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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A pathogenic role for histone H3 copper reductase activity in a yeast model of Friedreich’s ataxia

Disruptions to iron-sulfur (Fe-S) clusters, essential cofactors for a broad range of proteins, cause widespread cellular defects resulting in human disease. A source of damage to Fe-S clusters is cuprous (Cu 1+ ) ions. Since histone H3 enzymatically produces Cu 1+ for copper-dependent functions, we asked whether this activity could become detrimental to Fe-S clusters. Here, we report that histone H3–mediated Cu 1+ toxicity is a major determinant of cellular functional pool of Fe-S clusters. Inadequate Fe-S cluster supply, due to diminished assembly as occurs in Friedreich’s ataxia or defective distribution, causes severe metabolic and growth defects in Saccharomyces cerevisiae. Decreasing Cu 1+ abundance, through attenuation of histone cupric reductase activity or depletion of total cellular copper, restored Fe-S cluster–dependent metabolism and growth. Our findings reveal an interplay between chromatin and mitochondria in Fe-S cluster homeostasis and a potential pathogenic role for histone enzyme activity and Cu 1+ in diseases with Fe-S cluster dysfunction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Models of dislocation glide and strengthening mechanisms in bcc complex concentrated alloys

Abstract The mechanical response of complex concentrated alloys (CCAs) deviates from that of their pure and dilute counterparts due to the introduction of a combinatorially sized chemical concentration dimension. Compositional fluctuations constantly alter the energy landscape over which dislocations move, leading to line roughness and the appearance of defects such as kinks and jogs under stress and temperature conditions where they would ordinarily not exist in pure metals and dilute alloys. The presence of such chemical defects gives rise to atomic-level mechanisms that fundamentally change how CCAs deform plastically at meso- and macroscales. In this article, we provide a review of recent advances in modeling dislocation glide processes in CCAs, including atomistic simulations of dislocation glide using molecular dynamics, kinetic Monte Carlo simulations of edge and screw dislocation motion in refractory CCAs, and phase-field models of dislocation evolution over complex energy landscapes. We also discuss pathways to develop comprehensive simulation methodologies that connect an atomic-level description of the compositional complexity of CCAs with their mesoscopic dislocation-mediated plastic response with an eye toward improved design of CCA with superior mechanical response. Graphical abstract

36 MATERIALS SCIENCE↗
DOE OSTI2023

Development of a modeling toolbox for CORC cable performance evaluation

One critical, yet currently unknown aspect in the development process of CORC® cables is how current sharing around defects impact the overall performance of a cable design. Within the scope of this project, a simulation framework has been developed that is specialized on the quenching behavior and temperature rise around cable defects.

42 ENGINEERING↗
DOE OSTI2023

Additive Manufacturing for Powering the Blue Economy Applications: A Tidal Turbine Blade Case Study: Preprint

As the marine renewable energy industry continues to expand, innovation in the manufacturing space must grow accordingly to reduce costs and ensure the economic feasibility of new technologies. Additive manufacturing, more commonly known as 3D printing, provides an alternative for rapid prototyping of marine hydrokinetic technologies, particularly supporting Powering the Blue Economy initiatives of the U.S. Department of Energy Water Power Technologies Office. This study explores the application of additive manufacturing in the development of marine hydrokinetic structures, focusing on material and printing method selection, design, and analysis of a 3D-printed spar for an axial-flow tidal turbine blade. Corrosion-resistant metals were deemed ideal due to the loads and harsh marine environment the blade would experience. Laser metal deposition methods were determined to be the most effective and scalable for the considered scale. The designed spar adapts its geometry to the blade - a feature uniquely suited to additive manufacturing - and is intended to serve as the blade's primary structural component. A finite element model was used to study stresses and deformations under loading conditions. The spar was manufactured using 316L stainless steel through direct energy deposition, and defects were assessed and recorded. Future efforts will include mechanical testing of the spar. This research establishes a benchmark process for using additive manufacturing in developing marine hydrokinetic structures, paving the way for future optimization and techno-economic analysis.

additive manufacturing↗
DOE OSTI2021

Interface pinning causes the hysteresis of the hydride transformation in binary metal hydrides

