Search NASA⌕ Search

SEARCH · Search NASA

Results for “random microstructure”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High-Resolution Comonomer Sequencing of Blocky Brominated Syndiotactic Polystyrene Copolymers Using 13C NMR Spectroscopy and Computer Simulations

This work demonstrates the first high-resolution comonomer sequencing of Blocky brominated syndiotactic polystyrene (sPS-co-sPS-Br) copolymers based on pentad assign- ments of the quaternary carbon region of the nuclear magnetic resonance spectrum. Copolymers containing p-bromostyrene (Br-Sty) units were prepared in matched sets using postpolymerization bromination methods carried out in the heterogeneous gel state (Blocky) and homogeneous solution state (Random). Quantitative information from the quaternary carbon spectra, heteronuclear multiple bond correlation spectroscopy, electronic structure calculations, and simulated statistically random copolymers was correlated to confirm the carbon resonance assignments for all 20 possible pentad comonomer sequences. Using the experimental pentad sequence prevalences, a computer code was developed to simulate chains with microstructures typical of each sample as a means to visually represent the copolymer blockiness with quantitative precision. Based on the microstructure and distribution of run lengths in these chains, the simulations revealed that the Blocky copolymers contain a high degree of blockiness. By comparing the run lengths in the simulated chains to the average number of styrene units in a crystalline segment of sPS (found by small-angle X-ray scattering), copolymer crystallizability was predicted. For the simulated Blocky B-21% (21 mol % Br-Sty) chain, the probability of randomly selecting a styrene unit in a crystallizable block was 25.8%, while that in the simulated Random R-18% was zero, in excellent agreement with the experimental crystallization behavior measured by differential scanning calorimetry. Additionally, these predictions confirmed that the simulated chains accurately represent the ensemble of chains in their respective copolymer samples. Furthermore, each simulated Blocky chain contained one or more long sPS blocks that paralleled the measured 38-40 styrene units spanning a crystalline segment within the sPS/CCl4 gel. This finding affirmed that the long sPS segments originated from the precise lamellar structure within the heterogeneous gel morphology (i.e., block length is correlated with lamellar thickness). Overall, the ability to tailor the copolymer microstructure through control of the semicrystalline gel morphology opens the door to synthesizing ordered copolymers by postpolymerization functionalization processes with unprecedented levels of compositional control.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Anomalous lattice expansion of bcc Ta in helium-loaded diamond anvil cells

Anomalous lattice expansion of bcc Ta is observed in helium-loaded diamond anvil cell (DAC) experiments near 6 GPa and above 400 K, while co-loaded W, Mo, and Au exhibit normal thermal expansion. The Ta volume expansion increases with temperature, reaching ~14% near 650 K before plateauing, and is largely retained after recovery to ambient conditions. Time-resolved measurements at 500 K reveal progressive expansion over several hours, consistent with gradual, thermally activated He incorporation. The largely retained expansion during subsequent cooling and holding at 400 K indicates that the incorporated He is predominantly kinetically trapped. The data reveal two distinct regimes: below ~550 K, modest and spatially uniform expansion consistent with interstitial He trapping at isolated, randomly distributed vacancies; above ~550 K, He-vacancy cluster growth producing dramatically larger expansion, peak broadening, and a core–shell microstructure revealed by micron-resolution X-ray diffraction mapping. These results demonstrate that He is not always a passive pressure medium in DAC experiments and reveal a previously unrecognized regime of He-mediated lattice modification in Ta, complementing conventional ion-implantation studies relevant to nuclear and fusion structural materials.

Diamond anvil cell↗
DOE OSTI2021

A constitutive model incorporating grain refinement strengthening on metallic alloys

Surface nano-crystallization techniques have been recently developed as one of the most efficient ways to optimize materials’ structure, and therefore develop the local and global mechanical behavior as to increase strength without compromising ductility. Here, in this work, we present a constitutive model incorporating grain refinement hardening to simulate the nano-crystallization technique, specifically, surface mechanical attrition treatment. The computation is implemented using user-defined VUMAT subroutines. As an example of its application, a geometry model with full coverage of random impacts are employed. The results show that the model has rather precise predictability of grain size evolution during plastic deformation. The readily embedded with a computational code of material dynamics enables this novel model to be a promising tool to study the dynamic evolution of microstructures under plastic deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A detailed study of the microstructure and thermal stability of typical SiC fibers

