MultiphysicsAI has proven itself as a revolutionary tool to design piezoelectric micro-machined ultrasonic transducers (PMUTs). These biodegradable transducers are an important step toward a range of biomedical ultrasonic applications. This is where MultiphysicsAI comes in, revolutionizing PMUT design by leveraging cloud-based FE method simulation, directly integrated with advanced neural surrogates. This transforms a conventional trial-and-error process into a data-driven inverse optimization that is systematic. This groundbreaking technology helps engineers and researchers get to more efficient designs much faster.
The training MultiphysicsAI went through on 10,000 randomized geometries was not a turnkey plug-and-play process. This rich dataset has resulted in the AI generating surrogates with an impressive mean error of only 1%. These AI surrogates allow for inference at lightning speed in under 1 millisecond. This performance evaluation is essential for determining the quality of PMUT designs with respect to KPIs (Key Performance Indicators).
Optimizing Design Performance
Transmit sensitivity, center frequency, fractional bandwidth and electrical impedance are considered key performance indicators of PMUTs. Using MultiphysicsAI, experts will be able to efficiently navigate intricate design trade-offs between the sensitivity and bandwidth. The system’s advanced optimization capabilities enable remarkable improvements in performance metrics that previously took months of testing time to achieve.
MultiphysicsAI’s approach, which includes 10,000 coupled piezoelectric-structural-acoustic simulations, allows for the simultaneous optimization of four key geometric parameters. With this complex mathematical process, the technology realizing proven performance gains happens in a matter of minutes — not days. MultiphysicsAI adopts the Pareto front optimization method to enhance fractional bandwidth from 65% to a remarkable 100%. At the same time, it improves sensitivity by 2-3 dB. In addition to these impressive items, it ensures a consistent center frequency across the downlink of 12 MHz within ±0.2%.
Cloud Infrastructure and Rapid Results
Perhaps the most unique feature of MultiphysicsAI is its use of standard cloud infrastructure, increasing access and scalability. This collaborative, cloud-based framework enables researchers and engineers, regardless of geographic location, to work together more effectively. With the help of AI-driven design optimization, they don’t have to invest in specialized hardware. The system provides fast feedback that expedites the design process. This speed opens up a world of possibilities, enabling teams to iterate and experiment at an unprecedented pace with real-time data.
MultiphysicsAI removes the time-consuming cycle of test, improve, retest that plagues PMUT design. This lets end users focus on leading edge development and iterative improvements. The ability to quickly test multiple geometric scenarios allows teams to focus their efforts on more high-impact, strategic solutions. This greatly accelerates the development and optimization of effective ultrasonic solutions in biomedical applications.
