Ab Initio Model Research Articles

Construction of optimized tight-binding models using ab initio Hamiltonian: application to monolayer 2H-transition metal dichalcogenides

We present optimized tight-binding (TB) models with atomic orbitals to improve ab initio TB models constructed by truncating full density functional theory (DFT) Hamiltonian based on localized orbitals. Retaining qualitative features of the original Hamiltonian, the optimization reduces quantitative deviations in overall band structures between the ab initio TB model and the full DFT Hamiltonian. The optimization procedure and related details are demonstrated by using semiconducting and metallic Janus transition metal dichalcogenides monolayers in the 2 H configuration. Varying the truncation range from partial second neighbors to third ones, we show differences in electronic structures between the truncated TB model and the original full Hamiltonian, and how much the optimization can remedy the quantitative loss induced by truncation. We further elaborate the optimization process so that local electronic properties such as valence and conduction band edges and Fermi surfaces are precisely reproduced by the optimized TB model. We also extend our discussions to TB models including spin-orbit interactions, so we provide the optimized TB model replicating spin-related properties of the original Hamiltonian such as spin textures. The optimization process described here can be readily applied to construct the fine-tuned TB model based on various DFT calculations.

Turbulence-supported Massive Star Envelopes

The outer envelopes of massive (M ≳ 10 M ⊙) stars exhibit large increases in opacities from forests of lines and ionization transitions (particularly from iron and helium) that trigger near-surface convection zones. One-dimensional (1D) models predict density inversions and supersonic motions that must be resolved with computationally intensive three-dimensional (3D) radiation hydrodynamic (RHD) modeling. Only in the last decade have computational tools advanced to the point where ab initio 3D models of these turbulent envelopes can be calculated, enabling us to present five 3D RHD Athena++ models (four previously published and one new 13 M ⊙ model). When convective motions are subsonic, we find excellent agreement between 3D and 1D velocity magnitudes, stellar structure, and photospheric quantities. However, when convective velocities approach the sound speed, hydrostatic balance fails as the turbulent pressure can account for 80% of the force balance. As predicted by Henyey, we show that this additional pressure support leads to a modified temperature gradient, which reduces the superadiabaticity where convection is occurring. In addition, all five models display significant overshooting from the convection in the Fe convection zone. As a result, the turbulent velocities at the surface are indicative of those in the Fe zone. There are no confined convection zones as seen in 1D models. In particular, helium convection zones seen in 1D models are significantly modified. Stochastic low-frequency brightness variability is also present in the 13 M ⊙ model with comparable amplitude and characteristic frequency to observed stars.

Machine learning-assisted multi-scale modeling

Neural network-based machine learning is capable of approximating functions in very high dimension with unprecedented efficiency and accuracy. This has opened up many exciting new possibilities, one of which is to use machine learning algorithms to assist multi-scale modeling. In this review, we use three examples to illustrate the process involved in using machine learning in multi-scale modeling: ab initio molecular dynamics, ab initio meso-scale models, such as Landau models and generalized Langevin equation, and hydrodynamic models for non-Newtonian flows.

Parameters of 220 million stars from Gaia BP/RP spectra

ABSTRACT We develop, validate and apply a forward model to estimate stellar atmospheric parameters (Teff, log g, and [Fe/H]), revised distances and extinctions for 220 million stars with XP spectra from Gaia DR3. Instead of using ab initio stellar models, we develop a data-driven model of Gaia XP spectra as a function of the stellar parameters, with a few straightforward built-in physical assumptions. We train our model on stellar atmospheric parameters from the LAMOST survey, which provides broad coverage of different spectral types. We model the Gaia XP spectra with all of their covariances, augmented by 2MASS and WISE photometry that greatly reduces degeneracies between stellar parameters, yielding more precise determinations of temperature and dust reddening. Taken together, our approach overcomes a number of important limitations that the astrophysical parameters released in Gaia DR3 faced, and exploits the full information content of the data. We provide the resulting catalogue of stellar atmospheric parameters, revised parallaxes, and extinction estimates, with all their uncertainties. The modelling procedure also produces an estimate of the optical extinction curve at the spectral resolution of the XP spectra (R ∼ 20–100), which agrees reasonably well with the R(V) = 3.1 CCM model. Remaining limitations that will be addressed in future work are that the model assumes a universal extinction law, ignores binary stars and does not cover all parts of the Hertzsprung–Russell Diagram (e.g. white dwarfs).

