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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Residential Battery Modeling for Control-Oriented Techno-Economic Studies: Preprint

Electrochemical batteries, which serve as electric energy storage devices, are becoming increasingly popular among residential buildings that incorporate solar photovoltaic (PV) systems to help meet their energy needs. Battery economics are affected by performance degradation over time, and managing this degradation can help extend the battery's lifespan. The tradeoff between operational costs/benefits and managing battery degradation is of significant research interest. One of the key factors for assessing battery degradation is the dispatch strategy used to control the charging and discharging of the battery. Conventional dispatch strategies typically use simple rule-based methods, and these overly aggressive charging/discharging cycles can significantly reduce a battery’s life span. Our research seeks to develop optimized dispatch strategies for grid-connected PV homes with a goal of extending battery life while simultaneously taking into consideration utility costs and occupant comfort. To achieve this goal, we adapted lithium-ion battery life- and cyclic-degradation models for use in high-fidelity building simulations, so whole-building and grid-interactive controllers can dispatch the batteries along with other flexible loads. With the help of a co-simulation platform, we performed a simulation study to compute the optimized dispatch strategies for relevant operating conditions brought about by changing geographical locations, weather conditions, and utility pricing. Comparing the optimized strategies with the conventional strategies resulted in a >50% decrease in capacity degradation and >10% average reduction in operational costs during the months of January and July in Fort Collins, Colorado; Phoenix, Arizona; and Portland, Oregon.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Transition-metal doped titanate nanowire photocatalysts boosted by selective ion-exchange induced defect engineering

Defect engineering through elemental doping is an efficient way to boost the performance of semiconductor photocatalysts. For this work, transition-metal (TM) doped titanate nanowires (TNWs) were prepared via ion-exchange over the titanate precursors and demonstrated for the Rhodamine B (RhB) degradation under ultraviolet (UV) light irradiation. The ion-exchange of selective ions (V 5+ , Cr 3+ , Ni 2+ , and Zn 2+ ) with protons from pristine TNWs resulted in the hierarchical meso-porosity of nanowires with large pores of ~5–20 nm by TM doping and small pores of ~3.6–4.5 nm inherited from pristine TNWs, which facilitates the mass transfer while maintaining high surface area and active sites. Meanwhile, the TM intercalation partially reduces the Ti 4+ to Ti 3+ and narrows the optical bandgap, which, together with oxygen vacancies and superoxide radicals from pristine TNWs, enhance the adsorption and photocatalytic degradation performance of RhB. This work helps to elucidate the effects of transition-metal doping and provides a rational strategy towards high performance titanate-based photocatalysts for efficient and sustainable wastewater treatment.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A leaf-level spectral library to support high-throughput plant phenotyping: predictive accuracy and model transfer

Abstract Leaf-level hyperspectral reflectance has become an effective tool for high-throughput phenotyping of plant leaf traits due to its rapid, low-cost, multi-sensing, and non-destructive nature. However, collecting samples for model calibration can still be expensive, and models show poor transferability among different datasets. This study had three specific objectives: first, to assemble a large library of leaf hyperspectral data (n=2460) from maize and sorghum; second, to evaluate two machine-learning approaches to estimate nine leaf properties (chlorophyll, thickness, water content, nitrogen, phosphorus, potassium, calcium, magnesium, and sulfur); and third, to investigate the usefulness of this spectral library for predicting external datasets (n=445) including soybean and camelina using extra-weighted spiking. Internal cross-validation showed satisfactory performance of the spectral library to estimate all nine traits (mean R2=0.688), with partial least-squares regression outperforming deep neural network models. Models calibrated solely using the spectral library showed degraded performance on external datasets (mean R2=0.159 for camelina, 0.337 for soybean). Models improved significantly when a small portion of external samples (n=20) was added to the library via extra-weighted spiking (mean R2=0.574 for camelina, 0.536 for soybean). The leaf-level spectral library greatly benefits plant physiological and biochemical phenotyping, whilst extra-weight spiking improves model transferability and extends its utility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Device Feasibility Analysis of Multi-level FeFETs for Neuromorphic Computing

