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조성수(Seongsu Cho),신성훈(Seonghun Shin),심재민(Jaemin Sim),이진기(Jinkee Lee) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.11
River is the major water source for city. When eutrophication is occurred, green algae in water is increased abnormally, and it is harmful to ecosystem in river, and human health. To resolve this problem, additional purification procedure is needed. So, monitoring the green algae in river is important to manage the quality of water supply in city. Korean government manage the green algae alarm system based on the concentration of green algae cell in river. To maintain this system well, effective green algae concentration measurement device is needed. In this study, we developed the microfluidic device to measure the concentration of green algae cells in sample based on droplet generation and deep learning. We compared the result with the result measured by haematocytometry and confirmed that it had enough accuracy to apply on green algae alarm system.
조성수(Seongsu Cho),신성훈(Seonghun Shin),심재민(Jaemin Sim),이진기(Jinkee Lee) 한국가시화정보학회 2021 한국가시화정보학회지 Vol.19 No.2
River and stream are the important water supply source in our lives. Eutrophication causes excessive green algae growth including microcystis, which makes harmful to ecosystem and human health. Therefore, the water purification process to remove green algae is essential. In Korea, green algae alarm system exists depending on the concentration of green algae cells in river or stream. To maintain the growth amount under control, green algae monitoring system is being used. However, the unmanned, small and automatic monitoring system would be preferable. In this study, we developed the 3D printed device to measure the concentration of green algae cell using microfluidic droplet generator and deep learning. Deep learning network was trained by using transfer learning through pre-trained deep learning network. This newly developed microfluidic cell counter has sufficient accuracy to be possibly applicable to green algae alarm system.
신성훈(Seonghun Shin),조성수(Seongsu Cho),송륜근(Ryunguen Song),김혜정(Hyejeong Kim),이진기(Jinkee Lee) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.11
Since oil spill accidents bring serious damage to the marine ecosystem, effective remediation methods are required. Amphiphilic Janus particle can be adsorbed to the water/oil interface and stabilize it. Therefore, they have been widely studied to replace traditional methods. However, low production rate and complexity of the processes are main obstacles for the large-scale production. To solve this problem, we built a 3D printed parallelized microfluidic droplet generator for large-scale production of amphiphilic and magnetic Janus particles. We verified the mono-dispersity of the particles and analyzed the relationship between flow rate ratio and particle size. In addition, we experimentally prove that Janus particles can be adsorbed onto the interface and stabilize it. Then, we built a parallelized droplet generator to increase the production rate. It is expected that the mass production of these Janus particles would be an effective solution for oil adsorption and recovery.