Digital Twin

A digital twin is a virtual model of materials, devices, and systems that accelerates solar technology development by linking simulation and experimental data.

The Solar TAP platform enables faster and more efficient innovation through data-driven design, predictive modeling, and a reduced need for physical prototypes.

The digital twin integrates workflows across all relevant scales — from morphology formation and optical modeling to electronic transport and energy yield prediction. Machine learning and optimization serve as cross-cutting tools that enhance accuracy and reduce development time.

Multiscale Digital Twin Framework

The diagram shows how Solar TAP links material modeling, optics, electronic processes and device-level simulations into one integrated digital twin.

This enables faster design cycles, early validation and smarter scaling. Each step is enhanced through machine learning and optimization to ensure efficient development of next-generation PV technologies.

Learn more about it in our videos.

Workshop Insights: Digital Twin for Emerging PV

Discover expert talks from our June 2025 workshop, where leading researchers and industry partners share their latest approaches to digital twin technologies in photovoltaics. Each video covers a focused topic — from materials and optics to electronic processes, energy yield modeling, and machine learning and optimization.

Overview

Materials

Optics

Processes

Devices

Machine Learning and Optimization