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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Predicting the effects of thermally-induced density gradients on the hydrodynamic behavior of PBX 9502

High explosives are often exposed to thermal and mechanical stimuli within normal and abnormal environments. These stimuli can introduce density gradients in the explosive charge but the effect of such gradients is not well-understood. The goal of this work is to develop a comprehensive methodology to model the evolution of density gradients under various thermal conditions and then to predict shock initiation and detonation behavior of the gradated sample. PBX 9502 was chosen for these scoping studies because it has a large coefficient of thermal expansion and because the available shock initiation data indicates that initial temperature strongly affects the shock-to-detonation transition (SDT). The multiphysics code COMSOL was first used to model induced density gradients in a slab of PBX 9502 with asymmetric heating. Then, the gradated sample was constructed in the Pagosa hydrocode to simulate steel flyer impact scenarios, with SDT and detonation propagation following a calibrated Scaled Uniform Reactive Front (SURF) burn model. Furthermore, the gradated material exhibited very different initiation and corner turning behavior compared to homogeneous materials, and the orientation of the gradation was also found to have some effect. The methodology used here can estimate thermomechanical response of the material for non-uniform thermal environments and compute the resulting detonation properties of the PBX.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Single Molecule Spectroscopy Studies of Acid–Base Chemical Gradients Using Nile Red as a Probe of Local Surface Acidity

Single molecule spectroscopy studies of local acidity along bifunctional acid-base gradients are reported. Gradients are prepared by directional vapor phase diffusion and subsequent reaction of 3-aminopropyl-trimethoxysilane with a uniform silica film. Gradient formation is confirmed by spectroscopic ellipsometry and by static water contact angle measurements. X-ray photoelectron spectroscopy is used to characterize the nitrogen content and degree of nitrogen protonation along the gradient. Nile Red is employed as the probe dye in single molecule spectroscopy studies of these gradients. While Nile Red is well-known for its solvent sensitivity, it is used here, for the first time, to sense the acid/base properties of the film in two-color wide-field fluorescence imaging experiments. The data reveal broad bimodal distributions of Nile Red emission spectra that vary along the gradient direction. The single-molecule results are consistent with solution-phase ensemble acid/base studies of the dye. The former reveal a gradual transition from a surface dominated by basic aminosilane sites at the high-amine end of the gradient to one dominated by acidic silanol sites at the low-amine end. The sub-diffraction-limited spatial resolution afforded by superlocalization of the single molecules reveals spatial correlations in the acid/base properties of the gradient over ~ 200 nm distances. Furthermore, these studies provide data relevant to the use of aminosilane-modified silica in bifunctional, cooperative chemical catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Grain-boundary structure and segregation in Nb 3 Sn coatings on Nb for high-performance superconducting radiofrequency cavity applications

Here, we report on atomic-scale analyses of grain boundary (GB) structures and segregation in Nb 3 Sn coatings on Nb, prepared by the vapor-diffusion process, for superconducting radiofrequency (SRF) cavity applications, utilizing atom-probe tomography, high-resolution scanning transmission electron-microscopy and first-principles calculations. We demonstrate that the chemical composition of Nb 3 Sn GBs is correlated strongly with the diffusion of Sn and Nb at GBs during the coating process. In a sample coated with a relatively large Sn flux, we observe an interfacial width of Sn segregation at a GB of ~3 nm, with a maximum concentration of ~35 at.%. After post-annealing at 1100 °C for 3 h, the Sn segregated at GBs disappears and Nb segregation is observed subsequently at GBs, indicating that Nb diffused into the Nb3Sn GBs from the Nb substrate. It is also demonstrated that the amount of Sn segregation in a Nb 3 Sn coating can be controlled by: (i) Sn flux; and (ii) the temperatures of the Nb substrates and Sn source, which may affect the overall kinetics including GB diffusion of Sn and Nb. An investigation of the correlation between the chemical compositions of GBs and Nb 3 Sn SRF cavity performance reveals that the Nb 3 Sn SRF cavities with the best performance (high-quality factors at high accelerating electric-field gradients) do not exhibit Sn segregation at GBs. Our results suggest that the chemical compositions of GBs in Nb 3 Sn coatings for SRF cavities can be controlled by GB engineering and can be utilized to optimize fabrication of high-quality Nb 3 Sn coatings for SRF cavities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Solidification modes during additive manufacturing of steel revealed by high-speed X-ray diffraction