As an emerging non-volatile memory device technology, Ferroelectric Field-Effect Transistors (FeFETs) can enable low-power, adaptive intelligent system design. However, device dimension and operating voltage dependent reliability issues of scaled FeFETs can ultimately lead to degraded performance in solving machine learning tasks. In this article, detailed experimental characterization of FeFET devices of different dimensions have been carried out to explicitly evaluate the non-ideal behavior in device conductance programming properties like number of programming states, cycle-to-cycle (C2C) variations, device-to-device (D2D) variations, and state retention. A hardware-aware software simulation approach has been adopted to capture the adversarial effects of the non-idealities on recognition accuracy through algorithm-level performance assessment by including them in NeuroSim, a popular neural network hardware simulator, to execute a neural network model considering all other hardware constraints. With the added non-idealities, significant accuracy degradation has been observed compared to the ideal scenarios where D2D variations play the most critical role. Thereafter, feasibility of a variation-aware training method has been evaluated to tackle the accuracy drop.

42 ENGINEERING↗
DOE OSTI2023

PV encapsulant formulations and stress test conditions influence dominant degradation mechanisms

Polyethylene-based poly(ethylene-co-vinyl acetate) (EVA), polyolefin elastomer (POE), and thermoplastic polyolefin (TPO) are common polymer candidates for photovoltaic (PV) module encapsulants. The choice of encapsulant must be carefully considered in novel module designs, such as bifacial glass/glass laminates, to limit performance degradation through loss of optical transmittance, mechanical integrity, and corrosion - as well as potential-induced degradation. Encapsulant quality and resilience against environmental stressors are readily influenced by the additives in the encapsulant formulation. Here, we show that, the changes in optical transmittance after UV aging result from the discoloration caused by interactions between additives, and optical scattering from changes in the polymer crystal structure. We observed competing cross-linking and chain scission mechanisms, with their kinetics influenced by the presence of oxygen and elevated temperatures. Increasing chamber temperatures from 55 °C to 85 °C during the UV stress test amplified encapsulant discoloration and promoted polymer cross-linking, causing severe, irreversible damage that remains to be proven field relevant. Damp heat aging was found to be insufficient to produce significant encapsulant degradation; however, combining stress tests sequentially allowed detection of further degradation beyond the limitations of the damp heat test alone. Appropriate degradation screening methods are necessary to uncover potential encapsulant weaknesses.

14 SOLAR ENERGY↗
DOE OSTI2021

Evaluation of hybrid evaporative-vapor compression air conditioners for different global climates

Currently, a majority of global residential air-conditioning requirements are met using cooling systems based on the vapor compression cycle (VCC). To meet the future demand for space cooling and to reduce the corresponding environmental impact, there is a need for alternative cooling systems which require less resources and exhibit a higher coefficient of performance (COP). One of proposed alternatives is called the hybrid evaporative-vapor compression (HEVC) cycle, which utilizes adiabatic latent cooling in combination with the VCC. In this paper, we conducted a feasibility analysis of a HEVC system by comparing its performance to that of VCC for various global climates. To accomplish this, we developed and validated models to simulate the performance of residential VCC and HEVC systems. ASHRAE weather data and design conditions were then used to compare the performance of the two systems. In general, HEVC systems are best suited for hot arid climates with energy reduction greater than 20%. Conversely, humid climates are not suitable for HEVC adoption due to degraded performance of evaporative coolers in these climates. In addition to comparing the energy savings from HEVC systems, it is also critical to analyze their water consumption. Generally, climates that benefit the most from HEVC technology tend to also experience water scarcity issues. Thus, both the energy savings and water consumption of HEVC systems must be analyzed to guide the discussion on their adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

A Feasibility Study on the Integration of Human Performance Data From Diverse Sources Based on the Complexity of a Proceduralized Task

