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At least 487 records · Page 27

Stress Corrosion Cracking of NaSICON Membranes in Aqueous Electrolytes for Redox-Flow Batteries

The sodium super-ionic conductor (NaSICON) has versatile applications as a ceramic electrolyte for energy storage, where it can serve as an impermeable separator in solid-state batteries and redox flow systems. In particular, NaSICON systems have been proposed to be relatively stable in contact with water, making them compatible with aqueous battery chemistries. However, owing to their brittle nature and metal oxide constituents, stress-corrosion cracking (SCC) is an important failure mechanism that has not been previously explored. In this study, we assess the fracture toughness of NaSICON membranes in contact with aqueous solutions that are relevant to redox flow systems. Microindentation was performed to generate visible surface cracks and residual stress, which were observed to grow in length after exposure to aqueous solutions. This allows for a quantitative measurement of fracture toughness, which decreases after exposure to water. To contextualize these results, we develop a simplified model of the fracture behavior in aqueous redox-flow batteries that incorporate NaSICON membranes, illustrating the importance of SCC in cell design. This work provides quantitative insights into SCC as a failure mode in NaSICON, enhancing our understanding of the chemo-mechanical behavior of ceramic electrolytes in contact with aqueous solutions.

Zhang, Mengyao↗

In situ Diagnostics of Coupled Electrochemical-Mechanical Properties of Solid Electrolyte Interphases on Lithium Metal Rechargeable Batteries (Final Technical Report)

The fundamental understanding of the coupled mechanical/chemical degradation of the SEI layer during lithium cycling will enable the project to identify the desirable mechanical properties on SEI/lithium as a system and the specific transport properties that enable the homogenous lithium stripping/plating while avoiding the mossy structure. Furthermore, it will allow the project to develop a highly impactful strategy to protect lithium metal and achieve dendrite free high cycle efficiency, which can dramatically increase the energy density of lithium batteries for EV applications. During past three years, four coherent steps have been taken to solve the coupled mechanical and electrochemical degradation: (1) Developed a comprehensive set of in-situ diagnostic techniques to investigate the coupled mechanical/chemical properties of SEI layer and its impact on lithium striping/plating. (2) Identified failure mechanisms of SEI/Li as a whole electrode system using in-situ electrochemical tools. (3) Established a design strategy of protective coatings on Li metal to extend the cycle life Li meal electrode. (4) Developed novel surface coatings as the artificial SEI layer to protect Li metal and significantly extend cycle life. During past 3-year budget period, we have published over 16 peer-reviewed paper, filed 7 patents, and given over 30 invited talks. 5 graduated students and 2 postdocs were supported by this project.

36 MATERIALS SCIENCE↗

Results of TC-1 boost pump icing tests in the space power facility

A series of tests were conducted in the space power facility to investigate the failure of the Centaur oxidizer boost pump during the Titan/Centaur proof flight February 11, 1974. The three basic objectives of the tests were: (1) demonstrate if an evaporative freezing type failure mechanism could have prevented the pump from operating, (2) determine if steam from the exhaust of one of the attitude control engine could have entered a pump seal cavity and caused the failure, and (3) obtain data on the heating effects of the exhaust plume from a hydrogen peroxide attitude control engine.

Gentile, L. C.↗

Machine learning for photovoltaic single axis tracker fault detection and classification

More than 81% of the annual capacity of utility-scale photovoltaic (PV) power plants in the U.S. use single-axis trackers (SATs) due to SATs delivering 4% in capacity factor on average over fixed-array systems. However, SATs are subject to faults, such as software misconfigurations and mechanical failures, resulting in suboptimal tracking. If left undetected, the overall power yield of the PV power plant is reduced significantly. Minimizing downtime and ensuring efficient operation of SATs requires robust detection and diagnosis mechanisms for SAT faults. We present a machine learning framework for implementing real-time SAT fault detection and classification. Our implementation of the proposed framework reliably identifies measurements taken from a test PV system undergoing emulated SAT faults relative to state-of-the-art algorithms and produces nearly zero false positives on our testing days. Code and data are available at https://pvpmc.sandia.gov/tools.

