Scanning Apparatus Research Articles

When Wetting Spills into Formation: Using Acoustics to Probe Electrolyte Dynamics in Lithium Ion Batteries

Wetting is a critical step of lithium-ion battery manufacturing. Following electrolyte filling and sealing, the electrolyte percolates through the porous matrix of the electrodes to encapsulate and penetrate the active particles. This impregnation facilitates necessary ionic conductivity and passivation on formation, resulting in maximum capacity retention during cycling. Unfortunately, incumbent electrochemical techniques fail to fully elucidate this process, particularly in multilayered cells. In this work, we leverage acoustics to demonstrate that the wetting process is not simply a function of thermotemporal conditions but invariably continues into the formation cycles. In particular, transmitted acoustic signal energy is shown to be a function of wetting and a predictor for subsequent cycling performance. The spatial extent of wetting is probed using a purpose-built acoustic scanning apparatus, and a high-throughput fixed-location jig yields a statistical distribution for multiple cells under various wetting and formation conditions. These insights indicate that the two-step pre-cycling conditions should not be considered two separate processes but rather intimately entangled.

Accreditation of in-abattoir Dual Energy X-ray Absorptiometry scanning apparatus to predict lamb carcass composition in Australia

Dual Energy X-ray Absorptiometry (DXA) scanners operating at abattoir processing speeds are currently installed in six sheep meat abattoirs around Australia, predicting carcass composition as estimates of computed tomography (CT) determined fat %, lean %, and bone %. This study tested an updated bone-detection algorithm for these DXA scanners. This algorithm improved the precision of prediction for carcass fat% and lean%, but most notably for bone % (R2 = 0.92, RMSE = 0.61 %), compared to the previous algorithm (R2 = 0.51, RMSE = 1.57 %). This was due to improved allocation of bone-containing pixels, resulting from the inclusion of tissue thickness in the bone-detection equation. In a second experiment, the predictions from this new algorithm, along with an automated phantom calibration technique, were assessed relative to their ability to meet the AUS-MEAT accreditation accuracy standards required for predicting CT determined carcass fat%, lean%, and bone%. The DXA met these standards for predicting fat % (range 10.9 % - 37.1 %), lean % (range 49.0 % - 66.2 %), and bone % (range 11.6 % - 25.0 %), across three weight bands of light carcasses (<22 kg), mid-weight carcasses (22-28 kg), and heavy carcasses (>28 kg). This work allowed for the accreditation of DXA, enabling its predictions of carcass composition to be used for trading sheep carcasses in Australia. The accuracy of these predictions far exceed those provided by the historical industry measure of GR tissue depth, and hot carcass weight.

Inline edge illumination X-ray phase contrast imaging through mask misalignment.

X-ray imaging is becoming more commonplace for inline industrial inspection, where a sample placed on a conveyor belt is translated through a scanning setup. However, the conventional X-ray attenuation contrast is often insufficient to characterize soft materials such as polymers and carbon reinforced components. Edge illumination (EI) is an X-ray phase contrast imaging technique that provides complementary differential phase and dark field contrasts, next to attenuation contrast. Combining multiple of these contrasts has been shown to improve industrial defect detection tasks. Unfortunately, conventional EI imaging is incompatible with an inline setup, as it requires moving part of the setup during acquisitions, while for inline scanning objects translate through a fixed inspection setup. Current solutions require either limiting the number of retrieved contrasts, or acquiring dedicated hardware. In this work, we demonstrate a method of inline EI imaging that does not limit the number of retrieved contrasts and does not require any new hardware. The method is validated through both simulation and experiment, demonstrating high flexibility and possible noise reduction, while successfully retrieving all three EI contrasts.

