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At least 73 records · Page 4

On the solution of integral equations with a generalized cauchy kernal

A certain class of singular integral equations that may arise from the mixed boundary value problems in nonhonogeneous materials is considered. The distinguishing feature of these equations is that in addition to the Cauchy singularity, the kernels contain terms that are singular only at the end points. In the form of the singular integral equations adopted, the density function is a potential or a displacement and consequently the kernal has strong singularities of the form (t-x)(-2), x(n-2) (t+x)(n), (n is = or 2, 0 x, t b). The complex function theory is used to determine the fundamental function of the problem for the general case and a simple numerical technique is described to solve the integral equation. Two examples from the theory of elasticity are then considered to show the application of the technique.

Kaya, A. C.↗

Quantum Chemistry Study of Cycloaddition Pathways for the Reaction of o-Benzyne with Fullerenes and Carbon Nanotubes

Functionalization of fullerenes via the [2+2] cycloaddition reaction with o-benzyne has been demonstrated in the laboratory. In contrast, [2+4) cycloaddition products are formed when benzyne reacts with planar polycyclic aromatic hydrocarbons. Using density functional theory (DFT) calculations with Becke's hybrid functional and small contracted gaussian basis sets, we are able to reproduce these product preferences. The objective of this work is to explore the functionalization of carbon nanotubes. We have studied o-benzyne cycloaddition products with a [14,0] single-walled nanotube. We find both the [2+2] and [2+4] adducts to be stable, with the latter product being somewhat favored.

Jaffe, Richard↗

Symmetry Breaking and the B3LYP Functional

The infrared spectra of six molecules, each of which contains a five-membered ring, and their cations are determined using density functional theory (DFT); both the B3LYP and BP86 functionals are used. The computed results are compared with the experimental spectra. For the neutral molecules, both methods are in good agreement with experiment. Even the Hartree-Fock (HF) approach is qualitatively correct for the neutrals. For the cations, the HF approach fails, as found for other organic ring systems. The B3LYP and BP86 approaches are in good mutual agreement for five of the six cation spectra, and in good agreement with experiment for four of the five cations where the experimental spectra are available. It is only for the fluoranthene cation, where the BP86 and B3LYP functionals yield different results; the BP86 yields the expected C2v symmetry, while the B3LYP approach breaks symmetry. The experimental spectra supports the BP86 spectra over the B3LYP, but the quality of the experimental spectra does not allow a critical evaluation of the accuracy of the BP86 approach for this difficult system.

Bauschlicher, Charles W., Jr.↗

Influence of Cation Species on Thermal Expansion of Y2Si2O7–Gd2Si2O7 Solid Solutions

Mixtures of Y 2 Si 2 O 7 and Gd 2 Si 2 O 7 were synthesized by solid-state reaction at 1600°C and characterized via in situ x-ray diffraction (XRD) to determine their coefficients of thermal expansion (CTE). All solid solutions within the system exhibited the orthorhombic δ-RE 2 Si 2 O 7 (Pna2 1 ) structure. Thermal expansion measurements of Y 2 Si 2 O 7 and Gd 2 Si 2 O 7 correlated well with reported values in literature, and all synthesized solid solutions exhibited CTEs between Y 2 Si 2 O 7 and Gd 2 Si 2 O 7 . Generally, there was a slight decrease in CTE exhibited by the materials with increasing Gd 2 Si 2 O 7 content, with Gd 2 Si 2 O 7 having the lowest CTEs and Y 2 Si 2 O 7 the highest CTEs. The decrease in CTE was attributed to stronger bonds of Gd-O over Y-O, as determined by calculated crystal orbital Hamilton populations using density functional theory. However, such differences were very small and crystal structure was the dominating factor in CTE trends.

rare earth silicates↗

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.↗

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↗

Ab initio Screening of Refractory Nitrides and Carbides for High Temperature Hydrogen Permeation Barriers

