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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Circulating Mirna Spaceflight Signature Reveals Targets to Mitigate Associated Health Risks

We have identified and validated a spaceflight-associated microRNA (miRNA) signature that is shared by rodents and humans in response to simulated, short-duration, and long-duration spaceflight and regulates vascular damage caused by simulated deep space radiation. In previous studies, we had identified miRNAs that are predicted to regulate rodent responses to spaceflight in low-Earth orbit. Here we have confirmed the expression of these proposed spaceflight associated miRNAs in rodents reacting to simulated spaceflight conditions (exposure to ionizing radiation combined with simulated microgravity) and in astronaut samples from the NASA Twins Study via direct quantification of miRNAs, miRNA sequencing, and inferring miRNA target levels based on single-cell RNA (scRNA-seq) and single-cell chromatin (scATAC-seq) sequencing data. To demonstrate the physiological relevance of key spaceflight associated miRNAs, we utilized antagomirs to inhibit their expression and successfully rescue simulated deep space radiation-mediated damage in human 3D vascular constructs.

Sherina Malkani↗
DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1984

The structural optimization of a spreader bar for twin lift helicopter operations

An optimization study was performed to develop a minimum weight spreader bar to allow two helicopters to lift the same payload. With this arrangement, the maximum payload that can be lifted is almost doubled without the expense of designing and building a new helicopter. The concept has had some limited use by civil helicopter operators using small helicopters and has been demonstrated in large scale by two CH-54's which successfully lifted a total load of 20 ton. To this point, rather heavy available beams or tower structures have been used for the spreader bar. Since the weight of the bar not only detracts from payload but also adds to the logistics problem, there are more than the usual incentives to minimize weight. Since the design requirement is for classic beam column with uniform side loads resulting from bar weight and aerodynamic drag, the design problem is particularly amenable to optimization. A study has been performed at Sikorsky to establish the minimum weight for a spreader bar sized to carry a load equal to the capacity of two Army BLACK HAWK helicopters. Toward this end, a computer program was written to analyze the spreader bar deflections and stresses and coupled to the NASA developed CONMIN optimization routines.

Dobyns, A.↗
DOE OSTI2022

Design metastability in high-entropy alloys by tailoring unstable fault energies

Metastable alloys with transformation-/twinning-induced plasticity (TRIP/TWIP) can overcome the strength-ductility trade-off in structural materials. Originated from the development of traditional alloys, the intrinsic stacking fault energy (ISFE) has been applied to tailor TRIP/TWIP in high-entropy alloys (HEAs) but with limited quantitative success. Here, we demonstrate a strategy for designing metastable HEAs and validate its effectiveness by discovering seven alloys with experimentally observed metastability for TRIP/TWIP. We propose unstable fault energies as the more effective design metric and attribute the deformation mechanism of metastable face-centered cubic alloys to unstable martensite fault energy (UMFE)/unstable twin fault energy (UTFE) rather than ISFE. Among the studied HEAs and steels, the traditional ISFE criterion fails in more than half of the cases, while the UMFE/UTFE criterion accurately predicts the deformation mechanisms in all cases. The UMFE/UTFE criterion provides an effective paradigm for developing metastable alloys with TRIP/TWIP for an enhanced strength-ductility synergy.

36 MATERIALS SCIENCE↗
NASA NTRS2005

Evaluation of the Advanced Subsonic Technology Program Noise Reduction Benefits

This report presents a detailed evaluation of the aircraft noise reduction technology concepts developed during the course of the NASA/FAA Advanced Subsonic Technology (AST) Noise Reduction Program. In 1992, NASA and the FAA initiated a cosponsored, multi-year program with the U.S. aircraft industry focused on achieving significant advances in aircraft noise reduction. The program achieved success through a systematic development and validation of noise reduction technology. Using the NASA Aircraft Noise Prediction Program, the noise reduction benefit of the technologies that reached a NASA technology readiness level of 5 or 6 were applied to each of four classes of aircraft which included a large four engine aircraft, a large twin engine aircraft, a small twin engine aircraft and a business jet. Total aircraft noise reductions resulting from the implementation of the appropriate technologies for each class of aircraft are presented and compared to the AST program goals.

