Investigating routes toward atomic layer deposition of silicon carbide: Ab initio screening of potential silicon and carbon precursors

Silicon carbide (SiC) is a promising material for electronics due to its hardness, and ability to carry high currents and high operating temperature. SiC films are currently deposited using chemical vapor deposition (CVD) at high temperatures 1500–1600 °C. However, there is a need to deposit SiC-based films on the surface of high aspect ratio features at low temperatures. One of the most precise thin film deposition techniques on high-aspect-ratio surfaces that operates at low temperatures is atomic layer deposition (ALD). However, there are currently no known methods for ALD of SiC. Herein, the authors present a first-principles thermodynamic analysis so as to screen different precursor combinations for SiC thin films. The authors do this by calculating the Gibbs energy ΔGΔG of the reaction using density functional theory and including the effects of pressure and temperature. This theoretical model was validated for existing chemical reactions in CVD of SiC at 1000 °C. The precursors disilane (Si2H6), silane (SiH4), or monochlorosilane (SiH3Cl) with ethyne (C2H2), carbontetrachloride (CCl4), or trichloromethane (CHCl3) were predicted to be the most promising for ALD of SiC at 400 °C.

Theoretical models and ab initio calculations of phonons

Questa tesi intende approfondire da un punto di vista, sia teorico sia computazionale, le proprietà fondamentali dei fononi. A tal fine, sono presentati i modelli quantistici di Einstein e di Debye che permettono la derivazione analitica degli osservabili macroscopici principali di un solido, come l’energia media e la capacità termica. Ciò è possibile tramite una trattazione meccano-statistica basata sull’approssimazione armonica dei modi normali di vibrazione degli ioni reticolari. Quindi, all’inizio si mostrano brevemente i risultati principali riguardanti l’oscillatore armonico quantistico. Successivamente, si approfondiscono i temi della dispersione fononica e della densità degli stati vibrazionali per reticoli cristallini 1D e 3D. Si ottiene che la prima non può essere considerata lineare se non nel limite di alte lunghezze d’onda, e che la seconda può presentare punti di singolarità correlati alla forma della relazione di dispersione. Infine, sono state svolte alcune analisi computazionali ab initio relative alla dispersione fononica, la densità degli stati vibrazionali e la frequenza di Debye del Carbonio (diamante) tramite i programmi VASP e Phonopy, confrontando i risultati con dati sperimentali presenti in letteratura.

Delocalized water and fluoride contributions to Dyson orbitals for electron detachment from the hydrated fluoride anion

The experimental vertical electron detachment energy (VEDE) of aqueous fluoride, [F(-)(H(2)O)], is approximately 9.8 eV, but spectral assignment is complicated by interference between F(-) 2p and H(2)O 1b(1) orbitals. The electronic structure of [F(-)(H(2)O)] is analyzed with Monte Carlo and ab initio quantum-mechanical calculations. Electron-propagator calculations in the partial third-order approximation yield a VEDE of 9.4 eV. None of the Dyson orbitals corresponding to valence VEDEs consists primarily of F 2p functions. These results and ground-state atomic charges indicate that the final, neutral state is more appropriately described as [F(-)(H(2)O)(+)] than as [F(H(2)O)]. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3431081]

Edge effects in bilayer graphene nanoribbons: Ab initio total-energy density functional theory calculations

We show that the ground state of zigzag bilayer graphene nanoribbons is nonmagnetic. It also possesses a finite gap, which has a nonmonotonic dependence with the width as a consequence of the competition between bulk and strongly attractive edge interactions. All results were obtained using ab initio total-energy density functional theory calculations with the inclusion of parametrized van der Waals interactions.

