Conventional Ab Initio Research Articles

Local structure, thermodynamics, and melting of boron phosphide at high pressures by deep learning-driven abinitio simulations.

Boron phosphide (BP) is a (super)hard semiconductor constituted of light elements, which is promising for high demand applications at extreme conditions. The behavior of BP at high temperatures and pressures is of special interest but is also poorly understood because both experimental and conventional abinitio methods are restricted to studying refractory covalent materials. The use of machine learning interatomic potentials is a revolutionary trend that gives a unique opportunity for high-temperature study of materials with abinitio accuracy. We develop a deep machine learning potential (DP) for accurate atomistic simulations of the solid and liquid phases of BP as well as their transformations near the melting line. Our DP provides quantitative agreement with experimental and abinitio molecular dynamics data for structural and dynamic properties. DP-based simulations reveal that at ambient pressure, a tetrahedrally bonded cubic BP crystal melts into an open structure consisting of two interpenetrating sub-networks of boron and phosphorous with different structures. Structure transformations of BP melt under compressing are reflected by the evolution of low-pressure tetrahedral coordination to high-pressure octahedral coordination. The main contributions to structural changes at low pressures are made by the evolution of medium-range order in the B-subnetwork and, at high pressures, by the change of short-range order in the P-subnetwork. Such transformations exhibit an anomalous behavior of structural characteristics in the range of 12-15GPa. DP-based simulations reveal that the Tm(P) curve develops a maximum at P ≈ 13 GPa, whereas experimental studies provide two separate branches of the melting curve, which demonstrate the opposite behavior. Analysis of the results obtained raises open issues in developing machine learning potentials for covalent materials and stimulates further experimental and theoretical studies of melting behavior in BP.

Temperature‐Dependent Anharmonic Phonons in Quantum Paraelectric KTaO3 by First Principles and Machine‐Learned Force Fields

AbstractUnderstanding collective phenomena in quantum materials from first principles is a promising route toward engineering materials properties and designing new functionalities. This work examines the quantum paraelectric state, an elusive state of matter characterized by the smooth saturation of the ferroelectric instability at low temperature due to quantum fluctuations associated with anharmonic phonon effects. The temperature‐dependent evolution of the soft ferroelectric phonon mode in the quantum paraelectric KTaO3 in the range 0–300 K is modeled by combining density functional theory (DFT) calculations with the stochastic self‐consistent harmonic approximation assisted by an on‐the‐fly machine‐learned force field. The calculated data show that including anharmonic terms is essential to stabilize the spurious imaginary ferroelectric phonon predicted by DFT in the harmonic approximation, in agreement with experiments. Augmenting the DFT workflow with machine‐learned force fields allows for efficient stochastic sampling of the configuration space using large supercells in a wide temperature range, inaccessible to conventional ab initio protocols. This work proposes a robust computational workflow capable of accounting for collective behaviors involving different degrees of freedom and occurring at large time/length scales, paving the way for precise modeling and control of quantum effects in materials.

Machine learning based energy-free structure predictions of molecules, transition states, and solids

The computational prediction of atomistic structure is a long-standing problem in physics, chemistry, materials, and biology. Conventionally, force-fields or ab initio methods determine structure through energy minimization, which is either approximate or computationally demanding. This accuracy/cost trade-off prohibits the generation of synthetic big data sets accounting for chemical space with atomistic detail. Exploiting implicit correlations among relaxed structures in training data sets, our machine learning model Graph-To-Structure (G2S) generalizes across compound space in order to infer interatomic distances for out-of-sample compounds, effectively enabling the direct reconstruction of coordinates, and thereby bypassing the conventional energy optimization task. The numerical evidence collected includes 3D coordinate predictions for organic molecules, transition states, and crystalline solids. G2S improves systematically with training set size, reaching mean absolute interatomic distance prediction errors of less than 0.2 Å for less than eight thousand training structures — on par or better than conventional structure generators. Applicability tests of G2S include successful predictions for systems which typically require manual intervention, improved initial guesses for subsequent conventional ab initio based relaxation, and input generation for subsequent use of structure based quantum machine learning models.

