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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Magnesium Hall Thruster

This Phase II project is developing a magnesium (Mg) Hall effect thruster system that would open the door for in situ resource utilization (ISRU)-based solar system exploration. Magnesium is light and easy to ionize. For a Mars- Earth transfer, the propellant mass savings with respect to a xenon Hall effect thruster (HET) system are enormous. Magnesium also can be combusted in a rocket with carbon dioxide (CO2) or water (H2O), enabling a multimode propulsion system with propellant sharing and ISRU. In the near term, CO2 and H2O would be collected in situ on Mars or the moon. In the far term, Mg itself would be collected from Martian and lunar regolith. In Phase I, an integrated, medium-power (1- to 3-kW) Mg HET system was developed and tested. Controlled, steady operation at constant voltage and power was demonstrated. Preliminary measurements indicate a specific impulse (Isp) greater than 4,000 s was achieved at a discharge potential of 400 V. The feasibility of delivering fluidized Mg powder to a medium- or high-power thruster also was demonstrated. Phase II of the project evaluated the performance of an integrated, highpower Mg Hall thruster system in a relevant space environment. Researchers improved the medium power thruster system and characterized it in detail. Researchers also designed and built a high-power (8- to 20-kW) Mg HET. A fluidized powder feed system supporting the high-power thruster was built and delivered to Busek Company, Inc.

Szabo, James J.↗
DOE OSTI2023

Highly cascaded first-order sapphire optical fiber Bragg gratings fabricated by a femtosecond laser

This Letter reports an innovative technique for fabricating large-scale, highly cascaded first-order sapphire optical fiber Bragg gratings (FBGs) using a femtosecond laser-assisted point-by-point inscription method. For the first time, to the best of our knowledge, this study successfully demonstrates a distributed array of 10 FBGs within highly multimode sapphire crystal fiber, made possible by employing a high-power laser technique to generate larger reflectors with a Gaussian intensity profile. These first-order FBGs offer advantages such as enhanced reflectivity, shorter fabrication time, and simplified spectral characteristics, making them easier to interpret compared with high-order FBGs. The FBGs’ resilience and effectiveness are analyzed by subjecting them to temperature tests, proving their capacity for accurate temperature monitoring up to 1500°C—a testament to their suitability for harsh environments. This novel approach broadens the scope for sensing and communication applications in sapphire fibers, particularly under challenging conditions. The novelty of our work lies in successfully overcoming the limitations of previous designs by integrating a cascade of 10 FBGs in sapphire fibers, thereby enhancing multiplexing capabilities, minimizing overlapping of FBG peaks, and ensuring reliable temperature monitoring in industries and applications with thermal gradients.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Accelerating Discovery of Solid‐State Thin‐Film Metal Dealloying for 3D Nanoarchitecture Materials Design through Laser Thermal Gradient Treatment

Thin‐film solid‐state metal dealloying (thin‐film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high‐throughput characterization of thermal treatment parameters is demonstrated using a laser‐based thermal treatment to create temperature gradients on single thin‐film samples of Nb‐Al/Sc and Nb‐Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X‐ray multimodal and high‐throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified. While the oxidation may influence nanostructure formation during thin‐film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. Further, this approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin‐film SSMD systems with targeted nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Phylogenomic discovery and engineering of nitrogen fixation into the bioenergy woody crop poplar

Biological nitrogen fixation (BNF) is a key process enabling plants in specific lineages to convert atmospheric dinitrogen (N₂) into bioavailable ammonia through symbioses with diazotrophic microbes. Expanding this capability beyond native nitrogen-fixing clades into non-nodulating crops would reduce synthetic fertilizer use, lowering energy inputs and environmental impacts in agriculture. Supported by DOE Funding Award DE-SC0018247, the NitFix project advanced foundational knowledge required to engineer root-nodule symbioses in new host species. The team generated the most comprehensive phylogenomic analysis to date of all known nodulating lineages, resolving the evolutionary history of nitrogen-fixing symbiosis and identifying core gene suites retained across nodulating taxa. Through multimodal genomics, transcriptomics, and functional analyses in Medicago truncatula and related species, the project mapped regulatory networks underlying nodule organogenesis, bacterial infection, and nitrogen-fixation efficiency. Key discoveries include the identification of conserved signaling modules for rhizobial recognition, transcription factors controlling nodule differentiation, and metabolic pathways integrating fixed nitrogen into plant growth. The project also developed enabling tools—including optimized transformation pipelines, gene-editing workflows, and imaging-based phenotyping—to accelerate engineering efforts in emerging models. Together, these results refine the mechanistic framework of symbiotic nitrogen fixation and highlight transferable components essential for rewiring these traits into non-nodulating crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Mesoporous Thin Film Architectures: Addressing Material Demands through Molecular Self-Assembly

