Abstract:The relaxation dynamics of the isolated indole molecule has been tracked by femtosecond time-resolved ionization. The excitation region explored (283-243 nm) covers three excited states: the two ππ* L(b) and L(a) states, and the dark πσ* state with dissociative character. In the low energy region (λ > 273 nm) the transients collected reflect the absorption of the long living L(b) state. The L(a) state is met 1000-1500 cm(-1) above the L(b) origin, giving rise to an ultrafast lifetime of 40 fs caused by the int… Show more
“…At these CIs a coherent transfer can occur on a sub-picosecond timescale, dominating the overall k IC . [31][32][33][34][35][36][37][38][39][40][41][42] Computational studies examining IC pathways involving CIs have become more prevalent in the last decade. Unfortunately, IC is a challenging process to model because it arises from non-adiabatic nuclear dynamics.…”
Many emerging technologies depend on human's ability to control and manipulate the excited-state properties of molecular systems. These technologies include fluorescent labeling in biomedical imaging, light harvesting in photovoltaics, and electroluminescence in light-emitting devices. All of these systems suffer from non-radiative loss pathways that dissipate electronic energy as heat, which causes the overall system efficiency to be directly linked to quantum yield (Φ) of the molecular excited state. Unfortunately, Φ is very difficult to predict from first principles because the description of a slow non-radiative decay mechanism requires an accurate description of long-timescale excited-state quantum dynamics. In the present study, we introduce an efficient semiempirical method of calculating the fluorescence quantum yield (Φ fl) for molecular chromophores, which, based on machine learning, converts simple electronic energies computed using time-dependent density functional theory (TDDFT) into an estimate of Φ fl. As with all machine learning strategies, the algorithm needs to be trained on fluorescent dyes for which Φ fl 's are known, so as to provide a black-box method which can later predict Φ's for chemically similar chromophores that have not been studied experimentally. As a first illustration of how our proposed algorithm can be trained, we examine a family of 25 naphthalene derivatives. The simplest application of the energy gap law is found to be inadequate to explain the rates of internal conversion (IC) or intersystem crossing (ISC)-the electronic properties of at least one higher-lying electronic state (S n or T n) or one far-from-equilibrium geometry are typically needed to obtain accurate results. Indeed, the key descriptors turn out to be the transition state between the Franck-Condon minimum a distorted local minimum near an S 0 /S 1 conical intersection (which governs IC) and the magnitude of the spin-orbit coupling (which governs ISC). The resulting Φ fl 's are predicted with reasonable accuracy (± 22%), making our approach a promising ingredient for high-throughput screening and rational design of the molecular excited states with desired Φ's. We thus conclude that our model, while semi-empirical in nature, does in fact extract sound physical insight into the challenge of describing non-radiative relaxations.
“…At these CIs a coherent transfer can occur on a sub-picosecond timescale, dominating the overall k IC . [31][32][33][34][35][36][37][38][39][40][41][42] Computational studies examining IC pathways involving CIs have become more prevalent in the last decade. Unfortunately, IC is a challenging process to model because it arises from non-adiabatic nuclear dynamics.…”
Many emerging technologies depend on human's ability to control and manipulate the excited-state properties of molecular systems. These technologies include fluorescent labeling in biomedical imaging, light harvesting in photovoltaics, and electroluminescence in light-emitting devices. All of these systems suffer from non-radiative loss pathways that dissipate electronic energy as heat, which causes the overall system efficiency to be directly linked to quantum yield (Φ) of the molecular excited state. Unfortunately, Φ is very difficult to predict from first principles because the description of a slow non-radiative decay mechanism requires an accurate description of long-timescale excited-state quantum dynamics. In the present study, we introduce an efficient semiempirical method of calculating the fluorescence quantum yield (Φ fl) for molecular chromophores, which, based on machine learning, converts simple electronic energies computed using time-dependent density functional theory (TDDFT) into an estimate of Φ fl. As with all machine learning strategies, the algorithm needs to be trained on fluorescent dyes for which Φ fl 's are known, so as to provide a black-box method which can later predict Φ's for chemically similar chromophores that have not been studied experimentally. As a first illustration of how our proposed algorithm can be trained, we examine a family of 25 naphthalene derivatives. The simplest application of the energy gap law is found to be inadequate to explain the rates of internal conversion (IC) or intersystem crossing (ISC)-the electronic properties of at least one higher-lying electronic state (S n or T n) or one far-from-equilibrium geometry are typically needed to obtain accurate results. Indeed, the key descriptors turn out to be the transition state between the Franck-Condon minimum a distorted local minimum near an S 0 /S 1 conical intersection (which governs IC) and the magnitude of the spin-orbit coupling (which governs ISC). The resulting Φ fl 's are predicted with reasonable accuracy (± 22%), making our approach a promising ingredient for high-throughput screening and rational design of the molecular excited states with desired Φ's. We thus conclude that our model, while semi-empirical in nature, does in fact extract sound physical insight into the challenge of describing non-radiative relaxations.
“…By recording a series of mass spectra at various time delays (Δ t ) between pump and probe pulses, one is able to track the excited-state dynamics of both the parent molecule and subsequent fragments by monitoring the associated ions. This approach has been successfully used to study excited-state dynamics in nucleobases [18,30,31], phenol [22,32], indole [33], pyrrole [34–36] and imidazole [37,38]. Figure 3.Schematic of a velocity map imaging arrangement used to perform TR-MS, TR-VMI or TR-PES experiments.…”
Section: Experimental Methodologies Using Molecular Beam Methodsmentioning
In many chemical reactions, an activation barrier must be overcome before a chemical transformation can occur. As such, understanding the behaviour of molecules in energetically excited states is critical to understanding the chemical changes that these molecules undergo. Among the most prominent reactions for mankind to understand are chemical changes that occur in our own biological molecules. A notable example is the focus towards understanding the interaction of DNA with ultraviolet radiation and the subsequent chemical changes. However, the interaction of radiation with large biological structures is highly complex, and thus the photochemistry of these systems as a whole is poorly understood. Studying the gas-phase spectroscopy and ultrafast dynamics of the building blocks of these more complex biomolecules offers the tantalizing prospect of providing a scientifically intuitive bottom-up approach, beginning with the study of the subunits of large polymeric biomolecules and monitoring the evolution in photochemistry as the complexity of the molecules is increased. While highly attractive, one of the main challenges of this approach is in transferring large, and in many cases, thermally labile molecules into vacuum. This review discusses the recent advances in cutting-edge experimental methodologies, emerging as excellent candidates for progressing this bottom-up approach.
“…Indole was extensively studied using microwave [1,2] and optical spectroscopy, [3][4][5][6][7][8][9][10] including vibrationally [9,10] and rotationally resolved [3][4][5][6][7][8] electronic spectroscopy, and also using time-resolved ion and photoelectron spectroscopy. [11][12][13] Here, we extend these studies to the investigation of the photophysics and photofragmentation dynamics of indole following soft x-ray absorption.…”
A photofragmentation study of gas-phase indole (C8H7N) upon single-photon ionization at a photon energy of 420 eV is presented. Indole was primarily inner-shell ionized at its nitrogen and carbon 1s orbitals. Electrons and ions were measured in coincidence by means of velocity map imaging. The angular relationship between ionic fragments is discussed along with the possibility to use the angle-resolved coincidence detection to perform experiments on molecules that are strongly oriented in their recoil-frame. The coincident measurement of electrons and ions revealed fragmentation-pathway-dependent electron spectra, linking the structural fragmentation dynamics to different electronic excitations. Evidence for photoelectron-impact self-ionization was observed.
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