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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

Direct Visualization of Charge Migration in Bilayer Tantalum Oxide Films by Multimodal Imaging

Inspired by biological neuromorphic computing, artificial neural networks based on crossbar arrays of bilayer tantalum oxide memristors have shown to be promising alternatives to conventional complementary metal-oxide-semiconductor (CMOS) architectures. In order to understand the driving mechanism in these oxide systems, tantalum oxide films are resistively switched by conductive atomic force microscopy (C-AFM), and subsequently imaged by kelvin probe force microscopy (KPFM) and spatially resolved time-of-flight secondary ion mass spectrometry (ToF-SIMS). These workflows enable induction and analysis of the resistive switching mechanism as well as control over the resistively switched region of the film. In this work it is shown that the resistive switching mechanism is driven by both current and electric field effects. Reversible oxygen motion is enabled by applying low (<1 V) electric fields, while high electric fields generate irreversible breakdown of the material (>1 V). Fully understanding oxygen motion and electrical effects in bilayer oxide memristor systems is a fundamental step toward the adoption of memristors as a neuromorphic computing technology.

36 MATERIALS SCIENCE↗

Revisiting the Role of Conductivity and Polarity of Host Materials for Long-Life Lithium–Sulfur Battery

Despite their high theoretical energy density and low cost, lithium-sulfur batteries (LSBs) suffer from poor cycle life and low energy efficiency owing to the polysulfides shuttle and the electronic insulating nature of sulfur. Conductivity and polarity are two critical parameters for the search of optimal sulfur host materials. However, their role in immobilizing polysulfides and enhancing redox kinetics for long-life LSBs are not fully understood. In this work we have conducted an evaluation on the role of polarity over conductivity by using a polar but nonconductive platelet ordered mesoporous silica (pOMS) and its replica platelet ordered mesoporous carbon (pOMC), which is conductive but nonpolar. It is found that the polar pOMS/S cathode with a sulfur mass fraction of 80 wt% demonstrates outstanding long-term cycle stability for 2000 cycles even at a high current density of 2C. Furthermore, the pOMS/S cathode with a high sulfur loading of 6.5 mg cm -2 illustrates high areal and volumetric capacities with high capacity retention. Complementary physical and electrochemical probes clearly show that surface polarity and structure are more dominant factors for sulfur utilization efficiency and long-life, while the conductivity can be compensated by the conductive agent involved as a required electrode material during electrode preparation. The present findings shed new light on the design principles of sulfur hosts towards long-life and highly efficient LSBs.

25 ENERGY STORAGE↗

New Cost-Effective Halide Solid Electrolytes for All-Solid-State Batteries: Mechanochemically Prepared Fe 3+ -Substituted Li 2 ZrCl 6

Owing to the combined advantages of sulfide and oxide solid electrolytes (SEs), that is, mechanical sinterability and excellent (electro)chemical stability, recently emerging halide SEs such as Li 3 YCl 6 are considered to be a game changer for the development of all-solid-state batteries. However, the use of expensive central metals hinders their practical applicability. In this study, a new halide superionic conductors are reported that are free of rare-earth metals: hexagonal close-packed (hcp) Li 2 ZrCl 6 and Fe 3+ -substituted Li 2 ZrCl 6 , derived via a mechanochemical method. Conventional heat treatment yields cubic close-packed monoclinic Li 2 ZrCl 6 with a low Li + conductivity of 5.7 × 10 –6 S cm –1 at 30 °C. In contrast, hcp Li 2 ZrCl 6 with a high Li + conductivity of 4.0 × 10 –4 S cm –1 is derived via ball-milling. More importantly, the aliovalent substitution of Li 2 ZrCl 6 with Fe 3+ , which is probed by complementary analyses using X-ray diffraction, pair distribution function, X-ray absorption spectroscopy, and Raman spectroscopy measurements, drastically enhances the Li + conductivity up to ≈1 mS cm –1 for Li 2.25 Zr 0.75 Fe 0.25 Cl 6 . The superior interfacial stability when using Li 2+ x Zr 1– x Fe x Cl 6 , as compared to that when using conventional Li 6 PS 5 Cl, is proved. Furthermore, an excellent electrochemical performance of the all-solid-state batteries is achieved via the combination of Li 2 ZrCl 6 and single-crystalline LiNi 0.88 Co 0.11 Al 0.01 O 2 .

