Activation of LSCF–YSZ interface by cobalt migration during electrolysis operation in solid oxide electrolysis cells

High-temperature water electrolysis through solid oxide electrolysis cells (SOEC) will play a key role in building a hydrogen economy in the future. However, the delamination between the air electrode and the electrolyte remains a critical issue to be addressed. Previously, it was hypothesized that Co migration may improve the catalytic activity of the SrZrO₃ second phase at the LSCF-YSZ interface, eventually leading to the delamination. In this work, the LSCF-YSZ interfaces sintered at different temperatures were examined in detail. The activation behaviors of the LSCF electrodes upon application with electrolysis current were characterized under different conditions. Further, samples containing purposely added SrZrO₃ interlayer with and without cobalt were fabricated and compared. The activation process is less significant for the sample with cobalt-added SrZrO₃ interlayer than the sample with pure SrZrO₃ layer, supporting the hypothesis that Co migration may lead to the activation behavior.     

Feature selection methods for root-cause analysis among top-level product attributes

Manufacturing companies not only strive to deliver flawless products but also monitor product failures in the field to identify potential quality issues. When product failures occur, quality engineers must identify the root cause to improve any affected product and process. This root-cause analysis can be supported by feature selection methods that identify relevant product attributes, such as manufacturing dates with an increased number of product failures. In this paper, we present different methods for feature selection and evaluate their ability to identify relevant product attributes in a root-cause analysis. First, we compile a list of feature selection methods. Then, we summarize the properties of product attributes in warranty case data and discuss these properties regarding the challenges they pose for machine learning algorithms. Next, we simulate datasets of warranty cases, which emulate these product properties. Finally, we compare the feature selection methods based on these simulated datasets. In the end, the univariate filter information gain is determined to be a suitable method for a wide range of applications. The comparison based on simulated data provides a more general result than other publications, which only focus on a single use case. Due to the generic nature of the simulated datasets, the results can be applied to various root-cause analysis processes in different quality management applications and provide a guideline for readers who wish to explore machine learning methods for their analysis of quality data.     

Large domain-wall currents in epitaxial Au/BiFeO3/SrRuO3 thin-film capacitors with modulated oxygen vacancy and wall densities

Large domain wall (DW) conductivity in an insulating ferroelectric plays an important role in the future nanosensors and nonvolatile memories. However, the wall current was usually too small to drive high-speed memory circuits and other agile nanodevices requiring high output-powers. Here, a large domain-wall current of 67.8 μA in a high on/off ratio of ~4460 was observed in an epitaxial Au/BiFeO₃/SrRuO₃ thin-film capacitor with the minimized oxygen vacancy concentration. The studies from read current-write voltage hysteresis loops and piezo-response force microscope images consistently showed remaining of partially unswitched domains after application of an opposite poling voltage that increased domain wall density and wall current greatly. A theoretical model was proposed to explain the large wall current. According to this model, the domain reversal occurs with the appearance of head-to-head and tail-to-tail 180° domain walls (DWs), resulting in the formation of highly conductive wall paths. As the applied voltage increased, the domain-wall number increased to enhance the on-state current, in agreement with the measurements of current-voltage curves. This work paves a way to modulate DW currents within epitaxial Au/BiFeO₃/SrRuO₃ thin-film capacitors through the optimization of both oxygen vacancy and domain wall densities to achieve large output powers of modern domain-wall nanodevices.     

Revealing Electrical-Poling-Induced Polarization Potential in Hybrid Perovskite Photodetectors

Despite recent rapid advances in metal halide perovskites for use in optoelectronics, the fundamental understanding of the electrical-poling-induced ion migration, accounting for many unusual attributes and thus performance in perovskite-based devices, remain comparatively elusive. Herein, the electrical-poling-promoted polarization potential is reported for rendering hybrid organic–inorganic perovskite photodetectors with high photocurrent and fast response time, displaying a tenfold enhancement in the photocurrent and a twofold decrease in the response time after an external electric field poling. First, a robust meniscus-assisted solution-printing strategy is employed to facilitate the oriented perovskite crystals over a large area. Subsequently, the electrical poling invokes the ion migration within perovskite crystals, thus inducing a polarization potential, as substantiated by the surface potential change assessed by Kelvin probe force microscopy. Such electrical-poling-induced polarization potential is responsible for the markedly enhanced photocurrent and largely shortened response time. This work presents new insights into the electrical-poling-triggered ion migration and, in turn, polarization potential as well as into the implication of the latter for optoelectronic devices with greater performance. As such, the utilization of ion-migration-produced polarization potential may represent an important endeavor toward a wide range of high-performance perovskite-based photodetectors, solar cells, transistors, scintillators, etc.     

