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At least 19 records

Using Density Functional Theory (DFT) for the Calculation of Atomization Energies

The calculation of atomization energies using density functional theory (DFT), using the B3LYP hybrid functional, is reported. The sensitivity of the atomization energy to basis set is studied and compared with the coupled cluster singles and doubles approach with a perturbational estimate of the triples (CCSD(T)). Merging the B3LYP results with the G2(MP2) approach is also considered. It is found that replacing the geometry optimization and calculation of the zero-point energy by the analogous quantities computed using the B3LYP approach reduces the maximum error in the G2(MP2) approach. In addition to the 55 G2 atomization energies, some results for transition metal containing systems will also be presented.

Bauschlicher, Charles W., Jr.

An Ongoing Quantum Chemistry Study of Molecules with Potential for Molecular Quantum Communications Using Density Functional Theory (DFT) and Other Techniques

Molecular quantum communications (the term here being used to define the transfer of information using the movement of quantum states between molecules or between molecules and a sensing environment that can be queried) can be achieved with a wide range of phenomena. Although there are excellent materials databases such as the Open Quantum Materials Database (http://oqmd.org/analysis/gclp/) and the Materials Project (https://materialsproject.org/), there is no centralized database of materials correlated to their quantum communications possibilities.

Harry Shaw

IR Spectra and Bond Energies Computed Using DFT

The combination of density functional theory (DFT) frequencies and infrared (IR) intensities and experimental spectra is a very powerful tool in the identification of molecules and ions. The computed and measured isotopic ratios make the identification much more secure than frequencies and intensities alone. This will be illustrated using several examples, such as Mn(CO)n and Mn(CO)n-. The accuracy of DFT metal-ligand bond energies will also be discussed.

Bauschlicher, Charles

The Application of DFT to Systems Containing Metal Atoms

The application of density functional theory (DFT) to a series of metal containing systems will be described. The focus will be on the calculation of accurate bond energies, especially metal-ligand successive bond energies. The DFT results will be compared with experiment and other levels of theory. If time permits, metal clusters will also be discussed.

Ricca, Alessandra

High-precision predictions of properties of chemically disordered crystals

Multiple scattering theory (MST) combined with density functional theory (DFT) allows to predict properties of chemically disordered materials from the first principles. However, such predictions often suffer from the systematic errors, which depend on crystal geometry. Each computed property of a particular crystal structure typically has a relatively small random error and a larger systematic error. Cancellation of systematic errors allows more accurate predictions. We propose a computational methodology based on the subtraction of the systematic errors in MST. To exemplify it, we apply it to the precipitated alloys. Considering precipitation strengthening in Ni superalloys, we compute the relative enthalpies of the competing Ni_3(Al_{1-x}Ti_x)_1 crystal structures with a chemical disorder on the Al+Ti sublattice. Such predicted composition-structure-property dependencies are useful for the guided design of the next-generation alloys with improved strength. Our predictions are validated by comparison with the results of other DFT methods (having a higher computational cost) and with experiment.

density functional theory

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, development of new coating systems is hindered by the large design space and difficulty in predicting properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate accurate prediction of the anisotropy of the CTE in good agreement with diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

rare earth silicates

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning

Does Chirality Influence the Stability of Amino Acid –Cu Complexes in the Salt-Induced Peptide Formation Reaction? Insights from Density Functional Theory Calculations

The polymerization of amino acids into peptides and ultimately proteins is critical to evolution of life. Ribosomally-synthesized proteins are homochiral, composed entirely of L-amino acids. Abiotic syntheses of amino acids, however, produce racemic mixtures(equal amounts of L and D enantiomers), meaning that the pool of monomers available for abiotic protein synthesis would be racemic or nearly so. There are no prebiotically plausible mechanisms known to yield homochiral peptides from racemic pools of amino acids. While some mechanisms capable of producing or amplifying enantiomeric excesses have been observed, these excesses are small or not applicable to all biologically relevant amino acids. As a result, a prebiotically-feasible mechanism to create enantiopure pools of amino acids has not been identified. However, it is not clear that these enantio-enriched or enantiopure pools are necessary to produce homochiral peptides. Steric and electronic effects, or a combination of both, may influence how different enantiomers interact with each other, potentially leading to homochiral peptides from racemic mixtures. Here, we use density functional theory (DFT) calculations to assess the stability of homochiral and heterochiral reactive complexes produced during polymerization via the salt-induced peptide formation (SIPF) reaction. Experimental studies of the SIPF reaction have shown that it enables the formation of peptides under diverse environmental conditions, making it a plausible pathway to peptide formation on early Earth. In the SIPF reaction, NaCl acts as a condensation reagent while a divalent metal cation, primarily Cu2+, facilitates polymerization by complexing and activating amino acids forming a monochlorocuprate complex. To assess if hetero-or homochiral monochlorocuprate complexes were energetically favored, we compared the stability of LL, DD, and LD enantiomers of Cu2+–(alanine)2and Cu2+–(valine) 2 complexes. Gaussian 09 density DFT energy-minimization calculations were made for each Cu –amino acid complex in the cis and trans configuration. Models were energy minimized using the BH and HLYP/6-31++G(d,p) level of theory and free energies were compared to determine the most stable configuration.

