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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 OSTI2024

Heat Transport Hysteresis Generated Through Frequency Switching of a Time-Dependent Temperature Gradient

A stochastic energetics framework is applied to examine how periodically shifting the frequency of a time-dependent oscillating temperature gradient affects heat transport in a nanoscale molecular model. We specifically examine the effects that frequency switching, i.e., instantaneously changing the oscillation frequency of the temperature gradient, has on the shape of the heat transport hysteresis curves generated by a particle connected to two thermal baths, each with a temperature that is oscillating in time. Analytical expressions are derived for the energy fluxes in/out of the system and the baths, with excellent agreement observed between the analytical expressions and the results from nonequilibrium molecular dynamics simulations. We find that the shape of the heat transport hysteresis curves can be significantly altered by shifting the frequency between fast and slow oscillation regimes. We also observe the emergence of features in the hysteresis curves such as pinched loops and complex multi-loop patterns due to the frequency shifting. The presented results have implications in the design of thermal neuromorphic devices such as thermal memristors and thermal memcapacitors.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Understanding and Tuning the Electronic Properties of Prussian Blue Analogues

Prussian blue analogues (PBAs) have attracted increasing interest owing to their potential applications in various fields such as energy storage and conversion, neuromorphic computing, and magnetic switching. With a general formula of A x M N [M C (CN) 6 ], they feature an open framework that provides abundant channels for diffusion of alkali metal ions A and allows flexible compositional control of transition metal ions M N and M C . The oxidation states of transition metal ions can be tuned by adjusting the amount (x) of alkali ions A. Here, we carried out density functional theory calculations combined with experimental measurements to investigate the effects of transition metal ions, alkali ions, and oxidation states on the electronic properties of PBAs. Our calculations found that the band gaps of PBAs can be tuned from close to 0 eV to more than 4 eV. Experimentally, we introduced the synthesis/characterization of five previously unreported PBAs (M N = Ru, Os; M C = Fe, Ru, and Os) to complete the nine stable M N :M C transition metal combinations in group VIII of the periodic table. The optically measured intervalence charge transfer excitation energies of group VIII PBAs are consistent with calculated band gaps. They demonstrate wide band gap tunability by adjusting transition metals and oxidation states, enabling semiconductor-to-metal transitions for memristor applications and enhancing electronic conductivity for battery applications. In conclusion, this work provides a computational/experimental database of electronic properties versus structural compositions for PBAs.

Electrical conductivity↗
DOE OSTI2025

Crystallization Mechanisms of Poly(vinylidene Fluoride- co -chlorotrifluoroethylene): Nucleation Transitions, Growth Kinetics, and Microstructure Evolution

The crystallization kinetics of FK-800, a commercial semicrystalline copolymer of chlorotrifluoroethylene and vinylidene fluoride (poly(CTFE-co-VDF)), dictate its microstructure and functional performance. Crystallization occurs between the glass transition (T g ≈ 31 °C) and melting point (T m ≈ 110 °C), with grain boundaries playing a key role in applications such as memristors, where they regulate filament growth. This study integrates in situ atomic force microscopy (AFM), grazing-incidence wide-angle X-ray scattering (GIWAXS), and differential scanning calorimetry (DSC) to characterize nucleation, growth, and morphology across the full crystallization window. Hot-stage AFM reveals a transition from homogeneous to heterogeneous nucleation near 45 °C and a shift from reaction-limited to diffusion-limited growth above 60 °C. Kinetics are analyzed using Lauritzen–Hoffman, Turnbull–Fisher, and Avrami models to extract surface free energies and activation barriers. A multiscale modeling framework is developed in which nucleation densities and growth rates measured by AFM are used to reconstruct Avrami kinetics, which are then validated against coverage data, and extrapolated to predict bulk crystallization behavior observed by DSC. GIWAXS confirms a primarily flat-on chain orientation at all temperatures, linking orientation to domain morphology. This integrative approach quantitatively connects nanoscale crystallization dynamics with macroscopic phase evolution, establishing a quantitative framework for modeling crystallization across time, temperature, and length scales.

