Non-destructive Mapping Research Articles

Non-destructive orientation mapping of die-attach lead-free solder

Non-destructive orientation mapping of die-attach lead-free solder

Strain mapping in amorphous germanium thin films with scanning reflectance anisotropy microscopy

Strain imaging is a critical aspect in the design and characterization of opto-electronics, microelectronics, flexible electronics, and on-chip photonics. However, strain mapping techniques are often material specific and strain measurements in amorphous materials remain a challenge. Here, we demonstrate strain mapping and optical characterization of an amorphous semiconductor using scanning reflectance anisotropy microscopy. Using reflection anisotropy spectroscopy and finite element simulations on evaporated amorphous germanium films, we showcase the strain sensitivity of the ellipsometric parameters. We demonstrate nondestructive mapping for simple and complex strain states in amorphous systems. The sub-degree phase and amplitude sensitivity of the microscope is able to determine strain states on the order of 10−3.

Integration of line-field confocal optical coherence tomography and in situ microenvironmental mapping to investigate the living microenvironment of reconstructed human skin and melanoma models

BackgroundIn tissue engineering, real-time monitoring of tumors and of the dynamics of the microenvironment within in vitro models has traditionally been hindered by the need to harvest the cultures to obtain material to analyze. Line-field confocal optical coherence tomography (LC-OCT) has proven to be useful in evaluating in vivo skin conditions, including melanoma, by capturing dynamic, three-dimensional (3D) information without the need for invasive procedures, such as biopsies. Additionally, the M-Duo Technology® developed by IMcoMET presents a unique opportunity for continuous in situ biomarker sampling, providing insights into local cellular behavior and interactions. ObjectiveThis study aimed to validate the non-destructive mapping capabilities of two advanced methodologies (LC-OCT by DAMAE Medical and M-Duo Technology® by IMcoMET) to investigate the living microenvironment of in vitro reconstructed human skin (RhS) and melanoma-RhS (Mel-RhS). MethodsLC-OCT and M-Duo Technology® were compared to conventional analysis of the RhS and Mel-RhS microenvironments. ResultsLC-OCT successfully visualized the distinct layers of the epidermis and tumor structures within the Mel-RhS, identifying keratinocytes, melanocytes, tumor nests, and fibroblasts. The M-Duo Technology® revealed differences in in situ cytokine (IL-6) and chemokine (CCL2, CXCL10, and IL-8) secretion between Mel-RhS and the control RhS. Notably, such differences were not detected through conventional investigation of secreted proteins in culture supernatants. ConclusionThe combination of LC-OCT's high-resolution imaging and M-Duo Technology®’s in situ microenvironmental mapping has the potential to provide a synergistic platform for non-invasive, real-time analysis, allowing for prolonged observation of processes within Mel-RhS models without the need for culture disruption.

Gradient residual strain determination of surface impacted railway S38C axles by neutron Bragg-edge transmission imaging

Non-destructive and quantitative mapping of gradient residual strain distribution in surface-hardened railway S38C axles could provide a positive reference for determining service lifetime and maintenance strategy. To tackle this concern, time-of-flight neutron Bragg-edge transmission imaging was employed by real axle samples with and without impacted crater. A novel and simple procedure to formulate the residual strain field was also developed in this work, with the transmission batch code in Appendix A. By mapping the global two- dimensional residual strains, it can be verified that the residual strains into the axle are uniformly distributed in the hoop direction. Subsequently, it was revealed that the axial and hoop residual strains, respectively in the cylinder and the long strip samples prepared from a real S38C hollow axle, indicated a gradient evolution distribution with a depth of ∼ 8 mm, covering a range of −5500 ∼ 1000 με for axial strains and −6500 ∼ 1000 με for hoop strains. More importantly, the maximum compressive lattice strain of the cylinder sample was increased by 15.61 %, and 22.35 % at the impacting speeds of 100, and 125 m/s, respectively; and that of the long strip sample increased by 29.17 %, and 43.70 %, respectively. It can thus be concluded that lattice strains have redistributed around the impact crater, demonstrating the local alteration of the residual strain field. These new findings suggest the localized variation in residual strains should be taken into account while evaluating the service damage evolution of railway axles, especially those affected by high-speed impacts during operation.

