Lagrangian formulation with dissipation of Born-Oppenheimer molecular dynamics using the density-functional tight-binding method

CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published. They include the following: new faster simulation engines, accessible user interfaces for convenient workflows, and a vast array of simulation and analysis methods that encompass quantum mechanical, atomistic, and coarse-grained levels, as well as extensive coverage of force fields. In addition to providing the current snapshot of the CHARMM development, this review may serve as a starting point for exploring relevant theories and computational methods for tackling contemporary and emerging problems in biomolecular systems. CHARMM is freely available for academic and nonprofit research at https://academiccharmm.org/program.

Born-Oppenheimer Molecular Dynamics with a Linear Combination of Atomic Orbitals and Hybrid Functionals for Condensed Matter Simulations Made Possible. Theory and Performance for the Microcanonical and Canonical Ensembles

The implementation of an original Born-Oppenheimer molecular dynamics module is presented, which is able to perform simulations of large and complex condensed phase systems for sufficiently long time scales at the level of density functional theory with hybrid functionals, in the microcanonical (NVE) and canonical (NVT) ensembles. The algorithm is fully integrated in the Crystal code, a program for quantum mechanical simulations of materials, whose peculiarity stems from the use of atom-centered basis functions within a linear combination of atomic orbitals to describe the wave function. The corresponding efficiency in the evaluation of the exact Fock exchange series has led to the implementation of a rich variety of hybrid density functionals at a low computational cost. In addition, the molecular dynamics implementation benefits also from the effective MPI parallelization of the code, suited to exploit high-performance computing resources available on current generation supercomputer architectures. Furthermore, the information contained in the trajectory of the dynamics is extracted through a series of postprocessing algorithms that provide the radial distribution function, the diffusion coefficient and the vibrational density of states. In this work, we present a detailed description of the theoretical framework and the algorithmic implementation, followed by a critical evaluation of the accuracy and parallel performance (e.g., strong and weak scaling) of this approach, when ice and liquid water simulations are performed in the microcanonical and canonical ensembles.

Semi-Empirical Shadow Molecular Dynamics: A PyTorch Implementation

Extended Lagrangian Born-Oppenheimer molecular dynamics (XL-BOMD) in its most recent shadow potential energy version has been implemented in the semiempirical PyTorch-based software PySeQM. The implementation includes finite electronic temperatures, canonical density matrix perturbation theory, and an adaptive Krylov subspace approximation for the integration of the electronic equations of motion within the XL-BOMB approach (KSA-XL-BOMD). The PyTorch implementation leverages the use of GPU and machine learning hardware accelerators for the simulations. The new XL-BOMD formulation allows studying more challenging chemical systems with charge instabilities and low electronic energy gaps. The current public release of PySeQM continues our development of modular architecture for large-scale simulations employing semi-empirical quantum-mechanical treatment. Applied to molecular dynamics, simulation of 840 carbon atoms, one integration time step executes in 4 s on a single Nvidia RTX A6000 GPU.

Shadow energy functionals and potentials in Born-Oppenheimer molecular dynamics

In Born-Oppenheimer molecular dynamics (BOMD) simulations based on the density functional theory (DFT), the potential energy and the interatomic forces are calculated from an electronic ground state density that is determined by an iterative self-consistent field optimization procedure, which, in practice, never is fully converged. The calculated energies and forces are, therefore, only approximate, which may lead to an unphysical energy drift and instabilities. Here, we discuss an alternative shadow BOMD approach that is based on backward error analysis. Instead of calculating approximate solutions for an underlying exact regular Born-Oppenheimer potential, we do the opposite. Instead, we calculate the exact electron density, energies, and forces, but for an underlying approximate shadow Born-Oppenheimer potential energy surface. In this way, the calculated forces are conservative with respect to the approximate shadow potential and generate accurate molecular trajectories with long-term energy stabilities. We show how such shadow Born-Oppenheimer potentials can be constructed at different levels of accuracy as a function of the integration time step, δt, from the constrained minimization of a sequence of systematically improvable, but approximate, shadow energy density functionals. For each energy functional, there is a corresponding ground state Born-Oppenheimer potential. These pairs of shadow energy functionals and potentials are higher-level generalizations of the original "zeroth-level" shadow energy functionals and potentials used in extended Lagrangian BOMD [Niklasson, Eur. Phys. J. B 94, 164 (2021)]. The proposed shadow energy functionals and potentials are useful only within this extended dynamical framework, where also the electronic degrees of freedom are propagated as dynamical field variables together with the atomic positions and velocities. The theory is quite general and can be applied to MD simulations using approximate DFT, Hartree-Fock, or semi-empirical methods, as well as to coarse-grained flexible charge models.

