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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

EVs@Scale Next-Gen Profiles - Fleet Utilization 2023

As U.S. fleet operators begin transitioning to electric vehicles (EVs), critical questions arise regarding how to manage this shift without disrupting fleet operations or placing undue stress on the electric grid. A major challenge for fleets is maintaining effective operational schedules while accommodating charging requirements, particularly with high-power charging (HPC) infrastructure, which presents grid stability concerns for utilities. Proposed solutions such as charging substations, megawatt charging systems (MCS), and smart charge management systems (SCMS) offer potential pathways forward, but their effectiveness depends on alignment with real-world fleet behavior and operational constraints. This report investigates the charging and utilization behavior of EV and EVSE fleets actively employing HPC technologies by conducting detailed case study analyses based on telematics data. A suite of predefined metrics—covering charging, routing, and other operational behaviors—is developed to evaluate the impact of fleet activities on grid infrastructure and identify opportunities for optimization. Results highlight variations in charging behavior across fleets, such as weekday versus weekend usage, diurnal charging trends, and the role of operational predictability in enabling SCMS effectiveness. While SCMS can help lower costs and improve energy efficiency for fleets with stable schedules, they may be insufficient for fleets with highly variable or long-haul operations, which may require more robust solutions like MCS. Visualization of aggregated hourly energy metrics reveals that while fleet behaviors are diverse, there are common temporal patterns that could inform infrastructure planning and energy management. These insights emphasize the need for fleet-specific charging strategies that minimize grid impact while supporting reliable fleet operations. Additionally, the report underscores the broader economic stakes of electrification, particularly in high-value markets such as freight, where misaligned transitions could stall EV adoption. By examining current EV and EVSE fleet deployments using predetermined standardized metrics, this study offers a foundation for developing technologies and operational frameworks that support scalable, grid-compatible electrification across a variety of fleet types while establishing a baseline understanding of operational behaviors. In doing so, we aim to ensure that future charging solutions reflect actual fleet needs and grid constraints—an essential step toward maintaining operational continuity and achieving a successful transition to electric fleet operations.

Charging↗
DOE OSTI2022

Kinetic model development and Bayesian uncertainty quantification for the complete reduction of Fe-based oxygen carriers with CH 4 , CO, and H 2 for chemical looping combustion

In this work, three kinetic models are developed and calibrated for the complete multi-step reduction of an Fe-based oxygen carrier (OC) particle with CH 4 , CO, and H 2 , using data from thermogravimetric analysis. The complete reduction rate profiles exhibit complex dynamics whose trajectory is significantly different depending on the reducing gas. A Bayesian model building and parameter estimation framework is applied for simultaneous parameter and model structure uncertainty quantification. The final models show excellent agreement between model predictions and calibration data, as well as new data not used for calibration (for the reduction of the OC with CH 4 ). Parameter uncertainty is quantified by determining joint posterior distribution, and model structure uncertainty is addressed by incorporating Gaussian process stochastic functions (represented by Bayesian smoothing splines) into the kinetic models. The final kinetic models with discrepancy functions are readily employable in equation-oriented simulation and optimization platforms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Ion Size Effects on the Thermodynamic, Kinetic, and Mechanical Properties during Ion Exchange in Solid-State Electrolytes

Ion exchange offers a pathway to impose residual compressive stresses to mitigate the electro-chemo-mechanical cracking of solid-state electrolytes such as lithium lanthanum zirconium oxide. This study uses a coupled multiscale framework (integrating density functional theory (DFT), molecular dynamics (MD), and continuum modeling) to examine how exchange ion size influences stress, diffusion, fracture toughness, and electronic properties. Larger isovalent ions (Na + , Ag + , K + ) were exchanged with Li + , with DFT confirming their preference for octahedral 96h sites and a linear relationship between ion size and chemical free expansion coefficient. MD simulations reveal stress and concentration effects on exchange ion diffusivity at elevated temperatures, with Na + and Ag + maintaining favorable mobility while K + showing concentration-dependent clustering. Continuum modeling predicts the range of fracture strength improvements and the required ion exchange concentration profile. It was shown that a 5% surface exchange concentration can induce ∼0.6 GPa of surface compressive stress using Na + and ∼1.0 GPa of surface compressive stress using Ag + . On the other hand, larger ion exchange species may penalize Li + diffusivity by increasing the activation volume and activation energy. Interestingly, Na + has a negligible penalty on Li-ion diffusivity. The room temperature Li + ion diffusivity is reduced by ∼40% with Ag + ion exchange. Electronic band structure analysis shows no size-dependent change in the bandgap, though Ag + introduces localized defect states near the valence band maximum. This study highlights ion size as a key factor in optimizing LLZO properties, offering a framework to improve the solid-state battery performance.

