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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Structure–performance relationships of lithium-ion battery cathodes revealed by contrast-variation small-angle neutron scattering

Lithium-ion battery cathodes are porous composites of active material, conductive carbon, and polymer binder. Controlling the cathode microstructure is key to achieving high energy density and cycling stability. Current characterization techniques lack the nanoscale resolution over representative volumes necessary to relate cathode microstructure to cycling performance. To address this challenge, we utilize contrast-variation small-angle neutron scattering to quantify the chemical and structural features of cathodes wet by dimethyl carbonate, representing a relevant solvent environment. Using neutron scattering measurements, we identify an expansion in carbon and polymer structures that arises after calendering and wetting with solvent. Further, we deconvolute the carbon and binder phases to obtain the solvent-accessible carbon black surface area, which we correlate to diminished capacity retention driven by electrolyte decomposition on exposed carbon. This technique provides nanoscale insight into composite cathode microstructures and resulting cycling performance, promising future applications to a broad range of porous materials that exist in energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2026

Conformal hetero-electrolyte interface between soft oxyhalides and garnet enables low-pressure lithium-reservoir-free solid-state batteries

The operation of solid-state batteries with a lithium metal anode and a high voltage cathode requires solid electrolytes (SEs) that are chemically stable with lithium, have a wide electrochemical window, and accommodate volume changes in the electrodes. Unfortunately, no SE has exhibited satisfactory mechanical and electrochemical properties that fit these requirements to date. Dual solid electrolyte systems that use a different SE for the anolyte and catholyte present a viable solution. Here, we focus on oxyhalide SEs that demonstrate superior ionic conductivity and cathode compatibility, where their lithium metal reactivity and poor reduction stability can be resolved using a lithium garnet (Li 6.5 La 3 Zr 1.5 Ta 0.5 O 12 , LLZTO) separator. Nonetheless, this imposes a new hetero-electrolyte (H-E) interface at the anolyte|catholyte contact that defines the ion transport across the boundary. We report its promising properties, which are deconvoluted from the electrical measurements of bilayer symmetric cells, for three representative oxyhalide catholytes, LiNbOCl 4 , LiTaOCl 4 , and Li 3 Al 3 O 2 Cl 8 . Pressure-dependent measurements reveal that the relative softness of the oxyhalides (hardness ≤0.4 GPa) enables H-E resistances lower than 150 Ω cm 2 at 2–3 MPa. Mesoscale modelling reveals that the transfer-active contact area of oxyhalides with LLZTO is about 2–3-fold higher than that of argyrodite, Li 6 PS 5 Cl. The low H-E resistance of the LiNbOCl 4 |Li 6.5 La 3 Zr 1.5 Ta 0.5 O 12 dual electrolyte enables the cycling of a Li|LiNi 0.82 Mn 0.07 Co 0.11 O 2 full cell with a high discharge capacity (200 mA h g −1 ) at 60 °C and ∼7 MPa. Importantly, we demonstrate a Li-reservoir-free full cell with high Coulombic efficiency (>99.5%) and capacity at 1 MPa using this approach coupled with a garnet-silver interlayer.

Palmer, Max [University of California, Santa Barba↗
DOE OSTI2025

Unraveling membrane electrode assembly design for electrochemical conversion of carbon dioxide to formate/formic acid

This work presents a one-dimensional continuum modeling approach to investigate various cell architectures used for electrochemical conversion of CO 2 to formate/formic acid. Ion transport is simulated by a system of generalized modified Poisson–Nernst–Planck (GMPNP) equations that reflect the reactive transport phenomena including steric effects as the electrolyte solutions become concentrated. In the cathode catalyst layer, ionic current contributions from both the supporting electrolyte and solid-state ionomer are considered. Voltage and CO 2 utilization breakdowns are utilized to deconvolute the impacts of the cell architecture. The origins of (bi)carbonate formation in the cathode are explored, as the subsequent decrease in CO 2 availability is a key reason for low faradaic efficiencies to formate/formic acid. In addition, the role of a supporting electrolyte (KOH) is investigated to understand its tradeoffs: while the K + ions can improve both conductivity and electrochemically active surface area in the cathode, the presence of OH − ions raises the pH and leads to deleterious formation of (bi)carbonates. To this end, we also present parametric studies on the concentration and flow rate of supplied KOH to the cell, to establish a path towards eliminating the need for a supporting electrolyte.

