DFTB Parameters for the Periodic Table: Part 1, Electronic Structure

Long range piezoelectricity effects in van der Waals heterobilayer systems beyond 1000 atoms

Twist angle is a relevant design and control component for the piezoelectric coefficients of van der Waals (vdW) heterostructures. This theoretical work assesses in high detail the impact of the twist angle on the piezoelectricity of two-dimensional (2D) heterobilayer systems. We expand the density-functional based tight-binding method to predict the piezoelectric coefficients of twisted and corrugated 2D heterobilayer structures with more than 1000 atoms. We showcase the method on hexagonal III-V/transition metal dichalcogenide vdW heterosystems. Our calculations yield a periodic relationship between the in-plane piezoelectric coefficients and the corresponding twist angles, indicating the tunability of the in-plane piezoelectricity. In contrast, the out-of-plane piezoelectricity is not twist angle dependent, but nonlinearly changes with the average interlayer distance.

Multipole Expansion of Atomic Electron Density Fluctuation Interactions in the Density-Functional Tight-Binding Method

The accuracy of the density-functional tight-binding (DFTB) method in describing noncovalent interactions is limited due to its reliance on monopole-based spherical charge densities. In this study, we present a multipole-extended second-order DFTB (mDFTB2) method that takes into account atomic dipole and quadrupole interactions. Furthermore, we combine the multipole expansion with the monopole-based third-order contribution, resulting in the mDFTB3 method. To assess the accuracy of mDFTB2 and mDFTB3, we evaluate their performance in describing noncovalent interactions, proton transfer barriers, and dipole moments. Our benchmark results show promising improvements even when using the existing electronic parameters optimized for the original DFTB3 model. Both mDFTB2 and mDFTB3 outperform their monopole-based counterparts, DFTB2 and DFTB3, in terms of accuracy. While mDFTB2 and mDFTB3 perform comparably for neutral and positively charged systems, mDFTB3 exhibits superior performance over mDFTB2 when dealing with negatively charged systems and proton transfers. Overall, the incorporation of the multipole expansion significantly enhances the accuracy of the DFTB method in describing noncovalent interactions and proton transfers.

Diversity of Behavior after Collisions of Sn and Si Nanoparticles Found Using a New Density Functional Tight-Binding Method

We present a new approach to studying nanoparticle collisions using density functional based tight binding (DFTB). A novel DFTB parametrization has been developed to study the collision process of Sn and Si clusters (NPs) using molecular dynamics (MD). While bulk structures were used as training sets, we show that our model is able to accurately reproduce the cohesive energy of the nanoparticles using density functional theory (DFT) as a reference. A surprising variety of phenomena are revealed for the Si/Sn nanoparticle collisions, depending on the size and velocity of the collision: from core-shell structure formation to bounce-off phenomena.

Toward Quantum Chemical Free Energy Simulations of Platinum Nanoparticles on Titania Support

Platinum nanoparticles (Pt-NPs) supported on titania surfaces are costly but indispensable heterogeneous catalysts because of their highly effective and selective catalytic properties. Therefore, it is vital to understand their physicochemical processes during catalysis to optimize their use and to further develop better catalysts. However, simulating these dynamic processes is challenging due to the need for a reliable quantum chemical method to describe chemical bond breaking and bond formation during the processes but, at the same time, fast enough to sample a large number of configurations required to compute the corresponding free energy surfaces. Density functional theory (DFT) is often used to explore Pt-NPs; nonetheless, it is usually limited to some minimum-energy reaction pathways on static potential energy surfaces because of its high computational cost. We report here a combination of the density functional tight binding (DFTB) method as a fast but reliable approximation to DFT, the steered molecular dynamics (SMD) technique, and the Jarzynski equality to construct free energy surfaces of the temperature-dependent diffusion and growth of platinum particles on a titania surface. In particular, we present the parametrization for Pt-X (X = Pt, Ti, or O) interactions in the framework of the second-order DFTB method, using a previous parametrization for titania as a basis. The optimized parameter set was used to simulate the surface diffusion of a single platinum atom (Pt1) and the growth of Pt6 from Pt5 and Pt1 on the rutile (110) surface at three different temperatures (T = 400, 600, 800 K). The free energy profile was constructed by using over a hundred SMD trajectories for each process. We found that increasing the temperature has a minimal effect on the formation free energy; nevertheless, it significantly reduces the free energy barrier of Pt atom migration on the TiO2 surface and the transition state (TS) of its deposition. In a concluding remark, the methodology opens the pathway to quantum chemical free energy simulations of Pt-NPs' temperature-dependent growth and other transformation processes on the titania support.