Jagad, Harsh D. [Brown Univ., Providence, RI (Unit↗
DOE OSTI2021

Computing molecular excited states on a D-Wave quantum annealer

Abstract The possibility of using quantum computers for electronic structure calculations has opened up a promising avenue for computational chemistry. Towards this direction, numerous algorithmic advances have been made in the last five years. The potential of quantum annealers, which are the prototypes of adiabatic quantum computers, is yet to be fully explored. In this work, we demonstrate the use of a D-Wave quantum annealer for the calculation of excited electronic states of molecular systems. These simulations play an important role in a number of areas, such as photovoltaics, semiconductor technology and nanoscience. The excited states are treated using two methods, time-dependent Hartree–Fock (TDHF) and time-dependent density-functional theory (TDDFT), both within a commonly used Tamm–Dancoff approximation (TDA). The resulting TDA eigenvalue equations are solved on a D-Wave quantum annealer using the Quantum Annealer Eigensolver (QAE), developed previously. The method is shown to reproduce a typical basis set convergence on the example $$\hbox {H}_2$$ H 2 molecule and is also applied to several other molecular species. Characteristic properties such as transition dipole moments and oscillator strengths are computed as well. Three potential energy profiles for excited states are computed for $$\hbox {NH}_3$$ NH 3 as a function of the molecular geometry. Similar to previous studies, the accuracy of the method is dependent on the accuracy of the intermediate meta-heuristic software called qbsolv.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Optimization of the size and shape of the scanning aperture in autocollimator-based deflectometric profilometers

Deflectometric profilometers based on industrial electronic autocollimators (ACs), as the ELCOMAT-3000, have become indispensable tools for precision form measurements of optical surfaces. A growing number of labs at synchrotron and free electron laser x-ray facilities are going for BESSY-II NOM-like versions of the AC-based profilometers. These tools have proven capable of characterizing state-of-the-art aspherical x-ray optics with an accuracy on the level of 100 nrad (root-mean-square) over the spatial frequency range limited by the size of the aperture used in the profilometer. Normally, a round aperture with a diameter of about 2.5 mm is used. Previous investigations have shown that with the optimally aligned 2.5-mm aperture, the spatial resolution of a NOM-like profilometer corresponding to the first zero-crossing of the optical transform function (OTF) is ~1.2 mm. In this paper, we investigate the performance of an AC ELCOMAT-3000 for a slope profilometer with different aperture sizes and shapes. The results of angular calibration of the AC equipped with circular and rectangular apertures placed at different distances from the AC are discussed. The calibration was performed at the Physikalisch-Technische Bundesanstalt using the original experimental arrangements, also discussed in the paper. The OTF measurements with the specially developed test sample with chirped surface slope profiles were performed at the Advanced Light Source X-Ray Optics Laboratory (XROL) in application to a new optical surface measuring system under development at the XROL. In the OTF measurements, we have shown that application of a rectangular aperture with dimensions of 1.5 mm × 3 mm improves the spatial resolution in the tangential direction by a factor of ~1.4 compared to that of the standard circular aperture of 2.5-mm diameter. We postulate that the conclusions of our investigations are crucial for reaching fundamental metrological limits in deflectometric profilometry utilizing state-of-the-art electronic autocollimators.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Compilation and utilization of a sorghum transcriptome compendium for gene regulatory network analysis and crop trait engineering