Solidification during fusion-based additive manufacturing (AM) is characterized by high solidification velocities and large thermal gradients, two factors that control the solidification mode of metals and alloys. Using two synchrotron-based, in situ setups, we perform high-speed X-ray diffraction measurements to investigate the impact of the solidification velocities and thermal gradients on the solidification mode of a hot-work tool steel over a wide range of thermal conditions of relevance to AM of metals. The solidification mode of primary δ-ferrite is observed at a cooling rate of 2.12x10 4 K/s, and at a higher cooling rate of 1.5x10 6 K/s, δ-ferrite is sup-pressed, and primary austenite is observed. The experimental thermal conditions are evaluated and linked to a Kurz-Giovanola-Trivedi (KGT) based solidification model. The modelling results show that the predictions from the multicomponent KGT model agree with the experimental observations. This work highlights the role of in situ XRD measurements for a fundamental understanding of the microstructure evolution during AM and for vali-dation of computational thermodynamics and kinetics models, facilitating parameter and alloy development for AM processes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Short-Term Groundwater Level Fluctuations Drive Subsurface Redox Variability

As global change processes modify the extent and functions of terrestrial-aquatic interfaces, the variability of critical and dynamic transitional zones between wetlands and uplands increases. However, it is still unclear how fluctuating water levels at these dynamic boundaries alter groundwater biogeochemical cycling. Here, we used high-temporal resolution data along gradients from wetlands to uplands and during fluctuating water levels at freshwater coastal areas to capture spatiotemporal patterns of groundwater redox potential (E h ). We observed that topography influences groundwater E h that is higher in uplands than wetlands; however, the high variability within TAI zones challenged the establishment of distinct redox zonation. Declining water levels generally decreased E h , but most locations exhibited significant E h variability, which is associated with rare instances of short-term water level fluctuations introducing oxygen. The E h -oxygen relationship showed distinct hysteresis patterns, reflecting redox poising capacity at higher E h , maintaining more oxidizing states longer than dissolved oxygen presence. Surprisingly, we observed more frequent oxidizing states in transitional areas and wetlands than in uplands. We infer that occasional oxygen entering specific wetland-upland boundaries acts as critical biogeochemical control points. Finally, high-resolution data can capture such rare yet significant biogeochemical instances, supporting redox-informed models and advancing the predictability of climate change feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Mass spectrometry and spectroscopic characterization of a tetrameric photosystem I supercomplex from Leptolyngbya ohadii , a desiccation-tolerant cyanobacterium

Cyanobacteria inhabiting desert biological soil crusts face the harsh conditions of the desert. They evolved a suite of strategies toward desiccation-hydration cycles mixed with high light irradiations, etc. In this study we purified and characterized the structure and function of Photosystem I (PSI) from Leptolyngbya ohadii, a desiccation-tolerant desert cyanobacterium. We discovered that PSI forms tetrameric (PSI-Tet) aggregate. We investigated it by using sucrose density gradient centrifugation, clear native PAGE, high performance liquid chromatography, mass spectrometry (MS), time-resolved fluorescence (TRF) and time-resolved transient absorption (TA) spectroscopy. MS analysis identified the presence of two PsaB and two PsaL proteins in PSI-Tet and uniquely revealed that PsaLs are N-terminally acetylated in contrast to non-modified PsaL in the trimeric PSI from Synechocystis sp. PCC 6803. Chlorophyll (Chl) a fluorescence decay profiles of the PSI-Tet performed at 77 K revealed two emission bands at ∼690 nm and 725 nm with the former appearing only at early delay time. The main fluorescence emission peak, associated with emission from the low energy Chls a, decays within a few nanoseconds. TA studies demonstrated that the 725 nm emission band is associated with low energy Chls a with absorption band clearly resolved at ∼710 nm at 77 K. As a result, our work suggests that the heterogenous composition of PsaBs and PsaL in PSI-Tet is related with the adaptation mechanisms needed to cope with stressful conditions under which this bacterium naturally grows.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

