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The M13 bacteriophage, a nature-inspired environmentally friendly biomaterial, is used as a perovskite crystal growth template and a grain boundary passivator in perovskite solar cells. The amino groups and carboxyl groups of amino acids on the M13 bacteriophage surface function as Lewis bases, interacting with the perovskite materials. The M13 bacteriophage-added perovskite films show a larger grain size and reduced trap-sites compared with the reference perovskite films. In addition, the existence of the M13 bacteriophage induces light scattering effect, which enhances the light absorption particularly in the long-wavelength region around 825 nm. Both the passivation effect of the M13 bacteriophage coordinating to the perovskite defect sites and the light scattering effect intensify when the M13 virus-added perovskite precursor solution is heated at 90 °C prior to the film formation. Heating the solution denatures the M13 bacteriophage by breaking their inter- and intra-molecular bondings. The denatured M13 bacteriophage-added perovskite solar cells exhibit an efficiency of 20.1% while the reference devices give an efficiency of 17.8%. The great improvement in efficiency comes from all of the three photovoltaic parameters, namely short-circuit current, open-circuit voltage, and fill factor, which correspond to the perovskite grain size, trap-site passivation, and charge transport, respectively.

Manipulation of grain boundaries in polycrystalline perovskite is an essential consideration for both the optoelectronic properties and environmental stability of solar cells as the solution-processing of perovskite films inevitably introduces many defects at grain boundaries. Though small molecule-based additives have proven to be effective defect passivating agents, their high volatility and diffusivity cannot render perovskite films robust enough against harsh environments. Here we suggest design rules for effective molecules by considering their molecular structure. From these, we introduce a strategy to form macromolecular intermediate phases using long chain polymers, which leads to the formation of a polymer-perovskite composite cross-linker. The cross-linker functions to bridge the perovskite grains, minimizing grain-to-grain electrical decoupling and yielding excellent environmental stability against moisture, light, and heat, which has not been attainable with small molecule defect passivating agents. Consequently, all photovoltaic parameters are significantly enhanced in the solar cells and the devices also show excellent stability.

Water electrolyzers powered by renewable energy are emerging as clean and sustainable technology for producing hydrogen without carbon emissions. Specifically, anion exchange membrane (AEM) electrolyzers utilizing non‐platinum group metal (non‐PGM) catalysts have garnered attention as a cost‐effective method for hydrogen production, especially when integrated with solar cells. Nonetheless, the progress of such integrated systems is hindered by inadequate water electrolysis efficiency, primarily caused by poor oxygen evolution reaction (OER) electrodes. To address this issue, a NiFeCo─OOH has developed as an OER electrocatalyst and successfully demonstrated its efficacy in an AEM electrolyzer, which is powered by renewable electricity and integrated with a silicon solar cell. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is characterized by multiple, intertwined pathological features, including amyloid-β (Aβ) aggregation, metal ion dyshomeostasis, and oxidative stress. We report a novel compound (ML) prototype of a rationally designed molecule obtained by integrating structural elements for Aβ aggregation control, metal chelation, reactive oxygen species (ROS) regulation, and antioxidant activity within a single molecule. Chemical, biochemical, ion mobility mass spectrometric, and NMR studies indicate that the compound ML targets metal-free and metal-bound Aβ (metal-Aβ) species, suppresses Aβ aggregation in vitro, and diminishes toxicity induced by Aβ and metal-treated Aβ in living cells. Comparison of ML to its structural moieties (i.e., 4-(dimethylamino)phenol (DAP) and (8-aminoquinolin-2-yl)methanol (1)) for reactivity with Aβ and metal-Aβ suggests the synergy of incorporating structural components for both metal chelation and Aβ interaction. Moreover, ML is water-soluble and potentially brain permeable, as well as regulates the formation and presence of free radicals. Overall, we demonstrate that a rational structure-based design strategy can generate a small molecule that can target and modulate multiple factors, providing a new tool to uncover and address AD complexity.

Fat-soluble vitamins (vitamin A, D, E, and K) assume a pivotal role in maintaining human homeostasis by virtue of their enzymatic functions. The daily inclusion of these vitamins is imperative to the upkeep of various physiological processes including vision, bone health, immunity, and protection against oxidative stress. Current research highlights fat-soluble vitamins as potential therapeutics for human diseases, especially cancer. Fat-soluble vitamins exert their therapeutic effects through multiple pathways, including regulation of matrix metalloproteinases' (MMPs) expression and enzymatic activity. As MMPs have been reported to be involved in the pathology of various diseases, such as cancers, cardiovascular diseases, and neurological disorders, regulating the expression and/or activity of MMPs could be considered as a potent therapeutic strategy. Here, we summarize the properties of fat-soluble vitamins and their potential as promising candidates capable of effectively modulating MMPs through multiple pathways to treat human diseases. [ABSTRACT FROM AUTHOR]

It has been claimed that a focused word may project its focus to a syntactic constituent larger than the focused item, under what are known as Focus Projection principles (Selkirk 1995; Rochemont 1998). Engdahl and Vallduvi (1996) rejected this purely syntax-based approach and proposed considering the interactions between the grammatical function and the types of an argument. Chung, Kim, and Sells (to appear) applied Engdahl and Valduvi’s theory to Korean and claimed that in Korean only a theme argument, but not an oblique argument (I.O or Locative PP), can project its focus to the Verb Phrase. This paper examines how VP focus is realized in Korean and tests Chung et al.’s claim that the types and the order of arguments can affect the focus projection (especially ‘VP focus’). The results show that there is no sensitivity to argument type, word order, or the length of VP in projecting the domain of focus to VP in Korean. Regardless of these factors, VP focus was prosodically marked by boosting the prominence of all words inside the VP, with the VP-initial word being the most prominent. Our data suggest that focus projection rules can be eliminated as proposed in Büring (2003).

Identifying the patterns of defective chips in wafer bin maps (WBMs) in semiconductor manufacturing processes is crucial because different defect patterns correspond to different root causes of process failures. Recently, mixed-type defect patterns (i.e., multiple defect patterns in a single wafer) have become increasingly common owing to the increased complexity of semiconductor manufacturing processes. Previous methods for classifying mixed-type defect patterns in WBMs focused on outputting only the class labels of the defect patterns and not their locations, although location information of the defect patterns is useful for tracking the root causes of failure and improving processes. Moreover, most previous methods used only labeled WBM data, although a larger quantity of unlabeled WBM data are more accessible because of the costly process of label annotation. Therefore, in this paper, we propose a semi-supervised learning method for classifying mixed-type defect patterns and detecting their locations simultaneously using both labeled and unlabeled WBM data. The proposed method extends a recent unsupervised object detection method called Attend-Infer-Repeat in a semi-supervised manner to perform object detection and classification simultaneously. The performance of the proposed method is verified using WBM datasets of different sizes. The results demonstrate the effectiveness of the proposed method for classification and location detection. [ABSTRACT FROM AUTHOR]