Parallel Pattern Research Articles

Design of central symmetric lattice structure for ocean engineering based on fluid-solid-interaction

Some structures that constitute underwater vehicles and other ocean engineering structures, such as the shell of underwater vehicles, shafting of power systems, compressor impellers and propeller hubs, all have central symmetric or rotationally symmetric cross sections. In this paper, a kind of central symmetric lattice is designed. The lightweight design of the above structure with this lattice can significantly reduce the weight of the structure on the premise of reducing the static response of the structure. Combined with the ANSYS Parameter Design Language (APDL), the homogenization method is used to analyze the static response of the rotationally symmetric lattice structure and the parallel pattern lattice structure under pressure. The fluid load (pressure) of impeller is calculated by CFX. The results show that the structural stress of the central symmetric lattice structures with the same volume fraction is smaller than that of parallel pattern lattice under the same load when the rotationally symmetric structures have the same form. The application of the homogenization method proves that the above conclusions also improve the efficiency of the static response calculation of the central symmetric lattice structure. The design and research methods in this paper provide technical support for the realization of lightweight design of small and medium-sized underwater rotationally symmetric structures.

The Trajectories of Hepato-Biliary Indices Following Exposure to SARS-CoV-2

<i>Background</i>: The impact of SARS-CoV-2 on the hepato-biliary system is conflicting within the existing literature. Previous studies on the subject have mostly been documented among Caucasians using retrospectively-acquired data from patients with several confounding variables. Hence, the current study evaluated the trajectories of hepato-biliary biochemical indices among SARS-CoV-2-infected Nigerians who had no background confounding factors. <i>Methods</i>: This was a prospectively-designed longitudinal study conducted within Southern Nigeria among patients with RT-PCR-confirmed mild SARS-CoV-2 infection. All eligible participants were serially monitored/followed up before, during, and after mild SARS-CoV-2 infection using clinical/laboratory parameters to determine the impact of the virus on the hepato-biliary system. Specimen acquisition, laboratory workflow, and data management were all carried out using standardized protocols. <i>Results</i>: Among 152 studied, 46.1% had mild SARS-CoV-2 infection 5–10 days (Mean=7.5; SD:=2.19) after exposure with male predominance. Cough, malaise, and loss of taste/smell were the most predominant clinical manifestations among the confirmed mild cases. During the follow-up period, an increasing trend of hepato-biliary indices of the cholestatic pattern (with only total bilirubin and GGT reaching statistically significant threshold) in parallel with inflammatory markers (CRP, di-dimer and the neutrophil to lymphocyte ratio) was observed between 2-12 days following mild SARS-CoV-2 infection. However, no relationship was established between these cholestatic and inflammatory markers among the mild SARS-CoV-2-infected patients (p>0.05). <i>Conclusion</i>: Mild SARS-CoV-2 infection is associated with altered hepato-biliary biochemical indices of cholestatic pattern independent of SARS-CoV-2-induced inflammatory events. Incorporating hepato-biliary assessment during the initial evaluation and the use of non-hepatotoxic therapeutics during treatment is highly recommended.

Distribution of capitalized benefits from land conservation

Land conservation efforts throughout the United States sustain ecological benefits while generating wealth in the housing market through capitalization of amenities. This paper estimates the benefits of conservation that are capitalized into proximate home values and quantifies how those benefits are distributed across demographic groups. Using detailed property and household-level data from Massachusetts, we estimate that new land conservation led to $62 million in new housing wealth equity. However, houses owned by low-income or Black or Hispanic households are less likely to be located near protected areas, and hence, these populations are less likely to benefit financially. Direct study of the distribution of this new wealth from capitalized conservation is highly unequal, with the richest quartile of households receiving 43%, White households receiving 91%, and the richest White households receiving 40%, which is nearly 140% more than would be expected under equal distribution. We extend our analysis using census data for the entire United States and observe parallel patterns. We estimate that recent land conservation generated $9.8 billion in wealth through the housing market and that wealthier and White households benefited disproportionately. These findings suggest regressive and racially disparate incidence of the wealth benefits of land conservation policy.

