Array-scale MUT simulations powered by the cloud

Designing and optimizing ultrasound transducers—whether PMUTs or CMUTs—requires accuracy at scale. 

Yet traditional simulation approaches are often constrained to individual cells or limited structures, leaving important array-level effects poorly understood until expensive and time-consuming testing begins. 

This gap can lead to longer development cycles and higher risk of failed devices.

In this webinar, we will introduce the improved approach: full array-scale MUT simulations with fully coupled multiphysics. 

By leveraging Quanscient’s cloud-native platform, engineers can model entire transducer arrays with all relevant physical interactions (electrical, mechanical, acoustic, and more) capturing system-level behaviors such as beam patterns and cross-talk that single-cell simulations miss.

Cloud scalability also enables extensive design exploration. 

Through parallelization, users can run Monte Carlo analyses, parameter sweeps, and large-scale models in a fraction of the time, enabling rapid optimization and higher throughput in the design process. 

This not only accelerates R&D but ensures more reliable designs before fabrication.

The session will feature real-world case examples with detailed insights of the methodology and key metrics. 

Attendees will gain practical understanding of how array-scale simulation can greatly improve MUT design workflows reducing reliance on costly prototypes, minimizing risk, and delivering better device performance.

Join us to learn how array-scale MUT simulations in the cloud can improve MUT design accuracy, efficiency, and reliability.

Key Learnings for Attendees:

• How full array-scale PMUT and CMUT simulations capture system-level effects such as beam patterns and cross-talk.
• Ways cloud scalability enables Monte Carlo studies, parameter sweeps, and large-scale models with higher throughput.
• Practical insights from real-world case studies, including methodology and key performance metrics.
• How array-scale simulation improves accuracy, efficiency, and reliability while reducing reliance on costly prototypes.