SymbolNet: neural symbolic regression with adaptive dynamic pruning for compression

Abstract Compact symbolic expressions have been shown to be more efficient than neural network (NN) models in terms of resource consumption and inference speed when implemented on custom hardware such as field-programmable gate arrays (FPGAs), while maintaining comparable accuracy (Tsoi et al 2024 EPJ Web Conf. 295 09036). These capabilities are highly valuable in environments with stringent computational resource constraints, such as high-energy physics experiments at the CERN Large Hadron Collider. However, finding compact expressions for high-dimensional datasets remains challenging due to the inherent limitations of genetic programming (GP), the search algorithm of most symbolic regression (SR) methods. Contrary to GP, the NN approach to SR offers scalability to high-dimensional inputs and leverages gradient methods for faster equation searching. Common ways of constraining expression complexity often involve multistage pruning with fine-tuning, which can result in significant performance loss. In this work, we propose S y m b o l N e t , a NN approach to SR specifically designed as a model compression technique, aimed at enabling low-latency inference for high-dimensional inputs on custom hardware such as FPGAs. This framework allows dynamic pruning of model weights, input features, and mathematical operators in a single training process, where both training loss and expression complexity are optimized simultaneously. We introduce a sparsity regularization term for each pruning type, which can adaptively adjust its strength, leading to convergence at a target sparsity ratio. Unlike most existing SR methods that struggle with datasets containing more than O ( 10 ) inputs, we demonstrate the effectiveness of our model on the LHC jet tagging task (16 inputs), MNIST (784 inputs), and SVHN (3072 inputs).

Tsoi, Ho Fung (ORCID:0000000225502184)↗
DOE OSTI2021

Physics-Infused AI/ML Based Digital-Twin Framework for Flow-Induced-Vibration Damage Prediction in a Nuclear Reactor Heat Exchanger

This report summarizes some of the ongoing work related to the development of an expert-elicitation-digital-twin framework for real time damage state prediction in heat exchanger components of a nuclear reactor. The framework is targeted towards predicting damage associated with coupled low cycle fatigue (associated with regular heat-up, cool-down and power operation transients) and high cycle fatigue (associated with flow induced vibration transients). The overall framework will be based on a NoSQL based database, physics-infused-geometry-dependent virtual-sensor data, different AI/ML techniques-based data-driven-predictive-model applications (Apps) and real-time plant sensor measurements available through few existing sensors. Towards this overall goal, this report updates some of the ongoing work, such as on implementation of a NoSQL Database (such as MongoDB), FE based heat transfer analysis of a heat exchanger (e.g. of a PWR steam generator) for generating geometry-dependent virtual sensor data and evaluation of various AI/ML models such as based on multivariate linear regression, ensembled decision-tree based Random-Forest and Gradient-Boosting regression and high-dimensional-kernel-function-transformation based Support-Vector-Machine regression models. The AI/ML models were evaluated for predicting multi-time-series thermal states at thousands of 3D point-clouds

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Capturing Secondary Kinetic Instabilities in Three‐Dimensional Dayside Reconnection Using an Improved Gradient‐Based Closure

Magnetic reconnection is a highly dynamic process that excites a wide variety of kinetic waves and instabilities. Transverse current sheet instabilities such as the lower-hybrid drift and secondary drift-kink instabilities in particular have been shown by kinetic simulations to modify the reconnection and introduce significant turbulence and mixing to the reconnection layer. Past studies using the ten-moment fluid model to capture important kinetic physics such as the electron inertia and full representation of the pressure tensor proved advantageous to a two-fluid representation of reconnection, but the model struggled when using a local relaxation closure for the heat flux to replicate the current sheet instabilities and subsequent mixing seen in kinetic simulations. This work uses the Gkeyll software framework to perform simulations of asymmetric reconnection based on the 16 October 2015 MMS crossing of a diffusion region, the Burch event. An improved gradient-based heat flux closure is implemented, showing significant improvement in secondary kinetic instabilities that grow in the current sheet. These instabilities generate turbulence which leads to growth of secondary magnetic islands and flux ropes.

