Augmentation of microbial fuel cell and photocatalytic polishing technique for the treatment of hazardous dimethyl phthalate containing wastewater

Sarmin, Sumaya; Tarek, Mostafa; Cheng, Chin Kui; Roopan, Selvaraj Mohana; Khan, Md. Maksudur Rahman

doi:10.1016/j.jhazmat.2021.125587

Cited by 24 publications

(5 citation statements)

References 52 publications

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“…1,132 However, the task of statistically establishing the inherent correlation involving the characteristics of catalysts' ngerprints and the decomposition of pollutants continues to pose a signicant difficulty. 133 In order to tackle these issues, scholars are employing simulations and experiments to quantitatively investigate the inherent correlation between the ngerprint attributes of catalysts and the degradation of pollutants. 134 They are also incorporating advanced techniques such as feature engineering and dimensionality reduction to nd set patterns and relationships within the data.…”

Section: Analysing the Performance Of Machine Learning Algorithmsmentioning

confidence: 99%

“…17 AI methods have enabled the quantitative identication of the intrinsic link between catalyst ngerprint properties and pollutant degradation, which was previously difficult to determine. 133 This breakthrough in utilizing machine learning algorithms for catalyst screening and selection signicantly improved our understanding of the factors that impact decontamination performance, together with the quantity and variety of reactive oxygen species produced during the degradation process. Estimating the catalytic degradation performance of organic contaminants is critical for creating efficient environmental remediation solutions.…”

Section: Analysing the Performance Of Machine Learning Algorithmsmentioning

confidence: 99%

“…For example, one of the authors developed a machine learning model to predict personal exposure to benzene. 133 They compared the performance of their machine learning model with a linear regression approach and found that the machine learning model showed higher variability in performance, accurately classifying personal exposure levels to benzene. These studies demonstrated the potential of machine learning methods for accurately predicting the catalytic degradation performance of organic contaminants.…”

Section: Analysing the Performance Of Machine Learning Algorithmsmentioning

confidence: 99%

See 2 more Smart Citations

Photocatalytic degradation of drugs and dyes using a maching learning approach

Anandhi,

Iyapparaja

2024

RSC Adv.

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Section: Analysing the Performance Of Machine Learning Algorithmsmentioning

confidence: 99%

Section: Analysing the Performance Of Machine Learning Algorithmsmentioning

confidence: 99%

Section: Analysing the Performance Of Machine Learning Algorithmsmentioning

confidence: 99%

See 1 more Smart Citation

Photocatalytic degradation of drugs and dyes using a maching learning approach

Anandhi,

Iyapparaja

2024

RSC Adv.

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“…This study also confirms that narrow bandgap TiO 2 can be easily obtained and effectively used as a photocatalyst and photovoltaic material. Not only does the photocathode material have a significant impact on cell capacity, but also the anode ( Wang et al, 2019b ) and biocatalyst ( Sarmin et al, 2021 ). Xu ( Xu et al, 2020b ) et al used PANi@CNTs/SS as the bioanode and CuInS 2 as the photocathode to construct a dual-chamber photocatalytic microbial fuel cell.…”

Section: Research Progress Of Pmfcmentioning

confidence: 99%

Photocatalytic Microbial Fuel Cells and Performance Applications: A Review

Yao

Wei

et al. 2022

Front. Chem.

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In recent years, photocatalytic microbial fuel cells have gradually become a hot research topic in pollutant treatment, using either in situ or indirectly the oxidation of organic pollutants by catalytic materials under light and the biodegradation and mineralization of various components in wastewater by microorganisms, or through the generation of electricity by the microbial fuel cell (MFC) system to promote the photogeneration and separation of electrons and holes by the catalytic materials of the photocatalytic cell (PC) system. This study aims to provide new ideas for the development of environmentally friendly wastewater treatment technologies by investigating the use of photocatalytic cells for the efficient degradation and resource utilization of target pollutants. This study aims to raise awareness of the use of photocatalytic microbial fuel cells for pollutant degradation by providing an overview of the practical status of photocatalytic microbial fuel cells. This is achieved by reviewing the key cathode development, production capacity, and progress in the degradation of pollutants in photocatalytic microbial fuel cells. The issues facing future developments are also discussed in terms of how photocatalytic microbial fuel cells work and how they degrade pollutants. This study shows that photocatalytic microbial fuel cells are beneficial for achieving renewable energy (bioenergy, photovoltaic, etc.) capacity and dealing with environmental pollution and that this is a novel technology that deserves to be promoted to achieve the current dual carbon targets.

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“…In a photocatalytic MFC (PMFC), photosynthetic bacteria that convert solar energy to electricity act as biocatalysts. Membrane reactor MFC and anaerobic digestor MFC are used to improve the treatment efficiency and bioenergy recovery, respectively . The other types of microbial technologies such as MECs, microremediation cell (MRC), microbial carbon capture cell (MCC), and microbial desalination cell (MDC) are also used for biosensor applications.…”

Section: Electrochemical and Bio-electrochemical Systemsmentioning

confidence: 99%

Tuning of Electrode Surface for Enhanced Bacterial Adhesion and Reactions: A Review on Recent Approaches

Ratheesh

Elias

Shibli

2021

ACS Appl. Bio Mater.

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The study of bacterial adhesion and its consequences has great significance in different fields such as marine science, renewable energy sectors, soil and plant ecology, food industry, and the biomedical field. Generally, the adverse effects of microbial surface interactions have attained wide visibility. However, herein, we present distinct approaches to highlight the beneficial aspects of microbial surface interactions for various applications rather than deal with the conventional negative aspects or prevention strategies. The surface microbial reactions can be tuned for useful biochemical or bio-electrochemical applications, which are otherwise unattainable through conventional routes. In this context, the present review is a comprehensive approach to highlight the basic principles and signature parameters that are responsible for the useful microbial−electrode interactions. It also proposes various surface tuning strategies, which are useful for tuning the electrode characteristics particularly suitable for the enhanced bacterial adhesion and reactions. The tuning of surface characteristics of electrodes is discussed with a special reference to the Microbial Fuel Cell as an example.

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Augmentation of microbial fuel cell and photocatalytic polishing technique for the treatment of hazardous dimethyl phthalate containing wastewater

Cited by 24 publications

References 52 publications

Photocatalytic degradation of drugs and dyes using a maching learning approach

Photocatalytic degradation of drugs and dyes using a maching learning approach

Photocatalytic Microbial Fuel Cells and Performance Applications: A Review

Tuning of Electrode Surface for Enhanced Bacterial Adhesion and Reactions: A Review on Recent Approaches

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