Practical Aspects of Computational Chemistry III

The present chapter depicts various theoretical methods that have been used in the context of experimental studies at the nanoscale. With the scanning tunneling microscopy (STM), we can investigate the manipulation of individual molecules and their electronic properties through electronically induced excitations. To explore in details the surface dynamics of a molecule in a bistable or quadristable motion, the nudged elastic band method is used to describe the energy barrier of the saddle point located along the molecular reaction pathway. When the physisorbed stilbene molecule is studied on the bare Si(100), the tight binding method is associated to the density functional theory (DFT) to simulate the scanning tunneling topographies. The physisorption of a molecule such as the hexaphenyle-benzene at the step edge of the Si(100) show particular lateral movements which diffusion barrier can be described accurately by the dispersive term added to the DFT to describe van der Waals interactions (DFT-D). In order to identify the nature of bonding of a porphyrin molecule adsorbed on a boron doped silicon surface, we have analyzed the Laplacian of the charge density. Finally, we present a full DFT-D study of a bidimensional nanoporous supramolecular network on a silicon surface. We have evaluated the molecule-molecule and molecule-substrate interactions energies that are key parameters to understand the mechanism of formation of these networks. In this context, the simulations of STM images with multi-diffusion with the presence of a tungsten tip show a better agreement with the experimental observations than the Tersoff-Hamann approach.

This chapter reviews structures and properties of various TiN-based heterostructures. The study of such systems is of vital importance in development of new materials with desired optimum properties. After discussion of the current literature, the recently published results of first-principles quantum molecular dynamics (QMD) calculations of heterostructures consisting of one monolayer of interfacial SiNx, SiC, BN and AlN inserted between several monolayers thick slabs of B1(NaCl)-TiN (001) and (111) in the temperature range of 0–1,400 K are reviewed in some detail. The results revealed that SiN(001) exists as pseudomorphic B1-SiN interfacial layer only at 0 K. At finite temperature, this heterostructure transforms into distorted octahedral SiN₆ and tetrahedral SiN₄ units aligned along the {110} directions. At 300 K, the aggregates of the SiN_x units are close to a disordered, essentially amorphous SiN. After heating to 1,400 K and subsequent relaxation at 300 K, the interfacial layer corresponds to a strongly distorted Si₃N₄-like structure. The B1-SiN, Si₃N₄-like SiN and Si₃N₄-like Si₂N₃ interfaces between the TiN(111) slabs are stable in the whole temperature range considered here. The B1-Si₃N₄-like interfaces derived from SiN by the formation of Si-vacancies are unstable at finite temperatures. An estimate of interfacial formation energies showed that the most favorable configurations of the (111) interfaces are silicon atoms tetrahedrally coordinated to nitrogen. The most stable (001) B1-derived heterostructure with Si_0.75 N interface consist of both tetrahedrally and octahedrally coordinated silicon atoms. The TiN(001)/B1-SiC/TiN(001) interface exists as pseudo-morphic B1-SiC layer between 0 K and 600 K. After heating to 900–1,400 K and subsequent static relaxations, the interfacial layer corresponds to a strongly distorted 3C-SiC-like structure oriented in the (111) direction in which the Si and C atoms are located in the same interfacial plane. The Si atoms form fourfold coordinated N-Si ≡ C₃ configurations, whereas the C atoms are located in the Ti₂ = C ≡ Si₃ surrounding. All the (111) interfaces simulated at 0, 300, and 1,400 K have the same atomic configurations. For these interfaces, the Si and C layers correspond to the Si-C network in the (111) direction of 3C-SiC. The Si and C atoms are located in N-Si ≡ C₃ and Ti₃ ≡ C ≡ Si₃ configurations, respectively. The BN(001) interfacial layer forms a disordered h-BN-like structure consisting of BN₃ units in the whole temperature range considered here. Finally, the B1-AlN(001) interface is found to be stable within the whole temperature range.

Phonon calculations show that the observed modifications of the interfaces are due to dynamical instability of the B1-type (001) and (111) interfacial layers of BN, SiC and SiN driven by soft modes within the given planes. The calculated electronic densities of states (EDOS) of the (001) interfaces suggest that the reconstructed interfaces should be semiconducting.

Surfaces of some materials exhibit vastly different structure than the bulk-truncated atomic structure due to the reduced surface atomic coordination that leads to surface dangling bonds and/or surface stress. In order to relieve the stress, partial dislocation networks are formed on some surfaces, changing the surface periodicity to tens or hundreds of nanometers. By using Pt(111) and Ag/Ag/Pt(111) surface reconstructions as examples, we demonstrate how such large length scale pattern formation can be investigated using “classical” models parameterized within density functional theory. We then present an example of determining the magnetic state of ultrathin films on semimetallic substrates. It is possible that such magnetic films also get reconstructed due to the mismatch in lattice spacing between the film and the substrate. Although the pattern formation on magnetic films can be studied using similar type of models, determining the magnetic state of such superstructures requires further modeling efforts.

