Mingrui Sui, Yue Dong, Zhishen Wang et al.

Journal of Photochemistry and Photobiology A Chemistry • 2017

Farzad Hejazi, Ali Asghar Ghoreyshi, Mostafa Rahimnejad

Biomass and Bioenergy • 2019

Ivar Zekker, Gourav Dhar Bhowmick, Hans Priks et al.

Biodegradation • 2020

Sze Pin Tan, Hong Feng Kong, Mohammed J.K. Bashir et al.

Bioresource Technology • 2017

Pedro Serra, António Espírito-Santo

Journal of Power Sources • 2020

Aura Kisieliūtė, Anton Popov, Roxana‐Mihaela Apetrei et al.

Chemical Engineering Journal • 2018

Hend Omar Mohamed, Sawsan Abo Talas, Enas Taha Sayed et al.

Energy • 2021

Haiming Zou, Yan Wang

Bioresource Technology • 2017

Swati Das, Sovik Das, Makarand M. Ghangrekar

Bioresource Technology • 2019

Clara Corbella, Jaume Puigagut

The Science of The Total Environment • 2018

Yeshona Sewsynker-Sukai, Funmilayo D. Faloye, E.B. Gueguim Kana

Biotechnology & Biotechnological Equipment • 2016

In view of the looming energy crisis as a result of depleting fossil fuel resources and environmental concerns from greenhouse gas emissions, the need for sustainable energy sources has secured global attention. Research is currently focused towards renewable sources of energy due to their availability and environmental friendliness. Biofuel production like other bioprocesses is controlled by several process parameters including pH, temperature and substrate concentration; however, the improvement of biofuel production requires a robust process model that accurately relates the effect of input variables to the process output. Artificial neural networks (ANNs) have emerged as a tool for modelling complex, non-linear processes. ANNs are applied in the prediction of various processes; they are useful for virtual experimentations and can potentially enhance bioprocess research and development. In this study, recent findings on the application of ANN for the modelling and optimization of biohydrogen, biogas, biodiesel, microbial fuel cell technology and bioethanol are reviewed. In addition, comparative studies on the modelling efficiency of ANN and other techniques such as the response surface methodology are briefly discussed. The review highlights the efficiency of ANNs as a modelling and optimization tool in biofuel process development.

Jong-Moon Choi, Pema Dorji, Ho Kyong Shon et al.

Desalination • 2018

Azize Ayol, İdris Biryol, Ergin Taşkan et al.

International Journal of Hydrogen Energy • 2020

Jia Liu, C. Vipulanandan

Waste Management • 2017

Mengni Tao, Zhao Jing, Zhengkai Tao et al.

Journal of Cleaner Production • 2021

Chun Cao, Liling Wei, Min Su et al.

Bioresource Technology • 2016

Anusha Vempaty, Ankit Kumar, Soumya Pandit et al.

Biocatalysis and Agricultural Biotechnology • 2022

Wenchao Xue, Yifan He, Sahawat Yumunthama et al.

Chemosphere • 2021

Osmotic microbial fuel cell (OsMFC) integrating forward osmosis into microbial fuel cell (MFC) favors the merits of organic removal, bioenergy generation, and high-quality water extraction from wastewater. This study demonstrated an 18.7% power density enhancement over a conventional MFC due to the water-flux-facilitated proton advection and net positive charge (NPC)-flux-promoted countercurrent proton exchange. Among the three examined membrane cleaning methods, chemical cleaning using 0.2% NaClO was found to be especially effective in removing organic foulants composed of proteins and polysaccharides, resulting in a water flux recovery of up to 91.6% with minimal impact on average maximum power density and internal resistance. The effects of operating parameters including anode HRT and draw solution concentration were studied. Shortening HRT from 6.0 to 3.0 h increased power density by 78.0% due to a high organic loading rate and a slightly reduced polarization concentration. Increasing draw solution concentration from 0.2 to 1.0 M NaCl enhanced power density by approximately 2.7-fold due to enhanced proton advection. Water-flux-facilitated proton advection played a more important role in determining the electricity generation performance of OsMFC than the NPC-flux-promoted countercurrent proton exchange under varied operating conditions.

Longmian Wang, Ying Zhou, Fuquan Peng et al.

Journal of Cleaner Production • 2020

Chin‐Tsan Wang, Thangavel Sangeetha, De-Quan Ding et al.

