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Detector-based radiometric measurement is advantageous in terms of measurement uncertainty. National Institute of Metrology China (NIM) has developed a facility for detector-based spectral radiance scale realization in the range of (400∼950) nm. The scale is realized based on a tunable-laser coupled integrating sphere source using galvanometer-driven mirror, and a silicon trap reference standard detector calibrated directly against NIM’s primary standard for spectral power responsivity and NIM’s effective area calibration facility for apertrue area. Sources and transfer standards are characterized, and spectral radiance responsivity can be measured with uncertainties at the (0.2∼0.4) % level.

The recently introduced minimal photon fluxes (MINFLUX) concept pushed the resolution of fluorescence microscopy to molecular dimensions. Initial demonstrations relied on custom made, specialized microscopes, raising the question of the method’s general availability. Here, we show that MINFLUX implemented with a standard microscope stand can attain 1–3 nm resolution in three dimensions, rendering fluorescence microscopy with molecule-scale resolution widely applicable. Advances, such as synchronized electro-optical and galvanometric beam steering and a stabilization that locks the sample position to sub-nanometer precision with respect to the stand, ensure nanometer-precise and accurate real-time localization of individually activated fluorophores. In our MINFLUX imaging of cell- and neurobiological samples, ~800 detected photons suffice to attain a localization precision of 2.2 nm, whereas ~2500 photons yield precisions <1 nm (standard deviation). We further demonstrate 3D imaging with localization precision of ~2.4 nm in the focal plane and ~1.9 nm along the optic axis. Localizing with a precision of <20 nm within ~100 µs, we establish this spatio-temporal resolution in single fluorophore tracking and apply it to the diffusion of single labeled lipids in lipid-bilayer model membranes. Minimal photon fluxes (MINFLUX) has enabled molecule-scale resolution in fluorescence microscopy but this had not been shown in standard, broadly applicable microscopy platforms. Here the authors report a solution to allow normal fluorescence microscopy while also providing 1-3 nm 3D resolution.

In order to explore how to etch high-precision FSS units on the surface of large-scale variable curvature non-expandable radome, this study designed and constructed a complete set of curved FSS laser etching systems. In the process of platform construction, by comparing the processing methods of various FSS, a galvanometer laser scanning system with high processing accuracy and efficiency was selected and equipped with a servo motion system. The proposed system can realize high-precision laser etching processing of frequency selection surface and thus provide a reference for other similar projects and practical applications.

Laser-processing system plays an important role in modern processing. To improve the precision of a galvanometer laser-processing system, a novel compensation method based on machine vision is proposed. First, the various errors existing in the scanning process of the galvanometer system and the influence on the accuracy of the scanning system were analyzed. Second, processing a specific grid within the processing range of the laser-processing system, the machine vision method was employed to extract the skeleton image and obtain the sub-pixel coordinates of each grid corner point. By comparing them with their theoretical positions, the position and error of all corner points of the mesh were obtained. Finally, the position and error of the four corner points in the arbitrary grid region were analyzed by the weighted interpolation method, and the error value and compensation value of any point in the grid were derived, and an error compensation model was established to compensate the scanning system. To verify the effectiveness of the proposed compensation method, a compensation experiment was conducted, and the workpiece machining accuracy after compensation was improved. The method is simple in operation, offers good compensation effect, and has important theoretical significance and practical value for improving the precision of laser-processing systems.

Surface cleaning is an essential procedure to improve quality and performance of workpiece in modern industrial manufacturing. Among surface cleaning technologies, laser cleaning has been regarded as the most promising green cleaning technology. Laser cleaning is a green cleaning technology that will not cause any environmental pollution. Laser cleaning has the ability of cleaning the area of the designated shape. A set of laser cleaning system that consists of two-dimensional galvanometer and 3-axis motion platform, was designed in this paper. The two-dimensional galvanometer was used to clean the area of the specified shape. The 3-axis motion platform expands the limited cleaning area of the two-dimensional galvanometer to a larger area. Laser displacement sensor is utilized to ameliorate the cleaning quality. To improve the cleaning accuracy of the system proposed in this article, a camera was adopted to recognize the origin of the workpiece and correct the pose of the workpiece. Experimental results demonstrate the performance of the proposed system for large-scale plane workpiece.

In this paper, a new laser linkage processing method based on trajectory distribution of galvanometer and mechanical servo system is proposed to achieve large-range high-feedrate laser processing. The proposed method can effectively improve the processing range, accuracy, and efficiency. Firstly, according to the processing trajectory characteristics of the galvanometer and mechanical servo system, a trajectory distribution filter algorithm is designed to reasonably distribute the interpolated trajectory to the equipment. Then, two linkage processing methods are designed based on off-line trajectory and real-time trajectory distribution. Moreover, an experimental platform consisting of the laser, galvanometer, and mechanical servo system is built, and experiments are performed on experimental equipment to verify these methods. Finally, the experimental data is collected at different processing feedrates, and the processing errors of two linkage processing methods and mechanical servo system processing are calculated and compared. The processing accuracy and effect of linkage processing are effectively improved. In addition, the processing effect of real-time trajectory distribution is also improved compared to the off-line trajectory distribution, which is simpler and easier to implement. These methods have been successfully applied to the large-scale high-feedrate laser processing equipment in the laboratory.

