Computational approaches combining physics-based molecular modeling with machine learning have revolutionized materials discovery at scale. But challenges still exist when it comes to large-scale and mega-scale simulations in terms of knowledge, infrastructure, speed, and resources.
This talk will showcase how Schrödinger's integrated materials science platform enables massive parallel screening and de novo design campaigns across diverse applications. Through real-world case studies, we will demonstrate automated solutions that have successfully impacted R&D efforts across industries, including designing novel polymers, identifying promising hole-transport materials for organic electronics, and accelerating the discovery of organometallic precursors for thin film processing. We will describe how cloud computing infrastructure in tandem with Schrödinger’s 10+ years of experience executing and supporting large-scale projects facilitates unprecedented throughput in materials screening. Attendees will gain actionable strategies for implementing large-scale computational screening in their own materials research programs, along with best practices for integrating simulation with experiment.
Key Learning Objectives:
- Learn to leverage advanced cloud computing infrastructure to meet the needs of large-scale materials simulations for industry applications.
- Hear case studies and customer success stories across industries including organic electronics, catalysis, energy capture and storage, polymeric materials, consumer packaged goods, pharmaceutical formulations, and thin film processing.
- Learn how Schrödinger can ensure a smooth implementation of a cloud-based materials modeling platform for your organization to maximize the value of digital simulations.
Who Should Attend:
- R&D Leaders
- Innovation Managers
- Digitization Managers
- Synthetic Chemists
- Materials Scientists
- Chemical Engineers
- Materials Research Engineers
- Computational Chemists
- Computational Materials Scientists