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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Instability seeding mechanisms due to internal defects in inertial confinement fusion targets

Performance degradation in laser-driven inertial confinement fusion (ICF) implosions is caused by several effects, one of which is Rayleigh–Taylor instability growth. Defects in ICF targets, such as internal voids and surface roughness, create instability seeds in the shell as shocks propagate through the target. A comprehensive understanding of seeding mechanisms is essential to characterize the impact of target defects on inflight shell integrity and mass injection into the central, lower-density vapor region. An analysis of early-time behavior of both single-mode shell mass modulations and isolated voids is performed by examining the evolution of the acoustic waves launched by these target imperfections. A systematic study of localized perturbation growth as a function of defect placement and size is presented. Furthermore, the use of low-density ablator materials (such as foams) is suggested as a potential mitigation strategy to improve target robustness against the impact of defect-initiated growth.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Binder-Free Cnt Cathodes for Li-O 2 Batteries with More Than One Life

Li-O 2 batteries (LOB) performance degradation ultimately occurs through the accumulation of discharge products and irreversible clogging of the porous electrode during the cycling. Electrode binder degradation in the presence of reduced oxygen species can result in additional coating of the conductive surface, exacerbating capacity fading. Herein, a facile method to fabricate free-standing is established, binder-free electrodes for LOBs in which multi-wall carbon nanotubes form cross-linked networks exhibiting high porosity, conductivity, and flexibility. These electrodes demonstrate high reproducibility upon cycling in LOBs. After cell death, efficient and inexpensive methods to wash away the accumulated discharge products are demonstrated, as reconditioning method. The second life usage of these electrodes is validated, without noticeable loss of performance. These findings aim to assist in the development of greener high energy density batteries while reducing manufacturing and recycling costs.

25 ENERGY STORAGE↗
DOE OSTI2022

Low power implementation of high frequency SiPM readout for Cherenkov and scintillation detectors in TOF-PET

State-of-the-art (SoA) electronic readout for silicon photomultiplier (SiPM)-based scintillation detectors that demonstrate experimental limits in achievable coincidence time resolution (CTR) leverage low noise, high frequency signal processing to facilitate a single photon time response that is near the limit of the SiPMs architecture. This readout strategy can optimally exploit fast luminescence and prompt photon populations, and promising measurements show detector concepts employing this readout can greatly advance PET detector CTR, relative to SoA in clinical systems. However, the technique employs power hungry components which make the electronics chain impractical for channel-dense time-of-flight (TOF)-PET detectors. We have developed and tested a low noise and high frequency readout circuit which is performant at low power and consists of discrete elements with small footprints, making it feasible for integration into TOF-PET detector prototypes. A 3 × 3 mm 2 Broadcom SiPM with this readout chain exhibited sub-100 ps single photon time resolution at 10 mW of power consumption, with a relatively minor performance degradation to 120 ± 2 ps FWHM at 5 mW. CTR measurements with 3 × 3 × 20 mm 3 LYSO and fast LGSO scintillators demonstrated 127 ± 3 ps and 113 ± 2 ps FWHM at optimal power operation and 133 ± 2 ps and 121 ± 3 ps CTR at 5 mW. BGO crystals 3 × 3 × 20 mm 3 in size show 271 ± 5 ps FWHM CTR (1174 ± 14 ps full-width-at-tenth-maximum (FWTM)) at optimal power dissipation and 289 ± 8 ps (1296 ± 33 ps FWTM) at 5 mW. The compact and low power readout topology that achieves this performance thereby offers a platform to greatly advance PET system CTR and also opportunities to provide high performance TOF-PET at reduced material cost.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Stabilized Co-Free Li-Rich Oxide Cathode Particles with An Artificial Surface Prereconstruction