A C Fox

Theoretical Study of Fe(CO)n-

The structures and CO binding energies are computed for Fe(CO)n- using a hybrid density functional theory (DFT) approach. The structures and ground states can be explained in terms of maximizing the Fe to CO 2pi* donation and minimizing Fe-CO 5 sigma repulsion. The trends in the CO binding energies for Fe(CO)n- and the differences between the trends for Fe(CO)n- and Fe(CO)n are also explained. For Fe(CO)n-, the second, third, and fourth CO bonding energies are in good agreement with experiment, while the first is too small. The first CO binding is also too small using the coupled cluster singles and doubles approach including a perturbation estimate of the connected triple excitations.

Ricca, Alessandra

Computational Study of Field Initiated Surface Reactions for Synthesis of Diamond and Silicon

This project involves using quantum chemistry to simulate surface chemical reactions in the presence of an electric field for nanofabrication of diamond and silicon. A field delivered by a scanning tunneling microscope (STM) to a nanometer scale region of a surface affects chemical reaction potential energy surfaces (PES) to direct atomic scale surface modification to fabricate sub-nanometer structures. Our original hypothesis is that the applied voltage polarizes the charge distribution of the valence electrons and that these distorted molecular orbitals can be manipulated with the STM so as to change the relative stabilities of the electronic configurations over the reaction coordinates and thus the topology of the PES and reaction kinetics. Our objective is to investigate the effect of applied bias on surface reactions and the extent to which STM delivered fields can be used to direct surface chemical reactions on an atomic scale on diamond and silicon. To analyze the fundamentals of field induced chemistry and to investigate the application of this technique for the fabrication of nanostructures, we have employed methods capable of accurately describing molecular electronic structure. The methods we employ are density functional theory (DFT) quantum chemical (QC) methods. To determine the effect of applied bias on surface reactions we have calculated the QC PESs in various applied external fields for various reaction steps for depositing or etching diamond and silicon. We have chosen reactions which are thought to play a role in etching and the chemical vapor deposition growth of Si and diamond. The PESs of the elementary reaction steps involved are then calculated under the applied fields, which we vary in magnitude and configuration. We pay special attention to the change in the reaction barriers, and transition state locations, and search for low energy reaction channels which were inaccessible without the applied bias.

Musgrave, Charles Bruce

C2 Fragmentation Energy of C60 Revisited: Theory Disagrees with Most Experiments

Following our earlier work on the subject, we have carried out density functional theory (DFT) and second-order Moller-Plesset perturbation theory (MP2) calculations of the dissociation energy of the reaction C60 yields C58 + C2 using polarized basis sets and geometries optimized with DFT methods. The present theoretical results support an electronic fragmentation energy D(sub e) around 10-11 eV in disagreement with most experimental results that place the dissociation energy D(sub o) (including zero point energy) around 7-8 eV. The plausible errors remaining in the theoretical calculations are unlikely to account for this big difference (2-4 eV).

Boese, A. Daniel

A Comparison of Density Functional Theory with Ab initio Approaches for Systems Involving First Transition Row Metals

Density functional theory (DFT) is found to give a better description of the geometries and vibrational frequencies of FeL and FeL(sup +) systems than second order Moller Plesset perturbation theory (MP2). Namely, the DFT correctly predicts the shift in the CO vibrational frequency between free CO and the Sigma(sup -) state of FeCO and yields a good result for the Fe-C distance in the quartet states of FeCH4(+) 4 These are properties where the MP2 results are unsatisfactory. Thus DFT appears to be an excellent approach for optimizing the geometries and computing the zero-point energies of systems containing first transition row atoms. Because the DFT approach is biased in favor of the 3d(exp 7) occupation, whereas the more traditional approaches are biased in favor of the 3d(exp 6) occupation, differences are found in the relative ordering of states. It is shown that if the dissociation is computed to the most appropriate atomic asymptote and corrected to the ground state asymptote using the experimental separations, the DFT results are in good agreement with high levels of theory. The energetics at the DFT level are much superior to the MP2 and in most cases in good agreement with high levels of theory.

Ricca, Alessandra

On the Interaction of CO and NH3 with BH3 and BF3

BH3CO, BF3CO, BH3NH3, and BF3NH3 have been studied using density functional theory (DFT). The computed geometries are in reasonable agreement with experiment. BF3CO is found to be weakly bound. The binding energies of BH3CO, BH3NH3 , and BF3NH3 have also been computed using the coupled cluster singles and doubles level of theory, including a perturbational estimate of the connected triples [CCSD(T)]. These CCSD(T) calculations are performed using correlation consistent polarized-valence triple-zeta basis sets. These are expected to be the most accurate binding energies to date. The DFT binding energies are in good agreement with those obtained at the CCSD(T) level. The bonding is analyzed using the constrained space orbital variation (CSOV) technique. In addition to analyzing the bonding in BH3CO, BH3NH3, and BF3NH3, the CSOV approach is used to study why the bonding in BF3CO is so weak.