Comparative Study of Nondestructive Mapping of Conformal-Coating Thickness on Microelectronics by Terahertz Time-of-Flight Tomography

Comparative Study of Nondestructive Mapping of Conformal-Coating Thickness on Microelectronics by Terahertz Time-of-Flight Tomography

Non-destructive mapping of electrical properties of semi-insulating compound semiconductor wafers using terahertz time-domain spectroscopy

With an increasing demand for THz electronics applications, it is essential to obtain the electrical properties of semiconductor materials used in their fabrication. This study presents an approach to estimate the electrical properties of semi-insulating compound semiconductors using terahertz time-domain spectroscopy (THz-TDS). By employing THz-TDS in transmission mode, the resistivity and carrier concentration of semi-insulating Silicon Carbide (SiC) and Indium Phosphide (InP) wafers are non-destructively measured. The study utilizes the simplified Drude model and the Nelder-Mead algorithm to estimate the electrical properties from the THz-TDS transmission (S21) measurement data. The resistivity values of the SiC and InP samples, (1.42 ± 0.15) × 105 Ω cm and (3.0 ± 0.1) × 107 Ω cm, respectively, are in accordance with the manufacturer specifications. Moreover, the feasibility of non-destructive mapping of the electrical properties of the wafers is demonstrated, offering a novel tomographic inspection approach for online monitoring. This technique holds significant promise for enhancing production yields in the semiconductor industry.

Laboratory-based non-destructive 3D spatial mapping of phases and orientations

Laboratory-based non-destructive 3D spatial mapping of phases and orientations

Assessment of Biodiversity Richness and Carbon Sequestration Potential in Institutional Campus – A Case Study

Within an increasingly sprawling city, it is almost far-fetched to identify a large patch of potential habitat for urban ecological conservation. In such cases, the institutional campuses become vital areas for such interventions, which can then be harmonized to realize the seemingly unreal idea of urban forest development. These institutional ecological patches remain a home to a number of species. Thus, it retains the urban biodiversity amidst the anthropogenic urban activities. The campus of Thiagarajar College of Engineering, Madurai, is one such institutional urban forest that sprawls across 143 acres of land, surrounded by the Thiruparankundram hills and the lake which support the species’ richness and their composition. This urban forest is considered for investigation in current study. The researchers followed the non-destructive sampling mapping technique and used a measuring tape to conduct the biodiversity assessment of trees and animal species. Further, the authenticity of the biological taxonomy was also validated using an open-source application, ‘Plant Net’. The results found that this urban forest harbours a total of 40 different species of trees, with Azadirachta indica being the dominant tree species, followed by Saraca asoca, the co-dominant. The total carbon sequestered by this urban forest was then calculated using the formula W= (AGB+BGB) *0.5*3.6663. The results suggest the implementation of appropriate management strategies by providing a diverse set of essential plant databases for the institutional campuses, which in turn can benefit the management of urban ecosystems. The study emphasizes the importance of diverse species in providing ecological services such as biodiversity conservation, improved air quality, and micro-climate regulation, thus escalating the institutional urban forests to contribute towards a harmonious urban ecological development.

Soft body reconstruction of a reptile fossil by the nondestructive elemental mapping with a newly designed XRF

AbstractVertebrate fossils usually consist only of mineralized skeletons and rarely preserve soft body parts. However, the buried soft body releases the degraded material into the surrounding sediments. The degraded material can be preserved as invisible signals of some chemicals or authigenic minerals, which can be revealed by the elemental distribution of the fossils' surface and their surrounding rock. As a method for surface elemental mapping, X‐ray fluorescence (XRF) measurement requires the samples to be ground and polished as a mirror‐like plane that keeps a stable distance of X‐ray source‐sample‐detector. This destructive pretreatment is undesirable for precious fossils. To rectify this problem, a nondestructive XRF for element mapping of the fossils' 3D surface is newly invented. The new equipment can follow the 3D shape model to keep the distance for every XRF scanned point. We performed the element mapping of Ca and Fe on the surface of a marine sauropterygian fossil (Keichousaurus hui) and its surrounding sediments, and found that the soft tissue around the thoracic cage is thicker than the abdomen. The abnormal elemental distribution on the area of the angular and surangular of the skull can be explained as unprofessionally prepared. In addition, this research found that elemental mapping revealed the invisible signals of the paleoenvironment around fossils and information for the reconstruction of soft‐tissue anatomy. We also give an example that based on the wide application of the “Internet of Things” and “Industrial Network,” the design and development of specialized equipment for paleontologists' requirements are going simple.

