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Register a new userTemplate Dissolution Interfacial Patterning of Single Colloids for Nanoelectrochemistry and Nanosensing
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Deterministic positioning and assembly of colloidal nanoparticles (NPs) onto substrates is a core requirement and a promising alternative to top down lithography to create functional nanostructures and nanodevices with intriguing optical, electrical, and catalytic features. Capillary-assisted particle assembly (CAPA) has emerged as an attractive technique to this end, as it allows controlled and selective assembly of a wide variety of NPs onto predefined topographical templates using capillary forces. One critical issue with CAPA, however, lies in its final printing step, where high printing yields are possible only with the use of an adhesive polymer film. To address this problem, we have developed a template dissolution interfacial patterning (TDIP) technique to assemble and print single colloidal AuNP arrays onto various dielectric and conductive substrates in the absence of any adhesion layer, with printing yields higher than 98%. The TDIP approach grants direct access to the interface between the AuNP and the target surface, enabling the use of colloidal AuNPs as building blocks for practical applications. The versatile applicability of TDIP is demonstrated by the creation of direct electrical junctions for electro- and photoelectrochemistry and nanoparticle-on-mirror geometries for single particle molecular sensing.
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We study how dispersions of colloidal particles in a cholesteric liquid crystal behave under a time-dependent electric field. By controlling the amplitude and shape of the applied field wave, we show that the system can be reproducibly driven out of equilibrium through different kinetic pathways and navigated through a glassy-like free energy landscape encompassing many competing metastable equilibria. Such states range from simple Saturn rings to complex structures featuring amorphous defect networks, or stacks of disclination loops. A non-equilibrium electric field can also trigger the alignment of particles into columnar arrays, through defect-mediated force impulses, or their repositioning within a plane. Our results are promising in terms of providing new avenues towards controlled patterning and self-assembly of soft colloid-liquid crystal composite materials.
Ultrasoft colloidal particle fluctuates due to its flexibility. Such fluctuation is essential for colloidal structure and dynamics, but is challenging to quantify experimentally. We use dendrimers as a model system to study the fluctuation of ultrasoft colloids. By considering the dynamic polydispersity in the small-angle neutron scattering (SANS) model, and introducing the fluctuation of invasive water into the contrast in SANS, we reveal the fluctuating amplitudes of the size and shape of the dendrimer of generation 6 at finite concentrations. The size fluctuation is suppressed while the shape fluctuation increases as the weight fraction of dendrimers passes 11%. With neutron spin echo data, we suggest that such crossover originates from the competition between the inter- and intra-particle dynamics. Further investigation on lower-generation samples shows a contrary result, which suggests a structural basis for these dynamic phenomena.
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Vertically vibrated rod-shaped granular materials confined to quasi-2D containers self organize into distinct patterns. We find, consistent with theory and simulation, a density dependent isotropic-nematic transition. Along the walls, rods interact sterically to form a wetting layer. For high rod densities, complex patterns emerge as a result of competition between bulk and boundary alignment. A continuum elastic energy accounting for nematic distortion and local wall anchoring reproduces the structures seen experimentally.
Soft nanocomposites represent both a theoretical and an experimental challenge due to the high number of the microscopic constituents that strongly influence the behaviour of the systems. An effective theoretical description of such systems invokes a reduction of the degrees of freedom to be analysed, hence requiring the introduction of an efficient, quantitative, coarse-grained description. We here report on a novel coarse graining approach based on a set of transferable potentials that quantitatively reproduces properties of mixtures of linear and star-shaped homopolymeric nanocomposites. By renormalizing groups of monomers into a single effective potential between a $f$-functional star polymer and an homopolymer of length $N_0$, and through a scaling argument, it will be shown how a substantial reduction of the to degrees of freedom allows for a full quantitative description of the system. Our methodology is tested upon full monomer simulations for systems of different molecular weight, proving its full predictive potential.
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