A new reverse reduce-error ensemble pruning algorithm

Although greedy algorithms possess high efficiency, they often receive suboptimal solutions of the ensemble pruning problem, since their exploration areas are limited in large extent. And another marked defect of almost all the currently existing ensemble pruning algorithms, including greedy ones, consists in: they simply abandon all of the classifiers which fail in the competition of ensemble selection, causing a considerable waste of useful resources and information. Inspired by these observations, an interesting greedy Reverse Reduce-Error (RRE) pruning algorithm incorporated with the operation of subtraction is proposed in this work. The RRE algorithm makes the best of the defeated candidate networks in a way that, the Worst Single Model (WSM) is chosen, and then, its votes are subtracted from the votes made by those selected components within the pruned ensemble. The reason is because, for most cases, the WSM might make mistakes in its estimation for the test samples. And, different from the classical RE, the near-optimal solution is produced based on the pruned error of all the available sequential subensembles. Besides, the backfitting step of RE algorithm is replaced with the selection step of a WSM in RRE. Moreover, the problem of ties might be solved more naturally with RRE. Finally, soft voting approach is employed in the testing to RRE algorithm. The performances of RE and RRE algorithms, and two baseline methods, i.e., the method which selects the Best Single Model (BSM) in the initial ensemble, and the method which retains all member networks of the initial ensemble (ALL), are evaluated on seven benchmark classification tasks under different initial ensemble setups. The results of the empirical investigation show the superiority of RRE over the other three ensemble pruning algorithms.     

Chemical-Shift Perturbations Reflect Bile Acid Binding to Norovirus Coat Protein: Recognition Comes in Different Flavors

Bile acids have been reported as important cofactors promoting human and murine norovirus (NoV) infections in cell culture. The underlying mechanisms are not resolved. Through the use of chemical shift perturbation (CSP) NMR experiments, we identified a low-affinity bile acid binding site of a human GII.4 NoV strain. Long-timescale MD simulations reveal the formation of a ligand-accessible binding pocket of flexible shape, allowing the formation of stable viral coat protein–bile acid complexes in agreement with experimental CSP data. CSP NMR experiments also show that this mode of bile acid binding has a minor influence on the binding of histo-blood group antigens and vice versa. STD NMR experiments probing the binding of bile acids to virus-like particles of seven different strains suggest that low-affinity bile acid binding is a common feature of human NoV and should therefore be important for understanding the role of bile acids as cofactors in NoV infection.     

Expression of Main Toll-Like Receptors in Patients with Different Types of Colorectal Polyps and Their Relationship with Gut Microbiota

Abnormal activation of Toll-like receptor (TLRs) signaling can result in colon cancer development. The aim of this study was to investigate the expression of important TLRs in different histological types of colorectal polyps and evaluate their relationship with intestinal microbiota. The expression levels of TLR2, 3, 4, and 5 were analyzed in intestinal biopsy specimens of 21 hyperplastic polyp (HP), 16 sessile serrated adenoma (SSA), 29 tubular adenoma (TA), 21 villous/tubulovillous (VP/TVP) cases, and 31 normal controls. In addition, selected gut bacteria including Streptococcus bovis, Enterococcus faecalis, Enterotoxigenic Bacteroides fragilis (ETBF), Fusobacterium nucleatum, Porphyromonas spp., Lactobacillus spp., Roseburia spp., and Bifidobacterium spp. were quantified in fecal samples using absolute qRT PCR, and, finally, the association between TLRs and these gut microbiota- was evaluated by Spearman’s correlation coefficient. Higher expression of TLR2 and TLR4 in VP/TVP and TA, and lower expression levels of TLR3 and TLR5 in all type of polyps were observed. The differences in TLR expression patterns was not only dependent on the histology, location, size, and dysplasia grade of polyps but also related to the intestinal microbiota patterns. TLR2 and TLR4 expression was directly associated with the F. nucleatum, E. faecalis, S. bovis, Porphyromonas, and inversely to Bifidobacterium, Lactobacillus, and Roseburia quantity. Furthermore, TLR3 and TLR5 expression was directly associated with Bifidobacterium, Roseburia, and Lactobacillus quantity. Our results suggest a possible critical role of TLRs during colorectal polyp progression. An abnormal regulation of TLRs in relation to gut microbial quantity may contribute to carcinogenesis.     

Supramolecular Zn(II)-Dipicolylamine-Azobenzene-Aminocyclodextrin-ATP Complex: Design and ATP Recognition in Water

Cyclodextrins (CyDs) are water-soluble host molecules possessing a nanosized hydrophobic cavity. In the realm of molecular recognition, this cavity is used not only as a recognition site but also as a reaction medium, where a hydrophobic sensor recognizes a guest molecule. Based on the latter concept, we have designed a novel supramolecular sensing system composed of Zn(II)-dipicolylamine metal complex-based azobenzene (1-Zn) and 3A-amino-3A-deoxy-(2AS,3AS)-γ-cyclodextrin (3-NH₂-γ-CyD) for sensing adenosine-5′-triphosphate (ATP). 1-Zn showed redshifts in the UV-Vis spectra and induced circular dichroism (ICD) only when both ATP and 3-NH₂-γ-CyD were present. Calculations of equilibrium constants indicated that the amino group of 3-NH₂-γ-CyD was involved in the formation of supramolecular 1-Zn/3-NH₂-γ-CyD/ATP. The Job plot of the ICD spectral response revealed that the stoichiometry of 1-Zn/3-NH₂-γ-CyD/ATP was 2:1:1. The pH effect was examined and 1-Zn/3-NH₂-γ-CyD/ATP was most stable in the neutral condition. The NOESY spectrum suggested the localization of 1-Zn in the 3-NH₂-γ-CyD cavity. Based on the obtained results, the metal coordination interaction of 1-Zn and the electrostatic interaction of 3-NH₂-γ-CyD were found to take place for ATP recognition. The “reaction medium approach” enabled us to develop a supramolecular sensing system that undergoes multi-point interactions in water. This study is the first step in the design of a selective sensing system based on a good understanding of supramolecular structures.