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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Chapter Twelve - Proton transfer and drug binding details revealed in neutron diffraction studies of wild-type and drug resistant HIV-1 protease

HIV-1 protease is an essential therapeutic target for the design and development of antiviral inhibitors to treat AIDS. We used room temperature neutron crystallography to accurately determine hydrogen atom positions in several protease complexes with clinical drugs, amprenavir and darunavir. Hydrogen bonding interactions were carefully mapped to provide an unprecedented picture of drug binding to the protease target. We demonstrate that hydrogen atom positions within the enzyme catalytic site can be altered by introducing drug resistant mutations and by protonating surface residues that trigger proton transfer reactions between the catalytic Asp residues and the hydroxyl group of darunavir. When protein perdeuteration is not feasible, we validate the use of initial H/D exchange with unfolded protein and partial deuteration in pure D2O with hydrogenous glycerol to maximize deuterium incorporation into the protein, with no detrimental effects on the growth of quality crystals suitable for neutron diffraction experiments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Plant metacaspase: A case study of microcrystal structure determination and analysis

Metacaspases are highly conserved in plants and play essential roles in mediating programmed cell death, biotic and abiotic stress responses, and damage-induced innate immunity. Ca 2+ signaling induced by plant damage leads to activation of metacaspase from Arabidopsis thaliana (AtMC4), which subsequently processes a plant elicitor peptide to trigger downstream immuno-response. To understand the structural basis of AtMC4 activation by Ca 2+ , we previously determined its crystal structure and performed in-crystal Ca 2+ treatment to probe activation-associated conformational changes. To enable structure determination and in-crystal Ca 2+ activation analysis, we used microcrystals and related methods which were essential for our successful approach. Here, in this paper, we describe in detail the methods that we used for determination of AtMC4 structure using single-wavelength isomorphous replacement with anomalous signals assembled from 22 microcrystals. We also describe the method for in-crystal Ca 2+ soaking, microcrystal data collection, data assembly and analysis to obtain the activated structure of AtMC4 from 91 micro-sized crystals. The described methods may be useful to study other plant metacaspases and more broadly other plant enzymes for their structure determination and in-crystal functional characterization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Crystallographic orientation and spatially resolved damage in a dispersion-hardened Al alloy

The in-situ neutron diffraction technique, in combination with both the full-field crystal elasto-viscoplastic finite element model and microstructural characterization, was used to study the deformation-induced damage anisotropy in a commercial Al alloy, subjected to uniaxial tensile and cyclic loading. The simulations capture well the crystallographic-orientation-dependent lattice strain behavior. The hard grains, e.g. those orientated with the <111> and <422> orientations parallel with the uniaxial loading direction (LD), feature large Taylor factors and seem more prone to form damage-related band structures. Their effective elastic moduli decrease with the accumulation of damage, which are different from the soft grains orientated with the <200> orientation along the LD. Correlation between the distribution of voids and that of the residual lattice strain developed after failure may exist. The maximum tensile type residual lattice strain observed after failure may be resulted from the band structure formed in the hardest <111> grains. It was revealed that the band structure triggered by the hard particles could be one of sources of damage. In addition, while the specimen was obviously damaged, a fast stress relief was evidenced after unloading from the tension, especially at the beginning of unloading. Our present investigations provide a novel method for exploring the damage mechanisms of polycrystalline materials during plastic deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The effects of stress, temperature and facet structure on growth of { 10 1 &#xAF; 2 } twins in Mg: a molecular dynamics and phase field study

The present study focuses on the roles of structure, stress and temperature on the mobility of facets bounding twin domains and on the overall impact on the growth kinetics of { 10 1 &#xAF; 2 } twins in Mg. We first use molecular dynamics simulations (MD) to study the relationship between interface structures, stress, temperature and mobility. As facets can exhibit distinct atomic scale structures, we also quantify the effect of stress relaxation mediated by misfit dislocations on the mobility of the basal-prismatic interface. The information gathered for ten different facets is used to calibrate an anisotropic phase field model predicting the effects of temperature and stress on the kinetics and shape of a growing { 10 1 &#xAF; 2 } 3D twin, by comparison with MD data. The comparative analysis suggests that, as compared to simulations of individual facets, the effective mobility of facets can be significantly different during growth of a 3D twin. This can be attributed to the complex three-dimensional internal stress state of the twin and to coupling in facet motion triggered by facet junctions. As such, by directly fitting both the twin growth kinetics and morphology as predicted by MD for different stresses and temperatures, we can identify a limited set of rate-limiting facets that control twin growth and morphology, and measure their effective mobility.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Unraveling kinking: A plasticity enhancing failure mode in high strength nano metallic laminates

