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At least 739 records · Page 41

Creep Deformation and Dynamic Grain Growth in an Interstitial-Free Steel

Dynamic grain growth is demonstrated to be much faster than static grain growth in a body-centered-cubic, interstitial-free steel sheet material at 850°C. Dynamic grain growth occurs during concurrent plastic deformation at elevated temperature, whereas static grain growth occurs during static annealing. Grain growth during steady-state plastic flow in tension at 850°C to a true strain of 0.2 at a true-strain rate of 10 -4 s -1 doubled grain size, while static annealing for the same time produced no increase in grain size. This is described as dynamic normal grain growth (DNGG) because no abnormally large grains were observed. The recrystallized microstructure of the steel demonstrated a log-normal distribution of grain sizes. DNGG produced bimodal grain size distributions that deviate from the theoretical expectation of a simple shift to larger sizes during normal growth. The bimodal distributions contained a remnant of small grains that were not consumed during grain growth. DNGG produced a crystallographic texture that is unique from both the recrystallized material and that produced by lattice rotation alone. DNGG strengthened the {111}⟨110⟩ and {111}⟨112⟩ components of the strong γ-fiber component in the original recrystallization texture. Lattice rotation from tensile deformation, by contrast, strengthened the α-fiber components that intersect the original γ-fiber.

36 MATERIALS SCIENCE↗

Molecular-Dynamics Analysis of the Mechanical Behavior of Plasma-Facing Tungsten

We report a systematic computational analysis of the mechanical behavior of plasma-facing component (PFC) tungsten focusing on the impact of void and helium (He) bubble defects on the mechanical response beyond the elastic regime. Specifically, we explore the effects of porosity and He atomic fraction on the mechanical properties and structural response of PFC tungsten, at varying temperature and bubble size. We find that the Young modulus of defective tungsten undergoes substantial softening that follows an exponential scaling relation as a function of matrix porosity and He atomic content. Beyond the elastic regime, our high strain rate simulations reveal that the presence of nanoscale spherical defects (empty voids and He bubbles) reduces the yield strength of tungsten in a monotonically decreasing fashion, obeying an exponential scaling relation as a function of tungsten matrix porosity and He concentration. Our detailed analysis of the structural response of PFC tungsten near the yield point reveals that yielding is initiated by emission of dislocation loops from bubble/matrix interfaces, mainly 1/2<111> shear loops, followed by gliding and growth of these loops and reactions to form <100> dislocations. Furthermore, dislocation gliding on the <111>{211} twin systems nucleates 1/6<111> twin regions in the tungsten matrix. These dynamical processes reduce the stress in the matrix substantially. Subsequent dislocation interactions and depletion of the twin phases via nucleation and propagation of detwinning partials lead the tungsten matrix to a next deformation stage characterized by stress increase during applied straining. Furthermore, our structural analysis reveals that the depletion of twin boundaries (areal defects) is strongly impacted by the density of He bubbles at higher porosities. After the initial stress relief upon yielding, increase in the dislocation density in conjunction with decrease in the areal defect density facilitates the initiation of dislocation-driven deformation mechanisms in the PFC crystal.

36 MATERIALS SCIENCE↗

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. Furthermore, we observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

97 MATHEMATICS AND COMPUTING↗

Temperature and Dynamic Strain Measurements Using a Single SAWR Sensor

Dynamic strain sensing is relevant in numerous applications involving structural health monitoring, condition-based maintenance, operation efficiency preservation, and work environment safety. These sensors are particularly critical for high-temperature (HT) harsh-environment (HE) industries such as aerospace, automotive, power plants, and advanced manufacturing. In HT/HE, sensor implementation and measurement present challenges such as maintaining sensor stability, accounting for temperature cross-sensitivity, providing HT attachment, and packaging of the sensors and system. Surface acoustic wave resonator (SAWR) sensors can address these needs and offer additional benefits such as compact size and wireless interrogation capability. The SAWR sensitivity to dynamic strain is temperature dependent, making it necessary to measure the sensor temperature in order to use the correct dynamic strain calibration curve. In this work, a method for determining the temperature, dynamic strain magnitude, and dynamic strain spectral components using a single SAWR sensor is presented. Here, the established technique for determining operational temperature and dynamic strain magnitude/spectral components using only one SAWR simplifies the sensor measurement system, thus being very attractive for HT /HE applications.