Exciton behavior under the influence of metal nanoparticle near fields: Significance of nonlocal effects

We analytically characterize the influence of a neighboring metal nanoparticle (MNP) on the behavioral trends of a quantum dot (QD) using a generalized nonlocal optical response (GNOR) method based approach, taking the MNP distance dependent modifications to the QD population relaxation and dephasing rates into account. The GNOR model is a recent generalization and an extension of the hydrodynamic Drude model (HDM), which goes beyond HDM by taking into account both the convection current and electron diffusion in the MNPs. It allows unified theoretical explanation of some experimentally observed plasmonic phenomena which otherwise would require ab initio analysis as the conventional local response approximation (LRA) fails to account for them. For example, it has been demonstrated in literature that the GNOR model captures size dependent resonance shifts of small MNPs which are unrevealed by the conventional LRA based methods, and it has proven to yield results displaying better agreement with the experimental observations for plasmonic experiments. Attempts to incorporate MNP nonlocal effects in the analytical characterization of vicinal excitons found in literature utilize the phenomenological hydrodynamic model and assume the absence of MNP interband effects. Moreover, they are only applicable to narrow parameter regions. In this paper we present a complete analytical characterization which overcomes these drawbacks and lends to the perusal of the system over wide continua of various parameters, enabling us to get an elevated view at a much lesser level of complexity compared to the conventional LRA based numerical methods or the conventional ab initio methods of accounting for the nonlocal effects. Our proposed GNOR based model predicts strong modifications to various QD properties such as population difference, absorption, MNP induced shifts to excitonic energy and F\orster enhanced broadening, coherent plasmonic field enhancement, and quantum state purity, compared to the conventional LRA based predictions. Such modifications are prominent with small MNP radii, high QD dipole moments, small detunings (of the coherent external illumination from the bare excitonic resonance), and near parameter regions exhibiting plasmonic meta resonance (PMR)-like behavior. Moreover, our complete analytical characterization enables optimization of the large system parameter space for different applications, a luxury not fully offered by the methods currently available in literature.

An Efficient Unrestricted PCM-Elongation Method for Large High-Spin Polymer/Dendrimer Systems

Abstract The application of conventional ab initio methods to large high-spin systems remains challenging because CPU time rapidly increases with the system size. The unrestricted elongation method performs stepwise electronic structure calculations for large high-spin systems and can reproduce the results of conventional methods, i.e., achieve a very small total energy error (∼ 10 –9 a.u. per atom). Moreover, a polarizable continuum model (PCM) method is incorporated for the estimation of solvent effect and it is demonstrated that the unrestricted PCM-elongation method is accurate and efficient for performing electronic structure calculations of large high-spin systems under solvent.

Reply to the ‘Comment on “Enhancement in the production of nucleating clusters due to dimethylamine and large uncertainties in the thermochemistry of amine-enhanced nucleation”’ by Kupiainen-Maatta et al.

We analyze the arguments of Kupiainen-Maatta et al. and show clearly that our study is free of ‘misrepresentations of earlier studies’ and that our conclusions are particularly well-justified. We demonstrate why and how the B3RICC2 (B3LYP/CBSB7//RI-CC2/aug-cc-pv(d+T)z) method criticized in our work overestimates the stability of sulfuric acid and sulfuric acid–base clusters compared to conventional DFT and ab initio methods and experimental data and fails to reproduce base dependencies of nucleation and cluster formation rates. We also show that the thermochemistry predicted by the conventional PW91PW91 method is consistent with experiments and can be used for simulations of atmospheric nucleation rates. We discuss uncertainties in simulations and experimental data and their impacts on conclusions about the nature of amine-enhanced nucleation and conclude that further high-resolution laboratory experiments, computational studies and measurements of atmospheric amine concentrations are needed in order to determine the extent, at which amines impact atmospheric nucleation.

Adaptive machine learning framework to accelerate ab initio molecular dynamics

Quantum mechanics‐based ab initio molecular dynamics (MD) simulation schemes offer an accurate and direct means to monitor the time evolution of materials. Nevertheless, the expensive and repetitive energy and force computations required in such simulations lead to significant bottlenecks. Here, we lay the foundations for an accelerated ab initio MD approach integrated with a machine learning framework. The proposed algorithm learns from previously visited configurations in a continuous and adaptive manner on‐the‐fly, and predicts (with chemical accuracy) the energies and atomic forces of a new configuration at a minuscule fraction of the time taken by conventional ab initio methods. Key elements of this new accelerated ab initio MD paradigm include representations of atomic configurations by numerical fingerprints, a learning algorithm to map the fingerprints to the properties, a decision engine that guides the choice of the prediction scheme, and requisite amount of ab initio data. The performance of each aspect of the proposed scheme is critically evaluated for Al in several different chemical environments. This work has enormous implications beyond ab initio MD acceleration. It can also lead to accelerated structure and property prediction schemes, and accurate force fields. © 2014 Wiley Periodicals, Inc.