Quantifying multiple stain distributions in bioimaging by hyperspectral X-ray tomography

Chemical staining of biological specimens is commonly utilised to boost contrast in soft tissue structures, but unambiguous identification of staining location and distribution is difficult without confirmation of the elemental signature, especially for chemicals of similar density contrast. Hyperspectral X-ray computed tomography (XCT) enables the non-destructive identification, segmentation and mapping of elemental composition within a sample. With the availability of hundreds of narrow, high resolution (~ 1 keV) energy channels, the technique allows the simultaneous detection of multiple contrast agents across different tissue structures. Here we describe a hyperspectral imaging routine for distinguishing multiple chemical agents, regardless of contrast similarity. Using a set of elemental calibration phantoms, we perform a first instance of direct stain concentration measurement using spectral absorption edge markers. Applied to a set of double- and triple-stained biological specimens, the study analyses the extent of stain overlap and uptake regions for commonly used contrast markers. An improved understanding of stain concentration as a function of position, and the interaction between multiple stains, would help inform future studies on multi-staining procedures, as well as enable future exploration of heavy metal uptake across medical, agricultural and ecological fields.

Reconstruction algorithms for grain mapping by laboratory X-ray diffraction contrast tomography.

X-ray-based non-destructive 3D grain mapping techniques are well established at synchrotron facilities. To facilitate everyday access to grain mapping instruments, laboratory diffraction contrast tomography (LabDCT), using a laboratory-based conical polychromatic X-ray beam, has been developed and commercialized. Yet the currently available LabDCT grain reconstruction methods are either ill-suited for handling a large number of grains or require a commercial licence bound to a specific instrument. To promote the availability of LabDCT, grain reconstruction methods have been developed with multiple reconstruction algorithms based on both forward and back calculations. The different algorithms are presented in detail and their efficient implementation using parallel computing is described. The performance of different reconstruction methods is assessed on synthetic data. The code to implement all the described algorithms has been made publicly accessible with the intention of fostering the development of grain mapping techniques on widely available laboratory instruments.

UAV Multispectral Data: A Reliable Approach for Managing Phosphate-Solubilizing Bacteria in Common Bean

Remote sensing can offer stakeholders opportunities to make precise and accurate decisions on agricultural activities. For instance, farmers can exploit aircraft systems to acquire survey-level, high-resolution imagery data for crop and soil management. Therefore, the objective of this study was to analyze whether an unmanned aerial vehicle (UAV) allows for the assessment and monitoring of biofertilization of the common bean upon vegetation indices (VIs). The biological treatment of the legume crop included its inoculation with phosphate-solubilizing bacteria (PSB), namely Bacillus subtilis and B. megaterium. Indicators of photosynthetic performance, such as chlorophylls (a and b) and carotenoids, were measured from actively growing leaves to determine effectiveness. In addition, images were acquired in the field, both spatially and temporally, to establish functional relationships between biometric and computational features. Microorganisms manifested as growth-promoting agents to the crop as they significantly increased its quantities of light-harvesting pigments. VIs allowed for predicting their impact on photosynthetic performance, making them on-site markers of PSB. Therefore, this research can provide insights into the remote, non-destructive mapping of spectral changes in the common bean upon the application of PSB. Imagery data from UAV would enable producers to generate information on the crop to intervene in the field at the right time and place for improved utilization of biofertilizers.

Non-destructive mapping of stress and strain in soft thin films through sound waves

Measuring the in-plane mechanical stress in a taut membrane is challenging, especially if its material parameters are unknown or altered by the stress. Yet being able to measure the stress is of fundamental interest to basic research and practical applications that use soft membranes, from engineering to tissues. Here, we present a robust non-destructive technique to measure directly in-situ stress and strain in soft thin films without the need to calibrate material parameters. Our method relies on measuring the speed of elastic waves propagating in the film. Using optical coherence tomography, we verify our method experimentally for a stretched rubber membrane, a piece of cling film (about 10 μm thick), and the leather skin of a traditional Irish frame drum. We find that our stress predictions are highly accurate and anticipate that our technique could be useful in applications ranging from soft matter devices to biomaterial engineering and medical diagnosis.

Mechanical surface treatment studies by Bragg edge neutron imaging

Mechanical surface treatment technologies such as laser peening and cavitation peening require detailed characterization, including residual stress analysis, to optimize their processing parameters. Recent developments at neutron facilities allow non-destructive 2-dimensional residual strain mapping through Bragg edge imaging, which provides specific advantages over more established methods. The present work highlights the application of Bragg edge neutron imaging for the study of mechanical surface treatments, through determination of lattice spacing distributions by energy-resolved radiography. Through three different examples, the unique capabilities of the method are demonstrated, particularly for providing near surface residual strain maps within samples with complex geometries with relatively high spatial resolution. By providing a comparison with X-ray diffraction and neutron diffraction results, the present work emphasizes the potential of Bragg edge neutron imaging as a tool for surface treatment research.

