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At least 451 records · Page 25

Migration and Precipitation of Platinum in Anion‐Exchange Membrane Fuel Cells

Abstract Despite the recent progress in increasing the power generation of Anion‐exchange membrane fuel cells (AEMFCs), their durability is still far lower than that of Proton exchange membrane fuel cells (PEMFCs). Using the complementary techniques of X‐ray micro‐computed tomography (CT), Scanning Electron Microscopy (SEM) and Energy Dispersive X‐ray (EDX) spectroscopy, we have identified Pt ion migration as an important factor to explain the decay in performance of AEMFCs. In alkaline media Pt +2 ions are easily formed which then either undergo dissolution into the carbon support or migrate to the membrane. In contrast to PEMFCs, where hydrogen cross over reduces the ions forming a vertical “Pt line” within the membrane, the ions in the AEM are trapped by charged groups within the membrane, leading to disintegration of the membrane and failure. Diffusion of the metal components is still observed when the Pt/C of the cathode is substituted with a FeCo−N−C catalyst, but in this case the Fe and Co ions are not trapped within the membrane, but rather migrate into the anode, thereby increasing the stability of the membrane.

Raut, Aniket↗

Migration and Precipitation of Platinum in Anion–Exchange Membrane Fuel Cells

Despite the recent progress in increasing the power generation of Anion-exchange membrane fuel cells (AEMFCs), their durability is still far lower than that of Proton exchange membrane fuel cells (PEMFCs). Using the complementary techniques of X-ray micro-computed tomography (CT), Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray (EDX) spectroscopy, we have identified Pt ion migration as an important factor to explain the decay in performance of AEMFCs. In alkaline media Pt+2 ions are easily formed which then either undergo dissolution into the carbon support or migrate to the membrane. In contrast to PEMFCs, where hydrogen cross over reduces the ions forming a vertical “Pt line” within the membrane, the ions in the AEM are trapped by charged groups within the membrane, leading to disintegration of the membrane and failure. Furthermore, diffusion of the metal components is still observed when the Pt/C of the cathode is substituted with a FeCo–N–C catalyst, but in this case the Fe and Co ions are not trapped within the membrane, but rather migrate into the anode, thereby increasing the stability of the membrane.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis of new two-dimensional titanium carbonitride Ti 2 C 0.5 N 0.5 T x MXene and its performance as an electrode material for sodium-ion battery

Two-dimensional (2D) layered transition metal carbides/nitrides, called MXenes, are attractive alternative electrode materials for electrochemical energy storage. Owing to their metallic electrical conductivity and low ion diffusion barrier, MXenes are promising anode materials for sodium-ion batteries (SIBs). Herein, we report on a new 2D carbonitride MXene, viz ., Ti 2 C 0.5 N 0.5 T x (T x stands for surface terminations), and the only second carbonitride after Ti 3 CNT x so far. A new type of in situ HF (HCl/KF) etching condition was employed to synthesize multilayer Ti 2 C 0.5 N 0.5 T x powders from Ti 2 AlC 0.5 N 0.5 . Spontaneous intercalation of tetramethylammonium followed by sonication in water allowed for large-scale delamination of this new titanium carbonitride into 2D sheets. Multilayer Ti 2 C 0.5 N 0.5 T x powders showed higher specific capacities and larger electroactive surface area than those of Ti 2 CT x powders. Multilayer Ti 2 C 0.5 N 0.5 T x powders show a specific capacity of 182 mAh g -1 at 20 mA g -1 , the highest among all reported MXene electrodes as SIBs with excellent cycling stability.