An investigation into the effect of scanning pattern and heat treatment on the mechanical properties of Inconel 718 in the direct metal deposition process

In this study, the additive manufacturing process of Inconel 718 superalloy on a homogenous forged substrate with three different patterns is investigated, followed by studying the samples’ mechanical properties and heat treatment effect on them. After additive manufacturing, the tensile properties of the samples were investigated by form of 50%-forging specimens and 50%-additively manufactured specimens. Results showed the best tensile properties are obtained in a sample made with a circular pattern. Also, the difference in the tensile properties of the sample made parallel to the tensile axis, and the sample created in the vertical direction indicate the anisotropic behavior of the additively manufactured samples. After additive manufacturing of samples with parallel, perpendicular, and circular patterns, the ultimate strength increased by 7, 6, and 11% compared to the control sample (forging). Despite the strength increase, the ductility of the specimens decreased by 28, 20, and 11% compared to forging specimen. In the 100%-additively manufactured sample, the ultimate strength increased by 6%, and the ductility decreased by 45%. After investigating the pattern for mechanical properties, annealing heat treatment at 1080 °C for 1 h and two aging processes at 620 and 720 °C for 4 and 8 h, respectively, were performed to improve the properties and create a strengthening phase. The ductility of the sample made with a 50% circular pattern and 50% forging sample increased by 51% and 36% by annealing compared to the raw state and the control sample, respectively. Moreover, the hardness level and ductility became uniform and increased after annealing.

An Ultracompact Single‐Ferroelectric Field‐Effect Transistor Binary and Multibit Associative Search Engine

Content addressable memory (CAM) is widely used in associative search tasks due to its parallel pattern matching capability. As more complex and data‐intensive tasks emerge, it is becoming increasingly important to enhance CAM density for improved performance and better area efficiency. To reduce the area overheads, various nonvolatile memory (NVM) devices, such as ferroelectric field‐effect transistors (FeFETs), are used in CAM design. Herein, a novel ultracompact 1FeFET CAM design that enables parallel associative search and in‐memory hamming distance calculation is used, as well as a multibit CAM for exact search using the same CAM cell. The proposed CAM design leverages the 1FeFET1R structure, and compact device designs that integrate the series resistor current limiter into the intrinsic FeFET structure are demonstrated to turn the 1FeFET1R structure into an effective 1FeFET cell. A two‐step search operation of the proposed binary and multibit 1FeFET CAM array through both experiments and simulations is proposed, showing a sufficient sensing margin despite unoptimized FeFET device variation. In genome pattern matching applications, using the hyperdimensional computing paradigm, the design results in a 89.9× speedup and 66.5× improvement in energy efficiency over the state‐of‐the‐art alignment tools on GPU.

Competence Attrition: A linguistic theory of the effects of external competence acquisition for organizations

What happens to old competences in organizations when new competences are acquired? In this paper, we propose a competence attrition theory to explain the effects of acquiring new competences on previously acquired ones. While the presumed positive role of available competences for the acquisition of new competences has been the subject of extensive research, the potentially negative effect of the acquisition of external competences on the availability and use of existing competences has not been sufficiently theorized. We aim to do so by extending existing learning and absorptive capacity theories with insights from linguistics on competence attrition. Specifically, informed by parallel patterns in language acquisition and attrition, we develop a set of focused propositions on competence acquisition and attrition in organizations. We end the paper by discussing the implications of our theorizing for existing theory and research.

On the building of efficient self-adaptable health data science services by using dynamic patterns

Health data science systems are becoming key for supporting healthcare decision-making processes. However, these systems should achieve continuous data processing and adapt their behavior to changes arising in real scenarios. Nevertheless, building this type of self-adaptable systems is not trivial, as it requires integrating data analytics and artificial intelligence with cloud computing tools and security and fault tolerance applications. This produces delays in the processing of data, affecting the information delivery in decision-making processes. In this paper, we present the design and implementation of a method to build self-adaptable data science services by using dynamic patterns. This method includes two models: a construction model and a coupling model. The construction model is based on dynamic parallel patterns to create, at design time, in-memory processing structures including as many applications as needed to meet the non-functional requirements (NFRs), such as security and fault tolerance, established by healthcare organizations without affecting the efficiency of a data science system. In turn, the coupling model converts the in-memory processing structures into software blocks that are coupled with the I/O interfaces of data science systems to support the automatic and transparent continuous management of data for facing changes in the incoming workload during execution time. A prototype was implemented to create self-adaptable health data science systems including in-memory processing structures for managing spirometry studies, tomography images, and electrocardiograms. The performance evaluation showed that the dynamic patterns significantly reduced the response time required to prepare contents with NFR characteristics in comparison with solutions from the state-of-the-art such as Nextflow and Makeflow.