Nondestructive and local mapping photoresponse of WSe2 by electrostatic force microscopy

We report a local mapping photoresponse of WSe2 using a second-harmonic (2w) channel based on nondestructive electrostatic force microscopy (EFM). The 2w signals resulting from interaction between WSe2 and EFM tip are intrinsically related to the electrical conductivity of WSe2. The photoresponse images and rise/decay time constants of WSe2 are obtained by local mapping 2w signals under illumination. We observe that the local photoresponse signals of WSe2 increase with the positive tip gate voltage while the WSe2 shows a p-type behavior in dark conditions We find that the reduced mobility of the photogenerated charge carriers resulting from the enhanced carrier scattering in the accumulation regime of WSe2 is responsible for the gate-dependent photoresponse behavior. Our results provide a deep understanding the intrinsic optoelectrical properties of WSe2 and contribute to the developments in the optoelectronic devices based on van der Waals layered materials.

Mapping of the mechanical response in Si/SiGe nanosheet device geometries

The performance of next-generation, nanoelectronic devices relies on a precise understanding of strain within the constituent materials. However, the increased flexibility inherent to these three-dimensional device geometries necessitates direct measurement of their deformation. Here we report synchrotron x-ray diffraction-based non-destructive nanoscale mapping of Si/SiGe nanosheets for gate-all-around structures. We identified two competing mechanisms at different length scales contributing to the deformation. One is consistent with the in-plane elastic relaxation due to the Ge lattice mismatch with the surrounding Si. The second is associated with the out-of-plane layering of the Si and SiGe regions at a length scale of film thickness. Complementary mechanical modeling corroborated the qualitative aspects of the deformation profiles observed across a variety of nanosheet sample widths. However, greater deformation is observed in the SiGe layers of the nanosheets than the predicted distributions. These insights could play a role in predicting carrier mobilities of future devices.

Upscaling aboveground biomass of larch (Larix olgensis Henry) plantations from field to satellite measurements: a comparison of individual tree-based and area-based approaches

ABSTRACT Currently, aboveground biomass (AGB) estimation primarily relies on an area-based approach (ABA), particularly at a large scale. With the advancement of individual tree detection techniques and the availability of multi-platform remotely sensed data, the individual tree-based approach (ITA) provides the potential of accurate and nondestructive fine AGB mapping. However, the performances of the two approaches on upscaling AGB from individual tree to stand level have not been thoroughly investigated. This study conducted the nondestructive AGB estimation using both ITA and ABA and compared the AGB estimates and their spatial uncertainties from an individual tree- to stand-level based on multi-platform LiDAR and Landsat 8 OLI imagery, taking Larix olgensis that is one of the most notable afforestation tree species in northeastern China as an example. Results showed that the point cloud segmentation (PCS) outperformed CHM-based individual tree crown delineation algorithms and obtained the highest accuracy of individual tree AGB estimate (R2 = 0.97, RMSE = 28.58 kg, rRMSE = 21.13%) for the dense larch plantations (about 1265 trees/ha). The plot-level AGB estimate aggregated by all detected trees and its uncertainty based on Monte Carlo simulation were 158.16 and 3.64 Mg·ha−1, respectively. The average pixel-level AGB of larch plantations in Maorshan Forest Farm estimated by ITA and ABA were similar (129.66 v.s 144.38 Mg·ha−1). ITA outperformed ABA in terms of pixel-level AGB accuracy and spatial uncertainty of pixel-level and stand-level AGB estimates. The overestimation of low AGB values, typical in ABA, was effectively eliminated by the ITA. The upscaling frameworks proposed in this study for AGB estimation and spatial uncertainty quantification based on ITA and ABA could be extended to other plantations or uncomplex forests. This study contributes to the accurate quantification of AGB and understanding of the uncertainties in the carbon stock of forest ecosystems at multi-scales.

