Structural supercapacitors are very interesting multifunctional devices combining the properties of an electrical energy storage device and a structural component simultaneously. These types of supercapacitors are mostly equipped with solid state electrolytes, instead of traditional liquid electrolytes, avoiding leakage and safety problems and supporting the mechanical performance of the composite materials. In the present study, the Lithium-ion based solid ceramic electrolyte Li1.4Al0.4Ti1.6(PO4)3 was successfully synthesized by sol-gel method. Its electrical properties were characterized by electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). Results show that Li1.4Al0.4Ti1.6(PO4)3 possesses a conductivity of 2.94×10−4 S/cm at room temperature and a specific capacity of 55.57 μF/g. The as-prepared samples were embedded into fiber composite material using the aviation approved resin RTM6 with an injection process making the composite structure flexible. Subsequently, the specific capacity and conductivity were tested getting values of 53.44μF/g and 2.00×10−4 S/cm respectively. The reason for electrical properties loss was investigated by computerized tomography (CT) and EIS tests and the results provide reference for the future research.
Skip Nav Destination
ASME 2015 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 21–23, 2015
Colorado Springs, Colorado, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-5729-8
PROCEEDINGS PAPER
Li1.4Al0.4Ti1.6(PO4)3 Used as Solid Electrolyte for Structural Supercapacitors
Guangyue Liao,
Guangyue Liao
German Aerospace Center (DLR), Braunschweig, Germany
Search for other works by this author on:
Sebastian Geier,
Sebastian Geier
German Aerospace Center (DLR), Braunschweig, Germany
Search for other works by this author on:
Thorsten Mahrholz,
Thorsten Mahrholz
German Aerospace Center (DLR), Braunschweig, Germany
Search for other works by this author on:
Peter Wierach,
Peter Wierach
German Aerospace Center (DLR), Braunschweig, Germany
Search for other works by this author on:
Martin Wiedemann
Martin Wiedemann
German Aerospace Center (DLR), Braunschweig, Germany
Search for other works by this author on:
Guangyue Liao
German Aerospace Center (DLR), Braunschweig, Germany
Sebastian Geier
German Aerospace Center (DLR), Braunschweig, Germany
Thorsten Mahrholz
German Aerospace Center (DLR), Braunschweig, Germany
Peter Wierach
German Aerospace Center (DLR), Braunschweig, Germany
Martin Wiedemann
German Aerospace Center (DLR), Braunschweig, Germany
Paper No:
SMASIS2015-8915, V001T01A006; 7 pages
Published Online:
January 11, 2016
Citation
Liao, G, Geier, S, Mahrholz, T, Wierach, P, & Wiedemann, M. "Li1.4Al0.4Ti1.6(PO4)3 Used as Solid Electrolyte for Structural Supercapacitors." Proceedings of the ASME 2015 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Mechanics and Behavior of Active Materials; Modeling, Simulation and Control of Adaptive Systems. Colorado Springs, Colorado, USA. September 21–23, 2015. V001T01A006. ASME. https://doi.org/10.1115/SMASIS2015-8915
Download citation file:
20
Views
Related Proceedings Papers
Related Articles
Effect of Sintering on Structural Modification and Phase Transition of Al-Substituted LLZO Electrolytes for Solid State Battery Applications
J. Electrochem. En. Conv. Stor (August,2021)
Electrochemical Performance Optimization of Li 2 Ni x Fe 1− x SiO 4 Cathode Materials for Lithium-Ion Batteries
J. Electrochem. En. Conv. Stor (May,2017)
Performance Study of Nickel Covered by Lithium Cobaltite Cathode for Molten Carbonate Fuel Cells: A Comparison in Li/K and Li/Na Carbonate Melts
J. Fuel Cell Sci. Technol (April,2010)
Related Chapters
Glossary of Terms
Consensus on Operating Practices for Control of Water and Steam Chemistry in Combined Cycle and Cogeneration
Introduction and Definitions
Handbook on Stiffness & Damping in Mechanical Design
Application of Adaptive Grayscale Morphological Operators for Image Analysis
Intelligent Engineering Systems through Artificial Neural Networks Volume 18