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DOE OSTI2026

Visualization of the surface distribution of photocatalytic activity at the anatase/rutile TiO2 interface using X-ray photoelectron emission microscopy

We applied X-ray photoelectron emission microscopy (XPEEM) to visualize the surface distribution of photocatalytic activity at the anatase/rutile (A/R) interface of titanium dioxide. Acetic acid was adsorbed on the surface, and its decomposition and desorption reactions under ultraviolet light irradiation were monitored by observing C 1s spectra, enabling direct observation of the spatial distribution of photocatalytic activity. Complementary crystal structure information was obtained using spatially resolved low-energy electron diffraction, low-energy electron microscopy, X-ray absorption spectroscopy, and micro-focused Raman spectroscopy. Comparison with these structural data allowed for the evaluation of the photocatalytic activity as a function of the distance from the A/R interface. The activity is enhanced in the vicinity of the interface and gradually decreases toward both the anatase and rutile regions. These results demonstrate that XPEEM is an effective technique for spatially resolved mapping of photocatalytic activity, which has\\r\\npreviously been inaccessible using conventional characterization techniques.

25 ENERGY STORAGE↗

NASA NTRS1991

The Real-Time Control of Planetary Rovers Through Behavior Modification

It is not yet clear of what type, and how much, intelligence is needed for a planetary rover to function semi-autonomously on a planetary surface. Current designs assume an advanced AI system that maintains a detailed map of its journeys and the surroundings, and that carefully calculates and tests every move in advance. To achieve these abilities, and because of the limitations of space-qualified electronics, the supporting rover is quite sizable, massing a large fraction of a ton, and requiring technology advances in everything from power to ground operations. An alternative approach is to use a behavior driven control scheme. Recent research has shown that many complex tasks may be achieved by programming a robot with a set of behaviors and activation or deactivating a subset of those behaviors as required by the specific situation in which the robot finds itself. Behavior control requires much less computation than is required by tradition AI planning techniques. The reduced computation requirements allows the entire rover to be scaled down as appropriate (only down-link communications and payload do not scale under these circumstances). The missions that can be handled by the real-time control and operation of a set of small, semi-autonomous, interacting, behavior-controlled planetary rovers are discussed.

David P Miller↗

DOE OSTI1968

Nuclear Physics Made Very, Very Easy

The fundamental approach to nuclear physics was prepared to introduce basic reactor principles to various groups of non-nuclear technical personnel associated with NERVA Test Operations. NERVA Test Operations functions as the field test group for the Nuclear Rocket Engine Program. Nuclear Engine for Rocket Vehicle Application (NERVA) program is the combined efforts of Aerojet-General Corporation as prime contractor, and Westinghouse Astronuclear Laboratory as the major subcontractor, for the assembly and testing of nuclear rocket engines. Development of the NERVA Program is under the direction of the Space Nuclear Propulsion Office, a joint agency of the U. S. Atomic Energy Commission and the National Aeronautics and Space Administration. This report is being reprinted for use in the U. S. Atomic Energy Commission and National Aeronautics and Space Administration educational and technology utilization programs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

Characterization Testing of a 20 Kelvin Cryocooler for Space Applications

Future NASA space exploration missions will require long-duration storage and liquefaction of cryogenic liquids, enabled by active cooling provided by cryocoolers. Recent gap analyses of Lunar and Mars transportation systems have identified 20 K-class cryocoolers as a critical enabling technology for chemical and nuclear thermal propulsion architectures using liquid hydrogen propellant. To address this technology gap, NASA has undergone the development of a high-efficiency, high-capacity 20 K cryocooler via an SBIR partnership with Creare. While the January 2025 testing demonstrated functionality and compliance with contractual requirements, the objective of the NASA-led characterization effort was to generate a dataset for supporting future mission designs across a broader operating envelope, including off-nominal conditions. The cryocooler demonstrated strong performance, achieving a peak coefficient of performance of 17.68% relative to Carnot efficiency and a maximum lift capacity of 24.4 W at 21 K. Overall, the results confirm that the 20 W 20 K cryocooler provides a flexible range of capabilities to enable zero boil-off storage of liquid hydrogen for future Lunar and Mars missions. The data collected provide a strong foundation for model validation and future system design efforts.