25 ENERGY STORAGE↗

Triggering Anionic Redox Activity in Li 3 NbS 4 Through Cationic Disordering or Substitution

Extensive utilization of Li-ion batteries for varieties of applications necessitates ceaseless improvements of electrode materials for achieving higher energy density. Towards this goal, Li-rich layered oxides exhibiting high capacity due to cumulated cationic and anionic redox activities are under study for nearly a decade. Still, several unanswered questions remain with respect to these Li-driven anionic redox reactions in terms of the activation process and long-term consequences upon cycling. Here, the Li-rich Li 3 NbS 4 phase is focused, and synthesized as two different polymorphs, namely ordered and disordered phases. From analyses of their chemical and electrochemical properties, a crystal-electronic structure relationship is unraveled that triggers the anionic redox activity in these compounds. Moreover, through complementary theoretical calculations, the capability of cationic disorder to trigger anionic redox activity via the hybridization of cationic and non-bonding anionic energy levels is shown. This finding is further supported by the appearance of anionic redox activity by introducing the disorder through cationic substitution. Altogether, the insights derived here can help in designing new anionic redox materials with optimum performances for practical applications.

25 ENERGY STORAGE↗

In‐Silico Device Performance Prediction of Cosensitizer Dye Pairs for Dye‐Sensitized Solar Cells

Abstract Endeavors in the field of dye‐sensitized solar cells (DSCs) have shown great promise when adopting a data‐driven approach to materials discovery, such as successful molecular‐scale predictions of light‐harvesting chromophores. However, predictions of DSC dyes would become much more sophisticated if a molecular‐to‐macroscopic DSC device prediction methodology existed. Thereby, a fully computational pipeline is presented that predicts device‐performance parameters of DSCs which contain varying dye combinations. Optimal pairing of complementary dyes is identified via a data‐driven workflow that affords cosensitized DSCs with maximum power‐conversion efficiencies. Six high‐performing DSC dyes are paired with partner dyes that are screened from a database of 8488 compounds using sequential heuristic filters. Existing models that predict short‐circuit‐current density ( J SC ) and open‐circuit voltage ( V OC ) parameters are adapted to predict singly sensitized and cosensitized DSC performance. The predictions for J sc values of singly sensitized devices match experimental literature values with comparable accuracy to more computationally costly methods. Five out of six dye pairings are predicted to have greater J SC values when cosensitized compared to their corresponding singly sensitized devices, including two pairs that show strong J sc boosts of +13% and +12% when cosensitized. Thus, the prospect of an entirely in‐silico prediction pipeline for DSC performance that can be used to realize the fully automated design of optimized cosensitized DSCs is demonstrated.

14 SOLAR ENERGY↗

Iridium Oxide Coordinatively Unsaturated Active Sites Govern the Electrocatalytic Oxidation of Water

A special membrane electrode assembly to measure operando X-ray absorption spectra and resonant photoemission spectra of mesoporous templated iridium oxide films is used. These films are calcined to different temperatures to mediate the catalyst activity. By combining operando resonant photoemission measurements of different films with ab initio simulations these are able to unambiguously distinguish µ 2 -O (bridging oxygen) and µ 1 -O (terminal oxygen) in the near-surface regions of the catalysts. The intrinsic activity of iridium oxide scales with the formation of µ1-O (terminal oxygen) is found. Importantly, it is shown that the peroxo species do not accumulate under reaction conditions. Rather, the formation of µ 1 -O species, which are active in O-O bond formation during the OER, is the most oxidized oxygen species observed, which is consistent with an O-O rate-limiting step. Thus, the oxygen species taking part in the electrochemical oxidation of water on iridium electrodes are more involved and complex than previously stated. This result highlights the importance of employing theory together with true and complementary operando measurements capable of probing different aspects of catalysts surfaces during operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Neutron Scattering in Sodium-Ion Battery Research: Progress and Prospects

