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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Nanostructured double-layer FeO as nanotemplate for tuning adsorption of titanyl phthalocyanine molecules

The growth, structure of Pt(111) supported double-layer FeO and the adsorption of titanyl phthalocyanine (TiOPc) molecules with tunable site and orientation were presented. According to the atomic-resolution STM image, the structure was rationalized as (8√3 × 8√3) R30°/Pt(111) nanostructure constructed by Fe species coordinated with different number of oxygen on top of non-rotated (8 × 8) FeO /Pt(111) structure. Due to the modulation of the stacking of Fe atoms in the second layer relative to the O atoms in the second layer and the underlying layer, the interface and total dipole moment periodically vary within (8√3 × 8√3) R30°/Pt(111) structure. The resulted periodically distributed dipole-dipole interaction benefits the growth of TiOPc molecules with area-selective sites and molecular orientations. Thus, this study provides a reliable method to govern the adsorption process of the polar molecules for potential applications in future functional molecular devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Exploring Capability of Multimodal Foundation Model for Image-based Fault Detection of Photovoltaic Modules

Multimodal Foundation Model (MFM), like ChatGPT and Gemini, have emerged as powerful tools for their exceptional natural language processing capabilities and their emerging potential in image analysis. This paper investigates the application of MFMs for photovoltaic (PV) fault detection through image analysis, focusing on ChatGPT 4.0 and Gemini 1.5 Pro. Three types of PV images and the corresponding common PV faults are detected: bird droppings using visible images, cell cracks via electroluminescence (EL) images, and hotspots using infrared (IR) images. Among the two models, Gemini 1.5 Pro demonstrated superior performance, achieving near-perfect results with an average F1 score of 0.97, consistently outperforming ChatGPT 4.0 in accuracy and reliability. Unlike traditional machine learning (ML) models, MFMs can operate in a zero shot manner that does not require additional training by the user, and the input images are not limited by size, angle, scope, or PV technology. The strong adaptability and user-friendliness make MFM a promising tool for analyzing PV images and advancing health monitoring for PV modules.

Li, Baojie↗
DOE OSTI2018

Activation Energy Determination for Photovoltaic Encapsulant Discoloration by Indoor Accelerated UV Testing

A novel methodology for determining the activation energy of photovoltaic encapsulant discoloration using an indoor accelerated ultraviolet (UV) stress test while simultaneously maintaining multiple module temperatures in a single weathering chamber is presented. The testing was performed on some fresh mini-modules with a glass/EVA/cell/EVA/backsheet construction. The short-circuit current degradation from individual cells was used to quantify transmittance losses due to discoloration. Activation energy determined using indoor accelerated UV test data and Modified Arrhenius model ranges from 26 to 44 kJ/mol (0.27 to 0.46 eV). Activation energy was also determined from the outdoor field degradation data by employing different physical models that consider the individual or combined effects of key environmental factors. The approach here is instrumental to evaluating the reliability studies on encapsulant degradation mechanisms using relatively less time and resources.

14 SOLAR ENERGY↗
DOE OSTI2025

Physics-Based Analysis of Cell Imbalances and Aging in Lithium-Ion Battery Modules and Packs

Lithium-ion battery (LIB) packs are a key solution for grid-scale energy storage, enabling grid resilience and supporting critical infrastructure. LIB modules and packs experience current imbalances and uneven cell aging due to various design and operational factors, and require a battery management system (BMS) to continuously monitor and control. In this context, a physics-based modeling framework for LIB modules and packs (liionpack) was enhanced to identify design and control strategies that minimize current imbalance and improve module/pack operation. Simulations of an 8-cell parallel-connected module demonstrate that reducing current imbalance leads to more uniform cell aging and improved module/pack-level degradation predictions. The analysis shows that current imbalance are affected by the electrical resistances. Terminal location significantly affects imbalance, with opposite-end terminal connections at intermediate branches minimizing the imbalance, and the pack circuit construction influences the accuracy of physics-based analysis at the pack scale. This framework enables design optimization of modules and packs through a fast and easy evaluation of pack performance and aging, and supports the development of aging-informed balancing strategies compatible with BMS implementation. Thereby, offering practical pathways to improve reliability and cycle life predictions in large-scale battery energy storage systems.