Fault classification↗

Polymorphism of garnet solid electrolytes and its implications for grain-level chemo-mechanics

Understanding and mitigating filament formation, short-circuit and solid electrolyte fracture is necessary for advanced all-solid-state batteries. Here, we employ a coupled far-field high-energy diffraction microscopy and tomography approach for assessing the chemo-mechanical behaviour for dense, polycrystalline garnet (Li 7 La 3 Zr 2 O 12 ) solid electrolytes with grain-level resolution. In situ monitoring of grain-level stress responses reveals that the failure mechanism is stochastic and affected by local microstructural heterogeneity. In this work, coupling high-energy X-ray diffraction and far-field high-energy diffraction microscopy measurements reveals the presence of phase heterogeneity that can alter local chemo-mechanics within the bulk solid electrolyte. These local regions are proposed to be regions with the presence of a cubic polymorph of LLZO, potentially arising from local dopant concentration variation. The coupled tomography and FF-HEDM experiments are combined with transport and mechanics modelling to illustrate the degradation of polycrystalline garnet solid electrolytes. The results showcase the pathways for processing high-performing solid-state batteries.

36 MATERIALS SCIENCE↗

Stress Analysis and Design of Silicon Solar Cell Arrays and Related Material Properties

A systematic approach is presented for the design of solar cell arrays to eliminate mechanical failures that might arise in components of the arrays in a thermal environment. A prerequisite to the approach is the characterization of material properties at different temperatures. Significant data is obtained for the thermal behavior of the silicon solar cell material and adhesives. Upon determining the mechanical and thermal material properties of the components of the solar cell array, utilizing a finite element idealization for predicting the stress fields in the components, and employing the von Mises failure criterion, potential failure areas in various design configurations in a given thermal environment are identified. Guide lines and means to optimize a given design are illustrated by two examples.

Salama, A. M.↗

Mapping 3D grain and precipitate structure during in situ mechanical testing of open-cell metal foam using micro-computed tomography and high-energy X-ray diffraction microscopy

Open-cell metal foams are ultra-low-density cellular metals with complex hierarchical structures that span bulk, cell, ligament, and sub-ligament scales and give rise to desirable properties such as high strength-to-weight ratio and excellent energy absorption. Although literature suggests that intrinsic material structures at sub-ligament length scales (e.g., grains and precipitates) play an important role in mechanical behavior of open-cell metal foams, there are very few experimental measurements of such structures in three dimensions and for meaningful volumes of foam. This study seeks to map and track the three-dimensional (3D) grain and precipitate structures of an intact volume of open-cell aluminum foam by advancing microstructural characterization techniques that leverage X-ray micro-computed tomography (μCT) and far-field high-energy X-ray diffraction microscopy (FF-HEDM). A 6%-relative-density aluminum foam sample was mechanically tested in compression while μCT and FF-HEDM measurements were collected at interrupted loading states at beamline 1-ID of the Advanced Photon Source. Further, a new scanning strategy and reconstruction algorithm were established to enable characterization of a foam volume with diameter approximately four times wider than the nominal width of the X-ray beam. The result is a set of maps that detail both the 3D grain and precipitate structures throughout the foam volume at successive strain steps. A novel grain tracking procedure was developed to track individual grains within the foam volume by accounting for the large rigid-body motions that individual ligaments can undergo during mechanical loading. The ability to track grains and precipitate structures in three dimensions throughout large bulk deformation of ultra-low-density polycrystalline materials enables new possibilities for validating numerical models and investigating local failure mechanisms. Furthermore, the methods and procedures developed in this study could be applied to other ultra-low-density structures, such as additively manufactured lattices.

36 MATERIALS SCIENCE↗

Delamination crack growth in unidirectional fiber-reinforced composites under static and cyclic loading

An investigation of delamination crack growth in a unidirectional composite laminate under static and fatigue loading conditions is presented. An experimental program was conducted to study failure mechanisms and characterize the crack growth rate; analytical modeling based on microscopic observations was carried out using an advanced singular finite element method of the hybrid-stress model. Using a mixed-mode failure criterion, the delamination growth under a monotonically increasing load can be predicted; the rate of delamination crack propagation under fatigue loading is directly related to the amplitudes of cyclic opening and shearing mode stress intensity factors by a power law relationship.