Li-rich metal oxide (LXMO) cathodes have attracted intense interest for rechargeable batteries because of their high capacity above 250 mAh g –1 . However, the side effects of hybrid anion and cation redox (HACR) reactions, such as oxygen release and phase collapse that result from global oxygen migration (GOM), have prohibited the commercialization of LXMO. GOM not only destabilizes the oxygen sublattice in cycling, aggravating the well-known voltage fading, but also intensifies electrolyte decomposition and Mn dissolution, causing severe full-cell performance degradation. In this study, an artificial surface prereconstruction (ASR) for Li 1.2 Mn 0.6 Ni 0.2 O 2 particles with a molten-molybdate leaching is conducted, which creates a crystal-dense anion-redox-free LiMn 1.5 Ni 0.5 O 4 shell that completely encloses the LXMO lattice (ASR-LXMO). Differential electrochemical mass spectroscopy and soft X-ray absorption spectroscopy analyses demonstrate that GOM is shut down in cycling, which not only stabilizes HACR in ASR-LXMO, but also mitigates the electrolyte decomposition and Mn dissolution. ASR-LXMO displays greatly stabilized cycling performance as it retains 237.4 mAh g –1 with an average discharge voltage of 3.30 V after 200 cycles. More crucially, while the pristine LXMO cycling cannot survive 90 cycles in a pouch full-cell matched with a commercial graphite anode and lean (2 g A –1 h –1 ) electrolyte, ASR-LXMO shows high capacity retention of 76% after 125 cycles in full-cell cycling.

25 ENERGY STORAGE↗
DOE OSTI2021

Evidence of Three-Dimensional Asymmetries Seeded by High-Density Carbon-Ablator Nonuniformity in Experiments at the National Ignition Facility

Inertial confinement fusion implosions must achieve high in-flight shell velocity, sufficient energy coupling between the hot spot and imploding shell, and high areal density ( ρ R = ∫ ρ d r ) at stagnation. Asymmetries in ρ R degrade the coupling of shell kinetic energy to the hot spot and reduce the confinement of that energy. In this study, we present the first evidence that nonuniformity in the ablator shell thickness ( ~ 0.5 % of the total thickness) in high-density carbon experiments is a significant cause for observed 3D ρ R asymmetries at the National Ignition Facility. These shell-thickness nonuniformities have significantly impacted some recent experiments leading to ρ R asymmetries on the order of ~ 25 % of the average ρ R and hot spot velocities of ~ 100 km / s . This work reveals the origin of a significant implosion performance degradation in ignition experiments and places stringent new requirements on capsule thickness metrology and symmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Models Integrated in Instrumentation & Control Systems

In recent years, the field of machine learning (ML), specifically neural networks, has grown significantly and has spurred research in its applicability to digital instrumentation and control systems (DI&C). While ML models have shown promise in operational contexts, the trustworthiness of using such algorithms has not been adequately assessed. Failures of ML integrated systems are not well understood, and the lack of comprehensive risk modeling can degrade the trustworthiness in these systems. In recent reports by the National Institute for Standards and Technology (NIST) [1] and the Nuclear Regulatory Commission (NRC) [2], they indicate that trustworthiness in ML is a critical barrier and will play a vital role in the safe, accountable, and secure operation of intelligent systems. Thus, in this work, we demonstrate a dynamic model-agnostic method to quantify the relative reliability of AI/ML predictions by incorporating out-of-distribution (OOD) detection on the training dataset. It is well documented that most ML algorithms excel at interpolation (or near-interpolation) tasks but experience significant performance degradation at extrapolation. The method, referenced as the Laplacian distributed decay for reliability (LADDR), determines the difference between the operational and training datasets which can used to the relative reliability of AI/ML predictions. LADDR is then demonstrated on a feedforward neural network based digital twin used for the prediction of safety significant factors during a loss-of-flow transient. LADDR is used to demonstrate how training data can be used as evidence to support the relative reliability of ML/AI predictions enhancing the overall trustworthiness of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Interfacial stabilization for inverted perovskite solar cells with long-term stability

Perovskite solar cells (PSCs) commonly exhibit significant performance degradation due to ion migration through the top charge transport layer and ultimately metal electrode corrosion. Here, we demonstrate an interfacial management strategy using a boron chloride subphthalocyanine (Cl 6 SubPc)/fullerene electron-transport layer, which not only passivates the interfacial defects in the perovskite, but also suppresses halide diffusion as evidenced by multiple techniques, including visual element mapping by electron energy loss spectroscopy. As a result, we obtain inverted PSCs with an efficiency of 22.0% (21.3% certified), shelf life of 7000 h, Τ 80 of 816 h under damp heat stress (compared to less than 20 h without Cl 6 SubPc), and initial performance retention of 98% after 2000 h at 80 °C in inert environment, 90% after 2034 h of illumination and maximum power point tracking in ambient for encapsulated devices and 95% after 1272 h outdoor testing ISOS-O-1. Our strategy and results pave a new way to move PSCs forward to their potential commercialization solidly.

