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| Title: | High-performance composite electrolytes for solid-state lithium metal batteries: Enhancing ionic conductivity and interfacial compatibility through polyvinylpyrrolidone blending and inorganic filler incorporation |
| Authors: | Gami, Pratiksha Kumar, Sunil |
| Issue Date: | 2026 |
| Publisher: | Elsevier B.V. |
| Citation: | Gami, P., & Kumar, S. (2026). High-performance composite electrolytes for solid-state lithium metal batteries: Enhancing ionic conductivity and interfacial compatibility through polyvinylpyrrolidone blending and inorganic filler incorporation. Journal of Power Sources, 668. https://doi.org/10.1016/j.jpowsour.2026.239382 |
| Abstract: | One of the significant challenges in advancing safe and high-energy-density solid-state lithium metal batteries is achieving high ionic conductivities and ensuring good interfacial compatibility between the solid electrolyte and the electrodes. To address these challenges, the study proposes a composite electrolyte that is made through a solution casting method, utilizing polyvinylidene fluoride hexafluorophosphate (PVDF-HFP) and polyvinylpyrrolidone (PVP) in conjunction with lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt and mid-entropy inorganic filler Li1.5Sn1.0Al0.5Zr0.5(PO4)3. The polymer blend with an optimized ceramic filler exhibits an exceptional room-temperature ionic conductivity 1.48 × 10−4 S cm−1, a significantly high Li-ion transference number of 0.74, and shows electrochemical stability up to 4.58 V. The symmetric Li Li cell fabricated with the composite electrolyte exhibits uniform Li+ deposition/stripping for over >500 h at 2 mA cm−2. Further, a full cell with LiFePO4 cathode and lithium anode is fabricated and shows excellent electrochemical performance with 78% capacity retention after 1000 cycles at 2C. The findings from this study advance the development of practical inorganic polymer electrolytes for fast-charging lithium batteries. © 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. |
| URI: | https://dx.doi.org/10.1016/j.jpowsour.2026.239382 https://dspace.iiti.ac.in:8080/jspui/handle/123456789/18244 |
| ISSN: | 0378-7753 |
| Type of Material: | Journal Article |
| Appears in Collections: | Department of Metallurgical Engineering and Materials Sciences |
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