Global plastic waste is increasing rapidly. In general, densely populated regions generate tons of plastic waste daily, which is sometimes disposed of on land or diverged to sea. Most of the plastics created in the form of waste have complex degradation behavior and are non-biodegradable by nature. These remain intact in the environment for a long time span and potentially originate complications within terrestrial and marine life ecosystems. The strategic management of plastic waste and recycling can preserve environmental species and associated costs. The key contribution in this work focuses on ongoing efforts to utilize plastic waste by introducing blockchain during plastic waste recycling. It is proposed that the efficiency of plastic recycling can be improved enormously by using the blockchain phenomenon. Automation for the segregation and collection of plastic waste can effectively establish a globally recognizable tool using blockchain-based applications. Collection and sorting of plastic recycling are feasible by keeping track of plastic with unique codes or digital badges throughout the supply chain. This approach can support a collaborative digital consortium for efficient plastic waste management, which can bring together multiple stakeholders, plastic manufacturers, government entities, retailers, suppliers, waste collectors, and recyclers.

Crystalline photodiodes remain the most viable infrared sensing technology of choice, yet the opacity and the limitation in pixel size reduction per se restrict their development for supporting high-resolution in situ infrared images. In this work, we propose an all-organic non-fullerene–based upconversion device that brings invisible infrared signal into human vision via exciplex cohost light-emissive system. The device reaches an infrared-to-visible upconversion efficiency of 12.56% by resolving the 940-nm infrared signal (power density of 103.8 μW cm ⁻² ). We tailor a semitransparent (AVT, ~60%), large-area (10.35 cm ² ), lightweight (22.91 g), single-pixel upconversion panel to visualize the infrared power density down to 0.75 μW cm ² , inferring a bias-switching linear dynamic range approaching 80 dB. We also demonstrate the possibility of visualizing low-intensity infrared signals from the Face ID and LiDAR, which should fill the gap in the existing technology based on pixelated complementary metal-oxide semiconductors with optical lenses.

The development of a simple, low-cost sensor for the effective sensing of multiple gases in industrial or residential zones has been in high demand in recent days. In this article, we have proposed an optical sensor for the dual sensing of oxygen (O₂) and ammonia (NH₃) gases, which consists of oxygen and ammonia-sensitive fluorescent dyes coated individually on both sides of a glass substrate. An ethyl cellulose (EC) matrix doped with platinum (II) meso-tetrakis (pentafluorophenyl) porphyrin (PtTFPP) serves as the oxygen-sensing material, whereas the NH₃-sensing material includes an eosin Y fluorescent indicator immobilized within a cellulose acetate (CA) matrix. Both the oxygen and ammonia-sensitive materials were excited by the same LED light source with a 405 nm peak wavelength, while the corresponding emissions were detected separately for the selective sensing of the gases under study. The dual gas sensor exhibits maximum sensitivities of around 60 and 20 for oxygen and ammonia gases, respectively. The high sensitivity and selectivity of the proposed optical dual sensor suggests the feasibility of the simultaneous sensing of oxygen and ammonia for practical applications.