Tailoring COFs: Transforming Nonconducting 2D Layered COF into a Conducting Quasi-3D Architecture via Interlayer Knitting with Polypyrrole.

Improving the electronic conductivity and the structural robustness of covalent organic frameworks (COFs) is paramount. Here, we covalently cross-link a 2D COF with polypyrrole (Ppy) chains to form a quasi-3D COF. The 3D COF shows well-defined reflections in the SAED patterns distinctly indexed to its modeled crystal structure. This knitting of 2D COF layers with conjugated polypyrrole units improves electronic conductivity from 10-9 to 10-2 S m-1. This conductivity boost is affirmed by the presence of density of states near the Fermi level in the 3D COF, and this elevates the COF's valence band maximum by 0.52 eV with respect to the parent 2D pyrrole-functionalized COF, which agrees well with the opto-electro band gaps. The extent of HOMO elevation suggests the predominant existence of a polaron state (radical cation), giving rise to a strong EPR signal, most likely sourced from the cross-linking polypyrrole chains. A supercapacitor devised with COF20-Ppy records a high areal capacitance of 377.6 mF cm-2, higher than that of the COF loaded with noncovalently linked polypyrrole chains. Thus, the polypyrrole acts as a "conjugation bridge" across the layers, lowering the band gap and providing polarons and additional conduction pathways. This marks a far-reaching approach to converting many 2D COFs into highly ordered and conducting 3D ones.

Covalent Organic Framework Cladding on Peptide-Amphiphile-Based Biomimetic Catalysts.

Peptide-based biomimetic catalysts are promising materials for efficient catalytic activity in various biochemical transformations. However, their lack of operational stability and fragile nature in non-aqueous media limit their practical applications. In this study, we have developed a cladding technique to stabilize biomimetic catalysts within porous covalent organic framework (COF) scaffolds. This methodology allows for the homogeneous distribution of peptide nanotubes inside the COF (TpAzo and TpDPP) backbone, creating strong noncovalent interactions that prevent leaching. We synthesized two different peptide-amphiphiles, C10FFVK and C10FFVR, with lysine (K) and arginine (R) at the C-termini, respectively, which formed nanotubular morphologies. The C10FFVK peptide-amphiphile nanotubes exhibit enzyme-like behavior and efficiently catalyze C-C bond cleavage in a buffer medium (pH 7.5). We produced nanotubular structures of TpAzo-C10FFVK and TpDPP-C10FFVK through COF cladding by using interfacial crystallization (IC). The peptide nanotubes encased in the COF catalyze C-C bond cleavage in a buffer medium as well as in different organic solvents (such as acetonitrile, acetone, and dichloromethane). The TpAzo-C10FFVK catalyst, being heterogeneous, is easily recoverable, enabling the reaction to be performed for multiple cycles. Additionally, the synthesis of TpAzo-C10FFVK thin films facilitates catalysis in flow. As control, we synthesized another peptide-amphiphile, C10FFVR, which also forms tubular assemblies. By depositing TpAzo COF crystallites on C10FFVR nanotubes through IC, we produced TpAzo-C10FFVR nanotubular structures that expectedly did not show catalysis, suggesting the critical role of the lysines in the TpAzo-C10FFVK.

Lead-Free Solid State Mechanochemical Synthesis of Cs2NaBi1-xFexCl6 Double Perovskite: Reduces Band Gap and Enhances Optical Properties.

Efficient and stable lead-free halide double perovskites (DPs) have attracted great attention for the future generation of electronic devices. Herein, we have developed a doping approach to incorporate Fe3+ ions into the Cs2NaBiCl6 crystal unit and reveal a crystallographic and optoelectronic study of the Cs2NaBi1-xFexCl6 double perovskite. We report a simple solid-state mechanochemical method that has a solvent-free, one-step, green chemistry approach for the synthesis of Cs2NaBi1-xFexCl6 phosphor. The analysis of powder X-ray diffraction (XRD) data determines the contraction of the lattice due to the incorporation of Fe3+ cations, and this effect is well supported by X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (FE-SEM), Raman spectroscopy, and solid-state nuclear magnetic resonance spectroscopy (ss-NMR). The band gap is reduced with increasing Fe content owing to the strong overlap of the Fe-3d orbitals with Cl-3p orbitals and shift of the valence band maxima (VBM) toward higher energies, as confirmed by ultraviolet photoelectron spectroscopy (UPS) and density functional theory (DFT) analyses. Photoluminescence (PL) studies of Cs2NaBi1-xFexCl6 phosphors exhibit a large Stokes shift, broadband emission, and increased PL intensity more than ten times for 15% of Fe content phosphor with enhancement in the average decay lifetimes (up to 38 ns) compared to pristine Cs2NaBiCl6 DP. These results indicate that the transition of dark self-trapping of excitons (STEs) into bright STEs enhances yellow emission. XRD, UV, and thermo-gravimetric analysis (TGA) confirmed that the Cs2NaB1-xFexCl6 DPs have good structural and thermal stabilities. Our findings indicate that the doping of Fe3+ cations into the Cs2NaBiCl6 lattice is a constructive strategy to enhance significantly the optoelectronic properties of these phosphors.

Covalent Organic Framework Thin-Film Photodetectors from Solution-Processable Porous Nanospheres.

