A Flexible Photoactive Titanium Metal–Organic Framework Based on a [TiIV3(μ3‐O)(O)2(COO)6] Cluster

The synthesis of titanium–carboxylate metal–organic frameworks (MOFs) is hampered by the high reactivity of the commonly employed alkoxide precursors. Herein, we present an innovative approach to titanium‐based MOFs by the use of titanocene dichloride to synthesize COK‐69, the first breathing Ti MOF, which is built up from trans‐1,4‐cyclohexanedicarboxylate linkers and an unprecedented [Ti^IV₃(μ₃‐O)(O)₂(COO)₆] cluster. The photoactive properties of COK‐69 were investigated in depth by proton‐coupled electron‐transfer experiments, which revealed that up to one Ti^IV center per cluster can be photoreduced to Ti^III while preserving the structural integrity of the framework. The electronic structure of COK‐69 was determined by molecular modeling, and a band gap of 3.77 eV was found.     

Multiscale Modeling of the Active Site of [Fe] Hydrogenase: The H2 Binding Site in Open and Closed Protein Conformations

A series of QM/MM optimizations of the full protein of [Fe] hydrogenase were performed. The FeGP cofactor has been optimized in the water‐bound resting state ( 1 ), with a side‐on bound dihydrogen ( 2 ), or as a hydride intermediate ( 3 ). For inclusion of H₄ MPT in the closed structure, advanced multiscale modeling appears to be necessary, especially to obtain reliable distances between CH‐H₄MPT⁺ and the dihydrogen (H₂) or hydride (H^?) ligand in the FeGP cofactor. Inclusion of the full protein is further important for the relative energies of the two intermediates 2 and 3 . We finally find that hydride transfer from 3 has a significantly higher barrier than found in previous studies neglecting the full protein environment.     

“Parallel factor analysis of multi-excitation ultraviolet resonance Raman spectra for protein secondary structure determination”

Protein secondary structural analysis is important for understanding the relationship between protein structure and function, or more importantly how changes in structure relate to loss of function. The structurally sensitive protein vibrational modes (amide I, II, III and S) in deep-ultraviolet resonance Raman (DUVRR) spectra resulting from the backbone C–O and N–H vibrations make DUVRR a potentially powerful tool for studying secondary structure changes. Experimental studies reveal that the position and intensity of the four amide modes in DUVRR spectra of proteins are largely correlated with the varying fractions of α-helix, β-sheet and disordered structural content of proteins. Employing multivariate calibration methods and DUVRR spectra of globular proteins with varying structural compositions, the secondary structure of a protein with unknown structure can be predicted. A disadvantage of multivariate calibration methods is the requirement of known concentration or spectral profiles. Second-order curve resolution methods, such as parallel factor analysis (PARAFAC), do not have such a requirement due to the “second-order advantage.” An exceptional feature of DUVRR spectroscopy is that DUVRR spectra are linearly dependent on both excitation wavelength and secondary structure composition. Thus, higher order data can be created by combining protein DUVRR spectra of several proteins collected at multiple excitation wavelengths to give multi-excitation ultraviolet resonance Raman data (ME-UVRR). PARAFAC has been used to analyze ME-UVRR data of nine proteins to resolve the pure spectral, excitation and compositional profiles. A three factor model with non-negativity constraints produced three unique factors that were correlated with the relative abundance of helical, β-sheet and poly-proline II dihedral angles. This is the first empirical evidence that the typically resolved “disordered” spectrum represents the better defined poly-proline II type structure.     

Modeling hydrate formation conditions in the presence of electrolytes and polar inhibitor solutions