Sodium-ion batteries have attracted renewed interest in recent years and are widely studied as a complementary power source to Li-ion batteries for large-scale stationary energy storage and small electric vehicles. Compared with Li-ion batteries, Na-ion batteries offer several advantages, including elemental abundance, lower cost, improved safety, and better low-temperature performance. An in-depth understanding of Na-ion batteries across multiple length and time scales has further accelerated the rapid development of this technology. Among the various advanced characterization techniques used to study Na-ion batteries, neutron scattering has gained significant traction in recent years. It has become a powerful and versatile tool for probing structure, morphology, and sodium-ion dynamics over a wide range of length and time scales. In this article, we will briefly review the development of neutron scattering technology and highlight recent advances in applying neutron-based techniques—including neutron diffraction, total scattering, small-angle scattering, quasi-elastic/inelastic scattering, and neutron imaging—to Na-ion battery materials. We also provide perspectives on future technique developments, particularly in the realm of in situ and operando neutron scattering characterization, and discuss how these approaches could further enhance our understanding of Na-ion battery systems.

Liu, Jue [ORNL] (ORCID:000000024453910X)↗

Toward Intelligent Multimodal Holography for Real-Time Chemical Imaging of Dynamic Ion Separation

Molecular-level visualization of ion transport and separation dynamics in complex environments is crucial for advancing energy systems, water purification, and critical materials recovery. Achieving this requires imaging platforms that combine structural sensitivity, chemical specificity, and real-time operation. Digital off-axis holography (DOAH) provides high-throughput, label-free quantitative phase imaging but inherently lacks chemical selectivity. Integrating DOAH with complementary spectroscopic channels such as fluorescence or hyperspectral imaging introduces the needed molecular specificity, while also creating challenges in multimodal data fusion, synchronization, and computational throughput. Artificial intelligence offers a powerful route to address these limitations by uniting physics-based reconstruction with data-driven interpretation. In this Perspective, we outline a framework for intelligent multimodal holography and demonstrate its potential using a preliminary AI-driven test case. Raw DOAH holograms of lanthanide solutions subjected to magnetic field gradients were analyzed using multi-agent AI workflows that autonomously selected reconstruction tools, extracted NMF components, and generated scientific claims consistent with true paramagnetic and diamagnetic behavior. This demonstration shows how AI-enabled reasoning can deliver real-time chemical–structural interpretation directly from raw holograms. Together, these advances define a path toward adaptive, intelligent holography platforms capable of supporting in situ chemical separations, dynamic ion transport analysis, and next-generation interfacial science.

Ricchiuti, Giovanna↗

A Roadmap for Reaching the Potential of Brain-Derived Computing

Neuromorphic computing is a critical future technology for the computing industry, but it has yet to achieve its promise and has struggled to establish a cohesive research community. A large part of the challenge is that full realization of the potential of brain inspiration requires advances in both device hardware, computing architectures, and algorithms. This simultaneous development across technology scales is unprecedented in the computing field. This article presents a strategy, framed by market and policy pressures, for moving past these current technological and cultural hurdles to realize its full impact across technology. Achieving the full potential of brain-derived algorithms as well as post-complementary metal-oxide-semiconductor (CMOS) scaling neuromorphic hardware requires appropriately balancing the near-term opportunities of deep learning applications with the long-term potential of less understood opportunities in neural computing.

97 MATHEMATICS AND COMPUTING↗

Time‐Lapse Image Classification Using a Diffractive Neural Network

Diffractive deep neural networks (D 2 NNs), comprised of spatially engineered passive surfaces, collectively process optical input information at the speed of light propagation through a thin diffractive volume, without any external computing power. Diffractive networks were demonstrated to achieve all‐optical object classification and perform universal linear transformations. Herein, a “time‐lapse” image classification scheme using a diffractive network is demonstrated for the first time, significantly advancing its classification accuracy and generalization performance on complex input objects by using the lateral movements of the input objects and/or the diffractive network, relative to each other. In a different context, such relative movements of the objects and/or the camera are routinely being used for image super‐resolution applications; inspired by their success, a time‐lapse diffractive network is designed to benefit from the complementary information content created by controlled or random lateral shifts. The design space and performance limits of time‐lapse diffractive networks are numerically explored, revealing a blind testing accuracy of 62.03% on the optical classification of objects from the CIFAR‐10 dataset. This constitutes the highest inference accuracy achieved so far using a single diffractive network on the CIFAR‐10 dataset. Time‐lapse diffractive networks will be broadly useful for the spatiotemporal analysis of input signals using all‐optical processors.

