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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Failure modes of protection layers produced by atomic layer deposition of amorphous TiO 2 on GaAs anodes

Amorphous titanium dioxide (a-TiO 2 ) films formed by atomic layer deposition can serve as protective coatings for semiconducting photoanodes in water-splitting cells using strongly alkaline aqueous electrolytes. Herein, we experimentally examine the mechanisms of failure for p + -GaAs anodes coated with a-TiO 2 films (GaAs/a-TiO 2 ). Galvanic displacement of exposed GaAs by Au allowed imaging of pinholes in the a-TiO 2 coatings, and enabled collection of quantitative and statistical data associated with pinhole defects. A combination of imaging, electrochemical measurements, and quantitative analyses of corrosion products indicated that extrinsic pinholes were present in the a-TiO 2 films before electrochemical operation. During electrochemical operation these pinholes led to pitting corrosion of the underlying GaAs substrate. The dominant source of pinholes was the presence of atmospheric particulate matter on the GaAs surface during deposition of the a-TiO 2 layer. The pinhole density decreased substantially when the thickness of the a-TiO 2 coating increased beyond 45 nm, and approached zero when the thickness of the film exceeded 112 nm. The density of pinholes in films thinner than 45 nm decreased when the a-TiO 2 coating was deposited in an environmentally controlled cleanroom. Pinhole-free GaAs/a-TiO 2 devices were also tested via chronoamperometry to quantify the rate of pinhole formation during electrochemistry. The time-to-failure increased with thickness, suggesting that the failure mechanism may involve diffusion or migration through the film. However, other mechanisms may also contribute to the degradation of thicker films (>112 nm). Nevertheless, as previously hypothesized, extrinsic pinhole defects formed during deposition and testing control the short-term protective performance of the a-TiO 2 film for GaAs anodes evolving O 2 from water.

25 ENERGY STORAGE↗
DOE OSTI2022

From lab to lamp: Understanding downconverter degradation in LED packages

Downconverters, primarily inorganic phosphors, are critical components in white solid-state LED-based lighting and liquid crystal display backlights. Research efforts have led to a fundamental understanding of a downconverter's absorption, photoluminescence, and efficiency as a function of composition, structure, and processing conditions. However, considerably less work has focused on the reliability of phosphors once they are incorporated into LED packages. Solving these issues is often the final step before the commercialization of new materials, but the significant resources and time required to evaluate and mitigate materials failure are rarely discussed in the literature. In this Perspective, we discuss the need for conducting downconverter reliability testing and the potential of accelerating, screening, and understanding downconverter failure modes. Our focus highlights the mechanisms of failure and discusses how this influences materials selection and the design of different LED packages. We also stress the potential for accelerated reliability testing protocols and note the potential role first-principles calculations and data-driven models could play in establishing the compositional-processing trends for different aspects of downconverter reliability. In conclusion, we close with possible research directions that could improve downconverter reliability and emphasize the importance of assessing a material's (chemical) stability where multiple manufacturing and processing steps can dictate system performance.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Towards validation of combined-accelerated stress testing through failure analysis of polyamide-based photovoltaic backsheets

Abstract Novel methods for advancing reliability testing of photovoltaic (PV) modules and materials have recently been developed. Combined-accelerated stress testing (C-AST) is one such method which has demonstrated reliable reproduction of some field-failures which were not reproducible by standard certification tests. To increase confidence and assist in the development of C-AST, and other new testing protocols, it is important to validate that the failure modes observed and mechanisms induced are representative of those observed in the field, and not the product of unrealistic stress conditions. Here we outline a method using appropriate materials characterization and modelling to validate the failure mechanisms induced in C-AST such that we can increase confidence in the test protocol. The method is demonstrated by applying it to a known cracking failure of a specific polyamide (PA)-based backsheet material. We found that the failure of the PA-based backsheet was a result of a combination of stress factors. Photo-oxidation from ultra-violet (UV) radiation exposure caused a reduction in fracture toughness, which ultimately lead to the cracking failure. We show that the chemical and structural changes observed in the backsheet following C-AST aging were also observed in field-aged samples. These results increase confidence that the conditions applied in C-AST are representative of the field and demonstrates our approach to validating the failure mechanisms induced.

