An in-depth understanding of the electrode-electrolyte interaction and electrochemical reactions at the electrode-solution interfaces in rechargeable batteries is essential to develop novel electrolytes and electrode materials with high performance. In this perspective, we highlight the advantages of the interface-specific sum-frequency generation (SFG) spectroscopy on the studies of the electrode-solution interface for the Li-ion and Li-O2 batteries. The SFG studies in probing solvent adsorption structures and solid-electrolyte interphase formation for the Li-ion battery are briefly reviewed. Recent progress on the SFG study of the oxygen reaction mechanisms and stability of the electrolyte in the Li-O2 battery is also discussed. Finally, we present the current perspective and future directions in the SFG studies on the electrode-electrolyte interfaces toward providing deeper insight into the mechanisms of discharging/charging and parasitic reactions in novel rechargeable battery systems.Electron-phonon interaction strongly affects and often limits charge transport in organic semiconductors (OSs). However, approaches to its experimental probing are still in their infancy. In this study, we probe the local electron-phonon interaction (quantified by the charge-transfer reorganization energy) in small-molecule OSs by means of Raman spectroscopy. Applying density functional theory calculations to four series of oligomeric OSs-polyenes, oligofurans, oligoacenes, and heteroacenes-we extend the previous evidence that the intense Raman vibrational modes considerably contribute to the reorganization energy in several molecules and molecular charge-transfer complexes, to a broader scope of OSs. The correlation between the contribution of the vibrational mode to the reorganization energy and its Raman intensity is especially prominent for the resonance conditions. The experimental Raman spectra obtained with various excitation wavelengths are in good agreement with the theoretical ones, indicating the reliability of our calculations. We also establish for the first time relations between the spectrally integrated Raman intensity, the reorganization energy, and the molecular polarizability for the resonance and off-resonance conditions. The results obtained are expected to facilitate the experimental studies of the electron-phonon interaction in OSs for an improved understanding of charge transport in these materials.Molecular simulations are widely applied in the study of chemical and bio-physical problems. However, the accessible timescales of atomistic simulations are limited, and extracting equilibrium properties of systems containing rare events remains challenging. Two distinct strategies are usually adopted in this regard either sticking to the atomistic level and performing enhanced sampling or trading details for speed by leveraging coarse-grained models. Although both strategies are promising, either of them, if adopted individually, exhibits severe limitations. In this paper, we propose a machine-learning approach to ally both strategies so that simulations on different scales can benefit mutually from their crosstalks Accurate coarse-grained (CG) models can be inferred from the fine-grained (FG) simulations through deep generative learning; in turn, FG simulations can be boosted by the guidance of CG models via deep reinforcement learning. Our method defines a variational and adaptive training objective, which allows end-to-end training of parametric molecular models using deep neural networks. Through multiple experiments, we show that our method is efficient and flexible and performs well on challenging chemical and bio-molecular systems.Recognition and binding of ice by proteins, crystals, and other surfaces is key for their control of the nucleation and growth of ice. Docking is the state-of-the-art computational method to identify ice-binding surfaces (IBS). However, docking methods require a priori knowledge of the ice plane to which the molecules bind and either neglect the competition of ice and water for the IBS or are computationally expensive. Here we present and validate a robust methodology for the identification of the IBS of molecules and crystals that is easy to implement and a hundred times computationally more efficient than the most advanced ice-docking approaches. AZD0095 inhibitor The methodology is based on biased sampling with an order parameter that drives the formation of ice. We validate the method using all-atom and coarse-grained models of organic crystals and proteins. To our knowledge, this approach is the first to simultaneously identify the ice-binding surface as well as the plane of ice to which it binds, without the use of structure search algorithms. We show that biased simulations even identify surfaces that are too small or too weak to heterogeneously nucleate ice. The biasing simulations can be used to identify of IBS of antifreeze and ice nucleating proteins and to equilibrate ice seeds bound to an IBS for the calculation of heterogeneous ice nucleation rates using classical nucleation theory.Rotationally and fine-structure resolved B̃←X̃ laser-induced fluorescence (LIF) spectra of alkoxy radicals have been simulated with a "coupled two-states model" [J. Liu, J. Chem. Phys. 148, 124112 (2018)], in which the nearly degenerate X̃ and à states are considered together. These two electronic states are separated by the "difference potential" and coupled by the spin-orbit (SO) interaction and the Coriolis interaction. Molecular constants determined in fitting the LIF spectra using the coupled two-states model provide quantitative insight into the SO and Coriolis interactions, as well as other intramolecular dynamics, including the pseudo-Jahn-Teller effect. The spectroscopic model also allows semi-quantitative prediction of effective spin-rotation constants using molecular geometry and SO constants, which can be calculated ab initio with considerable accuracy. The dependence of fit values of molecular constants on the size and conformation of alkoxy radicals is discussed.A laser vaporization cluster source is coupled to the Fourier-transform ion cyclotron resonance mass spectrometer beamline of the free-electron laser for intracavity experiments. Gas phase metal ions and their oxides (VO2+, NbO2+, and TaO2+) are formed and spectroscopically characterized using IR multiple-photon dissociation spectroscopy via loss of atomic oxygen and overcoming fragmentation energies of 3 eV-6 eV. The signal is observed for all MO2+ fundamental modes the symmetric and anti-symmetric ν1 and ν3 stretch modes in the 900 cm-1-1000 cm-1 range and the ν2 bending mode in the 300 cm-1-450 cm-1 range. A remarkable substructure is observed for the bending vibration, which is at least partly due to the rovibrational substructure.