Korea University · Engineering
Professor Seong-Yong Jeong's research lab specializes in advanced gas sensing technologies, focusing on the development of high-performance, selective, and sensitive oxide semiconductor-based chemiresistors for real-time detection of toxic and environmentally harmful volatile organic compounds (VOCs). The lab pioneers innovative sensor architectures—such as yolk–shell structures, bilayer oxide films, and catalytic overlayers—engineered to enhance sensitivity, selectivity, and resistance to interference from humidity. Key research directions include the design of functional nanomaterials for sub-ppm detection of hazardous gases like benzene, toluene, xylene, and ethylene, with applications in environmental monitoring, indoor air quality control, and agricultural technology.
Figures are computed from collected data and may differ slightly.
Artificial olfaction based on gas sensor arrays aims to substitute for, support, and surpass human olfaction. Like mammalian olfaction, a larger number of sensors and more signal processing are crucial for strengthening artificial olfaction. Due to rapid progress in computing capabilities and machine-learning algorithms, on-demand high-performance artificial olfaction that can eclipse human olfaction becomes inevitable once diverse and versatile gas sensing materials are provided. Here, rational
Ultra-selective and sensitive detection of benzene was achieved using Pd-loaded SnO<sub>2</sub> yolk–shell micro-reactor sensing films coated with a catalytic Co<sub>3</sub>O<sub>4</sub> overlayer.
The accurate detection and identification of volatile aromatic hydrocarbons, which are highly toxic pollutants, are essential for assessing indoor and outdoor air qualities and protecting humans from their sources. However, real-time and on-site monitoring of aromatic hydrocarbons has been limited by insufficient sensor selectivity. Addressing the issue, bilayer oxide chemiresistors are developed using Rh-SnO<sub>2</sub> gas-sensing films and catalytic CeO<sub>2</sub> overlayers for rapidly and
A highly selective and sensitive detection of the plant hormone ethylene, particularly at low concentrations, is essential for controlling the growth, development, and senescence of plants, as well as for ripening of fruits. However, this remains challenging because of the non-polarity and low reactivity of ethylene. Herein, a strategy for detecting ethylene at a sub-ppm-level is proposed by using oxide semiconductor chemiresistors with a nanoscale oxide catalytic overlayer. The SnO<sub>2</sub>
Abstract Water poisoning, the dependence of gas‐sensing characteristics on moisture, in oxide chemiresistors remains a long‐standing challenge. Various approaches are explored to mitigate water poisoning but they are often accompanied by significant deterioration of sensing capabilities such as gas response deterioration, gas selectivity alteration, and sensor resistance increase up to unmeasurable levels. Herein, a novel sensor design with a moisture‐blocking Tb 4 O 7 overlayer is suggested as
Oxide chemiresistors have mostly been used to detect reactive gases such as ethanol, acetone, formaldehyde, nitric dioxide, and carbon monoxide. However, the selective and sensitive detection of volatile aromatic compounds such as benzene, toluene, and xylene, which are extremely toxic and harmful, using oxide chemiresistors remains challenging because of the molecular stability of benzene rings containing chemicals. Moreover, the performance of the sensing materials is insufficient to detect tr
A porous PdO-functionalized SnO 2 architecture is proposed as a solution for the exclusive detection of hydrogen, which is a biomarker for irritable bowel syndrome. The sensor will open a new avenue for simple disease diagnosis using breath analysis.
An FBG interrogator which consists of a broadband light source (BLS), a tunable Fabry-Perot (F-P) filter, and a LabVIEW program with an adequate signal processing algorithm is proposed and experimentally demonstrated.
An improved FBG interrogator for mitigating the effect the nonlinearity, path dependence, and ambient temperature dependence of the FFP filter is proposed and experimentally demonstrated. Experimental results with calibration show twelve times better than those without calibration.
This toxicological profile is prepared in accordance with guidelines developed
The authors propose and experimentally demonstrate a calibration process unit for mitigating the effects of nonlinearity and dependence on the ambient temperature for the fibre Fabry–Perot (FFP) filter. Additionally, the performance limits of the peak detection process unit based on the maximum detection algorithm according to the noise and the characteristics of the fibre Bragg grating (FBG) and FFP filter are presented. The experimental results obtained without and with the calibration process
In article number 2007895, Jong-Heun Lee and co-workers show that the coating of a moisture-blocking Tb4O7 overlayer provides a general and facile solution to mitigate the water poisoning effect of oxide semiconductor gas sensors without significant alteration of the gas-sensing characteristics such as gas response, selectivity, and sensor resistance, enabling the design of reliable gas sensors and artificial olfaction with the strong endurance against the variation in the ambient moisture.
In article number 1903093, Jong-Heun Lee and co-workers describe exclusive detection of sub-ppm-level ethylene, a representative plant hormone, using bilayer sensors. The sensor can be widely used for real-time assessment of fruit freshness/ripening or the control of plant growth/development.
Although downlink multi-user MIMO (MU-MIMO) technology is included in the IEEE 802.11ac Standard, multi-cell interference in IEEE 802.11ac MU-MIMO networks degrades expected performance gain from the technology due to unplanned deployment of access points. To this end, recent research efforts envision that a central controller coordinates a set of APs to alleviate the multi-cell interference. However, to fully exploit the benefits of the coordinated access points with MU-MIMO, it is essential th
Open papers in the app to read, cite, and organize with AI.