Hydriding and dehydriding transitions in bulk and nanocrystalline binary metal hydrides were studied using the Pd-H model system by measuring pressure-composition isotherms with in situ x-ray diffractometry. Nanocrystalline Pd showed a smaller pressure hysteresis, solvus hysteresis, and hysteresis in lattice parameter, compared to bulk Pd. The time-dependence of pressure equilibration was measured after dosing with aliquots of hydrogen, giving equilibration times that were much faster in the single-phase regions than in the two-phase plateaus. In the broad two-phase plateaus, the pressure relaxations were exponential functions of time. An explanation of hysteresis is developed that is based on a dissipative potential barrier that impedes the motion of the interface due to interactions between lattice defects and the two-phase interface. The exponential pressure relaxations and hysteresis are consistent for this mechanism. For a simple model of the pinning potential, the potential barrier maximum is an order of magnitude less than typical grain boundary energies. These pinning effects are substantially different in the nanocrystalline Pd, suggesting differences in the hydriding mechanism.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simurgh: A Framework for Cad-Driven Deep Learning Based X-Ray CT Reconstruction

High-resolution X-ray computed tomography (XCT) is an important technique for the inspection of additively manufactured (AM) parts. While XCT is typically used off-line to inspect a subset of manufactured parts, significantly accelerating measurement speed while retaining accuracy would enable use of XCT for in-line inspection to rapidly identify defects in each part as it is manufactured. Here, we propose a deep learning (DL) based approach that uses computer aided design (CAD) models of the AM parts and physics-based information to rapidly produce high-quality reconstructions from sparse XCT measurements without high quality ground truth data. Our approach uses a generative adversarial neural network (GAN) to produced realistic training data from the CAD-based simulations and a deep neural network that is trained using data from the first stage to produce accurate 3D reconstructions. Using experimental XCT data of metal parts, we demonstrate enhanced defect detection capabilities while dramatically reducing the scan time.

Ziabari, Amir↗
DOE OSTI2019

Energetic Substantiation of the Formation of Ytterbium Dimers in Single Forsterite Crystals

A structural computer simulation of ytterbium-containing forsterite crystals has been carried out. Atomistic simulation is performed using the GULP 4.1 software package (General Utility Lattice Program). Different mechanisms of ytterbium dissolution in forsterite crystals are considered, and the dissolution energies of isolated defects, as well as charged and neutral clusters of various configurations, are calculated. The results of the calculation manifest that the formation of ytterbium clusters with a magnesium vacancy gives a significant gain in the dissolution energy. The formation of neutral clusters (dimers) in the M1 site (Yb{sub Mg1}ν{sub Mg1}Yb{sub Mg1}) leads to an energy reduction by 1.7 eV compared with the statistical distribution of defects. As a result of simulation, it is shown the energetic substantiation of the formation of ytterbium dimers in forsterite crystals. A model of the most energetically favorable center in the M1 site is proposed—a dimer, consisting of a pair of trivalent ytterbium ions with a magnesium vacancy between them, forming a chain parallel to the crystallographic axis c.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Formation and dissociation of shear-induced high-energy dislocations: insight from molecular dynamics simulations

Solid-phase processing (SPP) allows one to create complex microstructures, not achievable via thermal processing alone. The resulting structures exhibit a rich palette of defects, both thermal and non-thermal, including defect substructures, such as dislocation networks. It is essential to understand the mechanisms of deformation and defect structure formation to guide SPP towards achieving desired microstructures and material properties. In this study, large-scale molecular dynamics simulations are used to investigate the effects of inhomogeneous strain distribution, that mimics deformation conditions of tribological tests, on the evolution of defects under severe shear deformation in polycrystalline Al. Analysis of defect nucleation and reaction pathways reveals that strong geometric constraints suppress the nucleation and slide of low energy dislocation 1/2$\langle110\rangle${111} but promote the nucleation and slide of high energy dislocations, such as [$1\bar1$0] (001) and 1/2 [$1\bar1$$\bar2$]($1\bar1$1). Further, a rough contact surface, characteristic to tribological tests, imposes an inhomogeneous stress field leading to inhomogeneous defect substructures due to location-dependent activation of slip systems. The results suggest that high-energy dislocations can dominate the evolution of grain structures in highly constrained environments, which should be considered in modeling plastic deformation and grain refinement during SPP.

