Quantum Mechanical Molecular Dynamics Simulations Research Articles

2-Halomethyleneoxetanes from 2-Methyleneoxetanes by Reaction with N-Halosuccinimides: Reactant Influences on Stereochemical Outcomes and Reaction Pathways.

The first general synthesis of 2-halomethyleneoxetanes, realized by the reaction of 2-methyleneoxetanes with N-halosuccinimides (NXS), is reported. The relative diastereoselectivities of the transformations were dependent on the halogen of NXS, while alternative reaction outcomes were influenced by substituents on the oxetane. Quantum mechanical calculations and molecular dynamics simulations exploring the basis of the observed diastereoselectivities are described. These highly strained heterocycles underwent standard cross-coupling reactions, demonstrating their utility as synthetic intermediates.

Efficient Mixed-Precision Matrix Factorization of the Inverse Overlap Matrix in Electronic Structure Calculations with AI-Hardware and GPUs.

In recent years, a new kind of accelerated hardware has gained popularity in the artificial intelligence (AI) community which enables extremely high-performance tensor contractions in reduced precision for deep neural network calculations. In this article, we exploit Nvidia Tensor cores, a prototypical example of such AI-hardware, to develop a mixed precision approach for computing a dense matrix factorization of the inverse overlap matrix in electronic structure theory, S-1. This factorization of S-1, written as ZZT = S-1, is used to transform the general matrix eigenvalue problem into a standard matrix eigenvalue problem. Here we present a mixed precision iterative refinement algorithm where Z is given recursively using matrix-matrix multiplications and can be computed with high performance on Tensor cores. To understand the performance and accuracy of Tensor cores, comparisons are made to GPU-only implementations in single and double precision. Additionally, we propose a nonparametric stopping criteria which is robust in the face of lower precision floating point operations. The algorithm is particularly useful when we have a good initial guess to Z, for example, from previous time steps in quantum-mechanical molecular dynamics simulations or from a previous iteration in a geometry optimization.

Rational Design of Non-Covalent Imprinted Polymers Based on the Combination of Molecular Dynamics Simulation and Quantum Mechanics Calculations.

Molecular imprinting is a promising approach for developing polymeric materials as artificial receptors. However, only a few types of molecularly imprinted polymers (MIPs) are commercially available, and most research on MIPS is still in the experimental phase. The significant limitation has been a challenge for screening imprinting systems, particularly for weak functional target molecules. Herein, a combined method of quantum mechanics (QM) computations and molecular dynamics (MD) simulations was employed to screen an appropriate 2,4-dichlorophenoxyacetic acid (2,4-D) imprinting system. QM calculations were performed using the Gaussian 09 software. MD simulations were conducted using the Gromacs2018.8 software suite. The QM computation results were consistent with those of the MD simulations. In the MD simulations, a realistic model of the 'actual' pre-polymerisation mixture was obtained by introducing numerous components in the simulations to thoroughly investigate all non-covalent interactions during imprinting. This study systematically examined MIP systems using computer simulations and established a theoretical prediction model for the affinity and selectivity of MIPs. The combined method of QM computations and MD simulations provides a robust foundation for the rational design of MIPs.

Consideration of the effect of nanoscale porosity on mass transport phenomena in PECVD coatings

Here we show a novel approach to characterize the gas transfer behavior of silicon-oxide (SiO x ) coatings and explain the underlying dynamics. For this, we investigate the coating on a nm-scale both by measurement and simulation. Positron annihilation spectroscopy (PAS) and quantum mechanical electronic structure-based molecular dynamics simulations are combined to characterize the porous landscape of SiO x coatings. This approach analyses the influence of micropores smaller than 2 nm in diameter on gas permeation which are difficult to study with conventional methods. We lay out the main pore diameter ranges and their associated porosity estimates. An influence of layer growth on pore size and porosity was found, with an increased energy input during layer deposition leading to smaller pore sizes and a reduced porosity. The molecular dynamics simulations quantify the self-diffusion of oxygen and water vapor through those PAS deducted micropore ranges for hydrophilic and hydrophobic systems. The theoretical pore size ranges are fitting to our PAS results and complete them by giving diffusion coefficients. This approach enables detailed analysis of pore morphology on mass transport through thin film coatings and characterization of their barrier or membrane performance. This is a crucial prerequisite for the development of an exhaustive model of pore dominated mass transports in PECVD coatings.