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

A contactless in situ EFISH method for measuring electrostatic potential profile of semiconductor/electrolyte junctions

In photoelectrochemical cells, promising devices for directly converting solar energy into storable chemical fuels, the spatial variation of the electrostatic potential across the semiconductor–electrolyte junction is the key parameter that determines the cell performance. In principle, electric field induced second harmonic generation (EFISH) provides a contactless in situ spectroscopic tool to measure the spatial variation of electrostatic potential. However, the total second harmonic generation (SHG) signal contains the contributions of the EFISH signals of semiconductor space charge layer and the electric double layer, in addition to the SHG signal of the electrode surface. The interference of these complex quantities hinders their analysis. In this work, to understand and deconvolute their contributions to the total SHG signals, bias-dependent SHG measurements are performed on the rutile TiO2(100)–electrolyte junction as a function of light polarization and crystal azimuthal angle (angle of the incident plane relative to the crystal [001] axis). A quadratic response between SHG intensity and the applied potential is observed in both the accumulation and depletion regions of TiO2. The relative phase difference and amplitude ratio are extracted at selected azimuthal angles and light polarizations. At 0° azimuthal angle and s-in–p-out polarization, the SHG intensity minimum has the best match with the TiO2 flatband potential due to the orthogonal relative phase difference between bias-dependent and bias-independent SHG terms. We further measure the pH-dependent flatband potential and probe the photovoltage under open circuit conditions using the EFISH technique, demonstrating the capability of this contactless method for measuring electrostatic potential at semiconductor–electrolyte junctions.

Chemistry↗
DOE OSTI2025

Isomers and band assignments in the cryogenic vibrational spectrum of the binary complex between water and protonated formic acid using two color, IR–IR photobleaching and H/D isotopic substitution

Protonated formic acid (PFA) is purported to be the active species in the catalytic activation of condensation reactions at the acidic interface of microdroplets. Here, we investigate the fundamental interaction between PFA and water with cryogenic ion vibrational spectroscopy of the binary PFA–H 2 O complexes generated via electrospray ionization followed by buffer gas cooling to about 20 K. The patterns displayed by the isomer-specific IR spectra of D 2 -tagged PFA–H 2 O indicate that two distinct, non-interconverting rotamers are present at low temperatures based on the cis and trans structures of the HCO 2 $H$$^{+}_{2}$ core ion. Both of these occur with the water molecule attached to the OH that is in a cis-configuration relative to the CH group (denoted E), but differ in the E vs Z (cis vs trans relative to the CH group) orientation of the spectator OH. This assignment scheme corrects a previous theoretical analysis that invoked a scenario in which structures with E- and Z-bound water molecules interconvert at low (20 K) temperatures. Isomer-specific bands arising from the OH stretches and water bending modes are deconvoluted using isotopomer-specific spectroscopy of the complexes with partial H/D exchange. The dependence of the nominal shared proton OH stretch frequency on the deuteration of the tethered water confirms strong coupling between this mode and the water bending fundamental.

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

Energetic and structural control of polyspecificity in a multidrug transporter

Multidrug efflux pumps are dynamic molecular machines that drive antibiotic resistance by harnessing ion gradients to export chemically diverse substrates. Despite their clinical importance, the molecular principles underlying multidrug promiscuity and energy efficiency remain poorly understood. Using multiparametric deep mutational scanning across eight substrates and two energy conditions, we deconvolute the contributions of substrate recognition, energetic coupling, and protein stability, providing an integrated, high-resolution view of multidrug transport. We find that substrate specificity arises from a distributed network of residues extending beyond the binding site, with mutations that reshape binding, coupling, conformational flexibility, and membrane interactions. Further, we apply a pH-based selection scheme to measure the effect of mutation on pH-dependent transport efficiency. By integrating these data, we reveal a fundamental relationship between efficiency and promiscuity: Highly efficient variants exhibit broad substrate profiles, while inefficient variants are narrower. In conclusion, these findings establish a direct link between energy coupling and polyspecificity, uncovering the biochemical logic underlying multidrug transport.