14 SOLAR ENERGY↗
DOE OSTI2020

Modeling strategy for progressive failure prediction in lithium-ion batteries under mechanical abuse

The prediction for the internal failure of lithium-ion batteries (LIBs) under external mechanical abuse loading remains a challenge for safe design. This paper systematically studies the modeling approach for progressive failure simulation and short-circuit prediction. Hemispherical indentation experiments are conducted on a battery specimen containing 5 representative sandwich (RS) layers to examine the deformation and progressive failure behavior of battery components. Three different models, viz, a high-fidelity detailed model, an intermediate homogenized model and a fully homogenized model, are developed and employed to simulate the progressive failure in a multi-layer battery specimen. The simulation results obtained using the three models all correlate well with experimental phenomena, capturing the overall stress-strain response and ultimate failure of the battery structure. The numerical results can help us understand the failure behavior and the mechanism for mechanical abuse-induced short circuit in LIBs. The feasibility of the three models for use in progressive failure prediction is compared by analyzing the capability of the models in predicting the critical failure events, the computational efficiency of the models, and the feasibility to implement coupled mechanical-electrochemical-thermal simulations. The results of this work provide useful insights on practical choices for the modeling strategy and safety design of LIBs under mechanical abuse conditions.

25 ENERGY STORAGE↗
DOE OSTI2024

Machine Learning and Data Science to Advance Laboratory Earthquake Prediction and Illuminate the Mechanics of Precursors to Failure

Earthquakes represent one of our greatest natural hazards and in recent years human induced seismicity is adding to the threat. Even a modest improvement in the ability to forecast devastating large earthquakes or smaller shallow events associated with fluid injection could save thousands of lives and billions of dollars. Current efforts to forecast earthquakes are limited by knowledge of earthquake physics and hampered by a lack of reliable lab or field observations. However, recent work has provided a critical opportunity for advancement. We have found: 1) clear and consistent precursors prior to earthquake-like failure in the laboratory and 2) that lab earthquakes can be predicted using machine learning (ML). These works show that stick-slip failure events –the lab equivalent of earthquakes– are preceded by a cascade of micro-failure events that radiate elastic energy in a manner that foretells catastrophic failure. Remarkably, ML predicts the fault zone stress state, the failure time and in some cases the magnitude of lab earthquakes. In addition, the observations include clear precursors to failure in the form of changes in fault zone properties prior to lab earthquakes. Precursors have been observed in previous laboratory studies but their origin is poorly understood and their possible connection to ML based earthquake prediction is unknown. The work conducted under our project has dramatically expanded these efforts. We have developed an integrated data science approach to illuminate the physics of earthquake precursors and lab earthquake prediction. Our work has accelerated the development of ML, artificial intelligence (AI), and related data science approaches by providing massive data sets that are tightly connected to critical scientific problems and by bringing together leading subject matter experts and data scientists. Earthquake physics involves phenomena that are far from equilibrium. Our work has leveraged data science methods to illuminate these phenomena and investigate how they relate to earthquake prediction. In addition to a large database with many types of labeled events that is available to everyone, our work has advanced the fundamental understanding of seismic forecasting, earthquake physics, and fault rheology

58 GEOSCIENCES↗
DOE OSTI2020

Thermal Assessment and In-Situ Monitoring of Insulated Gate Bipolar Transistors in Power Electronic Modules: Preprint

Insulated gate bipolar transistor (IGBT) power modules are devices commonly used for switching of high voltages and currents. Usage and environmental conditions can cause these power modules to degrade over time, and this gradual process may eventually lead to catastrophic failure of the device. This degradation process may cause some early performance symptoms related to the state of health of the power module, making it possible to detect reliability degradation of the IGBT module. Testing can be used to accelerate this process, permitting a rapid determination of whether specific declines in device reliability can be characterized. In this study, thermal cycling was conducted on multiple power modules simultaneously in order to assess the effect of thermal cycling on the degradation of the power module. In-situ monitoring of temperature was performed from inside each power module using high temperature thermocouples. Device imaging and characterization was performed along with temperature data analysis, to assess failure modes and mechanisms within the power modules. While the experiment was aimed to assess the potential damage effects of thermal cycling on die attach, results indicated that wirebond degradation was the life limiting failure mechanism.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

The role of height–driven constraints and compensations on tree vulnerability to drought