Ayalasomayajula, Surya Mitra [Oak Ridge National L↗
DOE OSTI2015

A Massively Parallel Solver for the Mechanical Harmonic Analysis of Accelerator Cavities

ACE3P is a 3D massively parallel simulation suite that developed at SLAC National Accelerator Laboratory that can perform coupled electromagnetic, thermal and mechanical study. Effectively utilizing supercomputer resources, ACE3P has become a key simulation tool for particle accelerator R and D. A new frequency domain solver to perform mechanical harmonic response analysis of accelerator components is developed within the existing parallel framework. This solver is designed to determine the frequency response of the mechanical system to external harmonic excitations for time-efficient accurate analysis of the large-scale problems. Coupled with the ACE3P electromagnetic modules, this capability complements a set of multi-physics tools for a comprehensive study of microphonics in superconducting accelerating cavities in order to understand the RF response and feedback requirements for the operational reliability of a particle accelerator. (auth)

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Deployment of Dynamic Neural Network Optimization to Minimize Heat Rate During Ramping for Coal Power Plants (Final Technical Report)

Much success was achieved throughout the course of this project. A successful implementation of Dynamic Neural Network Optimization (D-NNO) was coupled with Adaptive Predictive Controls (APC) and a novel hardware installation comprised of an advanced sensor network (ASN) measuring mass-weighted averages of flue gas constituents above the horizontal superheater of a coal-fired utility boiler. From 2019 through 2023 (including an extension due to COVID delays), the team was able to prototype, evaluate, deploy, iterate, and ultimately finalize an advanced closed-loop control D-NNO system which demonstrated the ability to: •improve unit efficiency ~2.0% relative to unoptimized operation (represented as total fuel fired per MWh generated) •improve unit NOx emission rates 10%+ beyond static optimization baselines •improve unit temperature stability as much as 58% and on average 12% •improve operating load stability as much as 35% The culmination of this project has generated an advanced methodology of deploying specially designed recurrent neural networks (long short-term memory, gated recurrent unit, encoder-decoder networks, transformers, etc.), customized trajectory planning and closed-loop optimization modules capable of adapting to live electric grid responses and demands, self-tuning and adaptive expert controls constantly adjusting prediction parameters to real-time unit behavior, and a hardware/software package able to reliably calculate net unit heat rate (NUHR) in real-time using flue gas constituents, machine learning, and known combustion relationships. Through this real-time NUHR value, immediate feedback on system adjustments relative to operating efficiency was available, allowing for rapid improvements to system performance. In addition to development and deployment of the advanced D-NNO system, the approach methodology has been readily commercialized through the project platform Griffin Open Systems, LLC, the D-NNO software platform host. Similar methodologies to those developed by this project have already been deployed at 5 other units across the United States, with another 6 implementations scheduled, and more expected. Over the course of the project, multiple academic papers were submitted and accepted for publication within esteemed academic journals, and PhD students were trained and graduated, as well as undergraduate students becoming involved and participating to project objectives.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Selective consolidation of learning and memory via recall-gated plasticity

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Selective consolidation of learning and memory via recall-gated plasticity

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

Lindsey, Jack W. (ORCID:0000000309307327)↗
NASA NTRS1973

High efficiency ground data transmission

It is demonstrated that state-of-the-art communications technology can be implemented and reliably operated on a global basis to increase the transmission rates and efficiencies on circuits with bandwidths greater than the typical speech channel. Optimization is affected by optimum clock recovery procedures, multilevel pulse amplitude modulation, single sideband amplitude modulation, transversal filter equalizers, data scrambling, and active compensation for phase instability.

Dickinson, W. B.↗
NASA NTRS1979

Orifice calibration module

Module, consisting of transparent plastic cylinder containing separate suction and calibration chambers, allows static-pressure orifices to be calibrated, and rapidly checked for leaks. Device is compact, saves time, and improves accuracy, and reliability of pressure measurements.

Culotta, R.↗
NASA NTRS1980

Status of nickel-hydrogen cell technology

Nickel hydrogen cell technology has been developed which solves the problems of thermal management, oxygen management, electrolyte management, and electrical and mechanical design peculiar to this new type of battery. This technology was weight optimized for low orbit operation using computer modeling programs but is near optimum for other orbits. Cells ranging in capacity up to about 70 ampere-hours can be made from components of a single standard size and are available from two manufacturers. The knowledge gained is now being applied to the development of two extensions to the basic design: a second set of larger standard components that will cover the capacity range up to 150 ampere-hours; and the development of multicell common pressure vessel modules to reduce volume, cost and weight. A manufacturing technology program is planned to optimize the producibility of the cell design and reduce cost. The most important areas for further improvement are life and reliability which are governed by electrode and separator technology.

Warnock, D. R.↗
NASA NTRS1984

Fracture behavior in silicon

The fracture mechanics of crystalline Si are reviewed, together with known techniques for minimizing the occurences of fracture and/or their effects. The fracture toughness (Kic) of Si varies only 10 percent from cell-to-cell and standard values have been established for different types of crystalline Si cells. A critical flaw size of 10-100 microns has been identified, and also pertains to polycrystalline materials. Chemical polishing is known to double the value of Kic, while edge rounding has no effect. Internal stresses, particularly those caused during ribbon growth, do not exceed 10 percent of Kic. External stresses are imposed by the module hardware and the ambient environment. Multiple contacts reduce the effects of cell fracture and series-parallel wiring in modules in arrays ameliorates the effects of single-cell failures. During manufacturing, maintenance of quality control and removal of sheets displaying aberrations can, depending on the costs and the implementation of the array reliability features, result in arrays delivering any desired level of reliability.