The development and validation of a pseudoatoms approach for combined quantum mechanics and molecular mechanics calculations of polypeptide

A pseudoatoms approach was proposed for combined quantum mechanics and molecular mechanics (QM/MM) calculations of polypeptide to ensure that each amino acid residue was an indivisible unit in the partitioning of the polypeptide into QM and MM subsystems. The pseudoatoms approach broke the QM/MM boundary peptide bonds as follow: the pseudoatom Ops(sp3) replacing the QM frontier amine N(sp3), and the pseudoatoms Nps(sp2)Oca(sp2) replacing the QM frontier C(sp2)O(sp2) carbonyl group. Conventional ab initio effective core potential (ECP) were constructed on the pseudoatoms to duplicate the all-electron molecular structure and charge distribution. The pseudoatoms’ ECP parameters were optimized using a genetic algorithm method, and consequently validated by a test set of 19 amino acids. The pseudoatoms approach was further validated by simulating an oligopeptide involved reaction with QM/MM and full-QM methods, respectively. The results from the QM/MM simulations are similar to those from the corresponding full-QM simulations. In summary, the pseudoatoms approach may be useful for QM/MM calculations of polypeptide. Additionally, it can be implemented without program modifications due to the use of conventional ECP.

Evaluating the performance of DFT methods in electric property calculations: sodium chloride as a test case

We present a quantitative analysis of the performance of conventional ab initio and density functional theory (DFT) methods. The important NaCl diatomic is chosen as testing ground. The analysis relies on metric considerations and pattern recognition techniques. Taking into account a collection of ab initio methods A = {SCF, MP2, CCSD} and DFT = {B3LYP, B3PW91, mPW1PW91, mPW1PBE, PBEPW91, BHandH, BHandHLYP, HCTC}, we find that the DFT method most close to CCSD is BHandHLYP. The DFT method closest to the collection of ab initio methods is BHandHLYP.

Nuclear quantum effects on protonated lysine with an asymmetric low barrier hydrogen bond: an ab initio path integral molecular dynamics study

The nuclear quantum effect on the short and asymmetric hydrogen bond of protonated lysine (LysH+) at room temperature is explored by ab initio path integral molecular dynamics (PIMD) simulation. From static electronic structure calculations, the barrier height of proton transfer in LysH+ is 1.1 kcal mol−1, which is much lower than that of typical hydrogen bonds. The hydrogen-bonded proton is delocalized in between two nitrogen atoms in the PIMD simulation including both thermal and nuclear quantum effects, while the proton is localized on a nitrogen atom in a conventional ab initio molecular dynamics simulation including thermal effects alone. We found that the proton transfer barrier found in the static calculation and conventional ab initio simulation is completely washed out in the PIMD simulation. Meanwhile, the proton distribution at the Nζ atom was larger than that at the N atom, as found in the static calculation and conventional ab initio molecular dynamics simulation. We clarified that an asymmetric low barrier hydrogen bond exists in LysH+ at room temperature from our PIMD simulation.

Quantifying the performance of conventional DFT methods on a class of difficult problems: The interaction (hyper)polarizability of two water molecules as a test case

AbstractWe have investigated the predictive capability of a widely used group of density functional theory (DFT) methods on the interaction (hyper)polarizability of the two water molecules in the water dimer. We find that compared with conventional ab initio methods, DFT gives a different picture of the dipole moment and (hyper) polarizability for the water monomer and dimer. In addition, the DFT methods tested in this work predict for the water dimer a systematically higher value of the differential interaction‐induced second hyperpolarizability per water molecule, DHPM = [ $ \bar{\gamma} $(H2O)2]/2 − $ \bar \gamma $ (H2O) than the ab initio ones. The interaction‐induced mean polarizability and second hyperpolarizability is predicted to be small and positive for all DFT methods used here. The respective quantities predicted by conventional post‐Hartree–Fock ab initio methods are also quite small but negative. © 2011 Wiley Periodicals, Inc. Int J Quantum Chem, 2012

Linear optical properties and their bond length dependence of yttrium bromide from ab initio and density functional theory calculations

We have employed conventional ab initio and density functional theory methods to study the electronic properties such as the mean static dipole polarizability, α ¯ , anisotropy of the polarizability, Δ α, and dipole moment, μ, of yttrium bromide. The bond length dependence of properties is determined at different levels of theory and appropriate expansions around experimental internuclear distance have been presented. Moreover, the first and second geometrical derivatives for each property are quantified and their level of theory dependence has been analyzed. To study the effect of molecular rotation and vibration on the electronic properties, the rovibrational corrections have also been carried out. It is found that these corrections are less pronounced for considered properties of YBr. In all calculations, the electron correlation effects have been considered and discussed. The obtained results show that the electron correlation is more significant in the calculation of the mean and the anisotropy of dipole polarizability.