Effect of the Addition of Re on the Microstructure and Phase Composition of Haynes 282: Ab Initio Modelling and Experimental Investigation of Additively Manufactured Specimens.

Interactions in a multicomponent Ni-Cr-Mo-Al-Re model alloy were determined by ab initio calculations in order to investigate the Re doping effect on Haynes 282 alloys. Simulation results provided an understanding of short-range interactions in the alloy and successfully predicted the formation of a Cr and Re-rich phase. The Haynes 282 + 3 wt% Re alloy was manufactured using the additive manufacturing direct metal laser sintering (DMLS) technique, in which the presence of the (Cr17Re6)C6 carbide was confirmed by an XRD study. The results provide useful information about the interactions between Ni, Cr, Mo, Al, and Re as a function of temperature. The designed five-element model can lead to a better understanding of phenomena that occur during the manufacture or heat treatment of modern, complex, multicomponent Ni-based superalloys.

On the stability of Ti(Mn,Al)2 C14 Laves phase in an intermetallic Ti–42Al–5Mn alloy

In order to facilitate a more widespread use of intermetallic γ-TiAl based alloys in the aircraft and automotive sector, recent research focuses on the development of low-cost titanium aluminides. The strong β-stabilizing effect as well as the increased ductility upon Mn addition renders this alloying element a promising candidate to fully or partially substitute other, more expensive, alloying elements such as Mo, Ta and Nb. Mn-containing γ-TiAl based alloys, however, are prone to the formation of the undesired, brittle Ti(Mn,Al)2 C14 Laves phase during long-term exposure at the targeted service temperatures, which can deteriorate the ductility at ambient temperatures. In this study, the transformation kinetics as well as the chemical and thermal existence range of the C14 Laves phase in the low-cost Ti–42Al–5Mn (at.%) alloy were investigated by complementary experimental and computational approaches. In situ and ex situ high-energy X-ray diffraction in combination with microstructural investigations were used to study the occurrence and transformation kinetics of possible Laves phase formation in the course of annealing treatments. The chemical stability range of the C14 Laves phase was addressed by chemical analysis in conjunction with complementary ab initio modeling. Using these combined approaches, the critical local Mn concentration of ∼16 at.% for Laves phase formation within lamellar α2 and ∼17 at.% within βo in the Ti–42Al–5Mn alloy was determined. These results should be critically considered for future design of advanced low-cost γ-TiAl based alloys.

Near-Chromosomal-Level Genome Assembly of the Sea Urchin Echinometra lucunter, a Model for Speciation in the Sea.

Echinometra lucunter, the rock-boring sea urchin, is a widely distributed echinoid and a model for ecological studies of reproduction, responses to climate change, and speciation. We present a near chromosome-level genome assembly of E. lucunter, including 21 scaffolds larger than 10 Mb predicted to represent each of the chromosomes of the species. The 760.4 Mb assembly includes a scaffold N50 of 30.0 Mb and BUSCO (benchmarking universal single-copy orthologue) single copy and a duplicated score of 95.8% and 1.4%, respectively. Ab-initio gene model prediction and annotation with transcriptomic data constructed 33,989 gene models composing 50.4% of the assembly, including 37,036 transcripts. Repetitive elements make up approximately 39.6% of the assembly, and unresolved gap sequences are estimated to be 0.65%. Whole genome alignment with Echinometra sp. EZ revealed high synteny and conservation between the two species, further bolstering Echinometra as an emerging genus for comparative genomics studies. This genome assembly represents a high-quality genomic resource for future evolutionary and developmental studies of this species and more broadly of echinoderms.

