Scalable Multiphysics Simulation Software for MEMS

“Quanscient Allsolve is the 'go-to' tool for our most sophisticated superconductor simulations in stellarator design.”

Lucio M. Milanese, PhDCo-founder and COO
Proxima Fusion

”Quanscient Allsolve is a groundbreaking tool for advanced 3D superconductor simulations.”

Antti Stenvall, PhDAdjunct professor
Tampere University

”Allsolve is a key tool for us modelling HTS cables and coils, especially when dealing with complex 3D multiphysics simulations. It has significantly enhanced our efficiency.”

Jiabin YangMagnet Engineer
UKAEA

“With Quanscient Allsolve, I can run complex simulations in under a day, which would otherwise take a week to complete.”

Nicolo Riva, PhDMagnet Engineer
Proxima Fusion

PixierayAntony Hartley, CAE Consultant

"With Quanscient Allsolve, we were able to test different parameters to find the working design from the first iteration, saving three months in product development time."

kiutraKlaus Eibensteiner, Team Lead of Engineering

“Quanscient Allsolve made our hardware iterations much more reliable and functional, speeding up the development process by requiring fewer hardware iterations to get to a finalized product.”

Quanscient Allsolve

Key advantages in MEMS design

Increased simulation throughput

Run thousands of simulations in parallel, explore a wider design space, and optimize device performance without constraints

Tests with real-world conditions

Estimate manufacturing yield by taking into account real-world conditions and manufacturing constraints

Comprehensive multiphysics modeling

Capture complex interactions between elastic waves, acoustics, and piezoelectric / electrostatic effects

Integrate into workflows via API

Integrate Allsolve into your workflows and automate custom design processes with the Quanscient API

Challenges faced with existing solutions

Traditional software often requires simplifications, compromises on accuracy, or long runtimes

Slow prototyping and extended lead times

Extensive physical prototyping to validate designs
Time-consuming and expensive process

Delays product launches and hinders rapid response to manufacturing or reliability issues.

Limited design exploration

Limited computational resources
Inability to fully explore all potential design possibilities

Suboptimal designs that fail to maximize yield, reliability, or performance.

Limited multiphysics capabilities

Complex interactions between multiple physics domains (mechanical, thermal, electrical, fluidic)
Struggle to accurately simulate multiphysics interactions
Simplified models or separate simulations for each domain

Inaccurate results and potential oversights in the design process.

Trouble meshing complex geometries

Struggle to create accurate simulation meshes
Simplified models that do not fully capture the real-world behavior of the device

Less accurate simulation results.

Quanscient Allsolve

Production-level simulation platform for advanced MEMS design

Quanscient Allsolve was developed for accelerating the design and optimization of high-performance MEMS devices by providing accurate, scalable, and efficient multiphysics simulations. As a production-level tool, Allsolve offers capabilities for running large design of experiments for product optimization in later design stages, as well as earlier exploratory simulations.

Quanscient Allsolve

Proven applications

Quanscient Allsolve has been successfully applied to a wide range of ultrasound applications.

Medical imaging

PMUTs, CMUTs, Piezocomposites

Fingerprint sensing

PMUTs, CMUTs, Thin-film piezoelectrics

Wearable devices

Gyroscopes, accelerometers

Microvalves

Electrostatic, piezoelectric, thermal microactuators

Underwater sonar

Piezocomposites, Piezo stacks (Tonpilz, Langevin)

Automotive sensing

Parking sensors, passenger occupancy sensing

Quanscient Allsolve

Proven applications

Quanscient Allsolve has been successfully applied to a wide range of applications.

Fingerprint sensing

PMUTs, CMUTs, Thin-film piezoelectrics

Medical imaging

PMUTs, CMUTs, Piezocomposites

Automotive sensing

Parking sensors, passenger occupancy sensing

Underwater sonar

Piezocomposites, Piezo stacks (Tonpilz, Langevin)

Wearable devices

Gyroscopes, accelerometers

Microvalves

Electrostatic, piezoelectric, thermal microactuators

Real-life example

Estimating yield with a 1000-simulation Monte Carlo analysis

Even small variations can cause significant differences between what we expect in theory and how the device performs in real life.

Through a Monte Carlo analysis you can simulate these variations to predict their impact on device performance.

This method is particularly valuable as it allows engineers to estimate manufacturing yield using pass/fail criteria.

In our webinar in June, we covered the application of Monte Carlo analysis with a single-element PMUT model, running 1000 random variations to analyze performance effects.

This approach ensures greater reliability and efficiency in MEMS design, bridging the gap between simulation and real-world performance while significantly improving manufacturability and yield estimation.

Watch this case example step-by-step →
Download the PDF summary ->

Key features

Complete features for a comprehensive simulation workflow

Comprehensive suite of functionalities

Model import, edit, and material management. Meshing options: Structured, extruded, and tetrahedral. Python scripting interface for limitless customization and functionality. 3D post-processing, visualization, and data export.

Enhanced collaboration and project sharing

Unlimited users within an organization. Secure project sharing with custom permissions. No version incompatibilites.

Cost-effective pricing and simplified IT infrastructure

Flexible pricing according to capacity requirements. Access to high-performance computing resources without the overhead costs. Unlimited users with every plan.