It is agreed that low mass transfer and poor reaction kinetics are the main reasons behind the low power density of microbial fuel cells (MFCs). Microscale MFCs can introduce a marvelous solution for the mass transfer dilemma. However, the volumetric power density and coulombic efficiency of present microscale MFCs are still limited due to the poor reaction kinetics. The size, shape, chemical properties and material of the electrodes are essential parameters controlling the reaction kinetics. In this study, a 3D carbon nanofiber disk is introduced as an effective anode for a single-chamber air-cathode micro-sized MFC as it improved the reaction kinetics. The proposed electrode was fabricated by a judicious combination of the electrospinning technique and thermal treatment. Owing to the intercalation of the microorganisms in the carbon nanofiber skeleton, compared to many previous reports, high power and current densities of 8.1 Wm and 44.9 Am, respectively, were obtained from the 19.6 μL single-chamber air-cathode MFC. However, the thickness of the carbon nanofiber layer has to be optimized by adjusting the electrospinning time. The power density observed from a 10 min electrospinning time-based anode outperformed the 5- and 20 min ones by 1.5 and 2 times, respectively.
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http://dx.doi.org/10.1039/d2ra00591c | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China.
CO mineralization, a process where CO reacts with minerals to form stable carbonates, presents a sustainable approach for CO sequestration and mitigation of global warming. While the crucial role of water in regulating CO mineralization efficiency is widely acknowledged, a comprehensive understanding of the underlying mechanisms remains elusive. This study employs a combined experimental and atomistic simulation approach to elucidate the intricate mechanisms governing moisture-driven carbonation kinetics of calcium-bearing minerals.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Physics, The Hong Kong University of Science and Technology, Hong Kong, China.
Dissolution of CO in water followed by the subsequent hydrolysis reactions is of great importance to the global carbon cycle, and carbon capture and storage. Despite numerous previous studies, the reactions are still not fully understood at the atomistic scale. Here, we combined ab initio molecular dynamics (AIMD) simulations with Markov state models to elucidate the reaction mechanisms and kinetics of CO in supercritical water both in the bulk and nanoconfined states.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
School of Biomolecular Science and Engineering, Vidyasirimedhi Institute of Science and Technology (VISTEC), Rayong 10120, Thailand.
A single-component flavin-dependent halogenase, AetF, has emerged as an attractive biocatalyst for catalyzing halogenation. However, its flavin chemistry remains unexplored and cannot be predicted due to its uniqueness in sequence and structure compared to other flavin-dependent monooxygenases. Here, we investigated the flavin reactions of AetF using transient kinetics.
View Article and Find Full Text PDFInorg Chem
January 2025
School of Chemistry and Chemical Engineering, and Institute for Innovative Materials and Energy, Yangzhou University, 180 Si-Wang-Ting Road, Yangzhou 225002, China.
The interaction between electrocatalytic active centers and their support is essential to the electrocatalytic performance, which could regulate the electronic structure of the metal centers but requires precise design. Herein, we report on covalent grafting of graphene quantum dots (GQDs) on stepped TiO as a support to anchoring cobalt phosphide nanoparticles (CoP/GQD/S-TiO) for electrocatalytic hydrogen evolution reaction (HER). The covalent ester bonds between GQDs and TiO endow enlarged anchoring sites to achieve highly dispersed electroactive CoP nanoparticles but, more importantly, provide an efficient electron-transfer pathway from TiO to GQDs which could regulate the electronic structure of CoP.
View Article and Find Full Text PDFJ Am Chem Soc
January 2025
Department of Chemistry, University of Southern California, Los Angeles, California 90089, United States.
Generative artificial intelligence (AI) models trained on natural protein sequences have been used to design functional enzymes. However, their ability to predict individual reaction steps in enzyme catalysis remains unclear, limiting the potential use of sequence information for enzyme engineering. In this study, we demonstrated that sequence information can predict the rate of the S2 step of a haloalkane dehalogenase using a generative maximum-entropy (MaxEnt) model.
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