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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Design and Challenges of Edge Computing ASICs on Front-End Electronics

In situ or hardware-embedded data processing of raw signals, close to their source, in radiation detectors is expected to provide dramatic improvements in data quality and volumes. However, the implementation of artificial neural networks (ANNs) in the front-end electronics, and the design of custom integrated circuits (ASICs), comes with challenges. In addition, detectors have to operate with limited power budget and implement complex functionalities in a very dense space. They often are exposed to extreme conditions as they work in high-radiation environments and/or cryogenic temperatures. This paper presents examples of applications and design methodologies for in-situ ANNs, along with the challenges of retaining the fidelity of the trained networks. For illustration, we use the problem of estimating the energy deposited by the radiation from digitized waveforms. The proposed implementation starts with an ML algorithm trained in Qkeras and eventually leads to an equivalent ASIC implementation. The associated design challenges in realizing energy and area efficient implementations in CMOS processes are reviewed. Novel approaches that employ hybrid technologies (combination of CMOS with memristors), in-memory computing models, and bio-inspired spiking neural networks are also highlighted

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Bright magnetic dipole radiation from two-dimensional lead-halide perovskites

Light-matter interactions in semiconductors are uniformly treated within the electric dipole approximation; multipolar interactions are considered “forbidden.” We experimentally demonstrate that this approximation inadequately describes light emission in two-dimensional (2D) hybrid organic-inorganic perovskites (HOIPs), solution processable semiconductors with promising optoelectronic properties. By exploiting the highly oriented crystal structure, we use energy-momentum spectroscopies to demonstrate that an exciton-like sideband in 2D HOIPs exhibits a multipolar radiation pattern with highly directed emission. Electromagnetic and quantum-mechanical analyses indicate that this emission originates from an out-of-plane magnetic dipole transition arising from the 2D character of electronic states. Symmetry arguments and temperature-dependent measurements suggest a dynamic symmetry-breaking mechanism that is active over a broad temperature range. These results challenge the paradigm of electric dipole–dominated light-matter interactions in optoelectronic materials, provide new perspectives on the origins of unexpected sideband emission in HOIPs, and tease the possibility of metamaterial-like scattering phenomena at the quantum-mechanical level.

42 ENGINEERING↗
DOE OSTI2022

Fusion RF Modeling Machine Learning (FusionML_RF) v1.0

FusionML_RF consists of multiple codes and trained machine learning (ML) models that perform low-cost output modeling from the Genray-CQL3D. Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. For example, completing a single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time. On the other hand, these ML models achieve ~ms of inference time with high accuracy across the input parameter space. This software collection consists of multiple components. (1) codes that use ML methods and precomputed Genray-CQL3D simulation output to build regression models that enable approximate computations of Genray-CLQ3D outputs from arbitrary but physically meaningful input parameters (surrogate modeling); (2) three trained models created by the team, using a database of 16,000+ GENRAY/CQL3D simulations, to study the performance of ML models for surrogate modeling; (3) codes that load the trained models and simulation data, and then compute mean squared error between the models' predictions and the ground truth of simulation output data. This collection is being made available in conjunction with a scientific publication about the work to promote reusability and provide an artifact of the scientific work.

Bai, Zhe↗
DOE OSTI2021

The Tiny Heater: Creating Heat with Hybrid Nano-Antennas [LDRD HQ Highlights Article]

SRNL scientists demonstrate that an electromagnetic field, either as a light or magnetic field, is selectively coupled to shape-selective hybrid nano-antennas for efficient thermal processes. Localized heating occurs extremely fast, reducing the ‘wasted' thermal load on the environment. Being non-contact, efficient, and highly selective, the required input energy is greatly diminished. By strategically placing nano-antennas at desired locations, heat can be controlled at the nano-level. The location for nano-antennas, and the subsequent energy deposition, may be fine-tuned through specific chemical, steric, or magnetic interactions. The nano-antennas, composed of combinations of plasmonic, magnetic, and hydride components, are used for controlled release of hydrogen isotopes, chemotherapy drugs, environmental contaminants, enhanced catalytic processes, (bio)imaging and therapeutics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Cobalt-Free Cathodes for Next Generation Li-Ion Batteries

