Minimum energy paths of wetting transitions on grooved surfaces.

A method that computes minimum energy paths (MEPs) of wetting transitions is developed. The method couples the Cahn-Hilliard formulation of a modified phase-field method with the simplified string method. Its main computational kernel is the fast Fourier transform that is efficiently performed on graphics processing units. The effectiveness of the proposed method is demonstrated on two types of transitions of droplets on grooved surfaces. The first is the transition from the Cassie-Baxter wetting state to the Wenzel state, where it is shown that it progresses in a sequential manner with the droplet wetting each groove successively. The second transition type is a lateral displacement of the droplet against the grooves, where the droplet successively detaches/attaches from/to the rear/front protrusion of the surface (a transition in the reverse order is also possible). The energy barriers of both the transitions are extracted from the MEP; they are useful for the evaluation of the robustness of superhydrophobic surfaces (resistance to the Cassie-Baxter to Wenzel transition) and the droplet mobility on those surfaces (high mobility/small resistance to lateral displacements). The relation of the MEP with the potential transition paths coming from the solution space mapping is discussed.

Linking the operating parameters of chemical vapor deposition reactors with film conformality and surface nano-morphology.

A multiscale modeling framework is used to couple the co-existing scales, i.e., macro-, micro- and nano-scale, in chemical vapor deposition (CVD) processes. The framework consists of a reactor scale model (RSM) for the description of the transport phenomena in the bulk phase (macro-scale) of a CVD reactor and two models for the micro- and nano-scale: (a) A feature scale model (FSM) describing the deposition of a film inside features on a predefined micro-topography on the wafer and (b) a nano-morphology model (NMM) describing the surface morphology evolution during thin film deposition on an initially flat surface. The FSM is deterministic and consists of three sub-models: A ballistic model for the species' transport inside features, a surface chemistry model, and a profile evolution algorithm based on the level set method. The NMM is stochastic and is based on the kinetic Monte Carlo method. The coupling of RSM with FSM is performed through a correction of the species consumption on the wafer. The linking of RSM with NMM is performed through "feeding" of the deposition rate calculated by RSM to the NMM. The case study is CVD of Silicon (Si) from Silane. The effect of the reactor's operating parameters on the Si film conformality inside trenches is investigated by the coupling of RSM with FSM. The formation of dimmers on an initially flat Si (001) surface as well as the periodic change of the surface nano-morphology is predicted.

Applications of ultrasound to chiral crystallization, resolution and deracemization.

Industrial synthesis of enantiopure compounds is nowadays heavily based on the separation of racemates through crystallization processes. Although the application of ultrasound in solution crystallization processes (sonocrystallization) has become a promising emerging technology, offering several benefits (e.g. reduction of the induction time and narrowing of the metastable zone width, control over the product size, shape and polymorphic modification), little attention has been paid so far to the effects of ultrasound on chiral crystallization processes. Several recent studies have reported on the application of acoustic energy to crystallization processes that separate enantiomers, ranging from classical (diastereomeric) resolution and preferential crystallization to new and emerging processes such as attrition-enhanced deracemization (Viedma ripening). A variety of interesting effects have been observed, which include among others, enhanced crystallization yield with higher enantiomeric purity crystals, spontaneous mirror symmetry breaking crystallization, formation of metastable conglomerate crystals and enhanced deracemization rates. The objective of this review is to provide an overview of the effects of ultrasound on chiral crystallization and outline several aspects of interest in this emerging field.

Gold nanoparticles, radiations and the immune system: Current insights into the physical mechanisms and the biological interactions of this new alliance towards cancer therapy.

Considering both cancer's serious impact on public health and the side effects of cancer treatments, strategies towards targeted cancer therapy have lately gained considerable interest. Employment of gold nanoparticles (GNPs), in combination with ionizing and non-ionizing radiations, has been shown to improve the effect of radiation treatment significantly. GNPs, as high-Z particles, possess the ability to absorb ionizing radiation and enhance the deposited dose within the targeted tumors. Furthermore, they can convert non-ionizing radiation into heat, due to plasmon resonance, leading to hyperthermic damage to cancer cells. These observations, also supported by experimental evidence both in vitro and in vivo systems, reveal the capacity of GNPs to act as radiosensitizers for different types of radiation. In addition, they can be chemically modified to selectively target tumors, which renders them suitable for future cancer treatment therapies. Herein, a current review of the latest data on the physical properties of GNPs and their effects on GNP circulation time, biodistribution and clearance, as well as their interactions with plasma proteins and the immune system, is presented. Emphasis is also given with an in depth discussion on the underlying physical and biological mechanisms of radiosensitization. Furthermore, simulation data are provided on the use of GNPs in photothermal therapy upon non-ionizing laser irradiation treatment. Finally, the results obtained from the application of GNPs at clinical trials and pre-clinical experiments in vivo are reported.

Effect of Intrinsic Noise on the Phenotype of Cell Populations Featuring Solution Multiplicity: An Artificial lac Operon Network Paradigm.

