<span style="font-size: 12.0pt; mso-bidi-font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; color: black; mso-ansi-language: EN-GB; mso-fareast-language: DE; mso-bidi-language: AR-SA;">A Scoring Model for Catalyst Informatics based on Real-Time High-Throughput Fluorogenic Assay for Catalyst Discovery <span style="font-size: 12.0pt; mso-bidi-font-size: 10.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; color: black; mso-ansi-language: EN-US; mso-fareast-language: DE; mso-bidi-language: AR-SA;">and Kinetic Profiling

In this work, we propose an automated, real-time optical scanning approach to assessing catalyst performance in the nitro-to-amine reduction using well-plate readers to monitor reaction progress. This approach takes advantage of a simple on-off fluorescence probe that gives a shift in absorbance and strong fluorescent signal when the non-fluorescent nitro-moiety is reduced to the amine form. The combination of an affordable probe and a low barrier-to-entry technique provides an accessible approach to high-throughput catalyst screening. Under this paradigm, we screened 114 different catalysts and compared them in terms of reaction completion times, material abundance, price, recoverability, and safety. Using a simple scoring system, we plotted the catalysts in terms of cumulative scores, along with some intentional biases, including an emphasis on preference for catalysts with potential as green catalysts, considering environmental issues and possible geopolitical preferences.