25 ENERGY STORAGE↗

Morphology and composition of Goldeye (Hiodontidae; Hiodon alosoides) otoliths

In this work, we provide up-todate morphological and compositional data on otoliths of the osteoglossomorph Goldeye (Hiodon alosoides). Using computed tomography (CT) X-ray, we documented the location of each of the three pairs of otoliths (lapilli, sagittae, and asterisci) in relation to the swim bladder, which extended forward in close proximity to the sagittae and asterisci. The lappili were the largest otoliths in terms of surface area and volume, but the sagittae were highly modified, appearing spiral in shape when viewed dorsally, with a surface area to volume ratio more than double that of the lapilli. Using scanning electron microscopy, the surface of each otolith was viewable in great detail, and small otoconia (~10.5 μm diameter) were observed on each, but were most numerous on the sagittae. Additionally, on scanning electron micrographs, the sagittae appeared to be bi-lobed, with asymmetrical lobes each oriented in the same general direction. Using neutron and X-ray diffraction methods, we found three polymorphs of calcium carbonate crystals (aragonite, vaterite, and calcite), sometimes all within the same otolith. However, in general, lapilli and sagittae were composed predominately of aragonite whereas asterisci were composed chiefly of vaterite. With these results, we provide information on a unique species, whose inclusion in future studies would benefit our understanding of fish hearing, fish evolution, and fisheries ecology.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model

Abstract Background Accurate delineation of the clinical target volume (CTV) is essential in the radiotherapy treatment of soft tissue sarcomas. However, this process is subject to inter‐reader variability due to the need for clinical assessment of risk and extent of potential microscopic spread. This can lead to inconsistencies in treatment planning, potentially impacting treatment outcomes. Most existing automatic CTV delineation methods do not account for this variability and can only generate a single CTV for each case. Purpose This study aims to develop a deep learning‐based technique to generate multiple CTV contours for each case, simulating the inter‐reader variability in the clinical practice. Methods We employed a publicly available dataset consisting of fluorodeoxyglucose positron emission tomography (FDG‐PET), x‐ray computed tomography (CT), and pre‐contrast T1‐weighted magnetic resonance imaging (MRI) scans from 51 patients with soft tissue sarcoma, along with an independent validation set containing five additional patients. An experienced reader drew a contour of the gross tumor volume (GTV) for each patient based on multi‐modality images. Subsequently, two additional readers, together with the first one, were responsible for contouring three CTVs in total based on the GTV. We developed a diffusion model‐based deep learning method that is capable of generating arbitrary number of different and plausible CTVs to mimic the inter‐reader variability in CTV delineation. The proposed model incorporates a separate encoder to extract features from the GTV masks, leveraging the critical role of GTV information in accurate CTV delineation. Results The proposed diffusion model demonstrated superior performance with the highest Dice Index (0.902 compared to values below 0.881 for state‐of‐the‐art models) and the best generalized energy distance (GED) (0.209 compared to values exceeding 0.221 for state‐of‐the‐art models). It also achieved the second‐highest recall and precision metrics among the compared ambiguous image segmentation models. Results from both datasets exhibited consistent trends, reinforcing the reliability of our findings. Additionally, ablation studies exploring different model structures and input configurations highlighted the significance of incorporating prior GTV information for accurate CTV delineation. Conclusions The proposed diffusion model successfully generates multiple plausible CTV contours for soft tissue sarcomas, effectively capturing inter‐reader variability in CTV delineation.

Dong, Yafei [Yale Biomedical Imaging Institute Yal↗

Utilization of the Critic Subnetwork of a Generative Adversarial Network as Detector of Morphological Material Change in Image Data

The resolution of computed tomography (CT) has become high enough to monitor morphological changes due to aging in materials in long-term applications. For this work, we explored the utility of the critic of a generative adversarial network (GAN) to automatically detect such changes. The GAN was trained with images of pristine Pharmatose, which is used as a surrogate energetic material. It is important to note that images of the material with altered morphology were only used during the test phase. The GAN-generated images reproduced the microstructure of Pharmatose well, although some unrealistic particle fusion was seen. Calculated morphological metrics (volume fraction, interfacial line length, and local thickness) for the synthetic images also showed good agreement with the training data, albeit with signs of mode collapse in the interfacial line length. While the critic exposed changes in particle size, it showed limited ability to distinguish images by particle shape. The detection of shape differences was also a more challenging task for the selected morphological metrics that related to energetic material performance. We further tested the critic with images of aged Pharmatose. Subtle changes due to aging are difficult for the human analyst to detect; but both critic and morphological metrics analysis showed image differentiation.

