Electrode materials having high capacitance with outstanding stability are the critical issues for the development of flexible supercapacitors (SCs), which have recently received increasing attention. To meet these demands, coating of CeO₂ nanoparticles have been performed onto MWCNTs by using facile chemical bath deposition (CBD) method. The formed CeO₂/MWCNTs nanocomposite exhibits excellent electrochemical specific capacitance of 1215.7 F/g with 92.3% remarkable cyclic stability at 10000 cycles. Light-weight flexible symmetric solid-state supercapacitor (FSSC) device have been engineered by sandwiching PVA-LiClO₄ gel between two CeO₂/MWCNTs electrodes which exhibit an excellent supercapacitive performance owing to the integration of pseudocapacitive CeO₂ nanoparticles onto electrochemical double layer capacitance (EDLC) behaved MWCNTs complex web-like structure. Remarkable specific capacitance of 486.5 F/g with much higher energy density of 85.7 Wh/kg shows the inherent potential of the fabricated device. Moreover, the low internal resistance adds exceptional stability along with unperturbed behavior even under high mechanical stress which can explore its applicability towards high-performance flexible supercapacitor for advanced portable electronic devices.

This work utilizes a novel approach leveraging the machine learning (ML) technique to predict the electrochemical supercapacitor performance of graphene oxide nano-rings (GONs) as electrode nanomaterials. Initially, the experimental procedure was carried out to synthesize GO via a modified Hummers method, followed by GONs preparation using the water-in-oil (W/O) emulsion technique. High-resolution transmission electron microscopy (HRTEM) analysis reveals the formation of a typical two-dimensional GO nanosheet and multilayer-GO nano-rings. The X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and Brunauer–Emmett–Teller (BET) analysis results show that the GONs possess similar structural and surface chemistry properties as of GO, with a slight reduction in oxygenous functionalities, enhancing the capacitive behaviours through facile electron migration at the electrode surface. The electrochemical assessment of GO and GONs samples indicates outstanding specific capacitances of 164 F g⁻¹ and 294 F g⁻¹ at 1 mV s⁻¹, showcasing capacitive retention of up to 63% and 60% after 2500 cycles. In addition, four different machine learning models were tested to estimate the role of electrochemical parameters in determining the specific capacitance of GONs.

Fabrication of nanofibrous polymer electrolyte membranes of poly(vinylidene fluoride) (PVdF) and poly(methyl methacrylate) (PMMA) in different proportion (PVdF:PMMA = 100:0, 80:20 and 50:50) by electrospinning is reported to investigate the influence of PMMA on lithium ion battery performance of PVdF membrane as separator. As-fabricated polymer electrospun nanofibrous membranes were characterized by SEM, FTIR, XRD, TGA and DSC for morphology, structure, crystallinity and thermal stability. PVdF–PMMA (50:50) polymer electrolyte membrane showed ionic conductivity 0.15 S/cm and electrolyte uptake 290% at room temperature. After 50 cycles, the discharge capacity 140 mAh/g of Li/PE/LiFePO₄ cells with PVdF–PMMA (50:50) as polymer electrolyte (PE) membrane was found to be retained around 93.3%. The electrolyte uptake, ionic conductivity, and discharge capacity retention were improved by optimizing the proportion of PMMA in PVdF. Nanofibrous PVdF–PMMA (50:50) polymer electrolyte membrane was found to be a potential separator for lithium ion batteries.