42 ENGINEERING↗
DOE OSTI2021

A novel in vivo mouse intervertebral disc degeneration model induced by compressive suture

Intervertebral disc degeneration (IDD) is the root cause of many musculoskeletal disorders of the spine. However, the etiology of IDD is complex and still not well understood. Animal models of IDD would be useful in deciphering the underlying mechanisms. But the existing animal models have their limitations. Therefore, to establish a novel mouse model that can simulate the human IDD process in vivo, we proposed to carefully circumcise the 2 mm-wide tail skin and then compressively sutured the defect with a simple end-to-end suture to exert excessive pressure on the disc. After 1-week, 2-week, and 4-week compression, the mice were sacrificed and the intervertebral discs were harvested for tissue analysis. The radiological, morphological, and molecular modifications of intervertebral discs were measured to characterize this model. Radiologically, the water content of the intervertebral disc decreased significantly after 2-week compression. Morphologically, the nucleus pulposus showed a decrease in volume and the number of notochordal cells. The compressive suture also broke the balance between anabolic and catabolic enzymes in nucleus pulposus, which led to the remodeling of the extracellular matrix in nucleus pulposus as the content of aggrecan and collagen II decreased. The compressive suture could induce intervertebral discs degeneration in a more reasonable way, which was solely influenced by mechanical loading, as the mice caudal vertebrae still moved freely after the operation. This kind of animal model could be adapted as a reliable in vivo mouse IDD model for the research regarding the etiology and treatments of IDD.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Drosophila models to study causative genes for human rare intractable neurological diseases

Highlights: • Drosophila models targeting some ALS-causing genes are described. • Drosophila models targeting some CMT-causing genes are described. • Drosophila models targeting some Sotos syndrome-causing genes are described. • Genes and pathways that commonly interact with ALS- and/or CMT-causing genes are described. Drosophila is emerging as a convenient model for investigating human diseases. Functional homologues of almost 75% of human disease-related genes are found in Drosophila. Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease that causes defects in motoneurons. Charcot-Marie-Tooth disease (CMT) is one of the most commonly found inherited neuropathies affecting both motor and sensory neurons. No effective therapy has been established for either of these diseases. In this review, after overviewing ALS, Drosophila models targeting several ALS-causing genes, including TDP-43, FUS and Ubiquilin2, are described with their genetic interactants. Then, after overviewing CMT, examples of Drosophila models targeting several CMT-causing genes, including mitochondria-related genes and FIG 4, are also described with their genetic interactants. In addition, we introduce Sotos syndrome caused by mutations in the epigenetic regulator gene NSD1. Lastly, several genes and pathways that commonly interact with ALS- and/or CMT-causing genes are described. In the case of ALS and CMT that have many causative genes, it may be not practical to perform gene therapy for each of the many disease-causing genes. The possible uses of the common genes and pathways as novel diagnosis markers and effective therapeutic targets are discussed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Vector-level feedforward control of LPBF melt pool area using a physics-based thermal model

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and geometric inaccuracies, stemming in part from variations in the melt pool. Here, this paper proposes a novel vector-level feedforward control framework for regulating melt pool area in LPBF. By decoupling part-scale thermal behavior from small-scale melt pool physics, the controller provides a scale-agnostic prediction of melt pool area and efficient optimization over it. This is done by operating on two coupled lightweight models: a finite-difference thermal model that efficiently captures vector-level temperature fields and a reduced-order, analytical melt pool model. Each model is calibrated separately with minimal single-track and 2D experiments, and the framework is validated on a complex 3D geometry in both Inconel 718 and 316L stainless steel. Results showed that feedforward vector-level laser power scheduling reduced geometric inaccuracy in key dimensions by 62%, overall porosity by 16.5%, and photodiode root-mean-squared deviation by 38.5% on average. Overall, this modular, data-efficient approach demonstrates that proactively compensating for known thermal effects can significantly improve part quality while remaining computationally efficient and readily extensible to other materials and machines.

