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Determination of 17β-estradiol by surface-enhanced Raman spectroscopy merged with hybridization chain reaction amplification on Au@Ag core-shell nanoparticles
摘要： The authors describe an aptamer-based assay for 17β-estradiol. It relies on the combined use of surface enhanced Raman scattering (SERS) and hybridization chain reaction (HCR). The aptamer against 17β-estradiol is applied as the recognition probes, and this results in excellent specificity. Specific recognition of target 17β-estradiol induce the freedom of DNA 2, which will open the stem-loop structure of probe 1 on the Au@Ag and form the partial dsDNA structure. With the nicking enzyme, the partial dsDNA will be hydrolyzed and the reside ssDNA on Au@Ag will form a small stem-loop structure. With the help of the other probe 2 modified Au@Ag and pre-immobilized probe 3 on the well of the microplate, an enzyme-free HCR can occur and tremendous Au@Ag can be assembled along the formed dsDNA in HCR, which can act as the excellent substrate for Raman measurement and greatly amplify the Raman signal of R6G on the Au@Ag. Afterwards, the key factor, ratio between probe 2-Au@Ag (P2) and probe1-Au@Ag (P1), affects the detection sensitivity is systematically optimized for the best sensing performance. The SERS signal of R6G, best measured at 1651 cm?1, increases linearly in the wide range from 1 pM to 10 nM. The detection limit can be as low as 0.1 pM.
关键词： Estrogen,Hybridization chain reaction,SERS,Food safety,Aptamer,Gold nanoparticle,Signal amplification,Environment monitoring
更新于2025-09-23 15:23:52
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[IEEE 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - Rome, Italy (2019.6.17-2019.6.20)] 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring) - The Possibilities of Using LED Photometry and Ellipsometry Technology for Monitoring the Aquatic Anvironment
摘要： This paper develops new information-instrumental tools for operative diagnostics of the water objects including a detection of negative processes in their functioning. These tools are based on the big data approach and use such instrumental means as multi-channel optical sensors using of which provides the e?ciency and reliability of the diagnostics results. The system consists of a LED spectrophotometer and a LED spectroellipsometer, an information interface, a set of algorithms for identifying spectral images, a database of spectral standards, algorithms for solving inverse problems of spectrophotometry, spectroellipsometry, and an algorithm for learning the recognition of spectral images. Information-modeling instrumental technology developed in this paper has adaptation function to the spatial water objects and provides their water quality diagnostics on the base of episodic in-situ measurements.
关键词： spectroellipsometer,spectrophotometer,ellipsometry,LED photometry,aquatic environment monitoring
更新于2025-09-19 17:13:59
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New Techniques for Sizing Solar Photovoltaic Panels for Environment Monitoring Sensor Nodes
摘要： The development of perpetually powered sensor networks for environment monitoring to avoid periodic battery replacement and to ensure the network never goes offline due to power is one of the primary goals in sensor network design. In many environment-monitoring applications, the sensor network is internet-connected, making the energy budget high because data must be transmitted regularly to a server through an uplink device. Determining the optimal solar panel size that will deliver sufficient energy to the sensor network in a given period is therefore of primary importance. The traditional technique of sizing solar photovoltaic (PV) panels is based on balancing the solar panel power rating and expected hours of radiation in a given area with the load wattage and hours of use. However, factors like the azimuth and tilt angles of alignment, operating temperature, dust accumulation, intermittent sunshine and seasonal effects influencing the duration of maximum radiation in a day all reduce the expected power output and cause this technique to greatly underestimate the required solar panel size. The majority of these factors are outside the scope of human control and must be therefore be budgeted for using an error factor. Determining of the magnitude of the error factor to use is crucial to prevent not only undersizing the panel, but also to prevent oversizing which will increase the cost of operationalizing the sensor network. But modeling error factors when there are many parameters to consider is not trivial. Equally importantly, the concept of microclimate may cause any two nodes of similar specifications to have very different power performance when located in the same climatological zone. There is then a need to change the solar panel sizing philosophy for these systems. This paper proposed the use of actual observed solar radiation and battery state of charge data in a realistic WSN-based automatic weather station in an outdoor uncontrolled environment. We then develop two mathematical models that can be used to determine the required minimum solar PV wattage that will ensure that the battery stays above a given threshold given the weather patterns of the area. The predicted and observed battery state of charge values have correlations of 0.844 and 0.935 and exhibit Root Mean Square Errors of 9.2% and 1.7% for the discrete calculus model and the transfer function estimation (TFE) model respectively. The results show that the models perform very well in state of charge prediction and subsequent determination of ideal solar panel rating for sensor networks used in environment monitoring applications.
关键词： battery state of charge,environment monitoring,solar radiation,discrete calculus model,transfer function estimation,solar photovoltaic panels,sensor nodes
更新于2025-09-11 14:15:04