Biological Sciences↗
DOE OSTI2025

Systematic characterization of unknown compounds via dimensionality reduction of time series

Analysis of ambient aerosols provides valuable insight into particle sources and formation chemistry. However, due to the complexity of atmospheric data and the dynamic nature of aerosol composition, a substantial fraction of data often become discarded by conventional analysis methods. Furthermore, a large fraction of chemical species within those data are unidentifiable due to a lack of matching spectral information, resulting in suboptimal characterization of chemical composition. Previous work has demonstrated techniques for cataloging analytes in a chromatographic dataset by deconvolution of mass spectra, but integration of these analytes throughout a large dataset remains time consuming. Here, we present a method to automatically identify an ion for quantitation for single-ion chromatogram based peak fitting and integration, enabling comprehensive integration of analytes with minimal user interaction. The resulting time series are clustered with a machine-learning based dimensionality reduction technique to systematically investigate the underlying characteristics of the categorized analytes and gain new insights into the chemical composition and physicochemical properties of the unidentifiable analytes. We apply these methods to existing atmospheric datasets collected in Manacapuru, Brazil during the GoAmazon2014/5 campaign to identify new analytes and interpret their variability and transformations in the atmosphere. The analysis results generate 408 time series from cataloged analytes of interest, and the clustering of those time series with spherical k-means results in 8 distinct clusters. We find the analytes form clusters based on their distinct physicochemical properties, demonstrating the method’s ability to systematically identify and selectively filter contaminants and instrumental analytes and characterize the unidentifiable analytes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Spectro-Microscopic Analysis of Soot Particle Composition and Source Attribution

Ambient soot particles significantly impact Earth’s radiative balance, human health, and atmospheric visibility. Their microstructural properties depend on formation and aging mechanisms, which vary by emission source and atmospheric processes. Hence, accurately identifying sources of soot enhances our understanding of their physicochemical properties and atmospheric implications. This study used a multi-modal approach to characterize and attribute sources of submicron soot particles collected in Israel during new particle formation events, biomass burning episodes, and background atmospheric conditions. Synchrotron-based X-ray microscopy was used to map soot (elemental carbon), organic carbon, and inorganic species. Implemented atomic force microscopy showed highly diverse phase states, with soot consistently exhibiting a solid-like phase. Automated µ-Raman analysis was subsequently performed on ~690 particles, identifying three soot classes based on spectral features corresponding to the "Defect" (D) and "Graphite" (G) bands of soot. We applied two-peak and five-peak fitting approaches to deconvolute the “Defect” peaks (D1, D2, D3, and D4) and G band from average Raman, revealing varying degrees of graphitic order. The degree of graphitic order was determined from metrics such as the D3 peak area, often observed when soot was internally mixed with organic material. Raman spectral features, along with temporal variations in particle classes contributions, suggest that Particle Type 1 corresponds to traffic related soot and Particle Type 2 to less graphitic soot from biomass burning, while Particle Type 3 is associated with more heterogeneous particulate representative of soot-OC mixtures emitted during new particle formation and biomass burning episodes.

Rivera-Adorno, Felipe (ORCID:0000000273557999)↗
DOE OSTI2025

Analysis of the density field around a supersonic conical projectile using quantitative schlieren

