Kokholmchoate9222

It predicts the thermodynamic phase boundary in almost perfect agreement with the experiment, although this excellent agreement does reflect fortuitous cancellation of errors between the enthalpy and entropy of transition.Intermolecular interactions between cholesterol and lipids in cell membranes, which play critical roles in cellular processes such as the formation of nano-domains, depend on the molecular structure of the lipids. The diffusion and the spatial arrangement of cholesterol within the lipid membranes also change with the type of lipids. For example, the flip-flop, an important transport mechanism for cholesterol in the membranes, can be facilitated significantly by the presence of unsaturated lipids. However, how the structure of lipids affects the spatial arrangement and the dynamics of cholesterol remains elusive at a molecular level. In this study, we investigate the effects of lipid-cholesterol interactions on the spatial arrangement and the dynamics of cholesterol. We perform molecular dynamics simulations for the binary component membranes of lipids and cholesterol. We employ seven different kinds of lipids by changing either the degree of a saturation level or the length of lipid tails. We find from our simulations that the rate of cholesterol flip-flop is enhanced as the lipids are either less saturated or shorter, which is consistent with previous studies. Interestingly, when the lipid tails are fully saturated and sufficiently long, the center in between two leaflets becomes metastable for cholesterol to stay at. Because the cholesterol at the membrane center diffuses faster than that within leaflets, regardless of the lipid type, such an emergence of the metastable state (in terms of the cholesterol position) complicates the cholesterol diffusion significantly.Free energies govern the behavior of soft and liquid matter, and improving their predictions could have a large impact on the development of drugs, electrolytes, or homogeneous catalysts. Unfortunately, it is challenging to devise an accurate description of effects governing solvation such as hydrogen-bonding, van der Waals interactions, or conformational sampling. We present a Free energy Machine Learning (FML) model applicable throughout chemical compound space and based on a representation that employs Boltzmann averages to account for an approximated sampling of configurational space. Using the FreeSolv database, FML's out-of-sample prediction errors of experimental hydration free energies decay systematically with training set size, and experimental uncertainty (0.6 kcal/mol) is reached after training on 490 molecules (80% of FreeSolv). Corresponding FML model errors are on par with state-of-the art physics based approaches. To generate the input representation for a new query compound, FML requires approximate and short molecular dynamics runs. We showcase its usefulness through analysis of solvation free energies for 116k organic molecules (all force-field compatible molecules in the QM9 database), identifying the most and least solvated systems and rediscovering quasi-linear structure-property relationships in terms of simple descriptors such as hydrogen-bond donors, number of NH or OH groups, number of oxygen atoms in hydrocarbons, and number of heavy atoms. FML's accuracy is maximal when the temperature used for the molecular dynamics simulation to generate averaged input representation samples in training is the same as for the query compounds. The sampling time for the representation converges rapidly with respect to the prediction error.We report detailed measurements of velocities and sizes of superfluid helium droplets produced from an Even-Lavie pulse valve at stagnation pressures of 20-60 atm and temperatures between 5.7 and 18.0 K. By doping neutral droplets with Rhodamine 6G cations produced from an electrospray ionization source and detecting the positively charged droplets at two different locations along the beam path, we determine the velocities of the different groups of droplets. By subjecting the doped droplet beam to a retardation field, size distributions can then be analyzed. We discover that at stagnation temperatures above 8.0 K, a single group of droplets is observed at both locations, but at 8.0 K and below, two different groups of droplets with different velocities are detectable. The slower group, considered from fragmentation of liquid helium, cannot be deterred by the retardation voltage at 9 kV, implying an exceedingly large size. The faster group, considered from condensation of gaseous helium, has a bimodal distribution when the stagnation temperatures are below 12.3 K at 20 and 40 atm, or 16.1 K at 60 atm. We also report similar size measurements using low energy electrons for impact ionization, and this latter method can be used for facile in situ characterization of pulsed droplet beams. The mechanism of the bimodal size distribution of the condensation group and the reason for the coexistence of both the condensation and fragmentation groups remain elusive.Patchy colloids can be modeled as hard spheres with directional conical association sites. selleck A variety of physical phenomena have been discovered in the patchy colloid system due to its short range and directional interactions. In this work, we combined a cluster distribution theory with generalized Flory and Stockmayer percolation theory to investigate the interplay between phase behavior and percolation for a binary patchy colloid system. The binary patchy colloid system consists of solute molecules with spherically symmetric bonding sites and solvents with two singly bondable sites. Wertheim's first order thermodynamic perturbation theory (TPT1) has been widely applied to the patchy colloids system and it has been combined with percolation theory to study the percolation threshold. However, due to assumptions behind TPT1, it will lose accuracy for a system in which particles have multiple association sites or multiply bondable sites. A recently proposed cluster distribution theory accurately models association at sites that can form multiple bonds. In this work, we investigate the comparison among cluster distribution theory, TPT1, and Monte Carlo simulation for the bonding states of this binary system in which cluster distribution theory shows excellent agreement with Monte Carlo simulation, while TPT1 has a large deviation with the simulation. Cluster distribution theory was further combined with the Flory and Stockmayer percolation theory to investigate the interplay between phase behavior and percolation threshold. We found that the reduced density and the relative bonding strength of solvent-solvent association and solute-solvent association are key factors for the phase behavior and percolation. Percolation can form at low density and low temperature in the vapor phase of this binary system, where the star-like molecules with 12 long branches formed.