Graph-based quantum response theory and shadow Born-Oppenheimer molecular dynamics

Graph-based linear scaling electronic structure theory for quantum-mechanical molecular dynamics simulations [A. M. N. Niklasson et al., J. Chem. Phys. 144, 234101 (2016)] is adapted to the most recent shadow potential formulations of extended Lagrangian Born-Oppenheimer molecular dynamics, including fractional molecular-orbital occupation numbers [A. M. N. Niklasson, J. Chem. Phys. 152, 104103 (2020) and A. M. N. Niklasson, Eur. Phys. J. B 94, 164 (2021)], which enables stable simulations of sensitive complex chemical systems with unsteady charge solutions. The proposed formulation includes a preconditioned Krylov subspace approximation for the integration of the extended electronic degrees of freedom, which requires quantum response calculations for electronic states with fractional occupation numbers. For the response calculations, we introduce a graph-based canonical quantum perturbation theory that can be performed with the same natural parallelism and linear scaling complexity as the graph-based electronic structure calculations for the unperturbed ground state. The proposed techniques are particularly well-suited for semi-empirical electronic structure theory, and the methods are demonstrated using self-consistent charge density-functional tight-binding theory both for the acceleration of self-consistent field calculations and for quantum-mechanical molecular dynamics simulations. Graph-based techniques combined with the semi-empirical theory enable stable simulations of large, complex chemical systems, including tens-of-thousands of atoms.

Multiscale Strategy for Predicting Radiation Chemistry in Polymers

A primary mode for radiation damage in polymers arises from ballistic electrons that induce electronic excitations, yet subsequent chemical mechanisms are poorly understood. We develop a multiscale strategy to predict this chemistry starting from subatomic scattering calculations. Nonadiabatic molecular dynamics simulations sample initial bond-breaking events following the most likely excitations, which feed into semiempirical simulations that approach chemical equilibrium. Application to polyethylene reveals a mechanism explaining the low propensity to cross-link in crystalline samples.

Polymer degradation through chemical change: a quantum-based test of inferred reactions in irradiated polydimethylsiloxane

Chemical reaction schemes are key conceptual tools for interpreting the results of experiments and simulations, but often carry implicit assumptions that remain largely unverified for complicated systems. Established schemes for chemical damage through crosslinking in irradiated silicone polymers comprised of polydimethylsiloxane (PDMS) date to the 1950's and correlate small-molecule off-gassing with specific crosslink features. In this regard, we use a somewhat reductionist model to develop a general conditional probability and correlation analysis approach that tests these types of causal connections between proposed experimental observables to reexamine this chemistry through quantum-based molecular dynamics (QMD) simulations. Analysis of the QMD simulations suggests that the established reaction schemes are qualitatively reasonable, but lack strong causal connections under a broad set of conditions that would enable making direct quantitative connections between off-gassing and crosslinking. Further assessment of the QMD data uncovers a strong (but nonideal) quantitative connection between exceptionally hard-to-measure chain scission events and the formation of silanol (Si-OH) groups. Our analysis indicates that conventional notions of radiation damage to PDMS should be further qualified and not necessarily used ad hoc. In addition, our efforts enable independent quantum-based tests that can inform confidence in assumed connections between experimental observables without the burden of fully elucidating entire reaction networks.

