American Chemical Society (ACS) Fall Meeting 2023

American Chemical Society (ACS) Fall Meeting 2023: Harnassing the Power of Data

Join Enthought at the 2023 American Chemical Society (ACS) Fall Meeting on August 13-17 in San Francisco. ACS is one of the world’s largest scientific organizations with more than 173,000 members across 140 countries. At the annual Fall Meeting, leaders in R&D from industry and academia convene to learn about what’s the newest advancements in scientific research and technology.

Please come say hello!

 

Enthought at the Expo (Booth #456) | AI-Driven Solutions for Materials Science and Chemistry

Visit us at the Enthought booth (#456) at the Expo at the Moscone Center! We’re so excited to meet everyone in person. Come chat about how AI-driven solutions can advance materials science and chemical research in your research organization. AND get a very special giveaway! Let us know you’re coming by here. Hours of the Expo are:

• Monday, August 14 (11am – 5pm)
• Tuesday, August 15 (11am – 5pm)
• Wednesday, August 16 (10am – 2pm)

 

Session with Dr. Mike Heiber | Making an Impact in Industrial Polymer Product Development with Materials Informatics

Our own Dr. Mike Heiber, Materials Informatics Manager, will be speaking on the first day of the conference on Sunday, August 13th. Dr. Heiber holds a Ph.D. in polymer science and leads Enthought’s Materials Informatics Acceleration Program for R&D labs. His talk, Making an Impact in Industrial Polymer Product Development with Materials Informatics, is part of the session Application of Machine Learning in Polymers: Molecular Structure, Properties, Formulations, and Processing sponsored by ACS’s Division of Polymeric Materials Science and Engineering. Session details and abstract below.

Making an Impact in Industrial Polymer Product Development with Materials informatics
Session: Application of Machine Learning in Polymers: Molecular Structure, Properties, Formulations, and Processing
Sunday, August 13, 2023 | 10:35am-10:55am
San Francisco Marriot Marquis | Salon 1
Session Link

Abstract

Materials informatics methods and technologies have become extremely popular in the academic and government research community with many research teams adapting machine learning and AI concepts from other domains and applying them to the unique challenges of materials and chemical development. There are already numerous proof of concept examples for how these tools can accelerate and reduce the cost of developing multifunctional materials and formulations with target properties. However, translating this to industrial product development success is challenging due to the addition of many new technical and non-technical challenges that come into play, including new engineering and market-driven constraints, overcoming risk aversion and resistance to change, and identifying the right business-relevant projects that will generate a good return on investment. In this talk, we’ll present several industrial use-case examples that demonstrate proven strategies and techniques to successfully use data-driven methods to accelerate polymer product development. We hope this topic will be of particular interest to industrial researchers seeking to integrate materials informatics tools into their labs and to graduate students and postdocs interested in bringing their valuable digital R&D skills to industry.

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