Bradshaw, K. [Princeton University, NJ (United Sta↗
DOE OSTI2024

High Frequency Monitoring and Nitrate Sourcing Reveals Baseflow and Stormflow Controls on Total Dissolved Nitrogen and Carbon Export Along a Rural‐Urban Gradient

Abstract Efforts to reduce nitrogen and carbon loading from developed watersheds typically target specific flows or sources, but across gradients in development intensity there is no consensus on the contribution of different flows to total loading or sources of nitrogen export. This information is vital to optimize management strategies leveraging source reductions, stormwater controls, and restorations. We investigate how solute loading and sources vary across flows and land‐use using high frequency monitoring and stable nitrate isotope analysis from five catchments with different sanitary infrastructure, along a gradient in development intensity. High frequency monitoring allowed estimation of annual loading and attribution to storm versus baseflows. Nitrate loads were 16 kg/km 2 /yr. from the forested catchment and ranged from 68 to 119 kg/km 2 /yr., across developed catchments, highest for the septic served site. Across developed catchments, baseflow contributions ranged from 40% of N loading to 75% from the septic served catchment, and the contribution from high stormflows increased with development intensity. Stormflows mobilized and mixed many surface and subsurface nitrate sources while baseflow nitrate was dominated by fewer sources which varied by catchment (soil, wastewater, or fertilizer). To help inform future sampling designs, we demonstrate that grab sampling and targeted storm sampling would likely fail to accurately predict annual loadings within the study period. The dominant baseflow loads and subsurface stormflows are not treated by surface water management practices primarily targeted to surface stormflows. Using a balance of green and gray infrastructure and stream/riparian restoration may target specific flow paths and improve management.

Delesantro, Joseph M.↗
DOE OSTI2025

Finite element analysis of the impact of beam heating mode in molten salt corrosion experiments employing simultaneous ion irradiation

Finite element analysis was used to investigate the temperature and stress profiles that develop in 316L stainless steel membranes being irradiated using different proton beam conditions in contact with a molten salt environment. It was shown that in addition to a nonuniform irradiation profile, a focused 2 MeV proton beam leads to very strong temperature and stress gradients in the membrane, introducing highly localized driving forces that complicate and even compromise the integrity and reliability of the experimental results of corrosion studies. Here, the use of a focused beam in corrosion studies can create experimental artifacts that may misrepresent the true corrosion behavior. In contrast, the use of a rastered beam is shown to distribute the protons and resulting radiation damage uniformly across the membrane face, and more importantly, results in temperature and stress profiles that are not only very uniform but are of much lower magnitude. The use of a rastered beam during molten salt corrosion experiments is therefore recommended to achieve uniform damage rates, thereby reducing both gradients and magnitudes of the temperature and stress distributions.

43 - PARTICLE ACCELERATORS↗
DOE OSTI2022

Wire-coil insert optimization for high-heat-load/flux synchrotron components

Many synchrotron components require high levels of internal-flow, forced-convection heat transfer to minimize surface temperatures, thermal gradients, and thermally induced stress on high-power beam-interacting surfaces. Wire-coil inserts, physically similar to a common spring, are mechanically fitted inside of component cooling passages to optimize heat transfer performance. They are routinely used in Advanced Photon Source (APS) front end and beamline high-heat-load/flux components to significantly enhance convection heat transfer-up to 400% compared to plain open passages. This has the additional benefit of greatly reducing coolant flow requirements for these components. Using several cooling passage sizes, five different wire sizes, and a range of pitch values, an experimental investigation conducted at the APS has determined the average heat transfer coefficient and resulting pressure loss as a function of water flow rate for 65 different wire-coil inserts. Data from this study have been non-dimensionalized and generalized to yield relationships that can be used to determine the heat transfer performance and resulting pressure loss for any given wire-coil insert that may be used at the APS. Through data reduction, the wire-coil insert characteristic dimensions have also been optimized to yield the highest heat transfer enhancement while minimizing the coolant flow requirements. These generalized expressions for wirecoil inserts will be presented, and they can be used by scientists and engineers during the component design process to evaluate achievable heat transfer performance and associated pressure loss, aiding in the establishment of optimized operating parameters and cooling passage flow distribution schemes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Ground and excited state gradients with end-to-end differentiable semiempirical quantum chemistry