Highlights: • The cross-sectional microstructure and thermal stability of typical SiC fibers were characterized via SEM and TEM. • The SiC fiber with gradient microstructure has better properties than that with uniform microstructure. • The graphite exhibits straight planes on the fiber surface while they're turbostratic inside the fiber. Continuous SiC fibers have attracted increasing research interest for their significant application in aerospace and nuclear energy. Control of inhomogeneity and decrement of defects are crucial for improving the mechanical and high-temperature performance of SiC fibers. Thus an understanding of fine and detailed microstructural and microchemical distribution of SiC fibers is urgently needed. In the present work, the cross-sectional phase distributions, morphologies and defects of amorphous, non-stoichiometric and near-stoichiometric SiC fibers were well characterized. From surface to core, the amorphous and non-stoichiometric fibers exhibited uniform microstructures, but a gradient change along the radial direction was observed in the near-stoichiometric fiber. Nanosized SiC and turbostratic carbon (2–4 nm) were randomly distributed inside the amorphous fiber. A large amount of graphite surrounding SiC grains appears in the non-stoichiometric fiber which possess low strength and weak thermal stability. The near-stoichiometric fiber has transgranular fracturing, high strength and favorable thermal stability, and the graphite planes are turbostratic inside the fiber but straight on the surface. The results of both energy-dispersive X-ray spectrometry measurements and first-principles calculations demonstrate that Al atoms can occupy Si sites in the SiC grains. Our findings offer fine understanding for fabricating SiC fibers with superior properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Simulation of dynamic crystal plasticity with a Lagrangian discontinuous Galerkin hydrodynamic method

Here we present a new Lagrangian modal discontinuous Galerkin (DG) hydrodynamic method that supports a dynamic dislocation based crystal plasticity model for simulating the mechanical behavior of crystallographic materials, both single crystal and polycrystalline, under dynamic conditions. A modal DG approach is used to evolve fields relevant to conservation laws. These fields are approximated by Taylor series polynomials of varying degree. These polynomials describe macro-scale hydrodynamic behavior while their evolution is determined by evaluating the dynamic crystal plasticity model at material points within the element. The dynamic crystal plasticity model is sensitive to the time increment size, with too large of time increments leading to instability in the model. To mitigate this, the temporal evolution of the dynamic crystal plasticity model is achieved with the combination of a sub-incrementing scheme with Heun’s third-order time integration scheme, which is also used to temporally evolve the governing equations. The implementation of the dynamic crystal plasticity model within the DG framework is tested using a 2D approximation of the Taylor impact test with a single crystal material, using quadratic elements that have faces that can bend. In addition to the standard continuous material modeling, we propose a new simulation method that would represent the heterogeneous behavior of polycrystalline microstructures within an element by varying the position and material properties of the material points within the element. This method is demonstrated using random orientation distributions on materials points that are arranged in both structured and random configurations.

42 ENGINEERING↗
DOE OSTI2019

Development of Texture in Ultrafine-Grained Low-Carbon Steel Processed through Equal-Channel Angular Pressing

Developments of microstructures and texture are investigated for a low-carbon steel deformed by equal-channel angular pressing (ECAP) at room temperature for equivalent strain (ε{sub vm}) of 16.8. ECAP at ε{sub vm} = 0.6 reduces grain size by two orders of magnitude. With increasing strain, grain size reduces further and high-angle grain boundary (HAGB) fraction improves by grain subdivision and its change in orientation. ECAP of low-carbon steel up to ε{sub vm} = 16.8 can produce ultrafine grains of 0.2 µm size with HAGB fraction of 82%. The as-received steel has low texture index. Microstructural changes strongly influence texture development. It increases with equivalent strain as grain subdivision continues. Texture index fluctuates at intermediate strain range due to randomization of initial texture. Texture index reaches saturation at the high equivalent strain. On ECAP at low to intermediate strain ε{sub vm} = 0.6-6, components of both α (F{sub θ}, J{sub θ}, and J-bar {sub θ}) and γ (D{sub 1θ}, D{sub 2θ}, and E{sub θ}) fibers are developed though all of them deviate from their ideal positions. At higher strain (ε{sub vm} = 9-16.8), the γ fiber components (D{sub 1θ}, D{sub 2θ}, E{sub θ}) are strengthened, and the E{sub θ} component reaches the highest intensity of ≈ 17 at ε{sub vm} = 12. There is no texture symmetry at low to high strain level. The presence of pearlite in low-carbon steel enhances strongly the deviation of texture components from their ideal positions in Euler’s space as well as it increases the intensities of the components more than that of IF steel for a similar equivalent strain.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Synergetic Strengthening of Grain Refinement and Texture in Gradient Zircaloy-4 by Surface Mechanical Rolling Treatment