On the solubility of azodicarbonamide in water/DMSO mixtures: an experimental and computational study.

This work aims at studying why azodicarbonamide (ADCA), a formally apolar compound with good hydrogen bond (HB) acceptors, is soluble only in polar aprotic solvents like dimethyl sulfoxide (DMSO) but not in water. Solubility measurements, as well as quantum mechanical and classical molecular dynamics simulations, were employed to tackle the problem. We found that in the liquid phase a polar conformer of ADCA (µ = 8.7 D), unreported to date, is favoured under the enthalpic drive provided by a highly polar solvent. At the same time, the very high hydrogen bond propensity of water with itself prevents this solvent from providing an effective hydrogen bond-mediated solvation. Solvents bearing good HB acceptors, while lacking strong HB donors, contribute to further stabilizing solute-solvent adducts through weak and fluxional HBs that involve the amide groups of ADCA. Implications for the solubility of ADCA down to µM concentrations were evaluated, also with the aid of classical simulations of solution nanodroplets.

A Combined Experimental, DFT and Molecular Dynamics Simulation Study of Binary Mixture of Ethylbenzene and Aniline

AbstractDensity and viscosity values of the binary mixture of ethylbenzene and aniline have been experimentally measured in different mole fractions at temperatures of 293.15 to 313.15 K and at an absolute pressure of 86.7 kPa. Based on the obtained experimental data, the excess molar volume and viscosity deviations have been reported, which can interpret the interactions in this mixture. The obtained data were fitted with the Redlich‐Kister equation. In addition, the viscosity results are discussed using the equation proposed by Gruenberg‐Nissan. After experimental studies, in order to investigate the interactions of these two components and their mixture, quantum mechanical calculations and molecular dynamics simulation have been used. In this way, the structures of the desired molecules have been optimized. Then Atoms in Molecules (AIM) and frontier molecular orbital (FMO) techniques have been used for a more detailed investigation. Finally, by plotting radial distribution functions (RDFs) obtained from molecular dynamics, these interactions have been investigated in a more comprehensive way. In addition, the simulated densities at 298.15 K have been reported. At the end, clear pictures of the interactions of molecules in mixtures were obtained by comparing the achievements of experimental measurements, quantum chemical and calculations MD simulation.

Bayesian Mechanistic Inference, Statistical Mechanics, and a New Era for Monte Carlo.

On the one hand, much of computational chemistry is concerned with "bottom-up" calculations which elucidate observable behavior starting from exact or approximated physical laws, a paradigm exemplified by typical quantum mechanical calculations and molecular dynamics simulations. On the other hand, "top down" computations aiming to formulate mathematical models consistent with observed data, e.g., parametrizing force fields, binding or kinetic models, have been of interest for decades but recently have grown in sophistication with the use of Bayesian inference (BI). Standard BI provides an estimation of parameter values, uncertainties, and correlations among parameters. Used for "model selection," BI can also distinguish between model structures such as the presence or absence of individual states and transitions. Fortunately for physical scientists, BI can be formulated within a statistical mechanics framework, and indeed, BI has led to a resurgence of interest in Monte Carlo (MC) algorithms, many of which have been directly adapted from or inspired by physical strategies. Certain MC algorithms─notably procedures using an "infinite temperature" reference state─can be successful in a 5-20 parameter BI context which would be unworkable in molecular spaces of 103 coordinates and more. This Review provides a pedagogical introduction to BI and reviews key aspects of BI through a physical lens, setting the computations in terms of energy landscapes and free energy calculations and describing promising sampling algorithms. Statistical mechanics and basic probability theory also provide a reference for understanding intrinsic limitations of Bayesian inference with regard to model selection and the choice of priors.

An Update in Computational Methods for Environmental Monitoring: Theoretical Evaluation of the Molecular and Electronic Structures of Natural Pigment-Metal Complexes.