Mesoporous thin films spark interest across a wide range of disciplines due to their tunable nanostructures, large internal surface areas, and strong compatibility with planar optical, electronic, and microfluidic devices. While attention in the porous materials community has shifted toward macroporous or disordered nanoporous systems, a resurgence in mesoporous thin film research is underway, driven by new molecular self-assembly methods, advanced materials chemistry, and improved characterization techniques. The integration of high-χN block copolymer design, kinetically persistent micelle templating, and postdeposition processing protocols now allows control over structural parameters such as pore size, wall thickness, porosity, and connectivity. These advances have overcome many of the thermodynamic and processing constraints that previously limited widespread adoption. Rather than serving only as high-surface-area supports, mesoporous thin films are engineered as active interfaces where responsive chemistries and nanoscale confinement act in tandem. Embedding switchable ligands, thermoresponsive polymers, redox mediators, or ion-selective groups directly within the pore walls enables real-time control over transport, optical, and electrochemical properties. These capabilities open up new directions in adaptive coatings, gated membranes, and fast-response biosensors. To further expand their functional scope, mesoporous films are integrated into hierarchical and multicomponent architectures. Techniques such as triblock terpolymer templating, crack-directed assembly, and nanoimprint lithography allow for control over spatial organization on the micron and submicron scale and pore system orientation. This enables programmable anisotropy, enhanced molecular diffusion, and wavelength-selective photonic behavior, essential for next-generation sensing, catalysis, and energy applications. Such structural and functional complexity requires equally sophisticated characterization. Multimodal and in situ techniques can track material dynamics under operational conditions. Recent progress includes extended-range ellipsometric porosimetry (EP) for hierarchical architectures, vacuum EP for interface energetics, time-resolved EP for diffusion kinetics, and correlative AFM-SAXS mapping. The introduction of advanced neutron-based spectroscopies, particularly quasielastic neutron scattering (QENS), promises to provide real-time access to ion transport dynamics and segmental motion under nanoscale confinement, offering a path toward deeper mechanistic understanding of structure-performance correlations in mesoporous systems. This Account reflects the technical advances made and the interdisciplinary collaborations that have shaped our collective vision. The particular dimensions of mesopores enable us to subtly tune interactions at the molecular, interfacial, and mesoscopic levels that permit us to harness nanoconfinement. What emerges is a versatile, modular platform capable of chemical gating, energy transduction, and sensing with a level of tunability unmatched by other porous materials. We highlight critical challenges including the need for more robust large-area processing, a deeper understanding of dynamic behavior under cycling, and better integration with device-level architectures. Our strategies support the transition of mesoporous thin films into active high-performance components in next-generation energy, environmental, and biomedical systems.

oxides↗
DOE OSTI2024

An Integrated Deposition and Passivation Strategy for Controlled Crystallization of 2D/3D Halide Perovskite Films

Abstract This work introduces a simplified deposition procedure for multidimensional (2D/3D) perovskite thin films, integrating a phenethylammonium chloride (PEACl)‐treatment into the antisolvent step when forming the 3D perovskite. This simultaneous deposition and passivation strategy reduces the number of synthesis steps while simultaneously stabilizing the halide perovskite film and improving the photovoltaic performance of resulting solar cell devices to 20.8%. Using a combination of multimodal in situ and additional ex situ characterizations, it is demonstrated that the introduction of PEACl during the perovskite film formation slows down the crystal growth process, which leads to a larger average grain size and narrower grain size distribution, thus reducing carrier recombination at grain boundaries and improving the device's performance and stability. The data suggests that during annealing of the wet film, the PEACl diffuses to the surface of the film, forming hydrophobic (quasi‐)2D structures that protect the bulk of the perovskite film from humidity‐induced degradation.

2D/3D perovskites↗
NASA NTRS1991

A trajectory planning scheme for spacecraft in the space station environment

Simulated annealing is used to solve a minimum fuel trajectory problem in the space station environment. The environment is special because the space station will define a multivehicle environment in space. The optimization surface is a complex nonlinear function of the initial conditions of the chase and target crafts. Small permutations in the input conditions can result in abrupt changes to the optimization surface. Since no prior knowledge about the number or location of local minima on the surface is available, the optimization must be capable of functioning on a multimodal surface. It was reported in the literature that the simulated annealing algorithm is more effective on such surfaces than descent techniques using random starting points. The simulated annealing optimization was found to be capable of identifying a minimum fuel, two-burn trajectory subject to four constraints which are integrated into the optimization using a barrier method. The computations required to solve the optimization are fast enough that missions could be planned on board the space station. Potential applications for on board planning of missions are numerous. Future research topics may include optimal planning of multi-waypoint maneuvers using a knowledge base to guide the optimization, and a study aimed at developing robust annealing schedules for potential on board missions.

