Deep‐learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency

During the last decades the whispering gallery mode based sensors have become a prominent solution for label-free sensing of various physical and chemical parameters.At the same time,the widespread utilization of the approach is hindered by the restricted applicability of the known configurations for ambient variations quantification outside the laboratory conditions and their low affordability,where necessity on the spectrally-resolved data collection is among the main limiting factors.In this paper we demonstrate the first realization of an affordable whispering gallery mode sensor powered by deep learning and multi-resonator imaging at a fixed frequency.It has been shown that the approach enables refractive index unit(RIU)prediction with an absolute error at 3×10^(-6) level for dynamic range of the RIU variations from 0 to 2×10^(-3) with temporal resolution of several milliseconds and instrument-driven detection limit of 3×10−5.High sensing accuracy together with instrumental affordability and production simplicity places the reported detector among the most cost-effective realizations of the whispering gallery mode approach.The proposed solution is expected to have a great impact on the shift of the whole sensing paradigm away from the model-based and to the flexible self-learning solutions.

Detection of per-and polyfluoroalkyl water contaminants with a multiplexed 4D microcavities sensor

The per-and polyfluoroalkyl substances(PFAS)are a group of organofluorine chemicals treated as the emerging pollutants that are currently of particularly acute concern.These compounds have been employed intensively as surfactants over multiple decades and are already to be found in surface and ground waters at amounts sufficient to have an effect on human health and ecosystems.Because of the carbon–fluorine bonds,the PFAS have an extreme environmental persistence and their negative impact accumulates with further production and penetration into the environment.In Germany alone,more than thousands of sites have been identified as contaminated with PFAS;thus,timely detection of PFAS residue is becoming a high priority.In this paper,we report on the high performance optical detection method based on whispering gallery mode(WGM)microcavities applied for the first time to detect PFAS contaminants in aqueous solutions.A self-sensing boosted 4D microcavity fabricated with two-photon polymerization is employed as an individual sensing unit.In an example of the multiplexed imaging sensor with multiple hundreds of simultaneously interrogated microcavities we demonstrate the possibility to detect the PFAS chemicals representatives at a level down to 1 ppb(parts per billion).

Plasma transport simulation under different conditions and optimization analysis of dual-stage grid ion thruster

In order to study the extraction and acceleration mechanism of the dual-stage grid,a three-dimensional model based on the Particle-In-Cell/Monte Carlo Collision(PIC/MCC)method is performed.Dual-stage grid ion thruster is a new type of electrostatic ion thruster,which can break through the limitations of traditional gridded ion thrusters,and greatly improve the specific impulse.The high performance also makes the grid sensitive to operating parameters.In this paper,the influence of grid parameters on xenon ion thruster’s performance in a wide range is systematically simulated,and the optimal operating condition is given.Both the over-focusing of the plume,and the transparency of the screen grid are improved,and the grid corrosion is reduced through simulation optimization.The specific impulse under the given working conditions is 9877.24 s and the thrust is 7.28 mN.Based on the simulation optimization,the limitation of the dual-stage grid is discussed.The grid performs well under high voltage conditions(>3000 V)but not well under low voltage conditions(<2000 V).Finally,since argon is cheaper and more advantageous in future engineering applications,the plasma distribution and grid extraction ability under xenon and argon are analyzed and compared to study the flexibility of the dual-stage grid ion thruster.The simulation results show that a set of optimal parameters is only applicable to the corresponding propellant,which needs to be optimized for different propellant types.

Ion thruster accelerator grid erosion mechanism under extreme conditions of cylindrical erosion and chamfer erosion

In this paper,the abnormal experimental phenomenon on barrel erosion under extreme working conditions in the ultra-long life experiment(>10000 h)of ion thruster ion optics is studied by the Immersed-Finite-Element Particle-In-Cell Monte-Carlo-Collision(IFE-PIC-MCC)method and the grid erosion evaluation model.The transport process of beam ions and Charge Exchange(CEX)ions in the grid system,and the characteristics and mechanisms of the aperture barrel erosion under extreme erosion conditions(i.e.the cylindrical erosion and chamfer erosion)were systematically studied.Thanks to the advantage of the IFE method for dealing with complex boundaries in structured mesh,the aperture barrel erosion morphology of the accelerator grid is reconstructed accurately based on the experimental results.The results show that,with the evolution of working conditions,the mechanism of the aperture barrel erosion changes significantly,which relies heavily on the accelerator grid morphology.The change of the accelerator grid aperture barrel morphology has a significant effect on the behavior of CEX ions,and only affects the local electric field distribution,but has no effect on the upstream plasma sheath.As the erosion progresses,the erosion position moves downstream along the grid aperture axis direction,and the erosion range becomes narrower.Regardless of the erosion phase,the erosion rate of the CEX ions located downstream of the decelerator grid is the largest.The erosion rate is related to the mean incident energy and angle,and their variation is closely related to the position and trajectory of CEXions.