International Journal of Green Energy • 2018

Microbial fuel cells (MFC) are bioelectrochemical reactors that convert chemical energy in organic substrates to electrical energy through catalytic reactions of microorganisms. The relationship between microorganisms and electrodes plays a vital role for effective functioning of an MFC. The physical and chemical properties of the electrodes are more crucial for a feasible MFC performance. Plain Carbon cloth (CC) and surface modified CC with four different sizes of Biochar (BC) particles such as 2 mm BC< 2, BC2-4, BC4-6, and BC6-10 were employed as anode electrodes in dual-chambered MFCs and their performance was compared. Results showed that the electrode with BC< 2 enhanced the MFC performance to with power density of 312 mWm−2 and BC6-10 facilitated the maximum COD degradation performance of 77% in the MFC both due to electrode properties like high porosity and large surface area. This study in general is a proof that BC has high feasibility for usage in MFC electrode modification studies.

Aryama Raychaudhuri, Manaswini Behera

Process Biochemistry • 2021

Dongliang Wang, Jingyi Pan, Min Xu et al.

Journal of Power Sources • 2020

Aradhana Singh, Anubha Kaushik

3 Biotech • 2021

Prasanta Pattanayak, Nilkamal Pramanik, Farhan Papiya et al.

Journal of environmental chemical engineering • 2020

Denian Li, Lifang Deng, Haoran Yuan et al.

Electrochimica Acta • 2017

Fuhao Zhang, Cheng Shen, Yaqian Zhao et al.

Chemical Engineering Journal • 2024

Hongzhou Liu, Tiezhu Chen, Jianchang Li

Energy Conversion and Management • 2024

Ngan Hue Dai, Tam-Anh Duong Nguyen, Loan-Phung My Le et al.

International Journal of Hydrogen Energy • 2020

Yunfei Li, Jia Liu, Xuepeng Chen et al.

ACS Applied Materials & Interfaces • 2021

An extracellular electron transfer (EET) process between an electroactive biofilm and an electrode is a crucial step for the performance of microbial fuel cells (MFCs), which is highly related to the enrichment of exoelectrogens and the electrocatalytic activity of the electrode. Herein, an efficient N- and Fe-abundant carbon cloth (CC) electrode with the comodification of iron porphyrin (FePor) and polyquaternium-7 (PQ) was synthesized using a facile solvent evaporation and immersion method and developed as an anode (named FePor-PQ) in MFCs. The surface structural characterizations confirmed the successful introduction of N and Fe atoms, whereas FePor-PQ achieved the N content of 9.59 at %, which may offer various active sites for EET. The introduction of PQ contributed to improving the surface hydrophilicity, providing the composite electrode good biocompatibility for bacterial attachment and colonization as well as substrate diffusion. Based on the advantages, the MFC with the FePor-PQ anode produced a maximum power density of 2165.7 mW m -2 , strikingly higher than those of CC (1124.0 mW m -2 ), PQ (1668.8 mW m -2 ), and FePor (1978.9 mW m -2 ). Furthermore, with the EET mediated by the binding of flavins and c-type cytochromes on the outer membrane was enhanced prominently, the typical exoelectrogen Geobacter was enriched up to 55.84% in the FePor-PQ anode biofilm. This work reveals a synergistic effect from heteroatom coating and surface properties tailoring to boost both the EET efficiency and exoelectrogen enrichment for enhancing MFC performance, which also provides valuable insights for designing electrodes in other bio-electrochemical systems.

Bhanupriya Das, Surendra Singh Gaur, Anki Reddy Katha et al.

International Journal of Hydrogen Energy • 2020

Jhansi L. Varanasi, Arpan Kumar Nayak, Youngku Sohn et al.

Electrochimica Acta • 2016

Farhan Papiya, Prasanta Pattanayak, Piyush Kumar et al.

Electrochimica Acta • 2018

Haitao Xu, Junxiang Huang, Cunguo Lin et al.

Electrochimica Acta • 2020

Shan Huang, Guangcan Zhu, Xia Gu

Environmental Research • 2020

Yi-Kun Geng, Yuan Li, Tong Liu et al.

Applied Energy • 2020

Huiqiang Wang, Liling Wei, Jianting Liu et al.

International Journal of Hydrogen Energy • 2019

Dan Wu, Faqian Sun, Feng Jun Desmond Chua et al.

Chemical Engineering Journal • 2019

Chairat Treesubsuntorn, Wachira Chaiworn, Werasak Surareungchai et al.

The Science of The Total Environment • 2019

Marcelinus Christwardana, Domenico Frattini, Kimberley D.Z. Duarte et al.

Applied Energy • 2019

Sorina Iftimie, Anca Dumitru

Applied Surface Science • 2019