Quantum-Based Molecular Dynamics Simulations Using Tensor Cores

Tensor cores, along with tensor processing units, represent a new form of hardware acceleration specifically designed for deep neural network calculations in artificial intelligence applications. Tensor cores provide extraordinary computational speed and energy efficiency but with the caveat that they were designed for tensor contractions (matrix-matrix multiplications) using only low-precision floating-point operations. Despite this perceived limitation, we demonstrate how tensor cores can be applied with high efficiency to the challenging and numerically sensitive problem of quantum-based Born-Oppenheimer molecular dynamics, which requires highly accurate electronic structure optimizations and conservative force evaluations. The interatomic forces are calculated on-the-fly from an electronic structure that is obtained from a generalized deep neural network, where the computational structure naturally takes advantage of the exceptional processing power of the tensor cores and allows for high performance in excess of 100 Tflops on a single Nvidia A100 GPU. Stable molecular dynamics trajectories are generated using the framework of extended Lagrangian Born-Oppenheimer molecular dynamics, which combines computational efficiency with long-term stability, even when using approximate charge relaxations and force evaluations that are limited in accuracy by the numerically noisy conditions caused by the low-precision tensor core floating-point operations. A canonical ensemble simulation scheme is also presented, where the additional numerical noise in the calculated forces is absorbed into a Langevin-like dynamics.

Predicted Reaction Mechanisms, Product Speciation, Kinetics, and Detonation Properties of the Insensitive Explosive 2,6-Diamino-3,5-dinitropyrazine-1-oxide (LLM-105)

2,6-Diamino-3,5-dinitropyrazine-1-oxide (LLM-105) is a relatively new and promising insensitive high-explosive (IHE) material that remains only partially characterized. IHEs are of interest for a range of applications and from a fundamental science standpoint, as the root causes behind insensitivity are poorly understood. We adopt a multitheory approach based on reactive molecular dynamic simulations performed with density functional theory, density functional tight-binding, and reactive force fields to characterize the reaction pathways, product speciation, reaction kinetics, and detonation performance of LLM-105. We compare and contrast these predictions to 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), a prototypical IHE, and 1,3,5,7-tetranitro-1,3,5,7-tetrazoctane (HMX), a more sensitive and higher performance material. The combination of different predictive models allows access to processes operative on progressively longer timescales while providing benchmarks for assessing uncertainties in the predictions. We find that the early reaction pathways of LLM-105 decomposition are extremely similar to TATB; they involve intra- and intermolecular hydrogen transfer. Additionally, the detonation performance of LLM-105 falls between that of TATB and HMX. We find agreement between predictive models for first-step reaction pathways but significant differences in final product formations. Predictions of detonation performance result in a wide range of values, and one-step kinetic parameters show the similar reaction rates at high temperatures for three out of four models considered.

Extended Lagrangian Born-Oppenheimer molecular dynamics for orbital-free density-functional theory and polarizable charge equilibration models

Extended Lagrangian Born-Oppenheimer molecular dynamics (XL-BOMD) [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] is formulated for orbital-free Hohenberg-Kohn density-functional theory and for charge equilibration and polarizable force-field models that can be derived from the same orbital-free framework. The purpose is to introduce the most recent features of orbital-based XL-BOMD to molecular dynamics simulations based on charge equilibration and polarizable force-field models. These features include a metric tensor generalization of the extended harmonic potential, preconditioners, and the ability to use only a single Coulomb summation to determine the fully equilibrated charges and the interatomic forces in each time step for the shadow Born-Oppenheimer potential energy surface. The orbital-free formulation has a charge-dependent, short-range energy term that is separate from long-range Coulomb interactions. This enables local parameterizations of the short-range energy term, while the long-range electrostatic interactions can be treated separately. The theory is illustrated for molecular dynamics simulations of an atomistic system described by a charge equilibration model with periodic boundary conditions. The system of linear equations that determines the equilibrated charges and the forces is diagonal, and only a single Ewald summation is needed in each time step. The simulations exhibit the same features in accuracy, convergence, and stability as are expected from orbital-based XL-BOMD.