Golub, Robert A.↗
NASA NTRSDate not supplied

Circulating miRNA Signature Predicts and Rescues Spaceflight Associated Health Risks

We have identified and validated a spaceflight-associated microRNA (miRNA) signature that is shared by rodents and humans in response to simulated and real spaceflight and regulates vascular damage by simulated deep space radiation. In previous studies, we identified miRNAs that are predicted to regulate rodent responses to spaceflight in low-Earth orbit. Here we have validated the expression of key spaceflight-associated miRNAs in rodents reacting to simulated spaceflight conditions (exposure to ionizing radiation combined with simulated microgravity) and in astronaut samples from the NASA Twin Study. We demonstrate that this circulating miRNA siganture is conserved between these different species and will serve as an ideal biomarker to monitor increase health risk due to exposure to the space environment. Lastly, to demonstrate their physiological relevance, we have utilized antagomirs to target a subset of miRNAs from the spaceflight associated signature to successfully rescue simulated deep space radiation-mediated damage in human 3D vascular constructs. These results provide strong evidence to further develop a miRNA based countermeasure in astronauts.

Afshin Beheshti↗
NASA NTRS1982

Liquid encapsulated Czochralski growth of low dislocation GaAs

The availability of high-quality, large-diameter GaAs substrates is key to the successful development and production of high-speed GaAs devices and high-efficiency GaAs solar cells. The liquid encapsulated Czochralski (LEC) technique has provided a means for producing large-diameter GaAs. Progress in improving the LEC growth process which has resulted in 3-inch GaAs crystals with exceptionally low dislocation densities and reduced propensity for twinning is reported. Undoped, semi-insulating GaAs ingots were grown in a Melbourn high-pressure LEC system. The effects of seed perfection, seed necking, cone angle, melt stoichiometry, ambient pressure, thickness of the B2O3 encapsulating layer, and diameter control on the dislocation density were investigated. The material was characterized by preferential etching and X-ray topography. It is shown that 3-inch diameter substrates can be produced with dislocation densities as low as 6000 per sq cm through proper selection and control of growth parameters. Also, the incidence of twinning can be reduced significantly by growing from slightly As-rich melts.

Kirkpatrick, C. G.↗
NASA NTRS2002

CRYSTAL-FACE: A Field Experiment and Modeling Program Focused on Tropical Anvils and Cirrus Layers

The Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE) is a measurement campaign designed to investigate tropical Cirrus cloud physical properties and formation processes. Understanding the production of upper tropospheric cirrus clouds is essential for the successful modeling of 'he Earth's climate. The deployment phase will occur in July, 2002 in southern Florida, USA. Several aircraft will be used, including the ER-2 and Proteus for cloud remote sensing, the WB-57 and Citation for in situ cloud measurements, the P-3 with a Doppler radar for characterization of convective systems, and the Twin otter for sampling of inflow airmasses. In addition, numerous ground-based and satellite remote sensing measurements will be contributing. A central focus of the mission is improvement of our ability to model cirrus clouds with numerical models. Several research groups with a variety of model types (cloud-resolving models, mesoscale models, weather-prediction models, and general circulation models) will be participating. Our hope is to fully characterize several mulonimbus/cirrus anvil systems that can be used as case studies for testing and improvement of the models. The models will be used for investigating cirrus generation and dissipation processes and the sensitivity of tropical cirrus to convective intensity and aerosol properties. Ultimately, we expect this effort to improve our ability to represent tropical cirrus in GCMs. A general description of the CRYSTAL-FACE program will be presented, with an emphasis on the cloud modeling approach.

