We demonstrate the efficiency of the numerical calculation of thermal semiclassical transition state theory (SCTST) rates across several representative chemical reactions using the restricted partition function (RPF)─viz a function that depends only on the imaginary action associated with a reaction. Here, we treat the potential energy surfaces (PESs) through fourth order expansions around the saddle point and integrate the Hamiltonian up to second order in employing vibrational perturbation theory. We apply this formalism to uni- and bimolecular reactions with different─though relatively high─barrier heights to uncover the influence of the barrier properties, minimal energies, and separability of the rotational motion on rate constants and tunneling corrections. Although all modes are coupled within the RPF, we found in our numerical examples that the rotational component in the absence of significant rotational distortions can be separated from the vibrational contributions. Moreover, a classical treatment of the rotational contribution is adequate over the temperature range from approximately 100 to 1000 K. We also found that the choice of DFT basis set can lead to variations in rate constants of up to an order of magnitude. Finally, different schemes for counting eligible energy levels result in rate constants that differ by no more than a factor of 2, with the remaining discrepancies attributed to the treatment of near-convergent levels in perturbation theory.

The wide adoption of transition state theory in resolving the rates of molecular processes relies on the simplification from reducing the formal and numerical expense of dynamics by a geometric constraint. Such a reduction is at odds with the uncertainty in localization that the uncertainty principle requires. While many forms of semiclassical transition state theory (SCTST) have been aimed at addressing this challenge, a popular approach has relied on resolving the underlying phase space structure of the exact rate formula to leverage Bohr-Sommerfeld quantization. The Hernandez-Miller SCTST reframed the thermal rate formula into an integral of the so-called restricted partition function (RPF) over the action associated with the reaction. The density-of-state SCTST has reframed the rate formula in terms of the instanton's density of states (DoS). Here, we show the relationship between the RPF-SCTST and the DoS-SCTST and derive the latter from the former. In this way, we help unify these branches of SCTST and provide a clearer formalism for future advances.

DNA nanotechnology has broad applications in biomedical drug delivery and programmable materials. Characterization of the self-assembly of DNA origami and quantum dots (QDs) is necessary for the development of new DNA-based nanostructures. We use computation and experiment to show that the self-assembly of 3D hierarchical nanostructures can be controlled by programming the binding site number and their positions on DNA origami. Using biotinylated pentagonal pyramid wireframe DNA origamis and streptavidin capped QDs, we demonstrate that DNA origami with 1 binding site at the outer vertex can assemble multimeric origamis with up to 6 DNA origamis on 1 QD, and DNA origami with 1 binding site at the inner center can only assemble monomeric and dimeric origamis. Meanwhile, the yield percentages of different multimeric origamis are controlled by the QD:DNA-origami stoichiometric mixing ratio. DNA origamis with 2 binding sites at the alpha gamma positions (of the pentagon) make larger nanostructures than those with binding sites at the alpha beta positions. In general, increasing the number of binding sites leads to increases in the nanostructure size. At high DNA origami concentration, the QD number in each cluster becomes the limiting factor for the growth of nanostructures. We find that reducing the QD size can also affect the self-assembly because of the reduced access to the binding sites from more densely packed origamis.

We address the challenge of representativity and dynamical consistency when unbonded fine-grained particles are collected together into coarse-grained particles. We implement a hybrid procedure for identifying and tracking the underlying fine-grained particles & horbar;e.g., atoms or molecules & horbar;by exchanging them between the coarse-grained particles periodically at a characteristic time. The exchange involves a back-mapping of the coarse-grained particles into fine-grained particles and a subsequent reassignment to coarse-grained particles conserving total mass and momentum. We find that an appropriate choice of the characteristic exchange time can lead to the correct effective diffusion rate of the fine-grained particles when simulated in hybrid coarse-grained dynamics. In the compressed (supercritical) fluid regime, without the exchange term, fine-grained particles remain associated with a given coarse-grained particle, leading to substantially lower diffusion rates than seen in all-atom molecular dynamics of the fine-grained particles. Thus, this work confirms the need for addressing the representativity of fine-grained particles within coarse-grained particles and offers a simple exchange mechanism so as to retain dynamical consistency between the fine- and coarse-grained scales.