A Quantum-Based Approach to Predict Primary Radiation Damage in Polymeric Networks

Initial atomistic-level radiation damage in chemically reactive materials is thought to induce reaction cascades that can result in undesirable degradation of macroscale properties. Ensembles of quantum-based molecular dynamics (QMD) simulations can accurately predict these cascades, but extracting chemical insights from the many underlying trajectories is a labor-intensive process that can require substantial a priori intuition. We develop here a general and automated graph-based approach to extract all chemically distinct structures sampled in QMD simulations and apply our approach to predict primary radiation damage of polydimethylsiloxane (PDMS), the main constituent of silicones. A postprocessing protocol is developed to identify underlying polymer backbone structures as connected components in QMD trajectories. These backbones form a repository of radiation-damaged structures. A scheme for extracting and updating a library of isomorphically distinct structures is proposed to identify the spanning set and aid chemical interpretation of the repository. The analyses are applied to ensembles of cascade QMD simulations in which the four element types in PDMS are selectively excited in primary knock-on atom events. Our approach reveals a much higher degree of combinatorial complexity in this system than was inferred through radiolysis experiments. Probabilities are extracted for radiation-induced network changes including formation of branch points, carbon linkages, cycles, bond scissions, and carbon uptake into the Si-O siloxane backbone network. The general analysis framework presented here is readily extendable to modeling chemical degradation of other polymers and molecular materials and provides a basis for future quantum-informed multiscale modeling of radiation damage.

Mechanochemical synthesis of glycine oligomers in a virtual rotational diamond anvil cell

Mechanochemistry of glycine under compression and shear at room temperature is predicted using quantum-based molecular dynamics (QMD) and a simulation design based on rotational diamond anvil cell (RDAC) experiments. Ensembles of high throughput semiempirical density functional tight binding (DFTB) simulations are used to identify chemical trends and bounds for glycine chemistry during rapid shear under compressive loads of up to 15.6 GPa. Significant chemistry is found to occur during compressive shear above 10 GPa. Recovered products consist of small molecules such as water, structural analogs to glycine, heterocyclic molecules, large oligomers, and polypeptides including the simplest polypeptide glycylglycine at up to 4% mass fraction. The population and size of oligomers generally increases with pressure. A number of oligomeric polypeptide precursors and intermediates are also identified that consist of two or three glycine monomers linked together through C-C, C-N, and/or C-O bridges. Even larger oligomers also form that contain peptide C-N bonds and exhibit branched structures. Many of the product molecules exhibit one or more chiral centers. Our simulations demonstrate that athermal mechanical compressive shearing of glycine is a plausible prebiotic route to forming polypeptides.

Synthesis of functionalized nitrogen-containing polycyclic aromatic hydrocarbons and other prebiotic compounds in impacting glycine solutions

Proteinogenic amino acids can be produced on or delivered to a planet via impacting abiotic sources and consequently were likely present before the emergence of life on Earth. However, the role that these materials played in prebiotic scenarios remains an open question, in part because little is known about the survivability and reactivity of astrophysical organic compounds upon impact with a planetary surface. To this end, we use a force-matched semi-empirical quantum simulation method to study impacts of aqueous proteinogenic amino acids at conditions reaching 48 GPa and 3000 K. Here, we probe a relatively unstudied mechanism for prebiotic synthesis where sudden heating and pressurization causes condensation of complex carbon-rich structures from mixtures of glycine, the simplest protein-forming amino acid. These carbon-containing clusters are stable on short timescales and undergo a fundamental structural transition upon expansion and cooling from predominantly sp3-bonded tetrahedral-like moieties to those that are more sp2-bonded and planar. The recovered sp2-bonded structures include large nitrogen containing polycyclic aromatic hydrocarbons (NPAHs) with a number of different functional groups and embedded bonded regions akin to oligo-peptides. A number of small organic molecules with prebiotic relevance are also predicted to form. This work presents an alternate route to gas-phase synthesis for the formation of NPAHs of high complexity and highlights the significance of both the thermodynamic path and local chemical self-assembly in forming prebiotic species during shock synthesis. Our results help determine the role of comets and other celestial bodies in both the delivery and synthesis of potentially significant life building compounds on early Earth.

