Theoretical prediction of electronic absorption spectra without input from experiments is no easy feat, as it requires addressing all of the factors that affect line shapes. In practice, however, the methodologies are limited to treat these ingredients only to a certain extent. Here, we present a multiscale protocol that addresses the temperature, solvent, and nuclear quantum effects as well as anharmonicity and the reconstruction of the final spectra from individual transitions. First, quantum mechanics/molecular mechanics (QM/MM) molecular dynamics is conducted to obtain trajectories of solute–solvent configurations, from which the corresponding quantum-corrected ensembles are generated through the generalized smoothed trajectory analysis (GSTA). The optical spectra of the ensembles are then produced by calculating vertical transitions using time-dependent density-functional theory (TDDFT) with implicit solvation. To obtain the final spectral shapes, the stick spectra from TDDFT are convoluted with Gaussian kernels where the half-widths are determined by a statistically motivated strategy. We have tested our method by calculating the UV–vis spectra of a recently discovered acridine photocatalyst in two redox states. Vibronic progressions and broadenings due to the finite lifetime of the excited states are not included in the methodology yet. Nuclear quantization affects the relative peak intensities and widths, which is necessary to reproduce the experimental spectrum. We have also found that using only the optimized geometry of each molecule works surprisingly well if a proper empirical broadening factor is applied. This is explained by the rigidity of the conjugated chromophore moieties of the selected molecules, which are mainly responsible for the excitations in the spectra. In contrast, we have also shown that other parts of the molecules are flexible enough to feature anharmonicities that impair the use of other techniques such as Wigner sampling.

The accurate prediction of excited state properties is a key element of rational photocatalyst design. This involves the prediction of ground and excited state redox potentials, for which an accurate description of electronic structures is needed. Even with highly sophisticated computational approaches, however, a number of difficulties arise from the complexity of excited state redox potentials, as they require the calculation of the corresponding ground state redox potentials and the estimation of the 0-0 transition energies (E_0,0). In this study, we have systematically evaluated the performance of DFT methods for these quantities on a set of 37 organic photocatalysts representing 9 different chromophore scaffolds. We have found that the ground state redox potentials can be predicted with reasonable accuracy that can be further improved by rationally minimizing the systematic underestimations. The challenging part is to obtain E_0,0, as calculating it directly is highly demanding and its accuracy depends strongly on the DFT functional employed. We have found that approximating E_0,0 with appropriately scaled vertical absorption energies offers the best compromise between accuracy and computational effort. An even more accurate and cost-effective approach, however, is to predict E_0,0 with machine learning and avoid the use of DFT for excited state calculations. Indeed, the best excited state redox potential predictions are achieved with the combination of M062X for ground state redox potentials and machine learning (ML) for E_0,0. With this protocol, the excited state redox potential windows of the photocatalyst frameworks could be adequately predicted. This shows the potential of combining DFT with ML in the computational design of photocatalysts with preferred photochemical properties.

Photoredox chemistry has seen a dramatic rise in popularity in recent years, but mechanistic understanding has persistently lagged behind reaction development itself. This is particularly true for the emerging area of consecutive photoinduced electron transfer (conPET), which has attracted both great interest due to its ability to activate inert substrates selectively and under mild conditions and continuing controversy over its mechanistic feasibility. We describe herein the isolation of the key radical intermediate state of an acridinium‐based conPET catalyst and detailed investigations of its photochemistry by a suite of (photo)reactivity, photoluminescence and transient absorption techniques, supported by computational studies. We observe strong wavelength and solvent dependencies in the reactivity profile, which correlate well with observations of a long‐lived, fluorescent excited state that would be compatible with diffusion‐limited reactivity. However, photoluminescence and transient absorption spectroscopies suggest that, counter‐intuitively, this state does not actually participate in reactivity. Instead, changes occur far faster than the diffusion limit, which provides strong, direct evidence for preassembly of the photocatalyst and substrate prior to photoexcitation. Further inspection also indicates parallel formation of solvated electrons, likely providing the major pathway under previously reported synthetic conditions, suggesting that otherwise competing rationales for conPET can in fact operate simultaneously.

[1,2]‐shift of atoms in alkyl fragments belongs to the class of dyotropic rearrangements. Various atoms, including halogens can be involved in the migration, however participation of iodine is unprecedented. Herein, we report our experimental and DFT studies on the oxidation triggered dyotropic rearrangement of iodo and chloro functions via butterfly‐type transition state to demonstrate the migrating ability of λ³‐iodane centre. With the exploitation of dyotropic rearrangement we designed and synthesized a novel fluoroalkyl iodonium reagent from industrial feedstock gas HFO‐1234yf. We demonstrated that the hypervalent reagent serves as an excellent fluoroalkylation agent for various amines and nitrogen heterocycles.

In this paper, the kinetics of the reaction of phenyl isocyanate with crosslinking agents such as sucrose, sorbitol, and glycerol are reported. Crosslinking agents were used in high molar excess to isocyanate to obtain pseudo-first-order rate dependencies, and the reaction products were separated by high-performance liquid chromatography and detected by UV spectroscopy and mass spectrometry. It was found that the glycerol’s primary hydroxyl groups were approximately four times reactive than the secondary ones. However, in the case of sorbitol, the two primary OH groups were found to be the most reactive, and the reactivity of hydroxyl groups decreased in the order of k_OH(6)(8.43) > k_OH(1)(6.91) > k_OH(5)(1.19) > k_OH(2)(0.98) > k_OH(3)(0.93) > k_OH(4)(0.64), where the numbers in the subscript and in the brackets denote the position of OH groups and the pseudo-first-order rate constants, respectively. The Atomic Polar Tenzor (APT) charges of OH groups and dipole moments of monosubstituted sorbitol derivatives calculated by density functional theory (DFT) also confirmed the experimental results. On the other hand, the reactions of phenyl isocyanate with crosslinking agents were also performed using high excess isocyanate in order to determine the number of OH-groups participating effectively in the crosslinking process. However, due to the huge number of derivatives likely formed in these latter reactions, a simplified reaction scheme was introduced to describe the resulting product versus reaction time distributions detected by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS). Based on the results, the kinetically equivalent functionality (f_k) of each crosslinking agent was determined and found to be 2.26, 2.6, and 2.96 for glycerol, sorbitol, and sucrose, respectively.

Monochloramine is a widely employed agent in water treatment technologies. However, its utilization has some drawbacks like the transformation of the active species into the undesired dichloramine. Although it is more pronounced in acidic solutions, the features of this reaction have still remained largely unexplored in the pH < 4 region. In this study the decomposition of monochloramine is examined under such conditions by using kinetic and computational methods. Fast kinetics measurements have convincingly showed that the disproportion into dicloramine is relatively fast and can be studied without any interference from side reactions. By varying the pH, the deprotonation constant of monochloramine has been determined by UV spectroscopy (K_a = 0.023 ± 0.005 M for I = 1.0 M NaClO₄, and T = 25.0 °C). Dichloramine formation via monochloramine disproportion was found to follow second-order kinetics. The computations have provided the reaction mechanism and its free energy profile in accord with the proposed kinetic model. This involves the reaction between the protonated and unprotonated forms of monochloramine, with a rate constant k = 335.3 ± 11.8 M⁻¹ s⁻¹, corresponding to an activation free energy barrier of 14.1 kcal mol⁻¹. The simulations predicted a barrier of 14.9 kcal mol⁻¹ and revealed a key short-lived chlorine-bridged intermediate which yields dichloroamine and ammonium ion through a deprotonation-coupled chlorine shift.