Non-destructive Mapping Research Articles

Effect of architecture and process on the ultrasonic mapping of hybrid additively manufactured materials

Hybrid additive manufacturing enables the creation of materials with functional microstructure and mechanical property patterns. While samples with functional patterns provide unique advantages in the overall performance of the material, they present a challenge for nondestructive evaluation. In particular, the nondestructive mapping of the properties imparted by hybrid AM processes is critical. In this work, hybrid 316 stainless steel samples are created using laser powder bed fusion (LPBF) with varying hybrid architectures and with a variety of hybrid processes. The ultrasonic responses of these samples, in terms of wave speed, attenuation, and backscatter amplitude, are evaluated for each architecture and process combination. These responses are compared with those from conventionally manufactured samples and traditional AM samples. This evaluation provides information on the sensitivity of ultrasonic responses to hybrid architecture and process, highlighting the potential of ultrasonic nondestructive methods for the characterization of hybrid AM components. [This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. 1610400. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.]

Non-destructive 3D orientational mapping of bone using diffractive X-ray tomography

Non-destructive 3D orientational mapping of bone using diffractive X-ray tomography

Deep learning for improving non-destructive grain mapping in 3D.

Laboratory X-ray diffraction contrast tomography (LabDCT) is a novel imaging technique for non-destructive 3D characterization of grain structures. An accurate grain reconstruction critically relies on precise segmentation of diffraction spots in the LabDCT images. The conventional method utilizing various filters generally satisfies segmentation of sharp spots in the images, thereby serving as a standard routine, but it also very often leads to over or under segmentation of spots, especially those with low signal-to-noise ratios and/or small sizes. The standard routine also requires a fine tuning of the filtering parameters. To overcome these challenges, a deep learning neural network is presented to efficiently and accurately clean the background noise, thereby easing the spot segmentation. The deep learning network is first trained with input images, synthesized using a forward simulation model for LabDCT in combination with a generic approach to extract features of experimental backgrounds. Then, the network is applied to remove the background noise from experimental images measured under different geometrical conditions for different samples. Comparisons of both processed images and grain reconstructions show that the deep learning method outperforms the standard routine, demonstrating significantly better grain mapping.

Toward In Situ Synchrotron Mapping of Crystal Selection Processes during Crystal Growth

Here, we present an automated and rapid method for nondestructive mapping of crystal grains in a rod-shaped sample. The approach was designed for application to in situ float-zone crystal growth ex...

A novel nanoindentation protocol to characterize surface free energy of superhydrophobic nanopatterned materials

Surface Free Energy (SFE) has become a relevant design parameter to produce materials and devices with controlled wettability. The non-destructive measurement of SFE in nanopatterned super-hydrophobic hard surfaces is a challenge in both research and industry since in most cases time-consuming contact angle measurements are not feasible. In this work, we present a novel nanoindentation based method for the measurement of pull-off adhesive forces by carefully controlling environmental and instrumentation issues. The method is found to measure SFE over five orders of magnitude, covering hydrophilic to super-hydrophobic surfaces, and has been validated with contact angle measurements. Its limitations and shortcomings are critically discussed, with a specific focus on the experimental issues that could affect the reliability and reproducibility of the results. Finally, the potential applications of the newly developed methodology include fast non-destructive mapping of SFE over heterogeneous surfaces with spatially controlled wettability.Graphic abstract

Optimizing laboratory X-ray diffraction contrast tomography for grain structure characterization of pure iron.

Laboratory diffraction contrast tomography (LabDCT) is a recently developed technique for 3D nondestructive grain mapping using a conical polychromatic beam from a laboratory-based X-ray source. The effects of experimental parameters, including accelerating voltage, exposure time and number of projections used for reconstruction, on the characterization of the 3D grain structure in an iron sample are quantified. The experiments were conducted using a commercial X-ray tomography system, ZEISS Xradia 520 Versa, equipped with a LabDCT module; and the data analysis was performed using the software package GrainMapper3D, which produces a 3D reconstruction from binarized 2D diffraction patterns. It is found that the exposure time directly affects the background noise level and thus the ability to distinguish weak spots of small grains from the background. With the assistance of forward simulations, it is found that spots from the first three strongest {hkl} families of a large grain can be seen with as few as 30-40 projections, which is sufficient for indexing the crystallographic orientation and resolving the grain shape with a reasonably high accuracy. It is also shown that the electron current is a more important factor than the accelerating voltage to be considered for optimizing the photon numbers with energies in the range of 20-60 keV. This energy range is the most important one for diffraction of common metals, e.g. iron and aluminium. Several suggestions for optimizing LabDCT experiments and 3D volume reconstruction are finally provided.

Non-destructive and fast method of mapping the distribution of the soluble solids content and pH in kiwifruit using object rotation near-infrared hyperspectral imaging approach

This work aimed to offer a non-destructive and fast approach to visualizing the soluble solids content (SSC) and acidity (pH) of the whole kiwifruit. Most of the visible-near-infrared spectral imaging techniques used in postharvest fruit and vegetables assessment exhibit issues related to the identification of the quality spatial distribution within intact samples, mainly due to sampling surface curvature effects. Here, a push-broom-type NIR hyperspectral imaging camera and a sample rotation stage were combined to scan entire kiwifruit surfaces. Then, key wavelengths in the range of 1002–2300 nm were extracted for constructing SSC and pH calibration models by partial least squares regression analysis. The resulting SSC prediction accuracy was sufficiently high: the coefficient of determination (R2cv) and the root mean square error (RMSEcv) of cross-validation set were 0.74 and 0.7 %, respectively. For pH, the R2cv and RMSEcv were 0.64 and 0.14, respectively. Finally, the SSC and pH 360˚mapping results surpassed earlier works in this area that they showed a distinct spatial distribution within each intact sample. It was concluded that the proposed object rotation hyperspectral imaging approach is promising for the non-destructive prediction mapping of SSC and pH in kiwifruit or other cylindrical-shaped samples.

A flexible and standalone forward simulation model for laboratory X-ray diffraction contrast tomography.

Laboratory X-ray diffraction contrast tomography (LabDCT) has recently been developed as a powerful technique for non-destructive mapping of grain microstructures in bulk materials. As the grain reconstruction relies on segmentation of diffraction spots, it is essential to understand the physics of the diffraction process and resolve all the spot features in detail. To this aim, a flexible and standalone forward simulation model has been developed to compute the diffraction projections from polycrystalline samples with any crystal structure. The accuracy of the forward simulation model is demonstrated by good agreements in grain orientations, boundary positions and shapes between a virtual input structure and that reconstructed based on the forward simulated diffraction projections of the input structure. Further experimental verification is made by comparisons of diffraction spots between simulations and experiments for a partially recrystallized Al sample, where a satisfactory agreement is found for the spot positions, sizes and intensities. Finally, applications of this model to analyze specific spot features are presented.

Non-destructive Mapping of Organosulfur of Source Rocks Using Energy Dispersive Spectroscopy and Back Scatter Electron

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Non-contact, non-destructive mapping of thermal diffusivity and surface acoustic wave speed using transient grating spectroscopy

We present new developments of the laser-induced transient grating spectroscopy (TGS) technique that enable the measurement of large area 2D maps of thermal diffusivity and surface acoustic wave speed. Additional capabilities include targeted measurements and the ability to accommodate samples with increased surface roughness. These new capabilities are demonstrated by recording large TGS maps of deuterium implanted tungsten, linear friction welded aerospace alloys, and high entropy alloys with a range of grain sizes. The results illustrate the ability to view the grain microstructure in elastically anisotropic samples and to detect anomalies in samples, for example, due to irradiation and previous measurements. They also point to the possibility of using TGS to quantify grain size at the surface of polycrystalline materials.