The excellent cyclic efficiency, superior reversible charge/discharge rate, and high specific power density have made supercapacitors an important class of energy storage systems in recent time. In this study, two nano-ceria-based composites were developed to use as electrode materials in supercapacitor applications. The composites were synthesized by combining ceria with conductive polyaniline (PANI) and doped with HCl and p-toluene sulfonic acid (PTSA). The materials were characterized by FTIR spectroscopy, SEM, XRD, and XPS techniques. Electrochemical studies were performed by cyclic voltammetry, galvanometric charge-discharge, and AC impedance spectroscopy. The CeO2-PANI doped with HCl and PTSA composites displayed ideal supercapacitor behavior showing higher capacitances up to 504 F g−1 and 454 F g−1, respectively, at current density of 1 A g−1 in comparison with pristine ceria (109 F g−1). Both the composites exhibited excellent specific energy (up to 100.8 W h kg−1) as well as outstanding specific power (up to 830 W kg−1). These findings support the possibility of these composites for practical applicability as electrode materials in energy storage devices.

In this study, a laser scanning machining system supporting on-the-fly machining and laser power follow-up adjustment was developed to address the increasing demands for high-speed, wide-area, and high-quality laser scanning machining. The developed laser scanning machining system is based on the two-master and multi-slave architecture with synchronization mechanism, and realizes the integrated and synchronous collaborative control of the motion stage or robot, the galvanometer scanner, and the laser over standard industrial ethernet networks. The galvanometer scanner can be connected to the industrial ethernet topology as a node, via the self-developed galvanometer scanner control gateway module, and a “one-transmission and multiple-conversion” approach is proposed to ensure real-time ability and synchronization. The proposal of a laser power follow-up adjustment approach could realize real-time synchronous modulation of the laser power, along with the motion of the galvanometer scanner, which is conducive to ensuring the machining quality. In addition, machining software was developed to realize timesaving and high-quality laser scanning machining. The feasibility and practicability of this laser scanning machining system were verified using specific cases. Results showed that the proposed system overcame the limitation of working field size and isolation between the galvanometer scanner controller with the stage motion controller, and achieved high-speed and efficient laser scanning machining for both large-area consecutively and discontinuously arrayed patterns. Moreover, the integration of laser power follow-up adjustment into the system was conducive to ensuring welding quality and inhibiting welding defects. The proposed system paves the way for high-speed, wide-area, and high-quality laser scanning machining and provides technical convenience and cost advantages for customized laser-processing applications, exhibiting great research value and application potential in the field of material processing engineering.

Herein, we demonstrate the fabrication of highly capacitive activated carbon (AC) using a bio-waste Kusha grass (Desmostachya bipinnata), by employing a chemical process followed by activation through KOH. The as-synthesized few-layered activated carbon has been confirmed through X-ray powder diffraction, transmission electron microscopy, and Raman spectroscopy techniques. The chemical environment of the as-prepared sample has been accessed through FTIR and UV–visible spectroscopy. The surface area and porosity of the as-synthesized material have been accessed through the Brunauer–Emmett–Teller method. All the electrochemical measurements have been performed through cyclic voltammetry and galvanometric charging/discharging (GCD) method, but primarily, we focus on GCD due to the accuracy of the technique. Moreover, the as-synthesized AC material shows a maximum specific capacitance as 218 F g−1 in the potential window ranging from − 0.35 to + 0.45 V. Also, the AC exhibits an excellent energy density of ~ 19.3 Wh kg−1 and power density of ~ 277.92 W kg−1, respectively, in the same operating potential window. It has also shown very good capacitance retention capability even after 5000th cycles. The fabricated supercapacitor shows a good energy density and power density, respectively, and good retention in capacitance at remarkably higher charging/discharging rates with excellent cycling stability. Henceforth, bio-waste Kusha grass-derived activated carbon (DP-AC) shows good promise and can be applied in supercapacitor applications due to its outstanding electrochemical properties. Herein, we envision that our results illustrate a simple and innovative approach to synthesize a bio-waste Kusha grass-derived activated carbon (DP-AC) as an emerging supercapacitor electrode material and widen its practical application in electrochemical energy storage fields.

Structured Illumination Microscopy, SIM, is one of the most powerful optical imaging methods available to visualize biological environments at subcellular resolution. Its limitations stem from a difficulty of imaging in multiple color channels at once, which reduces imaging speed. Furthermore, there is substantial experimental complexity in setting up SIM systems, preventing a widespread adoption. Here, we present Machine-learning Assisted, Interferometric Structured Illumination Microscopy, MAI-SIM, as an easy-to-implement method for live cell super-resolution imaging at high speed and in multiple colors. The instrument is based on an interferometer design in which illumination patterns are generated, rotated, and stepped in phase through movement of a single galvanometric mirror element. The design is robust, flexible, and works for all wavelengths. We complement the unique properties of the microscope with an open source machine-learning toolbox that permits real-time reconstructions to be performed, providing instant visualization of super-resolved images from live biological samples. Structured Illumination Microscopy allows for the visualization of biological structures at resolutions below the diffraction limit, but this imaging modality is still hampered by high experimental complexity. Here, the authors present a combination of interferometry and machine learning to construct a structured illumination microscope for super resolution imaging of dynamic sub-cellular biological structures in multiple colors.