Examining the phase transition behavior of amphiphilic lipids in solution using statistical temperature molecular dynamics and replica-exchange Wang-Landau methods

Simulation of fluid/gel phase equilibrium in lipid vesicles

Simulation of single component dipalmitoylphosphatidylcholine (DPPC) coarse-grained DRY-MARTINI lipid vesicles of diameter 10 nm (1350 lipids), 20 nm (5100 lipids) and 40 nm (17 600 lipids) is performed using statistical temperature molecular dynamics (STMD), to study finite size effects upon the order-disorder gel/fluid transition. STMD obtains enhanced sampling using a generalized ensemble, obtaining a flat energy distribution between upper and lower cutoffs, with little computational cost over canonical molecular dynamics. A single STMD trajectory of moderate length is sufficient to sample 20+ transition events, without trapping in the gel phase, and obtain well averaged properties. Phase transitions are analyzed via the energy-dependence of the statistical temperature, T_S(U). The transition temperature decreases with decreasing diameter, in agreement with experiment, and the transition changes from first order to borderline first-second order. The size- and layer-dependence of the structure of both stable phases, and of the pathway of the phase transition, are determined. It is argued that the finite size effects are primarily caused by the disruption of the gel packing by curvature. Inhomogeneous states with faceted gel patches connected by unusual fluid seams are observed at high curvature, with visually different structure in the inner and outer layers due to the different curvatures. Thus a simple physical picture describes phase transitions in nanoscale finite systems far from the thermodynamic limit.

Molecular Dynamics Simulation for Mechanism Elucidation of Food Processing and Safety: State of the Art

Molecular dynamics (MD) simulation is a useful technique to study the interaction between molecules and how they are affected by various processes and processing conditions. This review summarizes the application of MD simulations in food processing and safety, with an emphasis on the effects that emerging nonthermal technologies (for example, high hydrostatic pressure, pulsed electric field) have on the molecular and structural characteristics of foods and biomaterials. The advances and potential projection of MD simulations in the science and engineering aspects of food materials are discussed and focused on research work conducted to study the effects of emerging technologies on food components. It is expected by showing key case studies that it will stir novel developments as a valuable tool to study the effects of emerging food technologies on biomaterials. This review is useful to food researchers and the food industry, as well as researchers and practitioners working on flavor and nutraceutical encapsulations, dietary carbohydrate product developments, modified starches, protein engineering, and other novel food applications.

Complex free-energy landscapes in biaxial nematic liquid crystals and the role of repulsive interactions: A Wang-Landau study

General quadratic Hamiltonian models, describing the interaction between liquid-crystal molecules (typically with D_{2h} symmetry), take into account couplings between their uniaxial and biaxial tensors. While the attractive contributions arising from interactions between similar tensors of the participating molecules provide for eventual condensation of the respective orders at suitably low temperatures, the role of cross coupling between unlike tensors is not fully appreciated. Our recent study with an advanced Monte Carlo technique (entropic sampling) showed clearly the increasing relevance of this cross term in determining the phase diagram (contravening in some regions of model parameter space), the predictions of mean-field theory, and standard Monte Carlo simulation results. In this context, we investigated the phase diagrams and the nature of the phases therein on two trajectories in the parameter space: one is a line in the interior region of biaxial stability believed to be representative of the real systems, and the second is the extensively investigated parabolic path resulting from the London dispersion approximation. In both cases, we find the destabilizing effect of increased cross-coupling interactions, which invariably result in the formation of local biaxial organizations inhomogeneously distributed. This manifests as a small, but unmistakable, contribution of biaxial order in the uniaxial phase. The free-energy profiles computed in the present study as a function of the two dominant order parameters indicate complex landscapes. On the one hand, these profiles account for the unusual thermal behavior of the biaxial order parameter under significant destabilizing influence from the cross terms. On the other, they also allude to the possibility that in real systems, these complexities might indeed be inhibiting the formation of a low-temperature biaxial order itself-perhaps reflecting the difficulties in their ready realization in the laboratory.

Enhanced Sampling of Phase Transitions in Coarse-Grained Lipid Bilayers

Freezing and melting of dipalmitoylphosphatidylcholine (DPPC) bilayers are simulated in both the explicit (Wet) and implicit solvent (Dry) coarse-grained MARTINI force fields with enhanced sampling, via the isobaric, molecular dynamics version of the generalized replica exchange method (gREM). Phase transitions are described with the entropic viewpoint, based upon the statistical temperature as a function of enthalpy, T_S(H) = 1/(dS(H)/dH), where S is the configurational entropy. Bilayer thickness, area per lipid, and the second-rank order parameter (P2) are calculated vs temperature in the transition range. In a 32-lipid Wet MARTINI system, transitions in the lipid and water subsystems are strongly coupled, giving rise to considerable structure in T_S(H) and the need to specify the state of the water when reporting a lipid transition temperature. For gel lipid + liquid water → fluid lipid + liquid water, we find 292.4 K. The small system is influenced by finite-size effects, but it is argued that the entropic approach is well suited to revealing them, which will be particularly relevant for studies of finite nanosystems where there is no thermodynamic limit. In a 390-lipid Dry MARTINI system, two-dimensional analogues of the topographies of coexisting states ("subphases") seen in pure fluids are found. They are not seen in the 32-lipid Wet or Dry system, but the Dry lipids show a new type of state with gel in one leaflet and tilted gel in the other. Dry bilayer transition temperatures are 333.3 K (390 lipids) and 338 K (32 lipids), indicating that the 32-lipid system is not too small for a qualitative study of the transition. Physical arguments are given for Dry lipid system size dependence and for the difference between Wet and Dry systems.