Frequent observations of higher mortality in larger trees than in smaller ones during droughts have sparked an increasing interest in size–dependent drought–induced mortality. However, the underlying physiological mechanisms are not well understood, with height–associated hydraulic constraints often being implied as the potential mechanism driving increased drought vulnerability. Here we performed a quantitative synthesis on how key traits that drive plant water and carbon economy change with tree height within species and assessed the implications that the different constraints and compensations may have on the interacting mechanisms (hydraulic failure, carbon starvation and/or biotic–agent attacks) affecting tree vulnerability to drought. While xylem tension increases with tree height, taller trees present a range of structural and functional adjustments, including more efficient water use and transport and greater water uptake and storage capacity, that mitigate the path–length–associated drop in water potential. These adaptations allow taller trees to withstand episodic water stress. Conclusive evidence for height–dependent increased vulnerability to hydraulic failure and carbon starvation, and their coupling to defence mechanisms and pest and pathogen dynamics, is still lacking. Further research is needed, particularly at the intraspecific level, to ascertain the specific conditions and thresholds above which height hinders tree survival under drought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Developing an experimental-computational framework to investigate the deformation mechanisms and mechanical properties of Al-8Ce-10Mg alloys at micro and macroscales

There is a promising future for the use of aluminum-cerium-magnesium alloys in a broad range of applications, including devices that operate at high temperatures. With cerium currently considered a waste product of rare earth mining validation studies of possible applications are essential to reduce the environmental waste. Here, a computational-experimental framework is developed to investigate the role both the intermetallic and matrix have on the mechanical properties of these alloys. A set of experiments, including SEM/EBSD imaging, nanoindentation, in-situ SEM tensile testing, and in-situ SEM-DIC tests are performed to characterize the microstructure and mechanical properties of these alloys. Furthermore, the elastic, plastic, and failure deformation mechanisms of the microstructure, and their correlation with the bulk scale mechanical properties are investigated. Experimental results are also used to calibrate parameters for a crystal plasticity finite element model, by performing a computational framework that minimizes the error between the computational and experimental results. This model is then utilized to investigate how the area percentage of intermetallics and the crystallographic texture control the mechanical properties of the alloy. Simulation results show that an increase in the percentage of intermetallics increase the strength but decrease the ductility of the alloy. Also, a change in material texture improves strength and reduces damage that leads to material failure. The development of the crystal plasticity model, as discussed in this work, opens opportunities for future investigations of similar aluminum-cerium-magnesium alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Insight into the deformation features and capacity loss mechanisms of lithium-ion pouch cells under spherical indentation conditions

Mechanical deformation under extreme conditions is one of the important reasons for the failure of lithium-ion batteries in automotive application. However, the deformation features and component failure of lithium-ion cells to external loading has never been a design consideration. Here, in this study, we conduct spherical indentation tests on a dozen of lithium-ion cells with different capacities under different control mode conditions to investigate their deformation features and capacity loss mechanisms. The experimental results show that, under mechanical deformation conditions, internal faults of cells occur in stages, and energy accumulation and sudden release are two key processes of cell's mechanical failure. The cells' state of charge is the main factor affecting their thermal runaway behaviors. In addition, a finite element model is developed to simulate the deformation features and the failure mechanism of key components of lithium-ion pouch cells; the 3D x-ray computed tomography is employed to demonstrate its internal configuration. With this model, the force-strain response, the deformation features as well as the size of the failure area of lithium-ion cells under spherical indentation conditions are accurately predicted. In 3D x-ray computed tomography images, unique mud cracks in cooper current collector are observed, and the influence mechanisms of the isolated fragments on the cell capacities are revealed. These results may provide useful information for the mechanical structure design of the components of lithium-ion pouch cells.

