Amber free energy tools: Interoperable software for free energy simulations using generalized quantum mechanical/molecular mechanical and machine learning potentials.

We report the development and testing of new integrated cyberinfrastructure for performing free energy simulations with generalized hybrid quantum mechanical/molecular mechanical (QM/MM) and machine learning potentials (MLPs) in Amber. The Sander molecular dynamics program has been extended to leverage fast, density-functional tight-binding models implemented in the DFTB+ and xTB packages, and an interface to the DeePMD-kit software enables the use of MLPs. The software is integrated through application program interfaces that circumvent the need to perform "system calls" and enable the incorporation of long-range Ewald electrostatics into the external software's self-consistent field procedure. The infrastructure provides access to QM/MM models that may serve as the foundation for QM/MM-ΔMLP potentials, which supplement the semiempirical QM/MM model with a MLP correction trained to reproduce ab initio QM/MM energies and forces. Efficient optimization of minimum free energy pathways is enabled through a new surface-accelerated finite-temperature string method implemented in the FE-ToolKit package. Furthermore, we interfaced Sander with the i-PI software by implementing the socket communication protocol used in the i-PI client-server model. The new interface with i-PI allows for the treatment of nuclear quantum effects with semiempirical QM/MM-ΔMLP models. The modular interoperable software is demonstrated on proton transfer reactions in guanine-thymine mispairs in a B-form deoxyribonucleic acid helix. The current work represents a considerable advance in the development of modular software for performing free energy simulations of chemical reactions that are important in a wide range of applications.

libMBD: A general-purpose package for scalable quantum many-body dispersion calculations.

Many-body dispersion (MBD) is a powerful framework to treat van der Waals (vdW) dispersion interactions in density-functional theory and related atomistic modeling methods. Several independent implementations of MBD with varying degree of functionality exist across a number of electronic structure codes, which both limits the current users of those codes and complicates dissemination of new variants of MBD. Here, we develop and document libMBD, a library implementation of MBD that is functionally complete, efficient, easy to integrate with any electronic structure code, and already integrated in FHI-aims, DFTB+, VASP, Q-Chem, CASTEP, and Quantum ESPRESSO. libMBD is written in modern Fortran with bindings to C and Python, uses MPI/ScaLAPACK for parallelization, and implements MBD for both finite and periodic systems, with analytical gradients with respect to all input parameters. The computational cost has asymptotic cubic scaling with system size, and evaluation of gradients only changes the prefactor of the scaling law, with libMBD exhibiting strong scaling up to 256 processor cores. Other MBD properties beyond energy and gradients can be calculated with libMBD, such as the charge-density polarization, first-order Coulomb correction, the dielectric function, or the order-by-order expansion of the energy in the dipole interaction. Calculations on supramolecular complexes with MBD-corrected electronic structure methods and a meta-review of previous applications of MBD demonstrate the broad applicability of the libMBD package to treat vdW interactions.

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.

Machine Learning Enhanced DFTB Method for Periodic Systems: Learning from Electronic Density of States.

Density functional tight binding (DFTB) is an approximate density functional based quantum chemical simulation method with low computational cost. In order to increase its accuracy, we have introduced a machine learning algorithm to optimize several parameters of the DFTB method, concentrating on solids with defects. The backpropagation algorithm was used to reduce the error between DFTB and DFT results with respect to the training data set and to obtain adjusted DFTB Hamiltonian and overlap matrix elements. Afterward, the generalization capability of the trained model was tested for geometries not being part of the training set. In the current work, we have focused on defective periodic silicon and silicon carbide systems as target materials and the density of states (DOS) as target property to demonstrate the feasibility of our approach. The trained model was able to reduce the differences between the DFTB and DFT DOS significantly, while other derived properties (for example, Mulliken population distribution, projected DOS) remained physically sound. Also, the transferability of the obtained model could be verified. Our method allows to carry out relatively fast simulations with high accuracy and only moderate training efforts, and represents a good compromise for cases, where long-range effects make direct machine learning predictions difficult.