Securing the safety of socio-technical systems including nuclear facilities is the upmost goal to ensure their sustainability because historical records demonstrate that the performance degradation of human operators (e.g., human errors) is one of the crucial contributors to the occurrence of unexpected events resulting in extensive casualties and financial losses. This implies that the collection of human performance data in diverse conditions with which they could be faced during the operation of nuclear facilities. As this collection requires significant resources, it is necessary to resolve how to accomplish it with limited resources. To address this challenge, as suggested in the SHEEP framework, it is indispensable to extract valuable insights after integrating various kinds of human performance data obtained from different sources. However, a practical method to soundly integrate them seems to be still incomplete. Accordingly, the applicability of TACOM (Task Complexity) measure is investigated as a tool to identify useful information based on the integration of human performance data observed from different simulation conditions. As a result, it is expected that the TACOM measure would play an important role in addressing the technical challenge in securing human performance data.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Improving durability and performance of solid oxide electrolyzers by controlling surface composition on oxygen electrodes

Solid oxide electrolysis cell (SOEC) is a promising technology for high-efficiency energy conversion, enabling the production of hydrogen, syngas, synthetic fuels, and various commodity chemicals. Unlike traditional thermochemical processes, SOECs operate at elevated temperatures (600-850°C), benefiting from favorable thermodynamics and reaction kinetics. This makes them highly energy efficient compared to alkaline or polymer electrolyte membrane (PEM) electrolysis technologies. However, despite these advantages, SOECs face significant challenges related to performance degradation over time. A primary issue is the degradation of the oxygen electrode due to strontium (Sr) segregation and impurity poisoning from chromium (Cr) and sulfur (S). This is because the pathway to deposition of Cr and S include the reaction of Cr and S with the segregated SrO at the surface. Sr segregation leads to the formation of insulating compounds such as SrCrO4 and SrSO4, which block active sites, reduce oxygen exchange rates, and compromise the electrode's electrochemical stability. The degradation mechanisms involve complex interactions between the electrode material's surface chemistry, microstructure, and the operating environment. Sr segregation is particularly problematic because it facilitates the deposition of Cr and S impurities, exacerbating performance losses. Addressing these issues is critical to enhancing the durability and economic viability of SOEC technology. The primary goal of this project is to improve the durability and performance of SOECs by controlling the surface composition of the oxygen electrode. This is achieved by suppressing Sr segregation, thereby mitigating impurity poisoning pathways. The project aims to enhance the oxygen exchange rate, improve cell stability, and extend the operational lifespan of SOECs without necessitating major changes to electrode chemistry or stack components.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Adhesively Bonded Copper and Polyimide for Flexible Printed Circuit Boards: A Data-Driven Degradation Study Under Accelerated Aging

The long-term durability of polyimide laminated adhesive based flexible printed circuit boards (PCBs) is critical to the microelectronics industry. The interface of the adhesive layer binding the polyimide and copper layers is particularly vulnerable since decreased bonding strength can lead to deadhesion, performance loss, and premature device failure. Here, in this study, adhesive-bonded polyimide and copper samples are subjected to 1000 h of damp heat exposure (85 °C/85%RH) to evaluate the impact of moisture and copper inclusion on the adhesive bonding performance. Significant copper diffusion through the adhesive layer is observed, which, combined with moisture uptake, is found to substantially weaken interfacial adhesion in copper-containing samples, thereby reducing device lifetime. Observed surface and bulk material changes are correlated to adhesion strength using the network structural equation modeling (netSEM) approach, resulting in a robust predictive model of performance degradation based on measurable materials properties.

