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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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34 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Probing Dynamic Phase Changes in Electrochemical Systems with Cryogenic and in Situ Analytical Electron Microscopy (Final Technical Report)

In this project, we focus on the advancement of our newly developed, unique in situ and cryogenic analytical electron microscopy (AEM) techniques and the development of additional high-end capabilities to quantitatively elucidate the mechanisms of resistive state changes in solid-state electrochemical materials for non-volatile, neuromorphic memory. The objectives of the proposed research are (1) to characterize and elucidate the mechanisms by which electronic state changes occur in various solid-state devices to build guiding principles for electrochemically activated smart materials; (2) to advance our understanding of such mechanisms by coupling cryogenic and in situ techniques to control kinetics of the observed mechanisms while mitigating probe-induced damage; and (3) to utilize additional advanced techniques including electron-beam induced current and quantum mechanical simulations in order to identify the underlying fundamental science of such processes, including roles of defect formation and its effect on phase nucleation, as well as dynamics of these processes in the electrochemical systems at the nanometer scale.

25 ENERGY STORAGE↗
DOE OSTI2026

Protonic nickelate device networks for spatiotemporal neuromorphic computing

Computation in biological neural circuits arises from the interplay of nonlinear temporal responses and spatially distributed dynamic network interactions. Replicating this richness in hardware has remained challenging, as most neuromorphic devices emulate only isolated neuron- or synapse-like functions. Here we introduce an integrated neuromorphic computing platform in which both nonlinear spatiotemporal processing and programmable memory are realized within a single perovskite nickelate material system. By engineering symmetric and asymmetric hydrogenated NdNiO 3 junction devices on the same wafer, we combine ultrafast, proton-mediated transient dynamics with stable multilevel resistance states. Networks of symmetric NdNiO 3 junctions exhibit emergent spatial interactions mediated by proton redistribution, while each node simultaneously provides short-term temporal memory, enabling nanosecond-scale operation with an energy cost of ~0.2 nJ per input. When interfaced with asymmetric output units serving as reconfigurable long-term weights, these networks allow both feature transformation and linear classification in the same material system. Leveraging these emergent interactions, the platform enables real-time pattern recognition and achieves high accuracy in spoken digit classification and early seizure detection, outperforming temporal-only or uncoupled architectures. These results position protonic nickelates as a compact, energy-efficient, CMOS-compatible platform that integrates processing and memory for scalable intelligent hardware.

Electrical and electronic engineering↗
DOE OSTI2025

Network analysis of memristive device circuits: dynamics, stability and correlations

Abstract Networks with memristive devices are a potential basis for the next generation of computing devices. They are also an important model system for basic science, from modeling nanoscale conductivity to providing insight into the information-processing of neurons. The resistance in a memristive device depends on the history of the applied bias and thus displays a type of memory. The interplay of this memory with the dynamic properties of the network can give rise to new behavior, offering many fascinating theoretical challenges. But methods to analyze general memristive circuits are not well described in the literature. In this paper we develop a general circuit analysis for networks that combine memristive devices alongside resistors, capacitors and inductors and under various types of control. We derive equations of motion for the memory parameters of these circuits and describe the conditions for which a network should display properties characteristic of a resonator system. For the case of a purely memresistive network, we derive Lyapunov functions, which can be used to study the stability of the network dynamics. Surprisingly, analysis of the Lyapunov functions show that these circuits do not always have a stable equilibrium in the case of nonlinear resistance and window functions. The Lyapunov function allows us to study circuit invariances, wherein different circuits give rise to similar equations of motion, which manifest through a gauge freedom and node permutations. Finally, we identify the relation between the graph Laplacian and the operators governing the dynamics of memristor networks operators, and we use these tools to study the correlations between distant memristive devices through the effective resistance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Hardenability and microstructural evolution of a precipitation strengthened Ni 50 Ti 21 Hf 25 Al 4 alloy