Moiré Kanamori-Hubbard model for transition metal dichalcogenide homobilayers

Ab initio and continuum model studies predicted that the $\mathrm{\ensuremath{\Gamma}}$ valley transition metal dichalcogenide (TMD) homobilayers could simulate the conventional multiorbital Hubbard model on the moir\'e honeycomb lattice. Here, we perform the Wannierization starting from the continuum model and show that a more general moir\'e Kanamori-Hubbard model emerges, beyond the extensively studied standard multiorbital Hubbard model, which can be used to investigate the many-body physics in the $\mathrm{\ensuremath{\Gamma}}$ valley TMD homobilayers. Using the unrestricted Hartree-Fock and Lanczos techniques, we study these half-filled multiorbital moir\'e bands. By constructing the phase diagrams we predict the presence of an antiferromagnetic state and in addition we found unexpected and dominant states, such as a $S=1$ ferromagnetic insulator and a charge density wave state. Our theoretical predictions made using this model can be tested in future experiments on the $\mathrm{\ensuremath{\Gamma}}$ valley TMD homobilayers.

Temperature and co-crystallization effects on Zr isotopes

We undertook Zr isotope measurements on zircon, titanite, biotite, amphibole, and whole rocks from the La Posta pluton (Peninsular Ranges, southern California) together with trace element analyses and U-Pb age measurements to understand the controls on Zr isotope fractionation in igneous rocks, including temperature, crystallization sequence, and kinetic effects. We find large (>0.6‰) Zr isotope fractionations (expressed as δ94/90Zr) between titanite and zircon forming at approximately the same temperature. Using equilibrium fractionation factors calculated from ionic and ab initio models, we infer the controls on Zr isotope evolution to include the relative order in which phases appear on the liquidus, with titanite fractionation resulting in isotopically lighter melt and zircon fractionation resulting in isotopically heavier melt. While these models of Zr fractionation can explain δ94/90Zr variations in zircon of up to ∼1.5‰, crystallization order, temperature and presence of co-crystallizing phases do not explain all aspects of the intracrystalline Zr isotopic distribution in zircons in the La Posta pluton or the large range of Zr isotopic values among zircons (>2‰). Without additional constraints, such as knowledge of co-crystallizing phases and a better understand of the true causes of Zr isotope fractionation, Zr isotopes in zircon remains an ambiguous proxy of magmatic evolution.

Electron Trap Depths in Cubic Lutetium Oxide Doped with Pr and Ti, Zr or Hf─From Ab Initio Multiconfigurational Calculations.

We propose a universal approach to model intervalence charge transfer (IVCT) and metal-to-metal charge transfer (MMCT) transitions between ions in solids. The approach relies on already well-known and reliable ab initio RASSCF/CASPT2/RASSI-SO calculations for a series of emission center coordination geometries (restricted active space self-consistent field, complete active space second-order perturbation theory, and restricted active space state interaction with spin-orbit coupling). Embedding with ab initio model potentials (AIMPs) is used to represent the crystal lattice. We propose a way to construct the geometries via interpolation of the coordinates obtained using solid-state density functional theory (DFT) calculations for the structures where the activator metal is at specific oxidation (charge) states of interest. The approach thus takes the best of two worlds: the precision of the embedded cluster calculations (including localized excited states) and the geometries from DFT, where the effects of ionic radii mismatch (and eventual nearby defects) can be modeled explicitly. The method is applied to the Pr activator and Ti, Zr, Hf codopants in cubic Lu2O3, in which the said ions are used to obtain energy storage and thermoluminescence properties. Electron trap charging and discharging mechanisms (not involving a conduction band) are discussed in the context of the IVCT and MMCT role in them. Trap depths and trap quenching pathways are analyzed.