Nanothermodynamics of iron clusters: Small clusters, icosahedral and fcc-cuboctahedral structures

The study of the thermodynamics and structures of iron clusters has been carried on, focusing on small clusters and initial icosahedral and fcc-cuboctahedral structures. Two combined tools are used. First, energy intervals are explored by the Monte Carlo algorithm, called σ-mapping, detailed in the work of Soudan et al. [J. Chem. Phys. 135, 144109 (2011), Paper I]. In its flat histogram version, it provides the classical density of states, g_p(E_p), in terms of the potential energy of the system. Second, the iron system is described by a potential which is called "corrected EAM" (cEAM), explained in the work of Basire et al. [J. Chem. Phys. 141, 104304 (2014), Paper II]. Small clusters from 3 to 12 atoms in their ground state have been compared first with published Density Functional Theory (DFT) calculations, giving a complete agreement of geometries. The series of 13, 55, 147, and 309 atom icosahedrons is shown to be the most stable form for the cEAM potential. However, the 147 atom cluster has a special behaviour, since decreasing the energy from the liquid zone leads to the irreversible trapping of the cluster in a reproducible amorphous state, 7.38 eV higher in energy than the icosahedron. This behaviour is not observed at the higher size of 309 atoms. The heat capacity of the 55, 147, and 309 atom clusters revealed a pronounced peak in the solid zone, related to a solid-solid transition, prior to the melting peak. The corresponding series of 13, 55, and 147 atom cuboctahedrons has been compared, underscoring the unstability towards the icosahedral structure. This unstability occurs clearly in several steps for the 147 atom cluster, with a sudden transformation at a transition state. This illustrates the concerted icosahedron-cuboctahedron transformation of Buckminster Fuller-Mackay, which is calculated for the cEAM potential. Two other clusters of initial fcc structures with 24 and 38 atoms have been studied, as well as a 302 atom cluster. Each one relaxes towards a more stable structure without regularity. The 38 atom cluster exhibits a nearly glassy relaxation, through a cascade of six metastable states of long life. This behaviour, as that of the 147 atom cluster towards the amorphous state, shows that difficulties to reach ergodicity in the lower half of the solid zone are related to particular features of the potential energy landscape, and not necessarily to a too large size of the system. Comparisons of the cEAM iron system with published results about Lennard-Jones systems and DFT calculations are made. The results of the previous clusters have been combined with that of Paper II to plot the cohesive energy E_c and the melting temperature T_m in terms of the cluster atom number N_at. The N_at^-1/3 linear dependence of the melting temperature (Pawlow law) is observed again for N_at > 150. In contrast, for N_at < 150, the curve diverges strongly from the Pawlow law, giving it an overall V-shape, with a linear increase of T_m when N_at goes from 55 to 13 atoms. Surprisingly, the 38 atom cluster is anomalously below the overall curve.

Molecular Dynamics and Monte Carlo simulations in the microcanonical ensemble: Quantitative comparison and reweighting techniques

Molecular Dynamics (MD) and Monte Carlo (MC) simulations are the most popular simulation techniques for many-particle systems. Although they are often applied to similar systems, it is unclear to which extent one has to expect quantitative agreement of the two simulation techniques. In this work, we present a quantitative comparison of MD and MC simulations in the microcanonical ensemble. For three test examples, we study first- and second-order phase transitions with a focus on liquid-gas like transitions. We present MD analysis techniques to compensate for conservation law effects due to linear and angular momentum conservation. Additionally, we apply the weighted histogram analysis method to microcanonical histograms reweighted from MD simulations. By this means, we are able to estimate the density of states from many microcanonical simulations at various total energies. This further allows us to compute estimates of canonical expectation values.

Reexamination of the mean-field phase diagram of biaxial nematic liquid crystals: Insights from Monte Carlo studies

Investigations of the phase diagram of biaxial liquid-crystal systems through analyses of general Hamiltonian models within the simplifications of mean-field theory (MFT), as well as by computer simulations based on microscopic models, are directed toward an appreciation of the role of the underlying molecular-level interactions to facilitate its spontaneous condensation into a nematic phase with biaxial symmetry. Continuing experimental challenges in realizing such a system unambiguously, despite encouraging predictions from MFT, for example, are requiring more versatile simulational methodologies capable of providing insights into possible hindering barriers within the system, typically gleaned through its free-energy dependences on relevant observables as the system is driven through the transitions. The recent paper from this group [Kamala Latha et al., Phys. Rev. E 89, 050501(R) (2014)], summarizing the outcome of detailed Monte Carlo simulations carried out employing an entropic sampling technique, suggested a qualitative modification of the MFT phase diagram as the Hamiltonian is asymptotically driven toward the so-called partly repulsive regions. It was argued that the degree of (cross) coupling between the uniaxial and biaxial tensor components of neighboring molecules plays a crucial role in facilitating a ready condensation of the biaxial phase, suggesting that this could be a plausible factor in explaining the experimental difficulties. In this paper, we elaborate this point further, providing additional evidence from curious variations of free-energy profiles with respect to the relevant orientational order parameters, at different temperatures bracketing the phase transitions.

