Energy storage performance of thin film nanocrystalline vanadium oxide with fluorinated tin oxide current carrier electrode for solid-state transparent supercapacitors based on ionic liquid gel electrolyte

Azadian, Farshad; Rastogi, A. C.

doi:10.1016/j.electacta.2019.135339

Cited by 28 publications

(12 citation statements)

References 58 publications

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“…The crystal structure of V 6 O 13 is formed by alternating single and double layers of VO 6 octahedrons [15,16]. These mixed valence oxides are also of great interest for high energy storage and electrochromic applications [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Microwave assisted growth of highly oriented vanadium oxides nanostructures: structural, vibrational and electrical properties

et al. 2021

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The proposed work focuses on the effects of growth time and annealing on the physico-chemical performance of vanadium oxides nanostructures (VO-NSs) films synthesized by a novel single reaction microwave synthesis. Thin films of VO-NSs were produced on glass substrates by varying the growth time and annealing temperature. Structural studies revealed that VO-NSs of synthesized films of VO 2 (B) + V 6 O 13 , VO 2 (B), V 3 O 7 and V 2 O 5 were crystallized in the form of monoclinic, monoclinic, tetragonal and orthorhombic structures with predominant orientation along ( 110), ( 110), ( 330) and ( 001) lattice plane, respectively. SEM analysis revealed that the VO-NSs thin films are dense and have uniform morphological characteristics. Furthermore, Raman spectroscopy show that all the samples undergo changes in intensities and peak positions that reflect changes in electronic structure and the vibrational properties. Our results demonstrate that the control of time and annealing treatment has a significant effect on the stoichiometry and the crystallinity leading to the control of the structure, size and morphology of VO-NSs. Moreover, the I-V curves were clearly linear and symmetrical with respect to both axes, with increasing the growth time and annealing treatment are two crucial parameters to improve the electrical conductivity, which influences the electrical properties and affects the behavior of the synthesized nanostructures. This synthesis approach offers a novel and simple route to produce one-dimensional nanostructured metal oxides, which are suitable for a wide range of applications, especially energy storage devices.

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Section: Introductionmentioning

confidence: 99%

Microwave assisted growth of highly oriented vanadium oxides nanostructures: structural, vibrational and electrical properties

et al. 2021

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“…[4][5][6] The most significant type of battery, which may be considered as a keyshift toward EVs, is lithium-ion batteries (LIBs), due to their high operational voltage, specific energy, light weight, compact size, longer life cycle, and lower idlestate discharge rate. [7][8][9][10] Significant efforts have been made toward the development of heat-optimization of the battery pack, new materials for electrode and various modeling-based estimation/prediction methods to evaluate state of health (SoH) and remaining useful life (RUL) of LIBs. [11][12][13][14][15] RUL and SoH are paramount in making efficient use of LIBs as these act as determining criteria for their reuse, disposal, and material recovery.…”

Section: Introductionmentioning

confidence: 99%

“…Power battery of the EV, being its single source of energy, is the most important part that influences the performance of the EV 4‐6 . The most significant type of battery, which may be considered as a key‐shift toward EVs, is lithium‐ion batteries (LIBs), due to their high operational voltage, specific energy, light weight, compact size, longer life cycle, and lower idle‐state discharge rate 7‐10 . Significant efforts have been made toward the development of heat‐optimization of the battery pack, new materials for electrode and various modeling‐based estimation/prediction methods to evaluate state of health (SoH) and remaining useful life (RUL) of LIBs 11‐15 .…”

Section: Introductionmentioning

confidence: 99%

Deep learning networks for capacity estimation for monitoring SOH of Li‐ion batteries for electric vehicles

et al. 2020

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Summary Data‐driven modeling using measurable battery signals tends to provide robust battery capacity estimation without delving deep into electrochemical phenomenon inside the battery. Nowadays, with the advent of artificial intelligence, deep neural networks are playing crucial role in data modeling and analysis. In this article, models of three different families of network architectures such as feed‐forward neural network (FNN), convolutional neural network (CNN), and long short‐term memory neural network (LSTM) are proposed for battery capacity estimation. Measurements from a set of two rechargeable Li‐ion batteries are considered for the model performance evaluation. The battery capacity estimation by different models has been evaluated by considering the effect of certain parameters such as model complexity, sampling rate of battery measurable signals and type of battery measurable signals. With its ability to process time‐series data efficiently by memorizing long‐term dependencies, LSTM outperforms other model architectures in estimating battery capacity more accurately and flexibly with 4.69% and 19.16% decline in average test root mean square error (RMSE) as compared with FNN and CNN, respectively. Simpler architectures of LSTM and FNN are able to perform well as compared with CNN, which needs architecture with certain hidden layers to interpret the battery aging process. Moreover, investigations reveal that sparsely sampled battery signals help all the proposed models to learn the battery dynamics in a better way as compared to densely sampled battery signals which also entails for less complex model learning process. Further, among all battery measurable signals, battery temperature has relatively less weightage in estimating battery capacity.

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“…In addition to the wide potential window (up to 4 V), ionic liquids are nontoxic and environmentally compatible. [24,25] A recent study by Ni et al reported on the performance of EDLSs fabricated with purchased oxygen and nitrogen-doped pitch-based carbon fibers. High capacitance values (301 F g À1 at a specific current of 1 A g À1 ) were reported; however, relatively low specific energy and power values were obtained.…”

Section: Introductionmentioning

confidence: 99%

“…In addition to the wide potential window (up to 4 V), ionic liquids are nontoxic and environmentally compatible. [ 24,25 ]…”

Section: Introductionmentioning

confidence: 99%

Superior Performance of Electrochemical Double Layer Supercapacitor Made with Asphaltene Derived Activated Carbon Fibers

et al. 2020

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High energy and power values are obtained from fabricated electrochemical double layer supercapacitor (EDLS) cells derived from asphaltene precursors, which are a solid by‐product of bitumen extraction in pentane solvents. Chemical activation, using dry KOH, is used to activate carbon fibers. Chemical activation introduces high specific surface areas (SSAs) into the fiber microstructure by partially etching the carbon. The electrodes are prepared by mixing activated fibers, polytetrafluoroethylene (PTFE), and acetylene black to form flexible electrode films. The unique bimodal pore size distribution with large micropore and mesopore volumes (micropore volume as high as 0.88 cm3 g−1), from chemical activation, generate high‐performance EDLS symmetric cells with capacitance values exceeding 310 F g−1 in aqueous electrolytes and 210 F g−1 in ionic liquid electrolytes (at a specific current of 40 mA g−1). A specific energy of 36 Wh kg−1 at a specific power of 525 W kg−1 is reached in ionic liquid electrolytes.

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Energy storage performance of thin film nanocrystalline vanadium oxide with fluorinated tin oxide current carrier electrode for solid-state transparent supercapacitors based on ionic liquid gel electrolyte

Cited by 28 publications

References 58 publications

Microwave assisted growth of highly oriented vanadium oxides nanostructures: structural, vibrational and electrical properties

Microwave assisted growth of highly oriented vanadium oxides nanostructures: structural, vibrational and electrical properties

Deep learning networks for capacity estimation for monitoring SOH of Li‐ion batteries for electric vehicles

Superior Performance of Electrochemical Double Layer Supercapacitor Made with Asphaltene Derived Activated Carbon Fibers

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