Quantitative schlieren imaging is a flow measurement technique that is capable of measuring density fields throughout refractive flowfields. The technique was applied here to measure the density field surrounding supersonic conical projectiles in free flight. Shock waves attached to a supersonic conical projectile offer a simple geometry with the well-established Taylor–Maccoll analytical flow solution to which these experimental measurements were compared. The schlieren images recorded a projection of the index of refraction field surrounding the 10° half-angle cones which was converted to density first through an Abel inversion and then the Gladstone–Dale law. Three Abel inversion methods—two-point, three-point, and arbitrary ray axisymmetric projection (ARAP)—were applied to deconvolute the three-dimensional flow within the constrained axisymmetric flow field. The resulting reconstructed density profiles were compared to the Taylor–Maccoll solution, parameterized by cone geometry and Mach number. The experimental density fields demonstrated strong agreement with the theoretical profiles. Experimental consistency was confirmed across various projectile speeds, demonstrating quantitative schlieren’s capability to accurately reconstruct the density of the flow field, even within the resolution constraints imposed by high-speed imaging. In conclusion, an assessment of experimental uncertainties in the density reconstruction was performed.

Abel Inversion↗
DOE OSTI2026

Neural posterior unfolding

Differential cross section measurements are the currency of scientific exchange in particle and nuclear physics. A key challenge for these analyses is the correction for detector distortions, known as deconvolution or unfolding. Binned unfolding of cross section measurements traditionally rely on the regularized inversion of the response matrix that represents the detector response, mapping pre-detector (`particle level') observables to post-detector (`detector level') observables. In this paper we introduce Neural Posterior Unfolding, a modern, Bayesian approach that leverages normalizing flows for unfolding. By using normalizing flows for neural posterior estimation, NPU offers several key advantages including implicit regularization through the neural network architecture, fast amortized inference that eliminates the need for repeated retraining, and direct access to the full uncertainty in the unfolded result. In addition to introducing NPU, we implement a classical Bayesian unfolding method called Fully Bayesian Unfolding (FBU) in modern Python so it can also be studied. These tools are validated on simple Gaussian examples and then tested on simulated jet substructure examples from the Large Hadron Collider (LHC). We find that the Bayesian methods are effective and worth additional development to be analysis ready for cross section measurements at the LHC and beyond.

Analysis and statistical methods↗
DOE OSTI2026

Experimental considerations and applications for time-resolved impedance on silicon-anode battery systems

Dynamic electrochemical impedance spectroscopy (dEIS) utilizes a superimposed multi-sinusoidal waveform and enables temporally resolved investigations on various electrochemical processes; however, the signal-to-noise ratio must be maximized while retaining linearity and stationarity within the system. In the present work, we probe the impact of the waveform’s total amplitude as well as the waveform and phase profiles. The equal amplitude multi-sinusoidal waveform with 35 mV total amplitude (<1 mV per frequency) and random phase profile exhibits the lowest impedance noise. This input signal is sufficient in avoiding the high frequency signal attenuation from the potentiostat’s low-pass filter. Additionally, we demonstrate the optimized dEIS waveform’s utility in investigating surface passivation within thin-film and composite silicon (Si) anodes. Within a two-electrode Si-lithium metal coin cell, the charge transfer resistance (RCT) associated with alloying kinetics dominates the overall impedance. RCT increases with state of charge indicating a kinetic bottleneck at higher lithiation states. To explore this further, we utilize a three-electrode Si-LiNi0.8Mn0.1Co0.1O2 pouch cell to deconvolute the Si impedance contributions. The evolution of the solid electrolyte interphase (SEI) and charge transfer resistances correlate to specific Li–Si alloy phases. We attribute this to the influence of Si particle volume expansion on SEI instabilities and a kinetic bottleneck at higher lithiation states.

Lam, Steven [ORNL]↗
DOE OSTI2024

String-based parametrization of nucleon GPDs at any skewness: A comparison to lattice QCD

We introduce a string-based parametrization for nucleon quark and gluon generalized parton distributions (GPDs) valid at all skewness values. The conformal moments of the GPDs are expressed as sums of the spin-j nucleon A-form factor and the skewness-dependent spin-j nucleon D-form factor. This representation, which fulfills the polynomiality condition (due to Lorentz invariance) and does not rely on model-specific assumptions, is derived from t-channel string exchanges in anti-de Sitter spaces. The spin-j nucleon D-form factor is closely related to the spin-j nucleon A-form factor. We use the Mellin moments from empirical parton distributions to model the spin-j nucleon A-form factors. Using only five Regge slope parameters, fixed from the electromagnetic and gravitational form factors, our string-based parametrization generates accurate singlet, nonsinglet, isovector, and flavor-separated nucleon quark GPDs, along with symmetric nucleon gluon GPDs from their Mellin-Barnes integral representations. Our isovector nucleon quark GPD is in agreement with existing lattice data. Our string-based parametrization should facilitate the empirical extraction and global analysis of nucleon GPDs in exclusive processes, bypassing the deconvolution challenge.

