattering of an ultrashort laser pulse by a turbid dispersive medium (namely a cloud of bubbles in water) is investigated by means of Monte Carlo simulations. The theory of Gouesbet and Gréhan (2000) is used to derive an energetic model of the scattering transient. It is shown that the spreading and extinction of the pulse can be decoupled from the transient of scattering, which allows to describe each phenomenon individually. The transient of scattering is modeled with the Lorenz-Mie Theory and thus is also valid for a relative refractive index lower than one, contrary to the Debye series expansion which does not converge close to the critical angle. This is made possible after the introduction of a new physical object, the Scattering Impulse Response Function (SIRF) which allows to detect the different modes of scattering transient, in time and direction. Here the present approach is more generic, as it enables to simulate clouds of air bubbles in water, which was not possible previously. Two different approaches are proposed within the Monte Carlo framework. The first is a pure Monte Carlo approach where the delay due to the scattering is randomly drawn at each event, while the second is based on the transport of the whole scattering signal. They are both embedded in the Monte Carlo code Scatter3D. Both models produce equivalent trends and are validated against published numerical results. They are then applied to the multiple scattering of ultra short pulse by a cloud of bubble in water in the forward direction. The pulse spread due to the propagation in water is computed for a wide range of traveled distances and pulse durations, and the optimal pulse duration is given to minimize the pulse spread at a given distance. The main result is that the scattered photons exit the turbid medium earlier than the ballistic photons and produce a double peak related to the refraction in the bubble. This demonstrates the possibility to develop new diagnostics to characterize dynamic bubbly flows.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Enabling probabilistic learning on manifolds through double diffusion maps

Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.

Double diffusion maps↗
DOE OSTI2023

Challenges and opportunities in plasma-activated reactions of CO 2 with light alkanes

We present upgrading CO 2 with surplus light alkanes to value-added chemicals using one-step plasma-activated processes under mild conditions, where opportunities and challenges for improving product selectivity focus on understanding reaction pathways, decoupling and benchmarking plasma and catalyst roles in reactions, tuning catalyst structural and electronic properties under plasma activation, and developing in situ characterization techniques.

03 NATURAL GAS↗
DOE OSTI2025

Differential Ligation Alters Electronic State and Coupling Signals of Iron-Sulfur Clusters in Flavin-Based Electron Bifurcation

Flavin-based electron bifurcation (FBEB) is employed by microorganisms for controlling pools of redox equivalents by reversibly splitting electron pairs into high- and low-energy levels from an initial midpoint potential. Our ability to harness this phenomenon is crucial for biocatalytic design which is limited by our understanding of energy coupling in the bifurcation system. In Pyrococcus furiosus, FBEB is carried out by the NADH-dependent ferredoxin:NADP+-oxidoreductase (NfnSL), coupling the uphill reduction of ferredoxin in NfnL to the downhill reduction of NAD+ in NfnS from oxidation of NADPH. Flanking the bifurcating flavin are two site-differentiated iron-sulfur clusters; the nearest is a glutamate-ligated [4Fe-4S] cluster in NfnL. Recent biochemical experiments substituting the native glutamate with cysteine led to loss of coupling between the uphill and downhill pathways, in contrast to the tight thermodynamic coupling in the native system. To understand how this decoupling is biochemically manifested by the cysteine-substituted [4Fe-4S] in NfnL, we employed electron paramagnetic resonance (EPR) spectroscopy to identify changes in electronic architecture and square wave voltammetry (SWV) to probe thermodynamic shifts produced by the substitution. We observed notable g-value shifts in the EPR for the cysteine-substituted iron-sulfur cluster in addition to significant downward shifts in the redox potential, as well as the disappearance of several low-field signals observed in the native NfnSL complex. These results suggest the site-differentiated glutamate residue facilitates higher spin states in the [4Fesingle bond4S] cluster to bridge energetic gaps in electron transfer to the bifurcating flavin in the native complex, preventing unwanted short-circuiting seen in the cysteine-substituted complex.

