BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//UM//UM*Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/Detroit
TZURL:http://tzurl.org/zoneinfo/America/Detroit
X-LIC-LOCATION:America/Detroit
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20070311T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20071104T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20230810T081908
DTSTART;TZID=America/Detroit:20230824T080000
DTEND;TZID=America/Detroit:20230824T180000
SUMMARY:Conference / Symposium:Merck Symposium 2023
DESCRIPTION:ACADEMIC KEYNOTE TITLE: Organic Reaction Development Meets Data Science\n\nABSTRACT: The optimization of catalytic reactions for organic synthesis is difficult as the interplay between the ligand\, reaction conditions\, and substrates involved is a complex multidimensional problem. In other words\, it is difficult to ascertain the pattern within the noise to offer a complete picture of how to optimize and/or interrupt why a certain set of conditions are required for a particular reaction. Therefore\, we have aimed to develop several data science-based tools that assist the rapid analysis of structure function relationships to reveal the underlying reasons for improved performance of substrates and catalysts. Specifically\, we have used new methods to develop descriptors for complex molecular architectures as well as data science methods to discern how these catalysts interact with a range of substrate types. This lecture will outline how we have put into practice a workflow that integrates data science tools\, physical organic chemistry\, and reaction optimization with a focus on new case studies in catalytic processes.
UID:109245-21821306@events.umich.edu
URL:https://events.umich.edu/event/109245
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Chemistry,Physical Chemistry,Science
LOCATION:Chemistry Dow Lab - 1300
CONTACT:
END:VEVENT
END:VCALENDAR