Accelerating the density-functional tight-binding method using graphical processing units.

Acceleration of the density-functional tight-binding (DFTB) method on single and multiple graphical processing units (GPUs) was accomplished using the MAGMA linear algebra library. Two major computational bottlenecks of DFTB ground-state calculations were addressed in our implementation: the Hamiltonian matrix diagonalization and the density matrix construction. The code was implemented and benchmarked on two different computer systems: (1) the SUMMIT IBM Power9 supercomputer at the Oak Ridge National Laboratory Leadership Computing Facility with 1-6 NVIDIA Volta V100 GPUs per computer node and (2) an in-house Intel Xeon computer with 1-2 NVIDIA Tesla P100 GPUs. The performance and parallel scalability were measured for three molecular models of 1-, 2-, and 3-dimensional chemical systems, represented by carbon nanotubes, covalent organic frameworks, and water clusters.

DFT exchange: sharing perspectives on the workhorse of quantum chemistry and materials science.

In this paper, the history, present status, and future of density-functional theory (DFT) is informally reviewed and discussed by 70 workers in the field, including molecular scientists, materials scientists, method developers and practitioners. The format of the paper is that of a roundtable discussion, in which the participants express and exchange views on DFT in the form of 302 individual contributions, formulated as responses to a preset list of 26 questions. Supported by a bibliography of 777 entries, the paper represents a broad snapshot of DFT, anno 2022.

Obtaining Electronic Properties of Molecules through Combining Density Functional Tight Binding with Machine Learning.

We have introduced a machine learning workflow that allows for optimizing electronic properties in the density functional tight binding method (DFTB). The workflow allows for the optimization of electronic properties by generating two-center integrals, either by training basis function parameters directly or by training a spline model for the diatomic integrals, which are then used to build the Hamiltonian and the overlap matrices. Using our workflow, we have managed to obtain improved electronic properties, such as charge distributions, dipole moments, and approximated polarizabilities. While both machine learning approaches enabled us to improve on the electronic properties of the molecules as compared with existing DFTB parametrizations, only by training on the basis function parameters we were able to obtain consistent Hamiltonians and overlap matrices in the physically reasonable ranges or to improve on multiple electronic properties simultaneously.

Dynamical evolution of the Schottky barrier as a determinant contribution to electron-hole pair stabilization and photocatalysis of plasmon-induced hot carriers.

The harnessing of plasmon-induced hot carriers promises to open new avenues for the development of clean energies and chemical catalysis. The extraction of carriers before thermalization and recombination is of fundamental importance to obtain appealing conversion yields. Here, hot carrier injection in the paradigmatic Au-TiO2 system is studied by means of electronic and electron-ion dynamics. Our results show that pure electronic features (without considering many-body interactions or dissipation to the environment) contribute to the electron-hole separation stability. These results reveal the existence of a dynamic contribution to the interfacial potential barrier (Schottky barrier) that arises at the charge injection pace, impeding electronic back transfer. Furthermore, we show that this charge separation stabilization provides the time needed for the charge to leak to capping molecules placed over the TiO2 surface triggering a coherent bond oscillation that will lead to a photocatalytic dissociation. We expect that our results will add new perspectives to the interpretation of the already detected long-lived hot carrier lifetimes and their catalytical effect, and concomitantly to their technological applications.

Density functional tight binding approach utilized to study X-ray-induced transitions in solid materials.

Intense X-ray pulses from free-electron lasers can trigger ultrafast electronic, structural and magnetic transitions in solid materials, within a material volume which can be precisely shaped through adjustment of X-ray beam parameters. This opens unique prospects for material processing with X rays. However, any fundamental and applicational studies are in need of computational tools, able to predict material response to X-ray radiation. Here we present a dedicated computational approach developed to study X-ray induced transitions in a broad range of solid materials, including those of high chemical complexity. The latter becomes possible due to the implementation of the versatile density functional tight binding code DFTB+ to follow band structure evolution in irradiated materials. The outstanding performance of the implementation is demonstrated with a comparative study of XUV induced graphitization in diamond.

