An Enantioselective e‐Nose: An Array of Nanoporous Homochiral MOF Films for Stereospecific Sensing of Chiral Odors. Issue 7 (15th December 2020)

• Record Type: Journal Article
• Authors: Okur, Salih; Qin, Peng; Chandresh, Abhinav; Li, Chun; Zhang, Zejun; Lemmer, Ulrich; Heinke, Lars
• Is Part Of: Angewandte Chemie international edition. Volume 60:Issue 7(2021)
• Page Start: 3566
• Page End: 3571
• Publication Date: 2020-12-15
• Subjects: chirality -- electronic nose -- enantioselectivity -- metal–organic frameworks -- sensors; Chemistry -- Periodicals; 540
• DOI: 10.1002/anie.202013227
• Languages: English
• ISSNs: 1433-7851

Abstract

Abstract: Chirality is essential in nature and often pivotal for biological information transfer, for example, via odor messenger molecules. While the human nose can distinguish the enantiomers of many chiral odors, the technical realization by an artificial sensor or an electronic nose, e‐nose, remains a challenge. Herein, we present an array of six sensors coated with nanoporous metal–organic framework (MOF) films of different homochiral and achiral structures, working as an enantioselective e‐nose. While the achiral‐MOF‐film sensors show identical responses for both isomers of one chiral odor molecule, the responses of the homochiral MOF films differ for different enantiomers. By machine learning algorithms, the combined array data allow the stereoselective identification of all compounds, here tested for five pairs of chiral odor molecules. We foresee the chiral‐MOF‐e‐nose, able to enantioselectively detect and discriminate chiral odors, to be a powerful approach towards advanced odor sensing. Abstract : An enantioselective electronic nose based on an array of six sensors coated with nanoporous metal–organic framework films of different homochiral and achiral structures is presented. Each chiral film shows a different response for each enantiomer of the chiral odor molecules, allowing their discrimination. All tested odor molecules can be enantioselectively identified with high precision by using the combined data of the sensor array.