Electric multipole moments, polarizability, and hyperpolarizability of xenon dihydride (HXeH)

We report an extensive theoretical investigation of the electric moments and dipole (hyper)polarizability of xenon dihydride. We have employed conventional ab initio and DFT methods and large, flexible Gaussian-type basis sets. Our best values for the electric moments are obtained at the CCSD level of theory and are Θ = −4.8760 ea 0 2 and Φ = −71.95 ea 0 4 . For the (hyper)polarizability, our best results, extracted from finite-field CCSD(T) calculations, are $$ \bar{\alpha } = 49.93 $$ and ∆α = 55.80 e 2 a 0 2 E −1 , for the mean and the anisotropy of the dipole polarizability and $$ \bar{\gamma } = 31.26 \times 10^{3} e^{4} a_{0}^{4} E_{h}^{ - 3} $$ for the mean second hyperpolarizability. Overall, the molecule is characterized by large (hyper)polarizability anisotropies. The DFT methods predict dipole polarizabilities comparable to those calculated by ab initio but overestimate the second hyperpolarizability.

Syntheses, antiproliferative activity and theoretical characterization of acitretin-type retinoids with changes in the lipophilic part

Acitretin analogs, incorporating changes in the lipophilic part, were efficiently synthesized from commercially available aromatic aldehydes or methyl ketones using the Wittig or Horner–Wadsworth–Emmons reaction. Their antiproliferative activity was evaluated against human breast MCF-7 epithelial cells. Analogs 3, 4, 8 and 11 exhibited strong, dose-dependent, antiproliferative activity on the tested cell line. Analog 3, incorporating three methoxy groups in the aromatic ring, exhibited the strongest inhibitory effect at 10 μM. High-level all electron conventional ab initio and density functional theory quantum chemical calculations were performed to obtain the molecular structure, electron charge distribution and polarization properties of all compounds of interest in this work. The most active analogs were planar and were characterized by larger dipole moments than the other synthesized molecules. Another factor of importance to the analysis of the activity of these molecules is the dipole polarizability.

Spin transport in carbon nanotubes with magnetic vacancy-defects

The spin-polarized electron transport properties of metallic carbon nanotubes containing vacancies are investigated using first-principles and nonequilibrium Green's function techniques. Reconstructed mono-and trivacancies, containing carbon atoms with unsaturated bonds, behave like quasilocalized magnetic impurities. However, in conventional ab initio simulations, these magnetic defects are artificially repeated periodically (supercell method) and are thus incorrectly coupled by long range interactions. Consequently, a technique based on an open system with an isolated magnetic impurity is used here to accurately describe the local magnetic properties of these defects, revealing spin-dependent conductances in tubes, which could be exploited in spintronic nanodevices.

Physicochemical characterization of neuroleptics. Relative stability of 7- and 9-hydroxyrisperidones and their protonated forms in gas phase and in solution

Conventional ab initio and DFT-B3LYP calculations have been used to investigate on molecular conformation, dipole moments, intramolecular hydrogen bond and relative energies of 9-hydroxy and 7-hydroxyrisperidone metabolites of risperidone, in their neutral and mono-protonated forms in the gas phase and in solution. Three minimum energy conformations characterize the potential energy surface of 7-hydroxyrisperidone, while 9-hydroxyrisperidone is dominated by a strong intramolecular OH⋯N hydrogen bond of ca. 8 kcal/mol, which drastically reduces in water solution. In the gas phase, 9-hydroxyrisperidone is the most stable isomer both in the neutral and in the protonated forms. Solvent effects favour 7-hydroxyrisperidone rotamers owing to their higher dipole moment values. Under the physiological pH of 7.4, the protonated forms of both isomers in water coexist in almost equivalent amount, in qualitative agreement with the experiment. It is suggested that to stabilize the pharmacologically active 9-hydroxyrisperidone over the 7-OH isomer one has to increase its molecular dipole moment and the intramolecular OH⋯N hydrogen bond energy.