A Zircaloy-4 rod was subjected to surface mechanical rolling treatment (SMRT) to form a gradient structure, and the evolution of the resulting sub-grain-boundary property and texture across the gradient structure was characterized using electron backscattered diffraction. Dual-gradient structures in grain size and orientation were formed; the grain size was refined from several microns at the center to approximately 400 nm at the topmost surface. Texture analysis revealed that the c-axis gradually tilted from a random orientation toward the parallel-to-radial direction on the radial–tangential plane. The SMRT-induced formation of the dual-gradient microstructure is attributed to the formation of gradient distributions of stress and strain, which resulted in various deformation mechanisms (twinning and dislocation) being active at different depths. During the SMRT process, twinning and dislocations were activated to refine the grains. When the dual-gradient microstructure formed, twinning was mainly activated at the subsurface near the matrix, whereas dislocations were activated across the entire gradient. The geometrically necessary dislocation density increased with decreasing depth and then slightly decreased near the surface. The synergetic strengthening of the dual-gradient microstructure resulted in a gradient distribution of the microhardness near the surface. Thus, the Zircaloy-4 rod exhibited a good combination of strength and ductility.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Robustness of magnetocrystalline anisotropy and coercivity in Fe–Co–B

As a potential candidate for critical chemical element free permanent magnet, (Fe 0.7 Co 0.3 ) 2 B, shows promising intrinsic magnetic properties, including large magnetization, high Curie temperature and moderate magnetocrystalline anisotropy (MCA). Still, the coercivity that has been achieved is relatively low. To understand and improve coercivity, here we study the robustness of MCA related to the fluctuation of chemical composition and the structural distortion and its effect on coercivity in (Fe 0.7 Co 0.3 ) 2 B from first principles DFT (density functional theory) calculation and micromagnetic simulation. A fluctuation of cobalt content of 10%, or 1% isotropic lattice strain, or 2% tetragonal distortion reduces MCA energy up to 30%. By considering randomly distributed local MCA energy reduction up to 30%, the calculated coercivity of anisotropic bulk magnets reduced from 3.6 kOe to 2.2 kOe. Rational microstructure design, such as grain size refinement and development of strong crystal texture of MCA easy-axis (i.e., degree of alignment for (Fe 0.7 Co 0.3 ) 2 B grains), can enhance coercivity and mitigate the effect of local MCA reduction. In addition to acceptable intrinsic magnetic properties, the promising hard magnetic phase needs good MCA robustness to facilitate the development of practical magnets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Crosslinked Matrimid®-like polyimide membranes with unimodal network structure for enhanced stability and gas separation performance

Gas separation membranes have attracted academic and industrial attention, and crosslinking has been identified to be one of the most effective ways to enhance membrane stability. In this paper, a series of crosslinked Matrimid®-like films with unimodal network structures are prepared via thermally end-linking phenylethnyl-terminated BTDA-DAPI oligomers with well-controlled molecular weight (i.e., 3000–15,000 g/mol), wherein the crosslink density (the inter-crosslink chain length) of resulting unimodal networks is systematically varied by using oligomers with various molecular weight. Comprehensive characterizations of chemical structure, thermal properties, microstructures are performed. Pure-gas permeation measurements are performed focusing on H 2 /CH 4 and CO 2 /CH 4 separations as a function of crosslink density. In sharp contrast to the commonly observed permeability reduction in randomly crosslinked networks, all the crosslinked unimodal films, even when densely crosslinked, present markedly enhanced permeability and well-maintained ideal selectivity relative to the uncrosslinked linear counterpart, leading to almost horizontal movements towards upper bounds along with expectedly enhanced membrane stability. In conclusion, it is concluded that introducing bulky groups at the crosslink sites provide a practical means to counteract the densification effect induced by crosslinking and the construction of unimodal networks exemplifies a fundamentally new strategy to regulate the microstructure and property of crosslinked membranes for gas separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Comparative study of microstructure and properties of low-alloy-steel/nickel-based-alloy interfaces in dissimilar metal weld joints prepared by different GTAW methods