Crystallization↗
DOE OSTI2024

Tunable multistate field-free switching and ratchet effect by spin-orbit torque in canted ferrimagnetic alloy

Spin-orbit torque is not only a useful probe to study manipulation of magnetic textures and magnetic states at the nanoscale but also it carries great potential for next-generation computing applications. Here we report the observation of rich spin-orbit torque switching phenomena such as field-free switching, multistate switching, memristor behavior and ratchet effect in a single shot, co-sputtered, rare earth-transition metal Gd x Co 100-x . Notably such effects have only been observed in antiferromagnet/ferromagnet bi-layer systems previously. We show that these effects can be traced to a large anistropic canting, that can be engineered into the Gd x Co 100-x system. Further, we show that the magnitude of these switching phenomena can be tuned by the canting angle and the in-plane external field. The complex spin-orbit torque switching observed in canted Gd x Co 100-x not only provides a platform for spintronics but also serves as a model system to study the underlying physics of complex magnetic textures and interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Strain-associated nanoscale fluctuating lithium transport within single-crystalline LiNi 1/3 Mn 1/3 Co 1/3 O 2 cathode particles

Solid-state lithium diffusion dynamics are critical for the rate capability and longevity of Li-ion batteries. Conventionally, nanoscale lithium diffusion within individual battery particles has been simplified as being primarily driven by concentration gradients, despite the associated processes inducing local lattice expansion, contraction, and strain fields. Using operando scanning transmission soft X-ray microscopy with high spatial resolution and chemical sensitivity to track nanoscale intraparticle lithium transport, and post-cycling Bragg coherent diffraction X-ray imaging to directly reveal three-dimensional intraparticle strain fields, we uncover strain-associated lithium transport dynamics within single-crystalline LiNi 1/3 Mn 1/3 Co 1/3 O 2 (scNMC) particles during cycling. Contrary to the expected thermodynamic solid-solution behavior of scNMC, our observations reveal near-uniform but fluctuating regions of lithium-dense and lithium-dilute areas during cycling. These fluctuations suggest that nanoscale lithium diffusion can proceed counter to concentration gradients. Additionally, we demonstrate that an increased presence of lithium-dilute regions near the surface enhances lithium surface insertion kinetics, emphasizing the importance of controlling surface lithium distribution to improve rate performance. Our study provides insights into nanoscale solid-state ion transport, with potential applications in batteries, solid-state fuel cells, and memristors.

Lee, Danwon [Seoul National Univ. (Korea, Republic↗
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 OSTI2025

How Interface Evolution at the Nanoscale Dictates Protonic Ceramic Cell Behavior

Understanding the effects of heterointerfaces in nanodevices remains a challenge in interface engineering for systems applied in solid oxide fuel cells, catalysis, sensors, and memristors [1]. Previous studies have shown that the presence of interfaces in ceramic oxide nanodevices affects their impedance properties compared to bulk systems [2]. In this work, we analyze a thin-film model system designed to study the interfaces between representative electrode and electrolyte materials employed in protonic ceramic electrochemical cells for the reversible conversion of hydrogen o electricity. The investigated device features a 21-layer architecture that alternates between an electrode material PBSCF (PrBa 0.5 Sr 0.5 Co 1.5 Fe 0.5 O 5+ϵ ) and a proton-conducting electrolyte BZY (BaZr 0.8 Y 0.2 O 3-δ ), with uniform 20 nm thickness for each layer. Here, the device was fabricated using Pulsed Laser Deposition (PLD) and supported on a conductive Nb-doped STO (Nb-SrTiO 3 ) substrate.

dos Santos, Gabriel T. [Northwestern University, E↗
DOE OSTI2024

2D Amorphous Carbon Dielectric Prepared from Solution Precursor for Nanoelectronics

The preparation of amorphous 2D nanodielectrics represents a major challenge due to the metastable nature of amorphous phases. We describe a scalable and solution-based strategy to prepare wafer-scale 2D amorphous carbon with thickness down to 1–2 atomic layers from coal-derived carbon quantum dots as precursors. The prepared atomically thin 2D amorphous carbon can be suspended over cavities as freestanding membranes with high modulus of 400±100 GPa and demonstrate robust dielectric properties with dielectric strength above 20 MV·cm-1 and leakage current density below 10-4 A·cm-2 through a scaled thickness of three-atomic layers. When implemented as ultrathin gate dielectrics in 2D transistors or ion-transport media in memristors, they enable exceptional device performance and spatiotemporal uniformity, resulting from their amorphous form, intrinsic ultrathinness, and 2D atomic structures.

Pham, Viet Hung↗
DOE OSTI2024

Solution-Based Synthesis of Ultrathin Quasi-2D Amorphous Carbon for Nanoelectronics

The synthesis of ultrathin 2D amorphous dielectric film represents a major challenge due to the metastable nature of amorphous phases. We describe a scalable and solution-based strategy to prepare wafer-scale 2D amorphous carbon with thickness down to 1–2 atomic layers from coal-derived carbon quantum dots as precursors. The prepared atomically thin 2D amorphous carbon can be suspended over cavities as freestanding membranes with high modulus of 400±100 GPa and demonstrate robust dielectric properties with dielectric strength above 20 MV·cm-1 and leakage current density below 10-4 A·cm-2 through a scaled thickness of three-atomic layers. When implemented as ultrathin gate dielectrics in 2D transistors or ion-transport media in memristors, they enable exceptional device performance and spatiotemporal uniformity, resulting from their amorphous form, intrinsic ultrathinness, and 2D atomic structures.