Metals are beneficial to life, but the presence of these elements in excessive amounts can harm both organisms and the environment; therefore, detecting the presence of metals is essential. Currently, metal detection methods employ powerful instrumental techniques that require a lot of time and money. Hence, the development of efficient and effective metal indicators is essential. Several synthetic metal detectors have been made, but due to their risk of harm, the use of natural pigments is considered a potential alternative. Experiments are needed for their development, but they are expensive and time-consuming. This review explores various computational methods and approaches that can be used to investigate metal-pigment interactions because choosing the right methods and approaches will affect the reliability of the results. The results show that quantum mechanical methods (ab initio, density functional theory, and semiempirical approaches) and molecular dynamics simulations have been used. Among the available methods, the density functional theory approach with the B3LYP functional and the LANL2DZ ECP and basis set is the most promising combination due to its good accuracy and cost-effectiveness. Various experimental studies were also in good agreement with the results of computational methods. However, deeper analysis still needs to be carried out to find the best combination of functions and basis sets.

QM/MM study of the catalytic reaction of aphid myrosinase

Brevicoryne brassicae, an aphid species, exclusively consumes plants from the Brassicaceae family and employs a sophisticated defense mechanism involving a myrosinase enzyme that breaks down glucosinolates obtained from its host plants. In this work, we employed combined quantum mechanical and molecular mechanical (QM/MM) calculations and molecular dynamics (MD) simulations to study the catalytic reaction of aphid myrosinase. A proper QM region to study the myrosinase reaction should contain the whole substrate, models of Gln-19, His-122, Asp-124, Asn-166, Glu-167, Lys-173, Tyr-180, Val-228, Tyr-309, Tyr-346, Ile-347, Glu-374, Glu-423, Trp-424, and a water molecule. The calculations show that Asp-124 and Glu-423 must be charged, His-122 must be protonated on NE2, and Glu-167 must be protonated on OE2. Our model reproduces the anomeric retaining characteristic of myrosinase and indicates that the deglycosylation reaction is the rate-determining step of the reaction. Based on the calculations, we propose a reaction mechanism for aphid myrosinase-mediated hydrolysis of glucosinolates with an overall barrier of 15.2 kcal/mol. According to the results, removing a proton from Arg-312 or altering it to valine or methionine increases glycosylation barriers but decreases the deglycosylation barrier.

Preparation of reed fibers reinforced graft-modified starch-based adhesives based on quantum mechanical simulation and molecular dynamics simulation

Starch is a biomass polymer material with a high yield and comprehensive source. It is used as a raw material for preparing adhesives because of its highly active hydroxyl group. However, poor adhesion and water resistance hinder the application of starch-based adhesives (SBAs). Based on this, the starch was modified through graft copolymerization with itaconic acid as a cross-linking agent, methyl methacrylate and methyl acrylate as copolymers. Additionally, reed fibers were synergistically modified with polydopamine deposition to prepare an environmentally friendly SBA used in plywood production. Fourier transform infrared spectroscopy (FT-IR), nuclear magnetic resonance spectroscopy (1H NMR), X-ray diffraction (XRD), and thermogravimetric analysis (TG) demonstrate that copolymerization of methyl methacrylate and methyl acrylate with starch improves the shear strength, water resistance, and thermal stability of the SBA. Compared to unmodified starch, the modified SBA exhibits a 129 % increase in dry strength and achieves a wet strength of 1.36 MPa. Fukui function, Frontier orbit theory, and molecular dynamics simulation have shown that itaconic acid promotes the copolymerization of starch and acrylate monomers. The modified starch has fewer hydrogen bonds, less order, and a denser macromolecular network structure, which provides a reference for studying the molecular interaction mechanisms of SBAs.

Modelling bulk and surface characteristics of cubic CeO2, Gd2O3, and gadolinium-doped ceria using a partial charge framework.