36 MATERIALS SCIENCE↗

Data‐Efficient Generation of Synthetic Microstructures of Polymer‐Bonded Energetic Material With Fine‐Tuned Stable Diffusion

Among current deep learning approaches for synthetic image generation, diffusion-based models stand out in terms of algorithmic stability and ability to retain high-fidelity image features with detailed resolution. Here, in this work, we employ Dreambooth, a method for fine-tuning Stable Diffusion, on X-ray CT images of microstructure of the polymer-bonded form (PBX) of a commonly used high explosive, Pentaerythritol tetranitrate (PETN), which yields generative models for creating synthetic PBX images. The models developed here represent five classes (or ‘lots’) of microstructures and demonstrate successful generation of images of each class with high fidelity, as verified by computed classification accuracy of ∼ 94% or higher. Data augmentation afforded by such image synthesis can be used to more reliably decipher underlying statistics, build processing-structure correlations, recognize off-normal structural anomalies, and identify age-related changes. Ideas related to converting image data into appropriate density mapping and performing mesoscale simulation or surrogate modeling of detonation are also discussed.

Dreambooth↗

Pt Nanoparticle Disintegration at Oxide Interfaces Enhances CO Oxidation Catalysis

Understanding how supported metal nanoparticles dynamically evolve under reaction conditions is critical for controlling their catalytic function. Here, the mechanism behind the dynamic disintegration of Pt nanoparticles (NPs) supported on CeOx-TiO2 (CT) during CO oxidation is elucidated, leading to the formation of single atoms (SAs) and/or sub-nanometer clusters. Density functional theory (DFT) calculations reveal that strong Pt-CO interactions weaken Pt─Pt cohesion, while electronic coupling between Pt and Ce ions stabilizes Pt-CO* intermediates at the oxide interface. Surface oxygen vacancies kinetically trap Pt-CO*, but the vacancies are replenished under oxygen-rich conditions, enabling Pt-CO* surface diffusion and subsequent structural reorganization. In situ spectroscopic analyses confirm the oxygen-driven transformation of Pt NPs, correlating with a threefold increase in mass-specific activity at 150 °C. These findings demonstrate that interfacial oxygen dynamics and metal-support interactions can be leveraged to induce nanoparticle disintegration and optimize catalytic performance, highlighting the catalytic potential of interface-engineered Pt nanostructures.

CO oxidation↗

A combination interferometric and morphological image processing approach to rapid quality assessment of additively manufactured cellular truss core components

Advanced manufacturing (AM) processes such as laser powder bed fusion (LPBF) are increasingly capable of fabricating components with useful and unprecedented mechanical properties by incorporating complex internal bracing structures. From the standpoint of quality control and assessment, however, internally complex assemblies present significant build-verification challenges. Here we propose a hybrid approach to the inspection involving the application of computer-aided speckle interferometry (CASI) and morphological image processing as a rapid, inexpensive, and facile method for AM quality control. The described methodology has low capital equipment costs, is full-field and non-contact, can be used in an industrial setting, and has very low requirements in terms of operator training and expertise. Consisting primarily of the combination of image processing software with a simple optical system of variable sensitivity, the method is shown to be effective for inspection of a titanium honeycomb component subjected to differential pressure. Results are compared to those achieved with computed tomography (CT), immersion ultrasound testing (UT), and optical holographic interferometry. Here we propose several possible processing strategies for automated quality assessment based on this powerful hybrid approach.

