Greveirwin0965

Path sampling approaches have become invaluable tools to explore the mechanisms and dynamics of the so-called rare events that are characterized by transitions between metastable states separated by sizable free energy barriers. Their practical application, in particular to ever more complex molecular systems, is, however, not entirely trivial. Focusing on replica exchange transition interface sampling (RETIS) and forward flux sampling (FFS), we discuss a range of analysis tools that can be used to assess the quality and convergence of such simulations, which is crucial to obtain reliable results. The basic ideas of a step-wise evaluation are exemplified for the study of nucleation in several systems with different complexities, providing a general guide for the critical assessment of RETIS and FFS simulations.The properties of KTiOPO4Mx (M = K, Na, and Li; x = 0.000-1.000) as an anode for potassium-ion batteries (PIBs), sodium-ion batteries (SIBs), and lithium-ion batteries (LIBs) are investigated by density functional theory calculations. Our work reveals that the electrochemical performance of KTiOPO4 as an anode for PIBs is superior to that for SIBs and LIBs, in terms of average voltage and ion diffusion kinetics. The ab initio molecular dynamics simulations indicate that the KTiOPO4Mx anode exhibits high structural stability, and alkali ion intercalation contributes to accelerating ion diffusion during the charging process. Particularly, the low activation energy of 0.406 eV of K migration on surface KTP(210), obtained by the climbing-image nudged elastic band method, suggests a high-rate capability. The systematical comparison of the performance of KTiOPO4 as an anode for PIBs, SIBs, and LIBs on the theoretical perspective clarifies that a large channel is not always promising for small radius ion intercalation and diffusion.Particulate physical gels are sparse, low-density amorphous materials in which clusters of glasses are connected to form a heterogeneous network structure. This structure is characterized by two length scales, ξs and ξG ξs measures the length of heterogeneities in the network structure and ξG is the size of glassy clusters. Accordingly, the vibrational states (eigenmodes) of such a material also exhibit a multiscale nature with two characteristic frequencies, ω* and ωG, which are associated with ξs and ξG, respectively (i) phonon-like vibrations in the homogeneous medium at ωω*. Remarkably, the Ioffe-Regel limit is located at the very low frequency of ω*. Thus, phonon transport is localized above ω*, even where phonon-like vibrational states persist. This markedly strong scattering behavior is caused by the sparse, porous structure of the gel.Valence bond (VB) wave functions are studied from the density point of view. The density is plotted as a difference with the quasi-state built on the same orbitals. The densities of the components of the VB wave function are also shown. The breathing orbital effect leads to small modifications of the density. It is shown that while the densities of ionic and covalent components are the same, their coupling ends-up in modifications of the electronic density.The microcanonical temperature of an isolated molecule is derived in terms of Boltzmann and Gibbs volume entropies within the quantum harmonic vibrational and equivalent degenerated model approximations. The effects of the entropy functional choice and various approximations are examined. The difference between Boltzmann and Gibbs volume temperatures is negligible for molecules bigger than ten atoms. However, it is significant for smaller systems, opening a way to probe them experimentally. A simple, analytical expression of the temperature as a function of the vibrational energy is provided, allowing predictions with a ±3% margin of error compared to the exact harmonic estimate. The microcanonical temperature is discussed and exemplified with polycyclic aromatic hydrocarbon molecules and other molecules of astrophysical interest.Due to the lack of specific collisional data, the abundance of NS+ in cold dense interstellar clouds was determined using collisional rate coefficients of CS as a substitute. To better understand the chemistry of sulfur in the interstellar medium, further abundance modeling using the actual NS+ collisional rate coefficients is needed. For this purpose, we have computed the first full 4D potential energy surface of the NS+-H2 van der Waals complex using the explicitly correlated coupled cluster approach with single, double, and non-iterative triple excitation in conjunction with the augmented-correlation consistent-polarized valence triple zeta basis set. The potential energy surface exhibits a global minimum of 848.24 cm-1 for a planar configuration of the complex. The long-range interaction energy, described using multipolar moments, is sensitive to the orientation of H2 up to radial distances of ∼50 a0. From this new interaction potential, we derived excitation cross sections, induced by collision with ortho- and para-H2, for the 15 low-lying rotational levels of NS+ using the quantum mechanical close-coupling approach. By thermally averaging these data, we determined downward rate coefficients for temperatures up to 50 K. By comparing them with the previous NS+-H2 data, we demonstrated that reduced dimensional approaches are not suited for this system. In addition, we found that the CS collisional data underestimate our results by up to an order of magnitude. The differences clearly indicate that the abundance of NS+, in cold dense clouds retrieved from observational spectra, must