In this U.S. Department of Energy sponsored project Nexceris, in collaboration with project partners; The Ohio State University and Navitas Advanced Systems have advanced the technical maturity of a non-cobalt containing cathode for next-generation Li-ion batteries. The cathode is based on the lithium manganese nickel-titanium oxide, LiNi 0.5 Mn 1.5 TiO 4 (LNMTO) high voltage spinel. To address limitations with poor cycle and calendar life an microstucturally hierarchical LNMO/LNMTO core-shell cathode powder has been developed that enables the formation of a solid-electrolyte interface that effectively passivates the cathode surface. The microstructural enhancements of the cathode material focus on preferentially enriching the surface with titanium. In parallel, new, optimized binder and electrolyte chemistries have been incorporated to address degradation mechanisms associated with high-voltage systems. Single-layer pouch cell and large-format 2-Ah cell testing have shown that an optimized LNMO/LNMTO core-shell powder significantly improves initial cell capacity and cycle life compared to homogeneous LNMO powder. To support development and the fabrication of 2-Ah cells a novel Hybrid Alternative Wet-Chemical Synthesis (HAWCS) process have been developed. This low-cost, synthesis approach enables the excellent compositional and particle morphology control achieved with co-precipitation without the strict process controls and associated expensive process equipment.

25 ENERGY STORAGE↗
DOE OSTI2025

White Paper: Scalable Digital Twin Capabilities for Aging and Surveillance of Engineered Systems

This white paper presents a multi-year initiative to develop practical, secure, and scalable digital twin capabilities for engineered systems in aging and surveillance contexts—an approach pioneered at the National Nuclear Security Administration (NNSA) Lawrence Livermore National Laboratory (LLNL) that maps directly onto the needs and ambitions of the Navy for ship- and fleet-level digital twins. LLNL’s work in building part- and process-level digital twins for advanced manufacturing, with a vision to scale up to entire factory floors and, ultimately, enterprise-wide digital twins, offers an adaptable pathway for the Navy as it seeks to modernize lifecycle management, readiness, and predictive maintenance across ships and fleets. For our application, we integrate physics-based modeling with automated data ingestion, processing, and AI-driven calibration, creating hybrid models that are both interpretable and data responsive. We modernized legacy workflows, established centralized data infrastructure, automated experimental pipelines, and demonstrated end-to-end coupling of accelerated aging data with finite element simulations via optimization and surrogate modeling. The result is a generalizable framework that supports part-level digital twins today and lays the groundwork for future system-level twins suitable for Navy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fabricating Silver Nanowire–IZO Composite Transparent Conducting Electrodes at Roll-to-Roll Speed for Perovskite Solar Cells

This study addresses the challenges of efficient, large-scale production of flexible transparent conducting electrodes (TCEs). We fabricate TCEs on polyethylene terephthalate (PET) substrates using a high-speed roll-to-roll (R2R) compatible method that combines gravure printing and photonic curing. The hybrid TCEs consist of Ag metal bus lines (Ag MBLs) coated with silver nanowires (AgNWs) and indium zinc oxide (IZO) layers. All materials are solutions deposited at speeds exceeding 10 m/min using gravure printing. We conduct a systematic study to optimize coating parameters and tune solvent composition to achieve a uniform AgNW network. The entire stack undergoes photonic curing, a low-energy annealing method that can be completed at high speeds and will not damage the plastic substrates. The resulting hybrid TCEs exhibit a transmittance of 92% averaged from 400 nm to 1100 nm and a sheet resistance of 11 Ω/sq. Mechanical durability is tested by bending the hybrid TCEs to a strain of 1% for 2000 cycles. The results show a minimal increase (<5%) in resistance. The high-throughput potential is established by showing that each hybrid TCE fabrication step can be completed at 30 m/min. We further fabricate methylammonium lead iodide solar cells to demonstrate the practical use of these TCEs, achieving an average power conversion efficiency (PCE) of 13%. The high-performance hybrid TCEs produced using R2R-compatible processes show potential as a viable choice for replacing vacuum-deposited indium tin oxide films on PET.