Wang, S. S.↗

Buckling of a fiber bundle embedded in epoxy

Buckling of a fiber bundle embedded in epoxy resin was studied to gain insight into compressive failure mechanisms in unidirectional composites. The fibers used were E-glass, T300 graphite, T700 graphite, and P75 graphite. These fibers were combined with two different resins: Epon 815/V140 and Epon 828/Z. In both resins the failure mode of the bundle was found to be microbuckling of fibers for the first three types of fibers; however, the high-modulus P75 fibers failed in shear without any sign of microbuckling. The strains at which microbuckling occurred were higher than the compressive failure strains of the corresponding unidirectional composites. In the soft resin, Epon 815/V140, fibers buckled at lower strains than in the stiff resin, Epon 828/Z. The buckling strains and the segment lengths followed the trends predicted for a single filament embedded in an infinite matrix.

Hahn, H. T.↗

Development of Predictive Model for Accurate Rupture Time from Multi-Axial Creep in Alloy 709 with Physics-Based Simulations

A physics-based model is developed to predict multiaxial creep behavior in Alloy 709 (A709), an advanced austenitic stainless steel intended for high-temperature applications such as Sodium Fast Reactors (SFRs). Compared to conventional stainless steels like 316H, A709 offers superior high-temperature performance; however, comprehensive data on its multiaxial creep response remain limited. To address this gap, a crystal plasticity finite element (CPFE) framework is used to simulate the deformation and failure mechanisms of A709 under multiaxial loading conditions. The model incorporates an extended Hu-Cocks dislocation creep formulation that accounts for precipitation effects, along with the Sham–Needleman model to capture grain boundary cavitation-driven failure. These advanced constitutive models enable a detailed understanding of the interplay between microstructural evolution and macroscopic creep response. Furthermore, the study evaluates the predictive accuracy of various effective stress measures in estimating creep rupture life, leveraging simulated multiaxial creep data. The findings provide critical insights into the applicability of different stress measures for engineering design and life prediction of A709 components operating under complex loading conditions. This work contributes to improving the reliability of high-temperature structural components by advancing predictive modeling capabilities for advanced austenitic steels.

Alloy 709↗

The effect of temperature on the deformation and fracture of SiC/Ti-24Al-11Nb

The effect of temperature on the stress-strain behavior in air and the failure mechanisms of Ti-24Al-11Nb alloy and of a SiC/Ti-24Al-11Nb composite with continuous SiC fibers oriented parallel to the loading direction was investigated over temperature range 23-815 C. It was found that the tensile failure process of SiC/Ti-24Al-11Nb was controlled at all temperatures by fiber fracture. Composite failure occurred at 0.8 percent strain at all temperatures. Debond and frictional stresses at the fiber-matrix interface decreased with increased temperature.

Brindley, P. K.↗

Melt Pool and Heat Treatment Optimization for the Fabrication of High-Strength and High-Toughness Additively Manufactured 4340 Steel

Additively manufactured (AM) components offer superior design flexibility compared to their conventionally manufactured counterparts, and optimizing processing parameters is key to achieving high-quality depositions with desirable and predictable mechanical properties. This study was focused on 4340 steel fabricated using laser powder bed fusion (LPBF), and 42 laser power and scan speed combinations have been systematically investigated to determine an optimized melt pool geometry that would ensure fully-dense parts. The AM material was compared with a wrought 4340 equivalent and studied in two customized heat treated conditions, optimized for strength and toughness, respectively. The microstructures of the as-fabricated and heat treated AM and wrought materials were characterized to assess differences introduced by the layer-by-layer fabrication process and subsequent heat treatment. Tensile properties of both materials were also evaluated and demonstrate that the AM materials offer equal or superior properties compared to the wrought equivalents. Differences in fracture surface morphologies indicate the distinct failure mechanisms associated with the materials’ characteristic microstructures, and the role of inclusions in the failures was studied to elucidate these differences. Complementary to the experimental investigations, the dataset was leveraged to make recommendations for future design of experiments to optimize AM build parameters in other material systems. A statistical Monte Carlo analysis was used to predict the interpolation error produced using reduced datasets and to enable informed processing parameters selection. These findings are discussed to make recommendations for the use of AM materials for high-integrity structural applications.

