Enantioselective Electrophilic Aromatic Nitration
Conference Year
January 2020
Abstract
Enantiomers are non-superimposable mirror images of each other which look almost identical but can have different properties. Often reactions produce racemic (equal) mixtures of these two enantiomers. A recently discovered enantioselective aromatic nitration method allows for the formation of one enantiomeric form of our nitrated substrate in excess of the other. Forming specific desired enantiomers has broad implications to organic synthesis techniques such as Chirality Assisted Synthesis and for the pharmaceutical industry in drug design and development. This presentation reports the development of a chiral auxiliary that made this nitration methodology possible. Chiral auxiliary development was guided, and the success of the auxiliaries explained, by use of Density Functional Theory modeling.
Primary Faculty Mentor Name
Severin T. Schneebeli
Graduate Student Mentors
Joseph Cambell
Faculty/Staff Collaborators
Joseph Cambell (Graduate Student Mentor)
Status
Undergraduate
Student College
College of Arts and Sciences
Program/Major
Biochemistry
Primary Research Category
Engineering & Physical Sciences
Enantioselective Electrophilic Aromatic Nitration
Enantiomers are non-superimposable mirror images of each other which look almost identical but can have different properties. Often reactions produce racemic (equal) mixtures of these two enantiomers. A recently discovered enantioselective aromatic nitration method allows for the formation of one enantiomeric form of our nitrated substrate in excess of the other. Forming specific desired enantiomers has broad implications to organic synthesis techniques such as Chirality Assisted Synthesis and for the pharmaceutical industry in drug design and development. This presentation reports the development of a chiral auxiliary that made this nitration methodology possible. Chiral auxiliary development was guided, and the success of the auxiliaries explained, by use of Density Functional Theory modeling.