Using DFTB to Model Photocatalytic Anatase-Rutile TiO2 Nanocrystalline Interfaces and Their Band Alignment.

Band alignment effects of anatase and rutile nanocrystals in TiO2 powders lead to electron-hole separation, increasing the photocatalytic efficiency of these powders. While size effects and types of possible alignments have been extensively studied, the effect of interface geometries of bonded nanocrystal structures on the alignment is poorly understood. To allow conclusive studies of a vast variety of bonded systems in different orientations, we have developed a new density functional tight-binding parameter set to properly describe quantum confinement in nanocrystals. By applying this set, we found a quantitative influence of the interface structure on the band alignment.

Semi-Automated Creation of Density Functional Tight Binding Models through Leveraging Chebyshev Polynomial-Based Force Fields.

Density functional tight binding (DFTB) is an attractive method for accelerated quantum simulations of condensed matter due to its enhanced computational efficiency over standard density functional theory (DFT) approaches. However, DFTB models can be challenging to determine for individual systems of interest, especially for metallic and interfacial systems where different bonding arrangements can lead to significant changes in electronic states. In this regard, we have created a rapid-screening approach for determining systematically improvable DFTB interaction potentials that can yield transferable models for a variety of conditions. Our method leverages a recent reactive molecular dynamics force field where many-body interactions are represented by linear combinations of Chebyshev polynomials. This allows for the efficient creation of multi-center representations with relative ease, requiring only a small investment in initial DFT calculations. We have focused our workflow on TiH2 as a model system and show that a relatively small training set based on unit-cell-sized calculations yields a model accurate for both bulk and surface properties. Our approach is easy to implement and can yield reliable DFTB models over a broad range of thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

Self-Consistent Potential Correction for Charged Periodic Systems.

Supercell models are often used to calculate the electronic structure of local deviations from the ideal periodicity in the bulk or on the surface of a crystal or in wires. When the defect or adsorbent is charged, a jellium counter charge is applied to maintain overall neutrality, but the interaction of the artificially repeated charges has to be corrected, both in the total energy and in the one-electron eigenvalues and eigenstates. This becomes paramount in slab or wire calculations, where the jellium counter charge may induce spurious states in the vacuum. We present here a self-consistent potential correction scheme and provide successful tests of it for bulk and slab calculations.

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.

A Real-Time Time-Dependent Density Functional Tight-Binding Implementation for Semiclassical Excited State Electron-Nuclear Dynamics and Pump-Probe Spectroscopy Simulations.

The increasing need to simulate the dynamics of photoexcited molecular systems and nanosystems in the subpicosecond regime demands new efficient tools able to describe the quantum nature of matter at a low computational cost. By combining the power of the approximate DFTB method with the semiclassical Ehrenfest method for nuclear-electron dynamics, we have achieved a real-time time-dependent DFTB (TD-DFTB) implementation that fits such requirements. In addition to enabling the study of nuclear motion effects in photoinduced charge transfer processes, our code adds novel features to the realm of static and time-resolved computational spectroscopies. In particular, the optical properties of periodic materials such as graphene nanoribbons or the use of corrections such as the "LDA+U" and "pseudo SIC" methods to improve the optical properties in some systems can now be handled at the TD-DFTB level. Moreover, the simulation of fully atomistic time-resolved transient absorption spectra and impulsive vibrational spectra can now be achieved within reasonable computing time, owing to the good performance of the implementation and a parallel simulation protocol. Its application to the study of UV/visible light-induced vibrational coherences in molecules is demonstrated and opens a new door into the mechanisms of nonequilibrium ultrafast phenomena in countless materials with relevant applications.

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.

Towards a simplified description of thermoelectric materials: accuracy of approximate density functional theory for phonon dispersions.