Stylize My Wrinkles: Bridging the Gap from Simulation to Reality

AbstractModeling realistic human skin with pores and wrinkles down to the milli‐ and micrometer resolution is a challenging task. Prior work showed that such micro geometry can be efficiently generated through simulation methods, or in specialized cases via 3D scanning of real skin. Simulation methods allow to highly customize the wrinkles on the face, but can lead to a synthetic look. Scanning methods can lead to a more organic look for the micro details, however these methods are only applicable to small skin patches due to the required image resolution. In this work we aim to overcome the gap between synthetic simulation and real skin scanning, by proposing a method that can be applied to large skin regions (e.g. an entire face) with the controllability of simulation and the organic look of real micro details. Our method is based on style transfer at its core, where we use scanned displacement maps of real skin patches as style images and displacement maps from an artist‐friendly simulation method as content images. We build a library of displacement maps as style images by employing a simplified scanning setup that can capture high‐resolution patches of real skin. To create the content component for the style transfer and to facilitate parameter‐tuning for the simulation, we design a library of preset parameter values depicting different skin types, and present a new method to fit the simulation parameters to scanned skin patches. This allows fully‐automatic parameter generation, interpolation and stylization across entire faces. We evaluate our method by generating realistic skin micro details for various subjects of different ages and genders, and demonstrate that our approach achieves a more organic and natural look than simulation alone.

A terahertz meta-sensor array for 2D strain mapping

Large-scale stretchable strain sensor arrays capable of mapping two-dimensional strain distributions have gained interest for applications as wearable devices and relating to the Internet of Things. However, existing strain sensor arrays are usually unable to achieve accurate directional recognition and experience a trade-off between high sensing resolution and large area detection. Here, based on classical Mie resonance, we report a flexible meta-sensor array that can detect the in-plane direction and magnitude of preloaded strains by referencing a dynamically transmitted terahertz (THz) signal. By building a one-to-one correspondence between the intrinsic electrical/magnetic dipole resonance frequency and the horizontal/perpendicular tension level, arbitrary strain information across the meta-sensor array is accurately detected and quantified using a THz scanning setup. Particularly, with a simple preparation process of micro template-assisted assembly, this meta-sensor array offers ultrahigh sensor density (~11.1 cm−2) and has been seamlessly extended to a record-breaking size (110 × 130 mm2), demonstrating its promise in real-life applications.

Effect of Macro Fibers on the Permeability and Crack Surface Topography of Layered Fiber Reinforced Concrete.

This paper describes the effects of macro fibers on permeability and crack surface topography of layered fiber-reinforced concrete (FRC) specimens with different layering ratios under uniaxial tensile load. The crack permeability of layered FRC specimens is investigated by a self-designed permeability setup. The topographical analysis of crack surfaces is investigated by a custom-designed laser scanning setup. The results show that when the fiber volume content and layering ratio of the FRC layer are constant, the tensile toughness of layered FRC specimens depends on the proportion of steel fiber in macro fibers, and with an increase in the proportion of steel fiber, the tensile toughness of layered FRC specimens increases. For the layered FRC specimens, the crack permeability is much lower than that of the normal concrete (NC) specimen. A significant positive synergistic effect on crack impermeability can be achieved by the combination of steel fiber and polypropylene fiber in the SF80PP2.3 specimen. The crack surface roughness parameter (Rn) values of the NC layer in layered FRC specimens are all higher than those of the NC specimen, and the crack surface Rn of the FRC layer in layered FRC specimens is higher than that of the unlayered FRC specimens. This can effectively increase the head loss of cracks and reduce the crack permeability of layered FRC specimens.

Integrated-mode proton radiography with 2D lateral projections

Integrated-mode proton radiography leading to water equivalent thickness (WET) maps is an avenue of interest for motion management, patient positioning, and in vivo range verification. Radiographs can be obtained using a pencil beam scanning setup with a large 3D monolithic scintillator coupled with optical cameras. Established reconstruction methods either (1) involve a camera at the distal end of the scintillator, or (2) use a lateral view camera as a range telescope. Both approaches lead to limited image quality. The purpose of this work is to propose a third, novel reconstruction framework that exploits the 2D information provided by two lateral view cameras, to improve image quality achievable using lateral views. The three methods are first compared in a simulated Geant4 Monte Carlo framework using an extended cardiac torso (XCAT) phantom and a slanted edge. The proposed method with 2D lateral views is also compared with the range telescope approach using experimental data acquired with a plastic volumetric scintillator. Scanned phantoms include a Las Vegas (contrast), 9 tissue-substitute inserts (WET accuracy), and a paediatric head phantom. Resolution increases from 0.24 (distal) to 0.33 lp mm−1 (proposed method) on the simulated slanted edge phantom, and the mean absolute error on WET maps of the XCAT phantom is reduced from 3.4 to 2.7 mm with the same methods. Experimental data from the proposed 2D lateral views indicate a 36% increase in contrast relative to the range telescope method. High WET accuracy is obtained, with a mean absolute error of 0.4 mm over 9 inserts. Results are presented for various pencil beam spacing ranging from 2 to 6 mm. This work illustrates that high quality proton radiographs can be obtained with clinical beam settings and the proposed reconstruction framework with 2D lateral views, with potential applications in adaptive proton therapy.