Electron-ion collisions↗
DOE OSTI2024

Parametrization of Generalized Parton Distributions from 𝑡-Channel String Exchange in AdS Spaces

We introduce a string-based parametrization for nucleon quark and gluon generalized parton distributions (GPDs) that is valid for all skewness. Our approach leverages conformal moments, representing them as the sum of spin-𝑗 nucleon 𝐴-form factor and skewness-dependent spin-𝑗 nucleon 𝐷-form factor, derived from 𝑡-channel string exchange in AdS spaces consistent with Lorentz invariance and unitarity. This model-independent framework, satisfying the polynomiality condition due to Lorentz invariance, uses Mellin moments from empirical data to estimate these form factors. With just five Regge slope parameters, our method accurately produces various nucleon quark GPD types and symmetric nucleon gluon GPDs through pertinent Mellin-Barnes integrals. Our isovector nucleon quark GPD is in agreement with existing lattice data, promising to improve the empirical extraction and global analysis of nucleon GPDs in exclusive processes, by avoiding the deconvolution problem at any skewness, for the first time.

QCD phenomenology↗
DOE OSTI2024

Three Photon Excited Image Scanning Microscopy for in-Depth Super-Resolution Studies of Biological Samples

Multiphoton laser scanning microscopy is a powerful tool for deep imaging of thick biological samples. Image scanning microscopy (ISM) has demonstrated significant improvements in the signal-to-noise ratio in confocal laser scanning microscopy, while at the same time improving upon the effectively attainable resolution. Two-photon excitation (2PE), combined with ISM, has been shown to allow for deep tissue imaging with enhanced resolution compared to 2PE microscopy. Three-photon excitation (3PE) has enabled record imaging depth and contrast for multiphoton imaging, due to the superior suppression of out-of-focus signal generation. In this paper, we demonstrate super-resolution 3PE ISM. This is achieved using a single-photon avalanche detector array, and 1040-nm pulses for 3PE of blue fluorescence. This method enables subdiffraction limited resolution imaging of biological samples stained with blue fluorescent markers, such as mouse myocardial and spinal cord tissues stained with 4 ′ , 6 -diamidino-2-phenylindole. Deconvolution improves the resolving power further and allows for imaging with better than λ / 8 resolution with respect to the 3PE wavelength λ . With the ISM pixel reassignment procedure, we demonstrate a resolution enhancement of ∼ 1.6 laterally, compared to the resolution attained using a photomultiplier tube in a non-descanned detection arrangement, and a factor of ∼ 1.8 enhancement in axial resolution. The experimentally measured three-dimensional point spread function volume is shrunk ∼ 4.4 -fold, which is close to the theoretically expected enhancement. Published by the American Physical Society 2024

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Surrogate Model for Distribution Networks Influenced by Weather

Here, we propose a method for generating reduced representations of time series and for constructing low dimensional surrogate models for time dependent calculations of power and voltage in distribution networks. We employ Fourier polynomials. The surrogate model strategy is aimed at reducing the computational cost of time dependent simulations, albeit, at the expense of fidelity. The reduced representation is achieved by identifying a small and most consequential subset of degrees of freedom. In power and voltage distribution networks dynamics that are heavily influenced by strong cyclic weather events, e.g., the hourly, diurnal and seasonal cycles, the weather/climate time series spectrum exposes these most energetic components. Once the degrees of freedom are identified their amplitudes are optimized using training data. The key challenge in using spectral methods in power network surrogates is addressing the computation of quotients. For this we propose a numerically-stable deconvolution strategy.

