The ongoing trend towards miniaturizing electronic devices and increasing their power densities has created substantial challenges in managing the heat they produce.

Global challenges such as energy scarcity and food security are intensified by a growing population and substantial post‐harvest food losses, contributing to alarming hunger levels. Solar drying is recognized as an effective, high‐quality, and sustainable method for food preservation, significantly aiding global food security. Dryers are essential in agriculture and the food industry for extending crop shelf life by removing moisture through thermal energy, with solar thermal energy being particularly suitable due to its environmental benefits and availability. This article reviews the classification of solar dryers, including direct (DSD), indirect (ISD), and hybrid (HSD) systems, examining key components like solar collectors, drying chambers, and auxiliary systems and the factors affecting their performance. The review highlights that the efficiency of solar dryers depends on dryer type, solar irradiation, drying duration, and operational conditions. Recent advancements to enhance solar dryers' energy efficiency include hybrid systems incorporating auxiliary heating sources (electric or biomass), solar‐assisted heat pump dryers, surface modification techniques, and heat storage systems utilizing sensible and latent heat storage. Findings suggest that HSD with auxiliary units can achieve up to 54% efficiencies, while solar collectors can reach up to 81%, yielding better product quality than traditional ones.

Researchers and stakeholders have shown interest in heterogeneous composite biodiesel (HCB) due to its enhanced fuel properties and environmental friendliness (EF). The lack of high viscosity datasets for parent hybrid oils has hindered their commercialisation. Reliable models are lacking to optimise the transesterification parameters for developing HCB, and the scarcity of predictive models has affected climate researchers and environmental experts. In this study, basic fuel properties were analysed, and models were developed models for the yield of HCB and kinematic viscosity (KV) for composite biodiesel/neem castor seed oil methyl ester (NCSOME) using Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS). Statistical indices such as computed coefficient of determination (R²), root-mean-square-error (RMSE), standard error of prediction (SEP), mean average error (MAE), and average absolute deviation (AAD) were used to evaluate the effectiveness of the techniques. Emission models for NCSOME-diesel blends were also established. The study investigated the impact of optimised fuel types/NCSOME-diesel (10–30 vol%), ZnO nanoparticle dosage (400–800 ppm), engine speed (1100–1700 rpm), and engine load (10–30%) on emission characteristics and environmental friendliness indices (EFI) such as carbon monoxide (CO), Oxides of Nitrogen (NOx), and Unburnt Hydrocarbon (UHC) using Response Surface Methodology (RSM). The ANFIS model demonstrated superior performance in terms of R², RMSE, SEP, MAE, and AAD compared to the ANN model in predicting yield and KV of HCB. The optimal emission levels for CO (49.26 ppm), NO_x (0.5171 ppm), and UHC (2.783) were achieved with a fuel type of 23.4%, nanoparticle dosage of 685.432 ppm, engine speed of 1329.2 rpm, and engine load of 10% to ensure cleaner EFI. The hybrid ANFIS and ANN models can effectively predict and model fuel-related characteristics and improve the HCB process, while the RSM model can be a valuable tool for climate and environmental stakeholders in accurate forecasting and promoting a cleaner environment. The valuable datasets can also provide reliable information for strategic planning in the biodiesel and automotive industries.

This study introduces the Smart Grid Hybrid Electrolysis-and-Combustion System (SGHE-CS), designed to seamlessly integrate hydrogen production, storage, and utilization within smart grid operations to maximize renewable energy use and maintain grid stability. The system achieves a hydrogen production efficiency of 98.5%, indicating the effective conversion rate of electrical energy to hydrogen via PEM electrolysis. Combustion efficiency reaches 98.1%, reflecting the proportion of hydrogen energy successfully converted into usable power through advanced staged combustion. Storage and transportation efficiency is 96.3%, accounting for energy losses during hydrogen compression, storage, and delivery. Renewable integration efficiency is 97.3%, representing the system’s capacity to utilize variable renewable energy inputs without curtailment. Operational versatility is 99.3%, denoting the system’s ability to maintain high performance across load demands and grid conditions. Real-time monitoring and adaptive control strategies ensure reliability and resilience, positioning SGHE-CS as a promising solution for sustainable, low-carbon energy infrastructure.

Polyhydroxyalkanoate (PHA) as bioplastic is considered a replacement for conventional plastic due to its more beneficial properties. The ability of PHA to biodegrade in a shorter period is a major advantage. Different sewage water samples were collected from the Budha Nala near the Maheru regions of Punjab. PHA-producing bacteria were isolated using minimal salt media supplemented with Nile blue. Further screening was carried out using Sudan Black B stain and Nile red stain. The positive isolates were characterized for gram reaction, motility, and biochemical tests. The individual isolates were later screened for maximum PHA accumulation using minimal salt supplemented with glucose. The extracted PHA was characterized using FTIR, XRD, SEM, UV spectroscopy, NMR, and TGA. Twenty-six different PHA-producing bacteria were isolated on minimal salt media supplemented with Nile blue. Upon Sudan Black B stain and Nile red stain, nineteen isolates showed black granules and orange fluorescence bodies under 100X magnification that confirmed polyhydroxyalkanoates. The biochemical tests partially characterized isolates belonging to the Bacillus genus. All the isolates produced PHA in granular form, however, isolate P-3 showed maximum production of 0.068 g/L. The extracted PHA was characterized using FTIR and XRD for its chemical and crystallinity studies and the UV spectroscopy confirmed the extracted PHA by analyzing absorption spectra at 235 nm of standard crotonic acid and sulfuric acid conversion of PHA to crotonic acid. The isolated P-3, Bacillus paranthracis RSKS-3 is the first reported bacterium to produce polyhydroxyalkanoates. Further studies is necessary to optimize the production efficiency of the bacterium for maximum PHA yield.