X-ray Micro-computed Tomography Research Articles

Exploring the micro-to-macro response of granular soils with real particle shapes by way of μCT-aided DEM analyses

This contribution provides high-fidelity images of real granular materials with the aid of X-ray micro-computed tomography (μCT), and employs a multi-sphere representation to reconstruct non-spherical particles. Through discrete-element method (DEM) simulations of granular samples composed of these non-spherical clumps, the effect of particle shape on the macroscopic mechanical response and microscopic soil fabric evolution is examined for soil assemblies under triaxial compression. Simulation results indicate that materials with more irregular particles tend to show higher shear resistance in both peak and critical states, while exhibiting higher void ratio under isotropic loading conditions and in the critical state. The proposed critical state parameters for describing the sensitivity of the mean coordination number to confining pressures are larger as particles become more irregular. At a microscopic level of observation, directional and scalar parameters of particle contacts are sensitive to predefined particle shapes. More irregular materials appear to exhibit higher fabric anisotropy with respect to particle orientation in the critical state, while the branch vector is affected by both contact modes and particle shape. The critical stress ratio from the simulation results is validated by comparing with experimental results, and further found to be linearly linked to the shape-weighted fabric anisotropy indices.

Utilizing Synchrotron-Based X-ray Micro-Computed Tomography to Visualize the Microscopic Structure of Starch Hydrogels In Situ.

This study aimed to visualize the microstructures of starch hydrogels using synchrotron-based X-ray micro-computed tomography (μCT). Waxy maize starch (WMS, 3.3% amylose, db), pea starch (PS, 40.3% amylose), and high-amylose maize starch (HMS, 63.6% amylose) were cooked at 95 and 140 °C to prepare starch hydrogels. WMS and HMS failed to form a gel after 95 °C cooking and storage, while PS developed a firm gel. At 140 °C cooking, HMS of a high amylose nature was fully gelatinized and generated a rigid gel with the highest strength. Both scanning electron microscopy (SEM) and μCT revealed the unique structural features of various starch hydrogels/pastes prepared at different temperatures, which were greatly affected by the degree of swelling and dispersity of the starches. As a nondestructive method, μCT showed certain advantages over SEM, including minimal shrinkage of the hydrogels, relatively simple sample preparation, and allowing for three-dimensional reconstruction of the hydrogel microstructure. This study indicated that synchrotron-based μCT could be a useful technique in visualizing biopolymer-based hydrogels.

Multiscale modeling for the impact behavior of 3D angle-interlock woven composites

In this paper, a multiscale modeling framework predicting the impact response of three-dimensional angle-interlock woven composites (3DAWCs) is presented. Multiscale modeling is performed sequentially at the mirco, meso, and macroscales. A microscopic representative volume element (RVE) model is established to characterize the yarn's nonlinear mechanical properties and damage behavior at different strain rates. At the mesoscale, a novel subcell-based discretization scheme is proposed to discretize 3DAWCs, and developing six representative subcells (RSCs) that bridge the microscale and macroscale effective properties. Based on it, a ballistic impact model involving six kinds of homogeneous material bricks is established. Furthermore, elastic-viscoplastic damage constitutive models are developed for the epoxy matrix and the yarn, respectively, to enhance the predicted accuracy of the multiscale model. Ballistic impact tests of 3DAWCs are conducted, and X-ray micro-computed tomography is employed to evaluate the internal damage of the 3DAWC target after impact. Validation work is conducted by comparing the experimental and numerical results of the ballistic impact of the 3DAWC target, which indicates the effectiveness and efficiency of the developed multiscale framework in the impact damage prediction of 3DAWCs.