NiTi-based quaternary alloys are used in a variety of mechanical components, such as bearings, actuators, and dampers, owing to their good hardenability, wear resistance, and corrosion resistance. Additionally, one of the most notable characteristics of NiTi-based alloys is their shape memory effect and pseudoelastic properties. Connecting the macroscopic processing parameters employed in the design of new intermetallic alloys to the nanoscale structural characteristics dictating their behavior is crucial for improving their mechanical properties and expanding the spectrum of potential applications. Here, in this work, an arc melted Ni 50 Ti 21 Hf 25 Al 4 (at%) alloy was solution treated at 1050 °C followed by quenching and aging at 600 °C to investigate the effect of aging time on the microstructure and mechanical properties. Two types of nano-sized precipitates were observed and determined as face-centered orthorhombic H-phase (TiHf)Ni and L2 1 Heusler precipitates Ni 2 TiAl. The morphology and orientation of the H-phase were investigated using scanning and transmission electron microscopy (SEM and TEM), elucidating the coarsening kinetics and strengthening contribution of that phase to the intermetallic mechanical behavior. Following coarsening, the presence of Heusler nanoprecipitates was detected under overaged conditions through TEM imaging and nanobeam electron diffraction patterns. A peak hardness condition of 756 HV was achieved after 70 h of aging, indicating that the co-precipitation of H-phase and Heusler precipitates through a well-designed aging treatment can lead to optimal mechanical performance, thus elevating the alloy’s potential as a viable material for industrial applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Multifunctional electrochemical memory stabilized by phase coexistence

Our growing computing needs, especially in applications that heavily rely on artificial intelligence (AI), motivate a search for new components that could substantially augment the performance of general-purpose digital computers. Beyond ON/OFF switching, new components with linear multistate analog resistive tuning, nonlinear volatile switching, spiking, oscillatory, stochastic and other complex functionalities could enable highly efficient neuromorphic computing schemes for AI information processing. Compared to the extreme multifunctionality of biological neurons, realizing all the above characteristics in a single, scalable analog component remains a grand challenge. Here we investigate electrochemical gating combined with localized thermal activation to program and switch a single, vertically integrated and dimensionally scaled electrothermal chemical random access memory (ETCRAM) with a channel and reservoir composed of phase-separated vanadium oxide. Closely related to electrochemical RAM (ECRAM), ETCRAM uses an integrated gate-heater electrode to overcome kinetic barriers that help retain states at ambient temperatures. In addition to synapse-like stable and programmable analog resistance states arising from redox-tunable phase coexistence, a single component exhibits neuron-like nonlinear conductance switching with a tunable threshold and self-driven dynamics owing to the thermally driven metal-insulator phase transition in vanadium dioxide. More broadly, we demonstrate that electrochemically stabilized phase coexistence could unlock analog electronics with novel functionality, stability, reconfigurability, and scalability.

Oh, Sangheon [Sandia National Lab. (SNL-CA), Liver↗
DOE OSTI2026

Carbon doping in GeTe drives differences in local structure and properties

Advances in low-power, energy-efficient information storage and computing require understanding and controlling the atomic and nanoscale structures of functional materials, such as phase-change materials. Phase-change memory technology enables nonvolatile, low-power memory in devices by storing information through reversible changes in a phase-change material's atomic structure (i.e., transformations between amorphous and crystalline phases) that have corresponding changes in properties, including electronic resistivity and optical reflectivity. Here, we apply complementary X-ray absorption spectroscopy and X-ray pair distribution function analyses to experimentally identify the local- and medium-range atomic structure differences of GeTe and C-doped GeTe thin films. Upon controlled heating, composition- and temperature-dependent atomic structure evolution in GeTe and C-doped GeTe films shows differences in bonding behavior and local structure that directly influence crystallization onset temperature. We find that the introduction of C interrupts Ge–Ge bonds in amorphous GeTe, altering the as-deposited structure to be more similar to the distorted rocksalt structure of crystalline α–GeTe. The change alters the response of the amorphous atomic structure to heating and also lowers the crystallization onset temperature, from 230 °C in GeTe to 220 °C in the C-doped film. The combined insights from both X-ray techniques provide understanding of structural transformations that enables the development and optimization of next-generation memory and computing materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

CLPNets: Coupled Lie–Poisson neural networks for multi-part Hamiltonian systems with symmetries