Parallel replica dynamics simulations of reactions in shock compressed liquid benzene

The study of the long-term evolution of slow chemical reactions is challenging because quantum-based reactive molecular dynamics simulation times are typically limited to hundreds of picoseconds. Here, the extended Lagrangian Born-Oppenheimer molecular dynamics formalism is used in conjunction with parallel replica dynamics to obtain an accurate tool to describe the long-term chemical dynamics of shock-compressed benzene. Langevin dynamics has been employed at different temperatures to calculate the first reaction times in liquid benzene at pressures and temperatures consistent with its unreacted Hugoniot. Our coupled engine runs for times on the order of nanoseconds (one to two orders of magnitude longer than traditional techniques) and is capable of detecting reactions that are characterized by rates significantly slower than we could study before. At lower pressures and temperatures, we mainly observe Diels-Alder metastable reactions, whereas at higher pressures and temperatures we observe stable polymerization reactions.

Effects of pressure on the structure and lattice dynamics of α-glycine: a combined experimental and theoretical study

This concomitant experimental and theoretical study provides a definitive EOS for α-glycine up to the record pressure of 50 GPa.

Chemical Degradation Pathways in Siloxane Polymers Following Phenyl Excitations

We use ensembles of quantum-based molecular dynamics simulations to predict the chemical reactions that follow radiation-induced excitations of phenyl groups in a model copolymer of polydimethylsiloxane and polydiphenylsiloxane. Our simulations span a wide range of highly porous and condensed phase densities and include both wet and dry conditions. We observe that in the absence of water, excited phenyl groups tend to abstract hydrogen from other methyl or phenyl side groups to produce benzene, with the under-hydrogenated group initiating subsequent intrachain cyclization reactions. These systems also yield minor products of diphenyl moieties formed by the complete abstraction of both phenyl groups from a single polydiphenylsiloxane subunit. In contrast, we find that the presence of water promotes the formation of free benzene and silanol side groups, reduces the likelihood for intrachain cyclization reactions, and completely suppresses the formation of diphenyl species. In addition, we predict that water plays a critical role in chain scission reactions, which indicates a possible synergistic effect between environmental moisture and radiation that could promote alterations of a larger polymer network. These results could have impact in interpreting accelerated aging experiments, where polymer decomposition reactions and network rearrangements are thought to have a significant effect on the ensuing mechanical properties.

Origins of the Mechanochemical Coupling of Peptide Bond Formation to Protein Synthesis

Mechanical forces acting on the ribosome can alter the speed of protein synthesis, indicating that mechanochemistry can contribute to translation control of gene expression. The naturally occurring sources of these mechanical forces, the mechanism by which they are transmitted 10 nm to the ribosome's catalytic core, and how they influence peptide bond formation rates are largely unknown. Here, we identify a new source of mechanical force acting on the ribosome by using in situ experimental measurements of changes in nascent-chain extension in the exit tunnel in conjunction with all-atom and coarse-grained computer simulations. We demonstrate that when the number of residues composing a nascent chain increases, its unstructured segments outside the ribosome exit tunnel generate piconewtons of force that are fully transmitted to the ribosome's P-site. The route of force transmission is shown to be through the nascent polypetide's backbone, not through the wall of the ribosome's exit tunnel. Utilizing quantum mechanical calculations we find that a consequence of such a pulling force is to decrease the transition state free energy barrier to peptide bond formation, indicating that the elongation of a nascent chain can accelerate translation. Since nascent protein segments can start out as largely unfolded structural ensembles, these results suggest a pulling force is present during protein synthesis that can modulate translation speed. The mechanism of force transmission we have identified and its consequences for peptide bond formation should be relevant regardless of the source of the pulling force.