Jenson, Eric↗
DOE OSTI2022

Accumulative Roll Bonding of Alloy 2205 Duplex Steel and the Accompanying Impacts on Microstructure, Texture, and Mechanical Properties

The mechanical and microstructural evolution of Alloy 2205 during severe plastic deformation is examined in this study. A combination of accumulative roll bonding (ARB) and cold rolling results in the successful formation of a nanograined dual-phase microstructure of austenite and ferrite with some transformed martensite. Severe deformation to cumulative reductions of 80.5, 92.5, 95, and 97 pct were performed. Microscopy indicates that grain dimensions in the sheet normal direction is less than 100 nm for reductions ≥ 92.5 pct. Shear banding is observed at reductions ≥ 95 pct while twinning is only observed at reductions < 92.5 pct. Neutron diffraction measurements indicated the presence of martensite for reductions ≥ 95 pct at ~ 8 pct volume fraction. Taken in conjunction, it appears that during initial ARB processing, both slip and twinning are active plastic mechanisms. As twinning becomes exhausted, martensitic transformation, slip, and intermittent shear banding account for the active plasticity mechanisms. Material hardness saturates at 92.5 pct reduction, with a maximum hardness of 45 HRC. Sub-sized tensile testing confirms this approximate hardness with measurements indicating a UTS of ~ 1440 MPa. Texture analysis of crystal orientation distributions in the plate normal direction suggest an approximate Kurdjumov–Sachs orientation relationship at all reductions above 80 pct indicating stability of the orientation relationship at high strains. The intragranular structure develops a fine scale sub-grain content with increasing deformation, resulting in a continual evolution of texture up to and including 97 pct reduction. The final structure presents strong components of Goss and rotated cube texture in both the austenite and ferrite. In this body of work we aim to compare ARB of an industrially relevant FCC/BCC system (Alloy 2205) to historical model FCC/BCC systems such as Cu/Nb.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Deep Generative Models that Solve PDEs: Distributed Computing for Training Large Data-Free Models

Recent progress in scientific machine learning (SciML) has opened up the possibility of training novel neural network architectures that solve complex partial differential equations (PDEs). Several (nearly data free) approaches have been recently reported that successfully solve PDEs, with examples including deep feed forward networks, generative networks, and deep encoder-decoder networks. However, practical adoption of these approaches is limited by the difficulty in training these models, especially to make predictions at large output resolutions (≥1024×1024). Here we report on a software framework for data parallel distributed deep learning that resolves the twin challenges of training these large SciML models - training in reasonable time as well as distributing the storage requirements. Our framework provides several out of the box functionality including (a) loss integrity independent of number of processes, (b) synchronized batch normalization, and (c) distributed higher-order optimization methods. We show excellent scalability of this framework on both cloud as well as HPC clusters, and report on the interplay between bandwidth, network topology and bare metal vs cloud. We deploy this approach to train generative models of sizes hitherto not possible, showing that neural PDE solvers can be viably trained for practical applications. We also demonstrate that distributed higher-order optimization methods are 2-3× faster than stochastic gradient-based methods and provide minimal convergence drift with higher batch-size.

PDEs↗
DOE OSTI2025

Modeling the Impacts of Hydrogen Extraction on Anaerobic Fermentation Systems Using a Modified ADM1 Model

Here, this paper presents a modified ADM1 (mADM1) model for use in assessing the influence of active dissolved H 2 extraction on biogas production from anaerobic fermentation reactors, specifically in the context of high-strength brewery wastewater as the feed. The modified model adds regulation factors to account for the varying product stoichiometry of glucose degradation reactions as a function of H 2 concentration in anaerobic digestion, and incorporates the use of both lactate and ethanol as intermediates. The changes to the model are expected to better predict the effects of H 2 removal on the production of H 2 in fermentation processes. Both ADM1 and mADM1 were calibrated against experimental data from a fluidized-bed reactor containing encapsulated acidogenic-acetogenic microbial communities treating real brewery wastewater. The calibrated models were validated against another fluidized-bed reactor identical to the calibration reactor, with the addition of a hollow-fiber membrane module that was used to reduce dissolved H 2 concentrations in the validation reactor. It was found that ADM1 over-estimated the H 2 production rates of the validation reactor (117 mL/day simulated vs. 16.48 mL/day experimental), whereas mADM1 was able to successfully predict fermentation, and specifically the H 2 production rate (17 mL/day). The presented model is a first step towards a model that can predict the effects of dissolved H 2 removal on fermentation processes.