Chemistry↗
DOE OSTI2026

Overview of the KSTAR experiments and future plan

The Korea Superconducting Tokamak Advanced Research (KSTAR) device has recently entered a new phase of operation following the installation of a tungsten mono-block divertor, providing a unique platform to investigate high-performance, long-pulse plasma scenarios for future reactors. The 2023–2024 experimental campaigns demonstrated significant progress in commissioning the tungsten divertor, developing plasma operation scenarios, and achieving real-time control. Comparative studies revealed increased core radiation losses and associated performance degradation relative to the carbon divertor environment. Alleviation strategies, such as optimized neutral beam injection timing, boron powder seeding, and impurity control through gas puffing, were shown to reduce tungsten accumulation and extend high-performance phases, including record H-mode operation exceeding 100 s. International collaboration enabled the first demonstration of high poloidal beta scenarios with an internal transport barrier on KSTAR. Advances in control included upgraded real-time resonant magnetic perturbation schemes and disruption forecasting. Furthermore, divertor detachment control using a new surrogate-model-based approach with real-time radiation imaging demonstrated active impurity and heat flux management. Supported by enhanced heating, current drive, and diagnostic systems, these achievements offer valuable insights into tungsten impurity behavior, transport physics, and control strategies for future reactors including ITER. Planned upgrades toward a full-tungsten wall and ITER-aligned real-time plasma control will further establish KSTAR as a leading experimental platform for developing operational scenarios required to achieve steady-state, burning plasma conditions.

KSTAR↗
DOE OSTI2023

GaAs solar cells grown on acoustically spalled GaAs substrates with 27% efficiency

Acoustic spalling presents a potentially low-cost reuse pathway for III–V epitaxial growth substrates via exfoliation of device layers with recovery and reuse of the substrate. However, surface features formed during spalling can reduce the performance of subsequently grown devices. Here, we develop an understanding of how the surface morphology of acoustically spalled substrates affects GaAs solar cell performance and develop strategies to mitigate these impacts. We demonstrate that minor planarization of the surface by wet chemical etching and/or epitaxial growth, or the redesign of the device structure to thicken critical layers, prevents performance degradation. Using these strategies, we demonstrate a 0.25 cm 2 single-junction GaAs device with 26.9% ± 0.2% photovoltaic conversion efficiency under the AM1.5G spectrum grown on an acoustically spalled substrate. These results enable the growth of high-performance III–V devices on non-traditional substrates with the potential for significantly reduced device costs.

14 SOLAR ENERGY↗
DOE OSTI2026

INR-TEM: Robust cavity detection in multifocus TEM images via implicit neural representations

When characterizing materials using transmission electron microscopy (TEM) images, detecting and quantifying small features in microstructures, such as cavities, pose significant challenges. Off-the-shelf object detection models, including YOLOv8, show considerable performance degradation, particularly when images vary in resolution and the objects of interest possess a low percentage of the total image region of interest. In this study, we introduce a novel detection pipeline that incorporates an implicit neural representation (INR)-based detection method, INR-TEM, and two-modality imaging (e.g., under-focused and over-focused images typically acquired during materials characterization) to improve object detection performance. The INR-TEM method incorporates a pixel-wise prediction principle inspired by pixel-wise centerness weighting. INR-TEM demonstrates superior robustness to resolution variability, maintaining high detection accuracy even at low image resolutions compared to YOLOv8. To leverage INR-TEM effectively in real-world two-modality characterization applications, we further integrate a two-stage motion correction pipeline designed explicitly for aligning multifocus TEM images. The alignment process, comprising keypoint (based on scale-invariant feature transform, SIFT) and intensity matching, significantly mitigates the adverse effects of perceived motion-induced image degradation during through-focal TEM imaging, directly enhancing INR-TEM’s detection capability over conventional single-focus images. Our integrated INR-TEM cavity detection framework notably improves performance across various cavity sizes, outperforming off-the-shelf YOLOv8 detections that rely on a single image modality.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

An implicit barotropic mode solver for MPAS-ocean using a modern Fortran solver interface

Here, we demonstrate use of a modern Fortran solver interface to manage solver algorithms for an implicit barotropic mode solver in the Model for Predictions Across Scales-Ocean (MPAS-O). ForTrilinos, a Fortran interface to Trilinos that contains a large collection of solver capabilities written in C++, has been implemented in MPAS-O to provide access to a suite of linear solver options. By virtue of the simplified wrapper and interface generator (SWIG) automation tool that generates modern Fortran interfaces to C++ code, we were able to implement the Fortran solver interface in MPAS-O using a familiar Fortran coding style while minimizing performance degradation. The ForTrilinos solver interface is written within MPAS-O’s time stepping modules as a subroutine in conjunction with MPAS-O code. Applied to an idealized ocean and a high-resolution realistic ocean test case, parallel performance of ForTrilinos solvers is examined. It is found that parallel scalability of the ForTrilinos solvers is highly dependent on the number of global synchronization points per solver iteration in each iterative solver algorithm. ForTrilinos solvers perform best compared to the Fortran hand-crafted (FHC) solver when the amount of work per processor is large enough. However, parallel scalability is better with the FHC solver and so when the work per core is modest FHC outperforms ForTrilinos. The intercomparison between the ForTrilinos and FHC solvers reveals that this performance hit in the ForTrilinos solver mostly comes from the global synchronization process, while suggesting that the matrix-vector multiplication process in the FHC solver needs to be optimized for better performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Optimization of the light detection system of the ICARUS detector