Weather events↗
DOE OSTI2026

Deciphering competing elementary steps to correlate electrocatalyst chemical state with activity

The overpotential in multielectron transfer heterogeneous electrocatalysis fundamentally arises from thermodynamic and kinetic disparities among elementary steps; however, deciphering coupled and competing steps has long remained a challenge. Here, we establish an electrochemical deconvolution paradigm based on key processes in electrocatalytic reactions, such as charge accumulation, electron/proton transfer, and intermediate evolution, to resolve competing elementary steps. Taking the oxygen evolution reaction as a prototypical reaction, we design a model catalyst featuring a precise isolated cation-anion vacancy pair and track the previously elusive electrochemical behavior of lattice oxygen by disentangling interference from adsorbed oxygen intermediates. Mechanistically, the lattice oxygen oxidation pathway originates from the spontaneous, nonelectrochemical deprotonation of replenished water molecules coordinated to unsaturated cation sites. Alternating current techniques further reveal that although lattice oxygen oxidation requires a higher potential than metal oxidation, it exhibits faster kinetics, providing insight into its superior catalytic activity. These findings establish a direct experimental correlation between the initial chemical state and the catalytic activity and prove surface-confined lattice oxygen cycling. Furthermore, expanding conventional potential-current analysis into a multidimensional framework enables disentanglement of thermodynamic and kinetic contributions of key elementary steps, thereby guiding the rational optimization of various complex multielectron transfer reactions.

OER↗
DOE OSTI2025

Proton internal pressure from deeply virtual Compton scattering on collider kinematics

Abstract The unique experimental connection to the QCD energy–momentum tensor offered by generalised parton distributions has been strongly highlighted in the past few years with attempts to extract the pressure and shear forces distributions within the nucleon. If, in principle, this can be performed in a model independent way from experimental data, in practice, the current limited precision and kinematic coverage make such an extraction very challenging. Moreover, the limitation to a leading-order description in the strong coupling of the data has provided only an indirect and weakly sensitive access to gluon degrees of freedom, solely through their mixing to quarks via evolution. In this paper we address this issue by providing a next-to-leading order formalism allowing a reanalysis of global fits with genuine gluonic degrees of freedom. In addition, we provide an estimate of the reduction in uncertainty that could stem from the extended kinematic range relevant for the future Electron Ion Collider. Finally, we stress the connection between the analysis of the dispersion relation in terms of generalised parton distributions and the deconvolution problem.

Dutrieux, H. (ORCID:0000000183344885)↗
DOE OSTI2026

Design Trade-Offs in Composite Fuel Cell Membranes: Effects of Reinforcement and Chemical Additives

Perfluorosulfonic acid (PFSA) membranes are critical components in proton exchange membrane fuel cells, where performance depends on balancing ionic conductivity, mechanical durability, and chemical stability. This study characterizes a composite membrane (NC700) featuring PFSA-impregnated expanded polytetrafluoroethylene (ePTFE) reinforcement and cerium-based radical scavengers, benchmarked against unreinforced NR211. Complementary techniques, including electron microscopy, X-ray scattering, infrared spectroscopy, thermogravimetric analysis, and dynamic mechanical analysis, identify the structural and compositional strategies employed in NC700. Water sorption isotherms reveal lower water uptake for NC700 across all conditions, attributed to reinforcement and cerium incorporation. Reinforcement reduces in-plane swelling from 11% to 2.1% at 90% RH, confirming strong swelling anisotropy, while maintaining mechanical properties at elevated temperatures. While the ionic conductivity of NC700 is approximately 10% lower than that of NR211, the reduced thickness yields a 40% decrease in calculated area-specific resistance, suggesting the composite architecture can favorably shift the conductivity-stability trade-off. The composite structure also reduces gas permeability, indicating potential for improved separator function alongside favorable transport properties. Systematic deconvolution of reinforcement and additive contributions shows that conductivity losses from cerium incorporation are largely offset by gains from the lower equivalent-weight polymer, providing quantitative relationships that may guide composite membrane design for fuel cells and other electrochemical applications.

25 ENERGY STORAGE↗