In this paper, a new predictive model is proposed for prediction of gas hydrate formation conditions in the presence of single and mixed electrolytes and solutions containing both electrolyte and a polar inhibitor such as monoethylene glycol (MEG), diethylene glycol (DEG) and triethylene glycol (TEG). The proposed model is based on the γ–φ approach, which uses modified Patel–Teja equation of state (VPT EOS) for characterizing the vapor phase, the solid solution theory by van der Waals and Platteeuw for modeling the hydrate phase, the non-electrolyte NRTL-NRF local composition model and Pitzer–Debye–Huckel equation as short-range and long-range contributions to calculate water activity in single electrolyte solutions. Also, the Margules equation was used to determine the activity of water in solutions containing polar inhibitor (glycols). The model predictions are in acceptable agreement with experimental data. For single electrolyte solutions, the model predictions are similar to available models, while for mixtures of electrolytes and mixtures of electrolytes and inhibitors, the proposed model gives significantly better predictions. In addition, the absolute average deviation of hydrate formation pressures (AADP) for 144 experimental data in solutions containing single electrolyte is 5.86% and for 190 experimental data in mixed electrolytes solutions is 5.23%. Furthermore, the proposed model has an AADP of 14.13%, 5.82% and 5.28% in solutions containing (Electrolyte + MEG), (Electrolyte + DEG) and (Electrolyte + TEG), respectively.     

High-pressure phase equilibrium in the {carbon dioxide (1) + 1-chloropropane (2)} binary system

The current study reports original vapour-liquid equilibrium (VLE) for the system {CO₂ (1) + 1-chloropropane (2)}. The measurements have been performed over the entire pressure-composition range for the T = (303.15, 313.15 and 328.15) K isotherms. The values obtained have been used for comparison of four predictive approaches, namely the equation of state (EoS) of Peng and Robinson (PR), the Soave modification of Benedict–Webb–Rubin (SBWR) EoS, the Critical Point-based Revised Perturbed-Chain Association Fluid Theory (CP-PC-SAFT) EoS, and the Conductor-like Screening Model for Real Solvents (COSMO-RS). It has been demonstrated that the three EoS under consideration yield similar and qualitatively accurate predictions of VLE, which is not the case for the COSMO-RS model examined. Although CP-PC-SAFT EoS exhibits only minor superiority in comparison with PR and SBWR EoS in predicting VLE in the system under consideration, its relative complexity can be justified when taking into account the entire thermodynamic phase space and, in particular, considering the liquid densities and sound velocities over a wider pressure-volume-temperature range.     

Detecting changes in arabidopsis cell wall composition using time‐of‐flight secondary ion mass spectrometry

Time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) was previously used to characterize lignocellulosic materials, including woody biomass. ToF‐SIMS can acquire both rapid spectral and spatial information about a sample's surface composition. In the present study, ToF‐SIMS was used to characterize the cell walls of stem tissue from the plant model organism, Arabidopsis thaliana. Using principal component analyses, ToF‐SIMS spectra from A. thaliana wild‐type (Col‐0), cellulose mutant (irx3), and lignin mutant (fah1) stem tissues were distinguished using ToF‐SIMS peaks annotated for wood‐derived lignocellulose, where spectra from the irx3 and fah1 were characterized by comparatively low polysaccharide and syringyl lignin content, respectively. Spatial analyses using ToF‐SIMS imaging furthermore differentiated interfascicular fiber and xylem vessels based on differences in the lignin content of corresponding cell walls. These new data support the applicability of ToF‐SIMS peak annotations based on woody biomass for herbaceous plants, including model plant systems like arabidopsis. Copyright © 2015 John Wiley & Sons, Ltd.     

Multivariate analysis of extremely large ToFSIMS imaging datasets by a rapid PCA method

Principal component analysis (PCA) and other multivariate analysis methods have been used increasingly to analyse and understand depth profiles in X‐ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES) and secondary ion mass spectrometry (SIMS). These methods have proved equally useful in fundamental studies as in applied work where speed of interpretation is very valuable. Until now these methods have been difficult to apply to very large datasets such as spectra associated with 2D images or 3D depth‐profiles. Existing algorithms for computing PCA matrices have been either too slow or demanded more memory than is available on desktop PCs. This often forces analysts to ‘bin’ spectra on much more coarse a grid than they would like, perhaps even to unity mass bins even though much higher resolution is available, or select only part of an image for PCA analysis, even though PCA of the full data would be preferred. We apply the new ‘random vectors’ method of singular value decomposition proposed by Halko and co‐authors to time‐of‐flight (ToF)SIMS data for the first time. This increases the speed of calculation by a factor of several hundred, making PCA of these datasets practical on desktop PCs for the first time. For large images or 3D depth profiles we have implemented a version of this algorithm which minimises memory needs, so that even datasets too large to store in memory can be processed into PCA results on an ordinary PC with a few gigabytes of memory in a few hours. We present results from ToFSIMS imaging of a citrate crystal and a basalt rock sample, the largest of which is 134GB in file size corresponding to 67 111 mass values at each of 512 × 512 pixels. This was processed into 100 PCA components in six hours on a conventional Windows desktop PC. © 2015 The Authors. Surface and Interface Analysis published by John Wiley & Sons Ltd.     

