Quantitative Planar Laser-Induced Fluorescence Technology

Planar laser-induced fluorescence (PLIF) is a highly sensitive and space-time-resolved laser diagnostic technique. It is widely used in the diagnosis of combustion and flow fields to obtain the thermodynamic information of active components and interested molecules in flames. Nowadays, the PLIF technology is developing in two directions: high speed and quantification. In view of the high spatial and temporal resolution characteristics of PLIF technology that other laser diagnostics do not possess, this chapter will focus on the basic principle of laser-induced fluorescence and the current research status of quantitative PLIF technology. In addition, the advantages and disadvantages of various quantitative technologies of component concentration in flames based on laser-induced fluorescence technology are analyzed. At last, the latest works on the quantification of species concentration using planar laser-induced fluorescence in combustion are introduced

Background free imaging of upconversion nanoparticle distribution in human skin

Widespread applications of nanotechnology materials have raised safety concerns due to their possible penetration through skin and concomitant uptake in the organism. This calls for systematic study of nanoparticle transport kinetics in skin, where high-resolution optical imaging approaches are often preferred. We report on application of emerging luminescence nanomaterial, called upconversion nanoparticles (UCNPs), to optical imaging in skin that results in complete suppression of background due to the excitation light back-scattering and biological tissue autofluorescence. Freshly excised intact and microneedle-treated human skin samples were topically coated with oil formulation of UCNPs and optically imaged. In the first case, 8- and 32-nm UCNPs stayed at the topmost layer of the intact skin, stratum corneum. In the second case, 8-nm nanoparticles were found localized at indentations made by the microneedle spreading in dermis very slowly (estimated diffusion coefficient, D-np = 3-7 x 10(-12) cm(2) . s(-1)). The maximum possible UCNP-imaging contrast was attained by suppressing the background level to that of the electronic noise, which was estimated to be superior in comparison with the existing optical labels. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE)

Detection of peanut seed vigor based on hyperspectral imaging and chemometrics

Rapid nondestructive testing of peanut seed vigor is of great significance in current research. Before seeds are sown, effective screening of high-quality seeds for planting is crucial to improve the quality of crop yield, and seed vitality is one of the important indicators to evaluate seed quality, which can represent the potential ability of seeds to germinate quickly and whole and grow into normal seedlings or plants. Meanwhile, the advantage of nondestructive testing technology is that the seeds themselves will not be damaged. In this study, hyperspectral technology and superoxide dismutase activity were used to detect peanut seed vigor. To investigate peanut seed vigor and predict superoxide dismutase activity, spectral characteristics of peanut seeds in the wavelength range of 400-1000 nm were analyzed. The spectral data are processed by a variety of hot spot algorithms. Spectral data were preprocessed with Savitzky-Golay (SG), multivariate scatter correction (MSC), and median filtering (MF), which can effectively to reduce the effects of baseline drift and tilt. CatBoost and Gradient Boosted Decision Tree were used for feature band extraction, the top five weights of the characteristic bands of peanut seed vigor classification are 425.48nm, 930.8nm, 965.32nm, 984.0nm, and 994.7nm. XGBoost, LightGBM, Support Vector Machine and Random Forest were used for modeling of seed vitality classification. XGBoost and partial least squares regression were used to establish superoxide dismutase activity value regression model. The results indicated that MF-CatBoost-LightGBM was the best model for peanut seed vigor classification, and the accuracy result was 90.83%. MSC-CatBoost-PLSR was the optimal regression model of superoxide dismutase activity value. The results show that the R2 was 0.9787 and the RMSE value was 0.0566. The results suggested that hyperspectral technology could correlate the external manifestation of effective peanut seed vigor

Pre-Shaped Burst-Mode Hybrid MOPA Laser System at 10 kHz Pulse Frequency

A temporal pre-shaped burst-mode hybrid fiber-bulk laser system was illustrated at a 10 kHz rate with a narrow spectral linewidth. A theoretical model was proposed to counteract the temporal profile distortion and compensate for the desired one, based on reverse process of amplification. For uniformly modulated injection, amplified shapes were recorded and investigated in series for their varied pulse duration, envelope width and amplification delay, respectively. The pre-shaped output effectively realized a uniform distribution on a time scale for both the burst envelope and pulse shape under the action of the established theoretical method. Compared with previous amplification delay methods, this model possesses the capacity to extend itself for applications in burst-mode shaping with variable parameters and characteristics. The maximum pulse energy was enlarged up to 9.68 mJ, 8.94 mJ and 6.57 mJ with a 300 ns pulse duration over envelope widths of 2 ms to 4 ms. Moreover, the time-averaged spectral bandwidths were measured and characterized with Lonrentz fits of 68.3 MHz, 67.2 MHz and 67.7 MHz when the pulse duration varied from 100 ns to 300 ns

Investigation of Flame Evolution in Heavy Oil Boiler Bench Using High-Speed Planar Laser-Induced Fluorescence Imaging

Over recent years, much attention has been paid to the performance evaluation of industrial-type burners. The ignition and stable combustion process are of great significance in assessing the quality of burner. The planar laser-induced fluorescence (PLIF) technique can be applied to heavy oil boilers, extending this technique to engineering applications. Considering the complex environment of the bench test, measures such as temperature control and moisture proofing are made to improve the possibility of detection using PLIF. In this paper, an experimental investigation of flame growth following ignition is reported. A wrinkled structure could be observed from the configuration of the ignition flame; its trajectory will be depicted. The results showed that the wrinkled structure developed downward, i.e., by deviation from the direction of the airflow. The displacement velocity of the flame was used to describe the combustion rate. Good agreement was obtained for the flame shapes of both forced ignition and autoignition. In addition, the center of combustion deviated from the center of boiler, possibly due to some irregularity in the burner’s assembly which was critical to the design of the combustion chamber

Ultrabright Polymer-Dot Transducer Enabled Wireless Glucose Monitoring <i>via</i> a Smartphone

Optical methods such as absorptiometry, fluorescence, and surface plasmon resonance have long been explored for sensing glucose. However, these schemes have not had the clinical success of electrochemical methods for point-of-care testing because of the limited performance of optical sensors and the bulky instruments they require. Here, we show that an ultrasensitive optical transducer can be used for wireless glucose monitoring <i>via</i> a smartphone. The optical transducer combines oxygen-sensitive polymer dots (Pdots) with glucose oxidase that sensitively detect glucose when oxygen is consumed in the glucose oxidation reaction. By judicious design of the Pdots with ultralong phosphorescence lifetime, the transducer exhibited a significantly enhanced sensitivity by 1 order of magnitude as compared to the one in a previous study. As a result, the optical images of subcutaneous glucose level obtained with the smartphone camera could be utilized to clearly distinguish between euglycemia and hyperglycemia. We further developed an image processing algorithm and a software application that was installed on a smartphone. Real-time dynamic glucose monitoring in live mice was demonstrated with the smartphone and the implanted Pdot transducer