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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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210 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

NASA Small Spacecraft and Distributed Systems: Recent and Upcoming Technology Demonstrations and Development Efforts

NASA’s Small Spacecraft & Distributed Systems (SSDS) program strengthens U.S. ability to conduct unique missions by rapidly developing and demonstrating capabilities for SmallSat exploration, science, and commercial space. In collaboration with NASA Centers, other government agencies, commercial industry, and academia, SSDS advances next generation SmallSat technologies like power, processing, propulsion, communications, autonomous navigation, architectures (swarms), and applications (AI/ML/Edge Computing)—to extend missions beyond LEO into cislunar and planetary space. Various investment mechanisms exist for SSDS to select and fund projects that will ultimately advance NASA’s Moon to Mars Architecture. Presented here are the latest achievements and findings from recently completed SSDS projects, along with updates from ongoing efforts and planned future work. Successful missions like Starling and CAPSTONE continue to demonstrate their capability after several years on-orbit. Advancements in next generation swarm configurations are being implemented by Starling for space traffic monitoring and management applications. Findings from recent SSDS flight projects are discussed: DiskSat, a unique SmallSat platform alternative to canisterized nanosatellites, launched December 2025 and is gathering data; the PTD series of missions concluded in December 2025. Current SSDS efforts are focused on addressing NASA Shortfalls relating to rendezvous and proximity operations, neuromorphic computing, and space situational awareness.

Roger Hunter↗
NASA NTRSDate not supplied

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗
NASA NTRSDate not supplied

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗
DOE OSTI2025

Materials Selection Principles for Designing Electro‐Thermal Neurons

Artificial neurons exhibiting volatile threshold switching and action potential‐like oscillations are crucial for brain‐inspired computing. While Complimentary Metal‐Oxide‐Semiconductor (CMOS)‐based strategies require hundreds of transistors to simulate each neuron, neuronal oscillations arise spontaneously in individual electro‐thermal devices due to nonlinearities like the Mott transition in VO 2 . Despite improved understanding of the physics, quantitative connections between neuronal performance and material properties remain under‐explored, preventing predictive neuron design and rational materials selection. In this work, a physics‐aware forward design methodology is developed for interrogating a wide palette of materials with properties varying by orders of magnitude, and their performance (high frequency, high dynamical reconfigurability and low power) under external circuit and device geometry constraints is assessed. The space of viable materials is identified to be much larger than previously recognized, with candidates from a range of materials classes, including Ge, GaP and MoS 2 . CMOS‐compatible performance (such as 100 GHz oscillating frequencies) can be achieved with CMOS‐compatible node sizes (≈10 nm). Finally, combinations of material properties yielding desired neuronal performance under uncertain design constraints are considered. This work solidifies forward design principles for electro‐thermal neuron devices, a necessary pre‐condition for inverse design from desired neuronal performance to required materials properties.

compact model↗
DOE OSTI2025

Charge Regulation Stabilizes the Formation of Ionic Liquid‐Based Amphiphilic Oligomer Droplet Interface Bilayers

Amphiphilic charged oligomers (oligodimethylsiloxane – methylimidazolium cation, ODMS-MIM (+) ), assemble into bilayers using the droplet interface bilayer (DIB) platform, possess similar size and functionality as phospholipid bilayers, but exhibit increased stability. The oligomer ionic headgroups (MIM (+) ) are covalently bound to monodisperse, short-chain (n = 13) hydrophobic tails (ODMS). These self-assemble as monolayer brushes at the oil–aqueous interface of water droplets that are influenced by both the charged cationic headgroups, and the nature of the covalently attached tails in the organic phase. Charge regulation (CR) stabilizes the formation of ordered, molecularly close-packed brush phases, which results in highly insulating, stable DIB membranes, with contributions from specific ion-pairing effects, Debye screening, and voltage-dependent electrocompressive stresses. In the oil phase, interactions between hexadecane, a good solvent for ODMS, and the hydrophobic tails result in extended waiting times for bilayer formation compared to phospholipid DIBs, for which hexadecane is a poor solvent. Close agreement between experimental values and predictions for two key parameters, the critical membrane thickness, h c , and maximal grafted headgroup density, Γ 0 , validate an electrostatic CR model consisting of adsorption and partial neutralization of counterions at a charged interface.