Generating Converged Accurate Free Energy Surfaces for Chemical Reactions with a Force-Matched Semiempirical Model

We demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using density functional theory (DFT) is a highly accurate approach to generate free energy surfaces for chemical reactions, but the extreme computational cost often limits the time scales and range of thermodynamic states that can feasibly be studied. In contrast, DFTB is a semiempirical quantum method that affords up to a thousandfold reduction in cost and can recover DFT-level accuracy. Here, we show that a force-matched DFTB model for aqueous glycine condensation reactions yields free energy surfaces that are consistent with experimental observations of reaction energetics. Convergence analysis reveals that multiple nanoseconds of combined trajectory are needed to reach a steady-fluctuating free energy estimate for glycine condensation. Predictive accuracy of force-matched DFTB is demonstrated by direct comparison to DFT, with the two approaches yielding surfaces with large regions that differ by only a few kcal mol^-1.

Acceleration of Semiempirical QM/MM Methods through Message Passage Interface (MPI), Hybrid MPI/Open Multiprocessing, and Self-Consistent Field Accelerator Implementations

The strategy and implementation of scalable and efficient semiempirical (SE) QM/MM methods in CHARMM are described. The serial version of the code was first profiled to identify routines that required parallelization. Afterward, the code was parallelized and accelerated with three approaches. The first approach was the parallelization of the entire QM/MM routines, including the Fock matrix diagonalization routines, using the CHARMM message passage interface (MPI) machinery. In the second approach, two different self-consistent field (SCF) energy convergence accelerators were implemented using density and Fock matrices as targets for their extrapolations in the SCF procedure. In the third approach, the entire QM/MM and MM energy routines were accelerated by implementing the hybrid MPI/open multiprocessing (OpenMP) model in which both the task- and loop-level parallelization strategies were adopted to balance loads between different OpenMP threads. The present implementation was tested on two solvated enzyme systems (including <100 QM atoms) and an S_N2 symmetric reaction in water. The MPI version exceeded existing SE QM methods in CHARMM, which include the SCC-DFTB and SQUANTUM methods, by at least 4-fold. The use of SCF convergence accelerators further accelerated the code by ∼12-35% depending on the size of the QM region and the number of CPU cores used. Although the MPI version displayed good scalability, the performance was diminished for large numbers of MPI processes due to the overhead associated with MPI communications between nodes. This issue was partially overcome by the hybrid MPI/OpenMP approach which displayed a better scalability for a larger number of CPU cores (up to 64 CPUs in the tested systems).

On the existence of the optimal order for wavefunction extrapolation in Born-Oppenheimer molecular dynamics

Wavefunction extrapolation greatly reduces the number of self-consistent field (SCF) iterations and thus the overall computational cost of Born-Oppenheimer molecular dynamics (BOMD) that is based on the Kohn-Sham density functional theory. Going against the intuition that the higher order of extrapolation possesses a better accuracy, we demonstrate, from both theoretical and numerical perspectives, that the extrapolation accuracy firstly increases and then decreases with respect to the order, and an optimal extrapolation order in terms of minimal number of SCF iterations always exists. We also prove that the optimal order tends to be larger when using larger MD time steps or more strict SCF convergence criteria. By example BOMD simulations of a solid copper system, we show that the optimal extrapolation order covers a broad range when varying the MD time step or the SCF convergence criterion. Therefore, we suggest the necessity for BOMD simulation packages to open the user interface and to provide more choices on the extrapolation order. Another factor that may influence the extrapolation accuracy is the alignment scheme that eliminates the discontinuity in the wavefunctions with respect to the atomic or cell variables. We prove the equivalence between the two existing schemes, thus the implementation of either of them does not lead to essential difference in the extrapolation accuracy.