Fast and accurate prediction of material properties with three-body tight-binding model for the periodic table

Parametrized tight-binding models fit to first-principles calculations can provide an efficient and accurate quantum mechanical method for predicting properties of molecules and solids. However, well-tested parameter sets are generally only available for a limited number of atom combinations, making routine use of this method difficult. Furthermore, many previous models consider only simple two-body interactions, which limits accuracy. To tackle these challenges, we develop a density functional theory database of nearly 1 000 000 materials, which we use to fit a universal set of tight-binding parameters for 65 elements and their binary combinations. We include both two-body and three-body effective interaction terms in our model, plus self-consistent charge transfer, enabling our model to work for metallic, covalent, and ionic bonds with the same parameter set. To ensure predictive power, we adopt a learning framework where we repeatedly test the model on new low-energy crystal structures and then add them to the fitting data set, iterating until predictions improve. We distribute the materials database and tools developed in this paper publicly.

Self-Consistent-Charge Density-Functional Tight-Binding Parameters for Modeling an All-Solid-State Lithium Battery

All-solid-state lithium-ion batteries have been a promising solution for next-generation energy storage due to their safety and potentially high energy density. In this work, we developed a density-functional tight-binding (DFTB) parameter set for modeling solid-state lithium batteries, focusing on the band alignment at electrolyte/electrode interfaces. Despite DFTB being widely applied in the simulation of large-scale systems, parametrization is usually done for single materials, and less attention is paid to band alignment among multiple materials. Band offsets at the electrolyte/electrode interfaces are key quantities determining the performance. Here, an automated global optimization method based on DFTB confinement potentials of all elements is developed, while the band offsets between electrodes and electrolytes are introduced as constraints during the optimization. The parameter set is applied to model an all-solid-state Li/Li₂PO₂N/LiCoO₂ battery, and its electronic structure shows a good agreement with that from density-functional theory (DFT) calculations.

GPU-Enhanced DFTB Metadynamics for Efficiently Predicting Free Energies of Biochemical Systems

Metadynamics calculations of large chemical systems with ab initio methods are computationally prohibitive due to the extensive sampling required to simulate the large degrees of freedom in these systems. To address this computational bottleneck, we utilized a GPU-enhanced density functional tight binding (DFTB) approach on a massively parallelized cloud computing platform to efficiently calculate the thermodynamics and metadynamics of biochemical systems. To first validate our approach, we calculated the free-energy surfaces of alanine dipeptide and showed that our GPU-enhanced DFTB calculations qualitatively agree with computationally-intensive hybrid DFT benchmarks, whereas classical force fields give significant errors. Most importantly, we show that our GPU-accelerated DFTB calculations are significantly faster than previous approaches by up to two orders of magnitude. To further extend our GPU-enhanced DFTB approach, we also carried out a 10 ns metadynamics simulation of remdesivir, which is prohibitively out of reach for routine DFT-based metadynamics calculations. We find that the free-energy surfaces of remdesivir obtained from DFTB and classical force fields differ significantly, where the latter overestimates the internal energy contribution of high free-energy states. Taken together, our benchmark tests, analyses, and extensions to large biochemical systems highlight the use of GPU-enhanced DFTB simulations for efficiently predicting the free-energy surfaces/thermodynamics of large biochemical systems.

Divide-and-Conquer Linear-Scaling Quantum Chemical Computations

Fragmentation and embedding schemes are of great importance when applying quantum-chemical calculations to more complex and attractive targets. The divide-and-conquer (DC)-based quantum-chemical model is a fragmentation scheme that can be connected to embedding schemes. This feature article explains several DC-based schemes developed by the authors over the last two decades, which was inspired by the pioneering study of DC self-consistent field (SCF) method by Yang and Lee (J. Chem. Phys. 1995, 103, 5674-5678). First, the theoretical aspects of the DC-based SCF, electron correlation, excited-state, and nuclear orbital methods are described, followed by the two-component relativistic theory, quantum-mechanical molecular dynamics simulation, and the introduction of three programs, including DC-based schemes. Illustrative applications confirmed the accuracy and feasibility of the DC-based schemes.