Fast and quantitative 2D and 3D orientation mapping using Raman microscopy

Non-destructive orientation mapping is an important characterization tool in materials science and geoscience for understanding and/or improving material properties based on their grain structure. Confocal Raman microscopy is a powerful non-destructive technique for chemical mapping of organic and inorganic materials. Here we demonstrate orientation mapping by means of Polarized Raman Microscopy (PRM). While the concept that PRM is sensitive to orientation changes is known, to our knowledge, an actual quantitative orientation mapping has never been presented before. Using a concept of ambiguity-free orientation determination analysis, we present fast and quantitative single-acquisition Raman-based orientation mapping by simultaneous registration of multiple Raman scattering spectra obtained at different polarizations. We demonstrate applications of this approach for two- and three-dimensional orientation mapping of a multigrain semiconductor, a pharmaceutical tablet formulation and a polycrystalline sapphire sample. This technique can potentially move traditional X-ray and electron diffraction type experiments into conventional optical laboratories.

Paper aging and degradation monitoring by the non-destructive two-dimensional micro-Raman mapping.

The aim of this research is the identification of main and common physical-chemical parameters which induce paper degradation. A simple protocol to monitor the quality and molecular structure of ancient papers under natural degradation processes was proposed. Two-dimensional micro-Raman mapping were carried out. Then, point to point, the changes of both the cellulose Raman signature and fluorescence signal intensity were analysed. Modern papers were artificially aged to simulate the natural degradation and a comparison with the trend found for the ancient paper was presented and discussed. Cellulose degradation involves different mechanisms such as dehydration, cleaving of cellulose-glycosidic bonds and glucopyranose rings oxidation, that induce a reduction in the polymerization degree. As shown by the changes of Raman and fluorescence signals and NMR relaxation times, the rate of each processes depends on the initial amount of glycosidic bonds in the cellulose amorphous and crystalline regions, respectively. All these informations are useful both to define procedures to restore old documents and also to preserve the quality of modern papers for a long-term time.

Full-field neutron microscopy based on refractive optics

Placing a compound refractive lens (CRL) as an objective in a neutron beam generates new possibilities for 2D and 3D nondestructive mapping of the structure, strain and magnetic domains within extended objects. A condenser setup is introduced that allows correction for the lateral chromatic aberration. More generally, for full-field microscopy the loss in performance caused by the chromatic aberration can be more than offset by introducing arrays of CRLs and exploiting the fact that the field of view can be much larger than the physical aperture of the CRL. Comments are made on the manufacture of such devices. The potential use is illustrated by comparisons between state-of-the-art instrumentation and suggested approaches for bright-field microscopy, small-angle neutron scattering microscopy, grain mapping and mapping of stresses. Options are discussed for depth-resolved imaging inspired by confocal light microscopy. Finally, experimental demonstrations are given of some of the basic properties of neutron full-field imaging for a single CRL.

A DATA CAPTURE FRAMEWORK FOR IMPROVING THE QUALITY OF SUBSURFACE UTILITY INFORMATION

Abstract. To plan, develop, and manage underground space and make informed decisions leading to desirable outcomes, planners, land administrators, and engineers need to make sense of the underground. A reliable digital twin of the underground – a realistic, digital representation of the physical world below the surface – is required. Utilities, consisting of the pipes, ducts, cables, manholes and other assets that provide electricity, gas, water, sewerage, and telecommunication services, make up a significant portion of the shallow layers of the subsurface. A lack of reliable information on subsurface utilities may potentially lead to poor decisions leading to undesirable outcomes, lengthy and costly planning and land administration processes, and lengthy, costly, and hazardous development processes. The advent of mobile 3D ground penetrating radar technology offers the promise of non-destructive mapping of existing subsurface utilities in a large area in a relatively short amount of time and could potentially be used to improve the reliability of available information. In this work, a small number of cases studies are described at evaluating the feasibility of a large area mapping approach for subsurface utilities. Based on the results of the studies, a data capture framework for the gradual improvement of the quality of information on existing subsurface utilities is proposed.