The Short Baseline Neutrino (SBN) Program at Fermilab is designed to investigate short-baseline neutrino oscillations and test the hypothesis of sterile neutrinos, motivated by several experimental anomalies observed over the past decades. Within this program, the ICARUS experiment plays a key role. It employs the world’s largest Liquid Argon Time Projection Chamber (LArTPC) and serves as the farthest and most sensitive SBN detector for studying muon and electron neutrino oscillations. A crucial subsystem of the ICARUS detector is the Light Detection System (LDS), which captures the prompt scintillation light produced by neutrino interactions in the 600-ton active liquid Argon volume. This system provides precise timing information that is essential for event reconstruction, the trigger system, and cosmic background rejection. The LDS is composed of 360 Hamamatsu R5912-MOD 8-inch photomultiplier tubes (PMTs), operating under cryogenic conditions ($\sim 87 \ K$) inside the detector’s cryostats. During the detector’s operation at FNAL, a degradation in PMT gain has been observed, attributed to aging under low-temperature conditions. In collaboration with ICARUS teams from INFN Pavia and Catania, I developed an experimental setup to study the temperature-dependent behavior of the PMTs, performing gain measurements both at room temperature and down to $-70°C$ using a climatic chamber at INFN Catania. The results indicate that while the PMTs maintain stable gain at room temperature, a significant and permanent gain reduction occurs at low temperatures. Although $-70°C$ is still warmer than liquid Argon temperatures, the findings clearly demonstrate a gain-dependent performance degradation. The thesis also discusses mitigation strategies implemented in the ICARUS detector to address this issue and presents a simplified model to describe and simulate the observed behavior.

Saia, Clara [Catania U.] (ORCID:0009000464102417)↗
DOE OSTI2026

Review on Perovskite Solar Cells: From Single‐Junction Devices to Tandem Deployment in Space

Perovskite solar cells (PSCs) have emerged as a transformative photovoltaic technology, offering high power conversion efficiency (PCE) and the potential for cost-effective manufacturing. However, stability and large-scale manufacturing remain critical challenges that must be addressed for widespread adoption. This review provides a roadmap from single-junction perovskite solar cells to tandem deployment in space. First, material-level innovations are discussed, including mixed-cation and low-dimensional perovskites, transport materials, and additives that improve thermal and structural stability while enhancing efficiency. Then, we examine both established industrial standards and emerging scientific protocols aimed at stabilizing PSCs under operational conditions, including tandem cell integration strategies and encapsulation techniques to mitigate performance degradation. Manufacturing scalability is a focal point, where deposition methods and green solvents are explored to improve large-area film uniformity and reduce environmental impact. Additionally, the increasing viability of PSCs in extraterrestrial environments is assessed, with emphasis on their performance in space applications, radiation resistance, and flexible lamination methods for deployment in extreme conditions. Progress across materials innovation, device architectures, stability testing protocols, and both terrestrial and extraterrestrial applications collectively drives perovskite photovoltaics toward higher efficiency, stability, and cost-effectiveness.

flexible PSCs↗
DOE OSTI2022

Inferences of hot electron preheat and its spatial distribution in OMEGA direct drive implosions