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

Application of BISON to UO 2 MiniFuel fission gas release analysis

There has been a recent push to accelerate fuel qualification by developing revolutionary capabilities to reduce irradiation periods, and thereby, reduce the time required to qualify a new fuel system. One such capability is the MiniFuel irradiation capsule designed to miniaturize fuel samples and irradiate “mini” fuel samples under isothermal temperature conditions. MiniFuel allows steady-state irradiations to decouple the traditionally coupled fission rate (i.e., power) and temperature parameters to understand and generate microstructures observed in fuel operated in a commercial reactor. Furthermore, this process offers the possibility to gather in situ data as well as postirradiation or transient data such as thermal conductivity, specific heat, fission gas diffusion and release, etc. However, accelerating fuel qualification is not solely reliant on generating large amounts of data but also on developing an informed test matrix designed to rapidly generate impactful data. Additionally, this process is reliant on fuel performance codes, such as BISON, to evaluate MiniFuel irradiations using existing material models. This process pinpoints model/data gaps, identifies desired irradiation conditions, and subsequently supports model validation and development. This work describes the use of BISON to perform a number of sensitivity studies designed to understand conditions that lead to fission gas release (FGR) under steady-state isothermal irradiation conditions and temperature transient conditions. The model is applied to a UO 2 MiniFuel example and shows an overall good qualitative agreement with experimental FGR annealing tests under different temperature conditions. It also accounts well for microstructural effects on FGR. When quantitatively compared with FGR data from previously irradiated 103 MWd/kgU UO 2 discs under thermal annealing, the model shows a less satisfactory agreement with the experimental data. Finally, a UO 2 MiniFuel test matrix is proposed to help to extend the model's operational range and validate the new FGR model capabilities to higher burnups and transient conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Modular Electrochemical Synthesis Using a Redox Reservoir Paired with Independent Half-Reactions

Electrochemical synthesis of high-value chemicals using renewable electricity could lead to sustainability advantages over conventional chemical manufacturing. The tight coupling between paired anodic and cathodic reactions in conventional electrochemical processes, however, constrains the products and their efficiencies. Here, we demonstrate a strategy to achieve modular electrochemical synthesis (ModES) of different chemicals by decoupling and pairing the oxidative and reductive half-reactions with a heterogeneous redox reservoir (RR). Specifically, sodium nickel hexacyanoferrate (NaNiHCF) can serve as a robust and reversible RR that enables the modular production of several strong oxidants, hydrogen peroxide (H 2 O2) and sodium persulfate (Na 2 S 2 O 8 ) or active chlorine, in separate RR-coupled electrochemical processes. The system’s excellent performance and operational stability is demonstrated by continuous operation over 100 cycles (~36 h) to produce H 2 O 2 and Na 2 S 2 O 8 with a high voltage efficiency. The concept presented here highlights the prospects for using RRs to enable efficient, modular, and on-demand electrochemical synthesis of valuable chemicals.

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

Enhancing water and oxygen transport through electrode engineering for AEM water electrolyzers

Anion-exchange membrane water electrolyzers (AEMWEs) can accelerate the deployment of more efficient and affordable hydrogen production solutions. Here, electrode structure is shown to affect water back-diffusion and oxygen transport, which, in return, governs overpotential behaviors in AEMWEs. Measurements indicate that electrode with copious catalytic sites produces water close to the AEM, creating a higher water gradient and driving water back-diffusion, which improves membrane hydration and mass transport. In situ measurement reveals a high pH gradient near the anode surface, which affects anode kinetics. Operando measurement shows reduced oxygen accumulation when decoupling oxygen production and transport on anode. Catalyst ink rheology and stability are tuned with additives to realize scalable fabrication of electrodes with enhanced transport features, allowing AEMWE to operate at 2 A cm−2 for over 1,000+ h at a 2.3 μV h−1 degradation rate. Analysis during and post-durability provides insights into degradation mechanisms. This work demonstrates an electrode design strategy for efficient and durable AEMWEs.

