Time‐resolved three‐dimensional (3D) X‐ray imaging techniques rely on obtaining 3D information for each time point and are crucial for materials‐science applications in academia and industry. ...Standard 3D X‐ray imaging techniques like tomography and confocal microscopy access 3D information by scanning the sample with respect to the X‐ray source. However, the scanning process limits the temporal resolution when studying dynamics and is not feasible for many materials‐science applications, such as cell‐wall rupture of metallic foams. Alternatives to obtaining 3D information when scanning is not possible are X‐ray stereoscopy and multi‐projection imaging, but these approaches suffer from limited volumetric information as they only acquire a very small number of views or projections compared to traditional 3D scanning techniques. Here, we present optimized neural implicit X‐ray imaging (ONIX), a deep‐learning algorithm capable of retrieving a continuous 3D object representation from only a small and limited set of sparse projections. ONIX is based on an accurate differentiable model of the physics of X‐ray propagation. It generalizes across different instances of similar samples to overcome the limited volumetric information provided by limited sparse views. We demonstrate the capabilities of ONIX compared to state‐of‐the‐art tomographic reconstruction algorithms by applying it to simulated and experimental datasets, where a maximum of eight projections are acquired. ONIX, although it does not have access to any volumetric information, outperforms unsupervised reconstruction algorithms, which reconstruct using single instances without generalization over different instances. We anticipate that ONIX will become a crucial tool for the X‐ray community by (i) enabling the study of fast dynamics not possible today when implemented together with X‐ray multi‐projection imaging and (ii) enhancing the volumetric information and capabilities of X‐ray stereoscopic imaging.
Advancing time‐resolved X‐ray imaging with optimized neural implicit X‐ray imaging (ONIX): A 3D unsupervised approach for high‐quality reconstruction from extremely sparse projections (less than 10). ONIX uses an accurate physical model and prior knowledge from similar instances to achieve an accurate continuous representation of the object.
A recurring question is whether rating scales should be considered metrically scaled or merely ordinally scaled. This has direct implications for the permissible statistical procedures for ...significance testing. Based on the results of a simulation study, it is shown that the use of parametric procedures for rating scales has distinct advantages over the nonparametric alternatives. It is also shown that the parametric procedures are robust to violations of the assumption of normality, which only result in a modest loss of power compared with continuous variables. This loss should be taken into account when calculating the optimal sample size. The results suggest that sample sizes about 25% larger should be chosen for discrete rating scales than for continuous variables.
A simulation study shows that the use of parametric procedures for rating scales has distinct advantages over the nonparametric alternatives. It is also shown that parametric procedures are robust to violations of the normality assumption, which result in only a modest loss of power compared to continuous variables.
Zinc/air batteries are convenient energy storage devices for both small and massive applications. While future perspectives indicate the need for low‐cost components and sustainable fabrication ...processes, the battery performance is in part controlled by the kinetics of the oxygen reduction reaction (ORR), which typically involves transition metals as catalysts. In this context, we prepare a series of metal‐free water‐based carbon inks, which are tested for their catalytic performance, once deposited on a gas‐diffusion substrate, in the air cathode of a simple battery prototype. The inks contain a variety of well‐defined carbon nanomaterials and additives, exhibiting different physicochemical properties that critically influence the interaction with the gas diffusion hydrophobic substrate. The intrinsic ORR catalytic activity of the ink material is also analyzed on a glassy carbon electrode by the rotating ring‐disc electrode (RRDE) method and specific capacitance measurements. The discharge capacity on our zinc/air battery prototype correlates well with the intrinsic catalytic activity in the RRDE. However, only the activity in the RRDE does not actually assure the performance on the commercial cathode of the prototype, since other chemical compatibility issues play a role. Thus, we highlight the importance of catalyst testing, not only on the RRDE but also under realistic device conditions.
Electrochemical key parameters for different carbon nanotube compositions and typologies represented by colors, correlated to their respective performances in a zinc–air battery.
Robotic concrete extrusion is a novel additive manufacturing process (three‐dimensional concrete printing) and is part of a continuously digitally controlled value chain. According to the state of ...the art, concrete is considered to be an isotropic material due to the manufacturing process. However, for the additive manufacturing process, the isotropic approach has to be reconsidered due to the layered structure. It can be assumed that due to the layered structure, the material properties vary depending on the deposition direction and the geometry of the layers. The aim of the work was to record the material‐technical characteristics of extruded elements manufactured according to standards in comparison with concrete recipes. Process‐related influences on the mechanical parameters of additively manufactured concrete elements were examined and evaluated in more detail. Based on the findings obtained, the dimensioning, design and measurement of components can be carried out and thus guidelines for components can be derived. With these derived guidelines, the material utilization and economic efficiency can be improved.
The focus of this work is on the material properties of standard‐compliant samples compared to additively manufactured concrete elements. Process‐related influences on the mechanical parameters of additively manufactured concrete elements were examined and evaluated in more detail. The figure shows research facility for 3D concrete printing at the TU Chemnitz.
