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Recent Advances in AlN-Based Acoustic Wave Resonators
Hao Lu1, Xiaorun Hao1, Ling Yang1
1School of Microelectronics, Xidian University, Xi'an 710126, China.
Micromachines
|March 6, 2025
Summary
Aluminum Nitride (AlN)-based Bulk Acoustic Wave (BAW) filters are vital for 5G. This review covers AlN film growth, BAW resonator designs, and advanced filter technologies for improved performance.
Area of Science:
- Materials Science
- Electrical Engineering
- Telecommunications
Background:
- Aluminum Nitride (AlN)-based Bulk Acoustic Wave (BAW) filters are essential for 5G communication, offering high frequency, wide bandwidth, and power capacity.
- AlN resonators form the core of BAW filters, driving advancements in wireless technology.
Purpose of the Study:
- To review the fundamental principles and recent research progress in AlN-based BAW resonators and filters.
- To highlight key fabrication techniques, advanced resonator structures, and filter designs.
- To provide a comprehensive reference for future research and development in AlN-based BAW devices.
Main Methods:
- Summary of epitaxial growth techniques for AlN films, including single-crystal, polycrystalline, and doped variants.
- Discussion of BAW resonator structures such as Solidly Mounted Resonator (SMR) and Film Bulk Acoustic Resonator (FBAR).
- Exploration of advanced technologies like Xtended Bulk Acoustic Wave (XBAW) and Hybrid SAW/BAW Resonators (HSBRs).
Main Results:
- Focus on single-crystal AlN and ScAlN films as leading materials for BAW resonators.
- XBAW technology enhances filter bandwidth, while HSBRs reduce temperature drift.
- Advancements in ladder and lattice BAW filter designs, including frequency-reconfigurable filters, are presented.
Conclusions:
- AlN-based BAW filters are critical for 5G, with ongoing research focusing on material optimization and novel device architectures.
- The review provides insights into fabrication, design, and application of these filters, paving the way for next-generation communication systems.
- Optimization algorithms are crucial for efficient design and improved performance of AlN-based BAW filters.

