Sanath Kumar, Swati Sharma, Soumya Pandit et al.

Biosensors and Bioelectronics • 2023

Integration of carbon quantum dots for solar-enhanced MFC performance.

Yiying Fan, Emily Sharbrough, Hong Liu

Environmental Science & Technology • 2008

A novel method for quantifying different components of internal resistance in MFCs.

Jingying Ma, Donghui Chen, Wenwen Zhang et al.

RSC Advances • 2020

Active Red 30 was effectively removed in the cathode chamber of the microbial fuel cell.

Peng Wang, Haoran Li, Zhuwei Du

International Journal of Electrochemical Science • 2014

Weihuang Zhu, Haoxiang Gao, Fei Zheng et al.

International Journal of Energy Research • 2019

J. Vilas Boas, L. Peixoto, V.B. Oliveira et al.

Bioresource Technology Reports • 2022

Katja Fricke, Falk Harnisch, Uwe Schröder

Energy & Environmental Science • 2007

Ka Yu Cheng, Ralf Cord-Ruwisch, Goen Ho

Bioelectrochemistry • 2009

Peng Geng, Ji Zhao, Zhiwei Gao et al.

3D Printing and Additive Manufacturing • 2021

Polyphenylene sulfide (PPS) is a high-performance, low-cost special engineering polymer. The mechanical properties of three-dimensionally (3D) printed PPS samples are affected by the mass of the melt extruded filament and the printing pattern in the inner layer. The present study demonstrates the effects of the melt extrusion and filament alignment parameters on tensile, bending, and impact strengths of 3D printed PPS samples. The results indicate that by increasing the melt extrusion parameters, the tensile and bending strengths of 3D printed PPS samples can be improved and internal voids between adjacent filaments can be eliminated. However, the impact strength was restricted by excess melt extrusion. By measuring the strength of 3D printed PPS samples with different filament alignment, we observed that the tensile and bending strengths increase with decreasing angle between the filament and load direction. Moreover, the local tensile strain between adjacent filaments and slippage of the microstructure cell formed by aligning the filament are thought to absorb the impact energy. This study provides a useful guide for selection of appropriate printing parameters to realize a diverse range of mechanical properties for 3D printed PPS samples.

Lawrence Smith, Robert MacCurdy

3D Printing and Additive Manufacturing • 2024

Numerical modeling of soft matter has the potential to enable exploration of the soft robotic field's next frontier: human/machine cooperative design. However, access to material models suitable for predicting the behavior of soft matter is limited, and analysts typically conduct their own mechanical characterization on every new material they work with. In this work we present detailed mechanical characterization of 14 3D-printable soft materials suitable for fabricating soft robots. To allow the extension of this work by other researchers, our test procedures, raw data, constitutive model coefficients, and code used for curve fitting is freely available at www.SoRoForge.com .

Hae Woon Choi, Talal Alshammari, Jonghyun Kim

3D Printing and Additive Manufacturing • 2025

Polymeric tubing has played a crucial role in various industries. Manufacturing industries have traditionally used cutting methods for quality control, failure analysis, or to gain deeper insight into the device’s internal structure. A cross-sectional analysis of the tubes is required to control the manufacturing process of tubes produced by an extrusion process. However, small-scale factories and academic laboratories have so far used conventional hand cutters. Here, this study introduces a simple and novel analytical capability by fabricating and producing a dual-blade cutter tailored to the characteristics of the tubes. The dual-blade cutter, utilizing computer-aided design and three-dimensional (3D) printing, ensures low-cost parts, easy handling, and precise cutting. Through experiments, the cutting capability is verified by commercial polymer tubes. The dual-blade cutter is durable, allowing for an even distribution of cutting force. When cutting the outer diameter of the tube from 4 mm to 6 mm, the parallel angle deviation of the cut surface was 6–11%, demonstrating the ability to suppress surface roughness and burrs that may occur on the cut surface. It clamps the flexible tube effectively, minimizing tube deformation during cutting and increasing stability. As a result, the deformation of the tube can be quantified by ovality, and the values for hand-cut and cutter-cut are 11.5% and 4.3%, respectively. These suggested advantages could provide an inspiration for small factories and research institutes to reproduce our ideas or develop more efficient mechanisms. As additive manufacturing continues to advance, it is expected to significantly impact the prospective future of manufacturing processes, with expanded 3D printing capabilities via proposed practical application.

Siti Mariam Daud, Zainura Zainon Noor, Noor Sabrina Ahmad Mutamim et al.

Fuel • 2024

Asim Ali Yaqoob, Mohamad Nasir Mohamad Ibrahim, Nabil Al-Zaqri

Journal of Environmental Chemical Engineering • 2023

Priya Sharma, Guruprasad V. Talekar, Srikanth Mutnuri

Process Biochemistry • 2021

Xu Chen, Yun Wang, Nurimangvl Mamathaxim et al.