Sorghum bicolor (Sorghum) is a drought and heat tolerant C4 grass crop used to produce grain, forage, biofuels, and other bioproducts. Genetic improvement of sorghum hybrid crops is aided by a large and diverse germplasm, sorghum's diploid inbreeding genetics, and a relatively small genome that has facilitated genomic research. Over the past 20 years, the sorghum research community characterized the cytogenetic and recombinant landscapes of sorghum's 10 chromosomes, sequenced and annotated the sorghum genome, and used that information to identify genes/alleles that modulate flowering time, plant height, seed shattering, and other important traits. More recently, >1000 RNA-seq transcriptome profiles were collected from 15 sorghum genotypes to help understand the genetic basis of variation in growth and development of sorghum stems, tillers, roots, and leaves, and the regulation of biosynthetic pathways that produce epicuticular wax, dhurrin, and RFOs, compounds that contribute to sorghum's resilience. Transcriptome studies were designed to identify differentially expressed genes that are co-expressed during development or in response to a treatment to enable construction of gene regulatory networks. Co-expression and network analysis identified transcription factors and their cognate binding sites in target gene promoters and signaling pathways that modulate gene regulatory networks providing gene editing targets for further trait optimization. RNA-seq data from >20 experiments targeting sorghum organs, tissues, cell types, developmental stages, and responses to environmental conditions (i.e., diel, day-length, shading, water-deficit, temperature) has been compiled in a sorghum transcriptome compendium. The goal of this resource paper is to describe compendium content, accessibility, and a compendium data analysis pipeline and to illustrate the types of information that can be derived from the compendium with a focus on the elucidation of gene regulatory networks useful for guiding the improvement of sorghum traits through gene editing.

RNA-seq↗
DOE OSTI2016

A Novel Triazolopyridine-Based Spleen Tyrosine Kinase Inhibitor That Arrests Joint Inflammation

Autoantibodies and the immunoreceptors to which they bind can contribute to the pathogenesis of autoimmune diseases such as rheumatoid arthritis (RA). Spleen Tyrosine Kinase (Syk) is a non-receptor tyrosine kinase with a central role in immunoreceptor (FcR) signaling and immune cell functionality. Syk kinase inhibitors have activity in antibody-dependent immune cell activation assays, in preclinical models of arthritis, and have progressed into clinical trials for RA and other autoimmune diseases. Here we describe the characterization of a novel triazolopyridine-based Syk kinase inhibitor, CC-509. This compound is a potent inhibitor of purified Syk enzyme, FcR-dependent and FcR-independent signaling in primary immune cells, and basophil activation in human whole blood. CC-509 is moderately selective across the kinome and against other non-kinase enzymes or receptors. Importantly, CC-509 was optimized away from and has modest activity against cellular KDR and Jak2, kinases that when inhibited in a preclinical and clinical setting may promote hypertension and neutropenia, respectively. In addition, CC-509 is orally bioavailable and displays dose-dependent efficacy in two rodent models of immune-inflammatory disease. In passive cutaneous anaphylaxis (PCA), CC-509 significantly inhibited skin edema. Moreover, CC-509 significantly reduced paw swelling and the tissue levels of pro-inflammatory cytokines RANTES and MIP-1α in the collagen-induced arthritis (CIA) model. In summary, CC-509 is a potent, moderately selective, and efficacious inhibitor of Syk that has a differentiated profile when compared to other Syk compounds that have progressed into the clinic for RA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Production of Carbon Nanomaterials and Sorbents from Domestic U.S. Coal (Final Report)

