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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 217 records · Page 12

Low-nickel cathode chemistry for sustainable and high-energy lithium-ion batteries

The transition to sustainable energy storage demands lithium-ion batteries with high energy density and reduced reliance on critical metals such as nickel (Ni), yet current strategies to increase capacity have largely depended on raising Ni content, leading to escalating supply risks, rising costs and sustainability concerns. More critically, Ni-rich cathodes suffer from rapid electrochemical degradation driven by structural instability, creating an insurmountable trade-off between capacity and cycle life. Here, in this study, we introduce a low-Ni chemistry cathode, Li(Li 0.05 Ni 0.57 Mn 0.31 Co 0.07 )O 2 , with a radial phase integration design that overcomes these limitations, enabling a remarkable Ni usage reduction (Ni < 0.6) while demonstrating high capacity (215 mAh g −1 ) and markedly improved cyclability (~97% retention over 400 cycles) compared to conventional high-Ni cathodes (Ni = 0.8). Advanced X-ray and electron microscopy analyses reveal that the designed cathode exhibits a highly reversible oxygen anionic redox, benefiting from a structurally stable surface and minimizing irreversible phase transitions. Moreover, the integrated structure substantially mitigates lattice strain and improves mechanical stability even under harsh conditions. In conclusion, this advance offers a general design principle for developing next-generation cathodes that combine resource efficiency with long-term electrochemical reliability.

36 MATERIALS SCIENCE↗

Chaotic Dynamics Driven by Particle-Core Interactions

High-intensity beams in modern linacs are frequently encircled by diffuse halos, which drive sustained particle losses and result in gradual degradation of accelerating structures. In large part, the growth of halos is facilitated by internal space-charge forces within the beams, and detailed characterization of this process constitutes an active area of ongoing research. A partial understanding of dynamics that ensue within space-charge dominated beams is presented by the particle-core interaction paradigm – a mathematical model wherein single particle dynamics, subject to the collective potential of the core, are treated as a proxy for the broader behavior of the beam. In this work, we investigate the conditions for the onset of large-scale chaos within the framework of this model, and demonstrate that the propensity towards stochastic evolution is strongly dependent upon the charge distribution of the beam. In particular, we show that while particle motion within a uniformly charged beam is dominantly regular, rapid deterministic chaos readily arises within space-charge dominated Gaussian beams. Importantly, we find that for sufficiently high values of the beam’s space charge and beam pulsation amplitude, enhanced chaotic mixing between the core and the halo can lead to an enhanced radial diffusion of charged particles. We explain our results from analytic grounds by demonstrating that chaotic motion is driven by the intersection of two principal resonances of the system, and derive the relevant overlap conditions. Additionally, our analysis illuminates a close connection between the mathematical formulation of the particle-core interaction model and the Andoyer family of integrable Hamiltonians

43 PARTICLE ACCELERATORS↗

Assessment of Machine Learning for Ultrasonic Nondestructive Evaluation of Alkali–Silica Reaction in Concrete

Alkali–silica reaction (ASR) is a type of material degradation in concrete structures that leads to concrete cracking and rebar corrosion, thereby reducing the material’s structural integrity and the overall structure’s lifetime and raising safety concerns. Ultrasonic nondestructive evaluation (NDE) has been proven to be a valuable technique for assessing concrete properties and monitoring ASR progression in concrete. However, the deployment and analysis of ultrasonic NDE and its data requires specialized expertise, often relying on the engineer’s subjective interpretation. With the surge in computational power, artificial intelligence (AI) and machine learning (ML) algorithms have become popular in automating NDE data analysis. Various industrial sectors are increasingly adopting ML algorithms for NDE data analysis with a growing emphasis on AI–assisted automation. Regulatory agencies are also preparing for this technological shift, anticipating corresponding revisions in standards. Thus, there is an urgent need to identify the capabilities and limitations of current ML technologies for the evaluation of concrete material properties and damage status. Furthermore, the effects of various factors on ML model performance must be thoroughly investigated. The study summarized herein evaluated the effectiveness of two ML models (i.e., support vector regression (SVR) and deep neural network (DNN)) in predicting concrete material damage induced by ASR based on the long-term ultrasonic monitoring data. Four distinct concrete specimens were cast with artificially induced ASR, and over a period exceeding 500 days, ultrasonic signals and expansion data were continuously collected. For the SVR model, wave velocity and 12 other wave features were extracted from the ultrasonic signals, with 6 out of 13 features selected as input for the model. Different combinations of training and testing datasets were designed to explore factors influencing prediction performance, including the range of data within training and testing sets, in addition to various signal preprocessing methodologies. These findings suggest the importance of using a training dataset with a broader data range compared with testing datasets for improved model performance alongside consistent signal preprocessing across datasets.