The synthesis of homogeneous covalent organic framework (COF) thin films on a desired substrate with decent crystallinity, porosity, and uniform thickness has great potential for optoelectronic applications. We have used a solution-processable sphere transmutation process to synthesize 300 ± 20 nm uniform COF thin films on a 2 × 2 cm2 TiO2-coated fluorine-doped tin oxide (FTO) surface. This process controls the nucleation of COF crystallites and molecular morphology that helps the nanospheres to arrange periodically to form homogeneous COF thin films. We have synthesized four COF thin films (TpDPP, TpEtBt, TpTab, and TpTta) with different functional backbones. In a close agreement between the experiment and density functional theory, the TpEtBr COF film showed the lowest optical band gap (2.26 eV) and highest excited-state lifetime (8.52 ns) among all four COF films. Hence, the TpEtBr COF film can participate in efficient charge generation and separation. We constructed optoelectronic devices having a glass/FTO/TiO2/COF-film/Au architecture, which serves as a model system to study the optoelectronic charge transport properties of COF thin films under dark and illuminated conditions. Visible light with a calibrated intensity of 100 mW cm-2 was used for the excitation of COF thin films. All of the COF thin films exhibit significant photocurrent after illumination with visible light in comparison to the dark. Hence, all of the COF films behave as good photoactive substrates with minimal pinhole defects. The fabricated out-of-plane photodetector device based on the TpEtBr COF thin film exhibits high photocurrent density (2.65 ± 0.24 mA cm-2 at 0.5 V) and hole mobility (8.15 ± 0.64 ×10-3 cm2 V-1 S-1) compared to other as-synthesized films, indicating the best photoactive characteristics.

Hydroxide ion-conducting viologen-bakelite organic frameworks for flexible solid-state zinc-air battery applications.

Adaptable polymer-based solid-state electrolytes can be a game-changer toward safe, lightweight flexible batteries. We present a robust Bakelite-type organic polymer covalently decked with viologen, triazine, and phenolic moieties. Its flexible structure with cationic viologen centers incorporates counter-balancing free hydroxide ions into the polymeric framework. By design, the aromatic groups and heteroatoms in the framework can be activated under an applied potential to prompt a push-pull drive, setting off the towing of hydroxide ions via weak electrostatic, van der Waals, and hydrogen-bond interactions. The frontier orbitals from a DFT-modeled structure certify this. The hydroxyl-polymer requires minimal KOH wetting to maintain a humid environment for Grotthuss-type transport. The hydroxide ion conductivity reaches a value of 1.4 × 10-2 S cm-1 at 80 °C and 95% RH, which is retained for over 15 h. We enhanced its practical utility by coating it as a thin solid-state separator-cum-electrolyte on readily available filter paper. The composite exhibits a conductivity of 4.5 × 10-3 S cm-1 at 80 °C and 95% RH. A zinc-air battery (ZAB) constructed using this polymer-coated paper as electrolyte yields a maximum power density of 115 mW cm-2 and high specific capacitance of 435 mA h g-1. The power density recorded for our ZAB is among the best reported for polymer electrolyte-based batteries. Subsequently, the flexible battery fabricated with IISERP-POF11_OH@FilterPaper exhibits an OCV of 1.44 V, and three batteries in series power a demo traffic signal. To underscore the efficiency of hydroxide ion transport through the complex multifunctional backbone of the polymer, we calculated the diffusion coefficient for OH- (Exp: 2.9 × 10-5 cm2 s-1; Comp. 5.2 × 10-6 cm2 s-1) using electrochemical methods and MD simulations. Climbing-edge NEB calculations reveal a large energy barrier of 2.11 eV for Zn2+ to penetrate the polymer and identify hydroxide ions within the polymer, suggesting no undesirable Zn2+ crossover. Our findings assert the readily accessible C-C-linked cationic polymer's capacity as a solid-state electrolyte for ZABs and any anion-conducting membrane.

A statistical and deep learning-based daily infected count prediction system for the coronavirus pandemic.

We present new data analytics-based predictions results that can help governments to plan their future actions and also help medical services to be better prepared for the future. Our system can predict new corona cases with 99.82% accuracy using susceptible infected recovered (SIR) model. We have predicted the results of new COVID cases per day for dense and highly populated country i.e. India. We found that traditional statistical methods will not work efficiently as they do not consider the limited population in a particular country. Using the data analytics-based curve we predicted four most likely possibilities for the number of new cases in India. Hence, we expect that the results mentioned in the manuscript help people to better understand the progress of this disease. Supplementary Information: The online version contains supplementary material available at 10.1007/s12065-021-00600-2.

Chest X-ray Classification Using Deep Learning for Automated COVID-19 Screening.

In today's world, we find ourselves struggling to fight one of the worst pandemics in the history of humanity known as COVID-2019 caused by a coronavirus. When the virus reaches the lungs, we observe ground-glass opacity in the chest X-ray due to fibrosis in the lungs. Due to the significant differences between X-ray images of an infected and non-infected person, artificial intelligence techniques can be used to identify the presence and severity of the infection. We propose a classification model that can analyze the chest X-rays and help in the accurate diagnosis of COVID-19. Our methodology classifies the chest X-rays into four classes viz. normal, pneumonia, tuberculosis (TB), and COVID-19. Further, the X-rays indicating COVID-19 are classified on a severity-basis into mild, medium, and severe. The deep learning model used for the classification of pneumonia, TB, and normal is VGG-16 with a test accuracy of 95.9 %. For the segregation of normal pneumonia and COVID-19, the DenseNet-161 was used with a test accuracy of 98.9 %, whereas the ResNet-18 worked best for severity classification achieving a test accuracy up to 76 %. Our approach allows mass screening of the people using X-rays as a primary validation for COVID-19. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42979-021-00695-5.