The main goal of this project was to produce high-value carbon nanomaterials and carbon sorbents from domestic coal resources in a cost-effective manner. Four types of domestic coal samples were processed through a combination of deashing, devolatilization, oxidation, reduction, and activation treatments to produce graphene oxide (GO), reduced graphene oxide (RGO), and activated carbon (AC). The precursors and developed materials were extensively characterized by various methods to investigate the impact of the coal feedstock type on the yield and quality of each product. A commercial graphite-based GO sample was included in the experimental work as the baseline material for comparison with the coal-based materials developed in this work. The performed work also included a technoeconomic analysis and cost estimation for a plant processing 20 tons/day coal, a market evaluation for the graphene materials, and a technology gap analysis. A simple process by concentrated nitric acid oxidation is used to oxidize coal precursors for the production of GO. Fine oxidized coal particles that were separated from larger oxidized coal particles had significantly higher oxygen contents and were identified as coal-based GO samples. Coarse oxidized coal particles were used as precursors for production of AC. Based on the Raman spectroscopy results, coal-based GO samples exhibited G and D bands similar to those of graphite-based GO samples. X-ray photoelectron spectroscopy revealed that coal-based GO samples had surface oxygen contents of ~26-35% that were higher than the oxygen contents of graphite-based GO samples. Larger particles of oxidized coal samples were activated under different conditions to produce high surface area functionalized AC. Prepared materials had surface areas exceeding 1,500 m 2 /g and pore volumes more than 1 cm 3 /g with different pore size distributions. Reduced graphene oxide samples were prepared by thermal reduction of both coal-based and graphite-based GO samples at 170-2800 ºC. Coal-based and graphite-based RGO samples exhibited similar carbon contents, Raman spectra, and XRD profiles. Heat treatment above 1500 ºC shifted RGO to synthetic graphite. Among anthracite, bituminous, subbituminous, and lignite coals tested, anthracite was the best precursor to produce carbon nanomaterials exhibiting properties similar to those of graphite-based materials. Anthracite-based carbon nanomaterials also had the highest production yields. Technoeconomic analysis estimated the production cost of GO and RGO for anthracite-based samples at about 2,600 and 4,200 $/ton, respectively, which is about two orders of magnitude lower than the current estimated price of graphite-based materials. Several gaps to further develop the proposed technology were identified and discussed that include process and equipment optimization, process integration, need for additional bench- and pilot-scale experiments, and other items to reduce the scale up risk. Market analysis reports suggested a compound annual growth rate of 40% for graphene and related materials. Short-term applications include composites, inks, and coatings. However, energy storage applications appear to be the dominant potential long-term applications. Different applications of coal-based GO and RGO need to be explored and clear metrics and standards for each application need to be developed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

A PRACTICAL ELECTRODIALYSIS MODEL FOR ACCELERATING SYSTEM DEVELOPMENT

Empirical optimization of electrodialysis (ED) is dependent on repetitive experiments with incremental adjustments, which is cost prohibitive at scale. While models can reduce the costs associated with optimization and scale-up, existing ED models are limited in application to specific use cases and tend to be developed for the exploration of specific transport phenomena. The field requires a practical system-level model, generalized for the broad range of ED systems. This work presents a modeling framework that enables rapid evaluation of membrane stack design, flow configuration, scale, and operational inputs. Across applications spanning 1 L to 5400 L; use of conventional and bipolar membranes; operation in continuous, batch and fed-batch modes; and feedstocks including seawater, brine, wastewater, and manure hydrolysate, the model achieves a mean R2 of 0.978 for concentration-time profiles and links design choices to techno-economic trade-offs, enabling cost-aware prioritization of system configurations.

Bipolar Membrane↗
DOE OSTI2019

Parallel beamlet dose calculation via beamlet contexts in a distributed multi‐GPU framework