Kinking is an important and plasticity-enhancing deformation/failure mode in numerous mechanically anisotropic materials including high-strength nano metallic laminates (NMLs). However, our current limited understanding of the mechanics of kinking and its dependence on microstructural attributes is insufficient for thoroughly comprehending and eventually being able to control failure behaviors of materials. In this study, we investigate kinking dependencies on microstructural attributes in NMLs via in situ micropillar compression, multiscale microstructure characterization, dislocation dynamic simulations, and crystal plasticity modeling. Additionally, by examining several NML systems (Cu/Fe, Ag/Fe, Al-4Mg/Fe), we demonstrate that the development of internal stresses during loading activates local layer-parallel glide triggering kinking in NMLs. Furthermore, this work reveals the effect of key microstructural features including layer thickness, layer waviness, interface barrier strength, and work hardening capacity on kink band formation in NMLs. More broadly, our efforts represent a generically applicable approach for probing large-strain deformation behavior of complex materials via synergetic modeling and experimental efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rigorous computation of short-range order unifies its controversial effects in complex concentrated alloys

Direct experimental observations of chemical short-range order (SRO) in complex concentrated alloys (CCAs) have triggered high interest. However, the reported effects of SRO on yield stresses are controversial, and their atomic-scale mechanisms are elusive, which limits our ability to utilize SRO in alloy design. Here we tackle this challenge using an advanced computational approach that rigorously takes into account the critical lattice distortion in CCAs and further verify our theoretical predictions with experiments. We show that the CoCrNi model alloy has a narrow temperature window around 670 °C for SRO formation. This explains why the mechanical effect of SRO is observed in some experiments but not in others. Here, we propose an effective alloy-doping method to control SRO and reveal atomic-bonding types that dominate SRO formation for different alloys. The strategies and insights generally apply to a broad spectrum of alloys, laying the foundation for designing advanced alloys by manipulating their SRO.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nonequilibrium defect-phase nanostructures stabilized by irradiation in undersaturated Ni-Si nanocrystalline alloy

Nanocrystalline thin films of the undersaturated alloy Ni-8.5 at% Si were subjected to 2 MeV Ti irradiation at temperatures ranging from 450˚C to 550˚C. Correlative microscopy combining transmission electron microscopy (TEM), scanning-TEM and atom probe tomography (APT revealed that large dose irradiation at 450˚C of samples with initial grain sizes below 100 nm stabilized a novel nanostructure which surprisingly contained three co-existing phases, the γ face-centered-cubic (FCC) matrix, γ' L12 ordered precipitates on intragranular dislocation loops and Ni 31 Si 12 precipitates at triple junctions (TJs). In contrast, irradiation at 550˚C and irradiation of larger grain-size samples at 450˚C only produced a γ-γ' two-phase coexistence. Analysis of the three-phase nanostructure and phase field simulations indicates that radiation-induced segregation is most pronounced at TJs, thus triggering the formation of Ni 31 Si 12 precipitates. These incoherent precipitates, in turn, are expected to stabilize the grain size under irradiation. The results are generalized using the concept of driven defect-phases. It is suggested that the stabilization of driven defect-phases may impart radiation resilience by providing localized relaxation modes to the microstructure evolution during and after temporary perturbations in irradiation conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Oxide nucleation via threshold-driven volume instability in Ni oxidation

Oxide nucleation dictates the onset of metal oxidation, yet the atomistic pathways bridging initial oxygen adsorption to bulk phase transformation remain elusive. Here, we utilize in-situ atomic-resolution imaging to directly capture the nucleation of nickel oxide, revealing a threshold-driven, cooperative transformation of Ni into NiO. Our observations identify a distinct incubation period during which oxygen progressively accumulates in subsurface layers. Once a critical concentration and penetration depth are reached, a collective lattice reconfiguration is triggered, abruptly converting multiple Ni layers into NiO. Atomistic simulations corroborate this mechanism, identifying a cooperative lattice instability induced by subsurface oxygen saturation. These results establish subsurface oxygen incorporation as the missing mechanistic link between surface adsorption and three-dimensional oxide formation, providing an atomistic framework to understand and control reactive phase transformations in materials synthesis, catalysis, and degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predicting transport of intra-articularly injected growth factor fusion proteins into human knee joint cartilage