36 MATERIALS SCIENCE↗

Statistical analysis and degradation pathway modeling of photovoltaic minimodules with varied packaging strategies

Degradation pathway models constructed using network structural equation modeling (netSEM) are used to study degradation modes and pathways active in photovoltaic (PV) system variants in exposure conditions of high humidity and temperature. This data-driven modeling technique enables the exploration of simultaneous pairwise and multiple regression relationships between variables in which several degradation modes are active in specific variants and exposure conditions. Durable and degrading variants are identified from the netSEM degradation mechanisms and pathways, along with potential ways to mitigate these pathways. A combination of domain knowledge and netSEM modeling shows that corrosion is the primary cause of the power loss in these glass/backsheet PV minimodules. We show successful implementation of netSEM to elucidate the relationships between variables in PV systems and predict a specific service lifetime. The results from pairwise relationships and multiple regression show consistency. This work presents a greater opportunity to be expanded to other materials systems.

electrical measurements↗

Electromagnetic device having layered magnetic material components and methods for making same

A micro fabricated electromagnetic device and method for fabricating its component structures, the device having a layered magnetic core of a potentially unlimited number of alternating insulating and magnetic layers depending upon application, physical property and performance characteristic requirements for the device. Methods for fabricating the high performing device permit cost effective, high production rates of the device and its component structures without any degradation in device performance resulting from component layering.

Mehrotra, Vivek↗

In situ visualization of multicomponents coevolution in a battery pouch cell

Lithium-ion battery (LIB) is a broadly adopted technology for energy storage. With increasing demands to improve the rate capability, cyclability, energy density, safety, and cost efficiency, it is crucial to establish an in-depth understanding of the detailed structural evolution and cell-degradation mechanisms during battery operation. Here, we present a laboratory-based high-resolution and high-throughput X-ray micro–computed laminography approach, which is capable of in situ visualizing of an industry-relevant lithium-ion (Li-ion) pouch cell with superior detection fidelity, resolution, and reliability. This technique enables imaging of the pouch cell at a spatial resolution of 0.5 μm in a laboratory system and permits the identification of submicron features within cathode and anode electrodes. We also demonstrate direct visualization of the lithium plating in the imaged pouch cell, which is an important phenomenon relevant to battery fast charging and low-temperature cycling. Our development presents an avenue toward a thorough understanding of the correlation among multiscale structures, chemomechanical degradation, and electrochemical behavior of industry-scale battery pouch cells.

25 ENERGY STORAGE↗

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↗

Lipids represent a dynamic, yet stable pool of microbially-derived soil carbon

There is an emerging consensus that microorganisms are a primary source of persistent, slow-cycling soil organic matter (SOM), however which microbial residues contribute to SOM and what controls their accumulation remains unresolved. Lipids are a commonly overlooked biomolecular pool that could contribute significantly to stable SOM. While current estimates for phospholipid degradation in soils are rapid, lipids are structurally heterogeneous molecules that could turnover at different rates. Through a year-long soil incubation and compound-specific, stable isotope probing (SIP)-lipidomics, we were able to rigorously track the persistence of lipid compounds in silty and sandy switchgrass bioenergy crop soils. Here, we assessed the influence of lipid structure on soil lipid accrual and degradation as moderated by soil texture, since mineral association is presumed to be the primary mechanism for lipid persistence. After rapid incorporation of 13 C glucose into microbial biomass, we found 13 C label was retained broadly across chemically diverse lipid classes, even after one year. 13 C-labeled lipid profiles varied significantly with soil texture; however, we found no difference between sandy and silty soils in lipid retention, suggesting soil texture may only play a minor role in modulating lipid persistence. Only two lipid subclasses were found to be persistent (i.e., retention of 13 C label without significant degradation or production): phosphatidylinositol lipids and hydroxyceramide lipids, both of which are negatively charged, possibly facilitating stabilization by mineral complexation. However, several other subclasses displayed substantial ongoing production. In particular, the accumulation of triacylglycerol lipids across soil textures suggests that storage lipids may be an important component of SOC, highlighting a potential target for management strategies to promote C retention by lipid accrual. Overall, the retention for over a year of 13 C label in microbial intact lipid biomarkers reveals the importance of efficient biomass production and turnover when considering microbial C contributions to SOM.