A (Somewhat) New Way to See and Understand the Diverse and Strategic Use of the Interrogatives in Isa 40:12–31

Abstract Interpreters predominantly identify the interrogatives in Isa 40:12–31 as Rhetorical Questions (RQs) along with a single Genuine Question. However, upon closer examination the prophet also employs another type of interrogative that operates similarly to RQs, namely Conducive Questions. The prophet creatively and strategically arranges the interrogatives into a parallel pattern. Specifically, the prophet forms two parallel interrogative sequences with each placed in two respective parallel literary sequences (vv. 12–20; 21–26) that together constitute the first section of vv. 12–31. A second literary unit (vv. 27–31) begins with a Genuine Question immediately followed by a final pair of interrogatives. The prophet utilizes the Conducive and Rhetorical Questions to intentionally lead the addressee to verbally confirm, mentally assent to, and, in certain instances, confess with the inferred answers. The prophet’s purpose with these interrogatives aims at synchronizing the theological worldviews of both communicative participants.

Simultaneous Hydrogen Bonds with Different Binding Modes: The Acceptor "Rules" but the Donor "Chooses".

This computational work studies the different hydrogen bond (HB) binding modes that can be established between neighbouring HB donors and acceptors in structures with relevance in catalysis and biology. To analyse the electronic effect on the σ-hole, unsubstituted HB donors and ones with two different substituents, an electron withdrawing (EWG), and an electron donating (EDG) group, were studied. Upon complexation, three different binding modes were observed: bifurcated, parallel, and zigzag. It was found that, as a general trend, HBs within a parallel pattern are the strongest followed by those within bifurcated and zigzag binding modes, leading to a "competition" between the last two. Similar patterns and trends have been found in experimental structures found in a search within the CSD. In conclusion, even though the HB acceptors "rule" the pattern and strength of the HB interactions within the dimers, when there is an option for different binding modes within a particular dimer, the HB donors "choose" the type of binding established.

Deep Learning MRI Reconstruction for Accelerating Turbo Spin Echo Hand and Wrist Imaging: A Comparison of Image Quality, Visualization of Anatomy, and Detection of Common Pathologies with Standard Imaging

Magnetic resonance imaging (MRI) of the hand and wrist is a routine MRI examination and takes about 15-20 minutes, which can lead to problems resulting from the relatively long scan time, such as decreased image quality due to motion artifacts and lower patient throughput. The objective of this study was to evaluate a deep learning (DL) reconstruction for turbo spin echo (TSE) sequences of the hand and wrist regarding image quality, visualization of anatomy, and diagnostic performance concerning common pathologies. Twenty-one patients (mean age: 43 ± 19 [19-85] years, 10 men, 11 female) were prospectively enrolled in this study between October 2020 and June 2021. Each participant underwent two MRI protocols: first, standard fully sampled TSE sequences reconstructed with a standard GRAPPA reconstruction (TSES) and second, prospectively undersampled TSE sequences using a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Both protocols were acquired consecutively in one examination. Two experienced MSK-imaging radiologists qualitatively evaluated the images concerning image quality, noise, edge sharpness, artifacts, and diagnostic confidence, as well as the delineation of anatomical structures (triangular fibrocartilage complex, tendon of the extensor carpi ulnaris muscle, extrinsic and intrinsic ligaments, median nerve, cartilage) using a five-point Likert scale and assessed common pathologies. Wilcoxon signed-rank test and kappa statistics were performed to compare the sequences. Overall image quality, artifacts, delineation of anatomical structures, and diagnostic confidence of TSEDL were rated to be comparable to TSES (p > 0.05). Additionally, TSEDL showed decreased image noise (4.90, median 5, IQR 5-5) compared to TSES (4.52, median 5, IQR 4-5, p < 0.05) and improved edge sharpness (TSEDL: 4.10, median 4, IQR 3.5-5; TSES: 3.57, median 4, IQR 3-4; p < 0.05). Inter- and intrareader agreement was substantial to almost perfect (κ=0.632-1.000) for the detection of common pathologies. Time of acquisition could be reduced by more than 60% with the protocol using TSEDL. Compared to TSES, TSEDL provided decreased noise and increased edge sharpness, equal image quality, delineation of anatomical structures, detection of pathologies, and diagnostic confidence. Therefore, TSEDL may be clinically relevant for hand and wrist imaging, as it reduces examination time by more than 60%, thus increasing patient comfort and patient throughput.