14 SOLAR ENERGY↗
DOE OSTI2025

Substrate effects on phase formation and interfacial stability in superconducting vanadium silicide thin films

Thin films of vanadium silicide (V-silicide) in the A15 cubic phase (V 3 Si) are promising for superconducting quantum devices due to their high transition temperature and potential compatibility with scalable semiconductor fabrication. However, solid-phase synthesis often yields secondary silicide phases that degrade performance. Here, in this study, we investigate the influence of substrate properties using two silicon-on-insulator architectures: one with a polycrystalline HfO 2 buried layer (group A) and the other with amorphous SiO 2 (group B). Both systems exhibit superconductivity consistent with V 3 Si formation, yet structural analysis reveals mixed-phase films in both cases. Crucially, only group A maintains an atomically sharp and chemically stable interface, a prerequisite for phase purity. Prolonged annealing in group A reduces the unwanted V 5 Si 3 phase but also leads to the emergence of Si-rich VSi 2 , likely due to localized substrate degradation. Preliminary atomic-resolution imaging suggests that HfO 2 crystallinity may promote local phase-selective nucleation. These findings highlight the importance of substrate design in promoting phase control and maintaining interfacial integrity in superconducting silicides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Latticed-Confined Conversion Chemistry of Battery Electrode

The electrochemical conversion reaction, usually featured by multiple redox processes and high specific capacity, holds great promise in developing high energy rechargeable battery technologies. However, the complete structural change accompanied by spontaneous atomic migration and volume variation during the charge/discharge cycle leads to electrode disintegration and performance degradation, therefore severely restricting the application of conventional conversion-type electrodes. Herein, latticed-confined conversion chemistry is proposed, where the “intercalation-like” redox behavior is realized on the electrode with a “conversion-like” high capacity. By delicately formulating the high-entropy compounds, the pristine crystal structure can be preserved by the inert lattice framework, thus enabling an ultra-high initial Coulombic efficiency of 92.5% and a long cycling lifespan over a thousand cycles after the quasistatic charge–discharge cycle. This lattice-confined conversion chemistry unfolds a ubiquitous insight into the localized redox reaction and sheds light on developing high-performance electrodes toward next-generation high-energy rechargeable batteries.

25 ENERGY STORAGE↗
DOE OSTI2025

High-Intensity UV Exposure for the Rapid Screening of Silicon Photovoltaic Architectures

Advanced Si photovoltaic architectures incorporate different materials and processing pathways that influence degradation modes. Ultraviolet-induced degradation (UVID) is an understudied degradation mode for advanced cell architectures and is of increasing concern to industry due to growing adoption of UV-transparent encapsulation and bifacial technologies. In order to adopt new and evolving technologies confidently, novel component materials and processing techniques must be evaluated and designed for long-term stability, in addition to the conventional design focus on efficiency. In this work, a study protocol framework is presented for the rapid screening of unencapsulated devices against UVID. Unencapsulated passivated emitter rear contact (PERC) and tunnel oxide passivated contact (TOPCon) devices were aged under different UV irradiance intensities and measured via conventional nondestructive electrical characterization methods to assess performance degradation. Based on the results, protocol efficacy and recommendations for further study are discussed. As a result, this work is part of a broader effort to develop rapid screening processes that cut across architectures and exposure conditions to aid module manufacturers in vetting new materials choices for long-term stability.

Accelerated exposure↗
DOE OSTI2024

Protonation Stimulates the Layered to Rock Salt Phase Transition of Ni‐Rich Sodium Cathodes

Abstract Protonation of oxide cathodes triggers surface transition metal dissolution and accelerates the performance degradation of Li‐ion batteries. While strategies are developed to improve cathode material surface stability, little is known about the effects of protonation on bulk phase transitions in these cathode materials or their sodium‐ion battery counterparts. Here, using NaNiO 2 in electrolytes with different proton‐generating levels as model systems, a holistic picture of the effect of incorporated protons is presented. Protonation of lattice oxygens stimulate transition metal migration to the alkaline layer and accelerates layered‐rock‐salt phase transition, which leads to bulk structure disintegration and anisotropic surface reconstruction layers formation. A cathode that undergoes severe protonation reactions attains a porous architecture corresponding to its multifold performance fade. This work reveals that interactions between electrolyte and cathode that result in protonation can dominate the structural reversibility/stability of bulk cathodes, and the insight sheds light for the development of future batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