Automated forest inventory: Analysis of high-density airborne LiDAR point clouds with 3D deep learning

Detailed forest inventories are critical for sustainable and flexible management of forest resources, to conserve various ecosystem services. Modern airborne laser scanners deliver high-density point clouds with great potential for fine-scale forest inventory and analysis, but automatically partitioning those point clouds into meaningful entities like individual trees or tree components remains a challenge. The present study aims to fill this gap and introduces a deep learning framework, termed ForAINet, that is able to perform such a segmentation across diverse forest types and geographic regions. From the segmented data, we then derive relevant biophysical parameters of individual trees as well as stands. The system has been tested on FOR-Instance, a dataset of point clouds that have been acquired in five different countries using surveying drones. The segmentation back-end achieves over 85% F-score for individual trees, respectively over 73% mean IoU across five semantic categories: ground, low vegetation, stems, live branches and dead branches. Building on the segmentation results our pipeline then densely calculates biophysical features of each individual tree (height, crown diameter, crown volume, DBH, and location) and properties per stand (digital terrain model and stand density). Especially crown-related features are in most cases retrieved with high accuracy, whereas the estimates for DBH and location are less reliable, due to the airborne scanning setup.

Simulation Study: Data-Driven Material Decomposition in Industrial X-ray Computed Tomography

Material-resolving computed tomography is a powerful and well-proven tool for various clinical applications. For industrial scan setups and materials, several problems, such as K-edge absence and beam hardening, prevent the direct transfer of these methods. This work applies dual-energy computed tomography methods for material decomposition to simulated phantoms composed of industry-relevant materials such as magnesium, aluminium and iron, as well as some commonly used alloys like Al–Si and Ti64. Challenges and limitations for multi-material decomposition are discussed in the context of X-ray absorption physics, which provides spectral information that can be ambiguous. A deep learning model, derived from a clinical use case and based on the popular U-Net, was utilised in this study. For various reasons outlined below, the training dataset was simulated, whereby phantom shapes and material properties were sampled arbitrarily. The detector signal is computed by a forward projector followed by Beer–Lambert law integration. Our trained model could predict two-material systems with different elements, achieving a relative error of approximately 1% through simulated data. For the discrimination of the element titanium and its alloy Ti64, which were also simulated, the relative error increased to 5% due to their similar X-ray absorption coefficients. To access authentic CT data, the model underwent testing using a 10c euro coin composed of an alloy known as Nordic gold. The model detected copper as the main constituent correctly, but the relative fraction, which should be 89%, was predicted to be ≈70%.

Correction for Mechanical Inaccuracies in a Scanning Talbot-Lau Interferometer.

Grating-based X-ray phase-contrast and in particular dark-field radiography are promising new imaging modalities for medical applications. Currently, the potential advantage of dark-field imaging in early-stage diagnosis of pulmonary diseases in humans is being investigated. These studies make use of a comparatively large scanning interferometer at short acquisition times, which comes at the expense of a significantly reduced mechanical stability as compared to tabletop laboratory setups. Vibrations create random fluctuations of the grating alignment, causing artifacts in the resulting images. Here, we describe a novel maximum likelihood method for estimating this motion, thereby preventing these artifacts. It is tailored to scanning setups and does not require any sample-free areas. Unlike any previously described method, it accounts for motion in between as well as during exposures.