Non-destructive analysis of plant physiological traits using hyperspectral imaging: A case study on drought stress

• The analysis of hyperspectral images for non-destructive visual mapping of early stress symptoms in plants. • The use of Machine Learning Regression algorithms to develop prediction models for water-stress related physiological traits. • The development of a data-driven spectral analysis method to quantify stress-related phenomena from regular growth dynamics in plants. • The validation of the data-driven method by a small-scale study of water-stress of maize plants in a high-throughput plant phenotyping platform setting Conventional methods to access plant physiological traits are based on destructive measurements by means of biochemical extraction or leaf clipping, thereby limiting the throughput capability. With advances in hyperspectral imaging sensor, fast, non-invasive and non-destructive measurements of a plant’s physiological status became feasible. In this work, a non-destructive method for the characterization of a plant’s status from hyperspectral images is presented. A supervised data-driven method based on Machine Learning Regression (MLR) algorithms was developed to generate prediction models of four targeted physiological traits: water potential, effective quantum yield of photosystem II, transpiration rate and stomatal conductance. Standard Normal Variate (SNV) transformed reflectance spectra were used as the input variables for building the regression model. Three MLR algorithms: Gaussian Process Regression (GPR), Kernel Ridge Regression (KRR), and Partial Least Squares Regression (PLSR) were explored as candidate methods for building the prediction model of the targeted physiological traits. Validation results show that the non-linear prediction models, developed based on the GPR algorithm produced the best estimation accuracy on all plant traits. The best prediction models were applied to a small-scale phenotyping experiment to study drought stress responses in maize plants. Results show that all estimated traits revealed a significant difference between plants under drought stress and normal growth dynamics as early as after 3 days of drought induction.

Macroscopic mapping of microscale fibers in freeform injection molded fiber-reinforced composites using X-ray scattering tensor tomography

Fiber-reinforced composites deliver lightweight but strong structures that are crucial in applications ranging from aerospace to the automotive industry. The advent of freeform injection molding has made the manufacturing of complex fiber-reinforced composites with full design freedom possible. Prediction of the mechanical properties, dictated by the local microfiber orientation, is essential for the performance characterization of fiber-reinforced composites. However, with conventional microtomography, the required microscale spatial resolution and the macroscopic field of view for full-size fiber-reinforced composite pieces cannot be effectively decoupled. X-ray scattering tensor tomography enables non-destructive macroscopic mapping of the local microfiber orientation as well as their degree of alignment. Recent advancements in X-ray optics have significantly increased the acquisition speed, making the tensor tomography attractive for industrial applications. Nonetheless, integration of the tensor tomography within production lines requires a flexible and robust implementation. In this work, we demonstrate the potential of X-ray scattering tensor tomography for industrial applications by characterizing the microstructure of a centimeter-sized industrially relevant freeform injection molding fiber-reinforced composite sample. We also show that the tensor tomography is compatible with robotic arms, which can position and orient objects in three dimensions with high flexibility and therefore are ideal sample manipulators for the tensor tomography in industrial settings. The results obtained with the robotic arm are compared to those obtained with the state-of-the-art 2-axis sample manipulation scheme. The retrieved information is highly consistent and shows agreement also with structure tensor analyses of conventional microtomography data taken at selected regions of the sample for additional validation.

Non-Destructive Spatial Mapping of Glycosaminoglycan Loss in Native and Degraded Articular Cartilage Using Confocal Raman Microspectroscopy.

Articular cartilage is a collagen-rich tissue that provides a smooth, lubricated surface for joints and is also responsible for load bearing during movements. The major components of cartilage are water, collagen, and proteoglycans. Osteoarthritis is a degenerative disease of articular cartilage, in which an early-stage indicator is the loss of proteoglycans from the collagen matrix. In this study, confocal Raman microspectroscopy was applied to study the degradation of articular cartilage, specifically focused on spatially mapping the loss of glycosaminoglycans (GAGs). Trypsin digestion was used as a model for cartilage degradation. Two different scanning geometries for confocal Raman mapping, cross-sectional and depth scans, were applied. The chondroitin sulfate coefficient maps derived from Raman spectra provide spatial distributions similar to histological staining for glycosaminoglycans. The depth scans, during which subsurface data were collected without sectioning the samples, can also generate spectra and GAG distributions consistent with Raman scans of the surface-to-bone cross sections. In native tissue, both scanning geometries demonstrated higher GAG content at the deeper zone beneath the articular surface and negligible GAG content after trypsin degradation. On partially digested samples, both scanning geometries detected an ∼100 μm layer of GAG depletion. Overall, this research provides a technique with high spatial resolution (25 μm pixel size) to measure cartilage degradation without tissue sections using confocal Raman microspectroscopy, laying a foundation for potential in vivo measurements and osteoarthritis diagnosis.