The bifunctional photoacid omega-(2-hydroxynaphthyl-1)-decanoic acid (1S2N) takes part both in intramolecular excited-state proton transfer (ESPT) to the anion of a fatty acid and in intermolecular ESPT in the presence of a water solvent. Excited-state intra-and intermolecular proton transfer of 1S2N was investigated in homogeneous ethanol/water solution and in micellar solutions of various surfactants. The interfacial potential of micelles was changed by using cationic (CTAB), non-ionic (Brij-35) and anionic (SDS) surfactants. With the decrease of the interfacial potential, the protolytic photodissociation of naphthol and the diffusion-controlled intramolecular ESPT to carboxylic anion were suppressed.

The dynamical properties of a system of soft rods governed by stochastic hard collisions (SHCs) have been determined over a varying range of softness using molecular dynamics simulations in one dimension and analytic theory. The SHC model allows for interpenetration of the system's constituent particles in the simulations, generating overlapping clustering behavior analogous to the spatial structures observed in systems governed by deterministic bounded potentials. Through variation of an assigned softness parameter δ, the limiting ranges of intermolecular softness are bridged, connecting the limiting ensemble behavior from hard to ideal (completely soft). Various dynamical and structural observables are measured from simulation and compared to developed theoretical values. The spatial properties are found to be well predicted by theories developed for the deterministic penetrable-sphere model with a transformation from energetic to probabilistic arguments. While the overlapping spatial structures are complex, the dynamical properties can be adequately approximated through a theory built on impulsive interactions with Enskog corrections. Our theory suggests that as the softness of interaction is varied toward the ideal limit, correlated collision processes are less important to the energy transfer mechanism, and Markovian processes dominate the evolution of the configuration space ensemble. For interaction softness close to hard limit, collision processes are highly correlated and overlapping spatial configurations give rise to entanglement of single-particle trajectories.

The assembly of monomeric constituents into molecular superstructures through sequential-arrival processes has been simulated and theoretically characterized. When the energetic interactions allow for complete overlap of the particles, the model is equivalent to that of the sequential absorption of soft particles on a surface. In the present work, we consider more general cases by including arbitrary aggregating geometries and varying prescriptions of the connectivity network. The resulting theory accounts for the evolution and final-state configurations through a system of equations governing structural generation. We find that particle geometries differ significantly from those in equilibrium. In particular, variations of structural rigidity and morphology tune particle energetics and result in significant variation in the nonequilibrium distributions of the assembly in comparison to the corresponding equilibrium case.

The surface coverage of coarse-grained macromolecules bound to a solid substrate is not simply proportional to the two-dimensional number density because macromolecules can overlap. As a function of the overlap probability δ, we have developed analytical formulas and computational models capable of characterizing this nonlinear relationship. For simplicity, we ignore site-site interactions that would be induced by length-scale mismatches between binding sites and the radius of gyration of the incident coarse-grained macromolecular species. The interactions between macromolecules are modeled with a finite bounded potential that allows multiple macromolecules to occupy the same binding site. The softness of the bounded potential is thereby reduced to the single parameter δ. Through variation of this parameter, completely hard (δ = 0) and completely soft (δ = 1) behavior can be bridged. For soft macromolecular interactions (δ > 0), multiple occupancy reduces the fraction of sites ϕ occupied on the substrate. We derive the exact transition probability between sequential configurations and use this probability to predict ϕ and the distribution of occupied sites. Due to the complexity of the exact ϕ expressions and their analytical intractability at the thermodynamic limit, we apply a simplified mean-field (MF) expression for ϕ. The MF model is found to be in excellent agreement with the exact result. Both the exact and MF models are applied to an example dynamical system with multibody interactions governed by a stochastic bounded potential. Both models show agreement with results measured from simulation.

