DFTB+ is a versatile community developed open source software package offering fast and efficient methods for carrying out atomistic quantum mechanical simulations. By implementing various methods approximating density functional theory (DFT), such as the density functional based tight binding (DFTB) and the extended tight binding method, it enables simulations of large systems and long timescales with reasonable accuracy while being considerably faster for typical simulations than the respective ab initio methods. Based on the DFTB framework, it additionally offers approximated versions of various DFT extensions including hybrid functionals, time dependent formalism for treating excited systems, electron transport using non-equilibrium Green’s functions, and many more. DFTB+ can be used as a user-friendly standalone application in addition to being embedded into other software packages as a library or acting as a calculation-server accessed by socket communication. We give an overview of the recently developed capabilities of the DFTB+ code, demonstrating with a few use case examples, discuss the strengths and weaknesses of the various features, and also discuss on-going developments and possible future perspectives.

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DFTB+, a software package for efficient approximate density functional theory based atomistic simulations

The discovery of carbon nanotubes (CNTs) and graphene over the last two decades has heralded a new era in physics, chemistry and nanotechnology. During this time, intense efforts have been made towards understanding the atomic-scale mechanisms by which these remarkable nanostructures grow. Molecular simulations have made significant contributions in this regard; indeed, they are responsible for many of the key discoveries and advancements towards this goal. Here we review molecular simulations of CNT and graphene growth, and in doing so we highlight the many invaluable insights gained from molecular simulations into these complex nanoscale self-assembly processes. This review highlights an often-overlooked aspect of CNT and graphene formation?that the two processes, although seldom discussed in the same terms, are in fact remarkably similar. Both can be viewed as a 0D???1D???2D transformation, which converts carbon atoms (0D) to polyyne chains (1D) to a complete sp2-carbon network (2D). The difference in the final structure (CNT or graphene) is determined only by the curvature of the catalyst and the strength of the carbon?metal interaction. We conclude our review by summarizing the present shortcomings of CNT/graphene growth simulations, and future challenges to this important area.

https://iopscience.iop.org/article/10.1088/0034-4885/78/3/036501/pdf

Insights into carbon nanotube and graphene formation mechanisms from molecular simulations: a review

Research in graphene-based energy materials is a rapidly growing area. Many graphene-based energy applications involve interfacial processes. To enable advances in the design of these energy materials, such that their operation, economy, efficiency and durability is at least comparable with fossil-fuel based alternatives, connections between the molecular-scale structure and function of these interfaces are needed. While it is experimentally challenging to resolve this interfacial structure, molecular simulation and computational chemistry can help bridge these gaps. In this Review, we summarise recent progress in the application of computational chemistry to graphene-based materials for fuel cells, batteries, photovoltaics and supercapacitors. We also outline both the bright prospects and emerging challenges these techniques face for application to graphene-based energy materials in future.

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Computational chemistry for graphene-based energy applications: progress and challenges

TiO2 nanoparticles (NPs) are nowadays considered fundamental building blocks for many technological applications. Morphology is found to play a key role with spherical NPs presenting higher binding properties and chemical activity. From the experimental point of view, the characterization of these nano-objects is extremely complex, opening a large room for computational investigations. In this work, TiO2 spherical NPs of different sizes (from 300 to 4000 atoms) have been studied with a two-scale computational approach. Global optimization to obtain stable and equilibrated nanospheres was performed with a self-consistent charge density functional tight-binding (SCC-DFTB) simulated annealing process, causing a considerable atomic rearrangement within the nanospheres. Those SCC-DFTB relaxed structures have been then optimized at the DFT(B3LYP) level of theory. We present a systematic and comparative SCC-DFTB vs DFT(B3LYP) study of the structural properties, with particular emphasis on the surface-to-bulk sit...

Modelling realistic TiO2 nanospheres: A benchmark study of SCC-DFTB against hybrid DFT.