Purpose Dose calculation is one of the most computationally intensive, yet essential tasks in the treatment planning process. With the recent interest in automatic beam orientation and arc trajectory optimization techniques, there is a great need for more efficient model‐based dose calculation algorithms that can accommodate hundreds to thousands of beam candidates at once. Foundational work has shown the translation of dose calculation algorithms to graphical processing units ( GPU s), lending to remarkable gains in processing efficiency. But these methods provide parallelization of dose for only a single beamlet, serializing the calculation of multiple beamlets and under‐utilizing the potential of modern GPU s. In this paper, the authors propose a framework enabling parallel computation of many beamlet doses using a novel beamlet context transformation and further embed this approach in a scalable network of multi‐ GPU computational nodes. Methods The proposed context‐based transformation separates beamlet‐local density and TERMA into distinct beamlet contexts that independently provide sufficient data for beamlet dose calculation. Beamlet contexts are arranged in a composite context array with dosimetric isolation, and the context array is subjected to a GPU collapsed‐cone convolution superposition procedure, producing the set of beamlet‐specific dose distributions in a single pass. Dose from each context is converted to a sparse representation for efficient storage and retrieval during treatment plan optimization. The context radius is a new parameter permitting flexibility between the speed and fidelity of the dose calculation process. A distributed manager‐worker architecture is constructed around the context‐based GPU dose calculation approach supporting an arbitrary number of worker nodes and resident GPU s. Phantom experiments were executed to verify the accuracy of the context‐based approach compared to Monte Carlo and a reference CPU ‐ CCCS implementation for single beamlets and broad beams composed by addition of beamlets. Dose for representative 4 π beam sets was calculated in lung and prostate cases to compare its efficiency with that of an existing beamlet‐sequential GPU ‐ CCCS implementation. Code profiling was also performed to evaluate the scalability of the framework across many networked GPU s. Results The dosimetric accuracy of the context‐based method displays <1.35% and 2.35% average error from the existing serialized CPU ‐ CCCS algorithm and Monte Carlo simulation for beamlet‐specific PDD s in water and slab phantoms, respectively. The context‐based method demonstrates substantial speedup of up to two orders of magnitude over the beamlet‐sequential GPU ‐ CCCS method in the tested configurations. The context‐based framework demonstrates near linear scaling in the number of distributed compute nodes and GPU s employed, indicating that it is flexible enough to meet the performance requirements of most users by simply increasing the hardware utilization. Conclusions The context‐based approach demonstrates a new expectation of performance for beamlet‐based dose calculation methods. This approach has been successful in accelerating the dose calculation process for very large‐scale treatment planning problems ‐ such as automatic 4 π IMRT beam orientation and VMAT arc trajectory selection, with hundreds of thousands of beamlets ‐ in clinically feasible timeframes. The flexibility of this framework makes it as a strong candidate for use in a variety of other very large‐scale treatment planning tasks and clinical workflows.

Neph, Ryan↗
DOE OSTI2017

Impact of Nano- and Mesoscales on Macroscopic Cation Conductivity in Perfluorinated-Sulfonic-Acid Membranes

A mean-field local-density theory is outlined for ion transport in perfluorinated-sulfonic-acid (PFSA) membranes. A theory of molecular-level interactions predict nanodomain and macroscale conductivity. The effects of solvation, dielectric saturation, dispersion forces, image charge, finite size, and confinement are included in a physically consistent 3D-model domain geometry. Probability-distribution profiles of aqueous cation concentration at the domain-scale are in agreement with atomistic simulations using no explicit fitting parameters. Measured conductivities of lithium-, sodium-, and proton-form membranes with equivalent weights of 1100, 1000, and 825 g/mol(SO3) validate the macroscale predictions using a single-value mesoscopic fitting parameter. Cation electrostatic interactions with pendant sulfonate groups are the largest source of migration resistance at the domain-scale. Tortuosity of ionically conductive domains is the largest source of migration resistance at the macroscale. In conclusion, our proposed transport model is consistent across multiple length scales. We provide a compelling methodology to guide material design and optimize performance in energy-conversion applications of PFSA membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Prediction of microalgae hydrothermal liquefaction products from feedstock biochemical composition

Hydrothermal liquefaction (HTL) uses water under elevated temperatures and pressures (200–350 °C, 5–20 MPa) to convert biomass into liquid “biocrude” oil. Despite extensive reports on factors influencing microalgae cell composition during cultivation and separate reports on HTL products linked to cell composition, the field still lacks a quantitative model to predict HTL conversion product yield and qualities from feedstock biochemical composition; the tailoring of microalgae feedstock for downstream conversion is a unique and critical aspect of microalgae biofuels that must be leveraged upon for optimization of the whole process. This study developed predictive relationships for HTL biocrude yield and other conversion product characteristics based on HTL of Nannochloropsis oculata batches harvested with a wide range of compositions (23–59% dw lipids, 58–17% dw proteins, 12–22% dw carbohydrates) and a defatted batch (0% dw lipids, 75% dw proteins, 19% dw carbohydrates). HTL biocrude yield (33–68% dw) and carbon distribution (49–83%) increased in proportion to the fatty acid (FA) content. A component additivity model (predicting biocrude yield from lipid, protein, and carbohydrates) was more accurate predicting literature yields for diverse microalgae species than previous additivity models derived from model compounds. FA profiling of the biocrude product showed strong links to the initial feedstock FA profile of the lipid component, demonstrating that HTL acts as a water-based extraction process for FAs; the remainder non-FA structural components could be represented using the defatted batch. These findings were used to introduce a new FA-based model that predicts biocrude oil yields along with other critical parameters, and is capable of adjusting for the wide variations in HTL methodology and microalgae species through the defatted batch. Lastly, the FA model was linked to an upstream cultivation model (Phototrophic Process Model), providing for the first time an integrated modeling framework to overcome a critical barrier to microalgae-derived HTL biofuels and enable predictive analysis of the overall microalgal-to-biofuel process.