36 MATERIALS SCIENCE↗

It’s Not What You Take Up, It’s What You Keep: How Discoveries from Diverse Disciplines Directed the Development of the FDG PET/CT Scan

Although imaging glucose metabolism with positron emission tomography combined with X-ray CT (FDG-PET/CT) has become a standard diagnostic modality for the discovery and surveillance of malignant tumors and inflammatory processes, its origins extend back to more than a century of notable discoveries in the fields of inorganic and organic chemistry, nuclear physics, mathematics, biochemistry, solute transport physiology, metabolism, and imaging, accomplished by pioneering and driven investigators, of whom at least ten were recipients of the Nobel Prize. These tangled and diverse roots eventually coalesced into the FDG-PET/CT method, that through its many favorable characteristics inherent in the isotope used ( 18 F), the accurate imaging derived from coincidence detection of positron annihilation radiation combined with computed tomography, and the metabolic trapping of 2-deoxy-2-[ 18 F] fluoro-d-glucose (FDG) in tissues, provides safety, sensitivity, and specificity for tumor and inflammation detection. Here, the authors hope that this article will increase the appreciation among its readers of the insight, creativity, persistence, and drive of the many investigators who made this technique possible. This article is followed by a review of the many applications of FDG-PET/CT to the gastrointestinal tract and hepatobiliary system (Mandelkern in Dig Dis Sci 2022)

2-DG↗

A deep learning framework for layer-wise porosity prediction in metal powder bed fusion using thermal signatures

Abstract Part quality manufactured by the laser powder bed fusion process is significantly affected by porosity. Existing works of process–property relationships for porosity prediction require many experiments or computationally expensive simulations without considering environmental variations. While efforts that adopt real-time monitoring sensors can only detect porosity after its occurrence rather than predicting it ahead of time. In this study, a novel porosity detection-prediction framework is proposed based on deep learning that predicts porosity in the next layer based on thermal signatures of the previous layers. The proposed framework is validated in terms of its ability to accurately predict lack of fusion porosity using computerized tomography (CT) scans, which achieves a F1-score of 0.75. The framework presented in this work can be effectively applied to quality control in additive manufacturing. As a function of the predicted porosity positions, laser process parameters in the next layer can be adjusted to avoid more part porosity in the future or the existing porosity could be filled. If the predicted part porosity is not acceptable regardless of laser parameters, the building process can be stopped to minimize the loss.

42 ENGINEERING↗

Expert Text Analysis in the Inclusion of History and Philosophy of Science in Higher Education

The history and philosophy of science (HPS) plays a special role in education. An elective HPS course onthe philosophy of scientific experimentation for young scientists and graduate students of natural scienceis presented. The course bears a pragmatic character, and its main aims include the development of criticalthinking (CT), familiarization with philosophical problems in the relevant areas of knowledge, and thecultivation of a taste for reflective, critical analysis, both individual and group-based, which contributes todeeper understanding of the features of scientific practice in the context of modern complex groupcooperation. Students are offered a classical HPS program that included debates on the relationship betweenempiricism and rationalism, the role of Kant’s transcendental philosophy, modern topics associated withthe practical success of rationalism in the emergence of modern natural science, and the theory-ladennessof experimentation. Particular attention during the course is paid to the problems of megascience, theinclusion of which is justified by the specifics of the students’ engagement with science, technology,engineering, and mathematics (STEM). Emphasis is placed on the structure and typology of the collectivesubject in the modern educational process as well as in experimental practice. Lessons on the methodologyof expert text analysis (META), which are aimed at the development of critical thinking skills and thecreation of an interdisciplinary discussion space, are included in the course and relied on the example ofthe history and philosophy of high energy physics to motivate professional reflection. META classesincluded in the course prepare graduate students for teamwork in big science, proto-megascience, andmegascience. The course offers practical recommendations that could be applied to students’ own researchand could be useful for practitioners.