25 ENERGY STORAGE↗
DOE OSTI2023

Artificial neural network potentials for mechanics and fracture dynamics of two-dimensional crystals **

Understanding the mechanics and failure of materials at the nanoscale is critical for their engineering and applications. The accurate atomistic modeling of brittle failure with crack propagation in covalent crystals requires a quantum mechanics-based description of individual bond-breaking events. Artificial neural network potentials (NNPs) have emerged to overcome the traditional, physics-based modeling tradeoff between accuracy and accessible time and length scales. Previous studies have shown successful applications of NNPs for describing the structure and dynamics of molecular systems and amorphous or liquid phases of materials. However, their application to deformation and failure processes in materials is still uncommon. In this study, we discuss the apparent limitations of NNPs for the description of deformation and fracture under loadings and propose a way to generate and select training data for their employment in simulations of deformation and fracture simulations of crystals. We applied the proposed approach to 2D crystalline graphene, utilizing the density-functional tight-binding method for more efficient and extensive data generation in place of density functional theory. Then, we explored how the data selection affects the accuracy of the developed artificial NNPs. It revealed that NNP’s reliability should not only be measured based on the total energy and atomic force comparisons for reference structures but also utilize comparisons for physical properties, e.g. stress–strain curves and geometric deformation. In sharp contrast to popular reactive bond order potentials, our optimized NNP predicts straight crack propagation in graphene along both armchair and zigzag (ZZ) lattice directions, as well as higher fracture toughness of ZZ edge direction. Our study provides significant insight into crack propagation mechanisms on atomic scales and highlights strategies for NNP developments of broader materials.

2D materials↗
DOE OSTI2023

Grayscale Digital Light Processing Gradient Printing for Stress Concentration Reduction and Material Toughness Enhancement

Avoiding stress concentrations is essential to achieve robust parts since failure tends to originate at such concentrations. With recent advances in multimaterial additive manufacturing, it is possible to alter the stress (or strain) distribution by adjusting the material properties in selected locations. Here, we investigate the use of grayscale digital light processing (g-DLP) 3D printing to create modulus gradients around areas of high stress. These gradients prevent failure by redistributing high stresses (or strains) to the neighboring material. The improved material distributions are calculated using finite element analysis. The much-enhanced properties are demonstrated experimentally for thin plates with circular, triangular, and elliptical holes. In conclusion, this work suggests that multimaterial additive manufacturing techniques like g-DLP printing provide a unique opportunity to create tougher engineering materials and parts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Computational modeling of coupled mechanical damage and electrochemistry in ternary oxide composite electrodes

Performance degradation of ternary layered oxide cathodes largely originates from their loss of structural integrity in cyclic usage. Mechanical damage, such as intergranular fracture of the active particles, is not only a mechanical cleavage process but also interferes with electrochemical kinetics such as infiltration of liquid electrolyte, surface corrosion of the constituent primary particles, and may eventually isolate the primary grains from the electron conducting network. Here, in this work, we develop a computational framework that integrates electrochemistry of a LiNi x Mn y Co 1−x−y O 2 (NMC) composite cathode with mechanical damage of the active particles. To fully examine the intricate chemomechanical behavior of the electrode, we evaluate the effects of the anisotropic material properties, the influence of mechanical potential on Li transport, and the concurrent intergranular fracture and electrolyte penetration along the grain boundaries upon multiple cycles. Electrolyte infiltration benefits capacity retention but aggravates further mechanical damage by corrosion. Structural failure mostly occurs in the first charging due to the anisotropic mechanical strain between the primary grains, while the resulting damage remains stable in the later few cycles. The results are consistent with experimental observations and the integration of electrochemistry and mechanical failure enables a step further understanding of the complex mechanism of battery degradation.

Battery degradation↗
DOE OSTI2020

Status Update on the SCIP-IV Program in 2020

Phase 1 of the Studsvik Cladding Integrity Project (SCIP) was launched in 2004. It was a 5-year Organisation for Economic Co-operation and Development (OECD) / Nuclear Energy Agency (NEA) joint project operated by Studsvik with about 30 participating organizations, including regulatory bodies, research institutions, utilities, and fuel suppliers from 13 different countries. The initial SCIP program focus was directed toward studying basic phenomena of fuel rod failures driven by pellet cladding mechanical interaction to get a better understanding of fundamental failure mechanisms. SCIP IV is a continuation of the SCIP programs and is planned to be another five-year project that started in July 2019. It is organized and managed in a manner similar to the earlier SCIP programs, including both a technical group and a management board. The work of SCIP-IV includes significant research into issues related to the back end of the fuel cycle, including spent nuclear fuel (SNF) storage and transportation issues.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Size-Dependent Chemomechanical Failure of Sulfide Solid Electrolyte Particles during Electrochemical Reaction with Lithium

