Neural Network-Aided Spurious Modes Optimization Targeting Lithium Niobate MEMS Resonators
Author:
Affiliation:
1. Northeastern University,Department of Electrical and Computer Engineering,USA
Funder
Defense Advanced Research Project Agency Microsystems Technology Office (DARPA MTO)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9865233/9865240/09865277.pdf?arnumber=9865277
Reference20 articles.
1. High kt2×Q, multi-frequency lithium niobate resonators
2. Exploiting parallelism in resonators for large voltage gain in low power wake up radio front ends
3. Frequency-scalable fabrication process flow for lithium niobate based Lamb wave resonators
4. RF acoustic microsystems based on suspended lithium niobate thin films: advances and outlook
5. VHF and UHF Lithium Niobate MEMS Resonators Exceeding 30 dB of Passive Gain
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1. Neural Network Assisted 3D FBAR Modeling With Random Electrode Shapes;2024 IEEE MTT-S International Conference on Microwave Acoustics & Mechanics (IC-MAM);2024-05-13
2. Near Spurious-Free Thickness Shear Mode Lithium Niobate Resonator for Piezoelectric Power Conversion;IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control;2023-11
3. ANOVA Investigation of Neural Network Guided Spurious Modes Reduction in Lithium Niobate MEMS Resonators;2023 Joint Conference of the European Frequency and Time Forum and IEEE International Frequency Control Symposium (EFTF/IFCS);2023-05-15
4. Near-Spurious-Free Lithium Niobate Resonator for Piezoelectric Power Conversion with $Q$ of 3500 and k2 t of 45%;2022 IEEE International Ultrasonics Symposium (IUS);2022-10-10
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