Managing energy transition alongside environmental protection by making use of AI-led butanol powered SI engine optimization in compliance with SDGs.

Enormous consumption of fossil fuel resources has risked energy accessibility in the upcoming years. The price fluctuation and depletion rate of fossil fuels instigate the urgent need for searching their reliable substitute. The current study tries to address these issues by presenting butanol as a replacement for gasoline in SI engines at various speeds and loading conditions. The emission and performance parameters were ascertained for eight distinct butanol-gasoline fuel blends. The oxygenated butanol substantially increases engine efficiency and boosts power with lower fuel consumption. The carbon emissions were also observed to be lower in comparison with gasoline. Furthermore, the Artificial Intelligence (AI) approach was used in predicting engine performance running on the butanol blends. The correlation coefficients for the data training, validation, and testing were found to be 0.99986, 0.99942, and 0.99872, respectively. It was confirmed that the ANN predicted results were in accordance with the established statistical criteria. ANN was paired with Response Surface Methodology (RSM) technique to comprehend the influence of the sole design parameters along with their statistical interactions controlling the responses. Similarly, the R2 value of responses in case of RSM were close to unity and mean relative errors (MRE) were confined under specified range. A comparative study between ANN and RSM models unveiled that the ANN model should be preferred. Therefore, a joint utilization of the RSM and ANN can be more effective for reliable statistical interactions and predictions.

Integration of capacitive deionization and forward osmosis for high water recovery and ultrapure water production: concept, modelling and performance analysis.

Forward Osmosis (FO), a membrane desalination technology and Capacitive Deionization (CDI), an electrically operated desalination technology, are numerically integrated utilizing four different configurations for the high-water recovery rate and ultrapure water production from brackish water resource. To minimize the wastewater rejection, the CDI desorption stream is continuously fed to the FO unit, efficiently recovering the remaining freshwater. To produce ultrapure water, freshwater stream obtained from FO is provided to the CDI cell, which adsorbs the remaining dissolved solute particles. These two configurations serve the purpose of both industrial as well as domestic water supply requirements. Continuing this concept, the formation of the other two configurations allows us to obtain fresh water and ultrapure water simultaneously and up to a 90% freshwater recovery rate for the areas with inadequate supply. The performance parameters to assess the integration are the Water Recovery Rate (WRR) and Specific Energy Consumption (SEC). The first configuration (CDI-FO), proposed for a high freshwater recovery rate, resulted in 79.33% WRR with an SEC of 0.689kWh/m3. While, for the second configuration (FO-CDI), 34.25% water was recovered as 2.87 ppm ultrapure water along with 34.25% freshwater. The third proposed configuration (CDI-FO-CDI) had a WRR of 79.33%, 14.67% of which was recovered as ultrapure water of concentration 2.86 ppm. The fourth configuration (CDI-FO-FO) developed for high water recovery, removed the maximum of water from the feed stream with a WRR of 91.33% and remained energy-efficient, consuming an SEC of 0.908kWh/m3.

Influence of Low Sintering Temperature on BaCe0.2Zr0.6Y0.2O3-δ IT-SOFC Perovskite Electrolyte Synthesized by Co-Precipitation Method.

BaCe0.2Zr0.6Y0.2O3−δ (BCZY) perovskite electrolytes were synthesized for intermediate-temperature solid oxide fuel cell with a cost-effective and versatile co-precipitation method. The synthesized BCZY electrolytes were sintered at 900, 1000, and 1100 °C to observe the effects of low sintering temperature on the structural, morphological, thermal, and electrical properties of BCZY. All BCZY electrolytes materials exhibited a crystalline perovskite structure and were found to be thermally stable. The crystallinity and conductivity of BCZY electrolyte enhanced with increased sintering temperature, due to the grain growth. At the same time, secondary phases of carbonates were also observed for samples sintered at a temperature lower than 1100 °C. The BCZY sintered at 1100 °C exhibited a density >95%, and a power density of 350 mWcm−2 with open-circuit voltage 1.02 V at 650 °C was observed due its dense and airtight structure. Based on the current investigation, we suggest that the BaCe0.2Zr0.6Y0.2O3−δ perovskite electrolyte sintered at a temperature of 1100 °C is a suitable electrolyte for IT-SOFC.

Recent Developments in Plasmonic Nanostructures for Metal Enhanced Fluorescence-Based Biosensing.

Metal-enhanced fluorescence (MEF) is a unique phenomenon of surface plasmons, where light interacts with the metallic nanostructures and produces electromagnetic fields to enhance the sensitivity of fluorescence-based detection. In particular, this enhancement in sensing capacity is of importance to many research areas, including medical diagnostics, forensic science, and biotechnology. The article covers the basic mechanism of MEF and recent developments in plasmonic nanostructures fabrication for efficient fluorescence signal enhancement that are critically reviewed. The implications of current fluorescence-based technologies for biosensors are summarized, which are in practice to detect different analytes relevant to food control, medical diagnostics, and forensic science. Furthermore, characteristics of existing fabrication methods have been compared on the basis of their resolution, design flexibility, and throughput. The future projections emphasize exploring the potential of non-conventional materials and hybrid fabrication techniques to further enhance the sensitivity of MEF-based biosensors.