Additive manufacturing↗
DOE OSTI2025

Modeling active nematics via the nematic locking principle

Active nematic systems consist of rod-like internally driven subunits that interact with one another to form large-scale coherent flows. They are important examples of far-from-equilibrium fluids, which exhibit a wealth of nonlinear behavior. This includes active turbulence, in which topological defects in the nematic order braid around one another in a chaotic fashion. One of the most studied examples of active nematics consists of a dense two-dimensional layer of microtubules, crosslinked by kinesin molecular motors that inject extensile deformations into the fluid. Though numerous theoretical studies have modeled microtubule-based active nematics, no consensus has emerged on how to fully and quantitatively capture the features of the experimental system. Here, to better understand the theoretical foundations for modeling this system, we propose a fundamental principle we call the nematic locking principle—individual microtubules cannot rotate without all neighboring microtubules also rotating. Physically, this is justified by the high density of the microtubules, their elongated nature, and their corresponding steric interactions. We assert that the nematic locking principle holds throughout the majority of the material, but breaks down in the neighborhood of topological defects and other regions of low density. We derive the most general nematic transport equation consistent with this principle and also derive the most general term that violates it, introducing fracturing into the material. We then examine the standard Beris–Edwards approach, commonly used to model this system, and show that it violates the nematic locking principle throughout the majority of the material due to fracturing. We then propose a modification to the Beris–Edwards model that enforces nematic locking nearly everywhere. This modification shuts off fracturing except in regions where the order parameter (a proxy for density) is reduced. In these regions fracturing is turned on. The resulting simulations in turn show strong nematic locking throughout the bulk of the material, with narrow bands of fracturing, consistent with experimental observation. One additional advantage of enforcing nematic locking is that nontrivial stationary state solutions, common in Beris–Edwards simulations but not seen in experiments, are eliminated.

Mitchell, Kevin A. [Univ. of California, Merced, C↗
DOE OSTI2019

Interplay between Composition, Electronic Structure, Disorder, and Doping due to Dual Sublattice Mixing in Nonequilibrium Synthesis of ZnSnN 2 :O

We report the opportunity for enhanced functional properties in semiconductor solid solutions has attracted vast scientific interest for a variety of novel applications. However, the functional versatility originating from the additional degrees of freedom due to atomic composition and ordering comes along with new challenges in characterization and modeling. Developing predictive synthesis-structure-property relationships is prerequisite for effective materials design strategies. Here, a first-principles based model for property prediction in such complex semiconductor materials is presented. This framework incorporates nonequilibrium synthesis, dopants and defects, and the change of the electronic structure with composition and short range order. This approach is applied to ZnSnN 2 (ZTN) which has attracted recent interest for photovoltaics. The unintentional oxygen incorporation and its correlation with the cation stoichiometry leads to the formation of a solid solution with dual sublattice mixing. A nonmonotonic doping behavior as a function of the composition is uncovered. Finally, the degenerate doping of near-stoichiometric ZTN, which is detrimental for potential applications, can be lowered into the 10 17 cm -3 range in highly off-stoichiometric material, in quantitative agreement with experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Characterization of ultralow thermal conductivity in anisotropic pyrolytic carbon coating for thermal management applications

Pyrolytic carbon (PyC) is an important material used in many applications including thermal management of electronic devices and structural stability of ceramic composites. Accurate measurement of physical properties of structures containing textured PyC layers with few-micrometer thickness poses new challenges. Here a laser-based thermoreflectance technique is used to measure thermal conductivity in a 30-μm-thick textured PyC layer deposited using chemical vapor deposition on the surface of spherical zirconia particles. Raman spectroscopy is used to confirm the graphitic nature and characterize microstructure of the deposited layer. Room temperature radial and circumferential thermal conductivities are found to be 0.28 W m –1 K –1 and 11.5 W m –1 K –1 , corresponding to cross-plane and in-plane conductivities of graphite. While the anisotropic ratio of the in-plane to cross-plane conductivities is smaller than previous results, the magnitude of the smallest conductivity is noticeably smaller than previously reported values for carbon materials and offers opportunities in thermal management applications. Very low in-plane and cross-plane thermal conductivities are attributed to strong grain boundary scattering, high defect concentration, and small inter-laminar porosity. Lastly, experimental results agree with the prediction of thermal transport model informed by the microstructure information revealed by Raman spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Cooling dynamics of two titanium alloys during laser powder bed fusion probed with in situ X-ray imaging and diffraction

Metal parts produced by laser powder bed fusion (LPBF) additive manufacturing exhibit characteristic microstructures comparable to those observed in laser welding. The primary cause of this characteristic microstructure is rapid, localized heating and cooling cycles, which result in extreme thermal gradients where material solidification is followed by fast cooling in the solid state. The final microstructure and mechanical performance are also influenced by pore formation caused by melt pool fluid dynamics. Here, we use high speed, in situ X-ray diffraction to probe the kinetics of cooling and solid-solid phase transitions after laser melting in two aerospace titanium alloys: Ti-6Al-4V, an α + β alloy; and Ti-5Al-5V-5Mo-3Cr, a near-β alloy. We complement these diffraction studies with in situ X-ray imaging to probe melt pool dynamics and pore formation. From these two complementary probes, we quantify pore formation during melting and the subsequent microstructural evolution as the material rapidly cools after solidification. These results are critical for understanding defect formation and residual stress development in different titanium alloys under LPBF conditions and can help inform process models to predict final part performance.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Lithium Intercalation in Anatase Titanium Vacancies and the Role of Local Anionic Environment