DETECTION OF SILVER BIRCH GROWTH DYNAMICS AND TIMING WITH DENSE SPATIO-TEMPORAL LIDAR TIME-SERIES

Abstract. Silver birch (Betula pendula Roth) is a deciduous pioneer tree species with significant economic and ecological importance due to its rapid growth, high genetic variability and adaptability to diverse climates and environments. In this regard, understanding the factors that influence silver birch tree growth variability and its seasonal patterns has been a subject of research interests, which aim at effective forest management and ecological analyses. Tree size, competition, light availability, and topography has been considered significant factors affecting tree growth patterns. However, their relative contributions are not well understood. This is because, to study the interactions between neighbor trees and their competitive responses requires complex measurements. Accurately measuring tree attributes, such as 3D canopy shape and arrangement, is challenging but has been made possible through advancements in high-resolution 3D remote sensing, specifically laser scanning technology. This study shows the potential of high-spatial and temporal resolution LiDAR time-series from a permanent laser scanning setup to detect detailed structural changes and timing in individual tree canopies, focusing on assessment of the structural canopy growth characteristics of silver birch trees. We first investigate how silver birch trees respond to competition and neighboring species. Our results focusing on canopy height increment show that tree size, competition, neighboring species, and water availability affect the rate of vertical (height) growth of the studied silver birch trees. Further, we detect the timing in canopy vertical and horizontal growth using LiDAR time-series. Significant variations of up to one week were detected among trees, providing insights for future studies on growth dynamics of silver birch in coniferous-dominant forests.

Laser Scanning Method for High-Resolution Thickness Mapping of Lithium-Ion Pouch Cells

A precise understanding of the physical properties of lithium-ion cells including the cell thickness distribution during cycling and its connection with lifetime is important for cell improvement. A laser scanning instrument has been developed to perform contact-free thickness measurements in operando for small 250 mAh lithium-ion pouch cells and a large 60 Ah automotive format pouch cell. LiNi0.83Mn0.07Co0.10O2/silicon-graphite cells with 20 and 10 wt% micron-sized silicon particles, a LiNi0.8Mn0.1Co0.1O2/natural graphite cell, and a medium-Ni/graphite automotive cell were either cycled in the laser scanning setup with continuous operando thickness mapping or aged at elevated temperature on separate battery cyclers with intermittent operando thickness mapping using the new laser scanning instrument. During the operando cycles, the cell thickness was measured periodically every 1 h and a graphical quantification method was developed to determine reversible and irreversible swelling of the silicon-containing and silicon-free cells. Using the high-resolution laser scanning technique, irreversible cell swelling could be correlated with capacity loss, especially in cells with high silicon content. Graphite-based cells with mature interface like the large automotive pouch cell showed a fully reversible swelling profile indicative of a long-lived cell.

Positron emission tomography dataset of [11C]carbon dioxide storage in coal for geo-sequestration application

Positron Emission Tomography (PET) imaging has demonstrated its capability in providing time-lapse fluid flow visualisation for improving the understanding of flow properties of geologic media. To investigate the process of CO2 geo-sequestration using PET imaging technology, [11C]CO2 is the most optimal and direct radiotracer. However, it has not been extensively used due to the short half-life of Carbon-11 (20.4 minutes). In this work, a novel laboratory protocol is developed to use [11C]CO2 as radiolabelled tracer to visualise and quantify in-situ CO2 adsorption, spreading, diffusion, and advection flow in coal. This protocol consists of generation and delivering of [11C]CO2, lab-based PET scanning, subsequent micro-CT scanning, and data processing. The lab-based PET scanning setup integrates in-situ core flooding tests with PET scanning. The real-time PET images are acquired under different storage conditions, including early gas production stage, depleted stage, and late storage stage. These datasets can be used to study across-scale theoretical and experimental study of CO2 flow behaviour in coal with the application to CO2 geo-sequestration.

Detunable wireless Litzcage coil for human head MRI at 1.5 T.