Leipold, M. H.↗
NASA NTRS1991

Multi-reactor power system configurations for multimegawatt nuclear electric propulsion

A modular, multi-reactor power system and vehicle configuration for piloted nuclear electric propulsion (NEP) missions to Mars is presented. Such a design could provide enhanced system and mission reliability, allowing a comfortable safety margin for early manned flights, and would allow a range of piloted and cargo missions to be performed with a single power system design. Early use of common power modules for cargo missions would also provide progressive flight experience and validation of standardized systems for use in later piloted applications. System and mission analysis are presented to compare single and multi-reactor configurations for piloted Mars missions. A conceptual design for the Hydra modular multi-reactor NEP vehicle is presented.

George, Jeffrey A.↗
NASA NTRS2011

Thermally Stabilized Transmit/Receive Modules

RF-hybrid technologies enable smaller packaging and mass reduction in radar instruments, especially for subsystems with dense electronics, such as electronically steered arrays. We are designing thermally stabilized RF-hybrid T/R modules using new materials for improved thermal performance of electronics. We are combining advanced substrate and housing materials with a thermal reservoir material, and develop new packaging techniques to significantly improve thermal-cycling reliability and performance stability over temperature.

thermal cycling stress↗
NASA NTRS1999

Analog Module Architecture for Space-Qualified Field-Programmable Mixed-Signal Arrays

Spacecraft require all manner of both digital and analog circuits. Onboard digital systems are constructed almost exclusively from field-programmable gate array (FPGA) circuits providing numerous advantages over discrete design including high integration density, high reliability, fast turn-around design cycle time, lower mass, volume, and power consumption, and lower parts acquisition and flight qualification costs. Analog and mixed-signal circuits perform tasks ranging from housekeeping to signal conditioning and processing. These circuits are painstakingly designed and built using discrete components due to a lack of options for field-programmability. FPAA (Field-Programmable Analog Array) and FPMA (Field-Programmable Mixed-signal Array) parts exist but not in radiation-tolerant technology and not necessarily in an architecture optimal for the design of analog circuits for spaceflight applications. This paper outlines an architecture proposed for an FPAA fabricated in an existing commercial digital CMOS process used to make radiation-tolerant antifuse-based FPGA devices. The primary concerns are the impact of the technology and the overall array architecture on the flexibility of programming, the bandwidth available for high-speed analog circuits, and the accuracy of the components for high-performance applications.

Edwards, R. Timothy↗
DOE OSTI2015

Vibrationally resolved NEXAFS at C and N K-edges of pyridine, 2-fluoropyridine and 2,6-difluoropyridine: A combined experimental and theoretical assessment

In the present work, the near edge X-ray absorption spectroscopy (NEXAFS) spectra at both C and N K-edges of pyridine, 2-fluoropyridine, and 2,6-difluoropyridine have been studied both experimentally and theoretically. From an electronic point of view, both transition potential density functional theory and time-dependent density functional theory approaches lead to reliable results provided that suitable basis sets and density functionals are employed. In this connection, the global hybrid B3LYP functional in conjunction with the EPR-III basis set appears particularly suitable after constant scaling of the band positions. For the N K-edge, vertical energies obtained at these levels and broadened by symmetric Gaussian distributions provide spectra in reasonable agreement with the experiment. Vibronic contributions further modulate the band-shapes leading to a better agreement with the experimental results, but are not strictly necessary for semi-quantitative investigations. On the other hand, vibronic contributions are responsible for strong intensity redistribution in the NEXAFS C K-edge spectra, and their inclusion is thus mandatory for a proper description of experiments. In this connection, the simple vertical gradient model is particularly appealing in view of its sufficient reliability and low computational cost. For more quantitative results, the more refined vertical Hessian approach can be employed, and its effectiveness has been improved thanks to a new least-squares fitting approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Encoding multistate charge order and chirality in endotaxial heterostructures

Abstract High-density phase change memory (PCM) storage is proposed for materials with multiple intermediate resistance states, which have been observed in 1 T -TaS 2 due to charge density wave (CDW) phase transitions. However, the metastability responsible for this behavior makes the presence of multistate switching unpredictable in TaS 2 devices. Here, we demonstrate the fabrication of nanothick verti-lateral H -TaS 2 /1 T -TaS 2 heterostructures in which the number of endotaxial metallic H -TaS 2 monolayers dictates the number of resistance transitions in 1 T -TaS 2 lamellae near room temperature. Further, we also observe optically active heterochirality in the CDW superlattice structure, which is modulated in concert with the resistivity steps, and we show how strain engineering can be used to nucleate these polytype conversions. This work positions the principle of endotaxial heterostructures as a promising conceptual framework for reliable, non-volatile, and multi-level switching of structure, chirality, and resistance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