AEM↗
DOE OSTI2025

High-emissivity, thermally robust emitters for high power density thermophotovoltaics

Thermal radiative energy transport is essential for high-temperature energy harvesting technologies, including thermophotovoltaics (TPVs) and grid-scale thermal energy storage. However, the inherently low emissivity of conventional high-temperature materials constrains radiative energy transfer, thereby limiting system performance and technoeconomic viability. Here, in this study, we demonstrate ultrafast femtosecond laser-material interactions to transform diverse materials into near-blackbody surfaces with broadband spectral emissivity above 0.96. This enhancement arises from hierarchically engineered light-trapping microstructures enriched with nanoscale features, effectively decoupling surface optical properties from bulk thermomechanical properties. These laser-blackened surfaces (LaBS) exhibit exceptional thermal stability, retaining high emissivity for over 100 h at temperatures exceeding 1,000°C, even in oxidizing environments. When applied as TPV thermal emitters, Ta LaBS double electrical power output from 2.19 to 4.10 W cm −2 at 2,200°C while sustaining TPV conversion efficiencies above 30%. This versatile, largely material-independent technique offers a scalable and economically viable pathway to enhance emissivity for advanced thermal energy applications.

laser-blackened surfaces↗
DOE OSTI2021

Multi-fidelity electrochemical modeling of thermally activated battery cells

Thermally activated batteries undergo a series of coupled physical changes during activation that influence battery performance. These processes include energetic material burning, heat transfer, electrolyte phase change, capillary-driven two-phase porous flow, ion transport, electrochemical reactions, and electrical transport. Several of these processes are strongly coupled and have a significant effect on battery performance, but others have minimal impact or may be suitably represented by reduced-order models. Additionally, assessing the relative importance of these phenomena must be based on comparisons to a high-fidelity model including all known processes. In this work, we first present and demonstrate a high-fidelity, multi-physics model of electrochemical performance. This novel multi-physics model enables predictions of how competing physical processes affect battery performance and provides unique insights into the difficult-to-measure processes that happen during battery activation. We introduce four categories of model fidelity that include different physical simplifications, assumptions, and reduced-order models to decouple or remove costly elements of the simulation. Using this approach, we show an order-of-magnitude reduction in computational cost while preserving all design-relevant quantities of interest within 5 percent. The validity of this approach and these model reductions is demonstrated by comparison between results from the full fidelity model and the different reduced models.

25 ENERGY STORAGE↗
DOE OSTI2023

Design and operating principles for high-performing anion exchange membrane water electrolyzers

Anion-exchange-membrane water electrolyzers (AEMWEs) provide a promising pathway to utilize low-carbon renewable electricity to produce clean hydrogen at high efficiency and purity, while maintaining low system costs compared to incumbent technologies. Though significant progress has been made in developing membranes and catalysts, AEMWEs still require better performance and durability to realize widespread deployment. Here, we overcome these challenges by decoupling anode and cathode polarization behavior via integration of a reference electrode in the membrane-electrode assembly. This measurement identified that the mass-transport losses dominate the cathode overpotential if feeding with electrolytes, while kinetic losses dominate the anode overpotential. These losses are mitigated by varying electrode properties and operating strategies, where a more hydrophobic, optimal loaded cathode, a high porosity anode, and operating with the cathode dry exhibited the best performance. These findings eventually enabled achieving a high-performing and durable complete PGM-free AEMWE operating at 1.5 Acm –2 for over 500h with negligible degradation, demonstrating significant progress for AEMWEs.

25 ENERGY STORAGE↗
DOE OSTI2022

Activating nano-bulk interplays for sustainable ammonia electrosynthesis

Small changes in a catalyst’s composition, modification, and/or integration into a reactor can have significant yet often poorly understood effects on (electro)catalysis. Here we demonstrate the careful tailoring of Ru/La 0.25 Ce 0.75 O 2-x catalysts through the post-synthesized hydrothermal treatment together with control over the Ru loadings to create hydroxyl groups and electronic restructuring for ammonia electrosynthesis. When integrated into a protonic ceramic electrolyzer, the in situ formed Ce 3+ -OH/Ru sites facilitate both the N≡N decoupling and N—H formation at 400 °C and 1 bar of N 2 , boosting the ammonia production rate (2.92 mol h -1 m -2 ) up to 100-fold higher than the current state-of-the-art electrolyzers. Moreover, such catalysts and electrolyzer design concepts can be readily tuned to more complex applications such as coproducing ammonia and other chemicals with hydrocarbons as direct hydrogen sources. Here, the creation of coordinated saturated support –OH/metal sites in the advanced electrolyzer offers an attractive approach for future clean-energy and green-chemical industries.