Modelling DUALEM-2 measured soil conductivity as a function of measuring depth to correlate with soil moisture content and potato tuber yield

Electromagnetic induction (EMI) is a non-destructive technique to measure the apparent electrical conductivity (ECa) of agricultural soils. It has become popular in precision agriculture applications to estimate crop yield from ECa. This study was conducted to relate ECa with soil moisture content (θv) and potato tuber yield under Prince Edward Island (PEI), Canada growing conditions and to establish a two-layered soil model for ECa. During year one, horizontal co-planar (HCP), perpendicular co-planar (PRP), and θv were measured with DUALEM-2 sensor and time domain reflectometry (TDR) probe and correlated with yield measured from 12 m2 grids at 40 locations in each of the two potato fields on PEI. During 2018, vertical electrical sounding was undertaken by raising the DUALEM-2 from ground-level at 0.2 m intervals to a height of 1.6 m to investigate variations in ECa with soil depth. A two-layered soil model was developed using generalized reduction gradients to determine the surficial conductivity and thickness, and subsurface conductivity. ECa variables (HCP and PRP), θv, and yield were significantly correlated and remained consistent throughout the study period, indicating their potential in predicting potato tuber yield. ECa in the fields varied both spatially and laterally with depth. GIS interpolated maps of a representative set of data for HCP and tuber yield (2017 data) showed structured spatial patterns and thus feasibility for delineating management zones. Further studies should examine the potato root zone (0.15–0.3 m) ECa specifically for developing higher layered models, which may be useful for accurate prediction of tuber yield. Non-destructive and accurate yield mapping using DUALEM-2 sensor combined with mathematical modelling of soil ECa layering has potential for use in developing management zones in potato fields.

Single Rare-Earth Ions as Atomic-Scale Probes in Ultrascaled Transistors.

Continued scaling of semiconductor devices has driven information technology into vastly diverse applications. The performance of ultrascaled transistors is strongly influenced by local electric field and strain. As the size of these devices approaches fundamental limits, it is imperative to develop characterization techniques with nanometer resolution and three-dimensional (3D) mapping capabilities for device optimization. Here, we report on the use of single erbium (Er) ions as atomic probes for the electric field and strain in a silicon ultrascaled transistor. Stark shifts on the Er3+ spectra induced by both the overall electric field and the local charge environment are observed. Changes in strain smaller than 3 × 10-6 are detected, which is around 2 orders of magnitude more sensitive than the standard techniques used in the semiconductor industry. These results open new possibilities for 3D mapping of the local strain and electric field in the channel of ultrascaled transistors.

X-ray fluorescence mapping as a first-hand tool in disseminated ore assessment: sandstone-hosted U–Zr mineralization

Analytical capabilities of X-ray fluorescence for 2-dimensional elemental analysis were tested on worldwide-unique sandstone-hosted U–Zr mineralization (Bohemian Cretaceous Basin, Czech Republic), and combined with measured spectral data. The applied approach was aimed at the detection of uranium and zirconium, visualization of their distribution across mineralized lithological units and description of their relationships with associated elements (As, Fe, Nb, Pb, Sr, Ti). The studied samples were low-grade uranium-bearing sediments. Experimental work employed laboratory 2D scanning X-ray fluorescence analyzer with the gold target Mini-X X-ray tube. Maps of U–Zr and other identified elements demonstrated their patchy distribution and a frequent association of the elements with mineral fillings (clay matrix, organic matter or Fe sulfides). A correlation-based analysis was used to verify geochemical coherence between the measured elements. This showed an extremely strong linear dependence (R ≥ 0.90) between U and Zr. In addition, a strong correlation (R ≥ 0.85) between U–Zr and some associated elements (As, Nb ± Fe, Pb, Sr) was confirmed. The efficiency and the limits of X-ray fluorescence mapping were tested by comparison with high-resolution techniques. Non-destructive mapping of large natural samples provided relevant data for further mineralogical study with respect to rapid pre-concentration of the ore material.