14 SOLAR ENERGY↗
DOE OSTI2024

DeepPhenoMem V1.0: deep learning modelling of canopy greenness dynamics accounting for multi-variate meteorological memory effects on vegetation phenology

Abstract. Vegetation phenology plays a key role in controlling the seasonality of ecosystem processes that modulate carbon, water and energy fluxes between the biosphere and atmosphere. Accurate modelling of vegetation phenology in the interplay of Earth's surface and the atmosphere is thus crucial to understand how the coupled system will respond to and shape climatic changes. Phenology is controlled by meteorological conditions at different timescales: on the one hand, changes in key meteorological variables (temperature, water, radiation) can have immediate effects on the vegetation development; on the other hand, phenological changes can be driven by past environmental conditions, known as memory effects. However, the processes governing meteorological memory effects on phenology are not completely understood, resulting in their limited performance of vegetation phenology represented in land surface models. A deep learning model, specifically a long short-term memory network (LSTM), has the potential to capture and model the meteorological memory effects on vegetation phenology. Here, we apply the LSTM to model the vegetation phenology using meteorological drivers and high-temporal-resolution canopy greenness observations through digital repeat photography by the PhenoCam network. We compare a multiple linear regression model, a no-memory-effect LSTM model and a full-memory-effect LSTM model to predict the whole seasonal greenness trajectory and the corresponding phenological transition dates across 50 sites and 317 site years during 2009–2018, covering deciduous broadleaf forests, evergreen needleleaf forests and grasslands. Results show that the deep learning model outperforms the multiple linear regression model, and the full-memory-effect LSTM model performs better than the no-memory-effect model for all three plant function types (median R2 of 0.878, 0.957 and 0.955 for broadleaf forests, evergreen needleleaf forests and grasslands). We also find that the full-memory-effect LSTM model is capable of predicting the seasonal dynamic variations of canopy greenness and reproducing trends in shifting phenological transition dates. We also performed a sensitivity analysis of the full-memory-effect LSTM model to assess its plausibility, revealing its coherence with established knowledge of vegetation phenology sensitivity to meteorological conditions, particularly changes in temperature. Our study highlights that (1) multi-variate meteorological memory effects play a crucial role in vegetation phenology, and (2) deep learning opens up new avenues for improving the representation of vegetation phenological processes in land surface models via a hybrid modelling approach.

Geology↗
DOE OSTI2022

Towards Fast and Accurate Predictions of Radio Frequency Power Deposition and Current Profile via Data-driven Modeling

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. The machine learning models use a database of 16,000+ GENRAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods ensure that the database covers the range of 9 input parameters ($n_{e0}$, $T_{e0}$, $I_p$, $B_t$, $R_0$, $n_{||}$, $Z_{eff}$, $V_{loop}$, $P_{LHCD}$) with sufficient density in all regions of parameter space. The surrogate models reduce the inference time from minutes to ~ms with high accuracy across the input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1980

Automatic control of NASA Langley's 0.3-meter cryogenic test facility

Experience during the past 6 years of operation of the 0.3-meter transonic cryogenic tunnel at the NASA Langley Research Center has shown that there are problems associated with efficient operation and control of cryogenic tunnels using manual control schemes. This is due to the high degree of process crosscoupling between the independent control variables (temperature, pressure, and fan drive speed) and the desired test condition (Mach number and Reynolds number). One problem has been the inability to maintain long-term accurate control of the test parameters. Additionally, the time required to change from one test condition to another has proven to be excessively long and much less efficient than desirable in terms of liquid nitrogen and electrical power usage. For these reasons, studies have been undertaken to: (1) develop and validate a mathematical model of the 0.3-meter cryogenic tunnel process, (2) utilize this model in a hybrid computer simulation to design temperature and pressure feedback control laws, and (3) evaluate the adequacy of these control schemes by analysis of closed-loop experimental data. This paper will present the results of these studies.

Thibodeaux, J. J.↗
NASA NTRS1980

Graphite composite truss welding and cap section forming subsystems. Volume 1: Executive summary

A rolltrusion process was developed for forming of a hybrid, single-ply woven graphite and glass fiber cloth, impregnated with a polysulfone resin and coated with TI02 pigmented P-1700 resin into strips for the on-orbit fabrication of triangular truss segments. Ultrasonic welding in vacuum showed no identifiable effects on weld strength or resin flow characteristics. An existing bench model cap roll forming machine was modified and used to roll form caps for the prototype test truss and for column test specimens in order to test local buckling and torsional instability characteristics.

Source record↗
NASA NTRS1979

Contamination control in hybrid microcircuit modules

The influence of chemical and particulate contamination upon the reliability and service life of hybrid microelectronic systems is documented. Several coating systems used include the parylene and Dow Corning silicone (DC90-711). These passivating coatings have potential for decreasing the degradation caused by particulate contaminants in hybrid systems as well as the possible deleterious effect of trapping chemical contaminants which have long term degrading influences upon the performance of the system. The reliability of a representative hybrid microcircuit is enhanced by the coating process.