Hot electrons generated from laser plasma instabilities degrade performance of direct drive implosions by preheating the deuterium and tritium (DT) fuel resulting in early decompression and lower areal densities at stagnation. A technique to quantify the hot electron preheat of the dense DT fuel and connect it to the degradation in areal density is described in detail. Hot electrons are measured primarily from the hard x-rays they emit as they slow down in the target. The DT preheat is inferred from a comparison of the hard x-ray signals between a DT-layered implosion and its mass equivalent ablator only implosion. The preheat energy spatial distribution within the imploding shell is inferred from experiments using high Z payloads of varying thicknesses. It is found that the electrons deposit their energy uniformly throughout the shell material. For typical direct-drive OMEGA implosions driven with an overlapped intensity of ∼9·1014 W/cm2, approximately ∼0.02%–0.03% of the laser energy is converted into preheat of the stagnated fuel which corresponds to areal density degradations of 10%–20%. The degradations in areal density explain some of the observed discrepancies between the simulated and measured areal densities.

Christopherson, A. R. (ORCID:000000033578635X)↗
DOE OSTI2024

BCSR on GPU: A Way Forward Extreme-scale Graph Processing on Accelerator-enabled Frontier Supercomputer

Handling large graphs in a distributed environment requires effective partitioning across processors and efficient management of local partitions. In 2D partitioning, local graphs often become too sparse, making memory-efficient data structures crucial. Using the Compressed Sparse Row (CSR) format wastes space, especially for > 83% of vertices with empty edges for the sparse graphs. This study explores bit-CSR (BCSR), a modified CSR representation, on GPUs to reduce memory usage in graph computations. We achieved 16.67% memory savings on a sparse rmat dataset with 268 million vertices and 357 million edges, without performance degradation, supported by both theoretical and experimental storage savings of 33%. However, we observed a 1.7× slowdown in degree lookup times due to bitwise operations on AMD CPUs. This analysis highlights the potential of BCSR on GPUs for improving Graph500 benchmark performance on GPU-accelerated systems, such as the Frontier supercomputer.

Sattar, Naw Safrin↗
DOE OSTI2021

Perform Life Cycle Energy and GHG Emission Analysis, Select Candidate Refrigerant(s), Developing Heat Pump by Using Low-GWP Refrigerants and 5 mm Diameter Tubes

Reducing environmental impacts from the energy conversion systems has been an important research topic due to recent severe global climate changes. In residential buildings, the space heating and cooling are main energy consumers, which are relying on vapor compression based heat pumps. To mitigate the environmental impacts of residential systems, the heat pumps using low-GWP refrigerants and 5mm-tube heat exchangers are proposed to replace the conventional 9 mm or 7 mm tube heat exchangers. This research uses a simulation-based design method to optimize the refrigerant circuitries of a 5-ton low-GWP refrigerant heat pumps whose indoor and outdoor heat exchangers adopt 5 mm tubes. Heat pump systems using four commercially available low-GWP refrigerants (R454A, R454C, ARM20A and ARM20B) are optimized and compared with the baseline R410A system. The results indicate that directly replacing 9 mm tubes into 5mm tubes in the baseline systems induces heat pump performance degradation; by optimizing the 5 mm tube heat pumps with added tube rows, the system refrigerant charge is reduced up to 33% compared with the baseline; the optimized low-GWP 5 mm tube heat pumps offer the same or higher performance under both cooling and heating mode; that under cooling mode, the EER improvement is up to 10.7% and under heating mode the COP improvement is up to 3.4%; and a smart flow control device to maintain counter-flow circuitry pattern on both operating modes can improve the heating performance of 5 mm tube optimized system by up to 3.0%. In an effort to better understand the environmental impacts of these systems, life cycle climate performance (LCCP) evaluation method is used to assess the baseline and optimized systems. LCCP considers the direct and indirect emissions of the system over the course of its lifetime from manufacturing to disposal. Our analyses indicate that the optimized systems using 5mm tubes and low-GWP refrigerants can reduce life-cycle CO 2 emission significantly. And improving system efficiency is the most effective way to reduce the emission of low-GWP refrigerant systems. This report shows that using 5 mm diameter tubes in heat exchangers is a feasible approach to develop heat pumps with low-GWP refrigerants. Using the proposed design approach can yield higher system efficiency with lower environmental impact.

42 ENGINEERING↗