Anaerobic Digestion↗
NASA NTRS2018

The Balloon Experimental Twin Telescope for Infrared Interferometry (BETTII): First Flight

The Balloon Experimental Twin Telescope for Infrared Interferometry (BETTII) is an 8-meter far-infrared (30-100 μm) double-Fourier Michelson interferometer designed to fly on a high altitude scientific balloon. The project began in 2011, and the payload was declared ready for flight in September 2016. Due to bad weather, the first flight was postponed until June 2017; BETTII was successfully launched on June 8, 2017 for an engineering flight. Over the course of the one night flight, BETTII acquired a large amount of technical data that we are using to characterize the payload. Unfortunately, the flight ended with an anomaly that resulted in destruction of the payload. In this paper, we will discuss the path to BETTII flight, the results of the first flight, and some of the plans for the future.

Rinehart, S. A.↗
DOE OSTI2025

Teleoperation of Construction Robots Using Human Interaction: Case Study Examples: Preprint

The integration of advanced teleoperation methods in construction robotics has the potential to enhance productivity and safety in demanding environments. Among different methods, hand gestures have emerged as an intuitive approach, enabling seamless communication between human operators and robotic systems. This study demonstrates the use of hand gestures for controlling a model robotic excavator and a virtual robotic arm in construction applications. Two case study examples are presented. In the first case study, a series of hand gestures are performed to control a model robotic excavator's bucket and arm movements. The second case study focuses on using hand gestures to control a virtual robotic arm to perform a material handling task in a simulated environment. In both cases, the performed hand gestures are all successfully captured and interpreted by the gesture-based teleoperation method to conduct the corresponding tasks, which demonstrates the application of the gesture-based control method for various types of construction robots. Also, the limitations of the gesture-based teleoperation method (e.g., recognition delay, sensitivity to motion outliers) are discussed. Future work will focus on developing a digital twin system to support gesture-based teleoperation for a wider range of construction robots.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Development of Integrated Mechanical Pods

This presentation highlights early wins, updated progress, and upcoming developments on ‘national-scale shared development platform’ for rapid prototyping, testing and validation of various integrated Mechanical Pod solutions and form factors. Such pod solutions consist of a set of all-electric heat pump mechanical equipment that have integrated functionalities through built-in controls, with heating, cooling, hot water, ventilation (including energy recovery), electrical management, and battery storage within a single package. The presentation draws inspiration from the success of bathroom pods in the US modular construction industry, UK’s efforts with unitizing mechanical systems as ‘utility cupboards’, and VEIC’s early wins in design-build of all-electric Mechanical Pod solutions in Vermont. The presentation includes researchers and partners involved with NREL in Design for Manufacturing and Assembly (DfMA), Virtual Design and Construction (VDC), and digital twin based process optimization modeling of integrated Mechanical Pod solutions. The presentation aims to highlight early wins from such a platform and how various physical and virtual tools are currently being employed as part of NREL’s ongoing multi-year project funded by US DOE. Streamlined procurement, coordination, installation, and O&M of Mechanical Pods such that the majority of work is delegated to the off-site modular factory implies monetary savings. Such a seemingly basic shift in location of the construction process leads to great reduction in complexity, first cost, lead time, and waste, and greater opportunities for innovative compartmentalization and integration of mechanical systems appropriately sized for each apartment or hotel guest room. However, past studies on unitized combination systems show that high installation costs, maintenance issues, challenges with system integration, limitations in existing electrical infrastructure, and lack of architecturally appealing solutions are key barriers. NREL and partners aim to address key barriers through DfMA approach, rapid prototyping and testing, and digital twin process optimization modeling. The presentation is also a call for interested entities to partner with NREL as part of the national-scale development platform, help drive both product and process innovation, and encourage open source sharing of learnings. Learning objectives include (1) learn about the vision of national-scale shared development platform for process-product innovation on integrated mechanical pod solutions and how to get involved, (2) gain an understanding of the components of an all-electric, high performance home, design characteristics and equipment included in an all-electric mechanical pod, integration of mechanical systems within a modular factories’ assembly line, and the system’s commissioning, operation and maintenance. The pre-planning and coordination with the factory and sub-contractors are also highlighted, (3) gain an understanding of using process modeling tools to quantify resource-constrained performance of operations (such as integration of energy efficiency strategies) to manufacture modules of varying design, (4) gain insights on virtual design, rapid prototyping, and emulated testing of various form factors across different climatic conditions. The need for such preliminary testing with open source sharing of learnings will also be highlighted.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS1998