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

Axon-like active signal transmission

Any electrical signal propagating in a metallic conductor loses amplitude due to the natural resistance of the metal. Compensating for such losses presently requires repeatedly breaking the conductor and interposing amplifiers that consume and regenerate the signal. This century-old primitive severely constrains the design and performance of modern interconnect-dense chips. Here we present a fundamentally different primitive based on semi-stable edge of chaos (EOC), a long-theorized but experimentally elusive regime that underlies active (self-amplifying) transmission in biological axons. By electrically accessing the spin crossover in LaCoO 3 , we isolate semi-stable EOC, characterized by small-signal negative resistance and amplification of perturbations. In a metallic line atop a medium biased at EOC, a signal input at one end exits the other end amplified, without passing through a separate amplifying component. While superficially resembling superconductivity, active transmission offers controllably amplified time-varying small-signal propagation at normal temperature and pressure, but requires an electrically energized EOC medium. Operando thermal mapping reveals the mechanism of amplification—bias energy of the EOC medium, instead of fully dissipating as heat, is partly used to amplify signals in the metallic line, thereby enabling spatially continuous active transmission, which could transform the design and performance of complex electronic chips.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
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 OSTI2024

Electrically-driven IMT and volatile memristor behavior in NdNiO 3 films

Abstract Transition metal oxides with insulator-metal transitions (IMTs) are uniquely suited for volatile memristor devices that mimic the spiking of biological neurons. Unlike most non-volatile memristors, which often operate via ion migration into filaments, volatile devices utilize a reversible phase change that returns to a ground state in the absence of applied stimulus. In these devices, Joule heating triggers the IMT and changes the bulk resistivity rather than influencing conduction through defects, as in previous studies. This volatile resistive switching behavior has previous been leveraged in niobium and vanadium oxides, but not in rare-earth nickelates, despite their tunable transition temperatures. This study demonstrates an electrically driven IMT in the prototypical rare-earth nickelate, NdNiO 3 , in large area devices. While previous work examining the electrically-driven IMT in NdNiO 3 suggests defect-dominated conduction, this study shows clear s-type negative differential resistance (NDR) consistent with temperature-dependent resistivity measurements. The NDR peak-to-valley voltage scales linearly with temperature as expected for conductivity pathways dominated by bulk IMT behavior. Unlike other transition metal oxides, which are modeled using the insulator-metal phase fraction as the internal state variable, a thermoelectric model with temperature as the internal state variable is found to more accurately describe the current–voltage characteristic of NdNiO 3 volatile memristors. Overall, we report the synthesis, fabrication, and characterization of NdNiO 3 volatile memristors with resistivity dominated by bulk-like IMT behavior which is scalable and not dependent upon oxygen vacancy migration or defect mediated conduction pathways.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Neural units with time-dependent functionality

We show that the time-resolved dynamics of an underdamped harmonic oscillator can be used to do multifunctional computation, performing distinct computations at distinct times within a single dynamical trajectory. We consider the amplitude of an oscillator whose inputs influence its frequency. The activity of the oscillator at fixed times is a nonmonotonic function of its inputs, so it can solve problems such as XOR that are not linearly separable. The activity of the oscillator at fixed input is a nonmonotonic function of time, so it is multifunctional in a temporal sense, and able to carry out distinct nonlinear computations at distinct times within the same dynamical trajectory. We show that a single oscillator, observed at different times, can act as all of the elementary logic gates and perform binary addition, the latter usually implemented in hardware using five logic gates. We show that a set of n oscillators, observed at different times, can perform an arbitrary number of analog-to-n-bit digital conversions. We also show that oscillators can be trained by gradient descent to perform distinct classification tasks at distinct times. Computing with time-dependent functionality can be done in or out of equilibrium, and suggests a way of reducing the number of parameters or devices required to do nonlinear computations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Bypassing Fast Time Scales of the Hodgkin-Huxley Neuron Model via a Thresholded Hard Reset

We propose a modification to the Hodgkin-Huxley model to reduce the numerical stiffness of the equations by introducing an explicit voltage threshold. When this threshold is crossed, the voltage and the gating variables are reset to constant values. It is found that, for all of the current stimuli considered, the proposed model accurately reproduces the behavior of the baseline Hodgkin-Huxley model while bypassing the fast dynamics of spiking. Specifically, the model accurately reproduces the spike times and, between spikes, the time courses of the membrane potential and gating variables.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Foveal vision reduces neural resources in agent-based game learning

Efficient processing of information is crucial for the optimization of neural resources in both biological and artificial visual systems. In this paper, we study the efficiency that may be obtained via the use of a fovea. Using biologically-motivated agents, we study visual information processing, learning, and decision making in a controlled artificial environment, namely the Atari Pong video game. We compare the resources necessary to play Pong between agents with and without a fovea. Our study shows that a fovea can significantly reduce the neural resources, in the form of number of neurons, number of synapses, and number of computations, while at the same time maintaining performance at playing Pong. To our knowledge, this is the first study in which an agent must simultaneously optimize its visual system, along with its decision making and action generation capabilities. That is, the visual system is integral to a complete agent.

60 APPLIED LIFE SCIENCES↗