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Emerging Materials and Systems for Electrochemical Energy Storage Application

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A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Energy Materials".

Deadline for manuscript submissions: closed (20 October 2022) | Viewed by 10845

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Special Issue Editors

Prof. Dr. Dongfeng Xue

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Guest Editor

Multiscale Crystal Materials Research Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Interests: supercapattery; ion battery electrode materials; multiscale crystallization; chemical bonding; crystal growth

Prof. Dr. Kunfeng Chen

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State Key Laboratory of Crystal Materials, Institute of Crystal Materials, Shandong University, Jinan 250100, China
Interests: electrochemical energy storage; supercapacitor; battery; crystallization; solid state materials

Prof. Dr. Feng Liang

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Guest Editor

Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, China
Interests: metal-air/O₂ batteries; solid state batteries; carbon nanomaterials; plasma interact with electrode materials

Special Issue Information

Dear Colleagues,

Rechargeable metal-ion-based energy storage cells (lithium, sodium, potassium, magnesium, calcium, aluminum, zinc, manganese-ion batteries, their dual-ion batteries and capacitors) have been attracting enormous attention from the research community because these ion cells may be able to meet various challenges faced by human society in multiple applications. In these emerging ion-based systems, their performances may be worsened by a variety of undesired complications, including insufficient initial content of ions in a cell, poor initial coulombic efficiencies of electrode materials, loss of ions during long-term cycling, and the lack of practical possibility to optimize potential ranges in negative and positive electrodes. The intent of this Special Issue is to encourage the community to deepen physical and chemical understanding at both materials and systems levels for a broad range of metal-ion-based energy storage cells and provide an up-to-date overview of this emerging field. I hope this Special Issue will create important insights of a broad interest to a multidisciplinary community of energy researchers, materials chemists, and engineers working at the interface of new energy storage chemistry, device engineering, and relevant materials science.

Prof. Dr. Dongfeng Xue
Prof. Dr. Kunfeng Chen
Prof. Dr. Feng Liang
Guest Editors

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Keywords

supercapacitor electrode materials
ion battery electrode materials
interfacial structures
interfacial reactions
thermodynamic and kinetic phenomena

Published Papers (4 papers)

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Research

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12 pages, 2496 KiB

Open AccessArticle

Medium-Entropy SrV_1/3Fe_1/3Mo_1/3O₃ with High Conductivity and Strong Stability as SOFCs High-Performance Anode

by Guanjun Ma, Dezhi Chen, Shuaijing Ji, Xinyun Bai, Xinjian Wang, Yu Huan, Dehua Dong, Xun Hu and Tao Wei

Materials 2022, 15(6), 2298; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15062298 - 20 Mar 2022

Cited by 7 | Viewed by 1767

Abstract

Perovskite oxides using solid oxide fuel cells (SOFCs) anodes should possess high chemical stability, adequate electronic conductivity and excellent catalytic oxidation for fuel gas. In this work, the medium-entropy SrV_1/3Fe_1/3Mo_1/3O₃ (SVFMO) with Fe, V and Mo co-existing in the B site of a perovskite structure was fabricated in reducing 5% H₂/Ar mixed gas: (1) SVFMO demonstrates more stable physicochemical properties when using SOFCs anodes in a reducing environment; (2) the co-existence of Fe, V and Mo in SVFMO forms more small-polaron couples, demonstrating greatly enhanced electronic conductivity. With SVFMO in a porous structure (simulating the porous anode layer), its electronic conductivity can also reach 70 S cm⁻¹ when testing at 800 °C in an H₂ atmosphere; (3) SVFMO with more oxygen vacancies achieves higher catalytic ability for fuel gas, as an SOFCs anode layer demonstrates 720 mW cm⁻² at 850 °C. Full article

(This article belongs to the Special Issue Emerging Materials and Systems for Electrochemical Energy Storage Application)

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25 pages, 5678 KiB

Open AccessArticle

Starch as the Flame Retardant for Electrolytes in Lithium-Ion Cells

by Marita Pigłowska, Beata Kurc and Łukasz Rymaniak

Materials 2022, 15(2), 523; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15020523 - 10 Jan 2022