Cryocooler↗

NASA NTRSDate not supplied

Characterization Testing of a 20 Kelvin Cryocooler for Space Applications

Zero boil-off↗

NASA NTRS1991

Augmentation of the Space Station Module Power Management and Distribution Breadboard

The space station module power management and distribution (SSM/PMAD) breadboard models power distribution and management, including scheduling, load prioritization, and a fault detection, identification, and recovery (FDIR) system within a Space Station Freedom habitation or laboratory module. This 120 VDC system is capable of distributing up to 30 kW of power among more than 25 loads. In addition to the power distribution hardware, the system includes computer control through a hierarchy of processes. The lowest level consists of fast, simple (from a computing standpoint) switchgear that is capable of quickly safing the system. At the next level are local load center processors, (LLP's) which execute load scheduling, perform redundant switching, and shed loads which use more than scheduled power. Above the LLP's are three cooperating artificial intelligence (AI) systems which manage load prioritizations, load scheduling, load shedding, and fault recovery and management. Recent upgrades to hardware and modifications to software at both the LLP and AI system levels promise a drastic increase in speed, a significant increase in functionality and reliability, and potential for further examination of advanced automation techniques. The background, SSM/PMAD, interface to the Lewis Research Center test bed, the large autonomous spacecraft electrical power system, and future plans are discussed.

Bryan Walls↗

NASA NTRSDate not supplied

Air-Broadened Line Shapes in the 2n3 R Branch of 12ch4 Between 6014 and 6100 cm-1

Complete and accurate information on line shape parameters of 2?3 methane transitions for air broadening as a function of temperature is critical not only for the correct interpretation of the observed atmospheric spectra but also for the development of a reliable theoretical model. For this reason, we obtained a series of high-resolution, high S/N spectra of high-purity 12CH4 and 12CH4 broadened with dry air at temperatures in the 130 to 295 K range using the Bruker IFS 125HR Fourier transform spectrometer at JPL. Two absorption cells were used in the experiment, a White cell with path length of 13 m for room temperature spectra and a 21 m Herriott cella for cold sample spectra. The 15 spectra used in the analysis consisted of 3 low pressure (0.26 to 2.57 Torr) spectra with pure 12CH4 and 12 air-broadened spectra with total sample pressures of 79-805 Torr and volume mixing ratios of methane between 0.23 and 1%. A multispectrum least-squares fitting techniqueb was employed to fit all 15 spectra simultaneously. Preliminary results for select R(J) manifolds will be presented.

V Malathy Devi↗

NASA NTRS2026

Investigating Dual Electrospinning as a Means of Enhancing Passive Thermal Control Coatings for Cryogenic Propellant Storage in Extraterrestrial Environments

Passive thermal control is necessary as space exploration becomes increasingly widespread. Materials with superior optical properties (high solar reflectance and infrared emittance) are critical for passive thermal control because they can reject most of the incident solar radiation and promote thermal emission from cryogenic propellant storage tanks, enabling the extraterrestrial storage of cryogens. We have demonstrated in previous studies that electrospun nanofibers exhibit exceptional optical properties, offering significant benefits for passive radiative cooling in space. Particularly, electrospun polyvinylidene fluoride-co-hexafluoropropylene PVDF-HFP nanofibers demonstrate exceptionally high solar reflectance (>99%) and strong thermal emittance (measured at ~300 K). However, they exhibit nanostructural changes in the presence of atomic oxygen, which is prevalent in Low Earth Orbit. This study focuses on creating a unique blend of polymeric (PVDF-HFP) and ceramic-based (silica) nanofibers by leveraging the chemical stability and atomic oxygen resistance of silica, using the dual electrospinning manufacturing method. This approach aims to preserve the structural properties of the polymeric counterpart without compromising its optical performance, thereby providing an innovative method for manufacturing environmentally resilient passive thermal control nanofibers with desirable optical and thermal control functionalities for extraterrestrial storage of cryogenic propellants.