Magnetic interactions in intercalated transition metal dichalcogenides: A study based on ab initio model construction

Transition metal dichalcogenides (TMDs) are known to have a wide variety of magnetic structures by hosting other transition metal atoms in the van der Waals gaps. To understand the chemical trend of the magnetic properties of the intercalated TMDs, we perform a systematic first-principles study for 48 compounds with different hosts, guests, and composition ratios. Starting with calculations based on spin density functional theory, we derive classical spin models by applying the Liechtenstein method to the ab initio Wannier-based tight-binding model. We show that the calculated exchange couplings are overall consistent with the experiments. In particular, when the composition rate is 1/3, the chemical trend can be understood in terms of the occupation of the 3d-orbital in the intercalated transition metal. The present results give us a useful guiding principle to predict the magnetic structure of compounds that are yet to be synthesized.

Temperature-dependent elastic constants of thorium dioxide probed using time-domain Brillouin scattering

We report the adiabatic elastic constants of single-crystal thorium dioxide over a temperature range of 77–350 K. Time-domain Brillouin scattering, an all-optical, non-contact picosecond ultrasonic technique, is used to generate and detect coherent acoustic phonons that propagate in the bulk perpendicular to the surface of the crystal. These coherent acoustic lattice vibrations have been monitored in two hydrothermally grown single-crystal thorium dioxide samples along the (100) and (311) crystallographic directions. The three independent elastic constants of the cubic crystal (C11, C12, and C44) are determined from the measured bulk acoustic velocities. The longitudinal wave along the (100) orientation provided a direct measurement of C11. Measurement of C44 and C12 was achieved by enhancing the intensity of quasi-shear mode in a (311) oriented crystal by adjusting the polarization angle relative to the crystal axes. We find the magnitude of softening of the three elastic constants to be ∼2.5% over the measured temperature range. Good agreement is found between the measured elastic constants with previously reported values at room temperature, and between the measured temperature-dependent bulk modulus with calculated values. We find that semi-empirical models capturing lattice anharmonicity adequately reproduce the observed trend. We also determine the acoustic Grüneisen anharmonicity parameter from the experimentally derived temperature-dependent bulk modulus and previously reported temperature-dependent values of volumetric thermal expansion coefficient and heat capacity. This work presents measurements of the temperature-dependent elasticity in single-crystal thorium dioxide at cryogenic temperature and provides a basis for testing ab initio theoretical models and evaluating the impact of anharmonicity on thermophysical properties.

Resistance saturation in semi-conducting polyacetylene molecular wires

Realizing the promises of molecular electronic devices requires an understanding of transport on the nanoscale. Here, we consider a Su-Schrieffer-Heeger model for semi-conducting trans-polyacetylene molecular wires in which we endow charge carriers with a finite lifetime. The aim of this exercise is two-fold: (i) the simplicity of the model allows an insightful numerical and analytical comparison of the Landauer and Kubo linear-response formalism; (ii) we distill the prototypical characteristics of charge transport through gapped mesoscopic systems and compare these to bulk semiconductors. We find that both techniques yield a residual differential conductance at low temperatures for contacted polyacetylene chains of arbitrary length—in line with the resistivity saturation in some correlated narrow-gap semiconductors. Quantitative agreement, however, is limited to not too long molecules. Indeed, while the Landauer transmission is suppressed exponentially with the system size, the Kubo response only decays hyperbolically. Our findings inform the choice of transport methodologies for the ab initio modelling of molecular devices.

Predicting Protein-Peptide Interactions: Benchmarking Deep Learning Techniques and a Comparison with Focused Docking.