47 OTHER INSTRUMENTATION↗

Distributed Wind Resilience Metrics for Electric Energy Delivery Systems: Comprehensive Literature Review

While most people have a general concept of what it means to be “resilient,” an examination of definitions from different sources reveals that there are key commonalities but key differences as well. The lack of a generally accepted definition and application of resilience extends to electric energy delivery systems. Without an accepted definition, it is difficult to implement programs or processes to improve resiliency. In this paper, existing work from industry, regulatory bodies, and national laboratories to define and apply resilience to electric energy delivery systems is studied to understand the key components to define resilience and better understand associated metrics. This understanding is then applied to distributed wind for a specific example of how resilience of a system is affected by the technologies and generation sources used to support it. A key finding is that there is no “one size fits all” process for resilience. Each system has a “distinctiveness” characteristic, which qualifies the possibility of differences in resilience due to different threats, geography, stakeholders, risk tolerance, and mitigations. The distinctiveness characteristic extends to distributed wind, where different configurations may lend the distributed wind to contribute to the resilience of systems in a variety of ways. The findings of this research demonstrate the need for a resilience framework that can be readily applied by stakeholders to improve resilience based on the specific system, threat, risk tolerance and stakeholders.

17 WIND ENERGY↗

Photogrammetry: Develop methods for detecting deviations from expected geometry of components in a glovebox environment (Lawrence Livermore National Laboratory Aging and Lifetimes Program FY23, Milestone 8651, Grading Criterion #4)

Measurements in glovebox environments are challenging to conduct. Currently deployed techniques are time consuming and provide limited information. These limitations make current disposition and future assessments of products challenging. In FY23 we developed methods for detecting deviations of components in a glovebox environment that address these shortcomings by rapidly collecting information-dense measurements. Conducted tests demonstrate that camera pose (position and orientation) can be derived for images utilized in the photogrammetry process. This information, in conjunction with common image processing techniques, enables automated detection and size estimation of surface features. First, image processing is used to identify marks, or localized regions, that standout from the surrounding area. Then, the physical size of the region can be estimated because scale can be determined for photogrammetry images. Development of this methods shows that photogrammetry can identify measurable deviations from expected geometries. Although measurement error when using this technique through a glovebox window still needs to be reduced, this capability shows promise for eliminating or reducing the use of tedious manual measurements.

42 ENGINEERING↗

2021 Small Turbine Certification Awardee: Intergrid LLC

Currently, there are no U.S., fully certified inverters for wind turbines in the 10-15-kilowatt (kW) range. The federal government's Competitiveness Improvement Project (CIP) and Small Business Innovation Research programs present the most viable paths for manufacturers in the distributed wind energy industry to conduct research, develop their products, and, ultimately, commercialize them. Through CIP, Intergrid LLC is reducing the cost, size, and weight of its legacy inverter for distributed wind turbines while increasing efficiency, reliability, and serviceability. To accomplish this, Intergrid will address three areas related to power electronics for distributed wind turbines: (1) Software verification and functional safety certification; (2) Simulation for grid-interconnecting testing; (3) Component alternatives that reduce cost and improve reliability and serviceability. The first two areas relate to long-term management of inverter software, which, for grid-connected inverters, must comply with three standards - one issued by Underwriters Laboratories (UL) and two issued by the Institute of Electrical and Electronics Engineers.

CIP↗

Functionalized Silicon Particles for Enhanced Half- and Full-Cell Cycling of Si-Based Li-Ion Batteries

Vinylene carbonate (VC) and polyethylene oxide (PEO) have been investigated as functional agents that mimic the solid electrolyte interphase (SEI) chemistry of silicon (Si). VC and PEO are known to contribute to the stability of Si-based lithium-ion batteries as an electrolyte additive and as a SEI component, respectively. In this work, covalent surface functionalization was achieved via a facile route, which involves ball-milling the Si particles with sacrificial VC and PEO. Thermogravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS), and magic angle spinning nuclear magnetic resonance (MAS NMR) spectroscopy indicate that the additives are strongly bound to Si. In particular, MAS NMR shows Si–R or Si–O–R groups, which confirm functionalization of the Si after milling in VC or PEO. Particle size analysis by dynamic light scattering reveals that the additives facilitate particle size reduction and that the functionalized particles result in more stable dispersions based on zeta potential measurements. Raman mapping of the electrodes fabricated from the VC and PEO-coated active material with a polyacrylic acid (PAA) binder reveals a more homogenous distribution of Si and the carbon conductive additive compared to the electrodes prepared from the neat Si. Furthermore, the VC-milled Si strikingly exhibited the highest capacity in both half- and full-cell configurations, with more than 200 mAh g –1 measured capacity compared to the neat Si in the half-cell format. This is linked to an improved electrode processing based on the Raman and zeta potential measurements as well as a thinner SEI (with more organic components for the functionalized Si relative to the neat Si) based on XPS analysis of the cycled electrodes. In conclusion, the effect of binder was also investigated by comparing PAA with P84 (polyimide type), where an increased capacity is observed in the latter case.