Chieloka Ibekwe↗

DOE OSTI2024

Using scalable computer vision to automate high-throughput semiconductor characterization

Abstract High-throughput materials synthesis methods, crucial for discovering novel functional materials, face a bottleneck in property characterization. These high-throughput synthesis tools produce 10 4 samples per hour using ink-based deposition while most characterization methods are either slow (conventional rates of 10 1 samples per hour) or rigid (e.g., designed for standard thin films), resulting in a bottleneck. To address this, we propose automated characterization (autocharacterization) tools that leverage adaptive computer vision for an 85x faster throughput compared to non-automated workflows. Our tools include a generalizable composition mapping tool and two scalable autocharacterization algorithms that: (1) autonomously compute the band gaps of 200 compositions in 6 minutes, and (2) autonomously compute the environmental stability of 200 compositions in 20 minutes, achieving 98.5% and 96.9% accuracy, respectively, when benchmarked against domain expert manual evaluation. These tools, demonstrated on the formamidinium (FA) and methylammonium (MA) mixed-cation perovskite system FA 1−x MA x PbI 3 , 0 ≤ x ≤ 1, significantly accelerate the characterization process, synchronizing it closer to the rate of high-throughput synthesis.

Science & Technology - Other Topics↗

DOE OSTI2024

A thermal evaporation–trapping strategy to synthesize flexible and robust oxygen electrocatalysts for rechargeable zinc–air batteries

Great efforts have been devoted to the development of bifunctional electrocatalysts to accelerate the sluggish kinetics of cathodic oxygen reduction/evolution reactions (ORR/OER) in zinc–air batteries (ZABs). Here we report a thermal evaporation–trapping synergistic strategy to fabricate a bifunctional electrocatalyst of flexible N-doped carbon fiber cloth loaded with both CoFe-oxide nanoparticles and single-atom Co/Fe–Nx sites, in which the thermal evaporation process functions in both downsizing CoFe-oxide nanoparticles and trapping the evaporated Co/Fe species to generate Co/Fe–Nx sites. The obtained flexible electrocatalyst, directly serving as an oxygen electrode, displays a small potential gap of 0.542 V for the OER/ORR, large peak power densities (liquid-state ZAB: 237.4 mW cm2 ; solid-state ZAB: 141.1 mW cm2 ), and excellent charge–discharge cycling stability without decay after working more than 770 hours. Furthermore, in situ Raman spectroscopy characterization and theoretical calculations reveal that CoFe2O4 species is responsible for the OER while atomic Fe/Co sites play a key role in the ORR

Zhang, Hong-Bo↗

DOE OSTI2025

Dissipative Phase Transition in the Two-Photon Dicke Model

We explore the dissipative phase transition of the two-photon Dicke model, a topic that has garnered significant attention recently. Our analysis reveals that while single-photon loss does not stabilize the intrinsic instability in the model, the inclusion of two-photon loss restores stability, leading to the emergence of superradiant states, which coexist with the normal vacuum states. Using a second-order cumulant expansion for the photons, we derive an analytical description of the system in the thermodynamic limit, which agrees well with the exact calculation results. Additionally, we present the Wigner function for the system, shedding light on the breaking of the 𝑍4 symmetry inherent in the model. These findings offer valuable insights into stabilization mechanisms in open quantum systems and pave the way for exploring complex nonlinear dynamics in two-photon Dicke models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Computing the Critical Temperature of the Affine-Transformed $D=3$ Ising Model Using Masked Autoregressive Flow

The simple Ising model provides a rich environment to build and study lattice field theories. As part of an ongoing project to construct a conformal field theory (CFT) on an arbitrarily curved manifold, in this work we develop methods to measure the critical temperature $β_c$ of the affine-transformed Ising model on the face-centered cubic (FCC) lattice. The main challenge in this endeavor is finding a computationally efficient and accurate method of interpolating and extrapolating Monte Carlo observables with respect to coupling coefficients and temperature. Herein, we compare two such methods. A traditional statistical approach uses the multiple histogram (MH) method, while a newer machine learning approach uses a masked autoregressive flow (MAF) to estimate the underlying probability density function of a set of observables. While the MH method is specifically designed to interpolate and extrapolate Monte Carlo observables, we find that MAF is a viable alternative for measuring $β_c$ with a computational cost that scales more favorably. Furthermore, we comment on additional advantages of MAF relevant to our work, such as extrapolating in system volume.

