IMID 2025

From Molecules to Displays: A Digital Chemistry Platform Uniting Physics-Based Simulation with Machine Learning for Optoelectronic Design

Speaker:
Mathew D. Halls, Senior Vice President of Materials, Schrödinger

Abstract:
Experimental exploration of innovative architectures and material compositions for OLED devices requires substantial time, labor, and resources, due to the complexity and cost of device fabrication, characterization, and analysis. Predictive modeling offers a powerful alternative, enabling efficient and targeted evaluation of devices across broad design spaces by integrating informatics and large-scale property predictions. In this presentation, Schrödinger will showcase recent advances of its digital platform combining machine learning (ML) technologies with quantum mechanics and molecular dynamics. The first advancement extends our automated ML algorithm for chemical formulations [1] to predict performance parameters of multicomponent layered devices, e.g., OLEDs. The second advancement involves overcoming limitations of classical force fields by using a message-passing neural network potential with iterative charge equilibration to achieve quantum mechanical accuracy at minimal computational cost. These ML models encode device components (i.e., material structures, layer architectures, physicochemical properties, and operating conditions) as features to predict OLED device performance metrics for operational output, stability, and efficiency (Fig. 1). This approach moves beyond traditional chemical modeling strategies, capturing complex relationships between device architecture, composition and function. Complementing this development are advances in Schrödinger’s physics-based simulation software, which computes determinative properties of OLED materials. MPNICE, the latest version of our ML potential, delivers accurate DFT-quality predictions at reduced computational cost, enabling simulation of increasingly more complex films and processes. For example, systems combining metal and organic chemistries typically outside the coverage of traditional force fields can now be more efficiently explored. Schrödinger’s new solutions for optoelectronic materials development and device optimization provides unprecedented capabilities for accelerated development of innovative display technologies.