Fundamental Limits of Nanophotonic Design

Nanoscale fabrication techniques, computational inverse design, and fields from silicon photonics to metasurface optics are enabling transformative use of an unprecedented number of structural degrees of freedom in nanophotonics. A critical need is to understand the extreme limits to what is possible by engineering nanophotonic structures. This thesis establishes the first general theoretical framework identifying fundamental limits to light--matter interactions. It derives bounds for applications across nanophotonics, including far-field scattering, optimal wavefront shaping, optical beam switching, and wave communication, as well as the miniaturization of optical components, including perfect absorbers, linear optical analog computing units, resonant optical sensors, multilayered thin films, and high-NA metalenses. The bounds emerge from an infinite set of physical constraints that have to be satisfied by polarization fields in response to an excitation. The constraints encode power conservation in single-scenario scattering and requisite field correlations in multi-scenario scattering. The framework developed in this thesis, encompassing general linear wave scattering dynamics, offers a new way to understand optimal designs and their fundamental limits, in nanophotonics and beyond.Comment: PhD thesi

Many Physical Design Problems are Sparse QCQPs

Physical design refers to mathematical optimization of a desired objective (e.g. strong light--matter interactions, or complete quantum state transfer) subject to the governing dynamical equations, such as Maxwell's or Schrodinger's differential equations. Computing an optimal design is challenging: generically, these problems are highly nonconvex and finding global optima is NP hard. Here we show that for linear-differential-equation dynamics (as in linear electromagnetism, elasticity, quantum mechanics, etc.), the physical-design optimization problem can be transformed to a sparse-matrix, quadratically constrained quadratic program (QCQP). Sparse QCQPs can be tackled with convex optimization techniques (such as semidefinite programming) that have thrived for identifying global bounds and high-performance designs in other areas of science and engineering, but seemed inapplicable to the design problems of wave physics. We apply our formulation to prototypical photonic design problems, showing the possibility to compute fundamental limits for large-area metasurfaces, as well as the identification of designs approaching global optimality. Looking forward, our approach highlights the promise of developing bespoke algorithms tailored to specific physical design problems.Comment: 9 pages, 4 figures, plus references and Supplementary Material

SPPNet: A Single-Point Prompt Network for Nuclei Image Segmentation

Image segmentation plays an essential role in nuclei image analysis. Recently, the segment anything model has made a significant breakthrough in such tasks. However, the current model exists two major issues for cell segmentation: (1) the image encoder of the segment anything model involves a large number of parameters. Retraining or even fine-tuning the model still requires expensive computational re- sources. (2) in point prompt mode, points are sampled from the centre of the ground truth and more than one set of points is expected to achieve reliable performance, which is not efficient for practical applications. In this paper, a single-point prompt network is proposed for nuclei image segmentation, called SPPNet. We replace the original image encoder with a lightweight vision transformer. Also, an effective convolutional block is added in parallel to extract the low-level semantic information from the image and compensate for the performance degradation due to the small image encoder. We propose a new point-sampling method based on the Gaussian kernel. The proposed model is evaluated on the MoNuSeg-2018 dataset. The result demonstrated that SPPNet outperforms existing U-shape architectures and shows faster convergence in training. Compared to the segment anything model, SPPNet shows roughly 20 times faster inference, with 1/70 parameters and computational cost. Particularly, only one set of points is required in both the training and inference phases, which is more reasonable for clinical applications. The code for our work and more technical details can be found at https://github.com/xq141839/SPPNet

Bounds on the Coupling Strengths of Communication Channels and Their Information Capacities

The concept of optimal communication channels shapes our understanding of wave-based communication. Its analysis, however, always pertains to specific communication-domain geometries, without a general theory of scaling laws or fundamental limits. In this article, we derive shape-independent bounds on the coupling strengths and information capacities of optimal communication channels for any two domains that can be separated by a spherical surface. Previous computational experiments have always observed rapid, exponential decay of coupling strengths, but our bounds predict a much slower, sub-exponential optimal decay, and specific source/receiver distributions that can achieve such performance. Our bounds show that domain sizes and configurations, and not domain shapes, are the keys to maximizing the number of non-trivial communication channels and total information capacities. Applicable to general wireless and optical communication systems, our bounds reveal fundamental limits to what is possible through engineering the communication domains of electromagnetic waves

Assessment of Dry Epidermal Electrodes for Long-Term Electromyography Measurements

Commercially available electrodes can only provide quality surface electromyography (sEMG) measurements for a limited duration due to user discomfort and signal degradation, but in many applications, collecting sEMG data for a full day or longer is desirable to enhance clinical care. Few studies for long-term sEMG have assessed signal quality of electrodes using clinically relevant tests. The goal of this research was to evaluate flexible, gold-based epidermal sensor system (ESS) electrodes for long-term sEMG recordings. We collected sEMG and impedance data from eight subjects from ESS and standard clinical electrodes on upper extremity muscles during maximum voluntary isometric contraction tests, dynamic range of motion tests, the Jebsen Taylor Hand Function Test, and the Box & Block Test. Four additional subjects were recruited to test the stability of ESS signals over four days. Signals from the ESS and traditional electrodes were strongly correlated across tasks. Measures of signal quality, such as signal-to-noise ratio and signal-to-motion ratio, were also similar for both electrodes. Over the four-day trial, no significant decrease in signal quality was observed in the ESS electrodes, suggesting that thin, flexible electrodes may provide a robust tool that does not inhibit movement or irritate the skin for long-term measurements of muscle activity in rehabilitation and other applications. Keywords: neurological injury; stroke rehabilitation; impedance measurements; Jebsen Taylor Hand Function Test; Box & Block; signal-to-noise ratioNational Institute of Biomedical Imaging and Bioengineering (U.S.) (Grant R01EB021935

A multifunctional micropore-forming bioink with enhanced anti-bacterial and anti-inflammatory properties

Three-dimensional (3D) bioprinting has emerged as an enabling tool for various biomedical applications, such as tissue regeneration and tissue model engineering. To this end, the development of bioinks with multiple functions plays a crucial role in the applications of 3D bioprinting technologies. In this study, we propose a new bioink based on two immiscible aqueous phases of gelatin methacryloyl (GelMA) and dextran, further endowed with anti-bacterial and anti-inflammatory properties. This micropore-forming GelMA-dextran (PGelDex) bioink exhibited excellent printability with vat-polymerization, extrusion, and handheld bioprinting methods. The porous structure was confirmed after bioprinting, which promoted the spreading of the encapsulated cells, exhibiting the exceptional cytocompatibility of this bioink formulation. To extend the applications of such a micropore-forming bioink, interleukin-4 (IL-4)-loaded silver-coated gold nanorods (AgGNRs) and human mesenchymal stem cells (MSCs) were simultaneously incorporated, to display synergistic anti-infection behavior and immunomodulatory function. The results revealed the anti-bacterial properties of the AgGNR-loaded PGelDex bioink for both Gram-negative and Gram-positive bacteria. The data also indicated that the presence of IL-4 and MSCs facilitated macrophage M2-phenotype differentiation, suggesting the potential anti-inflammatory feature of the bioink. Overall, this unique anti-bacterial and immunomodulatory micropore-forming bioink offers an effective strategy for the inhibition of bacterial-induced infections as well as the ability of immune-regulation, which is a promising candidate for broadened tissue bioprinting applications