Svenson, Kai [Texas U.]↗

NASA NTRS2025

A Review of Direct Ink Writing of Polymer Derived Ceramics

With the growing demand for materials capable of withstanding extreme temperatures and pressures, ceramic components with exceptional corrosion resistance and reliable mechanical properties have experienced a significant surge in demand. However, traditional ceramic forming methods involve high-temperatures and energy-intensive processes that often struggle to produce complex parts or composites efficiently. Polymer-Derived Ceramics (PDCs) offer a transformative solution by using polymeric precursors that can be converted into a wide variety of silicon-based and non-silicon-based ceramics through heat treatment. The polymeric nature of PDC precursors enables the fabrication of geometrically intricate components using conventional polymer-forming techniques at significantly lower processing temperatures. Furthermore, PDCs are well-suited for additive manufacturing (AM), allowing the production of complex structural and functional components through cost-effective, low-temperature processes. By leveraging the diverse properties of PDC materials – each with unique advantages and limitations – manufacturers can optimise performance for specific applications. This review provides an overview of the types of PDCs developed to date and their broad range of applications. Specifically, it delves into the Direct Ink Writing (DIW) process, exploring its rheological requirements and the critical role of fillers in tailoring the rheological properties of polymeric precursors to meet the specific demands of DIW.

Victoria Bishop↗

DOE OSTI2024

Connectivity, Pathology, and ApoE4 Interactions Predict Longitudinal Tau Spatial Progression and Memory

ABSTRACT Tau pathology spread into neocortex indicates a transition from healthy aging to Alzheimer's disease (AD). Connectivity between tau epicenters and later accumulating regions of cortex has been proposed as a mechanism of tau spread, but how this relationship changes with greater AD pathology burden or genotype is not understood. We investigated tau accumulation in two key regions, precuneus and inferior temporal cortex, using resting state functional connectivity (rsFC) and longitudinal PET imaging from a multicohort sample of cognitively unimpaired older adults. We examined how baseline tau PET, Aβ PET, and ApoE4 genotype status interact with rsFC between hippocampus and these downstream regions to predict rate of tau accumulation in neocortex. We found that the 3‐way interaction between connectivity, baseline tau, and baseline Aβ or ApoE4 status was associated with neocortical tau accumulation in precuneus and inferior temporal cortex. In addition, baseline tau, Aβ, and ApoE4 status also moderated the association between connectivity and rate of memory decline. Together, these results suggest that the extent and distribution of future tau accumulation may be predicted by the interaction of baseline connectivity, AD pathology, and genetic risk.

Neurosciences & Neurology↗

DOE OSTI2025

AIVT: Inference of turbulent thermal convection from measured 3D velocity data by physics-informed Kolmogorov-Arnold networks

We propose the artificial intelligence velocimetry-thermometry (AIVT) method to reconstruct a continuous and differentiable representation of the temperature and velocity in turbulent convection from measured three-dimensional (3D) velocity data. AIVT is based on physics-informed Kolmogorov-Arnold networks and trained by optimizing a loss function that minimizes residuals of the velocity data, boundary conditions, and governing equations. We apply AIVT to a set of simultaneously measured 3D temperature and velocity data of Rayleigh-Bénard convection, obtained by combining particle image thermometry and Lagrangian particle tracking. This enables us to directly compare machine learning results to true volumetric, simultaneous temperature and velocity measurements. We demonstrate that AIVT can reconstruct and infer continuous, instantaneous velocity and temperature fields and their gradients from sparse experimental data at a high resolution, providing an additional approach for understanding thermal turbulence.

