Browsing by Author "Kaur, Simran"

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    Recent advances and challenges of carbon nano onions (CNOs) for application in supercapacitor devices (SCDs)
    (Elsevier Ltd, 2023-06-26T00:00:00) Kaur, Simran; Krishnan, Abhinand; Chakraborty, Sudip
    Since the discovery of CNOs, the number of publications and citations related to these carbon nanostructures research are still growing, indicating their strange behavior attracting the attention of the scientific community. As far as, the reviews published on CNOs have paid attention to the synthesis, characterization, surface functionalization and biomedical applications. However, very few works have summarized the advances and challenges of CNOs for application in SCDs. In this review, our objective is to summarize the recent advancement and challenges of the synthetic strategy, morphology, and electrochemical performance of different CNOs based materials along with their application in SCDs. The review commence with a short description of CNOs history and its structure, followed by the CNOs based supercapacitors and its recent advancement for the capacitance value augmentation. Then emphasized the synthetic procedure of Doped CNOs and its applications. After a critical analysis of the literature, we have discussed the molecular mechanism behind the improved electrochemical behavior of doped CNOs as compared with the pristine CNOs. A common guidance for selecting dopants based on their specific applications in supercapacitors have been explored. Further, the physico-chemical and electrochemical properties of CNO-composites are also discussed. We summarized the DFT based studies for CNOs based materials, and the advantages of Molecular Modeling/ReaxFF based simulation techniques for modeling of CNOs based electrodes and task specific electrolyte design for SCDs. The CNOs based materials are very good candidates for supercapacitor electrode design, with various challenges, more specifically the structural ordering of CNOs, electrochemical performance and condition of supercapacitor health. The Artificial Intelligence (AI)/Machine Learning (ML) based literatures are discussed and recommended several AI/ML based algorithms in the field of supercapacitors and energy storage devices (ESDs) to predict the specific capacitance value and the supercapacitors condition of health. We have outlined the current challenges and opportunities in this field. To the best of our knowledge, the review will be useful to provide a systematic framework for CNOs based research in the field of supercapacitor devices. � 2023 Elsevier Ltd