Recent technology advancements have made MultiphysicsAI a first-of-its-kind tool. It particularly improves the design procedure of PMUTs. This pioneering platform integrates cloud computing cloud-based finite element method (FEM) simulations with neural surrogate models. Most importantly, it dramatically accelerates the process of optimizing PMUT designs to meet application requirements. With MultiphysicsAI, the cost of time and resources spent drastically decreases. This allows engineers and researchers to discover new and intricate design trade-offs with unprecedented speed and accuracy.
We field tested the technology in a differentiated case study. This work was centered around the optimization of four geometric PMUT design parameters. This meant running 10,000 coupled piezoelectric-structural-acoustic simulations, a job that in the past would take days of designer-initiated iterations. MultiphysicsAI changes the game entirely. What would have previously taken several days can now be accomplished in only a few minutes, revolutionizing biomedical ultrasonic applications.
The Power of AI in PMUT Design
Unlike its competitors, MultiphysicsAI has unique advantages that allow it to generate AI surrogates with a mean error of only 1%! We all know that precision is important in the biomedical field. Especially for diagnostic applications, the performance of PMUTs is critical in determining their success and therapeutic effectiveness. The modular platform provides sub-millisecond inference on match-grade key performance indicators including transmit sensitivity, center frequency, fractional bandwidth, and electrical impedance. This fast analysis enables engineers to identify and advance the best solutions most quickly.
The tool’s cloud-based infrastructure increases its accessibility and scalability even further. Users are able to tap into very powerful computational resources without requiring any specialized hardware on their end. This evolution, away from big iron and into cloud computing, really reflects how engineering is done today. It strengthens cooperation and accelerates innovation between academic research institutions and industry partners.
Optimizing Design Trade-offs
This is where MultiphysicsAI plays a key role, by skillfully charting the course through intricate design trade-offs. It combines sensitivity and bandwidth with stunning accuracy. Using Pareto front optimization, the platform was able to raise the fractional bandwidth from 65% to a mind-blowing 100%. Moreover, it achieved enhanced sensitivity with 2-3dB improvement and completed constant center frequency at 12 MHz with ±0.2% stability.
These developments highlight how MultiphysicsAI could further unlock PMUT performance in practical applications. Simultaneously optimizing size, weight, and performance is what makes the design process truly powerful. This process unto itself results in the production of more efficient, higher-performing devices.
A New Era for Biomedical Ultrasonic Applications
As the healthcare industry continues to embrace advanced technologies, tools like MultiphysicsAI represent a significant leap forward in the design and optimization of biomedical devices. With MultiphysicsAI, we convert tried-and-true multiphysics/modeling approaches into a data-driven exploration and discovery process. This uniquely positions the company to lead deep into ultrasonic applications.