Estradiol is known as one of the most potent estrogenic endocrine-disrupting chemicals (EDCs) that may cause various health implications on human growth, metabolism regulation, the reproduction system, and possibly cancers. The detection of these EDCs in our surroundings, such as in foods and beverages, is important to prevent such harmful effects on humans. Aptamers are a promising class of bio-receptors for estradiol detection due to their chemical stability and high affinity. With the development of aptamer technology, electrochemical aptasensing became an important tool for estradiol detection. This review provides detailed information on various technological interventions in electrochemical estradiol detection in solutions and categorized the aptasensing mechanisms, aptamer immobilization strategies, and electrode materials. Moreover, we also discussed the role of estradiol in human physiology and signaling mechanisms. The level of estradiol in circulation is associated with normal and diseased conditions. The aptamer-based electrochemical sensing techniques are powerful and sensitive for estradiol detection.

Detecting trace amounts of explosives to ensure personal safety is important, and this is possible by using laser-based spectroscopy techniques. We performed surface-enhanced Raman scattering (SERS) using plasmonic nanogap substrates for the solution phase detection of some nitro-based compounds, taking advantage of the hot spot at the nanogap. An excitation wavelength of 785 nm with an incident power of as low as ≈0.1 mW was used to excite the nanogap substrates. Since both RDX and PETN cannot be dissolved in water, acetone was used as a solvent. TNT was dissolved in water as well as in hexane. The main SERS peaks of TNT, RDX, and PETN were clearly observed down to the order of picomolar concentration. The variations in SERS spectra observed from different explosives can be useful in distinguishing and identifying different nitro-based compounds. This result indicates that our nanogap substrates offer an effective approach for explosives identification.

The development of reliable gas sensors is very important in many fields such as safety, environment, and agriculture, and is especially essential for industrial waste and air pollution monitoring. As the performance of mobile platforms equipped with sensors such as smartphones and drones and the technologies supporting them (wireless communication, battery performance, data processing technology, etc.) are spreading and improving, a lot of efforts are being made to perform these tasks by using portable systems such as smartphones or installing them on unmanned wireless platforms such as drones. For example, research is continuously being conducted on chemical sensors for field monitoring using smartphones and rapid monitoring of air pollution using unmanned aerial vehicles (UAVs). In this paper, we review the measurement results of various chemical sensors available on mobile platforms including drones and smartphones, and the analysis of detection results using machine learning. This topic covers a wide range of specialized fields such as materials engineering, aerospace engineering, physics, chemistry, environmental engineering, electrical engineering, and machine learning, and it is difficult for experts in one field to grasp the entire content. Therefore, we have explained various concepts with relatively simple pictures so that experts in various fields can comprehensively understand the overall topics.

Explosive detection has become an increased priority in recent years for homeland security and counter-terrorism applications. Although drones may not be able to pinpoint the exact location of the landmines and explosives, the identification of the explosive vapor present in the surrounding air provides significant information and comfort to the personnel and explosives removal equipment operators. Several optical methods, such as the luminescence quenching of fluorescent polymers, have been used for explosive detection. In order to utilize sensing technique via unmanned vehicles or drones, it is very important to study how the air flow affects the luminescence quenching. We investigated the effects of air flow on the quenching efficiency of Poly(2,5-di(2′-ethylhexyl)-1,4-ethynylene) (PEE) by TNT molecules. We treated the TNT molecules incorporated into the polymer film as non-radiative recombination centers, and found that the time derivative of the non-radiative recombination rates was greater with faster air flows. Our investigations show that relatively high air flow into an optical sensing part is crucial to achieving fast PL quenching. We also found that a “continuous light excitation” condition during the exposure of TNT vapor greatly influences the PL quenching.

Detecting the presence of explosives is important to protect human lives during military conflicts and peacetime. Gas-phase detection of explosives can make use of the change of material properties, which can be sensitive to environmental conditions such as temperature and humidity. This paper describes a remote-controlled automatic shutter method for the environmental impact assessment of photoluminescence (PL) sensors under near-open conditions. Utilizing the remote-sensing method, we obtained environmental effects without being exposed to sensing vapor molecules and explained how PL intensity was influenced by the temperature, humidity, and exposure time. We also developed a theoretical model including the effect of exciton diffusion for PL quenching, which worked well under limited molecular diffusions. Incomplete recovery of PL intensity or the degradation effect was considered as an additional factor in the model.

Detecting the presence of explosives is important to protect human lives in military conflicts and peacetime. Gas-phase detection of explosives can make use of the change of material properties, which can be sensitive to environmental conditions such as temperature and humidity. This paper describes a remote-controlled automatic shutter method for environmental impact assessment of photoluminescence (PL) sensors under near-open conditions. Utilizing the remote-sensing method, we obtained environmental effects without being exposed to sensing vapor molecules, and explained how PL intensity was influenced by the temperature, humidity, and exposure time. We also developed a theoretical model including the effect of exciton diffusion for PL quenching, which worked well under limited molecular diffusions. Incomplete recovery of PL intensity, or degradation effect, was considered as an additional factor in the model.