36 MATERIALS SCIENCE↗

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗

Instrumented adhesion tests on plasma sprayed thermal barrier coatings

The failure mechanisms of plasma-sprayed two-layer coatings consisting of an NiCrAlY or NiCrAlZr bond coat with an yttria-stabilized zirconia overlay are presently examined by tensile adhesion tests. It has been found that adhesive failure within the bond coat exhibits greater failure strain than the cohesive failure of the ceramic overlay, supporting the view of the intermediate coatings being highly compliant. The absolute extension exhibited by failures occurring only through the ceramic coating is greater than that of adhesive failure, since the ceramic coating is much thicker than the bond coat.

Berndt, Christopher C.↗

Postbuckling failure of composite plates with holes

This paper summarizes a study focused on understanding the failure mechanisms present in a plate with a centrally located circular hole loaded inplane into the postbuckling range of deflections. The study was numerical and experimental in nature and had as a goal the a priori prediction of failure using existing failure data from several sources, together with a stress analysis. The maximum stress failure criterion was used to predict failure and both intra- and interlaminar stresses were considered. Four laminates were considered. The phenomenon of modal interaction, or the jumping from one deformed configuration to another, is discussed. With this jumping, the plate configuration may change from one half-wave in the loading direction to two half-waves in the loading direction. The study concludes that the failure in (+/-45/0/90)2s and (+/-45/2(2))2s laminates is due to fiber compression failure and is predictable. The failure load is, for the most part, independent of response configuration. The (+/-45/0/(6))s laminate fails due to interlaminar shear along the simple support, while the response and failure of the (+/-45)4s laminate is governed to a large degree by material nonlinearities and progressive failure.

Lee, H. H.↗

Plasticity and Kinky Chemistry of Carbon Nanotubes

Since their discovery in 1991, carbon nanotubes have been the subject of intense research interest based on early predictions of their unique mechanical, electronic, and chemical properties. Materials with the predicted unique properties of carbon nanotubes are of great interest for use in future generations of aerospace vehicles. For their structural properties, carbon nanotubes could be used as reinforcing fibers in ultralight multifunctional composites. For their electronic properties, carbon nanotubes offer the potential of very high-speed, low-power computing elements, high-density data storage, and unique sensors. In a continuing effort to model and predict the properties of carbon nanotubes, Ames accomplished three significant results during FY99. First, accurate values of the nanomechanics and plasticity of carbon nanotubes based on quantum molecular dynamics simulations were computed. Second, the concept of mechanical deformation catalyzed-kinky-chemistry as a means to control local chemistry of nanotubes was discovered. Third, the ease of nano-indentation of silicon surfaces with carbon nanotubes was established. The elastic response and plastic failure mechanisms of single-wall nanotubes were investigated by means of quantum molecular dynamics simulations.

Srivastava, Deepak↗

A Workflow to Rapidly Interrogate Multiscale Model Simulation Results Across Multiple Length Scales

Many tools can be used to visualize field and state variables for a single scale analysis so that the influence of relevant mechanisms can be evaluated. Finite element software is often utilized to simulate a unit cell of a material and visualize results at that scale. Material properties can be homogenized from individual constituents and local deformation, damage, and failure mechanisms can be evaluated within the unit cell due to globally applied boundary conditions. Such solutions can produce satisfactory results if a user is only interested in analyzing a single scale. But materials in general contain features across multiple length scales, and assumptions must be made when attempting to account for lower length scale phenomena within a higher length scale model. Multiscale modeling is an attractive means to model materials because detailed material responses can be tracked across multiple disparate length scales while reducing the amount of required assumptions. However, as the complexity of these models increases, a large amount of data can be produced, and data traceability can become increasingly more difficult. Field and state variables, which are naturally dependent on spatial position, may themselves be calculated from one or more lower length scale unit cell models each with their own appropriate field and state variables. The NASA Multiscale Analysis Tool (NASMAT) is one software that can be used to perform a multiscale analysis efficiently and output requested data at all length scales in the analysis. A companion open-source Python software, NASMAT PrePost, can be used to visualize NASMAT model results and rapidly interrogate multiscale data across multiple length scales. This presentation will demonstrate some of the key features of NASMAT PrePost on two multiscale problems by quickly displaying and demonstrating connectivity among multiscale results from large datasets.

Python↗