The growing challenge of electronic waste (e-waste) has heightened the interest in biodegradable electronic materials as sustainable options to traditional components. This review provides a comprehensive overview of recent advancements in biodegradable conductors, semiconductors, dielectrics, and encapsulation materials. It emphasizes assessing material performance, exploring fabrication methods, and showcasing applications in biomedical devices, environmental monitoring, and transient consumer electronics. Key biodegradation processes are outlined, along with evaluations of environmental impact and life cycle comparisons to conventional electronics. The review also examines how various production techniques affect material behavior and reliability. Major challenges such as maintaining functional stability, scaling up manufacturing, costs, and regulatory issues are thoroughly discussed. To guide future research, promising materials and technologies are highlighted, and critical questions are addressed, including degradation mechanisms, environmental benefits, and specific application needs. Biodegradable electronics offer a transformative approach to reduce e-waste while promoting sustainability. This review serves as a vital resource for understanding current capabilities and guiding future research toward practical and environmentally responsible electronic solutions. Graphical abstract

This review article critically examines the integration of Internet of Things (IoT) sensors and wireless technology into polymer composites, highlighting its transformative potential in materials science. The focus is on real-time monitoring of key parameters such as temperature, stress, strain, humidity, and environmental exposure, which are essential for predictive maintenance and performance optimization. This review covers existing research and technological developments in IoT-enabled polymer composites, including sensor technologies, data transmission, cloud-based analysis, and digital twin creation for rapid design optimization and troubleshooting. The scope of this review does not extend to experimental procedures for sensor integration, detailed material property enhancements unrelated to IoT technologies, or the development of new composite materials without IoT integration. Key challenges such as standardization, data security, and system interoperability are discussed, and future research directions are proposed. By defining the scope and boundaries of the discussion, this review provides a comprehensive overview of how IoT integration is advancing the performance, reliability, and sustainability of polymer composites across industries such as aerospace, automotive, and infrastructure.

Optimization of Oil Yield from the Macro Algae Spirogyra by Solvent Extraction Process Using RSM and ANN: The present work was done to optimize the process parameters of the oil extraction from the algae species spirogyra by using n-hexane as the solvent using the Soxhlet apparatus. The response surface methodology (RSM) and artificial neural network (ANN) were employed to optimize the particle size of the algae powder, dryness level of the algae powder, solid to solvent ratio, reaction time, and extraction temperature of the oil extraction process. Also, the physiochemical properties of the extracted oil were investigated. The comparative evaluation was done between the RSM and ANN models to select the more precise and accurate model. The coefficient of determination, of 98.92%, and the mean absolute percentage deviation (MAPD) of 0.492% for ANN revealed that the current model created with a network topology of 3 : 11 : 1 with tansig (hyperbolic tangent sigmoid) transfer function in the input layer and purelin (pure linear) transfer function in the output layer trained with trainlm (Levenberg–Marquardt) algorithm found to provide the optimal solution with better accuracy in prediction of the output. The physicochemical properties investigated, such as heating value, flashpoint, density, viscosity, iodine number, acid value, saponification value, and cetane index, showed that the extracted oil from the algae spirogyra species can be used as an alternative fuel.

Forming micro-dimples nearer to the cutting edge on the rack face of the tungsten carbide cutting inserts will positively influence the machinability. However, it is challenging to machine the perfect micro-dimple dimensions by utilizing the available machining techniques. Finite element analysis can be an efficient way to observe the influence of dimple-texture area density, micro-dimple size, and various micro-dimple shapes on cutting inserts' machinability. This paper numerically analyses the impact of micro-dimple-textured cutting inserts in dry machining of AISI H-13 steel using AdvantEdge (virtual machining and finite element analysis software). Micro-dimples are formed on the rack face of tungsten carbide cutting inserts to observe the effect of dimple-textured cutting inserts on machinability compared to non-textured cutting inserts in terms of micro-dimple shape, micro-dimple size, and micro-dimple area density ratio. Their outcomes are analysed in terms of chip-insert contact length, main cutting force, and thrust force. It is observed that micro-dimple textured cutting inserts exhibit minimal main cutting force and thrust force in line with increasing the cutting insert life span. The abrasive wear was reduced in dimple-textured cutting inserts due to minimal contact between the cutting insert and chip developed compared to non-textured cutting inserts.