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Solvent-Induced Frequency Shifts of 5-Hydroxymethylfurfural Deduced via Infrared Spectroscopy and ab Initio Calculations
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Many-body ab initio diffusion quantum Monte Carlo applied to the strongly correlated oxide NiO
We present a many-body diffusion quantum Monte Carlo (DMC) study of the bulk and defect properties of NiO. We find excellent agreement with experimental values, within 0.3%, 0.6%, and 3.5% for the lattice constant, cohesive energy, and bulk modulus, respectively. The quasiparticle bandgap was also computed, and the DMC result of 4.72 (0.17) eV compares well with the experimental value of 4.3 eV. Furthermore, DMC calculations of excited states at the L, Z, and the gamma point of the Brillouin zone reveal a flat upper valence band for NiO, in good agreement with Angle Resolved Photoemission Spectroscopy results. To study defect properties, we evaluated the formation energies of the neutral and charged vacancies of oxygen and nickel in NiO. A formation energy of 7.2 (0.15) eV was found for the oxygen vacancy under oxygen rich conditions. For the Ni vacancy, we obtained a formation energy of 3.2 (0.15) eV under Ni rich conditions. These results confirm that NiO occurs as a p-type material with the dominant intrinsic vacancy defect being Ni vacancy.
Using Machine Learning to Greatly Accelerate Path Integral Ab Initio Molecular Dynamics
Ab initio molecular dynamics (AIMD) has become one of the most popular and robust approaches for modeling complicated chemical, liquid, and material systems. However, the formidable computational cost often limits its widespread application in simulations of the largest-scale systems. Furthermore, the situation becomes even more severe in cases where the hydrogen nuclei may be better described as quantized particles using a path integral representation. Here, we present a computational approach that combines machine learning with recent advances in path integral contraction schemes, and we achieve a 2 orders of magnitude acceleration over direct path integral AIMD simulation while at the same time maintaining its accuracy.
Multireference Ab Initio Study of Ligand Field d–d Transitions in Octahedral Transition-Metal Oxide Clusters
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Ab initio translationally invariant nonlocal one-body densities from no-core shell-model theory
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Ab-Initio Investigation of Finite Size Effects in Rutile Titania Nanoparticles with Semilocal and Nonlocal Density Functionals
In this work, we employ hybrid and generalized gradient approximation (GGA) level density functional theory (DFT) calculations to investigate the convergence of surface properties and electronic gap of rutile titania nanoparticles with particle size. The surface energies and electronic gaps are calculated for cuboidal particles with minimum dimension ranging from 3.7 Angstrom (24 atoms) to 10.3 Angstrom (384 atoms) using a highly-parallel real-space DFT code to enable hybrid level DFT calculations of larger nanoparticles than are typically practical. We deconvolute the geometric and electronic finite size effects in surface energy, and evaluate the influence of defects on electronic gap and density of states (DOS). The electronic finite size effects in surface energy vanish when the minimum length scale of the nanoparticles becomes greater than 10 Angstrom. We show that this length scale is consistent with a computationally efficient numerical analysis of the characteristic length scale of electronic interactions. The surface energy of nanoparticles having minimum dimension beyond this characteristic length can be approximated using slab calculations that account for the geometric defects. In contrast, the finite size effects on the electronic gap and DOS is highly dependent on the shape and size of these particles. Furthermore, the DOS for cuboidal particles and more realistic particles constructed using the Wulff algorithm reveal that defect states within the electronic gap play a key role in determining the eigen value distribution of nanoparticles and the electronic gap does not converge to the bulk limit for the particle sizes investigated.
Iron Dissolution from Goethite (alpha-FeOOH) Surfaces in Water by Ab Initio Enhanced Free-Energy Simulations
Dissolution of redox-active metal oxides plays a key role in a variety of phenomena, including (photo)electrocatalysis, degradation of battery materials, corrosion of metal oxides, and biogeochemical cycling of metals in natural environments. Despite its widespread significance, mechanisms of metal-oxide dissolution remain poorly understood on the atomistic level. This study is aimed at elucidating the long-standing problem of iron dissolution from Fe(III)-oxide, a complex process involving coupled hydrolysis, surface protonation, electron transfer, and metal oxygen bond cleavage. We examine the case of goethite (alpha-FeOOH), a representative phase, bearing structural similarities with many other metal (hydr)oxides. By employing quantum molecular dynamics simulations (metadynamics combined with the Blue Moon ensemble approach), we unveil the mechanistic pathways and rates of both nonreductive and reductive dissolution of iron from the (110) and (021) goethite facets in aqueous solutions at room temperature. Our simulations reveal the interplay between concerted internal (structural) and external (from solution) protonations as essential for breaking Fe-O bonds as well as for stabilizing intermediate configurations of dissolving Fe. We demonstrate specifically how Fe(III) reduction to Fe(II) yields higher dissolution rates than the proton-mediated pathway, whereas the most rapid dissolution is expected for these two processes combined, in agreement with experiments.
