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Data-driven modeling of S<sub>0</sub> → S<sub>1</sub> excitation energy in the BODIPY chemical space: High-throughput computation, quantum machine learning, and inverse design.

Amit Gupta, Sabyasachi Chakraborty, Debashree Ghosh, Raghunathan Ramakrishnan

2021PubMed23 citationsDOI

Abstract

) molecules is demonstrated by inverse-designing candidates with desired target excitation energies.

Topics & Concepts

BODIPYExcitationComputer scienceChemical spaceDensity functional theoryThroughputAlgorithmComputational sciencePhysicsComputational chemistryChemistryQuantum mechanicsFluorescenceTelecommunicationsDrug discoveryBiochemistryWirelessLuminescence and Fluorescent MaterialsNanoplatforms for cancer theranosticsAdvanced biosensing and bioanalysis techniques
Data-driven modeling of S<sub>0</sub> → S<sub>1</sub> excitation energy in the BODIPY chemical space: High-throughput computation, quantum machine learning, and inverse design. | Litcius