Implementation of mobile augmented reality on physics learning in junior high school students

Technology has an essential role in the educational field. Technology-based mobile has the potential to improve education through Augmented Reality (AR). This study investigates the effect of mobile augmented reality on physics learning achievement and students' opinions on using this technology. The study used a convergent parallel pattern from mixed-method models in which quantitative and qualitative data are collected simultaneously and analyzed independently. The study participants are 64 (7th-grade students) who are learning solar system concepts at one of the junior high schools in West Java Province, Indonesia. This study collects pre- and post-test data as quantitative data to analyze students' learning achievement using the normalized gain score. The result showed that the students using mobile augmented reality have higher criteria for learning achievement than those using textbooks. The qualitative data was collected from interviewed students after using mobile augmented reality and analyzing using descriptive analysis. The results of the student opinion state that augmented reality is a new learning environment that effectively helps them understand physics concepts, enhances students' learning achievement and helps concretize abstract concepts through visual 3D simulations. Moreover, according to the study, students find it easier to understand physics concepts after using mobile augmented reality.

Multigraph learning for parallelism discovery in sequential programs

SummaryParallelization is an optimization technique that is playing an increasingly vital role in software applications. Discovering the potential parallelism in sequential programs is of primary importance for parallelization. To this end, various tools have been created to obtain parallelizable targets by analyzing the dependencies in sequential programs. However, the majority are constructed based on manually designed dependence analysis rules. Consequently, they must follow some constraints, which limit the scope of their program analysis capability. Furthermore, constructing a dependency analysis rule is a complicated and highly sophisticated endeavor. In this study, we exploit the fact that neural network models can learn the potential features of programs to tackle the parallelism discovery task in an end‐to‐end manner. Specifically, we developed a multigraph learning architecture on top of multiple abstract code representations in a complementary manner. In the architecture, we equip code representations with different neural network models in a targeted manner, including a deep convolutional neural network for analyzing both control and data flows and a novel neural network for learning the abstract syntax trees. Experimental results obtained on a common parallelism discovery dataset indicate that the developed multigraph learning architecture can learn potential parallelism patterns in sequential programs with high accuracy and efficiency.

Evidence for ecotone speciation across an African rainforest-savanna gradient.

Accelerating climate change and habitat loss make it imperative that plans to conserve biodiversity consider species' ability to adapt to changing environments. However, in biomes where biodiversity is highest, the evolutionary mechanisms responsible for generating adaptative variation and, ultimately, new species are frequently poorly understood. African rainforests represent one such biome, as decadal debates continue concerning the mechanisms generating African rainforest biodiversity. These debates hinge on the relative importance of geographic isolation versus divergent natural selection across environmental gradients. Hindering progress is a lack of robust tests of these competing hypotheses. Because African rainforests are severely at-risk due to climate change and other anthropogenic activities, addressing this long-standing debate is critical for making informed conservation decisions. We use demographic inference and allele frequency-environment relationships to investigate mechanisms of diversification in an African rainforest skink, Trachylepis affinis, a species inhabiting the gradient between rainforest and rainforest-savanna mosaic (ecotone). We provide compelling evidence of ecotone speciation, in which gene flow has all but ceased between rainforest and ecotone populations, at a level consistent with infrequent hybridization between sister species. Parallel patterns of genomic, morphological, and physiological divergence across this environmental gradient and pronounced allele frequency-environment correlation indicate speciation is mostly probably driven by ecological divergence, supporting a central role for divergent natural selection. Our results provide strong evidence for the importance of ecological gradients in African rainforest speciation and inform conservation strategies that preserve the processes that produce and maintain biodiversity.

Delineation of drainage potential area using geospatial techniques: A case study in the Indravati River Basin of India

For end users who use river networks and channel branches, the geo-hydrological examination of a basin is always of utmost relevance. With the aid of a remote sensing technique and GIS tool, this study attempted to evaluate the geomorphological properties of the strategic basin situated at Indravati River, Chhattisgarh, India. The findings might provide details about the basin's structural configuration, topographic features, and current geological variation. With dendritic, parallel, and trellis drainage patterns, the Indravati watershed was dispersed over a region of 29,408 km2 in the state of Chhattisgarh. The study area was classified as a fifth-order basin based on the findings. Lower and middle order streams pre-dominate the basin, which has gentle to steep slope terrain, medium-dense vegetation, and less permeable soil. When determining the ideal locations for recharge structures, the findings from the morphometric assessment of the basin can help to more effectively assess and manage water resources.

