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  1. Free, publicly-accessible full text available August 1, 2025
  2. In this Letter a novel, to our knowledge, approach for near-infrared (NIR) fluorescence portable confocal microscopy is introduced, aiming to enhance fluorescence imaging of biological samples in the NIR-II window. By integrating a superconducting nanowire single-photon detector (SNSPD) into a confocal microscopy, we have significantly leveraged the detection efficiency of the NIR-II fluorescence signal from indocyanine green (ICG), an FDA-approved dye known for its NIR-II fluorescence capabilities. The SNSPD, characterized by its extremely low dark count rate and optimized NIR system detection efficiency, enables the excitation of ICG with 1 mW and the capture of low-light fluorescence signals from deep regions (up to 512 µm). Consequently, our technique was able to produce high-resolution images of bio samples with a superior signal-to-noise ratio, making a substantial advancement in the field of fluorescence microscopy and offering a promising opportunity for future clinical study.

     
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  3. We demonstrate the fabrication of fiber-optic Fabry–Perot interferometer (FPI) temperature sensors by bonding a small silicon diaphragm to the tip of an optical fiber using low melting point glass powders heated by a 980 nm laser on an aerogel substrate. The heating laser is delivered to the silicon FPI using an optical fiber, while the silicon temperature is being monitored using a 1550 nm white-light system, providing localized heating with precise temperature control. The use of an aerogel substrate greatly improves the heating efficiency by reducing the thermal loss of the bonding parts to the ambient environment. A desirable temperature for bonding can be achieved with relatively small heating laser power. The bonding process is carried out in an open space at room temperature for convenient optical alignment. The precise temperature control ensures minimum perturbation to the optical alignment and no induced thermal damage to the optical parts during the bonding process. For demonstration, we fabricated a low-finesse and high-finesse silicon FPI sensor and characterized their measurement resolution and temperature capability. The results show that the fabrication method has a good potential for high-precision fabrication of fiber-optic sensors.

     
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  4. Wavelength tracking is a commonly used method for demodulating fiber-optic Fabry–Perot interferometric sensors due to its high resolution and straightforward implementation. We report the observation of random spurious jumps in a commonly used wavelength-tracking method based on curve fitting. These jumps were unrelated to the phase ambiguity of the spectral fringes and led to measurement errors. We analyzed the origin of the spurious jumps through Monte Carlo simulations where the fringe valley positions were obtained using polynomial curve fittings. The simulation results show that the spurious jumps arose mainly from the systematic errors of the curve-fitting function for modeling the sensor spectrum and manifested themselves by the changes in the pixel set for curve fitting. The centroid method also suffered from the spurious jumps. We proposed a modified correlation demodulation method free of the spurious jumps. In this method, the information of the measurand was obtained through the correlation between the measured sensor spectral frames and a sufficiently large number of calibrated frames of the sensor over the measurement range. The simulation and experimental results show that the modified correlation method was free of the spurious jumps encountered in the regular wavelength tracking. The resolution of the method was also studied and compared with the curve-fitting method.

     
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  5. We theoretically study the spectral characteristics and noise performance of wavelength-interrogated fiber-optic sensors based on an extrinsic Fabry–Perot (FP) interferometer (EFPI) formed by thin metal mirrors. We develop a model and use it to analyze the effect of key sensor parameters on the visibility and spectral width of the sensors, including the beam width of the incident light, metal coating film thickness, FP cavity length, and wedge angle of the two mirrors. Through Monte Carlo simulations, we obtain an empirical equation that can be used to estimate the wavelength resolution from the visibility and spectral width, which can be used as a figure-of-merit that is inherent to the sensor and independent on the system noises. The work provides a useful tool for designing, constructing, and interrogating high-resolution fiber-optic EFPI sensors.

     
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  6. Abstract Background The helmeted honeyeater (Lichenostomus melanops cassidix) is a Critically Endangered bird endemic to Victoria, Australia. To aid its conservation, the population is the subject of genetic rescue. To understand, monitor, and modulate the effects of genetic rescue on the helmeted honeyeater genome, a chromosome-length genome and a high-density linkage map are required. Results We used a combination of Illumina, Oxford Nanopore, and Hi-C sequencing technologies to assemble a chromosome-length genome of the helmeted honeyeater, comprising 906 scaffolds, with length of 1.1 Gb and scaffold N50 of 63.8 Mb. Annotation comprised 57,181 gene models. Using a pedigree of 257 birds and 53,111 single-nucleotide polymorphisms, we obtained high-density linkage and recombination maps for 25 autosomes and Z chromosome. The total sex-averaged linkage map was 1,347 cM long, with the male map being 6.7% longer than the female map. Recombination maps revealed sexually dimorphic recombination rates (overall higher in males), with average recombination rate of 1.8 cM/Mb. Comparative analyses revealed high synteny of the helmeted honeyeater genome with that of 3 passerine species (e.g., 32 Hi-C scaffolds mapped to 30 zebra finch autosomes and Z chromosome). The genome assembly and linkage map suggest that the helmeted honeyeater exhibits a fission of chromosome 1A into 2 chromosomes relative to zebra finch. PSMC analysis showed a ∼15-fold decline in effective population size to ∼60,000 from mid- to late Pleistocene. Conclusions The annotated chromosome-length genome and high-density linkage map provide rich resources for evolutionary studies and will be fundamental in guiding conservation efforts for the helmeted honeyeater. 
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  7. We report a fiber-optic silicon Fabry–Perot temperature sensor with high speed by considering the end conduction effect, which refers to the unwanted heat transfer between the sensing element and the fiber stub delaying the sensor from reaching thermal equilibrium with the ambient environment. The sensor is constructed by connecting the narrow edge surface of a thin silicon plate to the edge of the microtube attached to the fiber tip. Compared to the traditional design where the silicon plate is attached to the fiber end face on its large plate surface, the new sensor design minimizes the heat transfer path to the fiber stub for improved sensor speed. It has the additional benefit of increased cavity length for improved resolution. We show that, compared with the sensor of traditional design, the sensor of the new design shortened the characteristic response time in still air from 83 ms to 13 ms and improved the sensor resolution by a factor of 12, from 0.15 K to 0.012 K.

     
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  8. Hydrodynamic theories effectively describe many-body systems out of equilibrium in terms of a few macroscopic parameters. However, such parameters are difficult to determine from microscopic information. Seldom is this challenge more apparent than in active matter, where the hydrodynamic parameters are in fact fields that encode the distribution of energy-injecting microscopic components. Here, we use active nematics to demonstrate that neural networks can map out the spatiotemporal variation of multiple hydrodynamic parameters and forecast the chaotic dynamics of these systems. We analyze biofilament/molecular-motor experiments with microtubule/kinesin and actin/myosin complexes as computer vision problems. Our algorithms can determine how activity and elastic moduli change as a function of space and time, as well as adenosine triphosphate (ATP) or motor concentration. The only input needed is the orientation of the biofilaments and not the coupled velocity field which is harder to access in experiments. We can also forecast the evolution of these chaotic many-body systems solely from image sequences of their past using a combination of autoencoders and recurrent neural networks with residual architecture. In realistic experimental setups for which the initial conditions are not perfectly known, our physics-inspired machine-learning algorithms can surpass deterministic simulations. Our study paves the way for artificial-intelligence characterization and control of coupled chaotic fields in diverse physical and biological systems, even in the absence of knowledge of the underlying dynamics.

     
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