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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. 

Imaging of surface-enhanced Raman scattering (SERS) nanoparticles (NPs) has been intensively studied for cancer detection due to its high sensitivity, unconstrained low signal-to-noise ratios, and multiplexing detection capability. Furthermore, conjugating SERS NPs with various biomarkers is straightforward, resulting in numerous successful studies on cancer detection and diagnosis. However, Raman spectroscopy only provides spectral data from an imaging area without co-registered anatomic context. This is not practical and suitable for clinical applications. Here, we propose a custom-made Raman spectrometer with computer-vision-based positional tracking and monocular depth estimation using deep learning (DL) for the visualization of 2D and 3D SERS NPs imaging, respectively. In addition, the SERS NPs used in this study (hyaluronic acid-conjugated SERS NPs) showed clear tumor targeting capabilities (target CD44 typically overexpressed in tumors) by anex vivoexperiment and immunohistochemistry. The combination of Raman spectroscopy, image processing, and SERS molecular imaging, therefore, offers a robust and feasible potential for clinical applications. 

We investigate the emergence of current oscillations of a bipolar electrode (BPE) in coupled anode/cathode reaction under potentiostatic condition. In a traditional three-electrode setup, the nickel dissolution in sulfuric acid requires a minimum amount of IR ohmic drop, and thus series resistance for the oscillations to occur. In this paper, it is shown that in bipolar setup, when the nickel electrodissolution on the anodic side is coupled to hydrogen ion reduction on the cathodic side, spontaneous current oscillations can occur. An electrochemical analysis of the dynamics shows that the required circuit potential for the oscillations can be predicted from estimating the overpotentials needed for the anodic and cathodic reactions, the driving electrode, and the ohmic drop in the electrolyte. The dynamics and range of oscillations can be tuned by different concentrations of electrolyte, on both the anodic and the cathodic sides. In the considered example, the charge transfer resistance of the cathodic reaction can provide sufficient total resistance even when the solution resistance does not yield sufficient IR drop for the oscillations. Our findings have the potential to promote further studies of the collective behavior of electrochemical reactions using multielectrode arrays in bipolar electrode setups. 

A passive electrochemical coupling approach is proposed to induce spontaneous synchronization between chemical oscillators. The coupling exploits the potential difference between a catalyst redox couple in the Belousov–Zhabotinsky (BZ) reaction, without external feedback, to induce surface reactions that impact the kinetics of the bulk system. The effect of coupling in BZ oscillators under batch condition is characterized using phase synchronization measures. Although the frequency of the oscillators decreases nonlinearly over time, by a factor of 2 or more within 100 cycles, the coupling is strong enough to maintain synchronization. In such a highly drifting system, the Gibbs–Shannon entropy of the cyclic phase difference distribution can be used to quantify the coupling effect. We extend the Oregonator BZ model to account for the drifting natural frequencies in batch condition and for electrochemical coupling, and numerical simulations of the effect of acid concentration on synchronization patterns are in agreement with the experiments. Because of the passive nature of coupling, the proposed coupling scheme can open avenues for designing pattern recognition and neuromorphic computation systems using chemical reactions in a spontaneous process.