Tailorable infrared emission of microelectromechanical system-based thermal emitters with NiO films for gas sensing.

Infrared gas sensors hold great promise in the internet of things and artificial intelligence. Making infrared light sources with miniaturized size, reliable and tunable emission is essential but remains challenging. Herein, we present the tailorability of radiant power and the emergence of new emission wavelength of microelectromechanical system (MEMS)-based thermal emitters with nickel oxide (NiO) films. The coating of NiO on emitters increases top surface emissivity and induces the appearance of new wavelengths between 15 and 19 µm, all of which have been justified by spectroscopic methods. Furthermore, a sensor array is assembled for simultaneous monitoring of concentrations of carbon dioxide (CO2), methane (CH4), humidity, and temperature. The platform shows selective and sensitive detection at room temperature toward CO2 and CH4 with detection limits of around 50 and 1750 ppm, respectively, and also shows fast response/recovery and good recyclability. The demonstrated emission tailorability of MEMS emitters and their usage in sensor array provide novel insights for designing and fabricating optical sensors with good performance, which is promising for mass production and commercialization.

Quantitative Analysis of Gas Phase IR Spectra Based on Extreme Learning Machine Regression Model.

Advanced chemometric analysis is required for rapid and reliable determination of physical and/or chemical components in complex gas mixtures. Based on infrared (IR) spectroscopic/sensing techniques, we propose an advanced regression model based on the extreme learning machine (ELM) algorithm for quantitative chemometric analysis. The proposed model makes two contributions to the field of advanced chemometrics. First, an ELM-based autoencoder (AE) was developed for reducing the dimensionality of spectral signals and learning important features for regression. Second, the fast regression ability of ELM architecture was directly used for constructing the regression model. In this contribution, nitrogen oxide mixtures (i.e., N2O/NO2/NO) found in vehicle exhaust were selected as a relevant example of a real-world gas mixture. Both simulated data and experimental data acquired using Fourier transform infrared spectroscopy (FTIR) were analyzed by the proposed chemometrics model. By comparing the numerical results with those obtained using conventional principle components regression (PCR) and partial least square regression (PLSR) models, the proposed model was verified to offer superior robustness and performance in quantitative IR spectral analysis.

Probing electron-atom collision dynamics in gas plasma by high-order harmonic spectroscopy.

Plasma is a complex system involving diverse collisional processes and interactions, such as electron-impact excitation, ionization, recombination, etc. One of the most important methods for studying the properties and dynamics of plasma is to analyze the radiations from plasma. Here, we demonstrate the high-order harmonic (HH) spectroscopy for probing the complex electron-atom collision (EAC) dynamics in a laser-induced gas plasma. These measurements were carried out by using an elliptically polarized pump and a time-delayed linearly polarized probe. The HH spectra from argon and krypton plasmas were recorded by scanning the time delay up to hundreds of picoseconds. We found that the delay-dependent HH yield contains three distinct regions, i.e., the first enhancement, the subsequent suppression, and the final restoration regions. A qualitative analysis shows that these features are clear signatures of the EAC processes and interactions involved in the delay-dependent HH spectroscopy.

Reverse surface-polariton cherenkov radiation.

The existence of reverse Cherenkov radiation for surface plasmons is demonstrated analytically. It is shown that in a metal-insulator-metal (MIM) waveguide, surface plasmon polaritons (SPPs) excited by an electron moving at a speed higher than the phase velocity of SPPs can generate Cherenkov radiation, which can be switched from forward to reverse direction by tuning the core thickness of the waveguide. Calculations are performed in both frequency and time domains, demonstrating that a radiation pattern with a backward-pointing radiation cone can be achieved at small waveguide core widths, with energy flow opposite to the wave vector of SPPs. Our study suggests the feasibility of generating and steering electron radiation in simple plasmonic systems, opening the gate for various applications such as velocity-selective particle detections.