Fiber Supported Droplet Combustion-2 (FSDC-2)

Experimental results for the burning characteristics of fiber supported, liquid droplets in ambient Shuttle cabin air (21% oxygen, 1 bar pressure) were obtained from the Glove Box Facility aboard the STS-94/MSL-1 mission using the Fiber Supported Droplet Combustion - 2 (FSDC-2) apparatus. The combustion of individual droplets of methanol/water mixtures, ethanol, ethanol/water azeotrope, n-heptane, n-decane, and n-heptane/n-hexadecane mixtures were studied in quiescent air. The effects of low velocity, laminar gas phase forced convection on the combustion of individual droplets of n-heptane and n-decane were investigated and interactions of two droplet-arrays of n-heptane and n-decane droplets were also studied with and without gas phase convective flow. Initial diameters ranging from about 2mm to over 6mm were burned on 80-100 micron silicon fibers. In addition to phenomenological observations, quantitative data were obtained in the form of backlit images of the burning droplets, overall flame images, and radiometric combustion emission measurements as a function of the burning time in each experiment. In all, 124 of the 129 attempted experiments (or about twice the number of experiments originally planned for the STS-94/MSL-1 mission) were conducted successfully. The experimental results contribute new observations on the combustion properties of pure alkanes, binary alkane mixtures, and simple alcohols for droplet sizes not studied previously, including measurements on individual droplets and two-droplet arrays, inclusive of the effects of forced gas phase convection. New phenomena characterized experimentally for the first time include radiative extinction of droplet burning for alkanes and the "twin effect" which occurs as a result of interactions during the combustion of two-droplet arrays. Numerical modeling of isolated droplet combustion phenomenon has been conducted for methanol/water mixtures, n-heptane, and n-heptane/n-hexadecane mixtures, and results compare quantitatively with those found experimentally for methanol/water mixtures. Initial computational results qualitatively predict experimental results obtained for isolated n-heptane and n-heptane/n-hexadecane droplet combustion, although the effects of sooting are not yet included in the modeling work. Numerical modeling of ethanol and ethanol/water droplet burning is under development. Considerable data remain to be fully analyzed and will provide a large database for comparisons with further numerical and analytical modeling and development of future free droplet experiments aboard space platforms.

