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Creators/Authors contains: "Luo T."

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  1. Free, publicly-accessible full text available April 1, 2023
  2. The proposed approach, BJORK, provides a robust and generalizable workflow to jointly optimize non-Cartesian sampling patters and a physics-informed reconstruction. Several approaches, including re-parameterization of trajectories, multi-level optimization, and non-Cartesian unrolled neural networks, are introduced to improve training effect and avoid sub-optimal local minima. The invivo experiments show that the networks and trajectories learned on simulation dataset are transferable to the real acquisition even with different parameter-weighted MRI contrasts and noise-levels, and demonstrate improved image quality compared with previous learning-based and model-based trajectory optimization methods.
  3. Optical pulling force (OPF) can make a nanoparticle (NP) move against the propagation direction of the incident light. Long-distance optical pulling is highly desired for nano-object manipulation, but its realization remains challenging. We propose an NP-in-cavity structure that can be pulled by a single plane wave to travel long distances when the spherical cavity wrapping the NP has a refractive index lower than the medium. An electromagnetic multipole analysis shows that NPs made of many common materials can receive the OPF inside a lower index cavity. Using a silica-Au core-shell NP that is encapsulated by a plasmonic nanobubble, we experimentally demonstrate that a single laser can pull the Au NP-in-nanobubble structure for ~0.1 mm. These results may lead to practical applications that can use the optical pulling of NP, such as optically driven nanostructure assembly and nanoswimmers.