Science & Technology - Other Topics↗

DOE OSTI2024

Autonomous phototaxis of hydrogel swimmers

The design of synthetic soft matter capable of emulating the complex behaviors of living organisms, such as sensing and adapting to their environment, remains an important challenge in developing biomimetic materials. Functionalized hydrogels are ideal candidates for such materials since they are highly responsive to their environment and can be operated in water. In this work, we investigate a hybrid bonding hydrogel composed of peptide amphiphile supramolecular nanofibers covalently attached to a photoresponsive network, in which high-aspect-ratio ferromagnetic nanowires are aligned along the length of the sample, designed to swim under oscillating magnetic fields. This hybrid hydrogel swimmer can autonomously swim toward a light source by utilizing photoinduced interactions between supramolecular and covalent networks reminiscent of phototactic swimming in living systems. Using a combination of experimental techniques and a continuum model incorporating photochemistry, magnetoelasticity, and hydrodynamics, we explain the swimming mechanism and predict phototactic behavior. Our work highlights the potential role of hybrid bonding polymers, which leverage the interplay between supramolecular assemblies and covalent networks. We demonstrate how these polymers can be tailored to react dynamically to their environment, paving the way for developing intelligent and autonomous robotic systems.

Science & Technology - Other Topics↗

DOE OSTI2026

Electronegativity-Guided Site Differentiation in High-Entropy Alloy for pH-universal Hydrogen Evolution Reactions

Enhancing the intrinsic activity of transition metal catalysts for the hydrogen evolution reaction (HER) remains a critical challenge in sustainable energy conversion. Herein, we report an electronegativity-guided site differentiation strategy in a single-phase CoNiCuMoW high-entropy alloy (HEA) via electrodeposition by incorporating high-electronegativity 4d/5d orbital transition metals (Mo, W) into the face-centered cubic (fcc) matrix (CoNiCu). The as-synthesized HEA demonstrates exceptional HER performance in all pH conditions, delivering an outstanding overpotential of 65 mV (alkaline), 28 mV (acidic), and 155 mV (neutral) at a current density of 100 mA cm−2, showing performance comparable to commercial Pt/C and has excellent long-term stability at high current density (1 A cm−2, 1000 h). X-Ray absorption spectroscopy (XAS) and density functional theory (DFT) calculations reveal that the incorporation of Mo/W simultaneously alters the local coordination environment and induces element-dependent charge redistribution, accompanied by a system-level d-band center downshift, thereby optimizing the hydrogen binding strength across multimetallic sites. Meanwhile, oxophilic Mo/W sites lower the water dissociation energy barrier. These synergistic effects collectively enable efficient and durable pH-universal HER performance.

Wu, Yutong↗

DOE OSTI2026

All-Polyester Multilayer Plastics (‘All-Polyester MLPs’): A Redesign for Inherently Recyclable Plastics

Multilayer plastics (MLPs) are widely used in modern packaging because they combine multiple functions such as oxygen and moisture barriers, mechanical strength, puncture resistance, and heat sealability into lightweight and cost-effective packaging solutions. These attributes are essential for food, beverage, pharmaceutical, and consumer goods packaging. However, conventional commercial MLPs typically consist of five to twelve layers made from chemically incompatible materials, including polyolefins, polyethylene terephthalate, nylon, ethylene-vinyl alcohol (EVOH), adhesives, and tie layers. This complexity makes MLPs extremely difficult to recycle. As a result, the vast majority of multilayer plastics (MLPs) are disposed of through landfilling or incineration. This disposal pathway perpetuates demand for virgin material production, thereby driving high industrial energy consumption, increasing greenhouse gas (GHG) emissions, and contributing to the long-term accumulation of plastic waste. The scope of work included: (1) Design and fabrication of all-polyester multilayer structures using commercially relevant processing methods; (2) Experimental validation of barrier, mechanical, and sealing performance; (3) Demonstration of both mechanical and chemical recycling pathways; and (4) Comprehensive techno-economic analysis (TEA) and life-cycle assessment (LCA) to quantify cost, energy, and environmental impacts.

36 MATERIALS SCIENCE↗