09 BIOMASS FUELS↗
DOE OSTI2023

Density and temperature profiles after low-Z and high-Z shattered pellet injections on DIII-D

Abstract In this work we utilize the recently upgraded Thomson scattering diagnostic to resolve density and temperature plasma profiles after pure deuterium and mixed neon/deuterium shattered pellet injections (SPIs) on DIII-D. This allows us to study individual components of the staggered scheme proposed for disruption mitigation on ITER, consisting of a low-Z material SPI followed by a delayed high-Z SPI. Obtained spatio-temporal density profiles exhibit very different dynamics after dominantly neon and pure deuterium SPIs. The neon SPI causes a fast radiative plasma collapse in a few milliseconds and results in almost flat density profile once the impurity mixes with the plasma during and after the thermal quench (TQ). The deuterium SPI leads to a disruption delayed by ten and more milliseconds, but very limited core fueling can be observed before the disruption. Even during and after the TQ, the edge deuterium density significantly exceeds the core density. 1D transport modeling suggests that this poor core fueling can be explained by strong outward grad-B-induced drift of the injected deuterium. Preliminary simulations show that larger pellet shards and greater injected quantity can be used to improve the penetration of the low-Z material into the core. These results call for optimization and further evaluation of the staggered SPI on ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

SU-F-T-178: Optimized Design of a Diamond Detector Specifically Dedicated to the Dose Distribution Measurements in Clinical Proton Pencil Beams

Purpose: In proton-therapy, pencil beam scanning (PBS) dosimetry presents a real challenge due to the small size of the beam (about 3 to 8 mm in FWHM), the pulsed high dose rate (up to 100 Gy/s) and the proton energy variation (about 30 MeV to 250 MeV). In the framework of French INSERM DEDIPRO project, a specifically dedicated single crystal diamond dosimeter (SCDDo) was developed with the objective of obtaining accurate measurements of the dose distribution in PBS modality. Methods: Monte Carlo simulations with MCNPX were performed. A small proton beam of 5 mm in FWHM was simulated as well as diamond devices with various size, thickness and holder composition. The calculated doses-to-diamond were compared with the doses-to-water in order to reduce the perturbation effects. Monte-Carlo simulations lead to an optimized SCDDo design for small proton beams dosimetry. Following the optimized design, SCDDos were mounted in water-equivalent holders with electrical connection adapted to standard electrometer. First, SCDDos performances (stability, repeatability, signal-to-background ratio…) were evaluated with conventional photon beams. Then, characterizations (dose linearity, dose rate dependence…) with wide proton beams were performed at proton-therapy center (IC-CPO) from Curie Institute (France) with the passive proton delivery technique, in order to confirm dosimetric requirements. Finally, depth-dose distributions were measured in a water tank, for native and modulated Bragg Peaks with the collimator of 12 cm, and compared to a commercial PPC05 parallel-plate ionization chamber reference detector. Lateral-dose profiles were also measured with the collimator of 5 mm, and compared to a commercial SFD diode. Results: The results show that SCDDo design does not disturb the dose distributions. Conclusion: The experimental dose distributions with the SCDDo are in good agreement with the commercial detectors and no energy dependence was observed with this device configuration.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2017

High Strain Rate Mechanical Characterization of Carbon Fiber Reinforced Polymer Composites Using Digital Image Correlations

