A strategy for power generation from bilgewater using a photosynthetic microalgal fuel cell (MAFC)

Predicting bilgewater emulsion stability by oil separation using image processing and machine learning

Bilgewater is a shipboard multi-component oily wastewater, combining numerous wastewater sources. A better understanding of bilgewater emulsions is required for proper wastewater management to meet discharge regulations. In this study, we developed 360 emulsion samples based on commonly used Navy cleaner data and previous bilgewater composition studies. Oil value (OV) was obtained from image analysis of oil/creaming layer and validated by oil separation (OS) which was experimentally determined using a gravimetric method. OV (%) showed good agreement with OS (%), indicating that a simple image-based parameter can be used for emulsion stability prediction model development. An ANOVA analysis was conducted of the five variables (Cleaner, Salinity, Suspended Solids [SS], pH, and Temperature) that significantly impacted estimates of OV, finding that the Cleaner, Salinity, and SS variables were statistically significant (p < 0.05), while pH and Temperature were not. In general, most cleaners showed improved oil separation with salt additions. Novel machine learning (ML)-based predictive models of both classification and regression for bilgewater emulsion stability were then developed using OV. For classification, the random forest (RF) classifiers achieved the most accurate prediction with F1-score of 0.8224, while in regression-based models the decision tree (DT) regressor showed the highest prediction of emulsion stability with the average mean absolute error (MAE) of 0.1611. Turbidity also showed a good emulsion prediction with RF regressor (MAE of 0.0559) and RF classifier (F1-score of 0.9338). One predictor variable removal test showed that Salinity, SS, and Temperature are the most impactful variables in the developed models. This is the first study to use image processing and machine learning for the prediction of oil separation for the application of bilgewater assessment within the marine sector.

Recycling urine for bioelectrochemical hydrogen production using a MoS2 nano carbon coated electrode in a microbial electrolysis cell

In this study, a novel molybdenum disulfide (MoS₂) nano-carbon (NC) coated cathode was developed for hydrogen production in a microbial electrolysis cell (MEC), while treating simulated urine with 2-6 times dilution (conductivity <20 mS cm^-1). MoS₂ nanoparticles were electrodeposited on the NC coated cathodes at -100, -150 and -200 μA cm^-2 and their performances were evaluated in the MEC. The chronopotentiometry (CP) tests showed the improved catalytic activity of MoS₂-NC cathodes with much lower cathode overpotential than non-MoS₂ coated electrodes. The MoS₂-NC200 cathode, electrodeposited at -200 μA cm^-2, showed the maximum hydrogen production rate of 0.152 ± 0.002 m³ H₂ m^-2 d^-1 at 0.9V of E_ap, which is comparable to the previously reported Pt electrodes. It was found that high solution conductivity over 20 mS cm^-1 (>600 mg L^-1 NH₃-N) can adversely affect the biofilm architecture and the bacterial activity at the anode of the MEC. Exoelectrogenic bacteria for this system at the anode were identified as Tissierella (Clostridia) and Bacteroidetes taxa. Maximum ammonia-nitrogen (NH₃-N) and phosphorus (PO₄ ^3--P) removal were 68.7 and 98.6%, respectively. This study showed that the newly fabricated MoS₂-NC cathode can be a cost-effective alternative to the Pt cathode for renewable bioelectrochemical hydrogen production from urine.

Impact of light on microalgal photosynthetic microbial fuel cells and removal of pollutants by nanoadsorbent biopolymers: Updates, challenges and innovations

Photosynthetic microbial fuel cells (PMFCs) with microalgae have huge potential for treating wastewater while simultaneously converting light energy into electrical energy. The efficiency of such cells directly depends on algal growth, which depends on light intensity. Higher light intensity results in increased potential as well as enhancement in generation of biomass rich in biopolymers. Such biopolymers are produced either by microbes at anode and algae at cathode or vice versa. The biopolymers recovered from these biological sources can be added in wastewater alone or in combination with nanomaterials to act as nanoadsorbents. These nanoadsorbents further increase the efficiency of PMFC by removing the pollutants like metals and dyes. In this review firstly the effect of different light intensities on the growth of microalgae, importance of diatoms in a PMFC and their impact on PMFCs efficiencies have been narrated. Secondly recovery of biopolymers from different biological sources and their role in removal of metals, dyes along with their impact on circular bioeconomy have been discussed. Thereafter bottlenecks and future perspectives in this field of research have been narrated.