Nortonmeincke6541

Reducing carbon dioxide emissions is one of the possible solutions to prevent global climate change, which is urgently needed for the sustainable development of our society. In this work, easily available, biodegradable amino acid ionic liquids (AAILs) with great potential for CO2 absorption in the manned closed space such as spacecraft, submarines and other manned devices are used as the basic material. Molecular dynamics simulations and ab initio calculations were performed for 12 AAILs ([P4444][X] and [P66614][X], [X] = X = [GLy]-, [Im]-, [Pro]-, [Suc]-, [Lys]-, [Asp]2-), and the dynamic characteristics and the internal mechanism of AAILs to improve CO2 absorption capacity were clarified. Based on structural analysis and the analysis of interaction energy including van der Waals and electrostatic interaction energy, it was revealed that the anion of ionic liquids dominates the interaction between CO2 and AAILs. At the same time, the CO2 absorption capacity of AAILs increases in the order [Asp]2- less then [Suc]- less then [Lys]- less then [Pro]- less then [Im]- less then [Gly]-. Meanwhile, the synergistic absorption of CO2 by multiple-sites of amino and carboxyl groups in the anion was proved by DFT calculations. These findings show that the anion of AAILs can be an effective factor to regulate the CO2 absorption process, which can also provide guidance for the rational and targeted molecular design of AAILs for CO2 capture, especially in the manned closed space.In this study, X-ray imaging of inclusion compounds encapsulating various guest species was investigated based on the calculation of X-ray attenuation coefficients. The optimal photon energies of clathrate hydrates were simulated for high-contrast X-ray imaging based on the type of guest species. The proof of concept was provided by observations of Kr hydrate and tetra-n-butylammonium bromide (TBAB) semi-clathrate hydrate using absorption-contrast X-ray computed tomography (CT) and radiography with monochromated synchrotron X-rays. The radiographic image of the Kr hydrate also revealed a sudden change in its attenuation coefficient owing to the K-absorption edge of Kr as the guest element. With a photon energy of 35 keV, X-ray CT provided sufficient segmentation for the TBAB semi-clathrate hydrate coexisting with ice. In contrast, the simulation did not achieve the sufficient segmentation of the CH4 and CO2 hydrates coexisting with water or ice, but it revealed the capability of absorption-contrast X-ray CT to model the physical properties of clathrate hydrates, such as Ar and Cl2 hydrates. These results demonstrate that the proposed method can be used to investigate the spatial distribution of specific elements within inclusion compounds or porous materials.Photovoltaics is one of the most promising and fastest-growing renewable energy technologies. Although the price-performance ratio of solar cells has improved significantly over recent years, further systematic investigations are needed to achieve higher performance and lower cost for future solar cells. In conjunction with experiments, computer simulations are powerful tools to investigate the thermodynamics and kinetics of solar cells. Over the last few years, we have developed and employed advanced computational techniques to gain a better understanding of solar cells based on copper indium gallium selenide (Cu(In,Ga)Se2). Furthermore, we have utilized state-of-the-art data-driven science and machine learning for the development of photovoltaic materials. In this Perspective, we review our results along with a survey of the field.Scattering resonances above dissociation threshold are computed for four isotopically substituted ozone species 16O18O16O, 16O16O18O, 18O16O18O and 16O18O18O, using a variational method with accurate treatment of the rotation-vibration coupling terms (Coriolis effect) for all values of the total angular momentum J from 0 to 4. Temsirolimus clinical trial To make these calculations numerically affordable, a new approach was developed which employs one vibrational basis set optimized for a typical rotational excitation (J,Λ), to run coupled rotation-vibration calculations at several desired values of J. In order to quantify the effect of Coriolis coupling, new data are contrasted with those computed using the symmetric-top rotor approximation, where the rotation-vibration coupling terms are neglected. It is found that, overall, the major properties of scattering resonances (such as their lifetimes, the number of these states, and their cumulative partition function Q) are all influenced by the Coriolis effect and this influence grows as the angular momentum J is raised. However, it is found that the four isotopically substituted ozone molecules are affected roughly equally by the Coriolis coupling. When the ratio η of partition functions for asymmetric over symmetric ozone molecules is computed, the Coriolis effect largely cancels, and this cancelation seems to occur for all values of J. Therefore, it does not seem grounded to attribute any appreciable mass-independent symmetry-driven isotopic fractionation to the Coriolis coupling effect.Recently, machine learning methods have become easy-to-use tools for constructing high-dimensional interatomic potentials with ab initio accuracy. Although machine-learned interatomic potentials are generally orders of magnitude faster than first-principles calculations, they remain much slower than classical force fields, at the price of using more complex structural descriptors. To bridge this efficiency gap, we propose an embedded atom neural network approach with simple piecewise switching function-based descriptors, resulting in a favorable linear scaling with the number of neighbor atoms. Numerical examples validate that this piecewise machine-learning model can be over an order of magnitude faster than various popular machine-learned potentials with comparable accuracy for both metallic and covalent materials, approaching the speed of the fastest embedded atom method (i.e. several μs per atom per CPU core). The extreme efficiency of this approach promises its potential in first-principles atomistic simulations of very large systems and/or in a long timescale.