Elementary Reaction Steps That Precede or Follow a Unimolecular Reaction Step Can Obfuscate Interpretation of the Driving-Force Dependence to Its Rate Constant.

Assessing the validity of a driving-force-dependent kinetic theory for a unimolecular elementary reaction step is difficult when the observed reaction rate is strongly influenced by properties of the preceding or following elementary reaction step. A well-known example occurs for bimolecular reactions with weak orbital overlap, such as outer-sphere electron transfer, where bimolecular collisional encounters that precede a fast unimolecular electron-transfer step can limit the observed rate. A lesser-appreciated example occurs for bimolecular reactions with stronger orbital overlap, including many proton-transfer reactions, where equilibration of an endergonic unimolecular proton-transfer step results in a relatively small concentration of reaction products, thus slowing the rate of the following step such that it becomes rate limiting. Incomplete consideration of these points has led to discrepancies in interpretation of data from the literature. Our reanalysis of these data suggests that proton-transfer elementary reaction steps have a nonzero intrinsic free energy barrier, implying, in the parlance of Marcus theory, that there is non-negligible nuclear reorganization. Outcomes from our analyses are generalizable to inner-sphere electron-transfer reactions such as those involved in (photo)electrochemical fuel-forming reactions.

TURBOMOLE: Today and Tomorrow.

TURBOMOLE is a highly optimized software suite for large-scale quantum-chemical and materials science simulations of molecules, clusters, extended systems, and periodic solids. TURBOMOLE uses Gaussian basis sets and has been designed with robust and fast quantum-chemical applications in mind, ranging from homogeneous and heterogeneous catalysis to inorganic and organic chemistry and various types of spectroscopy, light-matter interactions, and biochemistry. This Perspective briefly surveys TURBOMOLE's functionality and highlights recent developments that have taken place between 2020 and 2023, comprising new electronic structure methods for molecules and solids, previously unavailable molecular properties, embedding, and molecular dynamics approaches. Select features under development are reviewed to illustrate the continuous growth of the program suite, including nuclear electronic orbital methods, Hartree-Fock-based adiabatic connection models, simplified time-dependent density functional theory, relativistic effects and magnetic properties, and multiscale modeling of optical properties.

Constructing the Mechanism of Dinoflagellate Luciferin Bioluminescence Using Computation.

Dinoflagellate luciferin bioluminescence is unique since it does not rely on decarboxylation but is poorly understood compared to that of firefly, bacteria, and coelenterata luciferins. Here we computationally investigate possible protonation states, stereoisomers, a chemical mechanism, and the dynamics of the bioluminescence intermediate that is responsible for chemiexcitation. Using semiempirical dynamics, time-dependent density functional theory static calculations, and a correlation diagram, we find that the intermediate's functional group that is likely responsible for chemiexcitation is a 4-member ring, a dioxetanol, that undergoes [2π + 2π] cycloreversion and the biolumiphore is the cleaved structure. The simulated emission spectra and luciferase-dependent absorbance spectra agree with the experimental data, giving support to our proposed mechanism and biolumiphore. We also compute circular dichroism spectra of the intermediate's four stereoisomers to guide future experiments in differentiating them.

Quantification of Excited-State Brønsted-Lowry Acidity of Weak Photoacids Using Steady-State Photoluminescence Spectroscopy and a Driving-Force-Dependent Kinetic Theory.

Photoacids and photobases constitute a class of molecules that upon absorption of light undergoes a reversible change in acidity, i.e. pKa. Knowledge of the excited-state pKa value, pKa*, is critical for predicting excited-state proton-transfer behavior. A reasonable approximation of pKa* is possible using the Förster cycle analysis, but only when the ground-state pKa is known. This poses a challenge for the study of weak photoacids (photobases) with less acidic (basic) excited states (pKa* (pKb*) > 7), because ground-state pKa (pKb) values are >14, making it difficult to quantify them accurately in water. Another method to determine pKa* relies on acid-base titrations with photoluminescence detection and Henderson-Hasselbalch analysis. This method requires that the acid dissociation reaction involving the thermally equilibrated electronic excited state reaches chemical quasi-equilibrium, which does not occur for weak photoacids (photobases) due to slow rates of excited-state proton transfer. Herein, we report a method to overcome these limitations. We demonstrate that liquid water and aqueous hydroxide are unique proton-accepting quenchers of excited-state photoacids. We determine that Stern-Volmer quenching analysis is appropriate to extract rate constants for excited-state proton transfer in aqueous solutions from a weak photoacid, 5-aminonaphthalene-1-sulfonate, to a series of proton-accepting quenchers. Analysis of these data by Marcus-Cohen bond-energy-bond-order theory yields an accurate value for pKa* of 5-aminonaphthalene-1-sulfonate. Our method is broadly accessible because it only requires readily available steady-state photoluminescence spectroscopy. Moreover, our results for weak photoacids are consistent with those from previous studies of strong photoacids, each showing the applicability of kinetic theories to interpret driving-force-dependent rate constants for proton-transfer reactions.

Non-Uniform Sampling in NMR Spectroscopy and the Preservation of Spectral Knowledge in the Time and Frequency Domains.

The increased sensitivity under weighted non-uniform sampling (NUS) is demonstrated and quantified using Monte Carlo simulations of nuclear magnetic resonance (NMR) time- and frequency-domain signals. The concept of spectral knowledge is introduced and shown to be superior to the frequency-domain signal-to-noise ratio for assessing the quality of NMR data. Two methods for rigorously preserving spectral knowledge and the time-domain NUS knowledge enhancement upon transformation to the frequency domain are demonstrated, both theoretically and numerically. The first, non-uniform weighted sampling using consistent root-mean-square noise, is applicable to data sampled on the Nyquist grid, whereas the second, the block Fourier transform using consistent root-mean-square noise, can be used to transform time-domain data acquired with arbitrary, off-grid NUS.