We calculate the phonon-dispersion relations of several two-dimensional materials and diamond using the density-functional based tight-binding approach (DFTB). Our goal is to verify if this numerically efficient method provides sufficiently accurate phonon frequencies and group velocities to compute reliable thermoelectric properties. To this end, the results are compared to available DFT results and experimental data. To quantify the accuracy for a given band, a descriptor is introduced that summarizes contributions to the lattice conductivity that are available already in the harmonic approximation. We find that the DFTB predictions depend strongly on the employed repulsive pair-potentials, which are an important prerequisite of this method. For carbon-based materials, accurate pair-potentials are identified and lead to errors of the descriptor that are of the same order as differences between different local and semi-local DFT approaches.

Simulation of Impulsive Vibrational Spectroscopy.

In the present work we applied a fully atomistic electron-nuclear real-time propagation protocol to compute the impulsive vibrational spectroscopy of the five DNA/RNA nucleobases in order to study the very first steps (subpicosecond) of their energy distribution after UV excitation. We observed that after the pump pulse absorption the system is prepared in a coherent superposition of the ground and the pumped electronic excited states in the equilibrium geometry of the ground state. Furthermore, for relatively low fluency values of the pump pulse, the dominant contribution to the electronic wave function of the coherent state is of the ground state and the mean potential energy surface within the Ehrenfest approximation is similar to that of the ground state. As a consequence, the molecular displacements are better correlated with ground-state normal modes. On the other hand, when the pump fluency is increased the excited-state contribution to the electronic wave function becomes more important and the mean potential energy surface resembles more that of the excited state, producing a better correlation between the molecular displacements and the excited-state normal modes. Finally, it has been observed that the impulsive activation of several vibrational modes upon electronic excitation is triggered by the development of excited-state forces which accelerate the nuclei from their equilibrium positions causing a distribution of the absorbed electronic energy on the nuclear degrees of freedom and could be closely related to the driving force of the ultrafast nonradiative deactivation observed in these systems.

Density functional tight binding-based free energy simulations in the DFTB+ program.

The timescale problem-in which high barriers on the free energy surface trap molecular dynamics simulations in local energy wells-is a key limitation of current reactive MD simulations based on the density functional tight binding (DFTB) potential. Here, we report a new interface between the DFTB+ software package and the PLUMED library for performing DFTB-based free energy calculations. We demonstrate the performance of this interface for 3 archetypal rare-event chemical reactions, (i) intramolecular proton transfer in malonaldehyde, (ii) bowl inversion in corannulene, and (iii) oxygen diffusion on graphene. Using third-order DFTB in conjunction with metadynamics (with/without multiple walkers) and well-tempered metadynamics, we report here free energies of activation (ΔG‡ ) of 13.1 ± 0.4, 48.2 ± 1.7, and 52.0 ± 6.2 kJ mol-1 , respectively, for these processes. In each case, our DFTB free energy barriers and local minima compare favorably with previous literature results, demonstrating the utility of the DFTB+ - PLUMED interface. © 2018 Wiley Periodicals, Inc.

Fully Atomistic Real-Time Simulations of Transient Absorption Spectroscopy.

We have implemented an electron-nuclear real-time propagation scheme for the calculation of transient absorption spectra. When this technique is applied to the study of ultrafast dynamics of Soret-excited zinc(II) tetraphenylporphyrin in the subpicosecond time scale, quantum beats in the transient absorption caused by impulsively excited molecular vibrations are observed. The launching mechanism of such vibrations can be regarded as a displacive excitation of the zinc-pyrrole and pyrrole C-C bonds.

Efficient Automatized Density-Functional Tight-Binding Parametrizations: Application to Group IV Elements.

Density-functional tight-binding methods stand out as a very good compromise between accuracy and computational efficiency. These methods rely on parameter sets that have to be determined and tabulated for every pair of chemical elements. We describe an efficient, and to a large extent automatic, procedure to build such parameter sets. This procedure includes the generation of unbiased training sets and subsequent optimization of the parameters using a pattern search method. As target for the optimization we ask that the formation energy and the forces on the atoms calculated within tight-binding reproduce the ones obtained using density-functional theory. We then use this approach to calculate parameter sets for group IV elements and their binaries. These turn out to yield substantially better results than previously available parameters, especially in what concerns energies and forces.