Quantum ring-polymer contraction method: Including nuclear quantum effects at no additional computational cost in comparison to ab initio molecular dynamics

We present a simple and accurate computational method which facilitates ab initio path-integral molecular dynamics simulations, where the quantum-mechanical nature of the nuclei is explicitly taken into account, at essentially no additional computational cost in comparison to the corresponding calculation using classical nuclei. The predictive power of the proposed quantum ring-polymer contraction method is demonstrated by computing various static and dynamic properties of liquid water at ambient conditions using density functional theory. This development will enable routine inclusion of nuclear quantum effects in ab initio molecular dynamics simulations of condensed-phase systems.

New QM/MM implementation of the DFTB3 method in the gromacs package

The approximate density-functional tight-binding theory method DFTB3 has been implemented in the quantum mechanics/molecular mechanics (QM/MM) framework of the Gromacs molecular simulation package. We show that the efficient smooth particle-mesh Ewald implementation of Gromacs extends to the calculation of QM/MM electrostatic interactions. Further, we make use of the various free-energy functionalities provided by Gromacs and the PLUMED plugin. We exploit the versatility and performance of the current framework in three typical applications of QM/MM methods to solve biophysical problems: (i) ultrafast proton transfer in malonaldehyde, (ii) conformation of the alanine dipeptide, and (iii) electron-induced repair of a DNA lesion. Also discussed is the further development of the framework, regarding mostly the options for parallelization.

Extended Lagrangian Born-Oppenheimer molecular dynamics simulations of the shock-induced chemistry of phenylacetylene

The initial chemical events that occur during the shock compression of liquid phenylacetylene have been investigated using self-consistent tight binding molecular dynamics simulations. The extended Lagrangian Born-Oppenheimer molecular dynamics formalism enabled us to compute microcanonical trajectories with precise conservation of the total energy. Our simulations revealed that the first density-increasing step under shock compression arises from the polymerization of phenylacetylene molecules at the acetylene moiety. The application of electronic structure-based molecular dynamics with long-term conservation of the total energy enabled us to identify electronic signatures of reactivity via monitoring changes in the HOMO-LUMO gap, and to capture directly adiabatic shock heating, transient non-equilibrium states, and changes in temperature arising from exothermic chemistry in classical molecular dynamics trajectories.

Thermostating extended Lagrangian Born-Oppenheimer molecular dynamics

Extended Lagrangian Born-Oppenheimer molecular dynamics is developed and analyzed for applications in canonical (NVT) simulations. Three different approaches are considered: the Nosé and Andersen thermostats and Langevin dynamics. We have tested the temperature distribution under different conditions of self-consistent field (SCF) convergence and time step and compared the results to analytical predictions. We find that the simulations based on the extended Lagrangian Born-Oppenheimer framework provide accurate canonical distributions even under approximate SCF convergence, often requiring only a single diagonalization per time step, whereas regular Born-Oppenheimer formulations exhibit unphysical fluctuations unless a sufficiently high degree of convergence is reached at each time step. The thermostated extended Lagrangian framework thus offers an accurate approach to sample processes in the canonical ensemble at a fraction of the computational cost of regular Born-Oppenheimer molecular dynamics simulations.

Generalized extended Lagrangian Born-Oppenheimer molecular dynamics

Extended Lagrangian Born-Oppenheimer molecular dynamics based on Kohn-Sham density functional theory is generalized in the limit of vanishing self-consistent field optimization prior to the force evaluations. The equations of motion are derived directly from the extended Lagrangian under the condition of an adiabatic separation between the nuclear and the electronic degrees of freedom. We show how this separation is automatically fulfilled and system independent. The generalized equations of motion require only one diagonalization per time step and are applicable to a broader range of materials with improved accuracy and stability compared to previous formulations.

