Three-dimensional grain resolved strain mapping using laboratory X-ray diffraction contrast tomography: theoretical analysis

Laboratory diffraction contrast tomography (LabDCT) is a recently developed technique to map crystallographic orientations of polycrystalline samples in three dimensions non-destructively using a laboratory X-ray source. In this work, a new theoretical procedure, named LabXRS, expanding LabDCT to include mapping of the deviatoric strain tensors on the grain scale, is proposed and validated using simulated data. For the validation, the geometries investigated include a typical near-field LabDCT setup utilizing Laue focusing with equal source-to-sample and sample-to-detector distances of 14 mm, a magnified setup where the sample-to-detector distance is increased to 200 mm, a far-field Laue focusing setup where the source-to-sample distance is also increased to 200 mm, and a near-field setup with a source-to-sample distance of 200 mm. The strain resolution is found to be in the range of 1–5 × 10−4, depending on the geometry of the experiment. The effects of other experimental parameters, including pixel binning, number of projections and imaging noise, as well as microstructural parameters, including grain position, grain size and grain orientation, on the strain resolution are examined. The dependencies of these parameters, as well as the implications for practical experiments, are discussed.

Precise strain mapping of nano-twinned axial ZnTe/CdTe hetero-nanowires by scanning nanobeam electron diffraction

The occurrence of strain is inevitable for the growth of lattice mismatched heterostructures. It affects greatly the mechanical, electrical and optical properties of nano-objects. It is also the case for nanowires which are characterized by a high surface to volume ratio. Thus, the knowledge of the strain distribution in nano-objects is critically important for their implementation into devices. This paper presents an experimental data for II-VI semiconductor system. Scanning nanobeam electron diffraction strain mapping technique for hetero-nanowires characterized by a large lattice mismatch (>6% in the case of CdTe/ZnTe) and containing segments with nano-twins has been described. The spatial resolution of about 2 nm is 10 times better than obtained in synchrotron nanobeam systems. The proposed approach allows us to overcome the difficulties related to nanowire thickness variations during the acquisition of the nano-beam electron diffraction data. In addition, the choice of optimal parameters used for the acquisition of nano-beam diffraction data for strain mapping has been discussed. The knowledge of the strain distribution enables, in our particular case, the improvement of the growth model of extremely strained axial nanowires synthetized by vapor-liquid solid growth mechanism. However, our method can be applied for the strain mapping in nanowire heterostructures grown by any other method.

Direct pixel to pixel principal strain mapping from tagging MRI using end to end deep convolutional neural network (DeepStrain)

Regional soft tissue mechanical strain offers crucial insights into tissue's mechanical function and vital indicators for different related disorders. Tagging magnetic resonance imaging (tMRI) has been the standard method for assessing the mechanical characteristics of organs such as the heart, the liver, and the brain. However, constructing accurate artifact-free pixelwise strain maps at the native resolution of the tagged images has for decades been a challenging unsolved task. In this work, we developed an end-to-end deep-learning framework for pixel-to-pixel mapping of the two-dimensional Eulerian principal strains $$\varvec{{\varepsilon }}_{\boldsymbol{p1}}$$ ε p 1 and $$\varvec{{\varepsilon }}_{\boldsymbol{p2}}$$ ε p 2 directly from 1-1 spatial modulation of magnetization (SPAMM) tMRI at native image resolution using convolutional neural network (CNN). Four different deep learning conditional generative adversarial network (cGAN) approaches were examined. Validations were performed using Monte Carlo computational model simulations, and in-vivo datasets, and compared to the harmonic phase (HARP) method, a conventional and validated method for tMRI analysis, with six different filter settings. Principal strain maps of Monte Carlo tMRI simulations with various anatomical, functional, and imaging parameters demonstrate artifact-free solid agreements with the corresponding ground-truth maps. Correlations with the ground-truth strain maps were R = 0.90 and 0.92 for the best-proposed cGAN approach compared to R = 0.12 and 0.73 for the best HARP method for $$\varvec{{\varepsilon }}_{\boldsymbol{p1}}$$ ε p 1 and $$\varvec{{\varepsilon }}_{\boldsymbol{p2}}$$ ε p 2 , respectively. The proposed cGAN approach's error was substantially lower than the error in the best HARP method at all strain ranges. In-vivo results are presented for both healthy subjects and patients with cardiac conditions (Pulmonary Hypertension). Strain maps, obtained directly from their corresponding tagged MR images, depict for the first time anatomical, functional, and temporal details at pixelwise native high resolution with unprecedented clarity. This work demonstrates the feasibility of using the deep learning cGAN for direct myocardial and liver Eulerian strain mapping from tMRI at native image resolution with minimal artifacts.

Prediction of load requirement and instabilities during end forming of friction stir processed AA 6063-T6 thin-walled tubes

PurposeThe current work aims to propose a finite element (FE) simulation methodology to predict the formability of friction stir processed (FSPed) tubes by end forming. Moreover, a strain mapping method is also presented to predict the end forming instabilities.Design/methodology/approachIn this work, FE simulation of end forming of raw tubes and FSPed AA6063-T6 tubes are done using Abaqus (explicit) incorporating anisotropic properties of the raw tube and FSPed zone. Actual thickness of the FSPed zone is also implemented. Expansion, reduction and beading are the end forming operations considered. Load requirement and instabilities are predicted. A new method “strain mapping method” is followed to predict the failure instabilities in expansion and beading, while during reduction, wrinkling is predicted by FE simulations. Lab scale experiments on FSP and end forming are done for validation at various rotational speeds.FindingsResults reveal that in the case of expansion and reduction of FSPed tubes, forming load predictions are accurate, while in beading, after initiation of bead, predictions are not accurate. Experimental observation on the type of instability is consistently predicted during numerical simulations. Prediction of displacement at failure by strain mapping method is encouraging in most of the cases including those that are FSPed. Hence, it is suggested that the method can be utilized to evaluate the onset of failure during tube expansion and beading.Originality/valueFE simulation methodology including anisotropic properties of raw tube and FSPed tubes is proposed, which is not attempted until now even for normal tubes. Strain mapping method is easy to implement for instability predictions, which is done usually by failure theories and forming limit diagram.

Strain Characterization in Two-Dimensional Crystals

Two-dimensional (2D) crystals provides a material platform to explore the physics and chemistry at the single-atom scale, where surface characterization techniques can be applied straightforwardly. Recently there have been emerging interests in engineering materials through structural deformation or transformation. The strain field offers crucial information of lattice distortion and phase transformation in the native state or under external perturbation. Example problems with significance in science and engineering include the role of defects and dislocations in modulating material behaviors, and the process of fracture, where remarkable strain is built up in a local region, leading to the breakdown of materials. Strain is well defined in the continuum limit to measure the deformation, which can be alternatively calculated from the arrangement of atoms in discrete lattices through methods such as geometrical phase analysis from transmission electron imaging, bond distortion or virial stress from atomic structures obtained from molecular simulations. In this paper, we assess the accuracy of these methods in quantifying the strain field in 2D crystals through a number of examples, with a focus on their localized features at material imperfections. The sources of errors are discussed, providing a reference for reliable strain mapping.