A Novel Multi-Agent Deep Reinforcement Learning-enabled Distributed Power Allocation Scheme for mmWave Cellular Networks

We consider the power allocation problem over shared spectrum for millimeter-Wave (mmWave) cellular downlink. Existing approaches usually find sub-optimal solutions by solving a non-convex optimization which leads to scalability issues due to centralized control. Therefore, distributed and adaptive approaches are desirable. Recently, model-free Deep Reinforcement Learning (DRL) has achieved success in such wireless resource management tasks. By modeling the radio environment as a Markov Decision Process (MDP) with the base stations (BSs) being the agents, power allocation can be automated at the agent level with comparable throughput performance to conventional centralized schemes. The multi-agent setting presents new challenges as the radio environment is impacted by the joint actions of the agents and is no longer stationary from any individual agent’s perspective. Existing literature bypasses this non-stationarity violation by ignoring it which may cause performance degradation. To tackle this issue, we propose a distributed continuous power allocation scheme based on a modified version of multi-agent Deep Deterministic Policy Gradient (MADDPG) that is tailored for the distributed multiple-agent setting. The proposed scheme employs a centralized-training distributed-execution framework where Q-functions are trained over subsets of BSs while each BS determines its transmit power based only on its own local observation. It admits constant per-BS communication and computation complexity and is thus scalable to large networks. Numerical evaluation shows that the proposed scheme adapts well to a wide range of interference conditions and can achieve comparable or better performance than several state-of-the-art non-learning approaches.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Investigating the effect of heterogeneities across the electrode|multiphase polymer electrolyte interfaces in high-potential lithium batteries

Polymer electrolytes hold great promise for safe and high-energy batteries comprising solid or semi-solid electrolytes. Multiphase polymer electrolytes, consisting of mobile and rigid phases, exhibit fast ion conduction and desired mechanical properties. However, fundamental challenges exist in understanding and regulating interactions at the electrode|electrolyte interface, especially when using high-potential layered oxide active materials at the positive electrode. Here we demonstrate that depletion of the mobile conductive phase at the interface contributes to battery performance degradation. Molecular ionic composite electrolytes, composed of a rigid-rod ionic polymer with nanometric mobile cations and anions, serve as a multiphase platform to investigate the evolution of ion conductive domains at the interface. Chemical and structural characterizations enable the visualization of concentration heterogeneity and spatially resolve the interfacial chemical states over a statistically significant field of view for buried interfaces. We report that concentration and chemical heterogeneities prevail at electrode|electrolyte interfaces, leading to phase separation in polymer electrolytes. In conclusion, understanding the hidden roles of interfacial chemomechanics in polymer electrolytes enables us to design an interphase tailoring strategy based on electrolyte additives to mitigate the interfacial heterogeneity and improve battery performance.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Target Detection via Cognitive Radars Using Change-Point Detection, Learning, and Adaptation

Many radar detection algorithms that assume a stationary environment (clutter) have been proposed and analyzed over the years. However, in practice, changes in the nonstationary environment can perturb the parameters of the clutter distribution, or even alter the clutter distribution family, which can greatly deteriorate the target detection capability. To avoid such potential performance degradation, cognitive radar systems are envisioned which are required to rapidly realize the nonstationarity, accurately learn the new characteristics of the environments, and adaptively update the detector. In this paper, aiming to develop a fully cognitive radar for target detection in nonstationary environments, we propose a unifying framework that integrates (i) change-point detection of clutter distributions by using a data-driven cumulative sum (CUSUM) algorithm and its extended version, (ii) learning/identification of clutter distribution by applying sparse theory and kernel density estimation methods, and (iii) adaptive target detection by automatically modifying the likelihood-ratio test and corresponding detection threshold. Further, with extensive numerical examples, we demonstrate the achieved improvements in detection performance due to the proposed framework in comparison to a nonadaptive case, an adaptive matched filter (AMF) method, and the clairvoyant case. Herein, we also use Wilcoxon rank-sum tests to evaluate the statistical significance of the performance improvements

42 ENGINEERING↗
DOE OSTI2025

Cross-scale modeling and experimental integration for advancing cathode electrolyte interphase studies in high energy density lithium-ion batteries

