Strong coupling of cavity photons and molecular vibrations creates vibrational polaritons that have been shown to modify chemical reactivity and alter material properties. While ultrafast spectroscopy of vibrational polaritons has been performed intensively in metal complexes, ultrafast dynamics in vibrationally strongly coupled organic molecules remain unexplored. Here, we report ultrafast pump2013probemeasurementandtwo−dimensionalinfraredspectroscopyindiphenylphosphorylazideundervibrationalstrongcoupling.Earlytimeoscillatorystructuresindicatecoherentenergyexchangebetweenthetwopolaritonmodes,whichdecaysin223C2 ps. We observe a large transient absorptive feature around the lower polariton, which can be explained by the overlapped excited-state absorption and derivative-shaped structures around the lower and upper polaritons. The latter feature is explained by the Rabi splitting contraction, which is ascribed to a reduced population in the ground state. These results reassure the previously reported spectroscopic theory to describe nonlinear spectroscopy of vibrational polaritons. We have also noticed the influence of the complicated layer structure of the cavity mirrors. The penetration of the electric field distribution into the layered structure of the dielectric-mirror cavities can significantly affect the Rabi splitting and the decay time constant of polaritonic systems.journal articl
In the pursuit of optimal quantitative structure2013activityrelationship(QSAR)models,twokeyfactorsareparamount:therobustnessofpredictiveabilityandtheinterpretabilityofthemodel.Symbolicregression(SR)searchesforthemathematicalexpressionsthatexplainatrainingdataset.Thus,themodelsprovidedbySRaregloballyinterpretable.WepreviouslyproposedanSRmethodthatcangenerateinterpretableexpressionsbyhumans.Thisstudyintroducesanenhancedsymbolicregressionmethod,termedfilter−inducedgeneticprogramming2(FIGP2),asanextensionofourpreviouslyproposedSRmethod.FIGP2isdesignedtoimprovethegeneralizabilityofSRmodelsandtobeapplicabletodatasetsinwhichcost−intensivedescriptorsareemployed.TheFIGP2methodincorporatestwomajorimprovements:amodifieddomainfiltertoeradicatedivergingexpressionsbasedonoptimalcalculationandtheintroductionofastabilitymetrictopenalizeexpressionsthatwouldleadtooverfitting.Ourretrospectivecomparativeanalysisusing12structure2013activity relationship data sets revealed that FIGP2 surpassed the previously proposed SR method and conventional modeling methods, such as support vector regression and multivariate linear regression in terms of predictive performance. Generated mathematical expressions by FIGP2 were relatively simple and not divergent in the domain of function. Taken together, FIGP2 can be used for making interpretable regression models with predictive ability.journal articl
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