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We describe the use of resonant amplification of light propelling forces for selective separation of fluid-suspended dielectric microparticles. The force amplification and the selectivity of the method is achieved using the whispering gallery mode resonances of the microparticles. The selectivity is determined by the inverse of the quality factor (Q) of the resonances in liquid (with Q ∼ 10^4 -10^6). We demonstrate that the evanescent field around a tapered optical fiber fed with ∼ 20 mW power from a 1064 nm laser can selectively move polystyrene microspheres of up to 20 μm in diameter through distances of more than 50 μm, thereby establishing that the technique is sufficient for efficient separation.
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Controlled microparticle separation using whispering gallery mode forces
There is a wide variety of applications that require sorting and separation of micro- particles from a large cluster of similar objects. Existing methods can distinguish micro-particles by their bulk properties, such as their size, density, and electric polarizability. These methods, however, are not selective with respect to the individual geometry of the particles. In this work, we focus on the use of a resonance effect between a microparticle and an evanescent light field known as the Whispering Gallery Mode (WGM) force. The WGM force is highly sensitive to the radius of the particle and is both controllable and tunable. In this paper, we explore through simulation the design of a WGM-based device for micro-particle separation. In this device, particles flow in through an inlet and are carried over two actuation regions given by waveguides carrying laser light to generate the evanescent field. Particles are observed by a camera, allowing for feedback control on the power of the lasers. While the basic control structure is simple, there are several challenges, including unknown disturbances to the fluid flow, limited laser power, and uni-directional control over each actuation region. We combine Expectation Maximization with Kalman filtering to both estimate the unknown disturbance and filter the measurements into a position estimate. We then develop simple hybrid controllers and compare them to the ideal setting (without any constraints) based on a Linear–Quadratic–Gaussian (LQG) control approach.
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- Award ID(s):
- 1661586
- PAR ID:
- 10186976
- Date Published:
- Journal Name:
- IFAC World Congress
- ISSN:
- 2405-8963
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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