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The loss properties of semiconductor laser beams propagating in hollow waveguides (HWGs) are crucial in several applications. The attenuation coefficient of the distributed feedback quantum cascade laser (DFB-QCL) in the HWG was quantitatively determined by measuring its beam profile and laser power along the length of the HWG. The experimental reliability was evaluated, with measurement uncertainties as low as 2.6% and 0.5% for the full width at half maximum (FWHM) of beam profile and the laser power, respectively. We derived an empirical formula for the attenuation coefficient, which is exponential rather than linear with the length of the HWG. The formula was verified to be highly accurate, with a 76.2% reduction in deviation compared to the data in the datasheet. We propose a new concept for a free optical path (FOP) that depends on the inner diameter of the HWG and the incident angle of the beam. The FOP could be an excellent parameter for designing or optimizing HWG-based sensors.

This paper presents a mid-infrared dimethyl sulfide (CH3SCH3, DMS) sensor based on tunable laser absorption spectroscopy with a distributed feedback interband cascade laser to measure DMS in the atmosphere. Different from previous work, in which only DMS was tested and under pure nitrogen conditions, we measured DMS mixed by common air to establish the actual atmospheric measurement environment. Moreover, we used tunable laser absorption spectroscopy with spectral fitting to enable multi-species (i.e., DMS, CH4, and H2O) measurement simultaneously. Meanwhile, we used empirical mode decomposition and greatly reduced the interference of optical fringes and noise. The sensor performances were evaluated with atmospheric mixture in laboratory conditions. The sensor’s measurement uncertainties of DMS, CH4, and H2O were as low as 80 ppb, 20 ppb, and 0.01% with an integration time 1 s, respectively. The sensor possessed a very low detection limit of 9.6 ppb with an integration time of 164 s for DMS, corresponding to an absorbance of 7.4 × 10−6, which showed a good anti-interference ability and stable performance after optical interference removal. We demonstrated that the sensor can be used for DMS measurement, as well as multi-species atmospheric measurements of DMS, H2O, and CH4 simultaneously.

This work describes a nanohybrid material consisting of gold nanoparticles (AuNPs) and nanosheets of layered double hydroxides (NLDHs) of Mg(II) and Al(III). Mono-disperse AuNPs were immobilized on the surface of the LDHs via Au-O bonding. The nanohybrid sorbent was packed in an organic filter along with a syringe and applied to the microextraction of triazine herbicides with the help of an injection pump. The collected hexane eluate was concentrated and directly injected into a HPLC column for quantification. The effects of the amount of Au/LDH nanohydrobrids, type, flow rate, volume of washing and eluting solvent were optimized. The method was validated by detecting four triazine herbicides (prometryn, atrazine, terbumeton and secbumeton) in spiked maize. The limits of detection range between 35 and 108 pg g. The relative standard deviations range from 1.0-6.9% for repeatability and 4.6-7.8% for reproducibility (for n = 5). Graphical abstract Schematic presentation of a nanohybrid material consisting of gold nanoparticles and nanosheets of layered double hydroxides of Mg(II) and Al(III) (Au/LDH) for use as an adsorbent for microextraction in a packed syringe. Organic filter heads were used as the container of Au/LDHs nanohybrids, and were connected with the syringes installed on the injection pump for the semi-automatic microextraction and preconcentration of triazines in maize.

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Imprecise measurements present universally due to variability in the measurement error. We devised a very simple membership function to evaluate fuzzily the quality of optical sensing with a small dataset, where a normal distribution cannot be assumed. The proposed membership function was further used as a weighting function for non-linear curve fitting under expected mathematical model constraints, namely the membership function-weighted Levenberg–Marquardt (MFW-LM) algorithm. The robustness and effectiveness of the MFW-LM algorithm were demonstrated by an optical-sensing simulation and two practical applications. (1) In laser-absorption spectroscopy, molecular spectral line modeling was greatly improved by the method. The measurement uncertainty of temperature and pressure were reduced dramatically, by 53.3% and 43.5%, respectively, compared with the original method. (2) In imaging, a laser beam-profile reconstruction from heavy distorted observations was improved by the method. As the dynamic range of the infrared camera increased from 256 to 415, the detailed resolution of the laser-beam profiles increased by an amazing 360%, achieving high dynamic-range imaging to capture optical signal details. Therefore, the MFW-LM algorithm provides a robust and effective tool for fitting a proper physical model and precision parameters from low-quality data.

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