Pham, Viet Hung [NETL Site Support Contractor, Nat↗
DOE OSTI2025

Interactions Enhance Ramp Reversal Memory in Locally Phase Separated Materials

The ramp-reversal memory (RRM) effect in metal–insulator transition metal oxides (TMOs), a non-volatile resistance change induced by repeated temperature cycling, has attracted considerable interest in neuromorphic computing and non-volatile memory devices. Our previous defect motion model successfully explained RRM in vanadium dioxide (VO 2 ), capturing observed critical temperature shifts and memory accumulation throughout the sample. However, this approach lacked interactions between metallic and insulating domains. Here, we extend our model by combining a correlated Random Field Ising Model with defect diffusion-segregation, enabling accurate hysteresis modeling while predicting the relationship between RRM and domain interactions. Our simulations demonstrate that the maximum RRM occurs when the turnaround temperature approaches the inflection point. This peak in RRM vs. turnaround temperature is consistent with prior transport measurements, as well as our own optical measurements reported here. Significantly, we find that increasing nearest-neighbor interactions enhances the maximum memory effect, thus providing a clear mechanism for optimizing RRM performance. Since our model employs minimal assumptions, we predict that RRM should be a widespread phenomenon in materials exhibiting patterned phase coexistence of electronic domains. This work not only advances fundamental understanding of memory behavior in TMOs but also establishes a much-needed theoretical framework for optimizing device applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Uncontrolled Learning: Codesign of Neuromorphic Hardware Topology for Neuromorphic Algorithms

Neuromorphic computing has the potential to revolutionize future technologies and our understanding of intelligence, yet it remains challenging to realize in practice. The learning-from-mistakes algorithm, inspired by the brain's simple learning rules of inhibition and pruning, is one of the few brain-like training methods. This algorithm is implemented in neuromorphic memristive hardware through a codesign process that evaluates essential hardware trade-offs. While the algorithm effectively trains small networks as binary classifiers and perceptrons, performance declines significantly with increasing network size unless the hardware is tailored to the algorithm. This work investigates the trade-offs between depth, controllability, and capacity—the number of learnable patterns—in neuromorphic hardware. This highlights the importance of topology and governing equations, providing theoretical tools to evaluate a device's computational capacity based on its measurements and circuit structure. The findings show that breaking neural network symmetry enhances both controllability and capacity. Additionally, by pruning the circuit, neuromorphic algorithms in all-memristive circuits can utilize stochastic resources to create local contrasts in network weights. Through combined experimental and simulation efforts, the parameters are identified that enable networks to exhibit emergent intelligence from simple rules, advancing the potential of neuromorphic computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Dual-ion ECRAM as a stable and accurate analog synapse

Electrochemical random-access memory (ECRAM) works by tuning the bulk electronic conductance of functional materials via reversible, electrochemical insertion of ions, resulting in stable analog resistive switching, attractive for analog in-memory and neuromorphic computing. However, achieving fast programming for training and long retention for inference has been elusive. Protonic ECRAM demonstrates fast programming but insufficient retention, while oxygen-based ECRAM with excellent retention requires elevated programming temperatures. Cu-based ECRAM offers a compromise, with an activation energy (E A ) of ≈0.76 eV between protons (E A ≈ 0.4 eV) and oxygen (E A > 1 eV), enabling extensive retention and room temperature programming. Combining Cu 2+ ions with protons to form a dual-ion ECRAM, we demonstrate two distinct switching behaviors: fast switching at ≤5 V, (E A ≈ 0.45 eV) via protons, and nonvolatile, room temperature switching at ≥8 V, with E A ≈ 0.76 eV via Cu 2+ ions. In conclusion, the Cu-based state exhibits a wide conductance range, with excellent retention, low noise, and linear current-voltage behavior, achieving digital-equivalent ImageNet inference accuracy.

analog in-memory computing↗
DOE OSTI2025

Dielectric-Engineered Monolayer MoS 2 Memtransistors for Brain-Inspired Computing with High Recognition Accuracy