Highlights: • Number of type I and type II boundaries: H-DMWJ > C-DMWJ > W-DMWJ. • Width carbon depleted zones and carbon enriched zones: H-DMWJ > C-DMWJ > W-DMWJ. • Type I and type II boundaries are susceptible to SCC and cracked during mechanical bending. • C-DMWJ has the best performance while H-DMWJ has the worst one. - Abstract: Low-alloy-steel/buttering (or welding) metal interfaces in safe-end dissimilar metal weld joints (DMWJs) at nuclear power plants are weak parts. To optimize the quality of the safe-end DMWJs used for the construction of domestic nuclear power plants and to improve the welding productivity, a series of DMWJs in full-size have been manufactured by using different gas tungsten arc welding (GTAW) methods. The microstructure, chemical composition distribution and local properties across the SA508/52(M) interfaces in these DMWJs are studied. The high heat input and long high temperature duration during hot-wire GTAW process promote the carbon diffusion and grain boundary migration and hence the DMWJ by hot-wire GTAW has the largest amount of type I and type II boundaries and the widest carbon depleted zones and carbon enriched zones, which resulting in the worst performance among the DMWJs in simulated primary water. Type I and type II boundaries are high angle random grain boundaries (RGBs) and Cr-depleted zones are found along type II boundaries resulting in their high susceptibility to SCC. In addition, these boundaries are prone to be cracked during mechanical bending process.

36 MATERIALS SCIENCE↗
DOE OSTI2026

ML-based Micro-CT SOFC Microstructure Models (from Kent 2026 Microstructural Augmentation paper)

Overview -------------------------- This repository contains datasets from the manuscript **"Enhanced Generalizability to Deep-Learning Quantification of 3D Microstructural Characteristics through Microstructurally Aware Augmentation of Scarce Data"** (*William F. Kent, Rochan Bajpai, Rachel C. Kurchin, William K. Epting, Harry W. Abernathy, Paul A. Salvador. Submitted 2026*). The methods are also described in the dissertation **Data Intensive Analysis of Solid Oxide Cell Microstructures** (*Doctoral dissertation, Carnegie Mellon University, 2025*). The datasets here are trained convolutional neural network (CNN) models for predicting key microstructural properties of solid oxide cell (SOC) electrodes from low-res, 2-channel 3D images, as well as some helpful code. The parameters for input images are provided in the paper. Sample data is provided in the file `Combined_anode_aug_dual_1k_examples` - that particular data was used to train `anode_all_aug.pth` and will work most accurately with that model. Please familiarize yourself with all caveats on accuracy and applicability, as detailed in the associated paper. Usage -------------------------- The basic usage is as follows, assuming `model_fn` is the path to the .pth file, and `X` is 2-channel input image(s) of the proper dimensions (either one image of shape `[2,12,24,24]`, or a batch of N input images of shape `[N,2,12,24,24]`): from CNN_inferencer import load_model_for_inference model = load_model_for_inference(model_fn) y_predicted = model(X) The model object automatically handles input scaling and output de-scaling based on the way the models were trained - in other words, pass in a 2-channel micro-CT image, and it will output microstructural property values in real units. ## Other model object attributes Note that model has useful attributes other than its forward pass model(X). * `model.output_descaler` - returns the output descaler object. Model does the de-scaling when generating inferences, but you may want to re-use this de-scaler on other values to e.g. compare predictions to ground truth from already-scaled training data. * `model.prop_names` - Gives the property names of the predicted y values, in order. Only exists if there's an output scaler as part of the model object, which there will be in the models provided here. ## Usage with sample data Here is a short script to use with the included sample data. from CNN_inferencer import display_predictions, load_model_for_inference, calculate_mape, parity_plot import h5py import numpy as np model_fn = 'anode_all_aug.pth' data_fn = 'Combined_anode_aug_dual_1k_examples.h5' N_samples = 200 figure_outdir = '.' model = load_model_for_inference(model_fn) with h5py.File(data_fn,'r') as f: XX = f['X'] #These are the 2-channel 3D images yy = f['y'] #These are the ground-truth microstructural properties, but they have been scaled for training - need to de-scale below N = XX.shape[0] #How many images total in the input data file #Run inferences on N_samples random samples from XX. #Run in a batch, much more efficient than one at a time. ii = np.random.choice(N,N_samples,replace=False) ii.sort() y_pred = model(XX[ii]) #Get the original/true (but normalized/scaled) values from the training dataset... #Because they were normalized, they are not in real units yet. So let's also de-scale them using model.output_scaler. y_true = model.output_scaler.transform(yy[ii]) #Let's display actual values for just 5 random ones for i in np.random.choice(N_samples,5,replace=False): display_predictions(y_true[i], y_pred[i], model.prop_names) #Make parity plots for each property (ground truth vs predicted values) #Also label each plot with the mean abs. percent error (MAPE) of the predicted values for i,key in enumerate(model.prop_names): mape = calculate_mape(y_true[:,i], y_pred[:,i]) parity_plot(y_true[:,i], y_pred[:,i], figure_outdir, key, extra_title=f' ({mape:.2f}% MAPE)')

