Semiconducting 2D Copper(I) Iodide Coordination Polymer as a Potential Chemiresistive Sensor for Methanol.

The development of a cost-effective, ultra-selective, and room temperature gas sensor is the need of an hour, owing to the rapid industrialization. Here, a new 2D semiconducting Cu(I) coordination polymer (CP) with 1,4-di(1H-1,2,4-triazol-1-yl)benzene (1,4-TzB) ligand is reported. The CP1 consists of a Cu2 I2 secondary building unit bridged by 1,4-TzB, and has high stability as well as semiconducting properties. The chemiresistive sensor, developed by a facile drop-casting method derived from CP1, demonstrates a response value of 66.7 at 100 ppm on methanol exposure, accompanied by swift transient (response and recovery time 17.5 and 34.2 s, respectively) behavior. In addition, the developed sensor displays ultra-high selectivity toward methanol over other volatile organic compounds , boasting LOD and LOQ values of 1.22 and 4.02 ppb, respectively. The CP is found to be a state-of-the-art chemiresistive sensor with ultra-high sensitivity and selectivity toward methanol at room temperature.

An integrated deep-learning model for smart waste classification.

Efficient waste management is essential for human well-being and environmental health, as neglecting proper disposal practices can lead to financial losses and the depletion of natural resources. Given the rapid urbanization and population growth, developing an automated, innovative waste classification model becomes imperative. To address this need, our paper introduces a novel and robust solution - a smart waste classification model that leverages a hybrid deep learning model (Optimized DenseNet-121 + SVM) to categorize waste items using the TrashNet datasets. Our proposed approach uses the advanced deep learning model DenseNet-121, optimized for superior performance, to extract meaningful features from an expanded TrashNet dataset. These features are subsequently fed into a support vector machine (SVM) for precise classification. Employing data augmentation techniques further enhances classification accuracy while mitigating the risk of overfitting, especially when working with limited TrashNet data. The results of our experimental evaluation of this hybrid deep learning model are highly promising, with an impressive accuracy rate of 99.84%. This accuracy surpasses similar existing models, affirming the efficacy and potential of our approach to revolutionizing waste classification for a sustainable and cleaner future.

Solvatochromic behaviour of cyclic dithioether-functionalized triphenylamine ligands and their mechano-responsive Cu(I) coordination polymers.

Cu(I)-based coordination polymers (CPs) are known as efficient emissive materials providing an eco-friendly and cost-effective platform for the development of various functional materials and sensors. In addition to the nature of the metal center, organic ligands also play a crucial role in controlling the emissive properties of coordination polymers. Herein, we report on the synthesis of dithiane- and dithiolane-substituted triphenylamine ligands L1 and L2. These ligands were found to be emissive both in the solid state and in solution. In addition, these ligands exhibit solvatochromic behaviour due to the twisted intramolecular charge transfer (TICT) phenomenon. Next, coordination behaviour of these ligands was explored with Cu(I)X salts (X = Br and Cl) and four new 1D coordination polymers [{Cu(µ2-X)2Cu}(µ2-L)]n, CP1 (X = Br, L = L1), CP2 (X = Cl, L = L1), CP3 (X = Br, L = L2), and CP4 (X = Cl, L = L2) were synthesized and crystallographically characterized. The emission behaviour of all the CPs suggests ligand-centered transitions. On mechanical grinding, emission maxima (λem) for CP1 and CP2 were blue-shifted, whereas for CP3 and CP4 red-shifts were observed. All CPs were found to emit at 448 nm with increased intensity after grinding. It is supposed that grinding is responsible for a change in the spatial arrangement (dihedral angles) of the phenyl groups of triphenylamine, causing the observed emission shifts. Furthermore, the higher emission intensity after grinding suggests the occurrence of a similar phenomenon as an aggregation-induced quenching in these CPs.