The very high ionic conductivity of Li 10 GeP 2 S 12 (LGPS) solid electrolyte (SE) makes it a promising candidate SE for solid-state batteries in electrical vehicles. However, chemomechanical failure, whose mechanism remains unclear, has plagued its widespread applications. Here, we report in situ imaging lithiation-induced failure of LGPS SE. In this work, we revealed a strong size effect in the chemomechanical failure of LGPS particles: namely, when the particle size is greater than 3 μm, fracture/pulverization occurred; when the particle size is between 1 and 3 μm, microcracks emerged; when the particle size is less than 1 μm, no chemomechanical failure was observed. This strong size effect is interpreted by the interplay between elastic energy storage and dissipation. Our finding has important implications for the design of high-performance LGPS SE, for example, by reducing the particle size to less than 1 μm the chemomechanical failure of LGPS SE can be mitigated.

25 ENERGY STORAGE↗
DOE OSTI2026

Relief Zones Enhance the Durability of Ultrathin Membranes in Electrochemical Conversion Devices

Premature failures in electrochemical conversion systems often result when membrane electrode assemblies (MEAs) use ultrathin (≤15 μm-thick) polymer electrolyte membranes, susceptible to mechanical degradation from stress concentrations arising from device-level integration. Herein, relief zones were developed to mitigate mechanical degradation by alleviating excess and nonuniform compression across active areas. Relief zones, created through ablation of carbonaceous diffusion media, enable seamless adaptation across MEA dimensions without need for hardware modifications. Demonstrated using fuel cells as a case study, accelerated stress tests revealed a 6-fold lifetime improvement (∼1500 h) compared to conventional edge-protected MEAs, decoupling device-level engineering effects from material limitations.

accelerated stress test↗
DOE OSTI2023

The Physical and Engineering Limits of Coupled In situ TEM Experiments

Almost all future energy systems (advanced nuclear reactors, fusion energy system, concentrating solar-thermal power (CSP), and wind technologies) are limited by degradation of key material systems exposed to multiple environmental stressors. The degradation during exposure to high temperatures, radiation, mechanical loading, and chemical attack is often dictated by mechanisms active at the microstructural level. The nature of these mechanisms and the associated variations between sequential and concurrent interplay can be explored if the transmission electron microscope (TEM) is utilized as a toolbox for exploration [1]. One such tool developed at Sandia National Laboratories to couple several of these environments is the In situ Ion Irradiation TEM (I3TEM) [2]. Several studies over the last decade utilizing this tool have shown that the scientific intuition developed over decades of sequential experiments is not always a good indicator of concurrent mechanisms or failure routes. This presentation will highlight the recent and planned additions into the I3TEM facility of a Waviks gas injection system and Raman system, respectively, as can be seen in Fig. 1, permitting environmental degradation from gas species leaked into the pole piece region during quantitative mechanical loading (indentation, monotonic loading, high temperature creep, irradiation induced creep, and high-cycle fatigue); multi-beam ion irradiation (energies ranging from 1 keV to 48 MeV and species from H to Au); laser exposure (20 W and 1064 nm), or various combinations thereof that are already possible [3]. This addition permits the facility to explore both sequential or concurrently the four axes of stressors: thermal, mechanical, radiation, and chemical. This information can be directly coupled to modeling, expediting the refinement and validation of both atomistic and mesoscale models.

degradation↗
DOE OSTI2022

An Application of a Modified Beta Factor Method for the Analysis of Software Common Cause Failures

This paper presents an approach for modeling software common cause failures (CCFs) within digital instrumentation and control (I&C) systems. CCFs consist of a concurrent failure between two or more components due to a shared failure cause and coupling mechanism. This work emphasizes the importance of identifying software-centric attributes related to the coupling mechanisms necessary for simultaneous failures of redundant software components. The groups of components that share coupling mechanisms are called common cause component groups (CCCGs). Most CCF models rely on operational data as the basis for establishing CCCG parameters and predicting CCFs. This work is motivated by two primary concerns: (1) a lack of operational and CCF data for estimating software CCF model parameters; and (2) the need to model single components as part of multiple CCCGs simultaneously. A hybrid approach was developed to account for these concerns by leveraging existing techniques: a modified beta factor model allows single components to be placed within multiple CCCGs, while a second technique provides software-specific model parameters for each CCCG. This hybrid approach provides a means to overcome the limitations of conventional methods while offering support for design decisions under the limited data scenario.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