A novel extrusion-based 3D bioprinting system for skeletal muscle tissue engineering

Three-dimensional (3D) bioprinting is an emerging technology, which turned out to be an optimal tool for tissue engineering approaches. To date, different printing systems have been developed. Among them, the extrusion-based approach demonstrated to be the most suitable for skeletal muscle tissue engineering, due to its ability to produce and deposit printing fibers in a parallel pattern that well mimic the native skeletal muscle tissue architecture. In tissue bioengineering, a key role is played by biomaterials, which must possess the key requisite of ‘printability’. Nevertheless, this feature is not often well correlated with cell requirements, such as motives for cellular adhesion and/or absorbability. To overcome this hurdle, several efforts have been made to obtain an effective bioink by combining two different biomaterials in order to reach a good printability besides a suitable biological activity. However, despite being efficient, this strategy reveals several outcomes limitations. We report here the development and characterization of a novel extrusion-based 3D bioprinting system, and its application for correction of volumetric muscle loss (VML) injury in a mouse model. The developed bioprinting system is based on the use of PEG-Fibrinogen, a unique biomaterial with excellent biocompatibility, well-suited for skeletal muscle tissue engineering. With this approach, we obtained highly organized 3D constructs, in which murine muscle progenitors were able to differentiate into muscle fibers arranged in aligned bundles and capable of spontaneously contracting when cultured in vitro. Furthermore, to evaluate the potential of the developed system in future regenerative medicine applications, bioprinted constructs laden with either murine or human muscle progenitors were transplanted to regenerate the Tibialis Anterior muscle of a VML murine model, one month after grafting.

Infrared thermography as a possible technique for the estimation of parturition onset in sows

BackgroundThis study explores the possibility of using infrared thermography to estimate the onset of parturition in sows. Infrared camera (IRC) and infrared laser thermometer (IRT) were used to obtain the auricular skin temperature of sows along with rectal temperatures, from approximately one week before the anticipated farrowing until 24 h post-partum. Three commercial piglet producing farms were included in the study.ResultsThere were large variations in observed auricular skin temperature, both by IRC and IRT per time point. Graphical exploration of the observed auricular skin temperature measured by the two methods showed the same parallel patterns, although temperatures measured by IRC were higher at any time point compared to IRT. Auricular skin thermography revealed a clear increase in temperatures before farrowing. Statistical analyses, adjusting for differences between farms, sow activity and respiration rate, confirmed this increase. When controlling for these variables, and comparing the baseline temperatures to temperatures at farrowing, the difference was 3.9 and 4.1 °C measured with IRT and IRC, respectively. The greatest increase, of more than 2 °C, was found between 16 and 8 h and 8 to 4 h before farrowing. Rectal temperature increased by 0.5 °C in the same time interval and reached a temperature peak after farrowing.ConclusionSows showed a more than 2 °C increase in auricular skin temperature, measured by either IRC or IRT, 8 to16 hours before the first piglet was born. Hence, monitoring auricular skin temperatures of sows using infrared thermography one week before expected farrowing may provide a baseline temperature for each sow from which a sudden rise is indicative of parturition in the following 8 to 16 h. This may lead to more efficient allocation of human assistance during farrowing time and thereby improve farrowing management and the welfare of sows and their offspring.

Effects of extrusion on structural properties, physicochemical properties and in vitro starch digestibility of Tartary buckwheat flour

Tartary buckwheat is a promising pseudocereal with health benefits. However, native Tartary buckwheat flour (NTBF) cannot satisfy the specific physicochemical properties required for food processing due to its gluten-free character. This study investigated structural and physicochemical properties, the starch digestibility of Tartary buckwheat flour pregelatinized with traditional extrusion processing technology (TEPT), and improved extrusion processing technology (IEPT). TEPT had a higher destructive effect on the starch structure than IEPT. Amorphous flakes and incomplete starch granules were observed in pregelatinized Tartary buckwheat flour (PTBF). After extrusion, the relative crystallinity, endothermic enthalpy, the slowly digested starch (SDS) and resistant starch content decreased by 23.76–70.44%, 48.91–100.00%, 28.43–88.65% and 53.23–78.79%, respectively. However, the amylose molecular weight of branched starches, the degree of gelatinization (DG), the water absorption index (WAI), the starch digestibility, the rapidly digested starch content, and the glycemic index increased by 29.00–119.04%, 26.05–1279.88%, 4.2–188.70%, 9.2–19.96%, 113.04–236.25%, and 25.55–37.00%, respectively. For IEPT, crystallinity decreased with the increase in extrusion temperature and the decrease in feed moisture, whereas the DG and WAI showed a contrary trend. Compared to TEPT (5.05%), PTBF obtained with IEPT retained a higher SDS content (11.28–31.85%). Starch digestion of all samples possessed a combination of sequential and parallel digestion patterns. Correlation analysis suggested that an increase in the destructive effect on the starch structure from IEPT to TEPT was responsible for the changes in physicochemical properties and improvement of in vitro starch digestibility. This study provides a scientific basis for the quality improvement in Tartary buckwheat starchy foods following extrusion.