Accurate and efficient gradients of molecular energy with respect to nuclear degrees of freedom are essential for geometry optimization and molecular dynamics, including simulations that go beyond the Born–Oppenheimer regime. A common approach involves deriving analytical formulas for new electronic structure methods, which is often conceptually difficult and requires tedious coding. Here, we implement analytical, semi-numerical, and automatic differentiation (AD)-based gradient pathways for semiempirical Hamiltonian models in the PYSEQM software package, leveraging both graphics processing unit (GPU) and central processing unit (CPU) architectures. We further extend these capabilities to excited states calculated using the configuration interaction singles and time-dependent Hartree–Fock ansätze. We benchmark wall time, peak memory usage, and accuracy across three molecular families of varying chemical complexity, including systems of up to a thousand atoms. For ground-state simulations, analytical and AD gradients achieve near-identical GPU runtimes, while semi-numerical gradients are slower on GPU but remain competitive on CPU. For excited states, both analytical and custom AD approaches using implicit differentiation show similar performance and low memory requirements, whereas gradients with full AD are memory-limited. AD gradients match analytical ones in accuracy across all tested systems, aided by a quaternion-based diatomic frame rotation for two-center quantities that ensures smooth energy surfaces. Overall, automatic differentiation emerges as a practical alternative to analytical gradients in semiempirical quantum chemistry, offering high accuracy while allowing seamless integration in AI-driven workflows and popular packages, such as PyTorch and JAX. Our results provide actionable guidance for selecting optimal gradient strategies in large-scale ground- and excited-state molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Broadening of the Divertor Heat Flux Profile in High Confinement Tokamak Fusion Plasmas with Edge Pedestals Limited by Turbulence in DIII-D

Multimachine empirical scaling predicts an extremely narrow heat exhaust layer in future high magnetic field tokamaks, producing high power densities that require mitigation. Here, in the experiments presented, the width of this exhaust layer is nearly doubled using actuators to increase turbulent transport in the plasma edge. This is achieved in low collisionality, high confinement edge pedestals with their gradients limited by turbulent transport instead of large-scale, coherent instabilities. The exhaust heat flux profile width and divertor leg diffusive spreading both double as a high frequency band of turbulent fluctuations propagating in the electron diamagnetic direction doubles in amplitude. The results are quantitatively reproduced in electromagnetic XGC particle-in-cell simulations which show the heat flux carried by electrons emerges to broaden the heat flux profile, directly supported by Langmuir probe measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Study on divertor detachment and pedestal characteristics in the DIII-D upper closed divertor

Abstract Experiments performed in DIII-D demonstrate that higher plasma current and heating power combined with impurity seeding facilitate the achievement of divertor detachment with a higher pedestal pressure and higher plasma performance in H-mode plasmas with a baffled closed divertor compared with an open divertor. Dedicated experiments were carried out to study the impact of power, plasma current and impurity seeding on divertor detachment with ion B × ∇ B directed into the divertor favorable for the L–H transition. With a factor of three variation in heating power and with only D 2 puffing, no significant difference in the separatrix density at detachment onset was found. The higher heating power leads to higher impurity concentration and wider scrape-off layer (SOL) width, and reduces the detachment onset density to one similar to that in lower-power plasmas. Higher current requires higher pedestal and line-averaged densities to achieve divertor detachment; however, the increase in separatrix density at increasing plasma current is found to be less pronounced. Initial calculations found that both power scan and plasma current scan datasets are qualitatively consistent with theory after considering the change in impurity concentration and heat flux width. This also motivates the future extensive study of transport and divertor impurity behavior in order to have a quantitative comparison between experiment and theory. Compared with an open divertor, a closed divertor facilitates detachment onset at ∼40% lower line-averaged plasma density. Additional N 2 seeding facilitates the achievement of detachment at a lower separatrix density and thus a higher pedestal temperature, which is beneficial for advanced tokamak scenarios. Higher heating power requires a higher N 2 puffing rate to achieve the same degree of detachment, while a higher N 2 puffing rate leads to lower detachment onset line-averaged density, both of which agree with theory. In contrast to the narrower pedestal in an open divertor approaching detachment, the pedestal density width in a closed divertor increases with density. The density gradient increases with line-averaged density at higher plasma current, but remains nearly unchanged at lower plasma current. In particular, compared with discharges with low power, at high heating power the pedestal density gradient is much weaker, while the SOL density is significantly higher and wider. At the same plasma current, both pedestal pressure gradient and temperature gradient decrease linearly with the line-averaged density but remain similar across different heating powers. Even with different plasma current and heating power, the normalized pressure gradient remains identical. As a result, achievement of divertor detachment with a higher pedestal pressure and higher plasma performance is shown in a closed divertor, which is important for improving core–edge integration as one of the critical issues for future tokamak fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Stellar Abundance Maps of the Milky Way Disk

