Effect of contact angle hysteresis on thermocapillary droplet actuation

Open microfluidic devices based on actuation techniques such as electrowetting, dielectrophoresis, or thermocapillary stresses require controlled motion of small liquid droplets on the surface of glass or silicon substrates. In this article we explore the physical mechanisms affecting thermocapillary migration of droplets generated by surface temperature gradients on the supporting substrate. Using a combination of experiment and modeling, we investigate the behavior of the threshold force required for droplet mobilization and the speed after depinning as a function of the droplet size, the applied thermal gradient and the liquid material parameters. The experimental results are well described by a hydrodynamic model based on earlier work by Ford and Nadim. The model describes the steady motion of a two-dimensional droplet driven by thermocapillary stresses including contact angle hysteresis. The results of this study highlight the critical role of chemical or mechanical hysteresis and the need to reduce this retentive force for minimizing power requirements in microfluidic devices

Capacitive sensing of droplets for microfluidic devices based on thermocapillary actuation

The design and performance of a miniaturized coplanar capacitive sensor is presented whose electrode arrays can also function as resistive microheaters for thermocapillary actuation of liquid films and droplets. Optimal compromise between large capacitive signal and high spatial resolution is obtained for electrode widths comparable to the liquid film thickness measured, in agreement with supporting numerical simulations which include mutual capacitance effects. An interdigitated, variable width design, allowing for wider central electrodes, increases the capacitive signal for liquid structures with non-uniform height profiles. The capacitive resolution and time response of the current design is approximately 0.03 pF and 10 ms, respectively, which makes possible a number of sensing functions for nanoliter droplets. These include detection of droplet position, size, composition or percentage water uptake for hygroscopic liquids. Its rapid response time allows measurements of the rate of mass loss in evaporating droplets

A Novel FastICA Method for the Reference-based Contrast Functions

This paper deals with the efficient optimization problem of Cumulant-based contrast criteria in the Blind Source Separation (BSS) framework, in which sources are retrieved by maximizing the Kurtosis contrast function. Combined with the recently proposed reference-based contrast schemes, a new fast fixed-point (FastICA) algorithm is proposed for the case of linear and instantaneous mixture. Due to its quadratic dependence on the number of searched parameters, the main advantage of this new method consists in the significant decrement of computational speed, which is particularly striking with large number of samples. The method is essentially similar to the classical algorithm based on the Kurtosis contrast function, but differs in the fact that the reference-based idea is utilized. The validity of this new method was demonstrated by simulations

Possible approach to improve sensitivity of a Michelson interferometer

We propose a possible approach to achieve an 1/N sensitivity of Michelson interferometer by using a properly designed random phase modulation. Different from other approaches, the sensitivity improvement does not depend on increasing optical powers or utilizing the quantum properties of light. Moreover the requirements for optical losses and the quantum efficiencies of photodetection systems might be lower than the quantum approaches and the sensitivity improvement is frequency independent in all detection band.Comment: 8 pages, 3 figures, new versio

Segmentation, Reconstruction, and Analysis of Blood Thrombus Formation in 3D 2-Photon Microscopy Images

We study the problem of segmenting, reconstructing, and analyzing the structure growth of thrombi (clots) in blood vessels in vivo based on 2-photon microscopic image data. First, we develop an algorithm for segmenting clots in 3D microscopic images based on density-based clustering and methods for dealing with imaging artifacts. Next, we apply the union-of-balls (or alpha-shape) algorithm to reconstruct the boundary of clots in 3D. Finally, we perform experimental studies and analysis on the reconstructed clots and obtain quantitative data of thrombus growth and structures. We conduct experiments on laser-induced injuries in vessels of two types of mice (the wild type and the type with low levels of coagulation factor VII) and analyze and compare the developing clot structures based on their reconstructed clots from image data. The results we obtain are of biomedical significance. Our quantitative analysis of the clot composition leads to better understanding of the thrombus development, and is valuable to the modeling and verification of computational simulation of thrombogenesis

An Efficient Algorithm by Kurtosis Maximization in Reference-Based Framework

This paper deals with the optimization of kurtosis for complex-valued signals in the independent component analysis (ICA) framework, where source signals are linearly and instantaneously mixed. Inspired by the recently proposed reference-based contrast schemes, a similar contrast function is put forward, based on which a new fast fixed-point (FastICA) algorithm is proposed. The new optimization method is similar in spirit to the former classical kurtosis-based FastICA algorithm but differs in the fact that it is much more efficient than the latter in terms of computational speed, which is significantly striking with large number of samples. The performance of this new algorithm is confirmed through computer simulations

Fractal-based autonomous partial discharge pattern recognition method for MV motors

On-line partial discharge (PD) monitoring is being increasingly adopted to improve the asset management and maintenance of medium-voltage (MV) motors. This study presents a novel method for autonomous analysis and classification of motor PD patterns in situations where a phase-reference voltage waveform is not available. The main contributions include a polar PD (PPD) pattern and a fractal theory-based autonomous PD recognition method. PPD pattern that is applied to convert the traditional phase-resolved PD pattern into a circular form addresses the lack of phase information in on-line PD monitoring system. The fractal theory is then presented in detail to address the task of discrimination of 6 kinds of single source and 15 kinds of multi-source PD patterns related to motors, as outlined in IEC 60034. The classification of known and unknown defects is calculated by a method known as centre score. Validation of the proposed method is demonstrated using data from laboratory experiments on three typical PD geometries. This study also discusses the application of the proposed techniques with 24 sets of on-site PD measurement data from 4 motors in 2 nuclear power stations. The results show that the proposed method performs effectively in recognising not only the single-source PD but also multi-source PDs

On the Renormalizability of Theories with Gauge Anomalies

We consider the detailed renormalization of two (1+1)-dimensional gauge theories which are quantized without preserving gauge invariance: the chiral and the "anomalous" Schwinger models. By regularizing the non-perturbative divergences that appear in fermionic Green's functions of both models, we show that the "tree level" photon propagator is ill-defined, thus forcing one to use the complete photon propagator in the loop expansion of these functions. We perform the renormalization of these divergences in both models to one loop level, defining it in a consistent and semi-perturbative sense that we propose in this paper.Comment: Final version, new title and abstract, introduction and conclusion rewritten, detailed semiperturbative discussion included, references added; to appear in International Journal of Modern Physics

Elasticity-Driven Nanoscale Electronic Structure in Superconductors

The effects of long-range anisotropic elastic deformations on electronic structure in superconductors are analyzed within the framework of the Bogoliubov-de Gennes equations. Cases of twin boundaries and isolated defects are considered as illustrations. We find that the superconducting order parameter is depressed in the regions where pronounced lattice deformation occurs. The calculated local density of states suggests that the electronic structure is strongly modulated in response to lattice deformations, and propagates to longer distances. In particular, this allows the trapping of low-lying quasiparticle states around defects. Some of our predictions can be directly tested by STM experiments.Comment: 5 pages, 5 figures, reference added, accepted to Physical Review Letter