25 ENERGY STORAGE↗

Explicit physics-informed neural networks for nonlinear closure: The case of transport in tissues

In upscaling methods, closures for nonlinear problems present a well-known challenge. While a number of theoretical methods have been proposed for handling such closures, nonlinearities still remain a significant obstacle for many problems. In this work, we use a combination of formal upscaling and data-driven machine learning for explicitly closing a nonlinear transport and reaction process in multiscale tissues. The classical effectiveness factor model is used to formulate the macroscale reaction kinetics. We train a multilayer perceptron network using training data generated by direct numerical simulations over microscale examples. Once trained, the network is used in an algorithm for numerically solving the upscaled (coarse-grained) differential equation describing mass transport and reaction in two example tissues. The network is described as being explicit in the sense that the network is trained using macroscale concentrations and gradients of concentration as components of the feature space rather than incorporating them as part of a constraint in the optimization process. Network training and solutions to the macroscale transport equations were computed for two different tissues. The two tissue types (brain and liver) exhibit markedly different geometrical complexity and spatial scale (cell size and sample size). The upscaled solutions for the average concentration are compared with numerical solutions derived from the microscale concentration fields by a posteriori averaging. There are three outcomes of this work of particular note. 1) Our overall approach results in an upscaled nonlinear PDE. The PDE is closed using a neural network, and our approach results in the definition of the classical effectiveness factor for effecting closure. 2) We identify particular source terms for the closure problem that are important for representing the structure of the closure. These source terms involve macroscale concentrations and their gradients. We adopt these source terms to use as explicit features in the learning algorithm. We find the trained networks that include the macroscale source terms generate models that are able to predict the correction factor with increased fidelity over those that do not. 3) We find that the trained network exhibits good generalizability, and it is able to predict the effectiveness factor with high fidelity for realistically-structured tissues despite the significantly different scale and geometrical complexity of the two example tissue types. This latter result emphasizes our purposeful connection between conventional averaging methods with the use of machine learning for closure; this contrasts with some machine learning methods for upscaling where the exact form of the macroscale equation remains unknown.

97 MATHEMATICS AND COMPUTING↗

The impacts of membrane pinholes on PEM water electrolysis

Polymer electrolyte membrane (PEM) water electrolysis is a promising technology to efficiently produce green hydrogen. Irregularities in membrane electrode assembly (MEA) component materials caused by manufacturing, processing, handling, or operation can lead to performance loss and failure. One example is the presence of pinholes in the membrane, which can cause increased gas transport (crossover) and lead to electrical shorting. This work investigates the effects of intentionally introduced pinholes with various sizes up to 350μm in diameter. The presence of the pinholes resulted in minimal impacts on the cell voltage (±30 mV at 4Acm -2 ). However, the pinholes significantly increased H 2 crossover, which decreased hydrogen production efficiency and increased the minimum current density for safe operation. The impacts of the pinhole on the H 2 crossover and efficiency are more severe for open pinhole features than tear-like pinhole features. In conclusion, this research demonstrates that even small pinholes cannot be disregarded from a safety, efficiency, and operating strategy perspective.

08 HYDROGEN↗

Intrinsically sodiophilic, mesoporous metal-free wetting layers based on inexpensive carbon black for sodium-metal batteries

In this article, elevated temperature molten Na batteries are seeing a resurgence of interest for low-cost electrochemical energy storage for the grid. Of the many recent innovations in this battery concept, new methods focused on intermediate temperature operation (e.g. 110–190 °C) have gained prominence as a way to enable comparable performance with less thermal energy loss and lower-cost materials of construction. However, the poor wettability of molten Na on suitable solid-electrolyte separators such as sodium Beta Alumina Solid-Electrolyte (Na-β”-Al 2 O 3 , ‘BASE’) requires continued innovation in interface engineering to promote full utilization of the solid-electrolyte surface area and minimize cell resistance. There have been many successful approaches to improve Na-wettability to-date including heat treatment in an inert atmosphere to remove adsorbed surface species, deposition of alloying metals such as Pb, Sn, or Bi, and use of carbon-based interfacial layers. However, these approaches either lack the ability to provide good wetting at very low temperatures (near the melting point of Na) or rely on non-scalable processes and/or toxic/expensive metals. To solve these issues, a new carbon-based sodiophilic treatment is demonstrated, which utilizes inexpensive components to form a meso/macroporous sodiophilic layer, is easily applied via drop-casting or spray-coating, provides excellent wetting as low as 110 °C, and is completely metal-free. It is found that the good sodium wetting can be attributed to the wider range of pore sizes in the carbon layers demonstrated in this study. Na wetting may occur as surface tension is initially broken by larger pores, followed by the intrusion of molten Na into smaller pores due to the apparent intrinsic affinity of Na-metal for carbon surfaces, in conjunction with the capillarity effect. Low cell-level area specific resistances of 20–30 and 13–15 Ω·cm 2 are demonstrated at 110 and 140 °C respectively. Finally, the utility of this metal-free wetting layer for solid-Na anodes is explored, showing that the metal-free wetting layer can reach a critical current density of 1.88 mA·cm -2 at 30 °C.