We report a comprehensive review on the geometric, electronic and energetic properties and the CO adsorption on bimetallic clusters Au _n V in the range of n = 1−20, obtained using density functional theory computations (BB95 and B3LYP functionals in conjunction with the pseudo-potential cc-pVDZ-PP basis set for metals and the full-electron cc-pVTZ basis set for non-metals). The effects of the vanadium dopant on the properties of gold clusters are analyzed in detail.

The structures of endohedral complexes of polyhedral oligomeric silsesquioxane (POSS) cage molecules (HSiO_3/2)₈, (HSiO_3/2)₁₀, and (HSiO_3/2)₁₂, containing either atomic or ionic lithium species are determined using density functional theory with the B3LYP functional and the 6-311G(d,p) and 6-311+G(d,p) basis sets. The structures and stabilities of these nanostructures depend on the cage size and the number and charge of the Li species encapsulated in the (HSiO_3/2)₈, (HSiO_3/2)₁₀, and (HSiO_3/2)₁₂ host cages. Li cation encapsulation shows attractive interactions with cage oxygen atoms leading to cage shrinkage. Li anion encapsulation breaks the (HSiO_3/2)₈ host cage. Stable endohedral POSS cages with varying number of neutral and ionic lithium were identified by calculating their inclusion energies and adiabatic and vertical ionization potentials.

The magnetic properties of axially confined hydrogenated single-walled carbon nanotubes (SWCNTs) of the (n, 0) type, as well as cross-linking architectures based on these units, are systematically explored by use of density functional theory. Emphasis is placed on the relation between the ground state magnetic moments of SWCNTs and zigzag graphene nanoribbons (ZGNRs). Comparison between SWCNTs with n = 5–24 and ZGNRs of equal length gives rise to two basic questions: (1) how does the nanotube curvature affect the antiferromagnetic order known to prevail in ZGNRs, and (2) to what extent do the magnetic moments localized at the SWCNT edges deviate from the zero-curvature limit n/3 μ_B? The studies on single SWCNTs are extended to cross-linking carbon nanotubes (CLCNTs) composed of three axially confined single-walled carbon nanotubes (SWCNTs) of the (10,0) type. Three CLCNT models, differing from each other by the structure of the contact regions of the three SWCNT constituents, are explored in terms of their geometric, electronic, and magnetic properties. Various magnetic phases, as obtained by combining finite SWCNTs in ferromagnetic (FM) or antiferromagnetic (AFM) coordination, are distinguished. The characteristics of these phases are shown to depend on the contact region geometry which plays an essential role in defining the order of their stabilities. Prospects of applying either of the two systems analyzed here, SWCNTs and CLCNTs, as transmission elements in spintronics are discussed.

It is not always possible to build predictive Quantitative Structure-Activity Relationships (QSAR) models for a given chemical dataset. In this work, we propose several statistical criteria, which can with high confidence answer a question, whether it is possible to build a predictive model for a dataset prior to actual modeling, i.e. to establish, whether the dataset is modelable. Calculation of these criteria is fast, and using them in QSAR studies could dramatically reduce modelers’ time and efforts, as well as computational resources necessary to build QSAR models for at least some datasets, especially for those which are not modelable. The calculation of modelability criteria is based on the k-nearest neighbors approach. For all datasets, as modelability criteria we have proposed dataset diversity (MODI_DIV) and new activity cliff indices (MODI_ACI). For datasets with binary end points, as modelability criteria we have proposed the correct classification rate (MODI_CCR) CCR = 0.5(sensitivity + specificity) for leave-one-out (LOO) cross-validation in the entire descriptor space, and correct classification rate for similarity search (MODI_ssCCR) in the entire descriptor space with leave 20 %-out (five-fold) cross-validation. For binary datasets, all these modelability criteria were tested on 42 datasets with previously generated QSAR models. Two latter criteria (MODI_CCR and MODI_ssCCR) were found to have high correlation with the predictivity of QSAR models (QSAR_CCR) and were additionally tested on 60 ToxCast end points with QSAR modeling results published recently (Thomas RS, Black MB, Li L, Healy E, Chu T-M, Bao W, Andersen MD, Wolfinger RD. Toxicol Sci: Off JSoc Toxicol 128(2):398–417, 2012). These modelability criteria can be used to classify many datasets as modelable or non-modelable. These criteria can be generalized to datasets with compounds belonging to more than two categories or classes. Additionally, criteria which take into account errors of prediction MODI_CAT _i and MODI_CLASS _i were proposed for datasets with compounds belonging to more than two (i > 2) categories or classes and continuous end points, divided into i > 2 bins. For continuous end points, LOO cross-validation q ² for similarity search with different numbers of nearest neighbors in the entire descriptor space (MODI_q ²), and similarity search coefficient of determination (MODI_ssR ²) in the entire descriptor space were proposed as modelability criteria. Our preliminary studies demonstrated high correlation between the external predictivity of QSAR models (QSAR_R ²) and each of the MODI_q ² and MODI_ssR ². On the other hand, for datasets with any binary or continuous response variable, MODI_DIVs and MODI_ACIs were found to be less useful to establish dataset modelability.