To understand the formation of the Milky Way's prominent bar it is important to know whether stars in the bar differ in the chemical element composition of their birth material as compared to disk stars. This requires stellar abundance measurements for large samples across the Milky Way's body. Such samples, e.g., luminous red giant stars observed by the Sloan Digital Sky Survey's APOGEE survey, will inevitably span a range of stellar parameters; as a consequence, both modeling imperfections and stellar evolution may preclude consistent and precise estimates of their chemical composition at a level of purported bar signatures, which has left current analyses of a chemically distinct bar inconclusive. Here, we develop a new self-calibration approach to eliminate both modeling and astrophysical abundance systematics among red giant branch (RGB) stars of different luminosities (and hence surface gravity $\mathrm{log} g$). We apply our method to 48,853 luminous APOGEE Data Release 16 RGB stars to construct spatial abundance maps of 20 chemical elements near the Milky Way's mid-plane, covering galactocentric radii of 0 kpc < R GC < 20 kpc. Our results indicate that there are no abundance variations whose geometry matches that of the bar, and that the mean abundance gradients vary smoothly and monotonically with galactocentric radius. We confirm that the high-α disk is chemically homogeneous, without spatial gradients. Furthermore, we present the most precise [Fe/H] versus R GC gradient to date with a slope of – 0.057 ±0.001 dex kpc –1 out to approximately 15 kpc.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Predicting the formation of fractionally doped perovskite oxides by a function-confined machine learning method

Abstract Fractionally doped perovskites oxides (FDPOs) have demonstrated ubiquitous applications such as energy conversion, storage and harvesting, catalysis, sensor, superconductor, ferroelectric, piezoelectric, magnetic, and luminescence. Hence, an accurate, cost-effective, and easy-to-use methodology to discover new compositions is much needed. Here, we developed a function-confined machine learning methodology to discover new FDPOs with high prediction accuracy from limited experimental data. By focusing on a specific application, namely solar thermochemical hydrogen production, we collected 632 training data and defined 21 desirable features. Our gradient boosting classifier model achieved a high prediction accuracy of 95.4% and a high F1 score of 0.921. Furthermore, when verified on additional 36 experimental data from existing literature, the model showed a prediction accuracy of 94.4%. With the help of this machine learning approach, we identified and synthesized 11 new FDPO compositions, 7 of which are relevant for solar thermochemical hydrogen production. We believe this confined machine learning methodology can be used to discover, from limited data, FDPOs with other specific application purposes.

08 HYDROGEN↗
DOE OSTI2023

Gradient nanostructured steel with superior tensile plasticity

Nanostructured metallic materials with abundant high-angle grain boundaries exhibit high strength and good radiation resistance. While the nanoscale grains induce high strength, they also degrade tensile ductility. We show that a gradient nanostructured ferritic steel exhibits simultaneous improvement in yield strength by 36% and uniform elongation by 50% compared to the homogenously structured counterpart. In situ tension studies coupled with electron backscattered diffraction analyses reveal intricate coordinated deformation mechanisms in the gradient structures. The outermost nanolaminate grains sustain a substantial plastic strain via a profound deformation mechanism involving prominent grain reorientation. This synergistic plastic co-deformation process alters the rupture mode in the post-necking regime, thus delaying the onset of fracture. The present discovery highlights the intrinsic plasticity of nanolaminate grains and their significance in simultaneous improvement of strength and tensile ductility of structural metallic materials.

36 MATERIALS SCIENCE↗