Inductively coupled radiofrequency (RF) coils are an inexpensive and simple method to realize wireless RF coils in magnetic resonance imaging (MRI), which can significantly ease the MRI scan setup and improve patient comfort because they do not require bulky components such as cables, baluns, preamplifiers, and connectors. However, volume-type wireless coils are typically operated in transmit/receive mode because detuning such coils is much more challenging due to their complex structure and multiple resonant modes. Meanwhile, adding too many detuning circuits to a wireless coil would decrease the coil's quality factor, impair the signal-to-noise ratio, and increase the cost. In this work, we proposed, constructed, and tested a novel wireless volume coil based on the Litzcage design for 1.5-T head imaging. Being an inductively coupled coil, it has a much simpler structure, resulting in a lighter weight and less bulky design. Despite its simpler structure, it exhibits comparable imaging performance with a commercial receive array, providing an alternative to conventional wired coils with a high cost and complex structure. The unique figure-of-8 conductor pattern within the rungs ensures that the proposed wireless Litzcage can be efficiently detuned with minimal detuning circuits.

Poor Man's Line Scan – a simple tool for the acquisition of high-resolution, undistorted drill core photos

Abstract. The analysis and presentation of drill cores, an essential part of geoscientific research, requires the acquisition of high-quality core photos. Typically, core photos are either taken by hand, which often results in poor and inconsistent image quality and perspective distortions, or with large, heavy, and thus inflexible as well as expensive line scan setups. We present a simple, portable “Poor Man's Line Scan” setup that turns a customary smartphone into a semi-automatic core scanner utilising its panoramic photo function while guided on a rail in order to record undistorted core photographs at high resolution. The resulting images, although affected by some minor artefacts, are clearly superior in quality and resolution to single photos taken by hand and are comparable to images taken with commercial line scan cameras. The low cost (∼ EUR 100) and high flexibility, including the potential for modifications, of our tool make it an interesting alternative to the classical line scan setup.

Third order nonlinear optical, dielectric, photoluminescence and thermal analysis of Gd3+ doped glycine copper chloride (GCC) crystals

In the present investigations, metal-organic third order nonlinear optical (NLO) crystals of glycine copper chloride (GCC) and gadolinium (Gd) doped GCC with molecular formula (C2H5NO2CuCl2)1−x [Gd(NO3)3]x, where [x = 0.05, 0.10, 0.20] have been successfully grown. The growth of these semi-organic crystal compositions has been achieved at room temperature by slow solvent evaporation technique. The crystals exhibit excellent properties which get confirmed by various characterization studies like single crystal X – ray diffraction (SCXRD), powder X – ray diffraction (PXRD), Fourier transform infrared spectroscopy (FTIR), ultraviolet visible spectroscopy (UV – Vis), photoluminescence (PL) spectroscopy, thermal analysis, electrical and nonlinear optical studies. SCXRD confirms that the grown crystal crystallizes in tetragonal crystal system having space group P42/mnm. The PXRD shows the appearance of sharp and strong peaks which refers to the good crystallinity and phase purity of the grown crystals. FTIR was recorded in order to identify various expected functional group. Linear optical behaviour using UV – Vis confirms the compositions to have good optical transmission in the entire visible region and lower cutoff wavelength ranging between 225 and 244 nm which is essential parameter for developing optoelectronic devices. The band gap value comes out to be in the range of 5.43 – 5.53 eV. The grown crystals possess excellent thermal stability. Results of dielectric studies conducted as a function of temperature divulged the electrical properties of crystals. Third – order nonlinear optical (TONLO) response have been observed using Z – scan setup. The calculated TONLO parameters n2, β, and χ(3) shows large value suggests that grown compositions can be used in practical non linear optical device applications.

Functional FDG-PET: Measurement of Task Related Neural Activity in Humans-A Compartment Model Approach and Comparison to fMRI.