Efficient Computation of the Interaction Energies of Very Large Non-covalently Bound Complexes

We present a new benchmark set consisting of 16 large non-covalently bound systems (LNCI16) ranging from 380 up to 1988 atoms and featuring diverse interaction motives. Gas-phase interaction energies are calculated with various composite DFT, semi-empirical quantum mechanical (SQM), and force field (FF) methods and are evaluated using accurate DFT reference values. Of the employed QM methods, PBEh-3c proves to be the most robust for large systems with a relative mean absolute deviation (relMAD) of 8.5% with respect to the reference interaction energies. r2SCAN-3c yields an even smaller relMAD, at least for the subset of complexes for which the calculation could be converged, but is less robust for systems with smaller HOMO–LUMO gaps. The inclusion of Fock-exchange is therefore important for the description of very large non-covalent interaction (NCI) complexes in the gas phase. GFN2-xTB was found to be the best performer of the SQM methods with an excellent result of only 11.1% deviation. From the assessed force fields, GFN-FF and GAFF achieve the best accuracy. Considering their low computational costs, both can be recommended for routine calculations of very large NCI complexes, with GFN-FF being clearly superior in terms of general applicability. Hence, GFN-FF may be routinely applied in supramolecular synthesis planning.

1 Introduction

2 The LNCI16 Benchmark Set

3 Computational Details

4 Generation of Reference Values

5 Results and Discussion

6 Conclusions

DFTB Parameters for the Periodic Table: Part III, Spin-Orbit Coupling

Spin-orbit coupling (SOC) is crucially important for the correct description of the electronic structure and transport properties of inorganic semiconductors, and for assessing topological properties as in topological insulators. We present a consistent set of SOC parameters for the density-functional based tight-binding (DFTB) method covering the elements throughout the periodic table. The parameters are based on atomic SOC data calculated at the level of density-functional theory (DFT). We tested these parameters for representative systems with significant SOC, including transition metal dichalcogenide two-dimensional crystals, III-V bulk semiconductors, and topological insulators. Our parameterization opens the door for DFTB-based electronic structure and transport calculations of very large systems, such as twisted van der Waals heterostructures.

Theoretical Studies of Furan and Thiophene Nanothreads: Structures, Cycloaddition Barriers, and Activation Volumes

This theoretical study examines the formation, structure, and stability of two of the most ordered nanothreads produced yet, those derived from furan and thiophene. The energetic consequences and activation barriers of the first two steps of oligomerization via a Diels-Alder mechanism were examined. The ca. 20 GPa difference in the synthetic pressures (lower for furan) is explainable in terms of the greater loss of aromaticity by the thiophene. The effects of pressure on the reaction profiles, operating through a volume decrease along the reaction coordinate, are illustrated. The interesting option of polymerization proceeding in one or two directions opens up the possibility of polymers with opposing, cumulative dipole moments. The computed activation volumes are consistently more negative for furan, in accordance with the lower onset pressure of furan polymerization. The energetics of three ordered polymer structures were examined. The syn polymer, with all O/S atoms on the same side, if not allowed to distort, is at a high energy relative to the other two due to the O/S lone pair repulsion, understandably greater for S than for O at the 2.8/2.6 Å separation. Set free, the syn isomers curve or arch in two- or three-dimensional (helical) ways, whose energetics are traced in detail. The syn polymer can also stabilize itself by twisting into zig-zag or helical energy minima. The release of strain in a linear thread as the pressure is relaxed to 1 atm, with consequent thread curving, is a likely mechanism for the observed loss of the crystalline order in the polymer as it is returned to ambient pressure.

