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Recent Advances in Electrochemistry: Analysis and Application

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Electrochemistry".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 815

Special Issue Editors


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Guest Editor
School of Materials Science and Engineering, Nankai University, Tianjin 300350, China
Interests: solid state materials; lithium-ion battery anodes; electrode materials; electrochemical energy storage; materials characterization; nanostructured materials

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Guest Editor
Key Laboratory of Microelectronics and Energy of Henan Province, Xinyang Normal University, Xinyang 464000, China
Interests: one-dimensional and two-dimensional materials; nanowires; nanotubes; nanobelts; lithium; sodium; potassium ion batteries; lithium-sulfur batteries; supercapacitors

Special Issue Information

Dear Colleagues,

Electrochemistry stands at the forefront of scientific innovation, serving as a critical bridge between chemistry, physics, and engineering. Its applications permeate numerous sectors, including energy conversion and storage, environmental protection, biotechnology, and materials science. Recent advancements have propelled the field into new territories, addressing global challenges such as sustainable energy production, environmental remediation, and the development of advanced analytical techniques.

The surge in research has led to significant breakthroughs—novel electrode materials enhance battery performance, innovative electrolytes improve fuel cell efficiency, and cutting-edge electrochemical sensors offer unprecedented sensitivity and selectivity. The integration of nanotechnology, bioelectrochemistry, and computational modeling has further expanded the horizons of electrochemical applications, enabling the design of systems with superior functionality and efficiency.

This Special Issue on "Recent Advances in Electrochemistry: Analysis and Application" aims to collate high-quality research articles, reviews, and communications that reflect the dynamic and interdisciplinary nature of modern electrochemistry. We invite contributions that explore new theories, methodologies, materials, and applications, shedding light on both fundamental studies and practical implementations.

Potential topics include, but are not limited to, the following:

  • Advanced electrode materials for energy storage and conversion;
  • Innovations in battery technologies (e.g., Li-ion, Na-ion, solid-state batteries);
  • Fuel cell development and novel electrocatalysts;
  • Electrochemical water splitting and hydrogen production;
  • Carbon dioxide reduction and electrochemical synthesis;
  • Electrochemical sensors and biosensors for medical and environmental monitoring;
  • Nanostructured materials and nano-electrochemistry;
  • Bioelectrochemistry and biofuel cells;
  • Electrochemical impedance spectroscopy and advanced analytical techniques;
  • Corrosion science and electrochemical protection strategies;
  • Electrochemical wastewater treatment and environmental remediation;
  • Computational electrochemistry and modeling of electrochemical systems;
  • Photoelectrochemistry and solar energy conversion;
  • Electropolymerization and conductive polymers;
  • Microbial fuel cells and bioelectrochemical systems;
  • Electrochemical synthesis of novel compounds and materials;
  • Electrochemical interface science and surface phenomena;
  • Redox flow batteries and large-scale energy storage solutions.

We believe this Special Issue will serve as a valuable platform for researchers to share their latest findings, stimulate academic discourse, and foster collaborations across various domains of electrochemistry.

We look forward to receiving your appreciated contributions.

Dr. Xiaolei Sun
Dr. Wenhe Xie
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • advanced electrode materials
  • electrochemical energy storage
  • bioelectrochemistry applications
  • nanotechnology in electrochemistry
  • electrochemical sensors and biosensors
  • computational electrochemistry
  • electrochemical water treatment

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Published Papers (1 paper)

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Research

18 pages, 1299 KiB  
Article
Application of Machine Learning for FOS/TAC Soft Sensing in Bio-Electrochemical Anaerobic Digestion
by Harvey Rutland, Jiseon You, Haixia Liu and Kyle Bowman
Molecules 2025, 30(5), 1092; https://doi.org/10.3390/molecules30051092 - 27 Feb 2025
Viewed by 602
Abstract
This study explores the application of various machine learning (ML) models for the real-time prediction of the FOS/TAC ratio in microbial electrolysis cell anaerobic digestion (MEC-AD) systems using data collected during a 160-day trial treating brewery wastewater. This study investigated models including decision [...] Read more.
This study explores the application of various machine learning (ML) models for the real-time prediction of the FOS/TAC ratio in microbial electrolysis cell anaerobic digestion (MEC-AD) systems using data collected during a 160-day trial treating brewery wastewater. This study investigated models including decision trees, XGBoost, support vector regression, a variant of support vector machine (SVM), and artificial neural networks (ANNs) for their effectiveness in the soft sensing of system stability. The ANNs demonstrated superior performance, achieving an explained variance of 0.77, and were further evaluated through an out-of-fold ensemble approach to assess the selected model’s performance across the complete dataset. This work underscores the critical role of ML in enhancing the operational efficiency and stability of bio-electrochemical systems (BES), contributing significantly to cost-effective environmental management. The findings suggest that ML not only aids in maintaining the health of microbial communities, which is essential for biogas production, but also helps to reduce the risks associated with system instability. Full article
(This article belongs to the Special Issue Recent Advances in Electrochemistry: Analysis and Application)
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