Colantonio, Renato↗
DOE OSTI2021

Tailoring plasticity mechanisms in compositionally graded hierarchical steels fabricated using additive manufacturing

Abstract While there exists in nature abundant examples of materials with site-specific gradients in microstructures and properties, engineers and designers have traditionally used monolithic materials with discrete properties. Now, however, additive manufacturing (AM) offers the possibility of creating structures that mimic some aspects of nature. One example that has attracted attention in the recent years is the hierarchical structure in bamboo. The hierarchical architecture in bamboo is characterized by spatial gradients in properties and microstructures and is well suited to accommodate and survive complex stress states, severe mechanical forces, and large deformations. While AM has been used routinely to fabricate functionally graded materials, this study distinguishes itself by leveraging AM and physical metallurgy concepts to trigger cascading deformation in a single sample. Specifically, we have been successful in using AM to fabricate steel with unique spatial hierarchies in structure and property to emulate the structure and deformation mechanisms in natural materials. This study shows an improvement in the strength and ductility of the nature-inspired “hierarchical steel” compared with conventional cast stainless steels. In situ characterization proves that this improvement is due to the sequential activation of multiple deformation mechanisms namely twinning, transformation-induced plasticity, and dislocation-based plasticity. While significantly higher strengths can be achieved by refining the chemical and processing technique, this study sets the stage to achieve the paradigm of using AM to fabricate structures which emulate the flexibility in mechanical properties of natural materials and are able to adapt to in-service conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Accelerating Laboratory-Based, All-Solid-State Battery Research and Development: Industrially Relevant Small-Batch Dry-Processing, Small and Low-Cost Test Fixtures, and Short-Tolerant Separators

This work presents improvements to mixing (for dry-processed electrodes), separator robustness, and cell testing jigs for all-solid-state batteries (ASSBs). These developments combine synergistically to enable rapid research and development of ASSB catholytes. A mechanical "kneader" is designed and built which emulates the mixing and fibrillation of poly-tetrafluoroethylene binder that occurs in industrially relevant twin-screw extruders. A modest improvement in the mixing and dispersion catholyte materials is observed using micro-resolution X-ray computed tomography (X-ray CT). Catholytes are paired with an In-metal anode and separated by a novel, dual-layer, polyaramid-fiber-supported, sulfide-solid electrolyte (Li6 PS5 Cl) separator. This separator achieves high short tolerance which enabled a 95% success rate across 20 attempted cells and to date over 100 successful cells have been built. ASSBs were tested in a 2032 coin-cell format. Simultaneous cycling of a large number of cells is further enabled by a compact and low cost (~ 38 USD per jig) pressure application jig of which 100 have been constructed to date. The utility of these advances is demonstrated through a brief study on the effect cathode-side conductive carbon and current collector type has on capacity and rate performance.

25 ENERGY STORAGE↗
NASA NTRS2013

Modeling X-Ray Binary Evolution in Normal Galaxies: Insights from SINGS

We present the largest-scale comparison to date between observed extragalactic X-ray binary (XRB) populations and theoretical models of their production. We construct observational X-ray luminosity functions (oXLFs) using Chandra observations of 12 late-type galaxies from the Spitzer Infrared Nearby Galaxy Survey (SINGS). For each galaxy, we obtain theoretical XLFs (tXLFs) by combining XRB synthetic models, constructed with the population synthesis code StarTrack, with observational star formation histories (SFHs). We identify highest-likelihood models both for individual galaxies and globally, averaged over the full galaxy sample. Individual tXLFs successfully reproduce about half of oXLFs, but for some galaxies we are unable to find underlying source populations, indicating that galaxy SFHs and metallicities are not well matched and/or XRB modeling requires calibration on larger observational samples. Given these limitations, we find that best models are consistent with a product of common envelope ejection efficiency and central donor concentration approx.. = 0.1, and a 50% uniform - 50% "twins" initial mass-ratio distribution. We present and discuss constituent subpopulations of tXLFs according to donor, accretor and stellar population characteristics. The galaxy-wide X-ray luminosity due to low-mass and high-mass XRBs, estimated via our best global model tXLF, follows the general trend expected from the L(sub X) - star formation rate and L(sub X) - stellar mass relations of Lehmer et al. Our best models are also in agreement with modeling of the evolution both of XRBs over cosmic time and of the galaxy X-ray luminosity with redshift.

Normal Galaxies↗