To accurately compute data-based prediction of Hamiltonian systems, it is essential to utilize methods that preserve the structure of the equations over time. We consider a particularly challenging case of systems with interacting parts that do not reduce to pure momentum evolution. Such systems are essential in scientific computations, such as discretization of a continuum elastic rod, which can be viewed as the group of rotations and translations $SE(3)$. The evolution involves not only the momenta but also the relative positions and orientations of the particles. The presence of Lie group-valued elements, such as relative positions and orientations, poses a problem for applying previously derived methods for data-based computing. We develop a novel method of data-based computation and complete phase space learning of such systems. We follow the original framework of SympNets (Jin et al., 2020) and LPNets (Eldred et al., 2024), building the neural network from phase space mappings that preserve the Lie–Poisson structure. We derive a novel system of mappings that are built into neural networks describing the evolution of such systems. We call such networks Coupled Lie–Poisson Neural Networks, or CLPNets. We consider increasingly complex examples for the applications of CLPNets, starting with the rotation of two rigid bodies about a common axis, progressing to the free rotation of two rigid bodies, and finally to the evolution of two connected and interacting $SE(3)$ components, describing the discretization of an elastic rod into two elements. Our method preserves all Casimir invariants to machine precision, preserves energy to high accuracy, and shows good resistance to the curse of dimensionality, requiring only a few thousand data points for all cases studied (three to eighteen dimensions). Additionally, the method is highly economical in memory requirements, requiring only about 200 parameters for the most complex case considered.

Data-based modeling↗
DOE OSTI2025

First-principles investigation of the resistive switching energetics in monolayer MoS 2 : insights into metal diffusion and adsorption

A deeper understanding of resistive switching (RS) in 2D materials is essential for advancing neuromorphic computing. The Dissociation-Diffusion-Adsorption (DDA) model offers a useful framework for probing RS mechanisms in non-volatile memory (NVM) and in-memory computing. We have employed first-principles density functional theory (DFT) to explore dissociation, diffusion, and adsorption phenomena within the DDA model, focusing on the interactions between exemplary metal atoms (Au, Ag, Cu) and monolayer MoS 2 . Nudged elastic band (NEB) calculations evaluated diffusion barriers in pristine and sulfur-vacancy MoS 2 . Charged systems were modeled to assess the impact of applied bias on migration pathways. We also examined metal dissociation from bulk electrodes and adsorption at S vacancies. Ag/MoS 2 shows the lowest dissociation barrier (~0.034 eV), while Au and Cu exhibit similar values (~0.32 eV). These insights highlight Ag as a promising candidate for low-energy RS applications and provide guidance for optimizing switching efficiency in 2D memory devices.

Atomistic models↗
DOE OSTI2025

The Effects of Compounded Model Size Reductions on Adversarial Robustness

Recent advances in Edge AI and Tiny Machine Learning (TinyML) have enabled the deployment of machine learning models on resource-constrained environments. However, deploying these models on edge devices, such as micro-controllers, requires significant model footprint reduction through a variety of techniques such as quantization, pruning, and clustering. While these optimization methods offer considerable advantages, they potentially introduce AI-related security vulnerabilities, particularly concerning model robustness with respect to adversarial AI attacks. Prior research has extensively examined the impact of quantization on adversarial robustness; however, the effects of alternative reduction techniques and their combinations remain understudied. This paper investigates the impact of model size reduction techniques on adversarial robustness, when applied individually and combined. We utilized Fast Gradient Sign Method (FGSM) and Projected Gradient Descent (PGD) attacks to generate adversarial perturbations for both training and testing data, and then evaluated the models' accuracy under adversarial training conditions. Our findings revealed that reduction techniques generally diminished robustness; although, combining techniques was not found to make robustness any worse than when applied individually. Moreover, specific techniques can potentially enhance resistance to small size perturbations. This research provides insights into the trade-offs between model size reduction and security, establishing a foundation for future investigations into improving adversarial training techniques and methodologies for maintaining robustness while preserving memory footprint benefits.

Austria, Phillipe [ORNL] (ORCID:0000000236223973)↗
DOE OSTI2025

Unconventional unidirectional magnetoresistance in heterostructures of a topological semimetal and a ferromagnet

Unidirectional magnetoresistance (UMR) in a bilayer heterostructure, consisting of a spin-source material and a magnetic layer, refers to a change in the longitudinal resistance on the reversal of magnetization and originates from the interaction of non-equilibrium spin accumulation and magnetization at the interface. Since the spin polarization of an electric-field-induced non-equilibrium spin accumulation in conventional spin-source materials is restricted to be in the film plane, the ensuing UMR can only respond to the in-plane component of magnetization. However, magnets with perpendicular magnetic anisotropy are highly desired for magnetic memory and spin-logic devices, whereas the electrical read-out of perpendicular magnetic anisotropy magnets through UMR is critically missing. Here, in this study, we report the discovery of an unconventional UMR in the heterostructures of a topological semimetal (WTe 2 ) and a perpendicular magnetic anisotropy ferromagnetic insulator (Cr 2 Ge 2 Te 6 ), which allows to electrically read the up and down magnetic states of the Cr 2 Ge 2 Te 6 layer through longitudinal resistance measurements.