Exploring in-situ combustion effects on reservoir properties of heavy oil carbonate reservoir

Laboratory modeling of in-situ combustion is crucial for understanding the potential success of field trials in thermal enhanced oil recovery and is a vital precursor to scaling the technology for field applications. The high combustion temperatures, reaching up to 480°C, induce significant petrophysical alterations of the rock, an often overlooked aspect in thermal EOR projects. Quantifying these changes is essential for potentially repurposing thermally treated, depleted reservoirs for CO2 storage.In this study, we depart from conventional combustion experiments that use crushed core, opting instead to analyze the thermal effects on reservoir properties of carbonate rocks using consolidated samples. This technique maintains the intrinsic porosity and permeability, revealing combustion's impact on porosity and mineralogical alterations, with a comparative analysis of these properties pre- and post-combustion. We characterize porosity and pore geometry evolution using low-field nuclear magnetic resonance, X-ray micro-computed tomography, and low-temperature nitrogen adsorption. Mineral composition of the rock and grain-pore scale alterations are analyzed by scanning electron microscopy and X-ray diffraction.The analysis shows a significant increase in carbonate rocks’ porosity, pore size and mineral alterations, and a transition from mixed-wet to a strongly water-wet state. Total porosity of rock samples increased in average for 15%–20%, and formation of new pores is registered at the scale of 1–30 μm size. High-temperature exposure results in the calcite and dolomite decomposition, calcite dissolution and formation of new minerals – anhydrite and fluorite. Increased microporosity and the shift to strongly water-wet rock state improve the prospects for capillary and residual CO2 trapping with greater capacity. Consequently, these findings highlight the importance of laboratory in-situ combustion modeling on consolidated rock over tests that use crushed core, and indicate that depleted combustion stimulated reservoirs may prove to be viable candidates for CO2 storage.

Modelling of microscopic crack initiation behaviour of fretting fatigue based on X-ray micro-computed tomography scan

Fretting fatigue is a particularly destructive form of fatigue failure that has drawn significant attention from researchers. This paper proposes a numerical modelling method based on tomography scan to investigate the impact of inclusions on fretting fatigue crack initiation behaviour. The results reveal that inclusions can affect the crack initiation direction of fretting fatigue and reduce the initiation lifetime. The difference between the properties of inclusions and matrix leads to local mechanical response mismatch, resulting in local stress, strain, and damage concentration. The mismatch in strain and damage follows a gradient distribution along the thickness as the distribution in these mechanical responses. These could explain why particles closer to the surface are more likely to cause damage. Additionally, the aggregation distribution of inclusions results in the merging and connection of local regions with high stress, strain, and damage concentration, ultimately promoting fracture behaviour. Finally, the numerical models are validated with experimental data from fretting fatigue tests. Compared to the homogeneous model, the numerical model that considers inclusions from topography data can more accurately analyse the material damage and provide a more comprehensive understanding of fretting fatigue behaviour.

Temperature Dependent Dynamic Response of Open-Cell Polyurethane Foams

Abstract Background Polyurethane foams have many uses ranging from comfort fitting seats and shoes to protective inserts in helmets and sports equipment. Current military helmet designs employ foam pads of varying densities and bulk material properties to help absorb energy from impacts ranging from quasi-static to ballistic level strain-rates. Objective This study aims to analyze the thermomechanical uniaxial compression behavior of a high density liner foam pad and a low density liner foam pad used in the Advanced Combat Helmet. These experiments were conducted under strain-rates of $$10^2$$ 10 2  s$$^{-1}$$ - 1 and under temperature conditions ranging from -20 to 40 °C. This temperature range was chosen to simulate desert and arctic conditions, with a strain-rate regime chosen to represent loads that would occur often throughout the life of the helmet, such as drops, bumps from riding in a vehicle, or heavy collisions from falling. Method Multiple experimental apparatuses were used in this study, including a Shimadzu TCE-N300 thermostatic chamber (used to create the varying temperature environments) and a custom-built drop-test system (used to induce intermediate strain-rates). Every experiment was paired with two accelerometers and a high speed camera used for Digital Image Correlation (DIC) to analyze sample deformation and resultant acceleration. The foam’s mechanical response and energy absorption properties were investigated from the measured stress-strain curves. Additionally, each foam composition was analyzed with X-ray computed micro-tomography (XCT) to investigate microstructure properties pre and post-mortem. Results Results show that temperature decreased the energy absorption of the low density composition by 48% ± 5% as temperature changed from -20 °C to 40 °C, while energy absorption increased by 53% ± 16% for the high density composition over the same temperature. Conclusion A comparison between the loading response and the material’s density characteristics revealed that the foam’s mechanical properties are heavily dependent on strain-rate applications, as well as environmental factors including temperature. Several important characteristics surrounding each foam composition’s deformation mechanics and damage tolerance as a result of temperature are discussed.