The accurate prediction of protein structures achieved by deep learning (DL) methods is a significant milestone and has deeply impacted structural biology. Shortly after its release, AlphaFold2 has been evaluated for predicting protein-peptide interactions and shown to significantly outperform RoseTTAfold as well as a conventional blind docking method: PIPER-FlexPepDock. Since then, new AlphaFold2 models, trained specifically to predict multimeric assemblies, have been released and a new ab initio folding model OmegaFold has become available. Here, we assess docking success rates for these new DL folding models and compare their performance with our state-of-the-art, focused peptide-docking software AutoDock CrankPep (ADCP). The evaluation is done using the same dataset and performance metric for all methods. We show that, for a set of 99 nonredundant protein-peptide complexes, the new AlphaFold2 model outperforms other Deep Learning approaches and achieves remarkable docking success rates for peptides. While the docking success rate of ADCP is more modest when considering the top-ranking solution only, it samples correct solutions for around 62% of the complexes. Interestingly, different methods succeed on different complexes, and we describe a consensus docking approach using ADCP and AlphaFold2, which achieves a remarkable 60% for the top-ranking results and 66% for the top 5 results for this set of 99 protein-peptide complexes.

Framework for efficient ab initio electronic structure with Gaussian Process States

We present a general framework for the efficient simulation of realistic fermionic systems with modern machine learning inspired representations of quantum many-body states, towards a universal tool for ab initio electronic structure. These machine learning inspired ansatzes have recently come to the fore in both a (first quantized) continuum and discrete Fock space representations, where however the inherent scaling of the latter approach for realistic interactions has so far limited practical applications. With application to the 'Gaussian Process State', a recently introduced ansatz inspired by systematically improvable kernel models in machine learning, we discuss different choices to define the representation of the computational Fock space. We show how local representations are particularly suited for stochastic sampling of expectation values, while also indicating a route to overcome the discrepancy in the scaling compared to continuum formulated models. We are able to show competitive accuracy for systems with up to 64 electrons, including a simplified (yet fully ab initio) model of the Mott transition in three-dimensional hydrogen, indicating a significant improvement over similar approaches, even for moderate numbers of configurational samples.

Ab initio modeling and thermodynamics of hydrated plutonium oxalates

An ab initio study on the plutonium oxalate hydrates: Pu2(C2O4)3⋅10H2O and Pu(C2O4)2⋅6H2O, using PBE exchange-correlation with D3 dispersion correction and Hubbard correction for the plutonium atoms was performed and compared to experimental vibrational spectral and thermodynamic property values. We demonstrated that this technique can accurately predict the experimental infrared spectra Pu(III) oxalate hydrate, as well as the Raman peak of PuO2 (used to calculate the thermodynamic properties of the oxalates). For Pu(IV) oxalate hydrate, we found that our predicted structure agreed qualitatively with PXRD measurements, the only available experimental determination of the structure. Using this method at standard temperature and pressure, we predicted standard enthalpies of formation of -6,755 kJ mol−1 and -3,923 kJ mol−1 and standard Gibbs free energy of formation of -5,899 kJ mol−1 and -3,386 kJ mol−1 for Pu2(C2O4)3⋅10H2O and Pu(C2O4)2⋅6H2O, respectively.

Thermal decomposition of trimethylindium and indium trisguanidinate precursors for InN growth: An abinitio and kinetic modeling study.

Indium nitride (InN) is an interesting material for future electronic and photonic-related applications, as it combines high electron mobility and low-energy band gap for photoabsorption or emission-driven processes. In this context, atomic layer deposition techniques have been previously employed for InN growth at low temperatures (typically <350 °C), reportedly yielding crystals with high quality and purity. In general, this technique is assumed to not involve any gas phase reactions as a result from the time-resolved insertion of volatile molecular sources into the gas chamber. Nonetheless, such temperatures could still favor the precursor decomposition in the gas phase during the In half-cycle, therefore altering the molecular species that undergoes physisorption and, ultimately, driving the reaction mechanism to pursue other pathways. Thence, we herein evaluate the thermal decomposition of relevant In precursors in the gas phase, namely, trimethylindium (TMI) and tris(N,N'-diisopropyl-2-dimethylamido-guanidinato) indium (III) (ITG), by means of thermodynamic and kinetic modeling. According to the results, at T = 593K, TMI should exhibit partial decomposition of ∼8% after 400s to first generate methylindium and ethane (C2H6), a percentage that increases to ∼34% after 1h of exposure inside the gas chamber. Therefore, this precursor should be present in an intact form to undergo physisorption during the In half-cycle of the deposition (<10s). On the other hand, the ITG decomposition starts already at the temperatures used in the bubbler, in which it slowly decomposes as it is evaporated during the deposition process. At T = 300 °C, the decomposition is a fast process that reaches 90% completeness after 1s and where equilibrium, at which almost no ITG remains, is achieved before 10s. In this case, the decomposition pathway is likely to occur via elimination of the carbodiimide ligand. Ultimately, these results should contribute for a better understanding of the reaction mechanism involved in the InN growth from these precursors.