Bauschlicher, Charles W., Jr.

What is the Structure of FeC5H6(+)?

Calculations performed using both density functional theory (DFT) and the modified coupled-pair functional (MCPF) approach show that FeC5H6(+) is more stable than HFeC5H5(+) by about 10 kcal/mol. The ground state of FeC5H6(+) is a quartet state derived from the 3d(sup 7) occupation of Fe+. For HFeC5H6(+), the MCPF 5 approach yields a sextet ground state while DFT yields a quartet; however, these two states are close in energy at both levels of theory.

Bauschlicher, Charles W., Jr.

The Successive H2O Binding Energies for Fe(H2O)n(+)

The binding energy, computed using density functional theory (DFT), are in good agreement with experiment. The bonding is electrostatic (charge-dipole) in origin for all systems. The structures are therefore determined mostly by metal-ligand and ligand-ligand repulsion. The computed structure for FeH2O(+) is C(2v) where sp hybridization is important in reducing the Fe-H2O repulsion. Fe(H2O)2(+) has D2d symmetry where sdo hybridization is the primary factor leading to the linear O-Fe-O geometry. The bonding in Fe(H2O)3(+) and Fe(H2O)4(+) are very complex because ligand-ligand and metal-ligand repulsion, both for the in-plane and out-of-plane water lone-pair orbitals, are important.

Ricca, Alessandra

Theoretical Infrared Spectra for Polycyclic Aromatic Hydrocarbon Neutrals, Cations and Anions

Calculations are carried out using density functional theory (DFT) to determine the harmonic frequencies and intensities of the neutrals and cations of thirteen polycyclic aromatic hydrocarbons (PAHs) up to the size of ovalene. Calculations are also carried out for a few PAH anions. The DFT harmonic frequencies, when uniformly scaled by the factor of 0.958 to account primarily for anharmonicity, agree with the matrix isolation fundamentals to within an average error of about 10 per centimeter. Electron correlation is found to significantly reduce the intensities of many of the cation harmonics, bringing them into much better agreement with the available experimental data. While the theoretical infrared spectra agree well with the experimental data for the neutral systems and for many of the cations, there are notable discrepancies with the experimental matrix isolation data for some PAH cations that are difficult to explain in terms of limitations in the calculations. In agreement with previous theoretical work, the present calculations show that the relative intensities for the astronomical unidentified infrared (UIR) bands agree reasonably well with those for a distribution of polycyclic aromatic hydrocarbon (PAH) cations, but not with a distribution of PAH neutrals. We also observe that the infrared spectra of highly symmetrical cations such as coronene agree much better with astronomical observations than do those of, for example, the polyacenes such as tetracene and pentacene. The total integrated intensities for the neutral species are found to increase linearly with size, while the total integrated intensities are much larger for the cations and scale more nearly quadratically with size. We conclude that emission from moderate-sized highly symmetric PAH cations such as coronene and larger could account for the UIR bands.

Langhoff, Stephen R.

On the Reaction of FNO2 with CH3, t-butyl, and C13H21

Theoretical studies are reported for the reaction of FN02 with the radicals CH3, t-butyl, and C13H21, which are templates for the radical site of a hydrogenated diamond surface. All structures axe fully optimized using density functional theory (DFT) based on the B3LYP functional. Calibration calculations axe performed for CH3 + FNO2 using the coupled cluster approach, the the internally contracted multireference configuration. interaction method, and second order perturbation theory based upon complete active space SCF (CASSCF) reference wave function. These calibration calculations support the B3LYP approach for the calculation of bond energies, but show the B3LYP barrier is too low. Combining the calibration calculations with the larger clusters yields our best estimate of a barrier of about 10 kcal/mol. for the reaction of FNO2 with a radical site on hydrogenated diamond.

Thuemmel, H. T.

Chemistry by Way of Density Functional Theory

In this work we demonstrate that density functional theory (DFT) methods make an important contribution to understanding chemical systems and are an important additional method for the computational chemist. We report calibration calculations obtained with different functionals for the 55 G2 molecules to justify our selection of the B3LYP functional. We show that accurate geometries and vibrational frequencies obtained at the B3LYP level can be combined with traditional methods to simplify the calculation of accurate heats of formation. We illustrate the application of the B3LYP approach to a variety of chemical problems from the vibrational frequencies of polycyclic aromatic hydrocarbons to transition metal systems. We show that the B3LYP method typically performs better than the MP2 method at a significantly lower computational cost. Thus the B3LYP method allows us to extend our studies to much larger systems while maintaining a high degree of accuracy. We show that for transition metal systems, the B3LYP bond energies are typically of sufficient accuracy that they can be used to explain experimental trends and even differentiate between different experimental values. We show that for boron clusters the B3LYP energetics are not as good as for many of the other systems presented, but even in this case the B3LYP approach is able to help understand the experimental trends.

Bauschlicher, Charles W., Jr.