Neuroimaging holds an essential position in global healthcare, as brain-related disorders are a substantial and growing burden. Non-degenerative disorders such as stress, depression and anxiety share common function related traits of diffuse and fluctuating changes, such as change in brain-based functions of mood, behavior and cognitive abilities, where underlying physiological mechanism remain unresolved. In this study we developed a novel application for studying intra-subject task-activated brain function by the quantitative physiological measurement of the change in glucose metabolism in a single scan setup. Data were acquired on a PET/MR-scanner. We implemented a functional [18F]-FDG PET-scan with double boli-tracer administration and finger-tapping activation, as proof-of-concept, in five healthy participants. The [18F]-FDG data were analyzed using a two-tissue compartment double boli kinetic model with an image-derived input function. For stand-alone visual reference, blood oxygenation level dependent (BOLD) functional MRI (fMRI) was acquired in the same session and analyzed separately. We were able to measure the cerebral glucose metabolic rate during baseline as well as activation. Results showed increased glucose metabolic rate during activation by 36.3-87.9% mean 62.0%, locally in the peak seed region of M1 in the brain, on an intra-subject level, as well as very good spatial accuracy on group level, and localization compared to the BOLD fMRI result at subject and group level. Our novel method successfully determined the relative increase in the cerebral metabolic rate of glucose on a voxel level with good visual association to fMRI at the subject-level, holding promise for future individual clinical application. This approach will be easily adapted in future clinical perspectives and pharmacological interventions studies.

Towards in vivo immunotherapy using high intensity focused ultraosund

High-intensity focused ultrasound (HIFU) has been regarded as an appealing anti-cancer treatment for over a decade. HIFU indeed offers a combination of unique advantages: it is non-invasive and capable of delivering a precise and local thermal or mechanical dose without affecting the surrounding healthy tissue. HIFU is therefore already being applied as a cancer treatment in the clinics, although mostly as a thermal modality. On the other hand, immunotherapy has demonstrated remarkable promise for durable cancer treatment. However, its cost and complexity are prohibitive. Here, we evaluate (moderate) mechanical HIFU treatment and its capacity to induce immunogenic cell death with the aim to achieve immunotherapy treatment, directly in vivo. To that end, we treat a full lummox dish using an automatic scanning setup. Immunogenic cell death is monitored via distinct biomolecular markers (ATP secretion, HMGB1 secretion, calreticulin exposure). Cavitation activity is monitored via passive cavitation detection. Beyond the correspondence between acoustic cavitation and immunogenic cell death, our results also show a major influence of the cell type, namely, standard CT26 or B16F1O cells.

Brief communication: The Glacier Loss Day as an indicator of a record-breaking negative glacier mass balance in 2022

Abstract. In the hydrological year 2021/2022, Alpine glaciers showed unprecedented mass loss. On Hintereisferner (Ötztal Alps, Austria), the glacier-wide mass balance was −3319 kg m−2. Near-daily observations of the surface elevation changes from a permanent terrestrial laser scanning set-up allowed the determination of the day when the mass balance of Hintereisferner started to become negative. This Glacier Loss Day (GLD) was already reached on 23 June in 2022 and gave way to a long ice ablation period. In 2021/2022, this and the high cumulative positive degree days explain the record-breaking mass loss. By comparing the GLDs of 2019/2020–2021/2022, we found a gross yet expressive indicator of the glacier's imbalance with the persistently warming climate.

A temperature-controlled cooling system for accurate quantitative post-mortem MRI.

To develop a temperature-controlled cooling system to facilitate accurate quantitative post-mortem MRI and enable scanning of unfixed tissue. A water cooling system was built and integrated with a 7T scanner to minimize temperature drift during MRI scans. The system was optimized for operational convenience and rapid deployment to ensure efficient workflow, which is critical for scanning unfixed post-mortem samples. The performance of the system was evaluated using a 7-h diffusion MRI protocol at 7T with a porcine tissue sample. Quantitative T1 , T2 , and ADC maps were interspersed with the diffusion scans at seven different time points to investigate the temperature dependence of MRI tissue parameters. The impact of temperature changes on biophysical model fitting of diffusion MRI data was investigated using simulation. Tissue T1 , T2 , and ADC values remained stable throughout the diffusion MRI scan using the developed cooling system, but varied substantially using a conventional scan setup without temperature control. The cooling system enabled accurate estimation of biophysical model parameters by stabilizing the tissue temperature throughout the diffusion scan, while the conventional setup showed evidence of significantly biased estimation. A temperature-controlled cooling system was developed to tackle the challenge of heating in post-mortem imaging, which shows potential to improve the accuracy and reliability of quantitative post-mortem imaging and enables long scans of unfixed tissue.