Two-dimensional transition metal dichalcogenides (2D-TMDs)-based memtransistors have emerged as promising candidates for neuromorphic hardware due to their exceptional ability to emulate synaptic behavior. However, many existing 2D-TMDs memtransistors rely on polycrystalline channels with grain boundaries or defects introduced through postgrowth treatments, raising concerns about material integrity and the preservation of intrinsic properties. Here, in this work, we demonstrate a monocrystalline monolayer MoS 2 memtransistor fabricated on a silicon nitride (SiN X ) substrate, achieving a large resistive switching ratio of 10 4 , a dynamic range exceeding 90, along with highly linear and symmetric weight updates, minimal cycle-to-cycle variability, and low device-to-device variability. These attributes are critical for enabling high-performance neuromorphic hardware. Based on experimental data, we further show that these artificial synapses enable a recognition accuracy of more than 97% on the MNIST handwritten digits data set. Our findings present a straightforward approach to realizing 2D-TMDs memtransistors through dielectric engineering, offering a promising platform for next-generation neuromorphic computing systems.

2D TMDs↗
DOE OSTI2025

Electrolytic gold plating, stripping, and ion transport dynamics through a solid-state iodide perovskite

The pronounced electrochemical reactivity between halide perovskites and metal electrodes can introduce mobile extrinsic metal ions which can cause device instability or enable novel functionalities. Here we systematically investigate the kinetics of gold cation (Au + ) migration in indium tin oxide (ITO)/methylammonium lead triiodide (MAPbI 3 )/Au model devices under long-term potentiostatic biasing. Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) analyses reveal that Au + ions, electrochemically generated at the Au anode, traverse the perovskite layer with diffusion coefficients on the order of 10 −11 to 10 −10 cm 2 s −1 and are subsequently reduced at the cathode as Au 0 clusters, resembling metal plating behavior in electrolytic cells and solid-state batteries during charging. Furthermore, reversing the applied bias strips the plated Au 0 , revealing reversibility suitable for bipolar resistive switching devices and providing direct evidence of the electrochemical and ionic nature of Au transport within the perovskite matrix. Quantitatively determining diffusion coefficients and ion concentrations provides foundational inputs for future drift-diffusion modelling opportunities and allows us to relate our findings to implications on long term operation of devices like photovoltaic modules. These results clearly demonstrate the solid-state electrochemical nature of perovskite devices, highlight methods to be more quantitative about ion transport properties, provide and emphasize the importance of disentangling electro-, photo-, photoelectrochemical processes for understanding device performance and unlocking new functionalities.

14 SOLAR ENERGY↗
DOE OSTI2025

Resistive Switching in SrFeO2.5/Nb:SrTiO3 Heterostructures with Growth-Controlled Film Orientation

Resistive switching, a behavior found in many oxide materials, has the potential to enable emerging computer hardware technologies and architectures. We present resistive switching devices fabricated from epitaxial brownmillerite SrFeO2.5 films with two distinct film orientations, wherein facile oxygen ion diffusion planes are aligned parallel (in-plane) and perpendicular (out-of-plane) with the electrodes. SrFeO2.5 films were grown on (001) oriented Nb:SrTiO3 to enable high-quality interfaces and future integration with Si CMOS technologies. Post-growth vacuum annealing and growth pressure were used to control film orientations, as confirmed by transmission electron microscopy and x-ray diffraction measurements. Films grown with diffusion planes oriented in-plane had oxygen-rich, perovskite-like nanodomains spread throughout the film, and fabricated devices exhibited worse switching consistency and more stochasticity. In contrast, films grown with diffusion planes oriented out-of-plane had a more uniform oxygen-rich perovskite interfacial layer above the bottom electrode, and devices built from this film orientation showed significant statistical improvements in switching voltages and cycling consistency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Quantum graph models for transport in filamentary switching

The formation of metallic nanofilaments bridging two electrodes across an insulator is a mechanism for resistive switching. Examples of such phenomena include atomic synapses, which constitute a distinct class of memristive devices the behavior of which is closely tied to the properties of the filament. Until recently, experimental investigation of the low-temperature regime and quantum transport effects has been limited. However, with growing interest in understanding the true impacts of the filament on device conductance, comprehending quantum effects has become crucial for quantum neuromorphic hardware. Here, we discuss quantum transport resulting from filamentary switching in a narrow region where the continuous approximation of the contact is not valid, and only a few atoms are involved. In this scenario, the filament can be represented by a graph depicting the adjacency of atoms and the overlap between atomic orbitals. Using the theory of quantum graphs with locally diffusive node scattering, we calculate the scattering amplitude of charge carriers on this graph and explore the interplay between filamentary formation and quantum transport effects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