Kao, I-Hsuan [Carnegie Mellon Univ., Pittsburgh, P↗
DOE OSTI2024

Cycle equivalence classes, orthogonal Weingarten calculus, and the mean field theory of memristive systems

Abstract It has been recently noted that for a class of dynamical systems with explicit conservation laws represented via projector operators, the dynamics can be understood in terms of lower dimensional equations. This is the case, for instance, of memristive circuits. Memristive systems are important classes of devices with wide-ranging applications in electronic circuits, artificial neural networks, and memory storage. We show that such mean-field theories can emerge from averages over the group of orthogonal matrices, interpreted as cycle-preserving transformations applied to the projector operator describing Kirchhoff’s laws. Our results provide insights into the fundamental principles underlying the behavior of resistive and memristive circuits and highlight the importance of conservation laws for their mean-field theories. In addition, we argue that our results shed light on the nature of the critical avalanches observed in quasi-two-dimensional nanowires as boundary phenomena.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Electrode Elastic Modulus as the Dominant Factor in the Capping Effect in Ferroelectric Hafnium Zirconium Oxide Thin Films

The discovery of ferroelectricity in hafnia based thin films has catalyzed significant research focused on understanding the ferroelectric property origins and means to increase stability of the ferroelectric phase. Prior studies have revealed that biaxial tensile stress via an electrode “capping effect” is a suspected ferroelectric phase stabilization mechanism. This effect is commonly reported to stem from a coefficient of thermal expansion (CTE) incongruency between the hafnia and top electrode. Despite reported correlations between ferroelectric phase fraction and electrode CTE, the thick silicon substrate dominates the mechanics and CTE-related stresses, negating any dominant contribution from an electrode CTE mismatch toward the capping effect. In this work, these discrepancies are reconciled, and the origin of these differences deriving from electrode elastic modulus, not CTE, is demonstrated. Pt/M/TaN/Hf 0.5 Zr 0.5 O 2 /TaN/Si devices, where M is platinum, TaN, iridium, tungsten, and ruthenium, were fabricated. Sin 2 (ψ)-based X-ray diffraction measurements of biaxial stress in the HZO layer reveal a strong correlation between biaxial stress, remanent polarization, and electrode elastic modulus. Conversely, a low correlation exists between the electrode CTE, HZO biaxial stress, and remanent polarization. A higher elastic modulus enhances the resistance to electrode elastic deformation, which intensifies the capping effect during crystallization, and culminates in the tandem restriction of out-of-plane hafnia volume expansion and preferential orientation of the polar c-axis normal to the plane. These behaviors concomitantly increase the ferroelectric phase stability and polarization magnitude. This work provides electrode material selection guidelines toward the development of high-performing ferroelectric hafnia into microelectronic devices, such as nonvolatile memories.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Heteroepitaxial control of thickness, strain, and domain architecture in few-layer ferroelectric tin monochalcogenides

Thin-film epitaxy and epitaxial strain have been widely exploited to tune domain configurations, switching behavior, and ferroic properties in conventional three-dimensional ferroelectric thin films; however, its application to controlling the properties of two-dimensional (2D) ferroelectrics has remained largely unexplored. Here, using SnX (X = Se, S) as a model system, we demonstrate heteroepitaxial control of thickness, strain state, and domain architecture in few-layer ferroelectric SnX via growth on monolayer MoS2 van der Waals (vdW) templates. Compared with conventional growth, MoS2-templated heteroepitaxy promotes epitaxial alignment, yielding ultrathin SnSe films with improved crystalline quality, full areal coverage, and enlarged lateral dimensions. Strong interfacial epitaxial coupling induces pronounced in-plane strain and stabilizes a hierarchical ferroelastic domain architecture, in which long-range 90° stripe domains are further subdivided into nanoscale rotational variants, as revealed by scanning transmission electron microscopy and synchrotron X-ray microscopy. Piezoresponse force microscopy and second-harmonic polarimetry confirm robust in-plane polarization, while ferroelectricity in SnSe is established through polarization-electric field hysteresis and nonvolatile ferroelectric resistive switching with on/off ratios approaching 1000. A nonvolatile, switchable ferroelectric diode effect further evidences direct coupling between polarization and charge transport. Notably, ferroelectric switchability exhibits a strong thickness dependence and is preserved only below ∼10 layers. This vdW heteroepitaxial strategy is further extended to ferroelectric SnS. The seamless heteroepitaxial integration of 2D ferroelectrics with CMOS-compatible, wafer-scale MoS2 templates provides a general and scalable route for strain-enabled structural and ferroelectric engineering in emerging memory and low-power optoelectronic applications.