We benchmark existing and improved self-consistent-charge density functional based tight-binding (SCC-DFTB) parameters for silver and gold clusters as well as for bulk materials. In the former case, our benchmarks focus on both the structural and energetic properties of small-size AgN and AuN clusters (N from 2 to 13), medium-size clusters with N = 20 and 55, and finally larger nanoparticles with N = 147, 309, and 561. For bulk materials, structural, energetics and elastic properties are discussed. We show that SCC-DFTB is quite satisfactory in reproducing essential differences between silver and gold aggregates, in particular their 2D–3D structural transitions, and their dependency upon cluster charge. SCC-DFTB is also in agreement with DFT and experiments in the medium-size regime regarding the energetic ordering of the different low-energy isomers and allows for an overall satisfactory treatment of bulk properties. A consistent convergence between the cohesive energies of the largest investigated nanop...

Benchmarking Density Functional Based Tight-Binding for Silver and Gold Materials: From Small Clusters to Bulk.

We present a parametrization of a self-consistent charge density functional-based tight-binding scheme (SCC-DFTB) to describe gold-organic hybrid systems by adding new Au-X (X = Au, H, C, S, N, O) parameters to a previous set designed for organic molecules. With the aim of describing gold-thiolates systems within the DFTB framework, the resulting parameters are successively compared with density functional theory (DFT) data for the description of Au bulk, Aun gold clusters (n = 2, 4, 8, 20), and Aun SCH3 (n = 3 and 25) molecular-sized models. The geometrical, energetic, and electronic parameters obtained at the SCC-DFTB level for the small Au3 SCH3 gold-thiolate compound compare very well with DFT results, and prove that the different binding situations of the sulfur atom on gold are correctly described with the current parameters. For a larger gold-thiolate model, Au25 SCH3 , the electronic density of states and the potential energy surfaces resulting from the chemisorption of the molecule on the gold aggregate obtained with the new SCC-DFTB parameters are also in good agreement with DFT results.

SCC-DFTB parameters for simulating hybrid gold-thiolates compounds.

Chemical vapor deposition (CVD) growth of graphene on Cu(111) has been modeled with quantum chemical molecular dynamics (QM/MD) simulations. These simulations demonstrate at the atomic level how graphene forms on copper surfaces. In contrast to other popular catalysts, such as nickel and iron, copper is in a surface molten state throughout graphene growth at CVD-relevant temperatures, and graphene growth takes place without subsurface diffusion of carbon. Surface Cu atoms have remarkably high mobilities on the Cu(111) surface, both before and after graphene nucleation. This surface mobility drives “defect healing” processes in the nucleating graphene structure that convert defects such as pentagons and heptagons into carbon hexagons. Consequently, the graphene defects that become “kinetically trapped” using other catalysts, such as Ni and Fe, are less commonly observed in the case of Cu. We propose this mechanism to be the basis of copper's ability to form high-quality, large-domain graphene flakes.

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Graphene nucleation on a surface-molten copper catalyst: quantum chemical molecular dynamics simulations

This work presents both the parametrization procedure of a self-consistent charge density functional based tight-binding scheme (SCC-DFTB) for hafnium oxide and the structural as well as the electronic results of the simulations of amorphous hafnium oxide $a\text{-HfO}{}_{2}$ using the data resulting during the parametrization. While aiming at describing amorphous hafnium oxide, the created parameters could be successfully compared to ab initio DFT data for hafnium and hafnium oxide crystalline structures. Furthermore the atomic structure and electronic properties obtained in the DFTB simulations of $a\text{-HfO}{}_{2}$ compare well to other theoretical studies using classical many-body as well as quantum-mechanical approaches.

Christian Hettich

Papers

SCC-DFTB parameters for simulating hybrid gold-thiolates compounds.

Graphene nucleation on a surface-molten copper catalyst: quantum chemical molecular dynamics simulations

Density functional based tight-binding parametrization of hafnium oxide: Simulations of amorphous structures