Soft core fluid in a quenched matrix of soft core particles: A mobile mixture in a model gel

We present a density-functional study of a binary phase-separating mixture of soft core particles immersed in a random matrix of quenched soft core particles of larger size. This is a model for a binary polymer mixture immersed in a crosslinked rigid polymer network. Using the replica `trick' for quenched-annealed mixtures we derive an explicit density functional theory that treats the quenched species on the level of its one-body density distribution. The relation to a set of effective external potentials acting on the annealed components is discussed. We relate matrix-induced condensation in bulk to the behaviour of the mixture around a single large particle. The interfacial properties of the binary mixture at a surface of the quenched matrix display a rich interplay between capillary condensation inside the bulk matrix and wetting phenomena at the matrix surface.Comment: 20 pages, 5 figures. Accepted for Phys. Rev.

Structure and Phase Transformations of DPPC Lipid Bilayers in the Presence of Nanoparticles: Insights from Coarse-Grained Molecular Dynamics Simulations

In this article, we investigate fluid-gel transformations of a DPPC lipid bilayer in the presence of nanoparticles, using coarse grained molecular dynamics. Two types of nanoparticles are considered, specifically a 3 nm hydrophobic nanoparticle located in the core of the bilayer and a 6 nm charged nanoparticle located at the interface between the bilayer and water phase. Both negatively and positively charged nanoparticles at the bilayer interface are investigated. We demonstrate that the presence of all types of nanoparticles induces disorder effects in the structure of the lipid bilayer. These effects are characterized using computer visualization of the gel phase in the presence of nanoparticles, radial distribution functions, and order parameters. The 3 nm hydrophobic nanoparticle immersed in the bilayer core and the positively charged nanoparticle at the bilayer surface have no effect on the temperature of the fluid-gel transformation, compared to the bulk case. Interestingly, a negatively charged hydrophobic nanoparticle located at the surface of the bilayer causes slight shift of the fluid-gel transformation to a lower temperature, compared to the bulk bilayer case

Incremental Adaptation Strategies for Neural Network Language Models

It is today acknowledged that neural network language models outperform backoff language models in applications like speech recognition or statistical machine translation. However, training these models on large amounts of data can take several days. We present efficient techniques to adapt a neural network language model to new data. Instead of training a completely new model or relying on mixture approaches, we propose two new methods: continued training on resampled data or insertion of adaptation layers. We present experimental results in an CAT environment where the post-edits of professional translators are used to improve an SMT system. Both methods are very fast and achieve significant improvements without overfitting the small adaptation data

Adsorption hysteresis and capillary condensation in disordered porous solids: a density functional study

We present a theoretical study of capillary condensation of fluids adsorbed in mesoporous disordered media. Combining mean-field density functional theory with a coarse-grained description in terms of a lattice-gas model allows us to investigate both the out-of-equilibrium (hysteresis) and the equilibrium behavior. We show that the main features of capillary condensation in disordered solids result from the appearance of a complex free-energy landscape with a large number of metastable states. We detail the numerical procedures for finding these states, and the presence or absence of transitions in the thermodynamic limit is determined by careful finite-size studies.Comment: 30 pages, 18 figures. To appear in J. Phys.: Condens. Matte

Slow dynamics of a confined supercooled binary mixture II: Q space analysis

We report the analysis in the wavevector space of the density correlator of a Lennard Jones binary mixture confined in a disordered matrix of soft spheres upon supercooling. In spite of the strong confining medium the behavior of the mixture is consistent with the Mode Coupling Theory predictions for bulk supercooled liquids. The relaxation times extracted from the fit of the density correlator to the stretched exponential function follow a unique power law behavior as a function of wavevector and temperature. The von Schweidler scaling properties are valid for an extended wavevector range around the peak of the structure factor. The parameters extracted in the present work are compared with the bulk values obtained in literature.Comment: 8 pages with 8 figures. RevTeX. Accepted for publication in Phys. Rev.

Capillary condensation in disordered porous materials: hysteresis versus equilibrium behavior

We study the interplay between hysteresis and equilibrium behavior in capillary condensation of fluids in mesoporous disordered materials via a mean-field density functional theory of a disordered lattice-gas model. The approach reproduces all major features observed experimentally. We show that the simple van der Waals picture of metastability fails due to the appearance of a complex free-energy landscape with a large number of metastable states. In particular, hysteresis can occur both with and without an underlying equilibrium transition, thermodynamic consistency is not satisfied along the hysteresis loop, and out-of-equilibrium phase transitions are possible.Comment: 4 pages, 4 figure

Nanomaterial interactions with biomembranes: Bridging the gap between soft matter models and biological context

Synthetic polymers, nanoparticles, and carbon-based materials have great potential in applications including drug delivery, gene transfection, in vitro and in vivo imaging, and the alteration of biological function. Nature and humans use different design strategies to create nanomaterials: biological objects have emerged from billions of years of evolution and from adaptation to their environment resulting in high levels of structural complexity; in contrast, synthetic nanomaterials result from minimalistic but controlled design options limited by the authors' current understanding of the biological world. This conceptual mismatch makes it challenging to create synthetic nanomaterials that possess desired functions in biological media. In many biologically relevant applications, nanomaterials must enter the cell interior to perform their functions. An essential transport barrier is the cell-protecting plasma membrane and hence the understanding of its interaction with nanomaterials is a fundamental task in biotechnology. The authors present open questions in the field of nanomaterial interactions with biological membranes, including: how physical mechanisms and molecular forces acting at the nanoscale restrict or inspire design options; which levels of complexity to include next in computational and experimental models to describe how nanomaterials cross barriers via passive or active processes; and how the biological media and protein corona interfere with nanomaterial functionality. In this Perspective, the authors address these questions with the aim of offering guidelines for the development of next-generation nanomaterials that function in biological media

Automated analysis and benchmarking of GCMC simulation programs in application to gas adsorption.

<p>In this work we set out to evaluate the computational performance of several popular Monte Carlo simulation programs, namely Cassandra, DL Monte, Music, Raspa and Towhee, in modelling gas adsorption in crystalline materials. We focus on the reference case of adsorption in IRMOF-1 at 208 K. To critically assess their performance, we first establish some criteria which allow us to make this assessment on a consistent basis. Specifically, the total computational time required for a program to complete a simulation of an adsorption point, consists of the time required for equilibration plus time required to generate a specific number of uncorrelated samples of the property of interest. Our analysis shows that across different programs there is a wide difference in the statistical value of a single MC step, however their computational performance is quite comparable. We further explore the use of energy grids and energy bias techniques, as well as the efficiency of the parallel execution of the simulations. The test cases developed are made openly available as a resource for the community, and can be used for validation and as a template for further studies.</p