25 ENERGY STORAGE↗

Visualization of large-scale charged domain Walls in hexagonal manganites

A ferroelectric charged domain wall (CDW) carries bound charges, originating from the variation of the normal components of polarization across the domain boundary, leading to a possible two-dimensional conductive interface in insulating materials. The ferroelectric CDW can be precisely created, erased, and manipulated, therefore offering an intriguing pathway toward the design of nano-devices. However, due to rather large energy costs, the size of the CDW is usually on the nanoscale. Here, taking flux-grown ferroelectric hexagonal manganites (h-RMnO 3 ) as an example, we creatively adopted an accessible inclined polishing process to reveal the domain evolution of stripe, loop, and vortex domain patterns by depth profiling. Interestingly, we observed an unexpected large-scale straight CDW in as-grown LuMnO 3 with length up to a millimeter size, which may result from the “polar catastrophe” during the flux growth. The large-scale CDW has a residual influence on the formation of the loop domain when the crystal anneals below the ferroelectric transition temperature, but completely disappears as the topological vortices emerge. The observed large-scale CDWs make h-RMnO 3 a potential candidate for advanced electronic devices, leading to a panoply of desired properties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Self-assembly of wood-based shape memory composites triggered by solar-thermal energy

Transporting and assembling large, complex structures poses significant challenges due to their size, geometry, and cost. Additionally, the installation sites are often inaccessible or hazardous for humans, necessitating self-assembling capabilities in these structures. To mitigate these challenges, we propose using 3D printing materials with shape memory effect (SME) for both transport and construction. This approach involves developing 3D modular components into flat sheets for easier transportation, and then self-assembling into 3D structures on-site using solar energy. To gain a deeper understanding of the factors influencing material memory performance, we have chosen a composite PLA/WF, which is polylactic acid (PLA) with 20 wt% wood flour (WF) for this purpose, leveraging its high tensile modulus at 0.966 GPa, low cost, and sustainability. Printed shapes with this material can maintain a recovery ratio over 90% after 3 cycles. While traditional composites fillers (e.g. glass or carbon fiber) are added to enhance mechanical and thermal properties, the addition of bio-based fillers like WF accomplish similar goals without compromising sustainability. We conducted multiple experiments to demonstrate how environmental conditions (i.e. temperature) maximize the material’s SME. Although still at an early stage, this study provides initial insights into bridging the gap between the small-scale nature of shape memory polymers (SMPs) and their potential for large-scale additive manufacturing, addressing a critical need for efficient and sustainable construction. In the long term, we hope our study contributes to the design vision of utilizing SMPs for transportation, assembly, and deployment of complex structures, providing a new pathway for sustainable construction and transportation of large-scale structures to hard-to-access locations such as disaster-affected areas and remote deserts, etc.

4D printing↗

A Bulk-Capacitance Reduction Method Using Self-Driven Thyristor for AC-DC Converters

Universal serial bus power delivery (USB-PD) fast chargers equipped with wide-bandgap devices are driven to higher power density and efficiency. Furthermore, the indispensable high-voltage bulk capacitors used to smooth the rectifier output could take 40% of the total system volume due to the large capacitance value required. This paper discussed a capacitor reduction method using a self-driven thyristor scheme comprised of only three components in total. No extra control circuit is needed. Circuit analysis and design equations are presented, and the design results are implemented in a 60-W GaN-based active-clamp flyback converter. The measurement results on the prototype show a 36.4% reduction of the bulk-capacitor size with similar efficiency compared to the conventional solution.