Monte Carlo simulation of full energy spectrum of electrons emitted from silicon in Auger electron spectroscopy

A Monte Carlo simulation including surface excitation, Auger electron‐ and secondary electron production has been performed to calculate the energy spectrum of electrons emitted from silicon in Auger electron spectroscopy (AES), covering the full energy range from the elastic peak down to the true‐secondary‐electron peak. The work aims to provide a more comprehensive understanding of the experimental AES spectrum by integrating the up‐to‐date knowledge of electron scattering and electronic excitation near the solid surface region. The Monte Carlo simulation model of beam–sample interaction includes the atomic ionization and relaxation for Auger electron production with Casnati's ionization cross section, surface plasmon excitation and bulk plasmon excitation as well as other bulk electronic excitation for inelastic scattering of electrons (including primary electrons, Auger electrons and secondary electrons) through a dielectric functional approach, cascade secondary electron production in electron inelastic scattering events, and electron elastic scattering with use of Mott's cross section. The simulated energy spectrum for Si sample describes very well the experimental AES EN(E) spectrum measured with a cylindrical mirror analyzer for primary energies ranging from 500 eV to 3000 eV. Surface excitation is found to affect strongly the loss peak shape and the intensities of the elastic peak and Auger peak, and weakly the low energy backscattering background, but it has less effect to high energy backscattering background and the Auger electron peak shape. Copyright © 2014 John Wiley & Sons, Ltd.     

Symmetry calculation for molecules and transition states

The symmetry of molecules and transition states of elementary reactions is an essential property with important implications for computational chemistry. The automated identification of symmetry by computers is a very useful tool for many applications, but often relies on the availability of three‐dimensional coordinates of the atoms in the molecule and hence becomes less useful when these coordinates are a priori unavailable. This article presents a new algorithm that identifies symmetry of molecules and transition states based on an augmented graph representation of the corresponding structures, in which both topology and the presence of stereocenters are accounted for. The automorphism group order of the graph associated with the molecule or transition state is used as a starting point. A novel concept of label‐stereoisomers, that is, stereoisomers that arise after labeling homomorph substituents in the original molecule so that they become distinguishable, is introduced and used to obtain the symmetry number. The algorithm is characterized by its generic nature and avoids the use of heuristic rules that would limit the applicability. The calculated symmetry numbers are in agreement with expected values for a large and diverse set of structures, ranging from asymmetric, small molecules such as fluorochlorobromomethane to highly symmetric structures found in drug discovery assays. The new algorithm opens up new possibilities for the fast screening of the degree of symmetry of large sets of molecules. © 2014 Wiley Periodicals, Inc.     

The effect of time step,thermostat, and strain rate on ReaxFF simulations of mechanical failure in diamond,graphene, and carbon nanotube

As the sophistication of reactive force fields for molecular modeling continues to increase, their use and applicability has also expanded, sometimes beyond the scope of their original development. Reax Force Field (ReaxFF), for example, was originally developed to model chemical reactions, but is a promising candidate for modeling fracture because of its ability to treat covalent bond cleavage. Performing reliable simulations of a complex process like fracture, however, requires an understanding of the effects that various modeling parameters have on the behavior of the system. This work assesses the effects of time step size, thermostat algorithm and coupling coefficient, and strain rate on the fracture behavior of three carbon‐based materials: graphene, diamond, and a carbon nanotube. It is determined that the simulated stress‐strain behavior is relatively independent of the thermostat algorithm, so long as coupling coefficients are kept above a certain threshold. Likewise, the stress‐strain response of the materials was also independent of the strain rate, if it is kept below a maximum strain rate. Finally, the mechanical properties of the materials predicted by the Chenoweth C/H/O parameterization for ReaxFF are compared with literature values. Some deficiencies in the Chenoweth C/H/O parameterization for predicting mechanical properties of carbon materials are observed. © 2015 Wiley Periodicals, Inc.