Clogging and Jamming of Colloidal Monolayers Driven Across a Disordered Landscape

We experimentally investigate the clogging and jamming of interacting paramagnetic colloids driven through a quenched disordered landscape of fixed obstacles. When the particles are forced to cross a single aperture between two obstacles, we find an intermittent dynamics characterized by an exponential distribution of burst size. At the collective level, we observe that quenched disorder decreases the particle ow, but it also greatly enhances the "faster is slower" effect, that occurs when increasing the particle speed. Further, we show that clogging events may be controlled by tuning the pair interactions between the particles during transport, such that the colloidal ow decreases for repulsive interactions, but increases for anisotropic attraction. We provide an experimental test-bed to investigate the crucial role of disorder on clogging and jamming in driven microscale matter

Universal dynamical properties preclude standard clustering in a large class of biochemical data

Motivation: Clustering of chemical and biochemical data based on observed features is a central cognitive step in the analysis of chemical substances, in particular in combinatorial chemistry, or of complex biochemical reaction networks. Often, for reasons unknown to the researcher, this step produces disappointing results. Once the sources of the problem are known, improved clustering methods might revitalize the statistical approach of compound and reaction search and analysis. Here, we present a generic mechanism that may be at the origin of many clustering difficulties. Results: The variety of dynamical behaviors that can be exhibited by complex biochemical reactions on variation of the system parameters are fundamental system fingerprints. In parameter space, shrimp-like or swallow-tail structures separate parameter sets that lead to stable periodic dynamical behavior from those leading to irregular behavior. We work out the genericity of this phenomenon and demonstrate novel examples for their occurrence in realistic models of biophysics. Although we elucidate the phenomenon by considering the emergence of periodicity in dependence on system parameters in a low-dimensional parameter space, the conclusions from our simple setting are shown to continue to be valid for features in a higher-dimensional feature space, as long as the feature-generating mechanism is not too extreme and the dimension of this space is not too high compared with the amount of available data. Availability and implementation: For online versions of super-paramagnetic clustering see http://stoop.ini.uzh.ch/research/clustering. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

Clogging and jamming of colloidal monolayers driven across disordered landscapes

Understanding microscale transport across heterogeneous landscapes is relevant for many phenomena in condensed matter physics, from pinning of vortices in dirty superconductors, to electrons on liquid helium, skyrmions, and active matter. Here, we experimentally investigate the clogging and jamming of field tunable interacting colloids driven through a quenched disordered landscape of fixed obstacles. We focus on the emergent phenomenon of clogging, that has been the matter of much investigation at the level of a single aperture in macroscopic and granular systems. With our colloidal system, we find that quenched disorder significantly alters the particle flow, and we provide the experimental observation of the 'Faster is Slower' effect with quenched disorder, that occurs when increasing the particle speed. Further, we show that clogging events may be controlled by tuning the pair interactions during transport, such that the colloidal flow decreases for repulsive interactions, but it increases for anisotropic attraction

Emergent colloidal currents across ordered and disordered landscapes

Many-particle effects in driven systems far from equilibrium lead to a rich variety of emergent phenomena. Their classification and understanding often require suitable model systems. Here we show that microscopic magnetic particles driven along ordered and defective lattices by a traveling wave potential display a nonlinear current-density relationship, which arises from the interplay of two effects. The first one originates from particle sizes nearly commensurate with the substrate in combination with attractive pair interactions. It governs the colloidal current at small densities and leads to a superlinear increase. We explain such effect by an exactly solvable model of constrained cluster dynamics. The second effect is interpreted to result from a defect-induced breakup of coherent cluster motion, leading to jamming at higher densities. Finally, we demonstrate that a lattice gas model with parallel update is able to capture the experimental findings for this complex many-body system

Collective directional locking of colloidal monolayers on a periodic substrate

We investigate the directional locking effects that arise when a monolayer of paramagnetic colloidal particles is driven across a triangular lattice of magnetic bubbles. We use an external rotating magnetic field to generate a two-dimensional traveling wave ratchet forcing the transport of particles along a direction that intersects two crystallographic axes of the lattice. We find that, while single particles show no preferred direction, collective effects induce transversal current and directional locking at high density via a spontaneous symmetry breaking. The colloidal current may be polarized via an additional bias field that makes one transport direction energetically preferred

Charge Noise in Organic Electrochemical Transistors

Organic electrochemical transistors (OECTs) are increasingly studied as transducers in sensing applications. While much emphasis has been placed on analyzing and maximizing the OECT signal, noise has been mostly ignored, although it determines the resolution of the sensor. The major contribution to the noise in sensing devices is the 1/f noise, dominant at low frequency. In this work, we demonstrate that the 1/f noise in OECTs follows a charge-noise model, which reveals that the noise is due to charge fuctuations in proximity or within the bulk of the channel material. We present the noise scaling behavior with gate voltage, channel dimensions and polymer thickness. Our results suggest the use of large area channels in order to maximize the signal-to-noise-ratio (SNR) for biochemical and electrostatic sensing applications. Comparison with literature shows that the magnitude of the noise in OECTs is similar to that observed in graphene transistors, and only slightly higher compared to Carbon nanotubes and Silicon nanowire devices. In a model ion-sensing experiment with OECTs, we estimate crucial parameters such as the characteristic SNR and corresponding limit of detection

Implementing Silicon Nanoribbon Field-Effect Transistors as Arrays for Multiple Ion Detection

Ionic gradients play a crucial role in the physiology of the human body, ranging from metabolism in cells to muscle contractions or brain activities. To monitor these ions, inexpensive, label-free chemical sensing devices are needed. Field-effect transistors (FETs) based on silicon (Si) nanowires or nanoribbons (NRs) have a great potential as future biochemical sensors as they allow for the integration in microscopic devices at low production costs. Integrating NRs in dense arrays on a single chip expands the field of applications to implantable electrodes or multifunctional chemical sensing platforms. Ideally, such a platform is capable of detecting numerous species in a complex analyte. Here, we demonstrate the basis for simultaneous sodium and fluoride ion detection with a single sensor chip consisting of arrays of gold-coated SiNR FETs. A microfluidic system with individual channels allows modifying the NR surfaces with self-assembled monolayers of two types of ion receptors sensitive to sodium and fluoride ions. The functionalization procedure results in a differential setup having active fluoride-and sodium-sensitive NRs together with bare gold control NRs on the same chip. Comparing functionalized NRs with control NRs allows the compensation of non-specific contributions from changes in the background electrolyte concentration and reveals the response to the targeted species

Competing surface reactions limiting the performance of ion-sensitive field-effect transistors

© 2015 Elsevier B.V. All rights reserved.Ion-sensitive field-effect transistors based on silicon nanowires are promising candidates for the detection of chemical and biochemical species. These devices have been established as pH sensors thanks to the large number of surface hydroxyl groups at the gate dielectrics which makes them intrinsically sensitive to protons. To specifically detect species other than protons, the sensor surface needs to be modified. However, the remaining hydroxyl groups after functionalization may still limit the sensor response to the targeted species. Here, we describe the influence of competing reactions on the measured response using a general site-binding model. We investigate the key features of the model with a real sensing example based on gold-coated nanoribbons functionalized with a self-assembled monolayer of calcium-sensitive molecules. We identify the residual pH response as the key parameter limiting the sensor response. The competing effect of pH or any other relevant reaction at the sensor surface has therefore to be included to quantitatively understand the sensor response and prevent misleading interpretations