Nano-sized titanium dioxide-reinforced poly(vinyl alcohol) (PVA) nanocomposite polymer electrolyte (NCPE) as proton conductor in electric double layer capacitor (EDLC)
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Kar Kien Ong
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Yik Hoong Liang
Abstract
A solution-casted poly(vinyl alcohol)/ammonium acetate/titanium dioxide (PVA/CH3COONH4/TiO2) nanocomposite polymer electrolyte (NCPE) exhibits an enhancement in ionic conductivity from 1.91 × 10−4 S/cm to 4.60 × 10−4 S/cm upon doping of 10 wt% of nano-sized TiO2 and follows a Grotthuss-type proton conduction mechanism. Fourier Transform Infrared (FTIR) study confirms the complexation among PVA, CH3COONH4 and TiO2. The NCPE exhibits a wide electrochemical window of 4.66 V and demonstrates thermal stability up to 700 °C, as shown in linear sweep voltammetry (LSV) and thermogravimetric analysis (TGA), respectively. The transference number analysis demonstrates that the proton is the charge carrier in the conduction mechanism, and doping of nano-sized TiO2 improves the ionic mobility and ionic diffusion coefficient. Differential scanning calorimetry (DSC) results show that the glass transition temperature (T g ) is only affected by the impregnation of CH3COONH4, while doping of nano-sized TiO2 has a negligible effect on T g . Electric double layer capacitors (EDLCs) were fabricated using filler-free SPE and the most conducting NCPE with two identical carbon-based electrodes. Cyclic voltammetry (CV) analysis shows that doping of nano-sized filler improves the specific capacitance (C sp ) from 1.05 to 11.35 F g−1. Galvanostatic charge-discharge (GCD) shows good cycling stability up to 500 cycles.
Funding source: Ministry of Higher Education, Malaysia
Award Identifier / Grant number: FRGS/1/2023/STG05/TARUMT/02/1
Acknowledgments
This work was supported by the Fundamental Research Grant Scheme (FRGS/1/2023/STG05/TARUMT/02/1) from the Ministry of Higher Education, Malaysia.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: Not applicable.
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Conflict of interest: All authors state no conflict of interest.
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Research funding: This work was supported by the Fundamental Research Grant Scheme (FRGS/1/2023/STG05/TARUMT/02/1) from the Ministry of Higher Education, Malaysia.
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Data availability: Not applicable.
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