3D microstructure↗
DOE OSTI2019

Structural and Hysteretic Properties of La{sub 0.7}Ca{sub 0.3−x}Sr{sub x}MnO{sub 3} Manganites Using the Hydrothermal Route

Manganitesof La{sub 0.7}Ca{sub 0.3−x}Sr{sub x}MnO{sub 3} have been produced using the hydrothermal method. The influence of the concentration of La, Ca, and Sr on the structural, morphological, and magnetic properties was studied and analyzed. The x-ray diffraction studies showed the occurrence of orthorombic and trigonal symmetries in the crystalline structure, depending on the stoichiometry. X-ray photoelectron spectroscopy studies were performed, showing the presence of the elements La3d, Ca2p, Sr3d, Mn2p, and O1s. In all samples, a deficiency of oxygen was observed and ascribed to hydroxide formation. The FTIR spectra shows the Mn–O–Mn bonds in the stretching vibration mode; on the other hand, a great relative amount of Mn{sup 4+} ions that are not included in the manganite phase was observed. Furthermore, morphology analyses developed using scanning electron microscopy showed cauliflower-type microstructures in all samples. The dependence of magnetization on magnetic field was also studied where a low coercivity and a high-saturation magnetization were evidenced. Values of the squareness ratio coefficient ranged between 0.0587 and 0.0867, indicating that the individual particles exhibit a strong random anisotropy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Seismic Anisotropy of Temperate Ice in Polar Ice Sheets

Here we present a series of simple shear numerical simulations of dynamic recrystallization of two-phase nonlinear viscous materials that represent temperate ice. First, we investigate the effect of the presence of water on the resulting microstructures and, second, how water influences on P wave (V p ) and fast S wave (V s ) velocities. Regardless the water percentage, all simulations evolve from a random fabric to a vertical single maximum. For a purely solid aggregate, the highest V p quickly aligns with the maximum c-axis orientation. At the same time, the maximum c-axis development reduces V s in this orientation. When water is present, the developed maximum c-axis orientation is less intense, which results in lower V p and V s . At high percentage of water, V p does not align with the maximum c-axis orientation. If the bulk modulus of ice is assumed for the water phase (i.e., implying that water is at high pressure), we find a remarkable decrease of V s while V p remains close to the value for purely solid ice. These results suggest that the decrease in V s observed at the base of the ice sheets could be explained by the presence of water at elevated pressure, which would reside in isolated pockets at grain triple junctions. Under these conditions water would not favor sliding between ice grains. However, if we consider that deformation dominates over recrystallization, water pockets get continuously stretched, allowing water films to be located at grain boundaries. This configuration would modify and even overprint the maximum c-axis-dependent orientation and the magnitude of seismic anisotropy.

58 GEOSCIENCES↗
DOE OSTI2019

Diffusion behaviors between metallic fuel alloys with Pd addition and Fe

Fission product lanthanides (Lns) in metallic fuel is the primary cause of fuel-cladding chemical interaction (FCCI). Palladium (Pd) is being explored as a potential additive to reduce or mitigate FCCI by forming stable Pd-Ln compounds. The current study is an investigation of diffusion behaviors between UZrPd, UZrPdLn, UPuZrPd, and UPuZrPdLn alloys (Ln = 53Nd-25Ce-16Pr-6La wt. %) and iron (Fe). Diffusion couple tests were performed followed by microstructural analysis using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). It is found that the diffusion of Fe into the fuel is reduced by PdZr2 precipitates randomly dispersed throughout the fuel matrix. Ln-Pd compounds form in UZrPdLn alloys, and (Ln,Pu)Pd forms in the UPuZrPdLn alloy. In both diffusion couples with Ln, small amounts of Lns are diffusing into the Fe. This could be due to small amounts of dissolved Lns in the precipitates, or could be due to the Ln-Pd compounds decomposing. In either case, diffusion caused by Lns is greatly reduced.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Using snowflake surface-area-to-volume ratio to model and interpret snowfall triple-frequency radar signatures