The development and characterization of materials for solid oxide fuel cells (SOFC) is an important step towards sustainable energy technologies. This present study models cubic CeO2, Gd2O3, and gadolinium-doped ceria (GDC) using newly constructed interaction potentials based on a partial atom charge framework. The interaction model was validated by comparing the structural properties with experimental reference data, which were found to be in good agreement. Validation of the potential model was conducted considering the surface stability of CeO2 and Gd2O3. Additionally, the accuracy of the novel potential model was assessed by comparing the oxygen diffusion coefficient in GDCn (n = 4-15) and the associated activation energy. The results demonstrate that the novel potential model is capable of describing the oxygen diffusion in GDC. In addition, this study compares the vibrational properties of the bulk with density functional theory (DFT) calculations, using a harmonic frequency analysis that avoids the need for computationally expensive quantum mechanical molecular dynamics (QM MD) simulations. The potential is compatible with a reactive water model, thus providing a framework for the simulation of solid-liquid interfaces.

A hybrid forces Quantum Mechanical Charge Field Molecular Dynamics of Cs+ ion in aqueous ammonia: A solvation lability, “structure breaking” phenomenon and hydrogen bond properties

AbstractThe dynamics and structure of Cs+ solvation in an aqueous ammonia solution have been investigated using the Quantum Mechanical Charge Field Molecular Dynamics (QMCF‐MD) simulation method. The system contained 18.6% ammonia in aqueous solution at 298.15 K. The QM region was set to a radius of 7.0 Å to include the first and second solvation shells. The Hartree‐Fock (HF) level was applied to calculate the ion‐ligand and ligand–ligand interactions in the QM region using the LANL2DZ‐ECP basis set for the ion and DZP‐Dunning for the ligands. The radial distribution revealed only one solvation shell, indicating a labile solvation structure. The various coordination number of ligands suggests an instant exchange between them. The mean residence times of 1.29 and 0.9 ps were less than in the pure water and liquid ammonia system, indicating higher mobility ligands of the aqueous ammonia system. The preferential factor 0.55 supports the hypothesis that the Cs+ ion prefers to be dissolved in water. As the ligands moves further away from the ion, the observed number of hydrogen bonds increases, revealing the “structure‐breaking” property of the Cs+ ion. The minimum angle ligand‐ion‐ligand tends to be higher near the ion, confirming this phenomenon.

Amino acid ionic liquids as efficient catalysts for CO2 capture: A combined static and dynamic approach

Amino acid ionic liquids (AAILs) have gained significant attention as green solvents that are biocompatible, biodegradable, and useful in various applications, including catalysts, absorbents, and solvents. This study investigates the detailed interactions of three amino acid anions (glycine [Gly]-, histidine [His]-, and arginine [Arg]-) with the cation 1-methoxylbutyl-3-methylimidazolium [MOBMIM]+ and their role in CO2 absorption using quantum mechanical calculations and molecular dynamics (MD) simulations. The Density Functional Theory (DFT) calculations elucidate the reaction mechanisms underlying CO2 absorption and cycloaddition, and facilitate a comparative analysis of the impact of different amino acids on these reactions, and the synergies between them. Notably, arginine displays superior CO2 absorption capacity in comparison to glycine and histidine. Additionally, the cycloaddition reaction with CO2 exhibits a lower energy barrier when arginine is involved. Insights from the MD simulations highlight the higher level of electrostatic interaction between [MOBMIM]+[Arg]- and CO2, relative to the other studied molecules. Moreover, the Lennard Jones interaction emerges as the dominant type of interaction in these systems. The diffusion coefficient for CO2 was highest when interacting with [MOBMIM]+[Gly]-, followed by [MOBMIM]+[Arg]-. Consequently, both MD and DFT investigations converge to suggest that [MOBMIM]+[Arg]- followed by [MOBMIM]+[Gly]- may serve as advantageous choices for CO2 fixation and cycloaddition. The findings from this study underscore the considerable potential of the investigated AAILs as materials conducive to CO2 capture and utilization, thus paving the way for the integration of CO2 capture into valuable chemical products.

Influence of soft segment structure, hydrogen bonding, and diisocyanate symmetry on morphology and properties of segmented thermoplastic polyurethanes and polyureas.