36 MATERIALS SCIENCE↗

Cryogenic Correlative Single‐Particle Photoluminescence Spectroscopy and Electron Tomography for Investigation of Nanomaterials

Abstract Cryogenic single‐particle photoluminescence (PL) spectroscopy has been used with great success to directly observe the heterogeneous photophysical states present in a population of luminescent particles. Cryogenic electron tomography provides complementary nanometer scale structural information to PL spectroscopy, but the two techniques have not been correlated due to technical challenges. Here, we present a method for correlating single‐particle information from these two powerful microscopy modalities. We simultaneously observe PL brightness, emission spectrum, and in‐plane excitation dipole orientation of CdSSe/ZnS quantum dots suspended in vitreous ice. Stable and fluctuating emitters were observed, as well as a surprising splitting of the PL spectrum into two bands with an average energy separation of 80 meV. In some cases, the onset of the splitting corresponded to changes in the in‐plane excitation dipole orientation. These dynamics were assigned to structures of individual quantum dots and the excitation dipoles were visualized in the context of structural features.

Dahlberg, Peter D.↗

Mass Spectrometry Imaging of Bio‐oligomer Polydispersity in Plant Tissues by Laser Desorption Ionization from Silicon Nanopost Arrays

Abstract Mass spectrometry imaging (MSI) enables simultaneous spatial mapping for diverse molecules in biological tissues. Matrix‐assisted laser desorption ionization (MALDI) mass spectrometry (MS) has been a mainstream MSI method for a wide range of biomolecules. However, MALDI‐MSI of biological homopolymers used for energy storage and molecular feedstock is limited by, e.g., preferential ionization for certain molecular classes. Matrix‐free nanophotonic ionization from silicon nanopost arrays (NAPAs) is an emerging laser desorption ionization (LDI) platform with ultra‐trace sensitivity and molecular imaging capabilities. Here, we show complementary analysis and MSI of polyhydroxybutyric acid (PHB), polyglutamic acid (PGA), and polysaccharide oligomers in soybean root nodule sections by NAPA‐LDI and MALDI. For PHB, number and weight average molar mass, polydispersity, and oligomer size distributions across the tissue section and in regions of interest were characterized by NAPA‐LDI‐MSI.

Samarah, Laith Z.↗

Low‐Density 2D Superlattices Assembled via Directional DNA Bonding

Abstract It is critical to assemble nanoparticles (NPs) into superlattices with controlled symmetries and spacings on substrates for metamaterials applications, where such structural parameters dictate their properties. Here, we use DNA to assemble anisotropic NPs of three shapes—cubes, octahedra, and rhombic dodecahedra—on substrates and investigate their thermally induced reorganization into two‐dimensional (2D) crystalline films. We report two new low‐density 2D structures, including a honeycomb lattice based on octahedral NPs. The low‐density lattices favored here are not usually seen when particles are crystallized via other bottom‐up assembly techniques. Furthermore, we show that, consistent with the complementary contact model, a primary driving force for crystallization is the formation of directional, face‐to‐face DNA bonds between neighboring NPs and between NPs and the substrate. Our results can be used to deliberately prepare crystalline NP films with novel morphologies.

Miao, Ziyi↗

Supported Lanthanum Borohydride Catalyzes CH Borylation Inside Zeolite Micropores

Abstract The zeolite‐supported lanthanide La(BH 4 ) x ‐HY 30 catalyzes C−H borylation of benzene with pinacolborane (HBpin), providing a complementary approach to precious, late transition metal‐catalyzed borylations. The reactive catalytic species are generated from La grafted at the Brønsted acid sites (BAS) in micropores of the zeolite, whereas silanoate‐ and aluminoate‐grafted sites are inactive under the reaction conditions. During typical catalytic borylations, conversion to phenyl pinacolborane (PhBpin) is zero‐order in HBpin concentration. A turnover number (TON) of 167 is accessed by capping external silanols, selectively grafting at BAS sites, and adding HBpin slowly to the reaction.