BENCHMARKS OF THE DENSITY FUNCTIONAL TIGHT-BINDING METHOD FOR REDOX, PROTONATION AND ELECTRONIC PROPERTIES OF QUINONES

Organic materials with controllable molecular design and sustainable resources are promising electrode materials. Crystalline quinones have been investigated in a variety of rechargeable battery chemistries due to their ubiquitous nature,...

Performance of GFN1-xTB for periodic optimization of Metal Organic Frameworks

Tight-binding approaches bridge the gap between force field methods and Density Functional Theory (DFT). Density Functional Tight Binding (DFTB) has been employed for a wide range of systems containing up...

Binding of Saturated and Unsaturated C6-Hydrocarbons to the Electrophilic Anion [B12Br11]−: A Systematic Mechanistic Study

The highly reactive gaseous ion [B12Br11]– is a metal-free closed-shell anion which spontaneously forms covalent bonds with hydrocarbon molecules, including alkanes. Herein, we systematically investigate the reaction mechanism for binding...

Molecular Dynamics Simulations of the Thermal Decomposition of 3,4-Bis(3-nitrofurazan-4-yl)furoxan

When stimulated, for example, by a high temperature, the physical and chemical properties of energetic materials (EMs) may change, and, in turn, their overall performance is affected. Therefore, thermal stability is crucial for EMs, especially the thermal dynamic behavior. In the past decade, significant efforts have been made to study the thermal dynamic behavior of 3,4-bis(3-nitrofurazan-4-yl)furoxan (DNTF), one of the new high-energy-density materials (HEDMs). However, the thermal decomposition mechanism of DNTF is still not specific or comprehensive. In this study, the self-consistent-charge density-functional tight-binding method was combined with molecular dynamics (MD) simulations to reveal the differences in the thermal decomposition of DNTF under four heating conditions. The O-N (O) bond would fracture first during DNTF initial thermal decomposition at medium and low temperatures, thus triggering the cracking of the whole structure. At 2000 and 2500 K, NO₂ loss on outer ring I is the fastest initial thermal decomposition pathway, and it determines that the decomposition mechanism is different from that of a medium-low temperature. NO₂ is found to be the most active intermediate product; large molecular fragments, such as C₂N₂O, are found for the first time. Hopefully, these results could provide some insights into the decomposition mechanism of new HEDMs.

Controlling potential difference between electrodes based on self-consistent-charge density functional tight binding

A proper understanding and description of the electronic response of the electrode surfaces in electrochemical systems are quite important because the interactions between the electrode surface and electrolyte give rise to unique and useful interfacial properties. Atomistic modeling of the electrodes requires not only an accurate description of the electronic response under a constant-potential condition but also computational efficiency in order to deal with systems large enough to investigate the interfacial electrolyte structures. We thus develop a self-consistent-charge density functional tight binding based method to model a pair of electrodes in electrochemical cells under the constant-potential condition. The method is more efficient than the (ab initio) density functional theory calculations so that it can treat systems as large as those studied in classical atomistic simulations. It can also describe the electronic response of electrodes quantum mechanically and more accurately than the classical counterparts. The constant-potential condition is introduced through a Legendre transformation of the electronic energy with respect to the difference in the number of electrons in the two electrodes and their electrochemical potential difference, through which the Kohn-Sham equations for each electrode are variationally derived. The method is applied to platinum electrodes faced parallel to each other under an applied voltage. The electronic response to the voltage and a charged particle is compared with the result of a classical constant-potential method based on the chemical potential equalization principle.

Curvature Constrained Splines for DFTB Repulsive Potential Parametrization

The Curvature Constrained Splines (CCS) methodology has been used for fitting repulsive potentials to be used in SCC-DFTB calculations. The benefit of using CCS is that the actual fitting of the repulsive potential is performed through quadratic programming on a convex objective function. This guarantees a unique (for strictly convex) and optimum two-body repulsive potential in a single shot, thereby making the parametrization process robust, and with minimal human effort. Furthermore, the constraints in CCS give the user control to tune the shape of the repulsive potential based on prior knowledge about the system in question. Herein, we developed the method further with new constraints and the capability to handle sparse data. We used the method to generate accurate repulsive potentials for bulk Si polymorphs and demonstrate that for a given Slater-Koster table, which reproduces the experimental band structure for bulk Si in its ground state, we are unable to find one single two-body repulsive potential that can accurately describe the various bulk polymorphs of silicon in our training set. We further demonstrate that to increase transferability, the repulsive potential needs to be adjusted to account for changes in the chemical environment, here expressed in the form of a coordination number. By training a near-sighted Atomistic Neural Network potential, which includes many-body effects but still essentially within the first-neighbor shell, we can obtain full transferability for SCC-DFTB in terms of describing the energetics of different Si polymorphs.