There are no drugs or treatment methods known to prevent the development of post-traumatic osteoarthritis (PTOA), a type of osteoarthritis (OA) that is triggered by traumatic joint injuries and accounts for ~12% of the nearly 600 million OA cases worldwide. Lack of effective drug delivery techniques remains a major challenge in developing clinically effective treatments, but cationic delivery carriers can help overcome this challenge. Scaling up treatments that are effective in in vitro models to achieve success in preclinical in vivo models and clinical trials is also a challenging problem in the field. Here we use a cationic green fluorescent protein (GFP) as a carrier to deliver Insulin-Like Growth Factor 1 (IGF-1), a drug considered as a potential therapeutic for PTOA. GFP-IGF-1 conjugates were first synthesized as fusion proteins with different polypeptide linkers, and their transport properties were characterized in human cartilage explants. In vitro experimental data were used to develop a predictive mathematical transport model that was validated using an independent in vitro experimental data set. In this study, the model was used to predict the transport of these fusion proteins upon intra-articular injection into human knee joints. The predictions included results for the rate and extent of fusion protein penetration into cartilage, and the maximum levels of fusion proteins that would escape into systemic circulation through the joint capsule. Together, our transport measurements and model set the stage for translation of such explant culture studies to in vivo preclinical studies and potentially clinical application.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Size-dependent stochastic tensile properties in additively manufactured 316L stainless steel

Recent work in metal additive manufacturing (AM) suggests that mechanical properties may vary with feature size; however, these studies do not provide a statistically robust description of this phenomenon, nor do they provide a clear causal mechanism. Because of the huge design freedom afforded by 3D printing, AM parts typically contain a range of feature sizes, with particular interest in smaller features, so the size effect must be well understood in order to make informed design decisions. This work investigates the effect of feature size on the stochastic mechanical performance of laser powder bed fusion tensile specimens. A high-throughput tensile testing method was used to characterize the effect of specimen size on strength, elastic modulus and elongation in a statistically meaningful way. The effective yield strength, ultimate tensile strength and modulus decreased strongly with decreasing specimen size: all three properties were reduced by nearly a factor of two as feature dimensions were scaled down from 6.25 mm to 0.4 mm. Hardness and microstructural observations indicate that this size dependence was not due to an intrinsic change in material properties, but instead the effects of surface roughness on the geometry of the specimens. Finite element analysis using explicit representations of surface topography shows the critical role surface features play in creating stress concentrations that trigger deformation and subsequent fracture. The experimental and finite element results provide the tools needed to make corrections in the design process to more accurately predict the performance of AM components.

316L stainless steel↗
DOE OSTI2023

Ultrafine-grained Fe-TiB 2 high-modulus nanocomposite steel with high strength and isotropic mechanical properties by laser powder bed fusion

Fe-TiB 2 metal matrix composite, also called high-modulus steels (HMSs), are of great interest for applications in fuel-efficient transportation infrastructure, aerospace, and wear industries due to their high specific stiffness and yield strength. However, conventional cast Fe-TiB 2 HMSs often contain coarse and sharp-edged TiB 2 particles which easily trigger premature cracking during loading. Here, we synthesized a Fe-TiB 2 nanocomposite HMS via laser powder bed fusion (LPBF) additive manufacturing of mixed micro-sized powders of Fe, Ti, and Fe 2 B. We investigated the microstructure formation and mechanical behavior of the Fe-TiB 2 HMS. We found that in situ chemical reaction of Ti and Fe 2 B enables the formation of TiB 2 particles at nanoscale during rapid solidification of LPBF. These nanoscale TiB 2 particles can serve as heterogeneous nucleation sites and promote the formation of ultrafine and equiaxed α-Fe grains with random crystallographic textures, which differ from many other additively manufactured (AM) metal alloys characteristic of strong crystallographic textures. As such, isotropic mechanical properties were achieved in the AM Fe-TiB 2 nanocomposite HMS with a high elastic modulus of ~ 240 GPa, an exceptional yield strength of ~ 1450 MPa, and a large plasticity of ~ 20% under compression. Quantitative analysis reveals that the high yield strength primarily originates from strengthening contributions of the ultrafine grains with an average grain size of ~450 nm, the nanoscale TiB 2 reinforcing particles of 20–180 nm, and a high density of printing-induced dislocations of the order of 10 15 m –2 . In situ synchrotron high-energy X-ray diffraction unveils the load partitioning from the softer α-Fe matrix to the stiffer and stronger TiB 2 nanoparticles, contributing to the sustained strain hardening during compression. Our work not only provides a general pathway for achieving high-performance metal matrix nanocomposites by in situ chemical reaction and precipitation of ceramic nanoparticles during additive manufacturing, but also offers mechanistic insights into the deformation mechanism of nanoparticle-reinforced HMS composites.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi-stage load partitioning in additively manufactured Al6061+TiC nanocomposite characterized by in-situ neutron diffraction