A Manufacturability Evaluation of Complex Architectures by Laser Powder Bed Fusion Additive Manufacturing

Abstract Additive manufacturing (AM) enables new possibilities for the design and manufacturing of complex metal architectures. Incorporating lattice structures into complex part geometries can enhance strength-to-weight and surface area-to-volume ratios for valuable components, particularly in industries such as medical devices and aerospace. However, lattice structures and their interconnections may result in unsupported down-skin surfaces, potentially limiting their manufacturability by metal AM technologies, such as laser powder bed fusion (LPBF). This study aimed to examine the correlation between down-skin surface area and the manufacturability of lattice structures fabricated using LPBF. Image processing algorithms were used to analyze down-skin surface areas of seven unique lattice designs and to devise quantitative metrics (such as down-skin surface area, discrete surface count, surface interconnectivity, down-skin ratio, over-print/under-print volumes, etc.) to evaluate LPBF manufacturability. The seven lattice designs were subsequently manufactured using maraging steel via LPBF and then examined using imaging using X-ray micro-computed tomography (XCT). The geometric accuracy of the lattice designs was compared with XCT scans of the manufactured lattices by employing a voxel-based image comparison technique. The results indicated a strong relationship between down-skin surface area, surface interconnectivity, and the manufacturability of a given lattice design. The digital manufacturability evaluation workflow was also applied to a medical device design, further affirming its potential industrial utility for complex geometries.

A microCT assessment of archaeological parenchyma from three riverine shell middens dating to the early Holocene, Yongjiang River Basin, Guangxi, southern China

Archaeobotanical investigations at three riverine shell midden sites dating to the early Holocene – Baozitou, Shichuantou and Nabeizui – in the Yongjiang River Basin, Guangxi, southern China have identified charred fragments of archaeological parenchyma. A subset of the archaeological parenchyma was assessed using X-ray micro-computed tomography (microCT), which enabled virtual histological examination of the interior of parenchyma fragments. The microCT scanning identified a fragment of lotus root (Nelumbo nucifera), a possible immature fig fruit (poss. Ficus sp.), cooked food fragments, and less diagnostic elements, some of which derive from underground storage organs (USOs), including a bud/bulb and potentially an aroid. The fragment of lotus root from Nabeizui was directly radiocarbon dated using Accelerator Mass Spectrometry to 8770–8544 cal BP. A new AMS radiocarbon chronology based on Canarium nutshells for the three sites indicates that they were all used during the early Holocene. These findings contribute to the understanding of broad spectrum plant use by hunter-gatherer-fisher communities in southern China during the early Holocene, as well as showing the potential of microCT imaging for the analysis of archaeological parenchyma from this region.

A Method for Automatic Three-Dimensional Particle Tracing Under Laboratory Conditions Using Dynamic X-Ray Computed Microtomography

AbstractThis paper presents a method for particle tracing in laboratory X-ray micro-computed tomography (µCT) using an adjusted Random Sample Consensus (RANSAC) algorithm combined with least squares ellipse fitting (LSF). For method testing, a setup for the investigation of deep bed filtration (DBF) has been used as an example of a complex process that can be elucidated with such a method. Particle tracking with tomography systems requires high-temporal resolution which can only be achieved with synchrotron radiation computer tomography. Therefore, in this work, it has been demonstrated that instead of particle tracking, particle tracing in opaque systems such as DBF can be performed in laboratory µCT systems. To achieve particle tracing, dynamic µCT scans with a duration between 30 and 110 s combined with an exposure time of 0.13 s/projection were executed and during the scan time the filtration was performed, causing parabola shaped motion artefacts. The developed method exploits the motion artefacts created by the particle motion during the scan. It could be shown that it is possible to trace particles in complex structures within only one 30 s scan. Furthermore, through trace length and time, it is possible to determine the average velocity. Whereby, the accuracy and limits depend on the particle size, particle velocity/data rate and the X-ray attenuation of particle and medium.

