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We use micro-bubble based thermo-optical tweezers to simultaneously synthesize, dope, and pattern conducting polymers to obtain unprecedented conductivity values.

We have designed a supramolecularly bound multi-component catalytic material based on a soft oxometalate (SOM) and a porous organic framework (POF) material, which shows high catalytic conversion efficiency.

A microbubble nucleated due to the absorption of a tightly focused laser at the interface of a liquid−solid substrate enables directed and irreversible self-assembly of mesoscopic particles dispersed in the liquid at the bubble base. This phenomenon has facilitated a new microlithography technique which has grown rapidly over the past decade and can now reliably pattern a vast range of soft materials and colloids, ranging from polymers to metals to proteins. In this review, we discuss the science behind this technology and the present state-of-the-art. Thus, we describe the physics of the self-assembly driven by the bubble, the techniques for generating complex mesoarchitectures, both discrete and continuous, and their properties, and the various applications demonstrated in plastic electronics, site-specific catalysis, and biosensing. Finally, we describe a roadmap for the technique to achieve its potential of successfully patterning "everything" mesoscopic and the challenges that lie therein.

We demonstrate that the active thermocapillary stresses induced by multiple microbubbles offer simple routes to directed self-assembly and complex but controllable micromanipulation of mesoscopic colloidal particles embedded in a liquid. The microbubbles are nucleated on a liquid-glass interface using optical tweezers. The flow around a single bubble causes self-assembly of the particles in rings at the bubble-base, while an asymmetric temperature profile generated across the bubble interface breaks the azimuthal symmetry of the flow, and induces simultaneous accumulation and repulsion of particles at different axial planes with respect to the bubble. The flows due to two adjacent bubbles leads to more diverse effects including the sorting of particles, and to local vorticity that causes radial and axial rotation of the particles -the latter being obtained for the first time using optical tweezers. The sorting is enabled by nucleating the bubbles on spatially discrete temperature profiles, while the vorticity is generated by nucleating them in the presence of a temperature gradient which once again causes a strong symmetry-breaking in the azimuthal flow. The flow profiles obtained in the experiments are explained by analytical solutions or qualitative explanations of the associated thermocapillary problem employing the Stokes and heat equations.

We study the growth of a homogeneously nucleated micro-bubble amidst convective flows in water superheated close to the critical point.

In this work, we have developed linear micro-patterns of phosphotungstic acid soft oxometalate (SOM) and perylene (as fluorophore) hybrid composite on a glass substrate using a thermo-optical tweezers set-up, and used it for sensing of biologically important molecules such as glucose, uric acid and ascorbic acid. Bulk scale studies on the SOM-fluorophore hybrid were initially performed to optimize the fabrication of the pattern. The aqueous dispersion of the hybrid composite [a] EFAML, College

Estimating entropy production directly from experimental trajectories is of great current interest but often requires a large amount of data or knowledge of the underlying dynamics. In this paper, we propose a minimal strategy using the short-time Thermodynamic Uncertainty Relation (TUR) by means of which we can simultaneously and quantitatively infer the thermodynamic force field acting on the system and the (potentially exact) rate of entropy production from experimental short-time trajectory data. We benchmark this scheme first for an experimental study of a colloidal particle system where exact analytical results are known, prior to studying the case of a colloidal particle in a hydrodynamical flow field, where neither analytical nor numerical results are available. In the latter case, we build an effective model of the system based on our results. In both cases, we also demonstrate that our results match with those obtained from another recently introduced scheme.