30 DIRECT ENERGY CONVERSION↗

Genome‐wide association and genomic prediction for yield and component traits of Miscanthus sacchariflorus

Abstract Accelerating biomass improvement is a major goal of Miscanthus breeding. The development and implementation of genomic‐enabled breeding tools, like marker‐assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of Miscanthus breeding. The present study conducted genome‐wide association (GWA) and genomic prediction of biomass yield and 14 yield‐components traits in Miscanthus sacchariflorus . We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across 4 years in one subtropical and three temperate locations and genotyped with 268,109 single‐nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported Miscanthus studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield‐component traits in M. sacchariflorus that may facilitate marker‐assisted breeding for biomass yield. Genomic prediction accuracy for the yield‐related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of M. sacchariflorus were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia ( N = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of M. sacchariflorus . This study indicated that MAS and genomic prediction will likely be beneficial for conducting population‐improvement of M. sacchariflorus .

09 BIOMASS FUELS↗

First demonstration of a TES based cryogenic Li 2 MoO 4 detector for neutrinoless double beta decay search

Cryogenic calorimetric experiments to search for neutrinoless double-beta decay (0vββ) are highly competitive, scalable and versatile in isotope. The largest planned detector array, CUPID, is comprised of about 1500 individual Li 2 100 MoO 4 detector modules with a further scale up envisioned for a follow up experiment (CUPID-1T). In this article, we present a novel detector concept targeting this second stage with a low impedance TES based readout for the Li 2 MoO 4 absorber that is easily mass-produced and lends itself to a multiplexed readout. We present the detector design and results from a first prototype detector operated at the NEXUS shallow underground facility at Fermilab. The detector is a 2-cm-side cube with 21 g mass that is strongly thermally coupled to its readout chip to allow rise-times of ~0.5 ms. This design is more than one order of magnitude faster than present NTD based detectors and is hence expected to effectively mitigate backgrounds generated through the pile-up of two independent two neutrino decay events coinciding close in time. Together with a baseline resolution of 1.95 keV (FWHM) these performance parameters extrapolate to a background index from pile-up as low as 5 • 10 –6 counts/keV/kg/yr in CUPID size crystals. The detector was calibrated up to the MeV region showing sufficient dynamic range for 0vββ searches. In combination with a SuperCDMS HVeV detector this setup also allowed us to perform a precision measurement of the scintillation time constants of Li 2 MoO 4 , which showed a primary component with a fast O(20 μs) time scale. Similar content being viewe

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

FY 2019 DOE-EERE Materials Vehicle Technologies Office Consolidated Report

The Materials Technology Program supports the Vehicle Technologies Office’s mission to help consumers and businesses reduce their transportation energy costs while meeting or exceeding vehicle performance expectations. The propulsion materials research portfolio seeks to develop higher performance materials that can withstand increasingly extreme environments and address the future properties needed for a variety of high-efficiency powertrain types, sizes, fueling concepts, and combustion modes. The lightweight materials research portfolio enables improvements in fuel economy by providing properties that are equal to or better than traditional materials at a lower weight. Because it takes less energy to accelerate a lighter object, replacing cast-iron and traditional steel components with lightweight materials such as advanced high-strength steels, magnesium alloys, aluminum alloys, and fiber-reinforced polymer composites can directly reduce a vehicle’s fuel consumption. By 2025, Materials Technology research activities seek to enable a 25% weight reduction of the glider for light-duty vehicles including body, chassis, and interior as compared to a 2015 baseline at no more than a $5/lb-saved increase in cost.

99 GENERAL AND MISCELLANEOUS↗

FY2019 Materials Annual Progress Report

The Materials Technology Program supports the Vehicle Technologies Office’s (VTO’s) mission to help consumers and businesses reduce their transportation energy costs while meeting or exceeding vehicle performance expectations. The propulsion materials research portfolio seeks to develop higher performance materials that can withstand increasingly extreme environments and address the future properties needed for a variety of high-efficiency powertrain types, sizes, fueling concepts, and combustion modes. The lightweight materials research portfolio enables improvements in fuel economy by providing properties that are equal to or better than traditional materials at a lower weight. Because it takes less energy to accelerate a lighter object, replacing cast-iron and traditional steel components with lightweight materials such as advanced high-strength steels, magnesium (Mg) alloys, aluminum (Al) alloys, and fiber-reinforced polymer composites can directly reduce a vehicle’s fuel consumption. By 2025, Materials Technology research activities seek to enable a 25% weight reduction of the glider for light-duty (LD) vehicles including body, chassis, and interior as compared to a 2015 baseline at no more than a $5/lb-saved increase in cost.

33 ADVANCED PROPULSION SYSTEMS↗