Batteries Beyond Mainstream
A topical collection in Physchem (ISSN 2673-7167). This collection belongs to the section "Electrochemistry".
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Editors
Dr. Sergei Manzhos
Dr. Sergei Manzhos
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Website
Guest Editor
School of Materials and Chemical Technology, Tokyo Institute of Technology, Tokyo, Japan
Interests: electrochemical batteries: photoelectrochemical cells; computational spectroscopy; potential energy surfaces; machine learning; ab initio modeling; large scale density functional methods
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Masashi Kotobuki
Prof. Dr. Masashi Kotobuki
E-Mail
Website
Guest Editor
Battery Research Center of Green Energy, Ming Chi University of Technology, 84 Gungjuan Road, Taishan District, New Taipei City 24301, Taiwan
Interests: electrochemical batteries; lithium battery; material science
Special Issues, Collections and Topics in MDPI journals
Topical Collection Information
Dear Colleagues,
Battery storage technologies are actively pursued to address electricity storage needs in diverse applications from portable electronics to grid storage. To the diversity of applications corresponds the diversity of desired combinations of device performance characteristics (volumetric and gravimetric energy densities, cycling rate and life, cost, scalability and environment-friendliness of materials, etc.). While much effort has been concentrated on metal-ion secondary batteries based on Li and other alkali (e.g., Na-ion, K-ion) and alkali-earth (e.g., Mg-ion) metal cations with inorganic hosts, it is also important to explore batteries based on other principles, both primary and secondary batteries, which may be advantageous for specialized applications as well as to generate new ideas for mainstream, larger-scale deployment. This Special Issue aims to publish original research articles and reviews about these types of batteries. This includes, but is not limited to, the following:
- Batteries utilizing non-alkali or alkali earth metal cations;
- Non-metal cation-based batteries;
- Nuclear batteries with thermal and non-thermal (including a, b, g-voltaic) conversion and other principles;
- Metal ion batteries utilizing non-standard host and electrolyte materials (i.e., beyond transition metal oxides, carbons, etc.);
- Organic batteries beyond mainstream materials;
- Metal hydride and hydrogen batteries.
Dr. Sergei Manzhos
Prof. Dr. Masashi Kotobuki
Guest Editors
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Keywords
- batteries
- post-lithium batteries
- alkali earth metal cations batteries
- non-metal cation-based batteries
- nuclear batteries
- metal ion batteries
- organic batteries
- metal hydride batteries
- hydrogen batteries
Published Papers (4 papers)
Open AccessArticle
Random Forest-Based Machine Learning Model Design for 21,700/5 Ah Lithium Cell Health Prediction Using Experimental Data
by
Sid-Ali Amamra
Cited by 1 | Viewed by 716
Abstract
In this research, the use of machine learning techniques for predicting the state of health (SoH) of 5 Ah—21,700 lithium-ion cells were explored; data from an experimental aging test were used to build the prediction model. The main objective of this work is
[...] Read more.
In this research, the use of machine learning techniques for predicting the state of health (SoH) of 5 Ah—21,700 lithium-ion cells were explored; data from an experimental aging test were used to build the prediction model. The main objective of this work is to develop a robust model for battery health estimation, which is crucial for enhancing the lifespan and performance of lithium-ion batteries in different applications, such as electric vehicles and energy storage systems. Two machine learning models: support vector regression (SVR) and random forest (RF) were designed and evaluated. The random forest model, which is a novel strategy for SoH prediction application, was trained using experimental features, including current (A), potential (V), and temperature (°C), and tuned through a grid search for performance optimization. The developed models were evaluated using two performance metrics, including R
2 and root mean squared error (RMSE). The obtained results show that the random forest model outperformed the SVR model, achieving an R
2 of 0.92 and an RMSE of 0.06, compared to an R
2 of 0.85 and an RMSE of 0.08 for SVR. These findings demonstrate that random forest is an effective and robust strategy for SoH prediction, offering a promising alternative to existing SoH monitoring strategies.
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Open AccessArticle
Morphological Engineering of Battery-Type Cobalt Oxide Electrodes for High-Performance Supercapacitors
by
Boddu Haritha, Mudda Deepak, Obili M. Hussain and Christian M. Julien
Viewed by 459
Abstract
Nanomaterials have attracted significant attention in recent decades for their diverse applications, including energy storage devices like supercapacitors. Among these, cobalt oxide (Co
3O
4) nanostructures stand out due to their high theoretical capacitance, unique electrical properties, and tunable morphology. This
[...] Read more.