DFTB Modeling of Lithium-Intercalated Graphite with Machine-Learned Repulsive Potential

Lithium ion batteries have been a central part of consumer electronics for decades. More recently, they have also become critical components in the quickly arising technological fields of electric mobility and intermittent renewable energy storage. However, many fundamental principles and mechanisms are not yet understood to a sufficient extent to fully realize the potential of the incorporated materials. The vast majority of concurrent lithium ion batteries make use of graphite anodes. Their working principle is based on intercalation, the embedding and ordering of (lithium-) ions in two-dimensional spaces between the graphene sheets. This important process, it yields the upper bound to a battery's charging speed and plays a decisive role in its longevity, is characterized by multiple phase transitions, ordered and disordered domains, as well as nonequilibrium phenomena, and therefore quite complex. In this work, we provide a simulation framework for the purpose of better understanding lithium-intercalated graphite and its behavior during use in a battery. To address large system sizes and long time scales required to investigate said effects, we identify the highly efficient, but semiempirical density functional tight binding (DFTB) as a suitable approach and combine particle swarm optimization (PSO) with the machine learning (ML) procedure Gaussian process regression (GPR) as implemented in the recently developed GPrep package for DFTB repulsion fitting to obtain the necessary parameters. Using the resulting parametrization, we are able to reproduce experimental reference structures at a level of accuracy which is in no way inferior to much more costly ab initio methods. We finally present structural properties and diffusion barriers for some exemplary system states.

Analytical approach to phonon calculations in the SCC-DFTB framework

Detailed derivation of the analytical, reciprocal-space approach of Hessian calculation within the self-consistent-charge density-functional based tight-binding framework (SCC-DFTB) is presented. This approach provides an accurate and efficient way for obtaining the SCC-DFTB Hessian of periodic systems. Its superiority with respect to the traditional numerical force differentiation method is demonstrated for doped graphene, graphene nanoribbons, boron-nitride nanotubes, bulk zinc-oxide, and other systems.

Fast Evaluation of Two-Center Integrals over Gaussian Charge Distributions and Gaussian Orbitals with General Interaction Kernels

We present efficient algorithms for computing two-center integrals and integral derivatives, with general interaction kernels K(r₁₂), over Gaussian charge distributions of general angular momenta l. While formulated in terms of traditional ab initio integration techniques, full derivations and required secondary information, as well as a reference implementation, are provided to make the content accessible to other fields. Concretely, the presented algorithms are based on an adaption of the McMurchie-Davidson Recurrence Relation (MDRR) combined with analytical properties of the solid harmonic transformation; this obviates all intermediate recurrences except the adapted MDRR itself, and allows it to be applied to fully contracted auxiliary kernel integrals. The technique is particularly well-suited for semiempirical molecular orbital methods, where it can serve as a more general and efficient replacement of Slater-Koster tables, and for first-principles quantum chemistry methods employing density fitting. But the formalism's high efficiency and ability of handling general interaction kernels K(r₁₂) and multipolar Gaussian charge distributions may also be of interest for modeling electrostatic interactions and short-range exchange and charge penetration effects in classical force fields and model potentials. With the presented technique, a 4894 × 4894 univ-JKFIT Coulomb matrix J_AB = (A|1/r₁₂|B) (183 MiB) can be computed in 50 ms on a Q2'2018 notebook CPU, without any screening or approximations.