To obtain stable states (SS) and transition states (TS) in chemical reactions in condensed phase, the free energy gradient (FEG) method was proposed in 1998 as an optimization method on a multidimensional free energy surface (FES). Analogous to the method for the Born Oppenheimer potential energy surface (PES) using ab initio molecular orbital calculation, the FEG method utilizes the force and Hessian on the FES, which can be adiabatically calculated by molecular dynamics (MD) or Monte Carlo (MC) methods, and, originally, the free energy (FE) perturbation theory. In fact, since then, a number of excellent approximate methods have been developed, e.g., the averaged solvent electrostatic potential (ASEP)/MD method and the average solvent electrostatic configuration (ASEC) method. In this chapter, the FEG methodology is reviewed in general and a future perspective to explore the FE landscape is introduced together with several applications of these methods. Based on computational demands and on the numerical accuracy, we believe that a family of the FEG methodologies should become more efficient as one strategic setting and will play promising and important roles to survey condensed state chemistry on the basis of recent supercomputing technology.

Non-point source pollution has become the major source of surface water impairment in the United States. The transport of suspended sediments and nutrients from watersheds to aquatic resources directly influences their environmental quality and ecosystem. The Environmental Protection Agency calculates maximum daily loads from watersheds that allow receiving water bodies to meet water quality standards and mandates load reductions on suspended sediments, nutrients, and other pollutants through the implementation of best management practices. Calculation of these loads and assessment of best management practices is often done with simplified methods, such as spreadsheets and lumped, empirical models that do not account for the spatial heterogeneity or the physical processes occurring in the watershed. The physically based, distributed watershed hydrologic, sediment, constituent transport and fate model Gridded Surface Subsurface Hydrologic Analysis (GSSHA) represents another approach where the spatial heterogeneity, physical and chemical processes in the watershed are explicitly included in the simulation. In this study, GSSHA is used to simulate sediment, nitrogen and phosphorous in Eight-Mile Run, a 264-ha watershed located in the Upper Eau Galle River Basin, west-central Wisconsin. The quality of the GSSHA simulation results demonstrates that the model is capable of quantifying and predicting flow and the transport of sediment and nutrients, nitrogen and phosphorous, in the watershed.

Formation of stable radical anion is one of the most apparent event resulting from the interaction of a biomolecule with an electron. Although, the dipole-bound (DB) anions of nucleobases (NBs) prevail in the gas phase as indicated by negative ion photoelectron spectroscopy (PES), even relatively weak interactions such as those present in the uracil-water complexes are sufficient to render the valence bound (VB) anions adiabatically stable. Moreover, since the electron clouds of dipole bound anionic states are much more diffuse than those of valence bound anions, they are strongly destabilized with respect to the latter in condensed phase. This is why VB anions rather than DB anions of nucleobases are more relevant for biological systems, i.e., in particular for DNA. In this review article, we discuss molecular factors governing the stability of valence anions of nucleobases. On the basis of PES measurements and quantum chemical calculations, we demonstrate that tautomerisation leading to the very rare tautomers of NBs renders the valence anions of nucleobases adiabatically stable. Moreover, we present how the stability of VB anions increases on the transition from NBs to nucleotides. On the other hand, studying anionic complexes of nucleobases with inorganic and organic proton donors, other nucleobases and nucleosides, we emphasize the importance of interactions within double stranded DNA as well as with species present in the environment in which DNA is always immersed under biological conditions. We show that in the complexes of NBs with sufficiently acidic proton donors, electron attachment frequently induces barrier-free proton transfer (BFPT) leading to a significant stabilization of anionic states in nucleobases. Our discussion is closing with a summary, including open questions on the influence of interactions between DNA and proteins on the stability and fate of anionic species induced by electrons in DNA.

The chemical evolution of biomolecules such as nucleobases and their analogues from simple, one carbon containing molecules under abiotic conditions is a puzzle closely connected to the origin of life. Theoretical elucidation of the abiotic reaction routes leading from basic molecules cyanide acid (HCN) and formamide (H₂NCHO) to the formation of purine and adenine is reviewed here. The mechanism of three pathways: from formamide dimer via pyrimidine to purine, from AICN (4-aminoimidazole-5-carboxamidine) to adenine, and from formamide to purine and adenine, are discussed. Based on the comparison of step-by-step mechanism of the reaction pathways, in the addition reaction formamide is suggested to be more reactive than HCN. Beside its simplicity, the formamide self-catalyzed mechanism is energetically more viable than either water-catalyzed mechanism or non-catalyzed process. Moreover, this self-catalyzed mechanism is able to explain the ratio of purine to adenine observed in experiments. The formamide self-catalyzed mechanism for the route leading from formamide to purine and/or adenine is most likely for the formation of adenine (and purine) in the formamide solutions in the early stage of the earth.