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Register a new userAb initio analysis of the x-ray absorption spectrum of the myoglobin-carbon monoxide complex: Structure and vibrations
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We present a comparison between Fe K-edge x-ray absorption spectra of carbonmonoxy-myoglobin and its simulation based on density-functional theory determination of the structure and vibrations and spectral simulation with multiple-scattering theory. An excellent comparison is obtained for the main part of the molecular structure without any structural fitting parameters. The geometry of the CO ligand is reliably determined using a synergic approach to data analysis. The methodology underlying this approach is expected to be especially useful in similar situations in which high-resolution data for structure and vibrations are available.
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The luminous infrared-loud quasar IRAS 13349+2438 was observed with the XMM-Newton Observatory as part of the Performance Verification program. The spectrum obtained by the Reflection Grating Spectrometer (RGS) exhibits broad (v ~ 1400 km/s FWHM) absorption lines from highly ionized elements including hydrogen- and helium-like carbon, nitrogen, oxygen, and neon, and several iron L-shell ions (Fe XVII - XX). Also shown in the spectrum is the first astrophysical detection of a broad absorption feature around lambda = 16 - 17 Ang identified as an unresolved transition array (UTA) of 2p - 3d inner-shell absorption by iron M-shell ions in a much cooler medium; a feature that might be misidentified as an O VII edge when observed with moderate resolution spectrometers. No absorption edges are clearly detected in the spectrum. We demonstrate that the RGS spectrum of IRAS 13349+2438 exhibits absorption lines from at least two distinct regions, one of which is tentatively associated with the medium that produces the optical/UV reddening.
Single-Particle Reconstruction (SPR) in Cryo-Electron Microscopy (cryo-EM) is the task of estimating the 3D structure of a molecule from a set of noisy 2D projections, taken from unknown viewing directions. Many algorithms for SPR start from an initial reference molecule, and alternate between refining the estimated viewing angles given the molecule, and refining the molecule given the viewing angles. This scheme is called iterative refinement. Reliance on an initial, user-chosen reference introduces model bias, and poor initialization can lead to slow convergence. Furthermore, since no ground truth is available for an unsolved molecule, it is difficult to validate the obtained results. This creates the need for high quality ab initio models that can be quickly obtained from experimental data with minimal priors, and which can also be used for validation. We propose a procedure to obtain such an ab initio model directly from raw data using Kams autocorrelation method. Kams method has been known since 1980, but it leads to an underdetermined system, with missing orthogonal matrices. Until now, this system has been solved only for special cases, such as highly symmetric molecules or molecules for which a homologous structure was already available. In this paper, we show that knowledge of just two clean projections is sufficient to guarantee a unique solution to the system. This system is solved by an optimization-based heuristic. For the first time, we are then able to obtain a low-resolution ab initio model of an asymmetric molecule directly from raw data, without 2D class averaging and without tilting. Numerical results are presented on both synthetic and experimental data.
X-ray photoemission (XPS) and Near Edge X-ray Absorption Fine Structure (NEXAFS) spectroscopy play an important role in investigating the structure and electronic structure of materials and surfaces. Ab-initio simulations provide crucial support for the interpretation of complex spectra containing overlapping signatures. Approximate core-hole simulation methods based on Density Functional Theory such as the Delta-Self-Consistent-Field ($Delta$SCF) method or the transition potential (TP) method are widely used to predict K-shell XPS and NEXAFS signatures of organic molecules, inorganic materials and metal-organic interfaces at reliable accuracy and affordable computational cost. We present the numerical and technical details of our variants of the $Delta$SCF and transition potential method (coined $Delta$IP-TP) to simulate XPS and NEXAFS transitions. Using exemplary molecules in gas-phase, in bulk crystals, and at metal-organic interfaces, we systematically assess how practical simulation choices affect the stability and accuracy of simulations. These include the choice of exchange-correlation functional, basis set, the method of core-hole localization, and the use of periodic boundary conditions. We particularly focus on the choice of aperiodic or periodic description of systems and how spurious charge effects in periodic calculations affect the simulation outcomes. For the benefit of practitioners in the field, we discuss sensible default choices, limitations of the methods, and future prospects.
Graphene oxide (GO) holds significant promise for electronic devices and nanocomposite materials. A number of models were proposed for GO structure, combining carboxyl, hydroxyl, carbonyl and epoxide groups at different locations. The complexity and variety of GO isomers, whose thermodynamic stability and formation kinetics depend on applied conditions, make determination of GO structure with atomistic precision challenging. We report high level theoretical investigation of multiple molecular configurations, which are anticipated in GO. We conclude that all oxygen containing groups at the GO surface are thermodynamically permitted, whereas the edge positions are systematically more favorable than the center and side positions. We discuss a potentially novel type of chemical bond or bonding reinforcement in GO, which consists of a covalent bond and a strong electrostatic contribution from a polarized graphene plane. We observe and analyze significant modifications of graphene geometry and electronic structure upon oxidation. The reported thermodynamic data guide experiments aimed at deciphering GO chemical composition and structure, and form the basis for predicting GO properties required for nano-technological applications.
Water is of the utmost importance for life and technology. However, a genuinely predictive ab initio model of water has eluded scientists. We demonstrate that a fully ab initio approach, relying on the strongly constrained and appropriately normed (SCAN) density functional, provides such a description of water. SCAN accurately describes the balance among covalent bonds, hydrogen bonds, and van der Waals interactions that dictates the structure and dynamics of liquid water. Notably, SCAN captures the density difference between water and ice I{it h} at ambient conditions, as well as many important structural, electronic, and dynamic properties of liquid water. These successful predictions of the versatile SCAN functional open the gates to study complex processes in aqueous phase chemistry and the interactions of water with other materials in an efficient, accurate, and predictive, ab initio manner.
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