Density functional theory was used to screen eleven refractory materials – two pure metals, six nitrides, and three carbides–as high-temperature hydrogen permeation barriers to prevent hydrogen embrittlement. Activation energies were calculated for atomic hydrogen (H) diffusion into the first subsurface layer from the lowest energy surface of the high-temperature phase of each candidate material. The candidate barrier materials with the highest activation energies are h-BN, c-BN, HfN, and ZrN with predicted barriers of 3.25 eV, 3.23 eV, 3.14 eV, and 2.76 eV, respectively. Strain energies, Bader charges, and density of states were calculated for the diffusing H at the relaxed initial state and the transition state to provide insight into contributing factors to high energy barriers. The diffusing H atom in materials with the highest predicted barriers are protic. In addition, interstitial H atoms induce mid-gap states in the density of states of both BN polymorphs. The nitrogen retention of each nitride material at high temperatures was predicted using nitrogen vacancy formation energies with respect to gaseous nitrogen. Experimental evaluation of nitrogen retention in h-BN, ZrN, and TiN confirmed their resistance to nitrogen loss at 1773 K. However, of these nitrides, TiN is predicted to be the least stable. This work identifies multiple promising materials that are predicted to be effective hydrogen barriers at high temperatures and that are stable at temperatures above 2700 K, with BN predicted to perform best.

Density Functional Theory (DFT)↗

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↗

Effects of Structural Deformation and Tube Chirality on Electronic Conductance of Carbon Nanotubes

A combination of large scale classical force-field (UFF), density functional theory (DFT), and tight-binding Green's function transport calculations is used to study the electronic properties of carbon nanotubes under the twist, bending, and atomic force microscope (AFM)-tip deformation. We found that in agreement with experiment a significant change in electronic conductance can be induced by AFM-tip deformation of metallic zigzag tubes and by twist deformation of armchair tubes. The effect is explained in terms of bandstructure change under deformation.

Svizhenko, Alexei↗

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↗

The Use of Vegetation For Estimating Broken-Cloud Optical Properties From Surface Measurements

It is known that because of complex three-dimensional (3D) radiative effects of broken clouds, the retrieval of cloud optical properties from upward measurements based on a one-dimensional (1D) inversion technique almost surely fails. To remove radiative effects of 3D cloud structure, we have developed a new technique that retrieves cloud optical thickness for broken clouds above green vegetation from simultaneous surface measurements in the VIS and Near Infrared (NIR) spectral regions. The theoretical basis of the method is the very different spectral behavior of cloud liquid water drops and green vegetation. For example, cloud optical properties, and hence cloud reflectivities, change little between 650 and 860 nm, while the vegetated surface albedo changes from 0.05 to 0.5 between the same two wavelengths. This spectral contrast in surface albedo suggests using ground measurements at both wavelengths not independently, but as an algebraic combination (a spectral index). For a spectral band in the NIR region, the green vegetation acts as a powerful reflector that "illuminates" horizontally inhomogeneous clouds from below. This provides the extra information needed to largely remove the 3D radiative effects, especially in the case of broken clouds; this in turn allows the retrieval of cloud optical depth using traditional 1D radiative transfer theory. This approach is similar to the so-called Green's function problem for radiative transfer where a laser beam illuminates clouds and the resulting "spot-size" of the reflected light around the beam characterizes cloud properties. We generalize Green's function theory to surf ace-cloud interaction and develop new spectral indices from which broken-cloud optical depth can be retrieved.

Marshak, A.↗

Multiscale Modeling of Grain Boundaries in ZrB2: Structure, Energetics, and Thermal Resistance

A combination of ab initio, atomistic and finite element methods (FEM) were used to investigate the structures, energetics and lattice thermal conductance of grain boundaries for the ultra high temperature ceramic ZrB2. Atomic models of idealized boundaries were relaxed using density functional theory. Information about bonding across the interfaces was determined from the electron localization function. The Kapitza conductance of larger scale versions of the boundary models were computed using non-equilibrium molecular dynamics. The interfacial thermal parameters together with single crystal thermal conductivities were used as parameters in microstructural computations. FEM meshes were constructed on top of microstructural images. From these computations, the effective thermal conductivity of the polycrystalline structure was determined.