compound-specific↗

Predictive machine learning approaches for the microstructural behavior of multiphase zirconium alloys

Abstract Zirconium alloys are widely used in harsh environments characterized by high temperatures, corrosivity, and radiation exposure. These alloys, which have a hexagonal closed packed (h.c.p.) structure thermo-mechanically degrade, when exposed to severe operating environments due to hydride formation. These hydrides have a different crystalline structure, than the matrix, which results in a multiphase alloy. To accurately model these materials at the relevant physical scale, it is necessary to fully characterize them based on a microstructural fingerprint, which is defined here as a combination of features that include hydride geometry, parent and hydride texture and crystalline structure of these multiphase alloys. Hence, this investigation will develop a reduced order modeling approach, where this microstructural fingerprint is used to predict critical fracture stress levels that are physically consistent with microstructural deformation and fracture modes. Machine Learning (ML) methodologies based on Gaussian Process Regression, random forests, and multilayer perceptrons (MLP) were used to predict material fracture critical stress states. MLPs, or neural networks, had the highest accuracy on held-out test sets across three predetermined strain levels of interest. Hydride orientation, grain orientation or texture, and hydride volume fraction had the greatest effect on critical fracture stress levels and had partial dependencies that were highly significant, and in comparison hydride length and hydride spacing have less effects on fracture stresses. Furthermore, these models were also used accurately predicted material response to nominal applied strains as a function of the microstructural fingerprint.

36 MATERIALS SCIENCE↗

Impact of Individual Structural Defects in GaAs Solar Cells: A Correlative and In Operando Investigation of Signatures, Structures, and Effects

Defects usually degrade device performance. Thus, many techniques and effort are devoted to studying semiconductor defects. However, it is rarely known: i) how individual defects affect device performance; ii) how the impact depends on the device operating conditions; iii) how the impact varies from one defect to another; and iv) how these variations are correlated to the microscopic-scale defect structure. To address these crucial questions, an array of correlative and spatially resolved techniques, including electroluminescence, photoluminescence, Raman, I–V characteristics, and high-resolution electron microscopy, are used to characterize dislocation defects in GaAs solar cells. Significantly, the study is carried out in a series mode and in operando. This approach provides quantitative and definitive correlation between the atomistic structure of defects and their explicit effects on device performance, thus giving unprecedented insight into defect physics.

dislocation defects↗

The Detection of Monoclinic Zirconia and Non-Uniform 3D Crystallographic Strain in a Re-Oxidized Ni-YSZ Solid Oxide Fuel Cell Anode

The solid oxide fuel cell (SOFC) anode is often composed of nickel (Ni) and yttria-stabilized zirconia (YSZ). The yttria is added in small quantities (e.g., 8 mol %) to maintain the crystallographic structure throughout the operating temperatures (e.g., room-temperature to >800 °C). The YSZ skeleton provides a constraining structural support that inhibits degradation mechanisms such as Ni agglomeration and thermal expansion miss-match between the anode and electrolyte layers. Within this structure, the Ni is deposited in the oxide form and then reduced during start-up; however, exposure to oxygen (e.g., during gasket failure) readily re-oxidizes the Ni back to NiO, impeding electrochemical performance and introducing complex structural stresses. In this work, we correlate lab-based X-ray computed tomography using zone plate focusing optics, with X-ray synchrotron diffraction computed tomography to explore the crystal structure of a partially re-oxidized Ni/NiO-YSZ electrode. These state-of-the-art techniques expose several novel findings: non-isotropic YSZ lattice distributions; the presence of monoclinic zirconia around the oxidation boundary; and metallic strain complications in the presence of variable yttria content. This work provides evidence that the reduction–oxidation processes may destabilize the YSZ structure, producing monoclinic zirconia and microscopic YSZ strain, which has implications upon the electrode’s mechanical integrity and thus lifetime of the SOFC.