Full-dimensional analytical ab initio potential energy surface of the ground state of HOI

Extensive ab initio calculations using a complete active space second-order perturbation theory wavefunction, including scalar and spin-orbit relativistic effects with a quadruple-zeta quality basis set were used to construct an analytical potential energy surface (PES) of the ground state of the [H, O, I] system. A total of 5344 points were fit to a three-dimensional function of the internuclear distances, with a global root-mean-square error of 1.26 kcal mol(-1). The resulting PES describes accurately the main features of this system: the HOI and HIO isomers, the transition state between them, and all dissociation asymptotes. After a small adjustment, using a scaling factor on the internal coordinates of HOI, the frequencies calculated in this work agree with the experimental data available within 10 cm(-1). (C) 2011 American Institute of Physics. [doi: 10.1063/1.3615545]

Opposite roles of O-2 in NO- and N2O-carbon reactions: An ab initio study

Previous experimental studies showed that the presence of O-2 greatly enhances NO-carbon reaction while it depresses N2O-carbon reaction on carbon surfaces. A popular explanation for the rate increase is that the addition of O-2 results in a large number of reactive carbon-oxygen complexes, and decomposition of these complexes produces many more active sites. The explanation for the latter is that excess O-2 simply blocks the active sites, thus reducing the rate of N2O-carbon reaction. The contradiction is that O-2 can also occupy active sites in NO-carbon reaction and produce active sites in N2O-carbon reduction. By using ab initio calculation, we find that the opposite roles of O-2 are caused by the different manners of N2O and NO adsorption on the carbon surface. In the presence of excess O-2, most Of the active sites are occupied by oxygen groups. In the competition for the remaining active sites, NO is more likely to chemisorb in the form of NO2 and NO chemisorption is mon thermodynamically favorable than O-2 chemisorption. By contrast, the presence of excess O-2 makes N2O chemisorption much less thermally stable either on the consecutive edge sites or edge sites isolated by semiquinone oxygen. A detailed analysis and discussion of the reaction mechanism of N-2 formation from NO- and N2O-carbon reaction in the presence of O-2 is presented in this paper.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Ab initio absorption spectrum of NiO combining molecular dynamics with the embedded cluster approach in a discrete reaction field

We developed a procedure that combines three complementary computational methodologies to improve the theoretical description of the electronic structure of nickel oxide. The starting point is a Car-Parrinello molecular dynamics simulation to incorporate vibrorotational degrees of freedom into the material model. By means ofcomplete active space self-consistent field second-order perturbation theory (CASPT2) calculations on embedded clusters extracted from the resulting trajectory, we describe localized spectroscopic phenomena on NiO with an efficient treatment of electron correlation. The inclusion of thermal motion into the theoretical description allowsus to study electronic transitions that, otherwise, would be dipole forbidden in the ideal structure and results in a natural reproduction of the band broadening. Moreover, we improved the embedded cluster model by incorporating self-consistently at the complete active space self-consistent field (CASSCF) level a discrete (or direct) reaction field (DRF) in the cluster surroundings. The DRF approach offers an efficient treatment ofelectric response effects of the crystalline embedding to the electronic transitions localized in the cluster. We offer accurate theoretical estimates of the absorption spectrum and the density of states around the Fermi level of NiO, and a comprehensive explanation of the source of the broadening and the relaxation of the charge transferstates due to the adaptation of the environment

Ab initio benchmark study for the oxidative addition of CH4 to Pd: importance of basis-set flexibility and polarization

To obtain a state-of-the-art benchmark potential energy surface (PES) for the archetypal oxidative addition of the methane C-H bond to the palladium atom, we have explored this PES using a hierarchical series of ab initio methods (Hartree-Fock, second-order Møller-Plesset perturbation theory, fourth-order Møller-Plesset perturbation theory with single, double and quadruple excitations, coupled cluster theory with single and double excitations (CCSD), and with triple excitations treated perturbatively [CCSD(T)]) and hybrid density functional theory using the B3LYP functional, in combination with a hierarchical series of ten Gaussian-type basis sets, up to g polarization. Relativistic effects are taken into account either through a relativistic effective core potential for palladium or through a full four-component all-electron approach. Counterpoise corrected relative energies of stationary points are converged to within 0.1-0.2 kcal/mol as a function of the basis-set size. Our best estimate of kinetic and thermodynamic parameters is -8.1 (-8.3) kcal/mol for the formation of the reactant complex, 5.8 (3.1) kcal/mol for the activation energy relative to the separate reactants, and 0.8 (-1.2) kcal/mol for the reaction energy (zero-point vibrational energy-corrected values in parentheses). This agrees well with available experimental data. Our work highlights the importance of sufficient higher angular momentum polarization functions, f and g, for correctly describing metal-d-electron correlation and, thus, for obtaining reliable relative energies. We show that standard basis sets, such as LANL2DZ+ 1f for palladium, are not sufficiently polarized for this purpose and lead to erroneous CCSD(T) results. B3LYP is associated with smaller basis set superposition errors and shows faster convergence with basis-set size but yields relative energies (in particular, a reaction barrier) that are ca. 3.5 kcal/mol higher than the corresponding CCSD(T) values