Ab initio rotation in 10 Be
Ab initio theory describes nuclei from a fully microscopic formulation, with no presupposition of collective degrees of freedom, yet signatures of clustering and rotation nonetheless arise. We can therefore look to ab initio theory for an understanding of the nature of these emergent phenomena. To probe the nature of rotation in 10 Be, here we observe the predicted rotational spectroscopy from no-core configuration interaction (NCCI) calculations with the Daejeon16 internucleon interaction, and further find spectra suggestive of coexisting rotational structures having qualitatively different intrinsic deformations: one triaxial and the other with large axial deformation arising primarily from the neutrons.
Rb + Adsorption at the Quartz(101)–Aqueous Interface: Comparison of Resonant Anomalous X-ray Reflectivity with ab Initio Calculations
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Ab initio GGA+U investigations of the structural, electronic, and magnetic properties of Cd 1-x Mn x Te alloy
The structural, electronic and magnetic properties of Cd 1-x Mn x Te alloy in the zinc-blende (ZB) phase within the framework of spin-polarized density functional theory using the generalized gradient approximation (GGA) are studied. In particular, we employ GGA+U SIC method that gives a better description of systems with strong Coulomb correlations of the d-electrons. First, we discuss implementation of GGA+U method to the ground state calculations of pure CdTe and ferromagnetic MnTe. The alloy is modelled at some selected compositions by ordered structures described in terms of periodically repeated supercells for the compositions x = 0.25, 0.5, and 0.75. The compositional dependence of the lattice constant, electronic band structure and partial densities of states of ferromagnetic Cd 1-x Mn x Te alloy are studied. We estimate the spin-exchange splitting energies produced by the Mn 3d-states and determine the exchange constants for the conduction and valence bands of the alloy. The energy positions of the occupied and unoccupied Mn 3d-bands in the electronic structure of ferromagnetic Cd 1-x Mn x Te alloy are also presented. Our calculations using GGA+U SIC approach agree well with the available experimental data and other calculations.
SQMBox: Interfacing a semiempirical integral library to modular ab initio electronic structure enables new semiempirical methods
Ab initio and semiempirical electronic structure methods are usually implemented in separate software packages or use entirely different code paths. As a result, it can be time-consuming to transfer an established ab initio electronic structure scheme to a semiempirical Hamiltonian. Here we present an approach to unify ab initio and semiempirical electronic structure code paths based on a separation of the wavefunction ansatz and the needed matrix representations of operators. With this separation, the Hamiltonian can refer to either an ab initio or semiempirical treatment of the resulting integrals. We built a semiempirical integral library and interfaced it to the GPU-accelerated electronic structure code TeraChem. Equivalency between ab initio and semiempirical tight-binding Hamiltonian terms is assigned according to their dependence on the one-electron density matrix. The new library provides semiempirical equivalents of the Hamiltonian matrix and gradient intermediates, corresponding to those provided by the ab initio integral library. This enables the straightforward combination of semiempirical Hamiltonians with the full pre-existing ground and excited state functionality of the ab initio electronic structure code. We demonstrate the capability of this approach by combining the extended tight-binding method GFN1-xTB with both spin-restricted ensemble-referenced Kohn–Sham and complete active space methods. We also present a highly efficient GPU implementation of the semiempirical Mulliken-approximated Fock exchange. The additional computational cost for this term becomes negligible even on consumer-grade GPUs, enabling Mulliken-approximated exchange in tight-binding methods for essentially no additional cost.
Composition dependent order-disorder transition in Nd Zr1−O2−0.5 pyrochlores: A combined structural, calorimetric and ab initio modeling study
Not Available
Migration of Single Iridium Atoms and Tri-iridium Clusters on MgO Surfaces: Aberration-Corrected STEM Imaging and Ab Initio Calculations
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A finite difference Davidson procedure to sidestep full ab initio hessian calculation: Application to characterization of stationary points and transition state searches
The cost of calculating nuclear hessians, either analytically or by finite difference methods, during the course of quantum chemical analyses can be prohibitive for systems containing hundreds of atoms. In many applications, though, only a few eigenvalues and eigenvectors, and not the full hessian, are required. For instance, the lowest one or two eigenvalues of the full hessian are sufficient to characterize a stationary point as a minimum or a transition state (TS), respectively. We describe here a method that can eliminate the need for hessian calculations for both the characterization of stationary points as well as searches for saddle points. A finite differences implementation of the Davidson method that uses only first derivatives of the energy to calculate the lowest eigenvalues and eigenvectors of the hessian is discussed. This method can be implemented in conjunction with geometry optimization methods such as partitioned-rational function optimization (P-RFO) to characterize stationary points on the potential energy surface. With equal ease, it can be combined with interpolation methods that determine TS guess structures, such as the freezing string method, to generate approximate hessian matrices in lieu of full hessians as input to P-RFO for TS optimization. This approach is shown to achieve significant cost savings relative to exact hessian calculation when applied to both stationary point characterization as well as TS optimization. The basic reason is that the present approach scales one power of system size lower since the rate of convergence is approximately independent of the size of the system. Therefore, the finite-difference Davidson method is a viable alternative to full hessian calculation for stationary point characterization and TS search particularly when analytical hessians are not available or require substantial computational effort.