25 ENERGY STORAGE↗

Evaluation of H-Canyon Ventilation Exhaust Tunnel Inspection at the Savannah River Site - 20052

The Department of Energy (DOE) H-Canyon Facility at the Savannah River Site (SRS) is operated by Savannah River Nuclear Solutions (SRNS). The Facility Structural Integrity Program [1] provides a process to inspect, evaluate, and document the conditions of passive safety related structural systems and components, their degradation mechanisms and their impact on the safety envelope. The Structural Integrity Program performs periodic visual inspections to confirm the systems and components can perform their safety function and recommend corrective actions before the function is compromised. The H-Canyon Exhaust Tunnel is part of the H-Canyon Ventilation System and is periodically inspected under the Structural Integrity Program. The Tunnel performs a Safety Class passive design feature function that is available 100% of the time. The underground reinforced concrete Tunnel directs Canyon process air from the Canyon to the Sand Filter System. The radiological and chemical airborne activity coupled with the physical configuration of the tunnel precludes a manned entry into the tunnel to perform the inspection. Unlike active systems that can be subjected to physical testing to confirm capability, qualification calculations, including modeling, is performed to assess passive design feature capabilities relative to operational, accident and natural phenomena hazards events. Input for these calculations come from knowledge of field conditions, design drawings and conservative assumptions. The knowledge of field conditions comes from concrete and soil testing activities as well as inspection data. The use of cameras on crawlers to obtain inspection data and how that data is used in qualification calculations is the focus of this discussion. Remote Tunnel inspections have been performed using cameras on a stick, referred to as pole cameras, prior to Calendar Year 2003 (CY2003). Since CY2003, six camera equipped crawlers have been used. Crawlers have evolved and improved by incorporating lessons learned from the previous inspections. The latest 2019 crawler successfully traveled the entire length of the tunnel between the Canyon and Sand Filter System and captured images that were previously unseen, thus providing key visual data for the Structural Integrity Program report [2]. The inspection data serves as 1) input to qualification calculations, 2) validates current conditions remain bounded by qualification calculations, and 3) documents a record of change over time. This data is vital for the effective evaluation of the tunnel structure and aids with predicting the life cycle service life safety envelope to protect the public, environment, and facility worker. The goal of the 2019 deployment was to use a more robust vehicle to ensure travel over obstacles, perform the inspection with higher resolution cameras, and have the ability to elevate the cameras to view surfaces previously obscured by abandon-in-place ducts in the tunnel. The inspection information will serve to strengthen the input basis for qualification calculations, versus using excessive conservative calculation assumptions. This 2019 inspection was compared with previous crawler visual evidence to identify change over time to project remaining service life and confirm field conditions remain bounded by qualification calculations. The results of the 2019 Exhaust Tunnel inspection continue to improve and provide a firm basis to make sound engineering judgements regarding tunnel capability and approaches in projecting remaining service life with an aging system and component. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Degradation Mode Identification by Photocarrier Lifetime Spectroscopy on Devices and Test Structures

In this presentation, I examine the basic concepts of the device physics that can be used to distinguish various degradation and recovery modes on a cell level. The known degradation modes (bulk LeTID and LID, UVID, etc.) are due to defects and impurities that cause the photocarrier recombination according to Shockley-Reed-Hall (SRH) statistics. The SRH recombination rate strongly depends on the balance of electron and hole capture rates into the defects, which in turn, are governed by their local concentrations. The strongest recombination takes place at approximately equal concentrations of electrons and holes, while at low injection conditions (when one type of carrier dominates) the SRH recombination is suppressed. For cell degradation modes that affect the passivated interface (UVID, H-induced TOPCon contact degradation) the defects are at the interface under low-injection conditions due to either high local doping or the adjacent built-in charge in the dielectric. This mode is characterized by changes in the "diode prefactor" J01 slope in the inverse lifetime-injection level curve. In contrast, bulk degradation (LeTID, LID) affects bulk lifetime, with J01 slope unchanged. Carrier lifetime - injection level plots therefore serve as clear indicators of different degradation modes and are shown by experimental examples.