Monoliths for gas storage manufactured with precision pore engineering using 3D-printed templates

A fast, customizable, and systematic route for producing activated carbon monoliths for gas storage with low interparticle porosity (9 % to 24 %) containing tailored macro channels is disclosed. The production uses a three-dimensional (3D)-printed polymeric lattice, rich in oxygen, as a sacrificial template. Its interstitial voids are filled with a phenolic resin that is carbonized and activated at 1173 K under carbon dioxide (CO2). Sequential pyrolysis occurs via thermal treatment with the 3D-printed lattice removed first, rendering macro channels with the same shape as the template in accurately placed positions. Resulting in adsorbents with interparticle porosities ranging from 10 % to 23 %, calculated from X-ray micro-computed tomography (micro-CT) images. The axial resolution of these macro channels was similar to the SLA printing layer thickness used of 100 µm. Making it the best resolution attained to date in fabricating monoliths via a 3D-printed sacrificial templating method. Breakthrough experiments indicated healthy macro channel connectivity due to the reduced mass transfer zone. Moreover, excellent mechanical integrity was displayed, with a monolith withstanding 900 N before excessive fracturing occurred despite the presence of macro channels. Therefore, this method emphasizes its use for gas storage applications by enabling the adsorbent material to efficiently utilize the volumetric space while allowing a fast rate of adsorption over the entire structure.

Characterisation of hygroelastic properties of compression and opposite wood found in branches of Norway spruce

AbstractThe differential swelling seen between softwood opposite wood (OW) and its neighbouring compression wood (CW) developed in branches prompts several engineering issues such as dimensional instability and cracking. For a more efficient use of resources, the inevitable CW and OW should not be discarded or used as fuel, but incorporated into engineered wood products. Swelling is a hygroelastic phenomenon, where both the swelling and elastic properties of CW and OW are needed in order to make proper structural predictions. In this paper, swelling coefficients and moisture dependent elastic moduli for both CW and OW in the three principal material directions are provided along with measurements of moisture content, density, and microfibril angle. The small deformations necessitate the use of precise X-ray micro-computed tomography for measurements. The results indicate that CW and OW from Norway spruce branches differ in swelling, especially in longitudinal direction at low moisture content. It is noted that CW is a wood type with less pronounced anisotropic behaviour than both OW and normal wood from the stem, with the elastic moduli less sensitive to moisture changes in both longitudinal and transverse directions.

Using internal standards in time-resolved X-ray micro-computed tomography to quantify grain-scale developments in solid-state mineral reactions

Abstract. X-ray computed tomography has established itself as a crucial tool in the analysis of rock materials, providing the ability to visualise intricate 3D microstructures and capture quantitative information about internal phenomena such as structural damage, mineral reactions, and fluid–rock interactions. The efficacy of this tool, however, depends significantly on the precision of image segmentation, a process that has seen varied results across different methodologies, ranging from simple histogram thresholding to more complex machine learning and deep-learning strategies. The irregularity in these segmentation outcomes raises concerns about the reproducibility of the results, a challenge that we aim to address in this work. In our study, we employ the mass balance of a metamorphic reaction as an internal standard to verify segmentation accuracy and shed light on the advantages of deep-learning approaches, particularly their capacity to efficiently process expansive datasets. Our methodology utilises deep learning to achieve accurate segmentation of time-resolved volumetric images of the gypsum dehydration reaction, a process that traditional segmentation techniques have struggled with due to poor contrast between reactants and products. We utilise a 2D U-net architecture for segmentation and introduce machine-learning-obtained labelled data (specifically, from random forest classification) as an innovative solution to the limitations of training data obtained from imaging. The deep-learning algorithm we developed has demonstrated remarkable resilience, consistently segmenting volume phases across all experiments. Furthermore, our trained neural network exhibits impressively short run times on a standard workstation equipped with a graphic processing unit (GPU). To evaluate the precision of our workflow, we compared the theoretical and measured molar evolution of gypsum to bassanite during dehydration. The errors between the predicted and segmented volumes in all time series experiments fell within the 2 % confidence intervals of the theoretical curves, affirming the accuracy of our methodology. We also compared the results obtained by the proposed method with standard segmentation methods and found a significant improvement in precision and accuracy of segmented volumes. This makes the segmented computed tomography images suited for extracting quantitative data, such as variations in mineral growth rate and pore size during the reaction. In this work, we introduce a distinctive approach by using an internal standard to validate the accuracy of a segmentation model, demonstrating its potential as a robust and reliable method for image segmentation in this field. This ability to measure the volumetric evolution during a reaction with precision paves the way for advanced modelling and verification of the physical properties of rock materials, particularly those involved in tectono-metamorphic processes. Our work underscores the promise of deep-learning approaches in elevating the quality and reproducibility of research in the geosciences.