Examination of the phase transition behavior of nano-confined fluids by statistical temperature molecular dynamics

The fluid-solid phase transition behavior of nano-confined Lennard-Jones fluids as a function of temperature and degree of nanoconfinement has been studied via statistical temperature molecular dynamics (STMD). The STMD method allows the direct calculation of the density of states and thus the heat capacity with high efficiency. The fluids are simulated between parallel solid surfaces with varying pore sizes, wall-fluid interaction energies, and registry of the walls. The fluid-solid phase transition behavior has been characterized through determination of the heat capacity. The results show that for pores of ideal-spacing, the order-disorder transition temperature (T(ODT)) is reduced as the pore size increases until values consistent with that seen in a bulk system. Also, as the interaction between the wall and fluid is reduced, T(ODT) is reduced due to weak constraints from the wall. However, for non-ideal spacing pores, quite different behavior is obtained, e.g., generally T(ODT) are largely reduced, and T(ODT) is decreased as the wall constraint becomes larger. For unaligned walls (i.e., whose lattices are not in registry), the fluid-solid transition is also detected as T is reduced, indicating non-ideality in orientation of the walls does not impact the formation of a solid, but results in a slight change in T(ODT) compared to the perfectly aligned systems. The STMD method is demonstrated to be a robust way for probing the phase transitions of nanoconfined fluids systematically, enabling the future examination of the phase transition behavior of more complex fluids.

Dynamical traps in Wang-Landau sampling of continuous systems: Mechanism and solution

We study the mechanism behind dynamical trappings experienced during Wang-Landau sampling of continuous systems reported by several authors. Trapping is caused by the random walker coming close to a local energy extremum, although the mechanism is different from that of the critical slowing-down encountered in conventional molecular dynamics or Monte Carlo simulations. When trapped, the random walker misses the entire or even several stages of Wang-Landau modification factor reduction, leading to inadequate sampling of the configuration space and a rough density of states, even though the modification factor has been reduced to very small values. Trapping is dependent on specific systems, the choice of energy bins, and the Monte Carlo step size, making it highly unpredictable. A general, simple, and effective solution is proposed where the configurations of multiple parallel Wang-Landau trajectories are interswapped to prevent trapping. We also explain why swapping frees the random walker from such traps. The efficacy of the proposed algorithm is demonstrated.

Scalable replica-exchange framework for Wang-Landau sampling

We investigate a generic, parallel replica-exchange framework for Monte Carlo simulations based on the Wang-Landau method. To demonstrate its advantages and general applicability for massively parallel simulations of complex systems, we apply it to lattice spin models, the self-assembly process in amphiphilic solutions, and the adsorption of molecules on surfaces. While of general current interest, the latter phenomena are challenging to study computationally because of multiple structural transitions occurring over a broad temperature range. We show how the parallel framework facilitates simulations of such processes and, without any loss of accuracy or precision, gives a significant speedup and allows for the study of much larger systems and much wider temperature ranges than possible with single-walker methods.

Thermodynamic and conformational insights into the phase transition of a single flexible homopolymer chain using replica exchange Monte Carlo method

The phase transition of a single flexible homopolymer chain in the limit condition of dilute solution is systematically investigated using a coarse-grained model. Replica exchange Monte Carlo method is used to enhance the performance of the conformation space exploration, and thus detailed investigation of phase behavior of the system can be provided. With the designed potentials, the coil-globule transition and the liquid-solid-like transition are identified, and the transition temperatures are measured with the conformational and thermodynamic analyses. Additionally, by extrapolating the coil-globule transition temperature, T Θ , and the liquid-solid-like transition temperature T(L → S) to the thermodynamic limit, N → ∞, we found no "tri-critical" point in the current model.

Molecular Dynamics in the Multicanonical Ensemble: Equivalence of Wang-Landau Sampling, Statistical Temperature Molecular Dynamics, and Metadynamics

We show a direct formal relationship between the Wang-Landau iteration [PRL 86, 2050 (2001)], metadynamics [PNAS 99, 12562 (2002)], and statistical temperature molecular dynamics (STMD) [PRL 97, 050601 (2006)] that are the major work-horses for sampling from generalized ensembles. We demonstrate that STMD, itself derived from the Wang-Landau method, can be made indistinguishable from metadynamics. We also show that Gaussian kernels significantly improve the performance of STMD, highlighting the practical benefits of this improved formal understanding.