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

Reduced-cost supercell approach for computing accurate phonon density of states in organic crystals

Phonon contributions to organic crystal structures and thermochemical properties can be significant, but computing a well-converged phonon density of states with lattice dynamics and periodic density functional theory (DFT) is often computationally expensive due to the need for large supercells. Using semi-empirical methods like density functional tight binding (DFTB) instead of DFT can reduce the computational costs dramatically, albeit with noticeable reductions in accuracy. This work proposes approximating the phonon density of states via a relatively inexpensive DFTB supercell treatment of the phonon dispersion that is then corrected by shifting the individual phonon modes according to the difference between the DFT and DFTB phonon frequencies at the Γ-point. The acoustic modes are then computed at the DFT level from the elastic constants. In several small-molecule crystal test cases, this combined approach reproduces DFT thermochemistry with kJ/mol accuracy and 1-2 orders of magnitude less computational effort. Finally, this approach is applied to computing the free energy differences between the five crystal polymorphs of oxalyl dihydrazide.

Adventures in DFTB: Toward an Automatic Parameterization Scheme

As we push forward on understanding the fate of chemicals in the environment, we need a method that will allow for the simulation of the inherent heterogeneity. Density functional tight binding (DFTB) is a methodology that allows for a detailed electronic description and would be ideal for this problem. While many parameters can be derived directly from DFT, empirical parameters still exist in the confinement and repulsion potentials. In this manuscript, we examine these potentials and present solutions that will minimize the degree of empiricism. Our results show that it is possible to construct confinement potentials from examining the atomic radial wavefunctions. Moreover, we found that the heterogeneous repulsion potentials can be derived from using only homogeneous repulsion curves.

Density-functional tight-binding for phosphine-stabilized nanoscale gold clusters

We report a parameterization of the second-order density-functional tight-binding (DFTB2) method for the quantum chemical simulation of phosphine-ligated nanoscale gold clusters, metalloids, and gold surfaces. Our parameterization extends the previously released DFTB2 "auorg" parameter set by connecting it to the electronic parameter of phosphorus in the "mio" parameter set. Although this connection could technically simply be accomplished by creating only the required additional Au-P repulsive potential, we found that the Au 6p and P 3d virtual atomic orbital energy levels exert a strong influence on the overall performance of the combined parameter set. Our optimized parameters are validated against density functional theory (DFT) geometries, ligand binding and cluster isomerization energies, ligand dissociation potential energy curves, and molecular orbital energies for relevant phosphine-ligated Au n clusters (n = 2-70), as well as selected experimental X-ray structures from the Cambridge Structural Database. In addition, we validate DFTB simulated far-IR spectra for several phosphine- and thiolate-ligated gold clusters against experimental and DFT spectra. The transferability of the parameter set is evaluated using DFT and DFTB potential energy surfaces resulting from the chemisorption of a PH3 molecule on the gold (111) surface. To demonstrate the potential of the DFTB method for quantum chemical simulations of metalloid gold clusters that are challenging for traditional DFT calculations, we report the predicted molecular geometry, electronic structure, ligand binding energy, and IR spectrum of Au108S24(PPh3)16.

Refined metadynamics through canonical sampling using time-invariant bias potential: A study of polyalcohol dehydration in hot acidic solutions

We propose a canonical sampling method to refine metadynamics simulations a posteriori, where the hills obtained from metadynamics are used as a time-invariant bias potential. In this way, the statistical error in the computed reaction barriers is reduced by an efficient sampling of the collective variable space at the free energy level of interest. This simple approach could be useful particularly when two or more free energy barriers are to be compared among chemical reactions in different or competing conditions. The method was then applied to study the acid dependence of polyalcohol dehydration reactions in high-temperature aqueous solutions. It was found that the reaction proceeds consistently via an S_N 2 mechanism, whereby the free energy of protonation of the hydroxyl group created as an intermediate is affected significantly by the acidic species. Although demonstration is shown for a specific problem, the computational method suggested herein could be generally used for simulations of complex reactions in the condensed phase.

Electronic conductance and thermopower of single-molecule junctions of oligo(phenyleneethynylene) derivatives

We report the synthesis and the single-molecule transport properties of three new oligo(phenyleneethynylene) (OPE3) derivatives possessing terminal dihydrobenzo[b]thiophene (DHBT) anchoring groups and various core substituents (phenylene, 2,5-dimethoxyphenylene and 9,10-anthracenyl). Their electronic conductance and their Seebeck coefficient have been determined using scanning tunneling microscopy-based break junction (STM-BJ) experiments between gold electrodes. The transport properties of the molecular junctions have been modelled using DFT-based computational methods which reveal a specific binding of the sulfur atom of the DHBT anchor to the electrodes. The experimentally determined Seebeck coefficient varies between -7.9 and -11.4 μV K^-1 in the series and the negative sign is consistent with charge transport through the LUMO levels of the molecules.

SARS-CoV-2 Virion Stabilization by Zn Binding

Zinc plays a crucial role in the process of virion maturation inside the host cell. The accessory Cys-rich proteins expressed in SARS-CoV-2 by genes ORF7a and ORF8 are likely involved in zinc binding and in interactions with cellular antigens activated by extensive disulfide bonds. In this report we provide a proof of concept for the feasibility of a structural study of orf7a and orf8 proteins. A conceivable hypothesis is that lack of cellular zinc, or substitution thereof, might lead to a significant slowing down of viral maturation.