Nanomaterials have attracted significant attention in recent decades for their diverse applications, including energy storage devices like supercapacitors. Among these, cobalt oxide (Co
3O
4) nanostructures stand out due to their high theoretical capacitance, unique electrical properties, and tunable morphology. This study explores the hydrothermal synthesis of Co
3O
4, revealing that the molar ratio of cobalt nitrate to potassium hydroxide significantly influences the morphology, crystal structure, and electrochemical performance. An optimized 1:1 molar ratio (COK 11) yielded well-defined cubic nanostructures with uniform elemental distribution, as confirmed by SEM, TEM, and EDS analyses. Structural characterization through XRD, XPS, and FTIR validated the formation of the Co
3O
4 spinel phase with distinctive lattice and surface oxygen features. Electrochemical property analysis demonstrated the superior performance of the COK 11 electrode, achieving a high specific capacity of 825 ± 3 F/g at a current density of 1 A/g, a rate capability of 56.88%, and excellent cycle stability of 88% at 3 A/g after 10,000 cycles. These properties are attributed to the nano-cubic morphology and interconnected porosity, which enhanced ion transport and active surface area. This study highlights the importance of synthesis parameters in tailoring nanomaterials for energy storage, establishing COK 11 as a promising candidate for next-generation high-performance supercapacitor applications.
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Open AccessArticle
Atomic-Scale Study of NASICON Type Electrode Material: Defects, Dopants and Sodium-Ion Migration in Na3V2(PO4)3
by
Vijayabaskar Seshan, Poobalasuntharam Iyngaran, Poobalasingam Abiman and Navaratnarajah Kuganathan
Viewed by 928
Abstract
Na
3V
2(PO
4)
3 (NVP), a NASICON-type material, has gained attention as a promising battery cathode owing to its high sodium mobility and excellent structural stability. Using computational simulation techniques based on classical potentials and density functional theory (DFT),
[...] Read more.
Na
3V
2(PO
4)
3 (NVP), a NASICON-type material, has gained attention as a promising battery cathode owing to its high sodium mobility and excellent structural stability. Using computational simulation techniques based on classical potentials and density functional theory (DFT), we examine the defect characteristics, diffusion mechanisms, and dopant behavior of the NVP. The study found that the Na Frenkel defect is the most favorable intrinsic defect, supporting the desodiation process necessary for capacity and enabling vacancy-assisted Na-ion migration. The Na migration is anticipated through a long-range zig-zag pathway with an overall activation energy of 0.70 eV. K and Sc preferentially occupy Na and V sites without creating charge-compensating defects. Substituting Mg at the V site can simultaneously increase Na content by forming interstitials and reducing the band gap. Additionally, doping Ti at the V site promotes the formation of Na vacancies necessary for vacancy-assisted migration, leading to a notable improvement in electronic conductivity.
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Open AccessArticle
Magnetite Thin Films by Solvothermal Synthesis on a Microstructured Si Substrate as a Model to Study Energy Storage Mechanisms of Supercapacitors
by
Karina Chavez and Enrique Quiroga-González
Viewed by 947
Abstract
Fast electrochemical phenomena occurring in supercapacitors are hard to analyze by ex situ or in situ techniques because many of them are meta-stable (the supercapacitor relaxes once it is not further polarized). In a steady state, one observes the effect of charge storage
[...] Read more.
Fast electrochemical phenomena occurring in supercapacitors are hard to analyze by ex situ or in situ techniques because many of them are meta-stable (the supercapacitor relaxes once it is not further polarized). In a steady state, one observes the effect of charge storage but not necessarily the mechanism. This is a problem for Raman spectroscopy, too, even though Raman spectra of the electrodes of supercapacitors are commonly recorded ex situ or in a steady state in situ. Raman operando is desired, but it represents a technological challenge since the electrochemical events in a supercapacitor are very fast (occurring within seconds), and in contrast, Raman requires from seconds to minutes to collect enough photons for reliable spectra. This work presents the development of electrodes made of thin layers of iron oxide grown solvothermally on Si wafers, with a porosified surface and resistivity of 0.005 Ωcm, to study their performance as electrodes in supercapacitors and analyze their energy storage mechanisms by cyclic voltammetry and Raman operando. Being flat and containing just iron oxide and silicon, these electrodes allow for studying interfacial phenomena with minor interferents.
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