2024 AIChE Annual Meeting
Date & Time - October 27th-31st, 2024
Location - San Diego, California
Schrödinger is excited to be participating in the 2024 AIChE Annual Meeting taking place on October 27th – 31st in San Diego, California. Join us for presentations by Schrödinger scientists. Stop by booth #521 to speak with us.
OCT 28 | 8:00AM – 8:30AM 
Hilton San Diego Bayfront Hotel, Sapphire Ballroom E Accelerating Polymer Design with Targeted Properties Using Machine Learning and Physics-Based Models
Speaker:
Alex Chew, Principal Scientist I, Schrödinger
Abstract:
Designing new, industrially relevant polymers is challenging because of the need to optimize multiple materials’ properties simultaneously, which is expensive and often infeasible using traditional trial-and-error approaches. One possible solution to identifying promising polymeric materials is to employ a combination of machine learning and physics-based tools to screen the polymer design space and provide suggestions for new polymers that meet the criteria for an industrial application. In this work, we demonstrate a workflow that utilizes machine learning and molecular modeling approaches to design new polymers (specifically, polycarbonates) that satisfy five polymer properties, including the glass transition temperature, optical properties, and mechanical properties. Using a relatively modest dataset of fewer than 200 points, we developed quantitative structure-property relationship (QSPR) models to accurately predict the experimental polymer properties given the homo- or co-polymer structures and composition as input. Leveraging these computationally efficient QSPR models, we then screened over ~10,000 polymer structures that were generated through R-group enumeration tools. We used these QSPR predictions to create multi-parameter optimization scores to help down-select the large polymer space to ~10 promising candidates. We validated the predicted properties of the top polymer candidates using classical molecular dynamics simulations and density functional theory, which revealed reliable correlation between physics-based and QSPR approaches. Finally, we validated the computational predictions against experiments, which showed good agreement with QSPR and physics-based models. Our workflow demonstrates the usefulness of combining data-driven and physics-based approaches in designing new polymers given a small dataset, which is broadly useful for scientists interested in leveraging computer-aided strategies to innovate new materials while mitigating the need for extensive trial-and-error experimentation.
OCT 29 | 4:00PM – 4:30PM
Hilton San Diego Bayfront Hotel, Aqua 300 (AB) Capturing the unmeasurable: How atomistic simulations are bringing understanding to interfacial phenomena
Speaker:
Andrea Browning, Director, Schrödinger
Abstract:
Most materials development at some point must consider an interface. Between adhesives and component parts, between matrix and filler in composite materials, and between atomic layers during assembly, the interface impacts the overall performance of the product. But these surfaces can be difficult to probe experimentally. Atomistic level modeling and simulation techniques such as quantum mechanics and molecular dynamics allows a window into the specific interactions that accumulate into the observed interfacial behavior. As simulation techniques and compute power has grown, we are now better able to explore how interfaces behave. However, there are still challenges remaining such as accounting for reactions at complex, multicomponent interfaces. From battery solid electrolyte interphases to dissolving polymers at tablet interfaces, simulations must capture discrete interactions that are important to the interface in order to be useful. This talk will review examples from various industries in how simulation of interfaces has developed and the role of technology exploration in Dr. Browning’s career evolution.