Towards and ab initio description of magnetism in ionic solids

The physical contributions to the KNiF3 magnetic exchange coupling integral have been obtained from specially designed ab initio cluster model calculations. Three important mechanisms have been identified. These are the delocalization of the magnetic orbitals into the anion p band, the variational contribution of the second-order interactions, and the many-body terms hidden in the two-body operator and the Heisenberg Hamiltonian.

Towards and ab initio description of magnetism in ionic solids

The physical contributions to the KNiF3 magnetic exchange coupling integral have been obtained from specially designed ab initio cluster model calculations. Three important mechanisms have been identified. These are the delocalization of the magnetic orbitals into the anion p band, the variational contribution of the second-order interactions, and the many-body terms hidden in the two-body operator and the Heisenberg Hamiltonian.

Chemisorption of atomic aluminum on Si(111): Evidence for an adsorbate-induced relaxation based on ab initio cluster-model calculations

Interaction models of atomic Al with Si4H9, Si4H7, and Si6H9 clusters have been studied to simulate Al chemisorption on the Si(111) surface in the atop, fourfold atop, and open sites. Calculations were carried out using nonempirical pseudopotentials in the framework of the ab initio Hartree-Fock procedure. Equilibrium bond distances, binding energies for adsorption, and vibrational frequencies of the adatoms are calculated. Several basis sets were used in order to show the importance of polarization effects, especially in the binding energies. Final results show the importance of considering adatom-induced relaxation effects to specify the order of energy stabilities for the three different sites, the fourfold atop site being the preferred one, in agreement with experimental findings.

Ab initio cluster-model study of the on-top chemisorption of F and Cl on Si(111) and Ge(111) surfaces

The interaction of atomic F and Cl with Si4H9 and Ge4H9 cluster models has been studied by using ab initio pseudopotentials and basis sets of increasing complexity. The results show that the effect of d orbitals is important in order to reproduce the experimental findings. However, the use of polarization functions in the atoms which are directly involved in the chemisorption bond leads to results which are very close to those obtained using extended basis sets. The local nature of the chemisorption bond is also interpreted by means of a Mulliken population analysis. For F-Si4H9 and Cl-Si4H9 the present results are in good agreement with previous ab initio all-electron calculations, and for the chemisorption of Cl on Si(111) and Ge(111) surfaces, good agreement is found with respect to the available experimental results as well as with previous slab calculations based on the local-density-functional formalism.

Performance of correlation functionals in ab initio chemisorption cluster-model calculations: Alkali metals on Si(111)

The performance of different correlation functionals has been tested for alkali metals, Li to Cs, interacting with cluster models simulating different active sites of the Si(111) surface. In all cases, the ab initio Hartree-Fock density has been obtained and used as a starting point. The electronic correlation energy is then introduced as an a posteriori correction to the Hartree-Fock energy using different correlation functionals. By making use of the ionic nature of the interaction and of different dissociation limits we have been able to prove that all functionals tested introduce the right correlation energy, although to a different extent. Hence, correlation functionals appear as an effective and easy way to introduce electronic correlation in the ab initio Hartree-Fock description of the chemisorption bond in complex systems where conventional configuration interaction techniques cannot be used. However, the calculated energies may differ by some tens of eV. Therefore, these methods can be employed to get a qualitative idea of how important correlation effects are, but they have some limitations if accurate binding energies are to be obtained.