Density-functional tight-binding: basic concepts and applications to molecules and clusters

The scope of this article is to present an overview of the Density Functional based Tight Binding (DFTB) method and its applications. The paper introduces the basics of DFTB and its standard formulation up to second order. It also addresses methodological developments such as third order expansion, inclusion of non-covalent interactions, schemes to solve the self-interaction error, implementation of long-range short-range separation, treatment of excited states via the time-dependent DFTB scheme, inclusion of DFTB in hybrid high-level/low level schemes (DFT/DFTB or DFTB/MM), fragment decomposition of large systems, large scale potential energy landscape exploration with molecular dynamics in ground or excited states, non-adiabatic dynamics. A number of applications are reviewed, focusing on -(i)- the variety of systems that have been studied such as small molecules, large molecules and biomolecules, bare orfunctionalized clusters, supported or embedded systems, and -(ii)- properties and processes, such as vibrational spectroscopy, collisions, fragmentation, thermodynamics or non-adiabatic dynamics. Finally outlines and perspectives are given.

Quantum mechanical molecular dynamics simulations of polaron formation in methylammonium lead iodide perovskite

Polaron formation in a halide perovskite is analyzed via nanometre-scale quantum mechanical molecular dynamics simulations.

Excitation and phase transitions of spin density waves in graphene nanoribbons

Anti-ferromagnetic states widely exist on graphene zigzag edges. Our previous work (Xie et al 2018 New J. Phys. 20 013035) shows there are also various spin density wave (SDW) states in the graphene nanoribbons (GNR). In this paper, we propose some excitation mechanism of these SDW by the absorbed magnetic atoms with the mean-field Hubbard model and the first-principles calculations. With the Floquet theory, we also find that by regulating the temperature or the light intensity, there are a lot of phase transitions for these SDW. The temperature or light can dramatically modify the inter-edge coupling or the spin stiffness of GNR. The artificial magnetization technique is employed to explore the establishment process of these SDW states. Some interesting intermedia phase transitions and the corresponding spin orders are discovered. This research may be helpful in the understandings and technique controls of magnetic orders in future nano magnetic devices.

Density functional tight binding study of β-Ga2O3: Electronic structure, surface energy, and native point defects

A new parameter set to model monoclinic gallium oxide, β-Ga₂O₃, with the density functional tight binding (DFTB) method is developed. Using this new parameter set, DFTB calculations of bulk electronic band structure, surface energy of low-index surfaces, and formation energy of native point vacancy defects are performed and compared with the state-of-the-art density functional theory (DFT) calculations using the advanced hybrid exchange correlation functional. DFTB calculates the bandgap energy of 4.87 eV around the Fermi energy with the conduction band approximately following the DFT study by Peelaers and Van de Walle [Phys. Status Solidi B 252, 828 (2015)]. The surface energies calculated feature the correct order of stability among low index surfaces with surface energies in semiquantitative agreement with Bermudez' report [Chem. Phys. 323, 193 (2006)]. Oxygen and gallium vacancy defect formation energies and respective transition levels calculated using DFTB with a new parameter set are in semiquantitative agreement with the previous DFT reports by Varley et al. and Zacherle et al. [Appl. Phys. Lett. 97, 142106 (2010); Phys. Rev. B 87, 235206 (2013)]. This new semiempirical parameter set for β-Ga₂O₃, validated in bulk, surface, and point properties, would be useful for large spatiotemporal quantum chemical calculations regarding β-Ga₂O₃.

Pattern Learning Electronic Density of States

Electronic density of states (DOS) is a key factor in condensed matter physics and material science that determines the properties of metals. First-principles density-functional theory (DFT) calculations have typically been used to obtain the DOS despite the considerable computation cost. Herein, we report a fast machine learning method for predicting the DOS patterns of not only bulk structures but also surface structures in multi-component alloy systems by a principal component analysis. Within this framework, we use only four features to define the composition, atomic structure, and surfaces of alloys, which are the d-orbital occupation ratio, coordination number, mixing factor, and the inverse of miller indices. While the DFT method scales as O(N3) in which N is the number of electrons in the system size, our pattern learning method can be independent on the number of electrons. Furthermore, our method provides a pattern similarity of 91 ~ 98% compared to DFT calculations. This reveals that our learning method will be an alternative that can break the trade-off relationship between accuracy and speed that is well known in the field of electronic structure calculations.

