An algorithm for the simulation of quantum-classical dynamics is presented. Quantum-classical evolution is effected by a propagator exp(iLt) involving the quantum classical Liouville operatorL that describes the evolution of a quantum subsystem coupled to a classical bath. Such a mixed description provides a means to study the dynamics of complex many-body systems where certain degrees of freedom are treated quantum mechanically. The algorithm is constructed by decomposing the time interval t into small segments of length t and successively applying the propagator in the short time segments to obtain the evolution for long times. The algorithm is shown to be a discretization of the iterated Dyson form of the propagator whose direct solution is vexatious. The sequential short-time propagation algorithm is applied to the spin-boson model for a range of values of the Kondo parameter and shown to be effective.

pH is a key parameter for technological and biological processes, intimately related to biomolecular charge. As such, it controls biomolecular conformation and intermolecular interactions, for example, protein/RNA stability and folding, enzyme activity, regulation through conformational switches, protein-polyelectrolyte association, and protein-RNA interactions. pH also plays an important role in technological systems in food, brewing, pharma, bioseparations, and biomaterials in general. Predicting the structure of large proteins and complexes remains a great challenge experimentally, industrially, and theoretically, despite the variety of numerical schemes available ranging from Poisson-Boltzmann approaches to explicit solvent based methods. In this work we benchmark a fast proton titration scheme against experiment and several theoretical methods on the following set of representative proteins: [HP36, BBL, HEWL (triclinic and orthorhombic), RNase, SNASE (V66K/WT, V66K/PHS, V66K/Δ+PHS, L38D/Δ+PHS, L38E/Δ+PHS, L38K/Δ+PHS), ALAC, and OMTKY3]; routinely used in similar tests due to the diversity of their structural features. Our scheme is rooted in the classical Tanford-Kirkwood model of impenetrable spheres, where salt is treated at the Debye-Hückel level. Treating salt implicitly dramatically reduces the computation time, thereby circumventing sampling difficulties faced by other numerical schemes. In comparison with experimental measurements, our calculated pK values have the average, maximum absolute, and root-mean-square deviations of 0.4-0.9, 1.0-5.2, and 0.5-1.2 pH units, respectively. These values are within the ranges commonly observed in theoretical models. They are also in the large majority of the cases studied here more accurate than the NULL model. For BBL, ALAC, and OMTKY3, the predicted pK are closer to experimental results than other analyzed theoretical data. Despite the intrinsic approximations of the fast titration scheme, its robustness and ability to properly describe the main system physics is confirmed.

We report computer simulations of an excess electron in various structural motifs of polyethylene at room temperature, including lamellar and interfacial regions between amorphous and lamellae, as well as nanometre-sized voids. Electronic properties such as density of states, mobility edges, and mobilities are computed on the different phases using a block Lanczos algorithm. Our results suggest that the electronic density of states for a heterogeneous material can be approximated by summing the single phase density of states weighted by their corresponding volume fractions. Additionally, a quantitative connection between the localized states of the excess electron and the local atomic structure is presented.The US National Science Foundation under grant CHE-0911635 and from his Stokes Professorship in Nano Biophysics from Science Foundation Ireland thanks the Irish Centre for High End Computing (ICHEC) for computer resources and Science Foundation Ireland for support from grant 08-IN.1-I1869

The structure and interactions of proteins play a critical role in determining the quality attributes of many foods, beverages, and pharmaceutical products. Incorporating a multiscale understanding of the structure–function relationships of proteins can provide greater insight into, and control of, the relevant processes at play. Combining data from experimental measurements, human sensory panels, and computer simulations through machine learning allows the construction of statistical models relating nanoscale properties of proteins to the physicochemical properties, physiological outcomes, and tastes of foods. This review highlights several examples of advanced computer simulations at molecular, mesoscale, and multiscale levels that shed light on the mechanisms at play in foods, thereby facilitating their control. It includes a practical simulation toolbox for those new to in silico modeling.

We perform combined temperature-accelerated and standard molecular dynamics (MD) simulations to elucidate the atomistic structure of hydrated Nafion (hydration level lambda = 6.5) in the slab and cylinder morphologies. Our samples are initially made of elongated Nafion strands with a relatively small fraction of gauche defects. Our simulations show that even very long (>50 ns) "brute force" MD simulations are insufficient to reach equilibrated structures. In fact, similar to 30-40 ns long temperature-accelerated molecular dynamics (TAMD) simulations started from the same initial conditions explore more stable (lower potential energy) stationary structures. The effect of TAMD is to allow a rearrangement of the backbone consisting of an increase in gauche defects, which cannot be obtained by "brute force" MD because the trans-gauche transition is a rare event at room temperature. Associated with the backbone rearrangement, we observe a change in the structure of the water layers/tubes as measured by the size and number of bulk (four-fold coordinated water molecules) and surface-like water clusters. At equilibrium, the mean size of bulk-like water clusters is small, typically between 10 and 20 molecules, depending on the morphology. Larger clusters are also present in our samples, the largest being made of similar to 350 molecules, but even the latter is too small for percolation. This suggests that the proton transport through each morphology might be a two-step process: Grotthuss-like within bulk-like water clusters and of a different type (e.g., diffusive or even transport across fluctuatively opening necks) between clusters