Kinser, D. L.↗
NASA NTRS1990

Conceptual design optimization study

The feasibility of applying multilevel functional decomposition and optimization techniques to conceptual design of advanced fighter aircraft was investigated. Applying the functional decomposition techniques to the conceptual design phase appears to be feasible. The initial implementation of the modified design process will optimize wing design variables. A hybrid approach, combining functional decomposition techniques for generation of aerodynamic and mass properties linear sensitivity derivatives with existing techniques for sizing mission performance and optimization, is proposed.

Hollowell, S. J.↗
NASA NTRS1991

Architecture and design of a 500-MHz gallium-arsenide processing element for a parallel supercomputer

The design of the processing element of GASP, a GaAs supercomputer with a 500-MHz instruction issue rate and 1-GHz subsystem clocks, is presented. The novel, functionally modular, block data flow architecture of GASP is described. The architecture and design of a GASP processing element is then presented. The processing element (PE) is implemented in a hybrid semiconductor module with 152 custom GaAs ICs of eight different types. The effects of the implementation technology on both the system-level architecture and the PE design are discussed. SPICE simulations indicate that parts of the PE are capable of being clocked at 1 GHz, while the rest of the PE uses a 500-MHz clock. The architecture utilizes data flow techniques at a program block level, which allows efficient execution of parallel programs while maintaining reasonably good performance on sequential programs. A simulation study of the architecture indicates that an instruction execution rate of over 30,000 MIPS can be attained with 65 PEs.

Fouts, Douglas J.↗
NASA NTRS1990

Weather prediction using a genetic memory

Kanaerva's sparse distributed memory (SDM) is an associative memory model based on the mathematical properties of high dimensional binary address spaces. Holland's genetic algorithms are a search technique for high dimensional spaces inspired by evolutional processes of DNA. Genetic Memory is a hybrid of the above two systems, in which the memory uses a genetic algorithm to dynamically reconfigure its physical storage locations to reflect correlations between the stored addresses and data. This architecture is designed to maximize the ability of the system to scale-up to handle real world problems.

Rogers, David↗
NASA NTRS1991

Ion injection simulations of quasi-parallel shock re-formation

One-dimensional hybrid simulations are used to investigate the process of quasi-parallel shock reformation and to examine the coupling of a beam of ions reflected at the shock to the incoming solar wind. A simple simulation configuration is constructed that makes it possible to control the properties of the background plasma and of the reflected ions. The length and time scales for the coupling of the reflected ions to the background plasma are investigated as functions of the upstream magnetic field direction, beam density, and beam temperature. The coupling length and time scales are found to vary systematically with the upstream magnetic field direction. The coupling occurs at roughly the time and location where the injected ions become deflected transverse to the shock normal direction.

Onsager, T. G.↗
NASA NTRS1992

Solar wind-magnetosphere interaction as simulated by a 3-D EM particle code

We present here our first results of simulating the solar wind-magnetosphere interaction with a new three-dimensional electromagnetic particle code. Hitherto such global simulations were done with MHD codes while lower-dimensional particle or hybrid codes served to account for microscopic processes and such transport parameters as have to be introduced ad hoc in MHD. Our kinetic model attempts to combine the macroscopic and microscopic tasks. It relies only on the Maxwell curl equation and the Lorentz equation for particles, which are ideally suited for computers. The preliminary results shown here are for an unmagnetized solar wind plasma streaming past a dipolar magnetic field. The results show the formation of a bow shock and a magnetotail, the penetration of energetic particles into cusp and radiation belt regions, and dawn-dusk asymmetries.

Buneman, Oscar↗
NASA NTRS1993

Method for producing a hybridization of detector array and integrated circuit for readout

A process is explained for fabricating a detector array in a layer of semiconductor material on one substrate and an integrated readout circuit in a layer of semiconductor material on a separate substrate in order to select semiconductor material for optimum performance of each structure, such as GaAs for the detector array and Si for the integrated readout circuit. The detector array layer is lifted off its substrate, laminated on the metallized surface on the integrated surface, etched with reticulating channels to the surface of the integrated circuit, and provided with interconnections between the detector array pixels and the integrated readout circuit through the channels. The adhesive material for the lamination is selected to be chemically stable to provide electrical and thermal insulation and to provide stress release between the two structures fabricated in semiconductor materials that may have different coefficients of thermal expansion.

Fossum, Eric R.↗