The structure and assembly of soft particles is difficult to characterize because their interpenetrability allows them to be packed at ever higher density albeit with an increasing penalty in energy and/or pressure. Alternatively, the use of impenetrable particles (such as hard spheres) as a reference model for soft particles can fail because the packing densities are limited by the impossibility of complete space filling. We recently introduced the stochastic penetration algorithm (SPA) so as to allow for the computationally efficient integration of hard sphere models while including overlaps seen in soft interactions [Craven et al., J. Chem. Phys., 2013, 138, 244901]. Moving beyond the initial one-dimensional case studied earlier, we now consider the spatial properties of systems of stochastically penetrable spheres in dimensions d≤ 3 through the use of molecular dynamics simulations and analytic methods. The stochastic potential allows spheres to either interpenetrate with a probability δ or collide elastically otherwise. For δ > 0 the particles interpenetrate (overlap), reducing the effective volume occupied by the particles in the system. We find that the occupied volume can be accurately predicted using analytic expressions derived from mean field arguments for the particle overlap probabilities with the exception of an observed clustering regime. This anomalous clustering behavior occurs at high densities and small δ. We find that this regime is coincident with that observed in deterministic penetrable models. The behavior of the stochastic penetrable particles also indicates that soft particles would be characterizable through a single reduced parameter that captures their overlap probability.

Molecular dynamics is fundamentally the integration of the equations of motion over a representation of an atomic and molecular system. The most rigorous choice for performing molecular dynamics entails the use of quantum‐mechanical equations of motion and a representation of the molecular system through all of its electrons and atoms. For most molecular problems involving at least hundreds of atoms, but generally many more, this is simply computationally prohibitive. Thus the art of molecular dynamics lies in choosing the representation and the appropriate equations of motion capable of addressing the requisite measurables. When used adroitly, it can provide both equilibrium (averaged) and time‐dependent properties of a molecular system. Many computational packages now exist that perform molecular dynamics simulations. They generally include force fields to represent the interactions between atoms and molecules (smoothing out electrons through the Born‐Oppenheimer approximation) and integrate the remaining particles classically. Despite these simplifications, all‐atom molecular dynamics remains computationally inaccessible if one includes the number of atoms required to simulate mesoscopic solvents. Here we use analytical models to demonstrate how molecular dynamics can be used to limit the solvent size in systems experiencing either equilibrium or nonequilibrium conditions. It is equally important to address the measurables (such as reaction rates) that are to be obtained prior to the generation of the data‐intensive trajectories. WIREs Comput Mol Sci 2014, 4:541–561. doi: 10.1002/wcms.1190 This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods Theoretical and Physical Chemistry > Reaction Dynamics and Kinetics

Kawai and Komatsuzaki [J. Chem. Phys. 134, 114523 (2011)] recently derived the nonequilibrium generalized Langevin equation (GLE) for a nonstationary system using the projection operator technique. In the limit when the environment is slowly changing (that is, a quasi-equilibrium bath), it should reduce to the irreversible GLE approach (iGLE) [J. Chem. Phys. 111, 7701 (1999)]. Kawai and Komatsuzaki, however, found that the driven harmonic oscillator, an example of a nonequilibrium system does not obey the iGLE presumably because it did not quite satisfy the limiting conditions of the latter. Notwithstanding the lack of a massive quasi-equilibrium bath (one of the conditions under which the iGLE had been derived earlier), we found that the temperature-driven iGLE (T-iGLE) [J. Chem. Phys. 126, 244506 (2007)] can reproduce the nonequilibrium dynamics of a driven dissipated pair of harmonic oscillators. It requires a choice of the function representing the coupling between the oscillator coordinate and the bath and shows that the T-iGLE representation is consistent with the projection operator formalism if only dominant bath modes are taken into account. Moreover, we also show that the more readily applicable phenomenological iGLE model is recoverable from the Kawai and Komatsuzaki model beyond the adiabatic limit used in the original T-iGLE theory.