be reassessed using these new collisional rate coefficients.We explore the photoprotection dynamics of Nannochloropsis oceanica using time-correlated single photon counting under regular and irregular actinic light sequences. The varying light sequences mimic natural conditions, allowing us to probe the real-time response of non-photochemical quenching (NPQ) pathways. Durations of fluctuating light exposure during a fixed total experimental time and prior light exposure of the algae are both found to have a profound effect on NPQ. this website These observations are rationalized with a quantitative model based on the xanthophyll cycle and the protonation of LHCX1. The model is able to accurately describe the dynamics of non-photochemical quenching across a variety of light sequences. The combined model and observations suggest that the accumulation of a quenching complex, likely zeaxanthin bound to a protonated LHCX1, is responsible for the gradual rise in NPQ. Additionally, the model makes specific predictions for the light sequence dependence of xanthophyll concentrations that are in reasonable agreement with independent chromatography measurements taken during a specific light/dark sequence.State specific orbital optimized density functional theory (OO-DFT) methods, such as restricted open-shell Kohn-Sham (ROKS), can attain semiquantitative accuracy for predicting x-ray absorption spectra of closed-shell molecules. OO-DFT methods, however, require that each state be individually optimized. In this Communication, we present an approach to generate an approximate core-excited state density for use with the ROKS energy ansatz, which is capable of giving reasonable accuracy without requiring state-specific optimization. This is achieved by fully optimizing the core-hole through the core-ionized state, followed by the use of electron-addition configuration interaction singles to obtain the particle level. This hybrid approach can be viewed as a DFT generalization of the static-exchange (STEX) method and can attain ∼0.6 eV rms error for the K-edges of C-F through the use of local functionals, such as PBE and OLYP. This ROKS(STEX) approach can also be used to identify important transitions for full OO ROKS treatment and can thus help reduce the computational cost of obtaining OO-DFT quality spectra. ROKS(STEX), therefore, appears to be a useful technique for the efficient prediction of x-ray absorption spectra.Helium droplets are unique hosts for isolating diverse molecular ions for infrared spectroscopic experiments. Recently, it was found that electron impact ionization of ethylene clusters embedded in helium droplets produces diverse carbocations containing three and four carbon atoms, indicating effective ion-molecule reactions. In this work, similar experiments are reported but with the saturated hydrocarbon precursor of ethane. In distinction to ethylene, no characteristic bands of larger covalently bound carbocations were found, indicating inefficient ion-molecule reactions. Instead, the ionization in helium droplets leads to formation of weaker bound dimers, such as (C2H6)(C2H4)+, (C2H6)(C2H5)+, and (C2H6)(C2H6)+, as well as larger clusters containing several ethane molecules attached to C2H4 +, C2H5 +, and C2H6 + ionic cores. The spectra of larger clusters resemble those for neutral, neat ethane clusters. This work shows the utility of the helium droplets to study small ionic clusters at ultra-low temperatures.It has been established that Newton's law of viscosity fails for fluids under strong confinement as the strain-rate varies significantly over molecular length-scales. We thereby investigate if a nonlocal shear stress accounting for the strain-rate of an adjoining region by a convolution relation with a nonlocal viscosity kernel can be employed to predict the gravity-driven isothermal flow of a Weeks-Chandler-Andersen fluid in a nanochannel. We estimate, using the local average density model, the fluid's viscosity kernel from isotropic bulk systems of corresponding state points by the sinusoidal transverse force method. A continuum model is proposed to solve the nonlocal hydrodynamics whose solutions capture the key features and agree qualitatively with the results of non-equilibrium molecular dynamics simulations, with deviations observed mostly near the fluid-channel interface.The artificial intelligence-based prediction of the mechanical properties derived from the tensile test plays a key role in assessing the application profile of new polymeric materials, especially in the design stage, prior to synthesis. This strategy saves time and resources when creating new polymers with improved properties that are increasingly demanded by the market. A quantitative structure-property relationship (QSPR) model for tensile strength at break is presented in this work. The QSPR methodology applied here is based on machine learning tools, visual analytics methods, and expert-in-the-loop strategies. From the whole study, a QSPR model composed of five molecular descriptors that achieved a correlation coefficient of 0.9226 is proposed. We applied visual analytics tools at two levels of analysis a more general one in which models are discarded for redundant information metrics and a deeper one in which a chemistry expert can make decisions on the composition of the model in terms of subsets of molecular descriptors, from a physical-chemical point of view. In this way, with the present work, we close a contribution cycle to polymer informatics, providing QSPR models oriented to the prediction of mechanical properties related to the tensile test.