An Atomistic Study of the Stress Corrosion Cracking in Graphene

Using molecular dynamics (MD) simulations, we study the mechanism of stress corrosion cracking in graphene. Two sets of modelings are conducted. In the first one, large graphene sheets with cracks in the armchair and zigzag directions are exposed to oxygen molecules. The crack growth as a result of chemical reactions between carbon radicals and oxygen molecules at different mechanical tensile stress levels is studied. In the second set of simulations, MD simulations are combined with the density functional-based tight bonding method to enhance the accuracy. This set of modelings focuses on a smaller zone in the vicinity of the crack tip. The impact of initial crack orientation on corrosion is studied by investigating corrosion of cracks in both armchair and zigzag directions. We investigate the subcritical crack propagation occurring as a result of the combined effects of both mechanical loading and chemical reactions. Our results show that cracks in graphene can grow due to chemical reactions with the environmental molecules. The MD modelings also predict that reaction of carbon atoms with oxygen molecules might lead to a stress relaxation at the crack tip, hence preventing further crack propagation. The results show that subcritical crack growth can happen by two mechanisms, which include the failure of C-C bonds or by removing the carbon atoms from graphene sheets in the form of CO or CO₂ molecules.

Accurate Many-Body Repulsive Potentials for Density-Functional Tight Binding from Deep Tensor Neural Networks

We combine density-functional tight binding (DFTB) with deep tensor neural networks (DTNN) to maximize the strengths of both approaches in predicting structural, energetic, and vibrational molecular properties. The DTNN is used to construct a nonlinear model for the localized many-body interatomic repulsive energy, which so far has been treated in an atom-pairwise manner in DFTB. Substantially improving upon standard DFTB and DTNN, the resulting DFTB-NN_rep model yields accurate predictions of atomization and isomerization energies, equilibrium geometries, vibrational frequencies, and dihedral rotation profiles for a large variety of organic molecules compared to the hybrid DFT-PBE0 functional. Our results highlight the potential of combining semiempirical electronic-structure methods with physically motivated machine learning approaches for predicting localized many-body interactions. We conclude by discussing future advancements of the DFTB-NN_rep approach that could enable chemically accurate electronic-structure calculations for systems with tens of thousands of atoms.

The CECAM electronic structure library and the modular software development paradigm

First-principles electronic structure calculations are now accessible to a very large community of users across many disciplines, thanks to many successful software packages, some of which are described in this special issue. The traditional coding paradigm for such packages is monolithic, i.e., regardless of how modular its internal structure may be, the code is built independently from others, essentially from the compiler up, possibly with the exception of linear-algebra and message-passing libraries. This model has endured and been quite successful for decades. The successful evolution of the electronic structure methodology itself, however, has resulted in an increasing complexity and an ever longer list of features expected within all software packages, which implies a growing amount of replication between different packages, not only in the initial coding but, more importantly, every time a code needs to be re-engineered to adapt to the evolution of computer hardware architecture. The Electronic Structure Library (ESL) was initiated by CECAM (the European Centre for Atomic and Molecular Calculations) to catalyze a paradigm shift away from the monolithic model and promote modularization, with the ambition to extract common tasks from electronic structure codes and redesign them as open-source libraries available to everybody. Such libraries include "heavy-duty" ones that have the potential for a high degree of parallelization and adaptation to novel hardware within them, thereby separating the sophisticated computer science aspects of performance optimization and re-engineering from the computational science done by, e.g., physicists and chemists when implementing new ideas. We envisage that this modular paradigm will improve overall coding efficiency and enable specialists (whether they be computer scientists or computational scientists) to use their skills more effectively and will lead to a more dynamic evolution of software in the community as well as lower barriers to entry for new developers. The model comes with new challenges, though. The building and compilation of a code based on many interdependent libraries (and their versions) is a much more complex task than that of a code delivered in a single self-contained package. Here, we describe the state of the ESL, the different libraries it now contains, the short- and mid-term plans for further libraries, and the way the new challenges are faced. The ESL is a community initiative into which several pre-existing codes and their developers have contributed with their software and efforts, from which several codes are already benefiting, and which remains open to the community.

Periodic DFT Calculations-Review of Applications in the Pharmaceutical Sciences

In the introduction to this review the complex chemistry of solid-state pharmaceutical compounds is summarized. It is also explained why the density functional theory (DFT) periodic calculations became recently so popular in studying the solid APIs (active pharmaceutical ingredients). Further, the most popular programs enabling DFT periodic calculations are presented and compared. Subsequently, on the large number of examples, the applications of such calculations in pharmaceutical sciences are discussed. The mentioned topics include, among others, validation of the experimentally obtained crystal structures and crystal structure prediction, insight into crystallization and solvation processes, development of new polymorph synthesis ways, and formulation techniques as well as application of the periodic DFT calculations in the drug analysis.

Graphenylene-based nanoribbons for novel molecular electronic devices

In the last decade, graphene has been frequently cited as one of the most promising materials for nanoelectronics. However, despite its outstanding mechanical and electronic properties, its use in the production of real nanoelectronic devices usually imposes some practical difficulties. This happens mainly due to the fact that, in its pristine form, graphene is a gapless material. We investigate theoretically the possibility of obtaining rectifying nanodevices using another carbon based two dimensional material, namely the graphenylene. This material has the advantage of being an intrinsic semiconductor, posing as a promising material for nanoelectronics. By doping graphenylene, one could obtain 2-dimensional p-n junctions, which can be useful for the construction of low dimensional electronic devices. We propose 2-dimensional diodes in which a clear rectification effect was demonstrated, with a conducting threshold of approximately 1.5 eV in direct bias and current blocking with opposite bias. During these investigations were found specific configurations that could result in devices with Zener-like behavior. Also, one unexpected effect was identified, which was the existence of transmission dips in electronic conductance plots. This result is discussed as a related feature to what was found in graphene nanoribbon systems under external magnetic fields, even though the external field was not a necessary ingredient to obtain such effect in the present case.