The structure of bulk and nondefective compounds is generally described with crystal models built from well mastered techniques such the analysis of an X-ray diffractogram. The presence of defects, such as cationic vacancies, locally disrupt the long-range order, with the appearance of local structures with order extending only a few nanometers. To probe and describe the electrochemical properties of cation-deficient anatase, we investigated a series of materials having different concentrations of vacancies, i.e., Ti 1–x–y $\square$ x+y O 2–4(x+y) F 4x (OH) 4y , and compared their properties with respect to defect-free stoichiometric anatase TiO2. At first, we characterized the series of materials Ti 1–x–y $\square$ x+y O 2–4(x+y) F 4x (OH) 4y by means of pair distribution function (PDF), 19 F nuclear magnetic resonance (NMR), Raman and X-ray photoelectron spectroscopies, to probe the compositional and structural features. Second, we characterized the insertion electrochemical properties vs metallic lithium where we emphasized the beneficial role of the vacancies on the cyclability of the electrode under high C-rate, with performances scaling with the concentration of vacancies. The improved properties were explained by the change of the lithium insertion mechanism due to the presence of the vacancies, which act as host sites and suppress the phase transition typically observed in pure TiO 2 , and further favor diffusive transport of lithium within the structure. NMR spectroscopy performed on lithiated samples provides evidence for the insertion of lithium in vacancies. By combining electrochemistry and DFT-calculations, we characterized the electrochemical signatures of the lithium insertion in the vacancies. Importantly, we found that the insertion voltage largely depends on the local anionic environment of the vacancy with a fluoride and hydroxide-rich environments, yielding high and low insertion voltages, respectively. Lastly, this work further supports the beneficial use of defects engineering in electrodes for batteries and provides new fundamental knowledge in the insertion chemistry of cationic vacancies as host sites.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Revealing nano-scale lattice distortions in implanted material with 3D Bragg ptychography

Small ion-irradiation-induced defects can dramatically alter material properties and speed up degradation. Unfortunately, most of the defects irradiation creates are below the visibility limit of state-of-the-art microscopy. As such, our understanding of their impact is largely based on simulations with major unknowns. Here we present an x-ray crystalline microscopy approach, able to image with high sensitivity, nano-scale 3D resolution and extended field of view, the lattice strains and tilts in crystalline materials. Using this enhanced Bragg ptychography tool, we study the damage helium-ion-irradiation produces in tungsten, revealing a series of crystalline details in the 3D sample. Our results lead to the conclusions that few-atom-large ‘invisible’ defects are likely isotropic in orientation and homogeneously distributed. A partially defect-denuded region is observed close to a grain boundary. These findings open up exciting perspectives for the modelling of irradiation damage and the detailed analysis of crystalline properties in complex materials.

42 ENGINEERING↗
DOE OSTI2021

Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved imaging

Abstract Exploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work well for semiconductors tend to fail in materials with strong correlations, either in electronic behavior or chemical segregation. In these cases, the details of atomic arrangements are generally not explored and analyzed. The knowledge of the generative physics and chemistry of the material can obviate this problem, since defect configuration libraries as stochastic representation of atomic level structures can be generated, or parameters of mesoscopic thermodynamic models can be derived. To obtain such information for improved predictions, we use data from atomically resolved microscopic images that visualize complex structural correlations within the system and translate them into statistical mechanical models of structure formation. Given the significant uncertainties about the microscopic aspects of the material’s processing history along with the limited number of available images, we combine model optimization techniques with the principles of statistical hypothesis testing. We demonstrate the approach on data from a series of atomically-resolved scanning transmission electron microscopy images of Mo x Re 1- x S 2 at varying ratios of Mo/Re stoichiometries, for which we propose an effective interaction model that is then used to generate atomic configurations and make testable predictions at a range of concentrations and formation temperatures.

25 ENERGY STORAGE↗