A comprehensive review of the structure-morphology-property relations in segmented thermoplastic polyurethanes and polyureas (TPU) is provided. Special emphasis is given to the influence of the soft segment structure, polarity, and molecular weight, diisocyanate symmetry and the nature, extent, and strength of hydrogen bonding on the morphology and thermal and mechanical properties of TPUs. Experimental results obtained on composition-dependent TPU morphology and properties by various techniques were also compared by the morphology profiles generated by computational methods such as quantum mechanical calculations and molecular dynamics simulations.

The solvation dynamics of CO2 by quantum mechanical molecular dynamics

The solvation dynamics of CO2 in an aqueous solution were investigated using quantum mechanical molecular mechanical molecular dynamics (QM/MM-MD) simulations. It is demonstrated that the formation of H2CO3 occurs through direct reactions between CO2 and nH2O, with extremely high activation barriers in the gas phase. However, in a solution, the activation energy decreases as the number of H2O molecules increases. Specifically, for the CO2 − H2O system, the activation energy is about 32 kcal/mol, while for the CO2 − 2H2O and CO2 − 3H2O systems, it decreases to 28 kcal/mol and 15 kcal/mol, respectively. These findings suggest that the solvation of CO2 in a solution favors a step-wise mechanism.

Unraveling pyrolysis mechanisms of lignin dimer model compounds: Neural network-based molecular dynamics simulation investigations

Unraveling the pyrolysis mechanisms of lignin is of great importance for effective lignin utilization. However, both conventional quantum mechanical method and molecular dynamics (MD) simulations based on empirical potentials, e.g., the ReaxFF, cannot guarantee simultaneous accuracy and efficiency in exploring lignin pyrolysis mechanisms. Here, we developed a neural network (NN) force field for four types of representative lignin dimers based on 56,164 structures at the level of density functional theory (DFT). Such NN model was demonstrated to possess more accurate predictive power in both energetic and atomistic force properties than ReaxFF and was far more efficient than QM method. The MD simulations with the NN model showed that entire pyrolysis process can be divided into three stages dependent on the reaction temperature: homolytic cleavage of C–C bond and C-O bond, the changes from methoxy group to hydroxy, methyl, and formyl group, ring-opening reactions and the ring structure evolutions, and some novel reactions. The NN-based MD has provided us an atomic-level understanding of lignin pyrolysis and enabled us to build a comprehensive lignin pyrolysis network by means of the reactions disclosed based on the NN-based MD, which provided a useful guide for taking advantage of lignin more effectively.

Origins of Periselectivity and Regioselectivity in Ambimodal Tripericyclic [8+6]/[6+4]/[4+2] Intramolecular Cycloadditions of a Heptafulvenyl-Fulvene.

Quantum mechanical calculations and molecular dynamics simulations have elucidated the reaction mechanism for intramolecular cycloadditions of a heptafulvenyl-fulvene tethered by a trimethylene chain. Prior experiments by Liu and Houk reported the formation of only an endo-[8+6] cycloadduct at 185 °C. Liu et al. later reported an exo-[4+2] Diels-Alder cycloadduct as the major product at 140 °C (Tetrahedron, 1999, 55, 9171). Cycloadditions involve Diels-Alder and an ambimodal intramolecular tripericyclic [8+6]/[6+4]/[4+2] cycloaddition. The mechanistic details explain the experimental reports of temperature dependence on the periselectivity of intramolecular cycloadditions. Additional calculations with multireference-based methods CASSCF and NEVPT2 highlight the artifacts of DFT methods and single-reference wavefunction-based CCSD(T) in the description of complete potential energy surface involving various cycloadditions of the heptafulvenyl-fulvene.

Origins of Conformational Heterogeneity in Peptoid Helices Formed by Chiral N-1-Phenylethyl Sidechains.