Vitronectin regulates osteoclastogenesis and bone remodeling in a mouse model of osteoporosis.

Vitronectin (VN) is an extracellular matrix protein with a crucial role in regulating bone remodeling. In this study, we aimed to investigate the effect of VN deficiency in a mouse model of osteoporosis induced by ovariectomy (OVX). The findings revealed that the absence of VN led to an increase in the activity of tartrate-resistant acid phosphatase (TRAP), a marker for osteoclasts, in the plasma of OVX-operated mice. TRAP staining further demonstrated that VN deficiency resulted in a higher number of osteoclasts within the femurs of OVX-operated mice. X-ray micro-computed tomography analysis of the femurs in OVX-operated mice indicated that VN deficiency significantly suppressed the OVX-induced increase of marrow area and total volume of bone. Additionally, we assessed structural model index (SMI) and degree of anisotropy (DA) as indices of osteoporosis. The results showed that VN deficiency effectively attenuated the OVX-induced increase in SMI and DA among OVX-operated mice. In summary, our study demonstrates the vital role of VN in regulating osteoclastogenesis and bone remodeling in the mouse model of osteoporosis.

Evolution of pore structure and reactive transport parameters during acid leaching of sandstone uranium ore

The changes in the micro-scale pore structure during the acid leaching of sandstone uranium ore significantly affect its reactive transport parameters, which, in turn, directly influence the leaching efficiency of uranium. Consequently, understanding and managing the dynamic evolution of the pore structure of sandstone at micro-scale during acid leaching is beneficial for enhancing the leaching efficiency of uranium. This paper employs a dynamic continuous water-rock reaction experiment on sandstone uranium ore to simulate the in-situ acid leaching process. Additionally, X-ray micro-computed tomography (μCT) scanning was utilized to produce three-dimensional (3D) images at various leaching stages. Subsequently, image processing techniques were employed to characterize and parameterize the pore structure within these images. The results revealed that, during the leaching process, mineral dissolution led to an increase in the interconnected pores, while there was a decrease in the isolated pores. Nonetheless, at the leading edge of the sandstone uranium ore, detachment of mineral grains occurred during the leaching process along the direction of fluid flow. The migration of mineral grains resulted in a reduction of interconnected pores and an increase in the isolated pores. The analysis of 3D images indicated that porosity, permeability, the percentage of connected pore area and the reactive surface area exhibited similar variation trends throughout the leaching process. Furthermore, the permeability, the percentage of connected pore area and the reactive surface area displayed a positive correlation with porosity. The study holds valuable insights to develop a deeper understanding of the evolutionary patterns regarding the pore structure during the in-situ acid leaching of sandstone uranium ore.

Does the choice of the measuring technique affect the comparison of fit between zirconia and cobalt-chromium prostheses?