Insight into the Molecular Mechanism for Enhanced Longevity of Supramolecular Vesicular Photocatalysts

AbstractSupramolecular self‐assembly is a promising strategy for stabilizing the photo‐sensitive components in photocatalysis. However, the underlying correlation between the enhanced photostability and supramolecular structure at the molecular level has not yet been fully understood. Herein, we develop a biomimetic vesicular membrane‐based polyporphyrin photocatalyst exhibiting excellent photocatalytic stability with at least activity time of 240 h in hydrogen generation. Time‐domain ab initio modelling together with transient absorption spectroscopy, visual frontier orbitals and Gibbs free energy calculation disclose that the ordered aggregation of porphyrin units in the vesicle membrane facilitates “hot” electron relaxation and the rapid dissipation of photo‐generated charges, thereby contributing to the longevity. This work deepens the molecular‐level understanding on photostability and photocatalytic mechanism of supramolecular photocatalysts.

Insight into the Molecular Mechanism for Enhanced Longevity of Supramolecular Vesicular Photocatalysts.

Supramolecular self-assembly is a promising strategy for stabilizing the photo-sensitive components in photocatalysis. However, the underlying correlation between the enhanced photostability and supramolecular structure at the molecular level has not yet been fully understood. Herein, we develop a biomimetic vesicular membrane-based polyporphyrin photocatalyst exhibiting excellent photocatalytic stability with at least activity time of 240 h in hydrogen generation. Time-domain ab Initio modelling together with transient absorption spectroscopy, visual frontier orbitals and Gibbs free energy calculation disclose that the ordered aggregation of porphyrin units in the vesicle membrane facilitates "hot" electron relaxation, a longer photo-generated carrier lifetime and the rapid dissipation of photo-generated charges, which contribute to the longevity. This work deepens the molecular-level understanding on photostability and photocatalytic mechanism of supramolecular photocatalysts.

The SCF convergence criteria of the ab initio calculations of elastic properties of single-crystal B2 ZrPd phase

The mechanical and dynamical stability of the geometry optimised structural phases of Zr50Pd50-xRux have been calculated using the ab initio modelling technique. The accuracy of the elastic constants largely depends on the accuracy of the self consistent field (SCF) setting and also on the level of convergence of geometry optimisation for each distorted structure. Parameters such as energy cutoff, SCF convergence criteria and k-points set form part of these calculations. Often, the importance of setting accuracy of these parameters is neglected and may result in erroneous reporting of elastic constants. In the present study, B2 ZrPd is used to demonstrate the disadvantage of inaccurate selection of energy cutoff and k-points set on the calculation of elastic constants. The computed results of phonon dispersion curves were in excellent agreement with existing experimental data, and further aided in resolving discrepancy among theoretical results. While current results showed that the B2 phase of ZrPd is neither mechanically or vibrationally stable at 0 K, contrary to some of the previous calculations, the phonon dispersion curves of all considered ZrPd phases reveal presence of imaginary frequencies. Introduction of Ru on Pd site of the B2 ZrPd has negligible effect on the thermodynamic stability (Hf), but increased both mechanical and lattice dynamic stability significantly. In addition, it is predicted for the first time from lattice dynamic calculations that addition of 18.75 at.% Ru alters the martenstic transformation path from that of pristine ZrPd towards that of TiNi. Lattice vibration results for other chosen reference alloys are also in excellent agreement with existing theoretical data.