Soller, Jeffrey Alan↗
DOE OSTI2025

Quantum Sensing Enhanced by Squeezing and Non-Hermitian Physics

We find extraordinary enhancement of sensitivity by integrating non-Hermitian and squeezing effects in a general framework for quantum sensing. When a bosonic-mode sensor operates at the parametric oscillation (PO) threshold and an exceptional point (EP), the sensing precision exhibits a quartic scaling with the perturbation strength, leading to ultrahigh sensitivity. The result generalizes to multimode squeezed-state sensors with higher-order EPs, with potential applicability across a wide range of quantum sensing platforms.

Wang, Changqing [Fermilab]↗
NASA NTRS1989

Design of fiber optic probes for laser light scattering

A quantitative analysis is presented of the role of optical fibers in laser light scattering. Design of a general fiber optic/microlens probe by means of ray tracing is described. Several different geometries employing an optical fiber of the type used in lightwave communications and a graded index microlens are considered. Experimental results using a nonimaging fiber optic detector probe show that due to geometrical limitations of single mode fibers, a probe using a multimode optical fiber has better performance, for both static and dynamic measurements of the scattered light intensity, compared with a probe using a single mode fiber. Fiber optic detector probes are shown to be more efficient at data collection when compared with conventional approaches to measurements of the scattered laser light. Integration of fiber optic detector probes into a fiber optic spectrometer offers considerable miniaturization of conventional light scattering spectrometers, which can be made arbitrarily small. In addition static and dynamic measurements of scattered light can be made within the scattering cell and consequently very close to the scattering center.

Dhadwal, Harbans S.↗
NASA NTRS1987

Virtual workstation - A multimodal, stereoscopic display environment

A head-mounted, wide-angle, stereoscopic display system controlled by operator position, voice and gesture has been developed for use in a multipurpose interface environment. The system provides a multisensory, interactive display environment in which a user can virtually explore a 360-degree synthesized or remotely sensed environment and can viscerally interact with its components. Primary applications of the system are in telerobotics, management of large-scale integrated information systems, and human factors research. System configuration, application scenarios, and research directions are described.

Fisher, S. S.↗
NASA NTRS2016

Using Multimodal Input for Autonomous Decision Making for Unmanned Systems

Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.

Neilan, James H.↗
DOE OSTI2021

A Multi-modal Approach to Understanding Degradation of Organic Photovoltaic Materials

State-of-the-art organic photovoltaic (OPV) materials are composed of complex, chemically diverse polymeric and molecular structures that form highly intricate solid-state interactions, collectively yielding exceptional tunability in performance and aesthetics. These properties are especially attractive for semitransparent power-generating windows or shades in living environments, greenhouses, or other architectural integrations. However, before such a future is realized, a broader and deeper understanding of property stability must be acquired. Stability during operating and environmental conditions is critical, namely, material color steadfastness, optoelectronic performance retention, morphological rigidity, and chemical robustness. To date, no single investigation encompasses all four distinct, yet interconnected, metrics. Here, we present a multimodal strategy that captures a dynamic and interconnected evolution of each property during the course of an accelerated photobleaching experiment. We demonstrate this approach across relevant length scales (from molecular to visual macroscale) using X-ray photoelectron spectroscopy, grazing-incidence X-ray scattering, microwave conductivity, and time-dependent photobleaching spectroscopies for two high-performance semitransparent OPV blends—PDPP4T:PC 60 BM and PDPP4T:IEICO-4F, with comparisons to the stabilities of the individual components. We present direct evidence that specific molecular acceptor (fullerene vs nonfullerene) designs and the resulting donor–acceptor interactions lead to distinctly different mechanistic routes that ultimately arrive at what is termed “OPV degradation.” We directly observe a chemical oxidation of the cyano endcaps of the IEICO-4F that coincides with a morphological change and large loss in photoconductivity while the fullerene acceptor-containing blend demonstrates a significantly greater fraction of oxygen uptake but retains 55% of the photoconductivity. Finally, this experimental roadmap provides meaningful guidance for future high-throughput, multimodal studies, benchmarking the sensitivity of the different analytical techniques for assessing stability in printable active layers, independent of complete device architectures.

