Four-flux Kubelka-Munk model of the light reflectance for printing of rough substrate

Author(s):  
Na Dong ◽  
Jinghuan Ge ◽  
Yixin Zhang
Biosensors ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 153
Author(s):  
Georgios Koukouvinos ◽  
Chrysoula-Evangelia Karachaliou ◽  
Ioannis Raptis ◽  
Panagiota Petrou ◽  
Evangelia Livaniou ◽  
...  

Carbendazim is a systemic benzimidazole-type fungicide with broad-spectrum activity against fungi that undermine food products safety and quality. Despite its effectiveness, carbendazim constitutes a major environmental pollutant, being hazardous to both humans and animals. Therefore, fast and reliable determination of carbendazim levels in water, soil, and food samples is of high importance for both food industry and public health. Herein, an optical biosensor based on white light reflectance spectroscopy (WLRS) for fast and sensitive determination of carbendazim in fruit juices is presented. The transducer is a Si/SiO2 chip functionalized with a benzimidazole conjugate, and determination is based on a competitive immunoassay format. Thus, for the assay, a mixture of an in-house developed rabbit polyclonal anti-carbendazim antibody with the standards or samples is pumped over the chip, followed by biotinylated secondary antibody and streptavidin. The WLRS platform allows for real-time monitoring of biomolecular interactions carried out onto the Si/SiO2 chip by transforming the shift in the reflected interference spectrum caused by the immunoreaction to effective biomolecular adlayer thickness. The sensor is able to detect 20 ng/mL of carbendazim in fruit juices with high accuracy and precision (intra- and inter-assay CVs ≤ 6.9% and ≤9.4%, respectively) in less than 30 min, applying a simple sample treatment that alleviates any “matrix-effect” on the assay results and a 60 min preincubation step for improving assay sensitivity. Excellent analytical characteristics and short analysis time along with its small size render the proposed WLRS immunosensor ideal for future on-the-spot determination of carbendazim in food and environmental samples.


Author(s):  
Adi Prasetio ◽  
Soyeon Kim ◽  
Muhammad Jahandar ◽  
Dong Chan Lim

AbstractIncorporating localized surface plasmon resonance (LSPR) into organic solar cells (OSCs) is a popular method for improving the power conversion efficiency (PCE) by introducing better light absorption. In this work, we designed a one-pot synthesis of Ag@SiO2@AuNPs dual plasmons and observed an immense increase in light absorption over a wide range of wavelengths. Ag@SiO2 plays the main role in enhancing light absorption near the ultraviolet band. The silica shell can also further enhance the LSP resonance effect and prevent recombination on the surface of AgNPs. The AuNPs on the Ag@SiO2 shell exhibited strong broad visible-light absorption due to LSP resonance and decreased light reflectance. By utilizing Ag@SiO2@AuNPs, we could enhance the light absorption and photoinduced charge generation, thereby increasing the device PCE to 8.57% and Jsc to 17.67 mA cm−2, which can be attributed to the enhanced optical properties. Meanwhile, devices without LSPR nanoparticles and Ag@SiO2 LSPR only showed PCEs of 7.36% and 8.18%, respectively.


2021 ◽  
Vol 2021 (49) ◽  
pp. 37-44
Author(s):  
I. B. Ivasiv ◽  

It has been proposed to utilize the median algorithm for determination of the extrema positions of diffuse light reflectance intensity distribution by a discrete signal of a photodiode linear array. The algorithm formula has been deduced on the base of piecewise-linear interpolation for signal representation by cumulative function. It has been shown that this formula is much simpler for implementation than known centroid algorithm and the noise immune Blais and Rioux detector algorithm. Also, the methodical systematic errors for zero noise as well as the random errors for full common mode additive noises and uncorrelated noises have been estimated and compared for mentioned algorithms. In these terms, the proposed median algorithm is proportionate to Blais and Rioux algorithm and considerably better then centroid algorithm.


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