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

Understanding silicon nanowire field-effect transistors for biochemical sensing

There is an ever increasing need for inexpensive chemical and biochemical sensors for medical diagnostics, drug screening as well as environmental monitoring. State-of-the-art methods require either expensive or time-consuming labeling and are not suitable for large-scale integration. Advances in biotechnology, microfluidics and micro- and nanotechnology have led to various approaches of micro-analytical systems. In particular systems based on silicon field-effect transistors (Si FETs) have a great potential for biochemical sensing due to their potentially cheap fabrication in a CMOS-compatible process and simple electronic readout. Thereby, the gate oxide material of the FET is in direct contact with the analyte solution, leading to the ion-sensitive field-effect transistor (ISFET). The detection principle of ISFETs is based on the change of the transistor current caused by charges adsorbed at the sensor surface. It has been suggested recently that by downscaling the devices to the nanoscale, increased sensitivities can be expected. In particular, ISFETs based on silicon nanowires (Si NWs) are therefore intensively studied. Despite the achievements obtained in the last years, commercial products based on ISFETs are using the device as a pH sensor only. The reason for this development lies in the incomplete understanding of the complex interface between the electrolyte and the solid-state sensor as well as the difficulties related to the design of surfaces which selectively bind a targeted analyte. In this PhD project, we address these points by studying arrays of ISFETs based on silicon nanowires (Si NWs) fabricated by a top-down lithography approach and investigate their potential as an integrable sensing platform. First we characterize the devices and analyze their pH response. We find a response to pH at the fundamental (Nernst) limit, due to the special properties of the gate oxide materials used for the devices. We further demonstrate that the sensor signal is not affected by the width of the NWs, i.e. enhanced sensing is not observed for nanoscale devices. However, we reveal that the low-frequency noise of the devices decreases for increasing NW width, an aspect which has to be considered when ultimate integration is targeted. For the specific detection of ionic species, the sensor surface needs to be modified with functional groups, which selectively bind the target analyte. Unfortunately, the high pH sensitivity of oxide surfaces greatly complicates the detection of any target analyte other than pH. To circumvent this problem, we propose the use of an additional coating with a material with minimal sensitivity to pH. We find that gold is a promising candidate easily applied for this purpose. The gold layer allows immobilizing ligands via the well-established thiol-based chemistry thereby providing a platform suitable for surface functionalization. Using the additional gold layer, we demonstrate the successful detection of different ions such as sodium, calcium and fluoride ions with a differential setup having both functionalized and control NWs on the same sample. Furthermore, we find that the residual pH response of the gold layer still influences the detection of the targeted species by affecting the effective binding constant via the surface potential. To take this effect into account, an extended site binding model is proposed. Finally, we show that SiNWs have the potential to even monitor binding kinetics of ligand-protein systems and we obtain concentration dependent signals for a clinically relevant protein

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

Enhanced diffusion and non-Gaussian dynamics in driven magnetic nanoparticles

We investigate the out-of-equilibrium dynamics of paramagnetic colloidal nanoparticles driven above a triangular lattice of cylindrical ferromagnetic domains. We use an external precessing magnetic field to create a dynamic energy landscape which propels the particles along complex trajectories, characterized by an alternation of periodic orbital motion (localization) and stochastic particle jumping between nearest domains. We show that this system is populated by localized particles as well as delocalized (transported) ones, and tune their relative fraction via the field cone angle. Our driven system presents enhanced diffusive dynamics and an emergent non-Gaussian behavior which can be explained by considering two coexisting dynamic transport modes

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