Cross Sectional Mapping of Nano-Mechanical Properties of Composite Electrodes for Lithium Ion Batteries Using Bimodal Mode Atomic Force Microscopy

Lithium-ion batteries (LIBs) have been widely used for various applications including portable devices and electric vehicles. Improvement of the cyclability and capacity is an important challenge. In the manufacturing process, active materials, conductive additives and binders are mixed in a solvent at a certain ratio and the slurry is casted, dried and pressed on a metallic foil current collector to yield a composite film. The composite films are assembled together with an electrolyte solution and a separator in coin or laminate cells. The packing density and mechanical strength of each material are important parameters for the cell performance because the volume expansion and resulting mechanical stress may cause a destruction of the electrical connections between binders, current collectors and the active materials during the charge/discharge processes. Young's modulus is one of the most important mechanical properties because it is an indicator of the mechanical strain in a material under a certain amount of stress. Nanoindentation has been used to measure the Young's moduli of various materials. However, it has a few restrictions as follows: (i) sample surface has to be destructed in nanoindentation and (ii) it has a limited spatial resolution, typically a few micrometers, due to the size of the disruption. Although recent atomic force microscopy (AFM) techniques allow non-destructive and high-resolution Young's modulus mapping by measuring force curves at each point using relatively weak force of<100 nN, this method is not applicable for stiff materials with modulus larger than 100 GPa because their sample deformation is too small to be detected by the cantilever deflection. Here, a newly developed technique, bimodal AFM that allows nanoscale mechanical mapping for a wide range of Young's modulus from 0.1 to 200 GPa in a non-destructive manner, was applied to LiCoO2-based positive and graphite-based negative composite electrodes before and after the charge-discharge cycles in a coin cell for a demonstration. Reference: H. Sakai, Y. Taniguchi, K. Uosaki, T. Masuda, “Quantitative cross-sectional mapping of nanomechanical properties of composite films for lithium ion batteries using bimodal mode atomic force microscopy”, 2019, 413, 29-33.

High Resolution Mapping of Orientation and Strain Gradients in Metals by Synchrotron 3D X-ray Laue Microdiffraction

Synchrotron 3D X-ray Laue microdiffraction, available at beamline 34-ID-E at Advanced Photon Source in Argonne National Laboratory, is a powerful tool for 3D non-destructive mapping of local orientations and strains at sub-micron scale in the bulk. With this technique, it is possible to study local residual stresses developed during manufacturing or while in service due to interactions between, for example, different phases and/or grains with different orientations in materials containing multiple or single phase(s). Such information is essential for understanding mechanical properties and designing advanced materials, but is largely non-existent in the current generation of materials models. In the present paper, the principle and experimental set-up of the 3D microdiffraction are introduced, followed by a description of a method for quantification of the local plastic deformation based on high-angular-resolution orientation maps. The quantification of local residual stresses in two model materials, ductile cast iron (two phases) and partially recrystallized pure nickel (single phase), using 3D microdiffraction will then be presented. The results show that 3D microdiffraction is important for understanding the origin of local residual stresses and to relate them to the microstructural evolution. Finally, the limitations of the 3D microdiffraction on the current generation synchrotron source and new possibilities after the synchrotron upgrade are discussed.

Non-Destructive Reflectance Mapping of Collagen Fiber Alignment in Heart Valve Leaflets.

Collagen fibers are the primary structural elements that define many soft-tissue structure and mechanical function relationships, so that quantification of collagen organization is essential to many disciplines. Current tissue-level collagen fiber imaging techniques remain limited in their ability to quantify fiber organization at macroscopic spatial scales and multiple time points, especially in a non-contacting manner, requiring no modifications to the tissue, and in near real-time. Our group has previously developed polarized spatial frequency domain imaging (pSFDI), a reflectance imaging technique that rapidly and non-destructively quantifies planar collagen fiber orientation in superficial layers of soft tissues over large fields-of-view. In this current work, we extend the light scattering models and image processing techniques to extract a critical measure of the degree of collagen fiber alignment, the normalized orientation index (NOI), directly from pSFDI data. Electrospun fiber samples with architectures similar to many collagenous soft tissues and known NOI were used for validation. An inverse model was then used to extract NOI from pSFDI measurements of aortic heart valve leaflets and clearly demonstrated changes in degree of fiber alignment between opposing sides of the sample. These results show that our model was capable of extracting absolute measures of degree of fiber alignment in superficial layers of heart valve leaflets with only general a priori knowledge of fiber properties, providing a novel approach to rapid, non-destructive study of microstructure in heart valve leaflets using a reflectance geometry.