The occupied volume of a penetrable hard rod (HR) system in one dimension is probed through the use of molecular dynamics simulations. In these dynamical simulations, collisions between penetrable rods are governed by a stochastic penetration algorithm (SPA), which allows for rods to either interpenetrate with a probability δ, or collide elastically otherwise. The limiting values of this parameter, δ = 0 and δ = 1, correspond to the HR and the ideal limits, respectively. At intermediate values, 0 < δ < 1, mixing of mutually exclusive and independent events is observed, making prediction of the occupied volume nontrivial. At high hard core volume fractions φ0, the occupied volume expression derived by Rikvold and Stell [J. Chem. Phys. 82, 1014 (1985)] for permeable systems does not accurately predict the occupied volume measured from the SPA simulations. Multi-body effects contribute significantly to the pair correlation function g2(r) and the simplification by Rikvold and Stell that g2(r) = δ in the penetrative region is observed to be inaccurate for the SPA model. We find that an integral over the penetrative region of g2(r) is the principal quantity that describes the particle overlap ratios corresponding to the observed penetration probabilities. Analytic formulas are developed to predict the occupied volume of mixed systems and agreement is observed between these theoretical predictions and the results measured from simulation.

The excited-state proton transfer (ESPT) reaction of the "super"photoacid N-methyl-6-hydroxyquinolinium (MHQ) was studied using both fluorescence upconversion and time-correlated single photon counting (TCSPC) techniques. The ultrafast ESPT kinetics were investigated in various alcohols and water and determined to be solvent-controlled. The ESPT temperature dependence of MHQ was also studied in various alcohols and compared to that observed for another "super"photoacid, 5,8-dicyano-2-naphthol (DCN2). A full set of kinetic and thermodynamic parameters describing the ESPT was obtained. The protolytic photodissociation rate constant for MHQ was higher than that for DCN2, while the ESPT activation energies of MHQ were smaller. These findings are attributed to the approximately 3 orders of magnitude differences in excited-state acidities of MHQ and DCN2.

The temperature-ramped irreversible Langevin equation [A. V. Popov and R. Hernandez, J. Chem. Phys. 134, 244506 (2007)] has been seen to describe the nonequilibrium atomic oscillations of a nanorod dragged across a surface. The nanorod and surface consist of hydroxylated α-Al(2)O(3) layers as was studied earlier by Hase and co-workers [J. Chem. Phys. 122, 094713 (2005)]. The present approach corresponds to the reduced Frenkel-Kontorova-Tomlinson model in which only one element of the vibrational chain representing a surface layer is considered explicitly. The key new concept centers on a separation of the environment into two effective reduced-dimensional baths: an equilibrium bath arising from the thermostated vibrations of the crystal lattice and a nonequilibrium bath arising from driven oscillations at the contact between the nanorod and the surface. The temperature of the latter is defined by the mean energy of a representative atomic oscillator for a given layer. The temporal temperature fluctuations and the dependence of the static part of the temperature on the sliding velocity are close to those found in the MD simulations of Hase and co-workers.

The dynamics of polymer reactions in solutions can often be described quite well using the known chemical reaction mechanism and solving the associated chemical kinetic equations. However, when polymerization—either because of vulcanization in cross-linking reactions or because of aggregative assembly in chain growth—leads to substantial changes in the solvation and hence in the reaction rates, the solution can exhibit heterogeneity both in time and space. These in turn, lead to nonstationary interactions that can no longer be described by conventional kinetic (master) equations. Thus far, we have described the time-dependent nature of such polymerizing environments both through stochastic and lattice models capable of addressing such complex environment dynamics. The current article focuses on the former approach, but now rephrases the earlier justification of the use of the irreversible Langevin equation (iGLE) to the polymerization problem in the context of kinetic models, and specifically the chemical stochastic equation. The nonstationarity in the solvent response due to collective polymerization within the dense solvent appears naturally, and leads to a direct connection between these models. The kinetics of the polymer size distribution (and other observables) for two distinct living polymer systems, α -methylstyrene and 4-vinylbenzocyclobutene, are analyzed in the context of these models.