Cited by 4 | Viewed by 2287

Abstract

The main purpose of this work is to illustrate the flame retardant properties of corn starch that is used as an additive to the classic electrolytes in lithium-ion cells. The advantages of using natural biomass include the increased biodegradability of the cell, compliance with the slogan of green chemistry, as well as the widespread availability and easy isolation of this ingredient. Due to the non-Newtonian properties of starch, it increases work safety and prevents the occurrence of thermal runaway as a shear-thinning fluid in the event of a collision. Thus, its use may, in the future, prevent explosions that affect electric cars with lithium-ion batteries without significantly degrading the electrochemical parameters of the cell. In the manuscript, the viscosity test, flash point measurements, the SET (self-extinguishing time) test and conductivity measurements were performed, in addition to the determination of electrochemical impedance spectroscopy (EIS) for the anode system. Additionally, the kinetic and thermodynamic parameters, for both flow and conductivity, were determined for a deeper analysis; this constitutes the scientific novelty of this study. Through mathematical analysis, it was shown that the optimal amount of added starch is 5%. This is supported primarily by the determined kinetic and thermodynamic parameters and the fact that the system did not gel during heating. Full article

(This article belongs to the Special Issue Emerging Materials and Systems for Electrochemical Energy Storage Application)

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13 pages, 2970 KiB

Open AccessArticle

Study of Construction and Performance on Photoelectric Devices of Cs–Pb–Br Perovskite Quantum Dot

by Shiyu Ma, Yan Lu, Bo Wang and Jinkai Li

Materials 2021, 14(21), 6716; https://0-doi-org.brum.beds.ac.uk/10.3390/ma14216716 - 08 Nov 2021

Cited by 1 | Viewed by 1562

Abstract

White LEDs were encapsulated using Cs₄PbBr₆ quantum dots and Gd₂O₃:Eu red phosphor as lamp powder. Under the excitation of a GaN chip, the color coordinates of the W-LED were (0.33, 0.34), and the color temperature was 5752 K, which is close to the color coordinate and color temperature range of standard sunlight. The electric current stability was excellent with an increase in the electric current, voltage, and luminescence intensity of the quantum dots and phosphors by more than 10 times. However, the stability of the quantum dots was slightly insufficient over long working periods. The photocatalytic devices were constructed using TiO₂, CsPbBr₃, and NiO as an electron transport layer, light absorption layer, and catalyst, respectively. The Cs–Pb–Br-based perovskite quantum dot photocatalytic devices were constructed using a two-step spin coating method, one-step spin coating method, and full PLD technology. In order to improve the water stability of the device, a hydrophobic carbon paste and carbon film were selected as the hole transport layer. The TiO₂ layer and perovskite layer with different thicknesses and film forming qualities were obtained by changing the spin coating speed. The influence of the spin coating speed on the device’s performance was explored through SEM and a J–V curve to find the best spin coating process. The device constructed by the two-step spin coating method had a higher current density but no obvious increase in the current density under light, while the other two methods could obtain a more obvious light response, but the current density was very low. Full article

(This article belongs to the Special Issue Emerging Materials and Systems for Electrochemical Energy Storage Application)

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Review

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16 pages, 2620 KiB

Open AccessReview

Smart Materials Prediction: Applying Machine Learning to Lithium Solid-State Electrolyte

by Qianyu Hu, Kunfeng Chen, Fei Liu, Mengying Zhao, Feng Liang and Dongfeng Xue

Materials 2022, 15(3), 1157; https://0-doi-org.brum.beds.ac.uk/10.3390/ma15031157 - 02 Feb 2022

Cited by 8 | Viewed by 3720

Abstract

Traditionally, the discovery of new materials has often depended on scholars’ computational and experimental experience. The traditional trial-and-error methods require many resources and computing time. Due to new materials’ properties becoming more complex, it is difficult to predict and identify new materials only by general knowledge and experience. Material prediction tools based on machine learning (ML) have been successfully applied to various materials fields; they are beneficial for modeling and accelerating the prediction process for materials that cannot be accurately predicted. However, the obstacles of disciplinary span led to many scholars in materials not having complete knowledge of data-driven materials science methods. This paper provides an overview of the general process of ML applied to materials prediction and uses solid-state electrolytes (SSE) as an example. Recent approaches and specific applications to ML in the materials field and the requirements for building ML models for predicting lithium SSE are reviewed. Finally, some current obstacles to applying ML in materials prediction and prospects are described with the expectation that more materials scholars will be aware of the application of ML in materials prediction. Full article

(This article belongs to the Special Issue Emerging Materials and Systems for Electrochemical Energy Storage Application)

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