Acceleration of Ab Initio QM/MM Calculations under Periodic Boundary Conditions by Multiscale and Multiple Time Step Approaches

Development of multiscale ab initio quantum mechanical and molecular mechanical (AI-QM/MM) method for periodic boundary molecular dynamics (MD) simulations and their acceleration by multiple time step approach are described. The developed method achieves accuracy and efficiency by integrating the AI-QM/MM level of theory and the previously developed semiempirical (SE) QM/MM-Ewald sum method [J. Chem. Theory Comput. 2005, 1, 2] extended to the smooth particle-mesh Ewald (PME) summation method. In the developed methods, the total energy of the simulated system is evaluated at the SE-QM/MM-PME level of theory to include long-range QM/MM electrostatic interactions, which is then corrected on the fly using the AI-QM/MM level of theory within the real space cutoff. The resulting energy expression enables decomposition of total forces applied to each atom into forces determined at the low-level SE-QM/MM method and correction forces at the AI-QM/MM level, to integrate the system using the reversible reference system propagator algorithm. The resulting method achieves a substantial speed-up of the entire calculation by minimizing the number of time-consuming energy and gradient evaluations at the AI-QM/MM level. Test calculations show that the developed multiple time step AI-QM/MM method yields MD trajectories and potential of mean force profiles comparable to single time step QM/MM results. The developed method, together with message passing interface (MPI) parallelization, accelerates the present AI-QM/MM MD simulations about 30-fold relative to the speed of single-core AI-QM/MM simulations for the molecular systems tested in the present work, making the method less than one order slower than the SE-QM/MM methods under periodic boundary conditions.

A density functional tight binding model with an extended basis set and three-body repulsion for hydrogen under extreme thermodynamic conditions

We present a new DFTB-p3b density functional tight binding model for hydrogen at extremely high pressures and temperatures, which includes a polarizable basis set (p) and a three-body environmentally dependent repulsive potential (3b). We find that use of an extended basis set is necessary under dissociated liquid conditions to account for the substantial p-orbital character of the electronic states around the Fermi energy. The repulsive energy is determined through comparison to cold curve pressures computed from density functional theory (DFT) for the hexagonal close-packed solid, as well as pressures from thermally equilibrated DFT-MD simulations of the liquid phase. In particular, we observe improved agreement in our DFTB-p3b model with previous theoretical and experimental results for the shock Hugoniot of hydrogen up to 100 GPa and 25000 K, compared to a standard DFTB model using pairwise interactions and an s-orbital basis set, only. The DFTB-p3b approach discussed here provides a general method to extend the DFTB method for a wide variety of materials over a significantly larger range of thermodynamic conditions than previously possible.

Floating orbital molecular dynamics simulations

We introduce an alternative ab initio molecular dynamics simulation as a unification of Hartree-Fock molecular dynamics and the floating orbital approach. The general scheme of the floating orbital molecular dynamics method is presented. Moreover, a simple but sophisticated guess for the orbital centers is provided to reduce the number of electronic structure optimization steps at each molecular dynamics step. The conservation of total energy and angular momentum is investigated in order to validate the floating orbital molecular dynamics approach with and without application of the initial guess. Finally, a water monomer and a water dimer are simulated, and the influence of the orbital floating on certain properties like the dipole moment is investigated.

Prebiotic chemistry within a simple impacting icy mixture

We present results of prebiotic organic synthesis in shock compressed mixtures of simple ices from quantum molecular dynamics (MD) simulations extended to close to equilibrium time scales. Given the likelihood of an inhospitable prebiotic atmosphere on early Earth, it is possible that impact processes of comets or other icy bodies were a source of prebiotic chemical compounds on the primitive planet. We observe that moderate shock pressures and temperatures within a CO2-rich icy mixture (36 GPa and 2800 K) produce a number of nitrogen containing heterocycles, which dissociate to form functionalized aromatic hydrocarbons upon expansion and cooling to ambient conditions. In contrast, higher shock conditions (48-60 GPa, 3700-4800 K) resulted in the synthesis of long carbon-chain molecules, CH4, and formaldehyde. All shock compression simulations at these conditions have produced significant quantities of simple C-N bonded compounds such as HCN, HNC, and HNCO upon expansion and cooling to ambient conditions. Our results elucidate a mechanism for impact synthesis of prebiotic molecules at realistic impact conditions that is independent of external constraints such as the presence of a catalyst, illuminating UV radiation, or pre-existing conditions on a planet.