Wang, Yueyin↗
DOE OSTI2026

Spatiotemporal Thermal Coupling in VO 2 Device Arrays

Correlated oxides such as VO 2 exhibit an electrically driven insulator–metal transition (IMT) that underlies their promise for neuromorphic and memory devices. Yet the IMT is not a uniform bulk process but a spatiotemporal phenomenon in which local heating nucleates filaments, contracts or dissolves them with the electric field, and couples to the environment. In this work, we directly image the VO 2 IMT dynamics by mid-wave infrared, thermography synchronized with electrical transport, resolving device temperature with micrometer spatial and microsecond temporal resolution. At the single-device level, we capture the full cycle of filament nucleation, contraction, and relaxation during current/voltage-driven resistive switching. At the array level, we show that heat propagates across etched gaps with an effective length scale of ∼131 µm, enabling cooperative behaviors among electrically isolated devices. Short-range distanced devices exhibit mutual filament attraction and sequential dissolution, while long-range distanced devices differentiate into distinct roles: drivers that initiate switching, cooperative responders that undergo assisted self-oscillations, and passive reporters that record the thermal field. Furthermore, these results reframe thermal crosstalk, long regarded as parasitic, as an intrinsic coupling channel and design principle for organizing collective switching behaviors, with direct implications for emergent circuit functionality in neuromorphic and unconventional computing architectures.

coupling↗
DOE OSTI2024

Defect-induced formation and frustration-driven multiple magnetic transitions in Gd 2 Co 0.90 Si 2.90

A new ternary compound, Gd 2 Co 0.90 Si 2.90 , has been synthesized in a chemically single phase by deliberately introducing lattice vacancies in the Co and Si sites. The system is characterized by DC magnetization, heat capacity, resistivity and density functional theory (DFT) calculations. Here, a detailed experimental study reveals that the system exhibits an antiferromagnetic transition below T N = 11.3 K followed by spin freezing behaviour below T B ~ 4.8 K. An additional high-temperature magnetic transition could also be detected at T H ~ 150 K, which is short range in character and is associated with defect-induced polarization of the conduction electrons. The spin-glass-like state formation in the system is additionally bolstered by the observation of magnetic relaxation and associated aging phenomena as well as the magnetic memory effect. On the basis of non-equilibrium dynamical behaviour, we argue that the glassy state in this compound favours the hierarchical model over the droplet model. DFT calculations and experimental outcomes establish that the ground state is magnetically frustrated due to the small energy difference between distinct spin configurations having closely spaced ground-state energies.

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

Niobium coaxial cavities with internal quality factors exceeding 1.4 × 10 9 for circuit quantum electrodynamics

Group-V materials such as niobium and tantalum have become popular choices for extending the performance of circuit quantum electrodynamics (cQED) platforms, allowing for quantum processors and memories with reduced error rates and more modes. The complex surface chemistry of niobium, however, makes identifying the main modes of decoherence difficult at millikelvin temperatures and single-photon powers. We use niobium coaxial quarter-wave cavities to study the impact of etch chemistry, prolonged atmospheric exposure, and the significance of cavity conditions prior to and during cooldown—in particular, niobium hydride evolution—on single-photon coherence. We demonstrate cavities with quality factors Q int ≳ 1.4 × 10 9 in the single-photon regime, a 15-fold improvement over aluminum cavities of the same geometry. We rigorously quantify the sensitivity of our fabrication process to various loss mechanisms and demonstrate a two- to fourfold reduction in the two-level system loss tangent and a three- to fivefold improvement in the residual resistance over traditional buffered chemical polishing etching techniques. Finally, we demonstrate transmon integration and coherent cavity control while maintaining a cavity coherence of 11.3 ms. The accessibility of our method, which can be easily replicated in academic laboratory settings, together with the demonstration of its performance, mark an advancement in three-dimensional cQED.

Oriani, Andrew E. [Chicago U., EFI; Chicago U.] (O↗