99 GENERAL AND MISCELLANEOUS↗

Path-Integrated X-Ray Images for Multi-Surface Digital Image Correlation (PI-DIC)

X-ray imaging offers unique possibilities for Digital Image Correlation (DIC), opening the door for full-field deformation measurements of a test article in complex environments where optical DIC suffers severe biases or is impossible. While X-ray DIC has been performed in the past with standard DIC codes designed for optical images, the path-integrated nature of X-ray images places constraints on the experimental setup, predominantly that only a single surface of interest moves/deforms. These requirements are difficult to realize for many practical situations and limit the amount of information that can be garnered in a single test. Other X-ray based diagnostics such as Digital Volume Correlation (DVC) and Projection DVC (P-DVC) overcome these obstacles, but DVC is limited to quasi-static tests, and both DVC and P-DVC necessitate high-resolution computed tomography (CT) scan(s) and often require a potentially invasive pattern throughout the volume of the specimen. Here this work presents a novel approach to measure time-resolved displacements and strains on multiple surfaces from a single series of 2D, path-integrated (PI) X-ray images, called PI-DIC. The principle of optical flow or conservation of intensity—the foundation of DIC—was reframed for path-integrated images, for an exemplar setup comprised of two plates moving and deforming independently. Synthetic images were generated for rigid translations, rigid rotations, and uniform stretches, where each plate underwent a unique motion/deformation. Experimental specimens were fabricated (either an aluminum plate with tantalum features or a plastic plate with steel features) and the two specimens were independently translated. PI-DIC was successfully demonstrated with the synthetic images and validated with the experimental images. Prescribed displacements were recovered for each plate from the single set of path-integrated, deformed images. Errors were approximately 0.02 px for the synthetic images with 1.5% image noise, and 0.05 px for the experimental images. These results provide the foundation for PI-DIC to measure motion and deformation of multiple, independent surfaces with subpixel accuracy from a single series of path-integrated X-ray images.

47 OTHER INSTRUMENTATION↗

Evaluation of desiccation cracking characteristics of inorganic micro-fiber-reinforced engineered barrier material (IMEBM) for geological repository

Abstract Buffer material is crucial for the engineering barrier system to dispose of high-level radioactive waste in a geological repository. A reliable buffer material should be able to maintain good sealing characteristics and minimize desiccation cracking. In this study, the effectiveness of inorganic fiber-reinforced engineering barrier material in reducing desiccation cracks in bentonite was evaluated via desiccation tests, image analysis, and air permeability tests. The effects of fiber type (E-glass fiber and basalt fiber) and fiber content (0.0%, 0.5%, 1.0%, 1.5%, 3.0%, and 5.0% of dry weight of the bentonite) on the development of desiccation cracks in the fiber–bentonite mixtures with the same given initial moisture content were evaluated. The results indicated that the addition of fibers could significantly reduce the crack size and area in bentonite during the drying. Basalt fibers showed a slightly better reinforcement effect than E-glass fibers when the fiber content was lower than 3.0%. The addition of fibers prevented the development of penetrating cracks and significantly reduced the permeability of the bentonite after drying. The permeabilities of basalt fiber- and E-glass fiber-reinforced bentonite composites with 3% reinforcement were 5.81 × 10 –11 m 2 and 7.24 × 10 –11 m 2 , respectively, which were 64 and 51 times smaller than that of pure bentonite. X-ray–CT observation of the internal structure of the samples after drying showed that the addition of fibers significantly changed the crack morphology and potentially increased the tortuosity.

Feng, Yuan↗

Near-Surface Layer Perforations as Precursors to Fracture in Accumulative Roll Bonding of a Multilayered Metal Composite

We use micro-computed tomography (µ-CT) to characterize the sizes, shapes, and locations of layer perforation (LP) defects in laminates of copper (Cu) and tantalum (Ta) processed by accumulative roll bonding (ARB). One—termed Cu/Ta—was processed from an initial stacking of seven alternating Cu and Ta sheets, with the exterior sheets being Cu. In the other—termed Ta/Cu—the exterior sheets are Ta. Cu/Ta remained intact during processing and exhibits an approximately uniform spatial distribution of LPs. By contrast, Ta/Cu fractured by longitudinal splitting. LPs in this latter sample are concentrated near the sample surfaces. Moreover, their density increases with decreasing distance to the fracture surface. Furthermore, these findings show that materials undergoing ARB may remain intact, despite profuse formation of LPs, provided that the LPs are uniformly distributed. However, a non-uniform distribution of LPs is correlated with longitudinal splitting.