14 SOLAR ENERGY↗

Permethylation as a strategy for high–molecular–weight polysaccharide structure analysis by nuclear magnetic resonance—Case study of Xylella fastidiosa extracellular polysaccharide

Current practices for structural analysis of extremely large-molecular-weight polysaccharides via solution-state nuclear magnetic resonance (NMR) spectroscopy incorporate partial depolymerization protocols that enable polysaccharide solubilization in suitable solvents. Non-specific depolymerization techniques utilized for glycosidic bond cleavage, such as chemical degradation or ultrasonication, potentially generate structural fragments that can complicate complete and accurate characterization of polysaccharide structures. Utilization of appropriate enzymes for polysaccharide degradation, on the other hand, requires prior structural knowledge and optimal enzyme activity conditions that are not available to an analyst working with novel or unknown compounds. Herein, we describe an application of a permethylation strategy that allows the complete dissolution of intact polysaccharides for NMR structural characterization. This approach is utilized for NMR analysis of Xylella fastidiosa extracellular polysaccharide (EPS), which is essential for the virulence of the plant pathogen that affects multiple commercial crops and is responsible for multibillion dollar losses each year.

13C↗

Understanding Degradation Mechanisms in SrIrO 3 Oxygen Evolution Electrocatalysts: Chemical and Structural Microscopy at the Nanoscale

Designing acid-stable oxygen evolution reaction electrocatalysts is key to developing sustainable energy technologies such as polymer electrolyte membrane electrolyzers but has proven challenging due to the high applied anodic potentials and corrosive electrolyte. This work showcases advanced nanoscale microscopy techniques supported by complementary structural and chemical characterization to develop a fundamental understanding of stability in promising SrIrO 3 thin film electrocatalyst materials. Cross-sectional high-resolution transmission electron microscopy illustrates atomic-scale bulk and surface structure, while secondary ion mass spectrometry imaging using a helium ion microscope provides the nanoscale lateral elemental distribution at the surface. After accelerated degradation tests under anodic potential, the SrIrO 3 film thins and roughens, but the lateral distribution of Sr and Ir remains homogeneous. A layer-wise dissolution mechanism is hypothesized, wherein anodic potential causes the IrO x -rich surface to dissolve and be regenerated by Sr leaching. Finally, the characterization approaches utilized herein and mechanistic insights into SrIrO 3 are translatable to a wide range of catalyst systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Intralattice-bonded phase-engineered ultrahigh-Ni single-crystalline cathodes suppress strain evolution

Single crystallization remains a debated strategy for advancing Ni-rich cathode materials. While it mitigates particle cracking and improves tap density by eliminating particle boundaries, extended diffusion pathways introduce volumetric and lattice distortions, compromising electrochemical and structural stability. These challenges hinder the commercialization of high-Ni single-crystal cathodes, calling for a reassessment of their viability. Here, in this study, we report a structural design: intralattice-bonded phase single-crystal LiNi 0.92 Co 0.03 Mn 0.05 O 2 (IBP-SC92). This architecture maintains structural integrity while shortening diffusion pathways, resulting in almost zero electrochemical degradation during cycling. The robust structure and fast ion transport mitigate lattice strain, as confirmed by multiscale high-resolution diffraction and imaging techniques, preventing intragranular cracks and irreversible phase transitions. As a result, IBP-SC92 shows outstanding cycling stability, with nearly 100% capacity retention after 100 cycles in half cells and 94.5% retention after 1,000 cycles in full cells. This redefined single-crystal cathode represents a significant step towards the industrial adoption of high-energy-density materials.

36 MATERIALS SCIENCE↗