Journal of Environmental Sciences • 2025

Microbial fuel cell (MFC) coupled constructed wetland (CW) is regarded as a promising green technology due to its simultaneous removal performance for the co-occurrence of various contaminants in wastewater. In this study, the simultaneous removal performance of sulfamethazine (SMZ) and hexavalent chromium Cr(VI) in the CW and MFCCW systems was investigated. The removal efficiencies of total nitrogen (N), total phosphorus (P), and chemical oxygen demand (COD) were also examined. The results demonstrated that Cr(VI) was effectively eliminated with an excellent removal efficiency of >98.0 %, followed by SMZ with a removal efficiency of 70.3 %-85.6 %. Additionally, during the long-term operation period, the average removal efficiency for N, P, and COD ranged from 74.0 % to 96.1 %, 83.6 % to 94.1 %, and 91.1 % to 95.3 %, respectively. The microbial community and antibiotic resistance genes (ARGs) in the anode and cathode were also analyzed separately to evaluate the SMZ and Cr(VI) removal performance of MFCCW. The abundance of corresponding ARGs was slightly different in the anode and cathode regions. The average abundance of sul4 in the SMZ+Cr(VI) treatment MFCCW was significantly higher than that of other sul1-3. This study offers valuable insights for the simultaneous removal of SMZ and Cr(VI) from wastewater by MFCCW.

Yudong Zhang, Dong Li, Liang Zhang et al.

Bioelectrochemistry • 2024

Abdelrhman Mohamed, Hannah M. Zmuda, Phuc T. Ha et al.

Bioelectrochemistry • 2021

Kavya Arun Dwivedi, Song-Jeng Huang

Chemical Engineering Journal • 2024

Oscar Guerrero-Sodric, Juan Antonio Baeza, Albert Guisasola

Chemical Engineering Journal • 2023

Lorenzo Cristiani, Lorenzo Leobello, Marco Zeppilli et al.

Renewable Energy • 2023

Priyakant Pushkar, Arvind Kumar Mungray

Sustainable Energy Technologies and Assessments • 2021

Jeetendra Prasad, Ramesh Kumar Tripathi

Biosensors and Bioelectronics • 2020

Hannah Bird, Elizabeth Susan Heidrich, Daniel David Leicester et al.

Journal of Cleaner Production • 2022

Mandar S. Bhagat, Arvind Kumar Mungray, Alka A. Mungray

Environmental Science and Pollution Research • 2022

V. Kiran Kumar, K. Man mohan, Sreelakshmi P. Manangath et al.

Chemical Engineering Journal • 2023

Rui Yang, Minhui Liu, Qiao Yang

Chemical Engineering Journal • 2022

Movaffaq Kateb, Sahar Safarian

Machine Learning with Applications • 2025

Tiezhu Chen, Hongzhou Liu, Jianchang Li

Biochemical Engineering Journal • 2024

Xin Huang, Ranqiao Zhang, Yuanyuan Li et al.

Neural Networks • 2025

Multi-view clustering can better handle high-dimensional data by combining information from multiple views, which is important in big data mining. However, the existing models which simply perform feature fusion after feature extraction for individual views, mostly fails to capture the holistic attribute information of multi-view data due to ignoring the significant disparities among views, which seriously affects the performance of multi-view clustering. In this paper, inspired by the attention mechanism, an approach called Multi-View Fusion Clustering with Attentive Contrastive Learning (MFC-ACL) is proposed to tackle these issues. Here, the Att-AE module which optimizes AE using Attention Networks, is firstly constructed to extract view features with global information effectively. To obtain consistent features of multi-view data from various perspectives, a Transformer Feature Fusion Contrastive Module (TFFC) is introduced to combine and learn the extracted low-dimensional features in a contrastive manner. Finally, the optimized clustering results can be derived by clustering the resulting high-level features with shared consistency information. Adequate experimental results indicate that the proposed approach presents better clustering compared to state-of-the-art methods on six benchmark datasets.

Unknown Author

International Journal of Renewable Energy Research • 2021

Ann Maxton, Sam A. Masih

Water, Air, & Soil Pollution • 2025

Songwei Lin, Huamin Zheng, Shuyue Ma et al.

International Journal of Hydrogen Energy • 2024

Anina James

Environmental Research • 2022

Sumin KIM

European Journal of Materials Science and Engineering • 2021

Supawadee Siripratum, Petch Pengchai

Engineering Journal • 2022

Supriya Gupta, Ashmita Patro, Yamini Mittal et al.

Science of The Total Environment • 2023

Mostafa Ghasemi, Hegazy Rezk

Energy • 2023

Liting Wang, Manman Li

Journal of Energy Bioscience • 2023

Benyi Xiao, Xindong Wang, Eerdunmutu He et al.

Fuel • 2024

Riya Bhattacharya, Debajyoti Bose, Jaya Yadav et al.

Fuel • 2023