The objectives of the study were to compare the adaptation of presintered zirconia and cobalt- chromium prostheses using microcomputed tomography (μCT), scanning electron microscopy (SEM), and stereomicroscope (SM). Twenty-four fixed dental prostheses (FDPs) were fabricated on metal abutments, duplicated from maxillary first premolar and first molar prepared on a typodont model. Teeth were reduced to obtain chamfer of 1.2 mm and reduction occlusaly of 2 mm occlusal. Scanning of the abutments was done with random assignment to two groups receiving the FDPs made from soft-milled Co-Cr (n = 12) and zirconia (n = 12). Marginal and internal gaps were assessed using three evaluation techniques (X-ray microcomputer tomography, SEM, and stereomicroscopy). Comparison of the results was made using Levene and analysis of variance tests (α =0.05). Irrespective of the material tested, statistical differences were found between the measuring techniques (P = 0.001 overall); the obtained mean gaps were for CT scan (92.60 ± 13.31), for SEM (101.92 ± 23.03), and for SM (113.44 ± 14.68): the multiple comparisons between techniques found a significant difference between CT and SM (P < 0.001), and SEM and SM (P = 0.025). When materials were compared within each measuring technique, Co-Cr showed lower values compared to zirconia in SEM (P < 0.001) and Stereo (P = 0.049); similar results were found in CT. Results values differed with the chosen measuring technique. Co-Cr prostheses had a better fit than zirconia prostheses in SEM and Stereo. µCT showed comparable results to SEM, smaller than SM results.

Porosity prediction in laser-based powder bed fusion of polyamide 12 using infrared thermography and machine learning

Achieving precise control in laser-based powder bed fusion of polymers is crucial for ensuring the structural integrity of aerospace and automotive components. Closed-loop feedback control systems using process monitoring techniques, such as infrared thermography, have the potential to provide reliable production by controlling the temperature of the melt. However, challenges arise from complex interactions among variables, such as part geometry, scan strategy, and laser parameters, affecting the melted polymer's temperatures and subsequent particle fusion. Thus, the correlation between thermal signals and resulting part density still needs to be clarified. In this work, a machine learning algorithm is trained to predict local porosity or, rather, solidity based on thermal and temporal features extracted from the melt's temperature-time profile. This enables statistical techniques to assess the contribution of the melt's thermal and temporal features in the decision-making process for evaluating porosity, along with the influence of voxel size and configuration. The in-situ process signature is measured using infrared thermography, and the porosity is analyzed by X-ray micro-computed tomography. The 2D thermal data is first converted into voxel information and then stitched with the 3D mircoCT data in a second step. The resulting 3D thermal features and porosity matrices are downsampled and utilized to train a machine learning algorithm (lightGBM). Models with high prediction accuracy are achieved using a small voxel size to avoid over-homogenizing features and by utilizing thermal signals from adjacent voxels to determine porosity in a volume element. The highest predictor for resulting porosity is the peak temperature of the melt during laser exposure. Interlayer effects, such as sufficient reheating of subsurface layers, are the second-highest indicator for dense parts. Furthermore, the model's performance is also affected by intra-layer effects, including the peak temperature of adjacent voxels and the cooling behavior after laser exposure. This research has several implications for industry, as it enables the detection of process defects based on in-situ process monitoring data without post-process material testing. Moreover, identifying thermal signal ranges that lead to the highest porosity can reduce the number of experiments needed for material qualification processes.

Optimized reinforcement of granite residual soil using a cement and alkaline solution: A coupling effect

Granite residual soil (GRS) is a type of weathering soil that can decompose upon contact with water, potentially causing geological hazards. In this study, cement, an alkaline solution, and glass fiber were used to reinforce GRS. The effects of cement content and SiO2/Na2O ratio of the alkaline solution on the static and dynamic strengths of GRS were discussed. Microscopically, the reinforcement mechanism and coupling effect were examined using X-ray diffraction (XRD), micro-computed tomography (micro-CT), and scanning electron microscopy (SEM). The results indicated that the addition of 2% cement and an alkaline solution with an SiO2/Na2O ratio of 0.5 led to the densest matrix, lowest porosity, and highest static compressive strength, which was 4994 kPa with a dynamic impact resistance of 75.4 kN after adding glass fiber. The compressive strength and dynamic impact resistance were a result of the coupling effect of cement hydration, a pozzolanic reaction of clay minerals in the GRS, and the alkali activation of clay minerals. Excessive cement addition or an excessively high SiO2/Na2O ratio in the alkaline solution can have negative effects, such as the destruction of C-(A)-S-H gels by the alkaline solution and hindering the production of N-A-S-H gels. This can result in damage to the matrix of reinforced GRS, leading to a decrease in both static and dynamic strengths. This study suggests that further research is required to gain a more precise understanding of the effects of this mixture in terms of reducing our carbon footprint and optimizing its properties. The findings indicate that cement and alkaline solution are appropriate for GRS and that the reinforced GRS can be used for high-strength foundation and embankment construction. The study provides an analysis of strategies for mitigating and managing GRS slope failures, as well as enhancing roadbed performance.