We present that the introduction of carbon fiber reinforced polymer (CFRP) composites to structural components in lightweight automotive structures necessitates an assessment to evaluate that their crashworthiness dynamic response provides similar or higher levels of safety compared to conventional metallic structures. In order to develop, integrate and implement predictive computational models for CFRP composites that link the materials design, molding process and final performance requirements to enable optimal design and manufacturing vehicle systems for this study, the dynamic mechanical response of unidirectional (UD) and 2x2 twill weave CRFP composites was characterized at deformation rates applicable to crashworthiness performance. Non-standardized specimen geometries were tested on a standard uniaxial frame and an intermediate-to-high speed dynamic testing frame, equipped with high speed cameras for 3D digital image correlation (DIC). Specimen cross-sections, according to each fiber orientation tested, were consistent across strain rates to ensure results were comparable. Tensile strength and modulus were experimentally investigated over a wide range of strain rates (0.0001 to 200 s -1 ). DIC was used to estimate strain profiles on composites surfaces, and the modulus was calculated from those strain measurements. Experimental results demonstrated an increase in the tensile strength of UD CFRP composites in the longitudinal (0°) and transverse (90°) direction with increasing strain rates. In contrast, the tensile strength of 2x2 woven composites and the tensile modulus of the UD material were insensitive to increasing strain rates. Finally, comparison of failure modes provided insights on how loading rates influenced failure mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Study of the Mechanism of Liquid Slag Infiltration for Lubrication in Slab Continuous Casting

Consistent and uniform lubrication of the solidifying shell, especially in the meniscus, is crucial for the smooth continuous casting operation and production of strands free of surface defects. Thus, the current study established a coupled model to study the inflow behavior of liquid slag to the mold-strand channel, taking the solidification of steel and slag and the periodic oscillation of mold into account. The difficulties and solutions for the simulation were described in detail. The predicted profiles of the slag rim and initial shell were in good agreement with the reports. The main results indicated that liquid slag could be squeezed out and back into the slag pool in a negative strip period while a large amount of liquid slag could infiltrate into the mold-strand channel. Thus, the amount of slag consumed in the negative strip period was relatively small compared with that in the positive strip period. The predicted variation of slag consumption during mold oscillation was periodic, and the average value was 0.274 kg/m{sup 2}, which agreed well with the slag consumption in industrial practice. The current model can predict and optimize the oscillation parameters aiming at stable lubrication conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Characterization of intermetallics in aluminum to zinc coated interstitial free steel joining by pulsed MIG brazing for automotive application

In order to meet the demand for lighter and more fuel efficient vehicles, a significant attempt is currently being focused toward the substitution of aluminum for steel in the car body structure. It generates vital challenge with respect to the methods of joining to be used for fabrication. However, the conventional fusion joining has its own difficulty owing to formation of the brittle intermetallic phases. In this present study AA6061-T6 of 2 mm and HIF-GA steel sheet of 1 mm thick are metal inert gas (MIG) brazed with 0.8 mm Al–5Si filler wire under three different heat inputs. The effect of the heat inputs on bead geometry, microstructure and joint properties of MIG brazed Al-steel joints were exclusively studied and characterized by X-ray diffraction, field emission scanning electron microscopy (FESEM), electron probe micro analyzer (EPMA) and high resolution transmission electron microscopy (HRTEM) assisted X-ray spectroscopy (EDS) and selective area diffraction pattern. Finally microstructures were correlated with the performance of the joint. Diffusion induced intermetallic thickness measured by FESEM image and concentration profile agreed well with the numerically calculated one. HRTEM assisted EDS study was used to identify the large size FeAl{sub 3} and small size Fe{sub 2}Al{sub 5} type intermetallic compounds at the interface. The growth of these two phases in A2 (heat input: 182 J mm{sup −1}) is attributed to the slower cooling rate with higher diffusion time (~ 61 s) along the interface in comparison to the same for A1 (heat input: 155 J mm{sup −1}) with faster cooling rate and shorter diffusion time (~ 24 s). The joint efficiency as high as 65% of steel base metal is achieved for A2 which is the optimized parameter in the present study. - Highlights: • AA 6061 and HIF-GA could be successfully joined by MIG brazing. • Intermetallics are exclusively studied and characterized by XRD, FESEM and EPMA. • Intermetallic formation by diffusion is worth considering or not. • HRTEM-EDS, SAD pattern identifies the morphologies and size of intermetallics. • A compromise concerning formation of IMC is necessary.

36 MATERIALS SCIENCE↗