Li, Yuting↗

Formation of Organic Acids and Carbonyl Compounds in n ‐Butane Oxidation via γ‐Ketohydroperoxide Decomposition

Abstract A crucial chain‐branching step in autoignition is the decomposition of ketohydroperoxides (KHP) to form an oxy radical and OH. Other pathways compete with chain‐branching, such as “Korcek” dissociation of γ‐KHP to a carbonyl and an acid. Here we characterize the formation of a γ‐KHP and its decomposition to formic acid+acetone products from observations of n ‐butane oxidation in two complementary experiments. In jet‐stirred reactor measurements, KHP is observed above 590 K. The KHP concentration decreases with increasing temperature, whereas formic acid and acetone products increase. Observation of characteristic isotopologs acetone‐ d 3 and formic acid‐ d 0 in the oxidation of CH 3 CD 2 CD 2 CH 3 is consistent with a Korcek mechanism. In laser‐initiated oxidation experiments of n ‐butane, formic acid and acetone are produced on the timescale of KHP removal. Modelling the time‐resolved production of formic acid provides an estimated upper limit of 2 s −1 for the rate coefficient of KHP decomposition to formic acid+acetone.

Popolan‐Vaida, Denisia M.↗

pH‐ and Redox‐Responsive Pickering Emulsions Based on Cellulose Nanocrystal Surfactants

Abstract Nanoparticle surfactants (NPSs), formed by using dynamic interactions between nanoparticles and complementary ligands at the liquid‐liquid interface, have emerged as “smart emulsifiers” with attributes of high emulsification efficiency, long‐term stability, and on‐demand emulsification/demulsification capabilities. However, only pH‐responsiveness can be adopted for the assembly of reported NPSs formed by electrostatic interactions. Here, we propose an alternative design strategy, by taking advantage of the ferrocenium (Fc + ) sulfate ion pair, to develop a new type of cellulose nanocrystal (CNC) surfactant. The Fc + groups are sensitive to pH, redox reagents and voltage, imparting the CNC surfactants and derived Pickering emulsions with multi‐stimuli‐responsiveness, and showing promising applications in controllable delivery, release, and biphasic biocatalysis.

Yang, Yang↗

Influence of Potassium Metal‐Support Interactions on Dendrite Growth

Abstract Combined synchrotron X‐ray nanotomography imaging, cryogenic electron microscopy (cryo‐EM) and modeling elucidate how potassium (K) metal‐support energetics influence electrodeposit microstructure. Three model supports are employed: O‐functionalized carbon cloth (potassiophilic, fully‐wetted), non‐functionalized cloth and Cu foil (potassiophobic, nonwetted). Nanotomography and focused ion beam (cryo‐FIB) cross‐sections yield complementary three‐dimensional (3D) maps of cycled electrodeposits. Electrodeposit on potassiophobic support is a triphasic sponge, with fibrous dendrites covered by solid electrolyte interphase (SEI) and interspersed with nanopores (sub‐10 nm to 100 nm scale). Lage cracks and voids are also a key feature. On potassiophilic support, the deposit is dense and pore‐free, with uniform surface and SEI morphology. Mesoscale modeling captures the critical role of substrate‐metal interaction on K metal film nucleation and growth, as well as the associated stress state.

Liu, Pengcheng↗

Migration and Precipitation of Platinum in Anion‐Exchange Membrane Fuel Cells

Abstract Despite the recent progress in increasing the power generation of Anion‐exchange membrane fuel cells (AEMFCs), their durability is still far lower than that of Proton exchange membrane fuel cells (PEMFCs). Using the complementary techniques of X‐ray micro‐computed tomography (CT), Scanning Electron Microscopy (SEM) and Energy Dispersive X‐ray (EDX) spectroscopy, we have identified Pt ion migration as an important factor to explain the decay in performance of AEMFCs. In alkaline media Pt +2 ions are easily formed which then either undergo dissolution into the carbon support or migrate to the membrane. In contrast to PEMFCs, where hydrogen cross over reduces the ions forming a vertical “Pt line” within the membrane, the ions in the AEM are trapped by charged groups within the membrane, leading to disintegration of the membrane and failure. Diffusion of the metal components is still observed when the Pt/C of the cathode is substituted with a FeCo−N−C catalyst, but in this case the Fe and Co ions are not trapped within the membrane, but rather migrate into the anode, thereby increasing the stability of the membrane.

Raut, Aniket↗