Metal matrix composites (MMCs), combining metal matrix and ceramic particles, exhibit high mechanical strength and stiffness compared to conventional metallic materials. During fusion-based additive manufacturing (AM), MMCs undergo a rapid heating and cooling thermal history, which affects the interfacial bonding, thermal misfit stress and mechanical load transfer behavior between the metal matrix and particles, thus impacting the bulk mechanical performance. Here, we investigate the deformation dynamics and phase-specific load transfer in fusion-based AMed Al6061 +TiC MMCs through in-situ neutron diffraction. By calculating the phase-specific lattice strains, a multi-stage load transfer and deformation behavior during uniaxial compression is revealed: (1) elastic deformation in Stage I for both phases; (2) sudden stress rebalance between two phases in Stage II, evidenced by a sudden decrease in Al lattice strain and increase in TiC; (3) active load carrying by both phases in Stage III, with both phases experiencing an increase in lattice strains. Further, the deformation mechanism of each stage is deducted by correlating the evolutions of the interphase stresses and peaks’ broadening and intensity of the Al matrix. The local plastic deformation of the Al matrix near the phase interface is triggered and leads to stress rebalancing in Stage II. The global plastic deformation subsequently propagates throughout the Al matrix in Stage III, and the composite is further hardened through both dislocation multiplication and load transfer. The findings offer valuable insights into deformation and load-sharing behavior in AMed MMCs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predicting spring green-up across diverse North American grasslands

Vegetation phenology influences many ecosystem and climate processes, such as carbon uptake and energy and water cycles. Thus, understanding drivers of vegetation phenology is crucial for predicting current and future impacts of climate change on ecological systems. Existing models can accurately predict the date of spring green-up in temperate forests but tend to perform poorly in grassland systems. We hypothesize this is because most do not incorporate water availability, a primary limiting factor for grassland plants. In this study, we used long-term datasets of digital imagery from the PhenoCam Network of 43 diverse North American grassland sites (195 site-years) to test existing spring phenology models, as well as develop several new models that incorporate precipitation or soil moisture (53 models). As a result, most of the new models performed substantially better, with the best model requiring sufficient accumulated precipitation followed by warm temperatures to trigger spring onset (root mean square error, RMSE, between predicted and observed dates = 16.0 days). Importantly, the best model performed well across all grassland types using a single set of parameters, from temperate to arid grasslands. Since plants are adapted to their local climates, model performance was further improved when parameters were independently optimized for four separate climate regions (RMSE = 10.4 days). Therefore, both sufficient precipitation and temperature are required for grassland green-up, but optimal thresholds vary by region. Running the top model with projected climate data (representative concentration pathway 8.5) suggests that, depending on the climate region, spring onset will occur up to 12 days earlier within 100 years in temperature-limited sites, but the trend is unclear for precipitation-limited sites (3.5 ± 8.0 days later). This new phenology model improves our ability to understand and predict grassland dynamics, with implications for both current and future ecosystem processes related to carbon and water cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Grazer-induced changes in molecular signatures of cyanobacteria

Algal biomass production is an emerging renewable source of fuels, nutrients, manufacturing materials, and pharmaceuticals. Industrial-scale production is predominantly performed in open raceway ponds that are inexpensive to build, operate, and maintain compared to closed bioreactors. However, these open pond systems suffer from increased opportunities for biological contamination from predators, pathogens, and competitors, which result in reduced biomass quality and yields and often the complete destruction of the crop over a short period of time. Early detection of contaminants is a necessary step of integrated pest management for triggering and informing interventions to prevent crop losses. To develop a sensitive method of detection utilizing mass spectrometry (MS), we used three methods – imaging mass spectrometry (imaging MS), liquid chromatography MS/MS (LC-MS/MS) combined with molecular networking, and gas chromatography MS/MS (GC–MS/MS) – to observe and identify molecular signatures from a model predator-prey system of the heterolobosean amoeba HGG1 preying on the filamentous cyanobacterium Anabaena sp. PCC 7120. Imaging MS enabled the association of molecules with the crop, the predator, or the activity of protozoan grazing, while LC-MS/MS-based molecular networking identified a subset of the grazing-specific signals as the chlorophyll breakdown products pyropheophytin, pheophorbide A, and pyropheophorbide. Application of MS techniques to other amoebacyanobacterial predator-prey pairs allowed categorization of grazing signatures as universal or specific to the species of prey, predator, or the prey-predator pairing, indicating that MS-based techniques can distinguish crops from competitors and potentially identify predators. Finally, GCMS/MS was shown to be capable of monitoring novel volatile organic compounds (VOCs), including those predicted to be released through chlorophyll breakdown, in the headspace over algal cultures under predation. Furthermore, these results demonstrate that the combination of multiple MS technologies creates a predictive framework to identify and catalog relevant molecular signatures for informing crop protection strategies.