N-substituted glycines (polypeptoids) containing chiral hydrophobic sidechains are known to fold into biomimetic alpha helices. These helix formers often produce conformationally heterogeneous structures and are difficult to characterize at a sub-nanometer resolution. Previously, peptoid N-1-phenylethyl (S)-enantiomer sidechains (Nspe) were inferred from various experiments to form right-handed helices and (R)-enantiomers (Nrpe), left-handed helices. Prior computational work for N(s/r)pe oligomers has struggled to reproduce this trend. Herein, quantum mechanics calculations and molecular dynamics simulations are used to understand the origins of this discrepancy. Results from DFT and molecular mechanics calculations on a variety of Nspe and Nrpe oligomers as a function of chain length are in agreement, showing that Nspe and Nrpe prefer left- and right-handed helices, respectively. Additional metadynamics simulations are used to study Nrpe and Nspe oligomers folding in water. These results show that the free-energy driving forces for assembly into a helical backbone configuration are very small (within ∼kBT). Lastly, we compare DFT calculations for other experimentally characterized peptoid sidechains, N(r/s)sb, N(r/s)tbe, and N(r/s)npe. In this analysis, we show that peptoid sidechains determined to be more robust experimentally (tbe and npe) have helical preferences opposite the trend seen in less robust assemblies formed by N(r/s)pe and N(r/s)sb chemistries. The more robust tbe and nnpe favor the (S)-enantiomer to right-handed and the (R)-enantiomers to left-handed helices.

Growth Mechanism and Kinetics of Diamond in Liquid Gallium from Quantum Mechanics Molecular Dynamics Simulations.

Ruoff and co-workers recently demonstrated low-temperature (1193 K) homoepitaxial diamond growth from liquid gallium solvent. To develop an atomistic mechanism for diamond growth underlying this remarkable demonstration, we carried out density functional theory-based molecular dynamics (DFT-MD) simulations to examine the mechanism of single-crystal diamond growth on various low-index crystallographic diamond surfaces (100), (110), and (111) in liquid Ga with CH4. We find that carbon linear chains form in liquid Ga and then react with the growing diamond surface, leading first to the formation of carbon rings on the surface and then initiation of diamond growth. Our simulations find faster growth on the (110) surface than on the (100) or (111) surfaces, suggesting the (110) surface as a plausible growth surface in liquid Ga. For (110) surface growth, we predict the optimum growth temperature to be ∼1300 K, arising from a balance between the kinetics of forming carbon chains dissolved in Ga and the stability of carbon rings on the growing surface. We find that the rate-determining step for diamond growth is dehydrogenation of the growing hydrogenated (110) surface of diamond. Inspired by the recent experimental studies by Ruoff and co-workers demonstrating that Si accelerates diamond growth in Ga, we show that addition of Si into liquid Ga significantly increases the rate of dehydrogenating the growing surface. Extrapolating from the DFT-MD predicted rates at 2800 to 3500 K, we predict the growth rate at the experimental growth temperature of 1193 K, leading to rates in reasonable agreement with the experiment. These fundamental mechanisms should provide guidance in optimizing low-temperature diamond growth.

Catalytic Mechanism of Human T-Cell Leukemia Virus Type 1 Protease Investigated by Combined QM/MM Molecular Dynamics Simulations.

Combined quantum mechanical and molecular mechanical (QM/MM) molecular dynamics simulations were performed to investigate the catalytic mechanism of human T-cell leukemia virus type 1 (HTLV-1) protease, a retroviral aspartic protease that is a potential therapeutic target for curing HTLV-1-associated diseases. To elucidate the proteolytic cleavage mechanism, we determined the two-dimensional free energy surfaces of the HTLV-1 protease-catalyzed reactions through various possible pathways. The free energy simulations suggest that the catalytic reactions of the HTLV-1 protease occur in the following sequential steps: (1) a proton is transferred from the lytic water to Asp32', followed by the nucleophilic addition of the resulting hydroxyl to the carbonyl carbon of the scissile bond, forming a tetrahedral oxyanion intermediate, and (2) a proton is transferred from Asp32 to the peptide nitrogen of the scissile bond, leading to the spontaneous breakage of the scissile bond. The rate-limiting step of this catalytic process is the proton transfer from Asp32 to the peptide nitrogen of the scissile bond, with a free energy of activation of 21.1 kcal/mol. This free energy barrier is close to the experimentally determined free energy of activation (16.3 kcal/mol) calculated from the measured catalytic rate constant (kcat). This mechanistic study provides detailed dynamic and structural information that will facilitate the design of mechanism-based inhibitors for the treatment of HTLV-1-associated diseases.