Advanced sustainable solid state energy storage devices based on FeOOH nanorod loaded carbon@PANI electrode: GCD cycling and TEM correlation

Singh, Nirbhay Kumar; Tanwar, Shweta; Kumar, Pradip; Sharma, Annu; Chaudhary, Priyanka

doi:10.1016/j.jallcom.2023.169580

Cited by 17 publications

(4 citation statements)

References 83 publications

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“…This model incorporates multiple modules to enhance prediction performance and durability compared to a single SVR model. However, the structure is complicated and sluggish, which is not favorable for realistic implementations [38,39].…”

Section: The Combining Modelmentioning

confidence: 99%

A Pork Price Prediction Model Based on a Combined Sparrow Search Algorithm and Classification and Regression Trees Model

Qin,

Yang,

Zhang

2023

Applied Sciences

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The frequent fluctuation of pork prices has seriously affected the sustainable development of the pork industry. The accurate prediction of pork prices can not only help pork practitioners make scientific decisions but also help them to avoid market risks, which is the only way to promote the healthy development of the pork industry. Therefore, to improve the prediction accuracy of pork prices, this paper first combines the Sparrow Search Algorithm (SSA) and traditional machine learning model, Classification and Regression Trees (CART), to establish an SSA-CART optimization model for predicting pork prices. Secondly, based on the Sichuan pork price data during the 12th Five-Year Plan period, the linear correlation between piglet, corn, fattening pig feed, and pork price was measured using the Pearson correlation coefficient. Thirdly, the MAE fitness value was calculated by combining the validation set and training set, and the hyperparameter “MinLeafSize” was optimized via the SSA. Finally, a comparative analysis of the prediction performance of the White Shark Optimizer (WSO)-CART model, CART model, and Simulated Annealing (SA)-CART model demonstrated that the SSA-CART model has the best prediction of pork price (compared with a single decision tree, R2 increased by 9.236%), which is conducive to providing support for pork price prediction. The accurate prediction of pork prices with an optimized machine learning model is of great practical significance for stabilizing pig production, ensuring the sustainable growth of farmers’ income, and promoting sound economic development.

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Section: The Combining Modelmentioning

confidence: 99%

A Pork Price Prediction Model Based on a Combined Sparrow Search Algorithm and Classification and Regression Trees Model

Qin,

Yang,

Zhang

2023

Applied Sciences

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“…The fundamental function of revolutionising energy storage technologies is attributed to the development and integration of innovative materials. The investigation of novel material categories, ranging from nanoparticles to metal-organic frameworks, has unparalleled prospects for augmenting the efficiency of energy storage, extending cycle life, and improving overall performance [15][16][17][18]. These materials enable the development of storage systems that exhibit increased energy density, enhanced speeds of charging and discharging, and better safety characteristics.…”

Section: The Significance Of Advanced Materials In Energy Storagementioning

confidence: 99%

Exploring the Uncharted Territory: Future Generation Materials for Sustainable Energy Storage

Kumar,

Dixit,

Haq

et al. 2023

E3S Web Conf.

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This study explores the domain of developing material categories for the purpose of sustainable energy storage, with the objective of addressing the constraints inherent in existing technologies and facilitating the development of inventive resolutions. The research examines the potential of nanomaterials, metal-organic frameworks (MOFs), polymers, and two-dimensional (2D) materials as a means to overcome the obstacles presented by current energy storage systems. This study investigates the qualities and potential of various materials, examining them in conjunction with a range of thorough characterization techniques. These approaches include electrochemical analysis, structural methodologies, nanoscale observations, and computer modelling. In the next analysis, this study will examine the future direction of research on energy storage materials, including prospective advancements and the critical obstacles related to scalability, cost-efficiency, and integration within energy systems. In general, this investigation highlights the significant impact of new materials on the development of a more environmentally friendly energy infrastructure. The present study focuses on the investigation of emerging materials for sustainable energy storage. Specifically, the research explores the potential of nanomaterials, metal-organic frameworks, polymers, and two-dimensional materials in this context. By examining the properties and characteristics of these materials, this study aims to contribute to the understanding and development of efficient and environmentally friendly energy storage solutions.

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“…Activated carbon provides a conductive pathway for rapid electron transfer. 43 The electrochemical analysis of the prepared materials has been carried out in a 2-electrode symmetric configuration for the voltage window of 0–1 V. The electrochemical measurements in a 2-electrode system are more appropriate compared to the 3-electrode system as they mimic all evaluation processes carried out in a real supercapacitor cell. 44 To enhance the operating voltage range, two ASC configurations have been fabricated using MnO 2 /AC and MnCo 2 O 4 /AC (from our previous reports) as negative electrodes.…”

Section: Introductionmentioning

confidence: 99%

All-redox hybrid supercapacitors based on carbon modified stacked zinc cobaltite nanosheets

Kour,

Sharma

2023

Sustainable Energy Fuels

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Advanced sustainable solid state energy storage devices based on FeOOH nanorod loaded carbon@PANI electrode: GCD cycling and TEM correlation

Cited by 17 publications

References 83 publications

A Pork Price Prediction Model Based on a Combined Sparrow Search Algorithm and Classification and Regression Trees Model

A Pork Price Prediction Model Based on a Combined Sparrow Search Algorithm and Classification and Regression Trees Model

Exploring the Uncharted Territory: Future Generation Materials for Sustainable Energy Storage

All-redox hybrid supercapacitors based on carbon modified stacked zinc cobaltite nanosheets

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