Platinum (Pt) persists as an exceptionally prevalent catalyst material in the proton exchange membrane fuel cells (PEMFCs), especially for cathodic oxygen reduction kinetics. However, the high cost and limited supply of Pt are driving interest in bio-based catalyst systems. In this review, three families of such catalysts, which include enzymes, metalloporphyrins, and biomass-derived carbon, are evaluated for their performance under PEMFC-relevant conditions. Rather than evaluating these as potential alternatives, this review focuses on their four-electron route driving capabilities, impurity sensitivity, and stability. Contemporary reports indicate that laccase-based systems, Fe/Co porphyrinic carbons, and microbial-templated Pd and Pt catalysts can attain activity levels comparable to Pt/C when immobilization and electronic coupling are effectively regulated. The primary concerns lie in durability and poisoning, with sulfur species and CO being detrimental to various biological templates. Furthermore, challenges persist regarding scalability and reproducibility because, unlike the conventional heterogeneous catalysts used in PEMFCs, bio-catalysts are contingent upon parameters including ligand chemistry, protein structural arrangement, and microbial growth. This makes the production process and maintenance of batch uniformity laborious. Although recent advancements have mitigated performance limitations, mechanistic understanding, operational longevity, and manufacturing scalability remain critical considerations. Overcoming these challenges will establish biocatalysts as a viable alternative to traditional precious-metal catalysts in PEMFCs.
The increasing demand for compact and energy-efficient heat exchangers has accelerated the development of passive heat transfer enhancement techniques and intelligent predictive tools for improved thermal system design. In the present study, an experimental and machine learning-based investigation was conducted to evaluate the thermo-hydraulic performance of a counter-flow double-pipe heat exchanger equipped with helical wire coil (WC) inserts under turbulent flow conditions. The novelty of this work lies in the systematic assessment of fifteen insert configurations by combining three wire diameters (1.0, 1.5, and 2.0 mm) with five pitch ratios (P/Dc = 0.625, 1.25, 1.875, 2.5, and 3.125). Experiments were performed over a Reynolds number range of 5500-15000, and the experimental setup was validated against established Nusselt number and friction factor correlations. The thermo-hydraulic performance was evaluated using the heat transfer coefficient, Nusselt number, friction factor, pressure drop, and thermal performance factor. The results showed that the wire coil inserts generated strong swirl flow and secondary vortices, which enhanced fluid mixing and suppressed thermal boundary layer development, resulting in a maximum Nusselt number enhancement of 126.7% compared with the plain tube. The highest Nusselt number (180.24) was achieved using a 2 mm wire diameter with a P/Dc of 0.625. Although the friction factor increased by 156.5-410.8% due to greater flow resistance, the thermal performance factor remained above unity (1.01-1.35) for all configurations, confirming the overall thermo-hydraulic effectiveness of the inserts. Furthermore, Linear Regression, Ridge Regression, Random Forest, and Gradient Boosting models were developed to predict the heat transfer and flow characteristics. Among them, the Gradient Boosting model demonstrated the highest prediction accuracy, achieving R2 values of 0.9984 and 0.9971 for the Nusselt number and friction factor, respectively, highlighting the potential of machine learning for the rapid design and optimization of advanced heat exchanger systems.
Efficient and sustainable planning of Electric Vehicle (EV) charging infrastructure requires balancing technical, economic, and environmental factors. Existing EV Charging Station (EVCS) designs often overlook user convenience and grid reliability, while failing to account for uncertainties, which can lead to inefficiencies and suboptimal system performance. This study presents an intelligent approach for profitable and reliable EV charging infrastructure using a Time-Series Power Flow (TSPF) model to enhance voltage and power stability. The proposed method integrates the Opposition-Based Botox Optimization Algorithm (OBOA) and Spatio-Temporal Field Neural Network (STFNN), referred to as the OBOA-STFNN technique. The BOA optimizes the siting and sizing of EVCSs to balance operator profit, grid stability, and user convenience, while STFNN predicts individual EV charging behavior and station demand. The effectiveness of the technique is evaluated in MATLAB and compared with Particle Swarm Optimization (PSO), Modified Snake Optimization (MSO), and Convolutional Neural Network (CNN) approaches. Simulation results demonstrate that the OBOA-STFNN method significantly reduces energy consumption to 38.74 MWh and energy loss to 418 MWh, while achieving a lower optimal cost, mean, and standard deviation, along with reduced total computation time. These results highlight the superior efficiency, reliability, and practicality of the proposed approach for EVCS planning and operation.
Paracetamol based benzoxazines (PA-Bz) were synthesized using structurally different amines namely 4-aminoacetanilide (AAC), aniline (AN), adamantylamine (AM) and 1,12-diaminododecane (DAD) through Mannich condensation (PA-AAC, PA-AN, PA-AM, PA-DAD). The molecular structure of the synthesized benzoxazines was confirmed through spectroscopic techniques. DSC studies showed that curing temperature of the synthesized benzoxazines are ranged between 205 and 232 degrees C. TGA results showed that poly(PA-DAD) showed the highest maximum degradation temperature of 452 degrees C. Contact angle measurement revealed that poly(PA-AM) exhibited the maximum water contact angle value of 142 degrees. The contact angle studies clearly showed that the resulting polymer can be used for the coating purpose as a hydrophobic sealant. Both PA-AM and its corresponding polymer demonstrated the higher antimicrobial activity. All the synthesized compounds showed 99% corrosion inhibition efficiency. The swelling ratio and high gel content of poly(PA-AN) and poly(PA-DAD) proved its higher crosslinking density. The results obtained on different analysis indicated that the synthesized benzoxazines can be used effectively in coating application, oil-water separation process and also to inhibit the microbial growth on the surface.
As an alternative to petroleum based raw materials, bio-based bisphenol (TC) was derived from thymol (T) and citronellal (C) emphasizing two principles of green chemistry by employing safer solvents and auxiliaries for synthesis and utilization of renewable feedstocks are justified. The novelty of this work lies in demonstrating the dual utility of this renewable bisphenol (TC) for the first time in the synthesis of two commercially significant thermosets polybenzoxazines and epoxy resins establishing a sustainable possible replacement for conventional petrochemical monomers. Benzoxazines (TC-fa, TC-la and TC-sa) were synthesized using TC with three different primary amines viz. furfurylamine (fa), laurylamine (la) and stearylamine (sa) separately. Also, TC was epoxidized to obtain bio-based epoxy (TC-E). The molecular structure of the targeted benzoxazines and epoxy were confirmed by spectral analysis. TC-fa showed lowest temperature of 205 °C to undergo polymerization. Whereas, poly(TC-sa) was found to possess highest water contact angle of 144o with a corrosion inhibition efficiency of 98.8