Formal structure of periodic system of elements

For more than 150 years, the structure of the periodic system of the chemical elements has intensively motivated research in different areas of chemistry and physics. However, there is still no unified picture of what a periodic system is. Herein, based on the relations of order and similarity, we report a formal mathematical structure for the periodic system, which corresponds to an ordered hypergraph. It is shown that the current periodic system of chemical elements is an instance of the general structure. The definition is used to devise a tailored periodic system of polarizability of single covalent bonds, where order relationships are quantified within subsets of similar bonds and among these classes. The generalized periodic system allows envisioning periodic systems in other disciplines of science and humanities.

Development of Divide-and-Conquer Density-Functional Tight-Binding Method for Theoretical Research on Li-Ion Battery

The density-functional tight-binding (DFTB) method is one of the useful quantum chemical methods, which provides a good balance between accuracy and computational efficiency. In this account, we reviewed the basis of the DFTB method, the linear-scaling divide-and-conquer (DC) technique, as well as the parameterization process. We also provide some refinement, modifications, and extension of the existing parameters that can be applicable for lithium-ion battery systems. The diffusion constants of common electrolyte molecules and LiTFSA salt in solution have been estimated using DC-DFTB molecular dynamics simulation with our new parameters. The resulting diffusion constants have good agreement to the experimental diffusion constants.

A Density Functional Tight Binding Layer for Deep Learning of Chemical Hamiltonians

Current neural networks for predictions of molecular properties use quantum chemistry only as a source of training data. This paper explores models that use quantum chemistry as an integral part of the prediction process. This is done by implementing self-consistent-charge Density-Functional-Tight-Binding (DFTB) theory as a layer for use in deep learning models. The DFTB layer takes, as input, Hamiltonian matrix elements generated from earlier layers and produces, as output, electronic properties from self-consistent field solutions of the corresponding DFTB Hamiltonian. Backpropagation enables efficient training of the model to target electronic properties. Two types of input to the DFTB layer are explored, splines and feed-forward neural networks. Because overfitting can cause models trained on smaller molecules to perform poorly on larger molecules, regularizations are applied that penalize nonmonotonic behavior and deviation of the Hamiltonian matrix elements from those of the published DFTB model used to initialize the model. The approach is evaluated on 15 700 hydrocarbons by comparing the root-mean-square error in energy and dipole moment, on test molecules with eight heavy atoms, to the error from the initial DFTB model. When trained on molecules with up to seven heavy atoms, the spline model reduces the test error in energy by 60% and in dipole moments by 42%. The neural network model performs somewhat better, with error reductions of 67% and 59%, respectively. Training on molecules with up to four heavy atoms reduces performance, with both the spline and neural net models reducing the test error in energy by about 53% and in dipole by about 25%.

Mechanical properties of pristine and defective carbon-phosphide monolayers: a density functional tight-binding study

Using density functional tight-binding theory, we investigated the elastic properties and deformation and failure behaviors of pristine and defective carbon-phosphide (CP) monolayers subjected to uniform uniaxial tensile strain along arm-chair (AC) and zig-zag (ZZ) directions. Two variants of CP (α-CP and β-CP) were studied and two types of carbon and phosphorous vacancies (single and double) were considered. It was found that carbon monovacancies have the lowest formation energy, while phosphorous divacancies have the highest one in both CP allotropes. A strong mechanical anisotropy for CP was found with the Young's modulus and the failure stress along ZZ direction being an order of magnitude larger than those along AC direction. In both allotropes, the Young's modulus, failure stress and strain are considerably affected by vacancies, especially along AC direction. Fracture of pristine CP monolayer occurred via the rupture of phosphorous-phosphorous bonds when CP monolayer is stretched along AC direction, while via the rupture of carbon-phosphorous bonds when stretched along ZZ direction. Defective α-CP and β-CP monolayers both undergo a brittle-like failure initiated around the hosted vacancies at a lower critical strain. The failure strain and stress along the AC direction are affected only by phosphorous vacancies, while along the ZZ direction, they are almost equally affected by both phosphorous and carbon vacancies. These understandings may provide useful guidelines for potential applications of CP monolayers in nanoelectromechanical systems.