14 SOLAR ENERGY↗
NASA NTRS1983

AFTI/F-16 DFCS development summary - A report to industry multimode control law design

The primary goal of the AFTI/F-16 program is to develop a reliable triplex digital multimode flight control system; this system is to be tailored to optimize fighter performance and capable of six-degree-of-freedom decoupled aircraft control. The multiple digital control law configurations arrived at through flight testing are presented. The changes in these designs from the results of flight tests establish that flight testing is an integral part of the development process. The flight test results are analyzed here from the standpoint of pilot comments and resulting control law design modifications.

Toles, R. D.↗
NASA NTRSDate not supplied

A Novel Framework for Multi-Path Data Fusion in Earth Observation and New Observing Strategies: Applications to Predicting Forest Canopy Height

Exponential growth of data from Earth Observation (EO) assets has necessitated the development of sophisticated methods for data interpretation and management. NASA’s New Observing Strategy (NOS) approach aims to coordinate operations among complex heterogenous systems of constellations, requiring advanced Artificial Intelligence and Machine Learning (AI/ML) techniques. Despite significant advancements in AI/ML across various domains, the EO and machine learning for satellite (SatML) fields remain fragmented, often relying on adapted techniques rather than domain-specific solutions. We present a novel end-to-end data fusion framework tailored specifically for EO and SatML, addressing this gap by facilitating rapid development of AI/ML applications. This framework, called, Multimodal Earth Observation Workflow for Machine Learning (MEOW-ML), sup- ports the entire AI/ML lifecycle, from dataset manipulation, to model training, evaluation, and logging, and is designed to expedite the development of next-generation NOS deployments and SOTA in EO. We apply our framework to predict canopy height model (CHM) derived from lidar data. We integrate multiple data modalities through a hierarchical, multi-path model architecture, effectively identifying and leveraging the unique strengths of each data source to enhance predictive accuracy. Our experiments demonstrate that the multi-path architecture outperforms traditional single-path models and provides significant advantages in both accuracy and computational efficiency.

Mark Moussa↗
DOE OSTI2020

Challenges in Lithium Metal Anodes for Solid-State Batteries

In this Perspective, we highlight recent progress and challenges related to the integration of lithium metal anodes in solid-state batteries. While prior reports have suggested that solid electrolytes may be impermeable to lithium metal, this hypothesis has been disproven under a variety of electrolyte compositions and cycling conditions. Herein, we describe the mechanistic origins and importance of lithium filament growth and interphase formation in inorganic and organic solid electrolytes. Multimodal techniques that combine real and reciprocal space imaging and modeling will be necessary to fully understand nonequilibrium dynamics at these buried interfaces. Currently, most studies on lithium electrode kinetics at solid electrolyte interfaces are completed in symmetric Li–Li configurations. To fully understand the challenges and opportunities afforded by Li-metal anodes, full-cell experiments are necessary. Lastly, the impacts of operating conditions on solid-state batteries are largely unknown with respect to pressure, geometry, and break-in protocols. Given the rapid growth of this community and the diverse portfolio of solid electrolytes, we highlight the need for detailed reporting of experimental conditions and standardization of protocols across the community.

25 ENERGY STORAGE↗
NASA NTRS1994

Multimodal correlation and intraoperative matching of virtual models in neurosurgery

The multimodal correlation between different diagnostic exams, the intraoperative calibration of pointing tools and the correlation of the patient's virtual models with the patient himself, are some examples, taken from the biomedical field, of a unique problem: determine the relationship linking representation of the same object in different reference frames. Several methods have been developed in order to determine this relationship, among them, the surface matching method is one that gives the patient minimum discomfort and the errors occurring are compatible with the required precision. The surface matching method has been successfully applied to the multimodal correlation of diagnostic exams such as CT, MR, PET and SPECT. Algorithms for automatic segmentation of diagnostic images have been developed to extract the reference surfaces from the diagnostic exams, whereas the surface of the patient's skull has been monitored, in our approach, by means of a laser sensor mounted on the end effector of an industrial robot. An integrated system for virtual planning and real time execution of surgical procedures has been realized.

Ceresole, Enrico↗
DOE OSTI2022

Deep generative molecular design reshapes drug discovery

Recent advances and accomplishments of artificial intelligence (AI) and deep generative models have established their usefulness in medicinal applications, especially in drug discovery and development. To correctly apply AI, the developer and user face questions such as which protocols to consider, which factors to scrutinize, and how the deep generative models can integrate the relevant disciplines. This review summarizes classical and newly developed AI approaches, providing an updated and accessible guide to the broad computational drug discovery and development community. We introduce deep generative models from different standpoints and describe the theoretical frameworks for representing chemical and biological structures and their applications. We discuss the data and technical challenges and highlight future directions of multimodal deep generative models for accelerating drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