Three‐Dimensional Thermoporoelastic Modeling of Hydrofracturing and Fluid Circulation in Hot Dry Rock

AbstractGeothermal energy, featured as a renewable low‐carbon energy resource, exhibits great potential in mitigating global warming. However, efficient mining of geothermal energy from hot dry rock remains challenging due to the lack of a thermoporoelastic modeling approach that allows for integrated simulation of hydrofracturing and fluid circulation, and poor understanding of the mechanisms of hydraulic stimulations. To conquer these challenges, we propose an advanced modeling approach, which enables us to deal with the interplay between fluid transport, heat transfer, rock deformation, and three‐dimensional fractures' growth and interaction. Based on the thermoporoelastic model, a refined investigation is performed to determine the hydrofracturing and fluid circulation processes, using data collected from the EGS Collab Experiment 1. This meso‐scale testbed involves creating major hydraulic fractures, accompanied by numerous secondary hydroshearing fractures, hydraulically connecting two horizontal wellbores to build a fluid circulation system. All wellbores in the testbed were heavily instrumented with monitoring devices, offering high‐quality data to properly constrain the geomechanical model. Our study provides insights into: (a) how the EGS Collab testbed responds to propagating fractures with strong stress shadowing and long‐term injection of chilled water; (b) why the parallel pattern of two hydraulic fractures with a distance much smaller than the fracture dimension forms during multi‐staged hydraulic stimulations; and (c) what the mechanisms are that determine hydrofracturing performance. Overall, this work not only contributes to a novel modeling approach for integrated simulation of hydrofracturing and fluid circulation, but advances our understanding of creating enhanced geothermal systems with interconnected fracture networks.

Expansion potential of novel skin grafts simulants with I-shaped auxetic incisions

Skin grafts play an important role in treatment of severe burn injuries. Split-thickness skin grafting is one of the most common grafting technique, in which, parallel incision patterns are projected onto a small portion of excised skin for generating expansions and covering a larger burn site. However, to date, expansions reported through experiments on such grafts, have been much lower than claimed, which inhibits their application in severe burn injury mitigation. In this work, novel skin graft simulants were developed to study the expansion potential of skin grafts with I-shaped auxetic incision patterns. A range of I-shape dimensional parameters were tested, and the effective Poisson's effect, meshing ratios, and generated stresses, biaxial deformation and stress were estimated across all skin graft simulants, with strain loadings up to 200%. High spacing between I-shaped unit cells, was found to generate high negative Poisson's ratio and meshing ratio (MR). With high spacing, lowest stresses were generated for the maximum edge lengths of the I-shape. Maximum negative Poisson's ratio of -1.12 and meshing ratio of 3.84 were produced by the skin graft simulants, indicating expansions much higher than traditional skin grafts. Such results have not been realized with skin grafts to date, which would be indispensable for further research into skin graft expansions and treatment of severe burn injuries.

Benzotrithiophene‐based Covalent Organic Framework Photocatalysts with Controlled Conjugation of Building Blocks for Charge Stabilization

AbstractCovalent organic frameworks have recently shown high potential for photocatalytic hydrogen production. However, their structure‐property‐activity relationship has not been sufficiently explored to identify a research direction for structural design. Herein, we report the design and synthesis of four benzotrithiophene (BTT)‐based covalent organic frameworks (COFs) with different conjugations of building units, and their photocatalytic activity for hydrogen production. All four BTT‐COFs had slipped parallel stacking patterns with high crystallinity and specific surface areas. The change in the degree of conjugation was found to rationally tune the rate of photocatalytic hydrogen evolution. Based on the experimental and calculation results, the tunable photocatalytic performance could be mainly attributed to the electron affinity and charge trapping of the electron accepting units. This study provides important insights for designing covalent organic frameworks for efficient photocatalysts.