Abstract. The snowflake microstructure determines the microwave scattering properties of individual snowflakes and has a strong impact on snowfall radar signatures. In this study, individual snowflakes are represented by collections of randomly distributed ice spheres where the size and number of the constituent ice spheres are specified by the snowflake mass and surface-area-to-volume ratio (SAV) and the bounding volume of each ice sphere collection is given by the snowflake maximum dimension. Radar backscatter cross sections for the ice sphere collections are calculated at X-, Ku-, Ka-, and W-band frequencies and then used to model triple-frequency radar signatures for exponential snowflake size distributions (SSDs). Additionally, snowflake complexity values obtained from high-resolution multi-view snowflake images are used as an indicator of snowflake SAV to derive snowfall triple-frequency radar signatures. The modeled snowfall triple-frequency radar signatures cover a wide range of triple-frequency signatures that were previously determined from radar reflectivity measurements and illustrate characteristic differences related to snow type, quantified through snowflake SAV, and snowflake size. The results show high sensitivity to snowflake SAV and SSD maximum size but are generally less affected by uncertainties in the parameterization of snowflake mass, indicating the importance of snowflake SAV for the interpretation of snowfall triple-frequency radar signatures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Microstructural and rheological training and memory of nanocolloidal soft glasses under cyclic shear

An intrinsic feature of disordered and out-of-equilibrium materials, such as glasses, is the dependence of their properties on their history. An important example is rheological memory, in which disordered solids obtain properties based on their deformation history. Here, in this study, we employ x-ray photon correlation spectroscopy with in situ rheometry to characterize memory formation in a nanocolloidal soft glass due to cyclic shear. During a cycle, particles undergo irreversible displacements composed of a combination of shear-induced diffusion and heterogeneous, residual strain fields. At lower shear amplitudes, the displacements resemble a random walk in which the directions in each cycle are independent of those in preceding cycles, while at high amplitude, the irreversible displacements in consecutive cycles become correlated. The magnitudes of the displacements decrease with each cycle before reaching a steady state where the microstructure has been trained to achieve enhanced reversibility even at shear amplitudes well above yielding and despite the presence of thermal fluctuations. At amplitudes below and near yielding, these decreases are monotonic, while well above yielding, they are nonmonotonic, suggesting evidence of shear banding. Accompanying this microstructural training are corresponding decreases in the dissipation during each cycle and the magnitude of the residual stress toward steady-state values. Memory of the training is revealed by measurements in which the amplitude of the shear is changed after steady state is reached. The magnitude of the particle displacements, as well as the dissipation and the change in residual stress, vary nonmonotonically with the new shear amplitude, having minima near the training amplitude, thereby revealing correlated microscopic and macroscopic signatures of memory.

Chen, Yihao [Johns Hopkins Univ., Baltimore, MD (U↗
DOE OSTI2018

Fatigue Properties of Ti-6Al-4V Titanium Alloy Friction Stir Welding Joint

Friction stir welding was used to consolidate 2-mm-thick Ti-6Al-4V titanium alloy sheets, and the static and fatigue properties of the joint were investigated. The results reveal that uniform microhardness distribution of the nugget zone (NZ) after post-weld heat treatment was associated with the uniform equiaxed microstructure of the NZ. The joint fatigue limit predicted by the S–N curve reached 640.84 MPa, up to 64.76% of joint tensile strength. Fatigue specimens fractured at the transition zone between the base material and NZ, and the positions of fatigue crack initiation sites were relatively random. The fracture surface of the fatigue crack propagation region was composed of radial strips and striations, and numerous dimples were observed on the final fast fracture surface.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Friction stir welding of multi-walled carbon nanotubes reinforced Al matrix composites

Highlights: • Al/MWCNT composites were successfully welded using friction stir welding. • After FSW, the composites possessed an excellent balance of mechanical properties. • High tensile strength and elongation over BM owing to MWCNTs after FSW. • Microstructures were investigated according to MWCNT contents and FSW conditions. - Abstract: In this study, we prepared composites between Al and multi-walled carbon nanotubes (MWCNTs) using the friction stir welding (FSW) method and investigated their microstructural evolution and mechanical properties by controlling the amount of MWCNT (1 and 3 vol%) and the plunging load (400 and 600 kg) used. After the FSW process, MWCNT showed slight coarsening of grain with random shear textures and accumulated dislocations; the differences obtained by varying the plunging load and MWCNT amount were insignificant. The friction-stir welded composite obtained using 3 vol% MWCNT and a plunging load of 600 kg possessed two-times better balance between strength and ductility than the base metal, due to the presence of both MWCNTs and the partially decomposed Al{sub 4}C{sub 3} in the composite.

36 MATERIALS SCIENCE↗