Density-functional tight-binding approach for metal clusters, nanoparticles, surfaces and bulk: application to silver and gold

Density-functional based tight-binding (DFTB) is an efficient quantum mechanical method that can describe a variety of systems, going from organic and inorganic compounds to metallic and hybrid materials. The present topical review addresses the ability and performance of DFTB to investigate energetic, structural, spectroscopic and dynamical properties of gold and silver materials. After a brief overview of the theoretical basis of DFTB, its parametrization and its transferability, we report its past and recent applications to gold and silver systems, including small clusters, nanoparticles, bulk and surfaces, bare and interacting with various organic and inorganic compounds. The range of applications covered by those studies goes from plasmonics and molecular electronics, to energy conversion and surface chemistry. Finally, perspectives of DFTB in the field of gold and silver surfaces and NPs are outlined.

Effect of vacancies on the mechanical properties of phosphorene nanotubes

Using density functional tight-binding method, we studied the mechanical properties, deformation and failure of armchair (AC) and zigzag (ZZ) phosphorene nanotubes (PNTs) with monovacancies and divacancies subjected to uniaxial tensile strain. We found that divacancies in AC PNTs and monovacancies in ZZ PNTs possess the lowest vacancy formation energy, which decreases with the tube diameter in AC PNTs and increases in ZZ PNTs. The Young's modulus is reduced, while the radial and thickness Poisson's ratios are increased by hosted vacancies. In defective AC PNTs, deformation involves fracture of the intra-pucker bonds and formation of the new inter-pucker bonds at a critical strain, and the most stretched bonds around the vacancy rupture first, triggering a sequence of the structural transformations terminated by the ultimate failure. The critical strain of AC PNTs is reduced significantly by hosted vacancies, whereas their effect on the critical stress is relatively weaker. Defective ZZ PNTs fail in a brittle-like manner once the most stretched bonds around a vacancy rupture, and vacancies are able to significantly reduce the failure strain but only moderately reduce the failure stress of ZZ PNTs. The understandings revealed here on the mechanical properties and the deformation and failure mechanisms of PNTs provide useful guidelines for their design and fabrication as building blocks in nanodevices.

Communication: Relaxation-limited electronic currents in extended reservoir simulations

Open-system approaches are gaining traction in the simulation of charge transport in nanoscale and molecular electronic devices. In particular, "extended reservoir" simulations, where explicit reservoir degrees of freedom are present, allow for the computation of both real-time and steady-state properties but require relaxation of the extended reservoirs. The strength of this relaxation, γ, influences the conductance, giving rise to a "turnover" behavior analogous to Kramers turnover in chemical reaction rates. We derive explicit, general expressions for the weak and strong relaxation limits. For weak relaxation, the conductance increases linearly with γ and every electronic state of the total explicit system contributes to the electronic current according to its "reduced" weight in the two extended reservoir regions. Essentially, this represents two conductors in series-one at each interface with the implicit reservoirs that provide the relaxation. For strong relaxation, a "dual" expression-one with the same functional form-results, except now proportional to 1/γ and dependent on the system of interest's electronic states, reflecting that the strong relaxation is localizing electrons in the extended reservoirs. Higher order behavior (e.g., γ2 or 1/γ2) can occur when there is a gap in the frequency spectrum. Moreover, inhomogeneity in the frequency spacing can give rise to a pseudo-plateau regime. These findings yield a physically motivated approach to diagnosing numerical simulations and understanding the influence of relaxation, and we examine their occurrence in both simple models and a realistic, fluctuating graphene nanoribbon.

Prediction of many-electron wavefunctions using atomic potentials

For a given many-electron molecule, it is possible to define a corresponding one-electron Schrödinger equation, using potentials derived from simple atomic densities, whose solution predicts fairly accurate molecular orbitals for single- and multi-determinant wavefunctions for the molecule. The energy is not predicted and must be evaluated by calculating Coulomb and exchange interactions over the predicted orbitals. Potentials are found by minimizing the energy of predicted wavefunctions. There exist slightly less accurate average potentials for first-row atoms that can be used without modification in different molecules. For a test set of molecules representing different bonding environments, these average potentials give wavefunctions with energies that deviate from exact self-consistent field or configuration interaction energies by less than 0.08 eV and 0.03 eV per bond or valence electron pair, respectively.