09 BIOMASS FUELS↗
DOE OSTI2021

Simulation-based methodology to assess the lattice defects creation as energy storing process

In nuclear industry, damages caused to in-core structural materials by high-energy neutrons have been studied for years. Recently, the possibility of storing energy through the creation of defects in crystalline materials via heavy particle bombardment was investigated. To evaluate the potential of the Wigner effect as energy-storing process, a graphite-moderated Molten Salt Reactor was adopted as a test case. Neutronics simulations performed with OpenMC Monte Carlo code allowed estimating the amount of energy released during fission events, the fraction that is deposited in graphite, and the fraction that has the potential to cause radiation damages. Additionally, molecular dynamics simulations were then performed to study the evolution of cascades triggered by high-energy neutrons. As a major outcome, a more accurate estimate of the radiation damage with respect to the traditional approaches was obtained, and the fraction of the deposited neutron energy that can be stored through long-lived defects was quantified.

25 ENERGY STORAGE↗
DOE OSTI2021

Power spectrum and form factor in random diagonal matrices and integrable billiards

Triggered by a controversy surrounding a universal behavior of the power spectrum in quantum systems exhibiting regular classical dynamics, we focus on a model of random diagonal matrices (RDM), often associated with the Poisson spectral universality class, and examine how the power spectrum and the form factor get affected by two-sided truncations of RDM spectra. Having developed a nonperturbative description of both statistics, we perform their detailed asymptotic analysis to demonstrate explicitly how a traditional assumption (lying at the heart of the controversy) – that the power spectrum is merely determined by the spectral form factor – breaks down for truncated spectra. This observation has important consequences as we further argue that bounded quantum systems with integrable classical dynamics are described by heavily truncated rather than complete RDM spectra. High-precision numerical simulations of semicircular and irrational rectangular billiards lend independent support to these conclusions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

On the prediction of critical heat flux using a physics-informed machine learning-aided framework

The critical heat flux (CHF) corresponding to the departure from nucleate boiling (DNB) crisis is essential to the design and safety of a two-phase flow boiling system. Despite the abundance of predictive tools available to the thermal engineering community, the path for an accurate, robust CHF model remains elusive due to lack of consensus on the DNB triggering mechanism. This work aims to apply a physics-informed machine learning (ML)-aided hybrid framework to achieve superior predictive capabilities. Such a hybrid approach takes advantage of existing understanding in the field of interest (i.e., domain knowledge) and uses ML to capture undiscovered information from the mismatch between the actual and domain knowledge-predicted target. A detailed case study is carried out with an extensive DNB-specific CHF database to demonstrate (1) the improved performance of the hybrid approach as compared to traditional domain knowledge-based models, and (2) the hybrid model’s superior generalization capabilities over standalone ML methods across a wide range of flow conditions. The hybrid framework could also readily extend its applicability domain and complexity on the fly, showing an elevated level of flexibility and robustness. Based on the case study conclusions, the window-type extrapolation mapping methodology is further proposed to better inform high-cost experimental work.

42 ENGINEERING↗
DOE OSTI2021

Unlocking large compressive strains in thin active elastocaloric layers

Elastocaloric cooling attracts broad interest and rapidly growing attention due to its potential for high efficiency and low environmental impact. While it is common knowledge that triggering reversible entropy and temperature changes with stress applied in compression prevents rapid failures of materials, realizing this regime in elastocaloric systems is highly challenging because nearly all geometries suited for efficient heat transfer are prone to buckling even under modest loads. This work describes a concept of a novel composite, where an active NiTi layer is embedded into a polymer support structure such that the elastocaloric material is entirely in compression when the assembly is subjected to bending. The active layer achieves 8.1 K temperature change at 2.5% compressive strain without buckling. After 10,000 cycles at 2% compressive strain, the composite maintains mechanical integrity without degradation of the elastocaloric effect. The results demonstrate that NiTi and, potentially, other elastocalorically active materials in geometries previously thought impossible can be successfully implemented in regenerative cooling systems operating in compression.

42 ENGINEERING↗