Continuous additive manufacturing of hemp yarn-reinforced biocomposites with improved impregnation method

This study was motivated by the development of new additively manufactured bio-based materials with high performance. Hemp yarn was used in continuous material extrusion additive manufacturing to produce novel hemp yarn-reinforced biocomposites. The hemp yarn was compared to an original hemp/poly(lactic acid) hybrid yarn prepared by commingling before printing as an improved impregnation method. In X-ray micro-computed tomography, the hybrid yarn-based biocomposite exhibited a higher impregnation rate accompanied by a reduced void content, more aligned fibers, and a more homogeneous distribution of the different constituents, resulting in significantly higher mechanical properties during tensile loading with a more brittle behavior compared to the additively manufactured biocomposite based on pure hemp yarn. In addition, superior mechanical performance was obtained while having lower fiber fraction with the use of hybrid yarns, raising awareness about the importance of improving the impregnation of the plant fibers as well as the fiber volume fraction. This original preparation method can provide bio-based materials with enhanced quality and performance, close to those obtained with conventional manufacturing techniques, while making the most of additive manufacturing for sustainable, lightweight, and high-end applications in health or aerospace.

Visualization of water transfer channel in sludge dewatering conditioned with skeleton builders by X-ray micro-computed tomography

Skeleton builders were normally deemed to improve the high porosity and newly-generated permeability of sludge cakes by building water transfer channel during high pressure filtration, thus enhancing sludge dewaterability. However, currently a direct visualization proof of water transfer channel was still lacking. This study provided the direct proof for visualizing water transfer channel in dewatered sludge cakes conditioned with a typical skeleton builder (i.e., phosphogypsum (PG)) by X-ray micro-computed tomography (micro-CT) for the first time. After the addition of PG, the pixel value and image luminance increased significantly, indicating the presence of high density substances from both two-dimensional (2D) cross section and three-dimensional (3D) reconstruction CT images. Moreover, the CT numbers showed strong and negative correlations with specific resistance to filtration (SRF) (R = − 0.99, p < 0.05), capillary suction time (CST) (regression coefficient (R) = − 0.87, probability (p) < 0.05), and water content of the dewatered sludge cake (R = − 0.99, p < 0.05), respectively. These results indicated that the X-ray micro-CT could be a potential technique for analyzing the water distribution in sludge samples conditioned with skeleton builders.

Phytohormonal regulation determines the organization pattern of shoot aerenchyma in greater duckweed (Spirodela polyrhiza).

Airspace or aerenchyma is crucial for plant development and acclimation to stresses such as hypoxia, drought, and nutritional deficiency. Although ethylene-mediated signaling cascades are known to regulate aerenchyma formation in stems and roots under hypoxic conditions, the precise mechanisms remain unclear. Moreover, the cellular dynamics underlying airspace formation in shoots are poorly understood. We investigated the stage-dependent structural dynamics of shoot aerenchyma in greater duckweed (Spirodela polyrhiza), a fast-growing aquatic herb with well-developed aerenchyma in its floating fronds. Using X-ray micro-computed tomography and histological analysis, we showed that the spatial framework of aerenchyma is established before frond volume increases, driven by cell division and expansion. The substomatal cavity connecting aerenchyma to stomata formed via programmed cell death (PCD) and was closely associated with guard cell development. Additionally, transcriptome analysis and pharmacological studies revealed that the organization of aerenchyma in common duckweed is determined by the interplay between PCD and proliferation. This balance is governed by spatiotemporal regulation of phytohormone signaling involving ethylene, abscisic acid, and salicylic acid. Overall, our study reveals the structural dynamics and phytohormonal regulation underlying aerenchyma development in duckweed, improving our understanding of how plants establish distinct architectural arrangements. These insights hold the potential for wide-ranging application, not only in comprehending aerenchyma formation across various plant species but also in understanding how airspaces are formed within the leaves of terrestrial plants.