Heterogeneity in cell populations originates from two fundamentally different sources: the uneven distribution of intracellular content during cell division, and the stochastic fluctuations of regulatory molecules existing in small amounts. Discrete stochastic models can incorporate both sources of cell heterogeneity with sufficient accuracy in the description of an isogenic cell population; however, they lack efficiency when a systems level analysis is required, due to substantial computational requirements. In this work, we study the effect of cell heterogeneity in the behaviour of isogenic cell populations carrying the genetic network of lac operon, which exhibits solution multiplicity over a wide range of extracellular conditions. For such systems, the strategy of performing solely direct temporal solutions is a prohibitive task, since a large ensemble of initial states needs to be tested in order to drive the system--through long time simulations--to possible co-existing steady state solutions. We implement a multiscale computational framework, the so-called "equation-free" methodology, which enables the performance of numerical tasks, such as the computation of coarse steady state solutions and coarse bifurcation analysis. Dynamically stable and unstable solutions are computed and the effect of intrinsic noise on the range of bistability is efficiently investigated. The results are compared with the homogeneous model, which neglects all sources of heterogeneity, with the deterministic cell population balance model, as well as with a stochastic model neglecting the heterogeneity originating from intrinsic noise effects. We show that when the effect of intrinsic source of heterogeneity is intensified, the bistability range shifts towards higher extracellular inducer concentration values.

Efficient coarse simulation of a growing avascular tumor.

The subject of this work is the development and implementation of algorithms which accelerate the simulation of early stage tumor growth models. Among the different computational approaches used for the simulation of tumor progression, discrete stochastic models (e.g., cellular automata) have been widely used to describe processes occurring at the cell and subcell scales (e.g., cell-cell interactions and signaling processes). To describe macroscopic characteristics (e.g., morphology) of growing tumors, large numbers of interacting cells must be simulated. However, the high computational demands of stochastic models make the simulation of large-scale systems impractical. Alternatively, continuum models, which can describe behavior at the tumor scale, often rely on phenomenological assumptions in place of rigorous upscaling of microscopic models. This limits their predictive power. In this work, we circumvent the derivation of closed macroscopic equations for the growing cancer cell populations; instead, we construct, based on the so-called "equation-free" framework, a computational superstructure, which wraps around the individual-based cell-level simulator and accelerates the computations required for the study of the long-time behavior of systems involving many interacting cells. The microscopic model, e.g., a cellular automaton, which simulates the evolution of cancer cell populations, is executed for relatively short time intervals, at the end of which coarse-scale information is obtained. These coarse variables evolve on slower time scales than each individual cell in the population, enabling the application of forward projection schemes, which extrapolate their values at later times. This technique is referred to as coarse projective integration. Increasing the ratio of projection times to microscopic simulator execution times enhances the computational savings. Crucial accuracy issues arising for growing tumors with radial symmetry are addressed by applying the coarse projective integration scheme in a cotraveling (cogrowing) frame. As a proof of principle, we demonstrate that the application of this scheme yields highly accurate solutions, while preserving the computational savings of coarse projective integration.

Superior performance of multilayered fluoropolymer films in low voltage electrowetting.

The requirement for low operational voltage in electrowetting devices, met using thin dielectrics, is usually connected with serious material failure issues. Dielectric breakdown (visible as electrolysis) is frequently evident slightly beyond the onset of the contact angle saturation. Here, plasma-enhanced chemical vapor deposition (PECVD) is used to deposit thin fluorocarbon films prior to the spin-coating of Teflon® amorphous fluoropolymer. The resulting multilayered hydrophobic top coating improves the electrowetting performance of the stack, by showing high resistance to dielectric breakdown at high applied voltages and for continuous long term application of DC and AC voltage. Leakage current measurements during electrowetting experiments with the proposed composite coating showed that current remains fairly constant at consecutive electrowetting tests in contrast to plain Teflon® coating in which material degradation is evident by a progressive increase in the leakage current after multiple electrowetting tests. Since the proposed composite coating demonstrates increased resistance to material failure and to dielectric breakdown even at thin configurations, its integration in electrowetting devices may impact their reliability, robustness, and lifetime.

On the connection between dielectric breakdown strength, trapping of charge, and contact angle saturation in electrowetting.

Electrowetting on dielectric (EWOD) is simulated by solving the equations of capillary electrohydrostatics, by the Galerkin/finite element method. Aiming to provide reliable predictions of the voltage dependence of the apparent contact angle, close to or beyond the saturation limit, special attention is given in the treatment of the dielectric properties of the solid dielectric where the liquid sits. It is proposed that in regions where the electric field strength locally exceeds the material breakdown strength, the dielectric locally switches to a conductor. Without using any fitting parameter, the implementation of the proposed phenomenological idea realized a surprising matching of published experimental data concerning materials ranging from SiO(2) to Parylene N and Teflon. Charge trapping is naturally connected to the field-induced transition, and its distribution as well as its dependence on the applied voltage is calculated.