A review of microbial fuel cell and its diversification in the development of green energy technology.

The advancement of microbial fuel cell technology is rapidly growing, with extensive research and well-established methodologies for enhancing structural performance. This terminology attracts researchers to compare the MFC devices on a technological basis. The architectural and scientific successes of MFCs are only possible with the knowledge of engineering and technical fields. This involves the structure of MFCs, using substrates and architectural backbones regarding electrode advancement, separators and system parameter measures. Knowing about the MFCs facilitates the systematic knowledge of engineering and scientific principles. The current situation of rapid urbanization and industrial growth is demanding the augmented engineering goods and production which results in unsolicited burden on traditional wastewater treatment plants. Consequently, posing health hazards and disturbing aquatic veracity due to partial and untreated wastewater. Therefore, it's sensible to evaluate the performance of MFCs as an unconventional treatment method over conventional one to treat the wastewater. However, MFCs some benefits like power generation, stumpy carbon emission and wastewater treatment are the main reasons behind the implementation. Nonetheless, few challenges like low power generation, scaling up are still the major areas needs to be focused so as to make MFCs sustainable one. We have focused on few archetypes which majorities have been laboratory scale in operations. To ensure the efficiency MFCs are needed to integrate and compatible with conventional wastewater treatment schemes. This review intended to explore the diversification in architecture of MFCs, exploration of MFCs ingredients and to provide the foreseen platform for the researchers in one source, so as to establish the channel for scaling up the technology. Further, the present review show that the MFC with different polymer membranes and cathode and anode modification presents significant role for potential commercial applications after change the system form prototype to pilot scale.

Recent Advances in the Applications of Green Synthesized Nanoparticle based Nanofluids for the Environmental Remediation.

With the ever-growing importance of green technology, the utilization of inorganic metal oxide nanoparticles and their nanofluids against microorganisms garnered more attention than organic metal oxides in recent years. Therefore, using safer, energy and cost-effective natural raw materials, stabilizing agents, and solvents are the fundamental considerations of the greener process. Due to their unique properties, larger surface area to volume ratio, higher stability and selective toxicity towards microbial pathogens, ZnO, TiO2 and silver nanoparticles are considered environmentally friendly and cost-effective antimicrobial agents. Furthermore, amine-based silica nanoparticles and carbon nanotubes are used for the carbon dioxide and hydrogen sulfide separation. The review mainly focuses on the green synthesis of the various nanoparticles to form nanofluids and their application in environmental remediation. In this light, the current paper briefly summarizes the preparation methods and the prospective environmental remediation applications of various nanofluids in the field of microorganisms controlling mechanisms, wastewater treatment methods and harmful gaseous removal methods.

Ultrasound assisted two-stage biodiesel synthesis from non-edible Schleichera triguga oil using heterogeneous catalyst: Kinetics and thermodynamic analysis.

Present work deals with the ultrasound-assisted biodiesel production from low cost, substantial acid value kusum (Schleichera triguga) oil using a two-step method of esterification in presence of acid (H2SO4) catalyst followed by transesterification using a basic heterogeneous barium hydroxide (Ba(OH)2) catalyst. The initial acid value of kusum oil was reduced from 21.65 to 0.84 mg of KOH/g of oil, by acid catalyzed esterification with 4:1 methanol to oil molar ratio, catalyst concentration 1% (v/v), ultrasonic irradiation time 20 min at 40 °C. Then, Ba(OH)2 concentration of 3% (w/w), methanol to oil molar ratio of 9:1, ultrasonic irradiation time of 80 min, and temperature of 50 °C was found to be the optimum conditions for transesterification step and triglyceride conversion of 96.8% (wt) was achieved. This paper also examined the kinetics as well as the evaluation of thermodynamic parameters for both esterification and transesterification reactions. The lower value of activation energy and higher values of kinetic constants indicated a fast rate of reaction, which could be attributed to the physical effect of emulsification, in which the microturbulence generated due to radial motion of bubbles, creates an intimate mixing of the immiscible reactants causing the increase in the interfacial area, giving faster reaction kinetics. The positive values of Gibbs-free energy (ΔG), enthalpy (ΔH) and negative value of entropy (ΔS) revealed that both the esterification and transesterification were non-spontaneous, endothermic and endergonic reactions. Therefore, the present work has not only established the escalation obtained due to ultrasonication but also exemplified the two-step approach for synthesis of biodiesel from non-edible kusum oil based on the use of heterogeneous catalyst for the transesterification step.

Optimization and Kinetic Studies on Biodiesel Production from Kusum (Schleichera triguga) Oil Using Response Surface Methodology.

In the present study, the low-cost non-edible kusum (Schleichera triguga) oil with a substantial amount of free fatty acid (FFA) was utilized for biodiesel synthesis. In pretreatment step, FFA was reduced by the acid catalyzed esterification method. Then, response surface method (RSM) in conjunction with centre composite design (CCD) containing 30 experimental runs were statistically employed for process optimization and kinetic study for the base catalyzed transesterification process. A statistical model predicted highest fatty acid methyl ester (FAME) yield of 97.37% at the optimal values of process parameters as follows: sodium methoxide concentration 0.9 wt% of oil, Methanol to oil molar ratio 9:1, temperature 58.9 ℃ and reaction time 58.5 min. Using these optimal parameters under experimental conditions in three independent replicates an actual FAME content of 98.14% was obtained which was in reasonable agreement with predicted one. The developed kinetic model suggested a 1.8(th) order reaction with activation energy of 31.42 kcal mol(-1) and frequency factor of 5.53×10(19) L mol(-1)min(-1). Furthermore, Important fuel properties of kusum oil biodiesel (KOB) was compared with ASTM 6751 and DIN EN 14214. The viscosity was found to be 5.34 Cst at 40 °C and the flash point was 152°C.

Ultrasound assisted biodiesel production from sesame (Sesamum indicum L.) oil using barium hydroxide as a heterogeneous catalyst: Comparative assessment of prediction abilities between response surface methodology (RSM) and artificial neural network (ANN).

The present study estimates the prediction capability of response surface methodology (RSM) and artificial neural network (ANN) models for biodiesel synthesis from sesame (Sesamum indicum L.) oil under ultrasonication (20 kHz and 1.2 kW) using barium hydroxide as a basic heterogeneous catalyst. RSM based on a five level, four factor central composite design, was employed to obtain the best possible combination of catalyst concentration, methanol to oil molar ratio, temperature and reaction time for maximum FAME content. Experimental data were evaluated by applying RSM integrating with desirability function approach. The importance of each independent variable on the response was investigated by using sensitivity analysis. The optimum conditions were found to be catalyst concentration (1.79 wt%), methanol to oil molar ratio (6.69:1), temperature (31.92°C), and reaction time (40.30 min). For these conditions, experimental FAME content of 98.6% was obtained, which was in reasonable agreement with predicted one. The sensitivity analysis confirmed that catalyst concentration was the main factors affecting the FAME content with the relative importance of 36.93%. The lower values of correlation coefficient (R(2)=0.781), root mean square error (RMSE=4.81), standard error of prediction (SEP=6.03) and relative percent deviation (RPD=4.92) for ANN compared to those R(2) (0.596), RMSE (6.79), SEP (8.54) and RPD (6.48) for RSM proved better prediction capability of ANN in predicting the FAME content.