Purpose:
The Data Science and Modeling for Green Chemistry award aims to recognize the research and development of computational tools that guide the design of sustainable chemical processes and the execution of green chemistry that demonstrates compelling environmental, safety, and efficiency improvements over current technologies in the pharmaceutical industry and its allied industrial partners.
Description:
The award recognizes innovation or excellence in the research and development of computational tools empowering users to effectively design, implement, and evaluate green processes with reduced process mass intensity, waste, health and safety impact, and other aspirational improvements.
The award will be presented at the Green Chemistry & Engineering Conference. The recipient, or a member of the winning team, will be invited to share their technology in an oral presentation at this event. The recipient’s transportation, lodging, and registration fees for the conference are reimbursable up to $2,500 USD (additional funds available for international travel following ACS guidelines). The recipient or winning team will also receive a plaque recognizing the achievement and certificates will be given to each team member.
Eligibility:
The computational invention can take the form of algorithms and/or software tools. All inventions that innovatively leverage machine learning/data science and other computational modeling techniques are in scope. Submissions should both highlight the technological breakthrough and show how the tool is specifically designed for end-users to drive towards greener processes (see selection criteria). Both academic and industrial research groups are eligible. Nominees do not have to be members of the American Chemical Society or the ACS GCIPR.