03 NATURAL GAS↗
DOE OSTI2025

Unraveling the pathway towards superionic transport in polymer electrolytes

Ionic transport in polymers is critical for Li-ion batteries, fuel cells, flow batteries and many other energy storage and conversion technologies. A significant enhancement of ion conductivity in polymers may be achieved through an increase in the polarity of side chains and their self-organization into specific morphologies, which can potentially act as percolated ionic structures. However, higher polarity increases attractive interactions within a polymer matrix and slows down its segmental dynamics, which conversely hinders ionic transport. To overcome this tradeoff, we designed the functionalization of a Li salt-doped polymer matrix by tailored amounts of zwitterionic (ZI) groups. Our results suggest the emergence of a self-assembled percolation conductivity regime above a specific ZI concentration, in which ion hopping decouples from segmental dynamics by up to ten orders of magnitude. Consequently, in the highly concentrated ZI regime, our polymeric materials exhibit in their glassy state energy barriers for ion hopping similar to, or even smaller than, those reported for superionic ceramics. Our study also reveals that ion dynamics in the poly(zwitterion) with all monomers carrying ZI groups is significantly faster than that of a monomeric ZI compound, although the latter has much faster structural relaxation. Furthermore, this result highlights the crucial role played by the local morphology on the ion transport of polymer electrolytes and opens a new pathway for the design of superionic polymers, significantly expanding the current limited portfolio of solid-state electrolytes for energy applications.

Ion conductivity↗
DOE OSTI2025

Fully implicit crystal plasticity models representing orientations with modified Rodrigues parameters

Here, this work describes a crystal plasticity formulation combining several mathematical, numerical, and implementation choices to produce a highly efficient model. Specifically, the key choices in the implementation are (1) representing orientations with modified Rodrigues parameters, (2) implementing a fully coupled implicit time integration for the elastic stretch, the crystal orientations, and the model internal variables, (3) implementing the model in the NEML2 constitutive modeling framework, based on PyTorch, to vectorize the calculations and port the computation to GPUs and other hardware accelerators, and (4) an exact implementation of the consistent tangent matrix, even for arbitrary coupling to other field variables beyond the displacements, like temperature, neutron fluence, etc. The first two features of the model are, to our knowledge, novel. The paper considers each of these choices individually as well as the final model as a whole. This includes a full description of modified Rodrigues parameters, their advantages over other representations of orientations, the mathematical formulae and tools required to implement a model with modified Rodrigues parameters, and a detailed description of the geometry of the space of modified Rodrigues parameters (in an appendix). It also includes a description of a fully implicit time integration scheme for the orientations and the advantages in representing orientations with modified Rodrigues parameters in implementing such a model. The work then assess, via numerical examples, the advantages of fully coupled implicit time integration versus more common decoupled and explicit time integration schemes. These studies demonstrate the computational advantages of fully coupled integration versus other time integration algorithms, though the performance of the competing models depends on the complexity of the underlying single crystal model. The study concludes by demonstrating that the choice of time integration method affects the sharpness of the predicted texture, with explicit methods for integrating the orientations overestimating texture sharpness and implicit methods underestimating texture sharpness.

Crystal plasticity↗
DOE OSTI2020

Tunable mechanical behavior of graphene nanoribbon-metal composites fabricated through an electrocharge-assisted process

This work investigates the role of a carbon nanophase on the local mechanical behavior of nanocarbon metal matrix composites (NCMCs) produced through an electrocharge-assisted process. Nanoindentation experiments on single crystal Al, Al 1350 parent alloys, and Al 1350 NCMCs revealed variable mechanical properties, caused by an interplay between microstructure and graphitic reinforcements. TEM and AFM studies also reveal nanoscale structural changes based on the incorporation of a carbon nanophase. In order to decouple the effects of the aforementioned mechanical behaviors, molecular dynamics nanoindentation simulations were performed on the (111) surface of Al and Al NCMC samples containing semi-infinite graphene nanoribbons to examine the evolution of plasticity over time. Findings indicate that the arrangement of a finite graphene nanophase within a host matrix can alter plasticity mechanisms and therefore yield strength in near-surface mechanical behavior with little effect on elastic properties. Here, this understanding enables further study into tunable bulk properties of Al-based NCMCs while isolating microstructural effects and reinforcement effects of the carbon phase. Such an understanding will lead to application-specific material geometries ranging from highperforming vehicle structures to next-generation electrical devices.

36 MATERIALS SCIENCE↗