36 MATERIALS SCIENCE↗

Multiscale mechanical design of the lightweight, stiff, and damage-tolerant cuttlebone: A computational study

Cuttlebone, the endoskeleton of cuttlefish, offers an intriguing biological structural model for designing low-density cellular ceramics with high stiffness and damage tolerance. Cuttlebone is highly porous (porosity ~93%) and lightweight (density less than 20% of seawater), constructed mainly by brittle aragonite (95 wt%), but capable of sustaining hydrostatic water pressures over 20 atmospheres and exhibits energy absorption capability under compression comparable to many metallic foams (~4.4 kJ/kg). Here, in this work, we computationally investigate how such remarkable mechanical efficiency is enabled by the multiscale structure of cuttlebone. Using the common cuttlefish, Sepia Officinalis, as a model system, we first conducted high-resolution synchrotron micro-computed tomography (µ-CT) and quantified the cuttlebone's multiscale geometry, including the 3D asymmetric shape of individual walls, the wall assembly patterns, and the long-range structural gradient of walls across the entire cuttlebone (ca. 38 chambers). The acquired 3D structural information enables systematic finite-element simulations, which further reveal the multiscale mechanical design of cuttlebone: at the wall level, wall asymmetry provides optimized energy absorption while maintaining high structural stiffness; at the chamber level, variation of walls (number, pattern, and waviness amplitude) contributes to progressive damage; at the entire skeletal level, the gradient of chamber heights tailors the local mechanical anisotropy of the cuttlebone for reduced stress concentration. Our results provide integrated insights into understanding the cuttlebone's multiscale mechanical design and provide useful knowledge for the designs of lightweight cellular ceramics.

36 MATERIALS SCIENCE↗

Multiscale porosity characterization in additively manufactured polymer nanocomposites using micro-computed tomography

Extrusion-based additive manufacturing (AM) of polymer composites exhibits complex thermally driven phenomena that introduce severe discontinuities in the internal structure across length scales, especially voids or porosity. This study utilizes a high-throughput porosity characterization technique to analyze large datasets from numerous micro-computed tomography (mu CT) scans to capture the influence of AM print parameters on the size, shape, and location of porosity across multiple print layers (up to a few cm) on fused granular fabrication (FGF) printers. The materials investigated include nanocomposite formulations based on commercially relevant nylon-12 and polyether ketone ketone (PEKK) materials comprising nano- or micro- sized fillers. The estimated global porosity follows an inverse linear correlation against the bulk density of the printed samples. Increasing the extrusion multiplier (EM) and the nozzle temperature while decreasing the print speeds reduces the global porosity. Outlier analyses (local porosity morphology) show that faster print speeds and higher extrusion rates result in long, slender inter-layer voids, while lower nozzle temperatures lead to large, symmetrical, inter-bead voids (at the bead junction). Lack of active chamber temperature increases inter-layer and intra-bead voids with a two-fold increase in global porosity. Overall, the micro filler-reinforced composites exhibit higher global porosity than nanofiller-reinforced composites, which is attributed to the increased mismatch in the thermal expansion coefficient between the filler and the polymers used in the study.

36 MATERIALS SCIENCE↗

Rapid determination of supercritical CO 2 and brine relative permeability using an unsteady-state flow method

In this study, relative permeability of supercritical CO 2 (scCO 2 ) and brine was determined in reactive and non-reactive rock cores using a combination of unsteady-state methodology and computed tomography. Experiments were conducted using a medical grade CT scanner to determine saturation using a custom Python script. The saturation and differential pressure across the core were then used to derive four empirical constants to calculate relative permeability. This methodology increases temporal efficiency while reducing experimental complexity. Additionally, we show that the method can be used to determine scCO 2 relative permeability in a wide range of lithologies and flow rates, and with the ability to account for matrix dissolution during scCO 2 flooding.

54 ENVIRONMENTAL SCIENCES↗