Electrochemical interfaces are critical to the performance and durability of lithium-ion batteries (LIBs). The solid electrode-electrolyte interphase (SEI and CEI) structures that form during cycling can passivate reactive surfaces, ensuring safe operation, but also may contribute to performance degradation. Understanding the microscopic factors influencing interphase formation, growth, and evolution is essential for balanced battery design. While significant research has focused on the anode-electrolyte interphase (SEI), the cathode-electrolyte interphase (CEI) remains less explored, despite its importance in high-voltage and advanced battery technologies. Challenges in conducting in-situ or operando experiments arise from the occluded nature of these interfaces and the long timescales involved, often leading to biased interpretations. A validated multi-scale, multi-physics modeling approach, integrated with advanced characterization techniques, can effectively elucidate the intrinsic stability of electrolyte and cathode surfaces, the impact of chemical heterogeneity, and the role of microstructural features on CEI performance. In conclusion, this article reviews current modeling and simulation strategies for studying CEI in advanced LIBs and highlights opportunities for future methodological advancements and experimental integration.

Cathode-electrolyte interphase↗
DOE OSTI2025

Nanoporous Wood Chips Based Sizable, Robust, and Low-Cost Honeycomb Vacuum Insulation Panels (DOE BENEFIT Final Research Performance Progress Report (RPPR))

Conventional vacuum insulation panels (VIPs) suffer from severe limitations including high cost, vulnerability to perforation, and significant performance degradation over time due to vacuum loss. InventWood Inc. (IW) and partnering teams completely re-engineered the VIP structure by constructing arrays of isolated vacuum-cells to enable limited cutting at designated areas (in between vacuum cells) and reduced consequential vacuum loss due to puncture. The teams also replaced the expensive vacuum insulation core materials with a low-cost commercial wood pulp and recycled long fiber. The wood pulp derived VIP can deliver an overall panel insulation of R15 (<0.01W/m·K) with over 90% thermal resistance retention after cutting (R13.5 overall, R5 along the cut edges). In addition, the vacuum-cell-array design minimizes edge losses, resulting in more durable performance, longer service life (>50 years), and higher R-value per dollar towards a cost target of <$1/ft 2 ·in. It is anticipated that the Nanochip-VIP will attract strong market interest and become an affordable insulation solution for energy efficient buildings and retrofits, leading to significant reductions in energy usage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Direct Observation of Defect‐Aided Structural Evolution in a Nickel‐Rich Layered Cathode

Abstract Ni‐rich LiNi 1− x − y Mn x Co y O 2 (NMC) layered compounds are the dominant cathode for lithium ion batteries. The role of crystallographic defects on structure evolution and performance degradation during electrochemical cycling is not yet fully understood. Here, we investigated the structural evolution of a Ni‐rich NMC cathode in a solid‐state cell by in situ transmission electron microscopy. Antiphase boundary (APB) and twin boundary (TB) separating layered phases played an important role on phase change. Upon Li depletion, the APB extended across the layered structure, while Li/transition metal (TM) ion mixing in the layered phases was detected to induce the rock‐salt phase formation along the coherent TB. According to DFT calculations, Li/TM mixing and phase transition were aided by the low diffusion barriers of TM ions at planar defects. This work reveals the dynamical scenario of secondary phase evolution, helping unveil the origin of performance fading in Ni‐rich NMC.

Li, Shuang↗
DOE OSTI2020

Performance Analysis of Scientific Computing Workloads on Trusted Execution Environments

Scientific computing sometimes involves computation on sensitive data. Depending on the data and the execution environment, the HPC (high-performance computing) user or data provider may require confidentiality and/or integrity guarantees. To study the applicability of hardware-based trusted execution environments (TEEs) to enable secure scientific computing, we deeply analyze the performance impact of AMD SEV and Intel SGX for diverse HPC benchmarks including traditional scientific computing, machine learning, graph analytics, and emerging scientific computing workloads. We observe three main findings: 1) SEV requires careful memory placement on large scale NUMA machines (1x -3.4x slowdown without and 1x -1.15x slowdown with NUMA aware placement), 2) virtualization - a prerequisite for SEV - results in performance degradation for workloads with irregular memory accesses and large working sets (1x -4x slowdown compared to native execution for graph applications) and 3) SGX is inappropriate for HPC given its limited secure memory size and inflexible programming model (1.2x -126x slowdown over unsecure execution). Finally, we discuss forthcoming new TEE designs and their potential impact on scientific computing.

97 MATHEMATICS AND COMPUTING↗