A Fully Automated Continuous‐Flow Platform for Fluorescence Quenching Studies and Stern–Volmer Analysis
Herein, we report the first fully automated continuous‐flow platform for fluorescence quenching studies and Stern–Volmer analysis. All the components of the platform were automated and controlled by a self‐written Python script. A user‐friendly software allows even inexperienced operators to perform...
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Published in: | Angewandte Chemie International Edition Vol. 57; no. 35; pp. 11278 - 11282 |
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Main Authors: | , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Germany
Wiley Subscription Services, Inc
27-08-2018
John Wiley and Sons Inc |
Edition: | International ed. in English |
Subjects: | |
Online Access: | Get full text |
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Summary: | Herein, we report the first fully automated continuous‐flow platform for fluorescence quenching studies and Stern–Volmer analysis. All the components of the platform were automated and controlled by a self‐written Python script. A user‐friendly software allows even inexperienced operators to perform automated screening of novel quenchers or Stern–Volmer analysis, thus accelerating and facilitating both reaction discovery and mechanistic studies. The operational simplicity of our system affords a time and labor reduction over batch methods while increasing the accuracy and reproducibility of the data produced. Finally, the applicability of our platform is elucidated through relevant case studies.
Rapid performance: The first fully automated continuous‐flow platform for fluorescence quenching studies and Stern–Volmer analysis is described. Equipped with user‐friendly software, the platform offers to any user the possibility to rapidly perform (<1 hour) these insightful analyses, thus accelerating reaction discovery. Compared to batch methods, an increase in the accuracy and reproducibility of the measured data was observed. |
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Bibliography: | These authors contributed equally to this work. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1433-7851 1521-3773 |
DOI: | 10.1002/anie.201805632 |