Lawson, John W.↗

Initiating Molecular Growth in the Interstellar Medium via Dimeric Complexes of Observed Ions and Molecules

A feasible initiation step for particle growth in the interstellar medium (ISM) is simulated by means of ab quantum chemistry methods. The systems studied are dimer ions formed by pairing nitrogen containing small molecules known to exist in the ISM with ions of unsaturated hydrocarbons or vice versa. Complexation energies, structures of ensuing complexes and electronic excitation spectra of the encounter complexes are estimated using various quantum chemistry methods. Moller-Plesset perturbation theory (MP2, Z-averaged perturbation theory (ZAP2), coupled cluster singles and doubles with perturbative triples corrections (CCSD(T)), and density functional theory (DFT) methods (B3LYP) were employed along with the correlation consistent cc-pVTZ and aug-cc-pVTZ basis sets. Two types of complexes are predicted. One type of complex has electrostatic binding with moderate (7-20 kcal per mol) binding energies, that are nonetheless significantly stronger than typical van der Waals interactions between molecules of this size. The other type of complex develops strong covalent bonds between the fragments. Cyclic isomers of the nitrogen containing complexes are produced very easily by ion-molecule reactions. Some of these complexes show intense ultraviolet visible spectra for electronic transitions with large oscillator strengths at the B3LYP, omegaB97, and equations of motion coupled cluster (EOM-CCSD) levels. The open shell nitrogen containing carbonaceous complexes especially exhibit a large oscillator strength electronic transition in the visible region of the electromagnetic spectrum.

Bera, Partha P.↗

Cr2 Revisited

Abstract Cr2 is studied at the coupled cluster singles and doubles level of theory, including a perturbational estimate of the connected triples [CCSD(T)]. Both spin restricted, RCCSD(T), and spin unrestricted, UCCSD(T), approaches are used. The UCCSD(T) bond length is much longer than the experimental value, while the RCCSD(T) bond length is shorter. This difference is due to the inability of the spin restricted Hartree-Fock reference to describe the antiferromagnetic coupling at larger r values. In contrast with the results obtained using density functional theory in conjunction with older functionals, the results obtained with recently developed functionals are in agreement with the UCCSD(T) results.

Bauschlicher, Charles W., Jr.↗

Energetics and Dynamics of GaAs Epitaxial Growth via Quantum Wave Packet Studies

The dynamics of As(sub 2) molecule incorporation into the flat Ga-terminated GaAs(100) surface is studied computationally. The time-dependent Schrodinger equation is solved on a two-dimensional potential energy surface obtained using density functional theory calculations. The probabilities of trapping and subsequent dissociation of the molecular As(sub 2) bond are calculated as a function of beam translational energy and vibrational quantum number of As(sub 2).

Dzegilenko, Fedor N.↗

Diffusion Quantum Monte Carlo Calculation of the Austenite and Martensite Phases of NiTi

NiTi is a promising material for smart and active technologies due to its exhibition of the shape memory effect, superelasticity, and biocompatibility. The shape memory effect is tied to the reversible transition between the austenite and martensite phases. A major research direction is to alloy NiTi with Zr, Hf, Pd, Pt, etc., in order to tune the martensitic transition temperature (MTT). Modeling the MTT from first principles is challenging because the lattice dynamics is complicated by anharmonicity and various low-energy structures. Using density functional theory, the energy difference between the austenite and martensite phases of NiTi varies by up to 100 meV/atom depending on the choice of density functional, which is of the same order of the energy difference itself. Consequently, free energy calculations with different functionals can result in estimates of the MTT that vary by several hundred K. Using diffusion quantum Monte Carlo, we calculated the energy difference between the B2 and B19' structures of NiTi to be 70.9 +- 2.5 meV/atom.

Kevin K Ly↗