On the Reaction of Glycerol Dehydratase with But‐3‐ene‐1,2‐diol

High-level conventional ab initio and density functional theory (DFT) calculations have been performed to examine the fate of the native substrate glycerol (1) and its analogue but-3-ene-1,2-diol (7) in the coenzyme B(12)-dependent enzyme glycerol dehydratase (GDH). Experimental studies find that 7 irreversibly inactivates GDH, though the mechanism for the inactivation remains unknown. Interestingly, the EPR data suggest that the spin density for an observed radical is located in the vicinity of the C1 atom, which has been interpreted to indicate termination of the pathway at the substrate-derived radical 8. Our calculations show that if analogue 7 were to follow a similar mechanistic pathway to that followed by 1, then the reaction would be unlikely to stop at 8 but would rather proceed to the highly stabilized product-related radical 9. However, the EPR characteristics of 9 would not be consistent with the observed EPR data. Calculations involving an initial H-atom abstraction from the C2 position of 7 identify alternative radicals that might account for the EPR data, though they are of relatively high energy. A proposal that could explain the experimental observations is that the enzyme binds 7 in such a manner as to prevent the efficient transformation of 8. Recent work with the related enzyme diol dehydratase suggests that a common, but as yet unexplained, inactivation mechanism may be operative for both enzymes. Finally, we note the good overall performance of the MPWB1K, BMK, M05-2X, and B2-PLYP DFT procedures for these reactions, with the BMK method producing the best results.

Density-functional based tight-binding: an approximate DFT method

The DFTB method, as well as its self-consistent charge corrected variant SCC-DFTB, has widened the range of applications of fundamentally well established theoretical tools. As an approximate density-functional method, DFTB holds nearly the same accuracy, but at much lower computational costs, allowing investigation of the electronic structure of large systems which can not be exploited with conventional ab initio methods. In the present paper the fundaments of DFTB and SCC-DFTB and inclusion of London dispersion forces are reviewed. In order to show an example of the DFTB applicability, the zwitterionic equilibrium of glycine in aqueous solution is investigated by molecular-dynamics simulation using a dispersion-corrected SCC-DFTB Hamiltonian and a periodic box containing 129 water molecules, in a purely quantum-mechanical approach.

How large is the static electric (hyper)polarizability anisotropy in HXeI?

An extensive conventional ab initio and density functional theory investigation reveals that HXeI is a polar molecule with large multipole moments and highly anisotropic (hyper)polarizability. At the CCSD(T) level of theory our best values for the mean (hyper)polarizability are alphae(2)a(0) (2)E(h) (-1)=101.46, betae(3)a(0) (3)E(h) (-2)=-850.7, and gammae(4)a(0) (4)E(h) (-3)=18.7x10(3). The corresponding anisotropies are Deltaalphae(2)a(0) (2)E(h) (-1)=119.66, Deltabetae(3)a(0) (3)E(h) (-2)=-2518.7, Delta(1)gammae(4)a(0) (4)E(h) (-3)=-249.1x10(3), and Delta(2)gammae(4)a(0) (4)E(h) (-3)=-99.6x10(3). The longitudinal components of the (hyper)polarizability are dominant. Our value for the anisotropy of the dipole polarizability is considerably larger than the recent empirical estimate of 22.9 e(2)a(0) (2)E(h) (-1) [N. H. Nahler et al., J. Chem. Phys. 119, 224 (2003)]. The results of the insertion of Xe into HI are quantified by the calculation of the differential (hyper)polarizability at the MP2 level of theory: alpha(diff) identical withalpha(HXeI)-alpha(HI)-alpha(Xe)=36.29 e(2)a(0) (2)E(h) (-1) and gamma(diff) identical with gamma(HXeI)-gamma(HI)-gamma(Xe)=18.1x10(3) e(4)a(0) (4)E(h) (-3).

Static electric polarizability and hyperpolarizability of sodium clusters: The case of the sodium tetramer

We have calculated the static polarizability and second hyperpolarizability of sodium tetramer using conventional ab initio and density functional theory based methods. Our best values for the mean and the anisotropy of the dipole polarizability are α¯= 548.81 and Δα=489.14 e$^{2}$a$_{0}^{2}$E$_{h}^{-1}$. The mean second hyperpolarizability is very large at γ¯=5531 × 10$^{3}$ e$^{4}$a$_{0}^{4}$E$_{h}^{-3}$. The differential-per-atom polarizability is negative but the differential-per-atom hyperpolarizability is positive. Density functional theory methods offer a rather fuzzy picture of the second hyperpolarizability of the molecule. Nevertheless, we have found that the widely used B3LYP and B3PW91 methods perform rather reliably for both the polarizability and the hyperpolarizability of Na$_{4}$.