Applications of soft matter physics to design, fabrication, and characterization of soft robots and actuators.
Soft matter physicists have pioneered many exciting phenomena and novel methods from self assembly to microfluidics and understood these through the application of fundamental physical principles. Physicists have suggested many interesting potential technological applications that these newly observed phenomena and methods enable. I am interested in applying my background in soft matter physics to transferring new developments in the field to realizing new technological applications. In the process of developing new materials and methods, new questions arise regarding the fundamental physics and often leads to further potential applications. Using materials and methods such as liquid crystals and colloidal self assembly I hope to create new actuation mechanisms and soft robots while developing new physics to better understand these systems.
Ph.D. Physics, University of Pennsylvania, USA, 2017
Proceedings of the National Academy of Sciences, 117(21):11306-11313, 2020 (article)
Self-assembly is a ubiquitous process that can generate complex and functional structures via local interactions among a large set of simpler components. The ability to program the self-assembly pathway of component sets elucidates fundamental physics and enables alternative competitive fabrication technologies. Reprogrammability offers further opportunities for tuning structural and material properties but requires reversible selection from multistable self-assembling patterns, which remains a challenge. Here, we show statistical reprogramming of two-dimensional (2D), noncompact self-assembled structures by the dynamic confinement of orbitally shaken and magnetically repulsive millimeter-scale particles. Under a constant shaking regime, we control the rate of radius change of an assembly arena via moving hard boundaries and select among a finite set of self-assembled patterns repeatably and reversibly. By temporarily trapping particles in topologically identified stable states, we also demonstrate 2D reprogrammable stiffness and three-dimensional (3D) magnetic clutching of the self-assembled structures. Our reprogrammable system has prospective implications for the design of granular materials in a multitude of physical scales where out-of-equilibrium self-assembly can be realized with different numbers or types of particles. Our dynamic boundary regulation may also enable robust bottom-up control strategies for novel robotic assembly applications by designing more complex spatiotemporal interactions using mobile robots.
Proceedings of the National Academy of Sciences, National Acad Sciences, 2020 (article)
Untethered dynamic shape programming and control of soft materials have significant applications in technologies such as soft robots, medical devices, organ-on-a-chip, and optical devices. Here, we present a solution to remotely actuate and move soft materials underwater in a fast, efficient, and controlled manner using photoresponsive liquid crystal gels (LCGs). LCG constructs with engineered molecular alignment show a low and sharp phase-transition temperature and experience considerable density reduction by light exposure, thereby allowing rapid and reversible shape changes. We demonstrate different modes of underwater locomotion, such as crawling, walking, jumping, and swimming, by localized and time-varying illumination of LCGs. The diverse locomotion modes of smart LCGs can provide a new toolbox for designing efficient light-fueled soft robots in fluid-immersed media.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems