## AI and Ultrasonic Transducers: A New Frontier A recent whitepaper explores the application of artificial intelligence (AI) to accelerate and improve the design of piezoelectric micromachined ultrasonic transducers (PMUTs), crucial devices in the biomedical field. The document is aimed at MEMS engineers, biomedical device developers, and multiphysics simulation specialists. ## Design Optimization via AI The presented approach combines cloud-based FEM simulations with neural surrogates, transforming the design process from trial-and-error iteration into systematic inverse optimization. Training on 10,000 randomized geometries produces AI surrogates with a 1% mean error and sub-millisecond inference for key performance indicators: transmit sensitivity, center frequency, fractional bandwidth, and electrical impedance. ## Results and Benefits Pareto front optimization simultaneously increases fractional bandwidth from 65% to 100% and improves sensitivity by 2-3 dB while maintaining a 12 MHz center frequency within ±0.2%. This accelerated workflow allows for more efficient exploration of design trade-offs, achieving performance improvements in minutes instead of days, using standard cloud infrastructure.