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180
- Yonsei University Successfully Hosts KSME Fluid Engineering Division Spring Conference
- Yonsei University Successfully Hosts KSME Fluid Engineering Division Spring Conference From April 2nd to 4th, the Spring Conference of the Korean Society of Mechanical Engineers (KSME), Fluid Engineering Division, was successfully held at Yonsei University's Baekyangnuri. The event was jointly organized by the Fluid Engineering Division of KSME, Yonsei University’s Department of Mechanical Engineering Education and Research Unit, and the Exascale Computing for Linear Solver Development Project. The conference brought together experts from both domestic and international institutions to share the latest research trends and practical applications in fluid engineering. A notable highlight was the invited lecture by Professor Hyung Hee Cho of Yonsei University, who presented recent research outcomes and future technological directions under the theme "High-Efficiency Turbine Technology for Advanced Aero-Engine Development." Professor Wonjung Kim of Yonsei University, recipient of this year's Gasan Academic Award, delivered a special lecture titled "Contact Line Dynamics of Gallium-Based Liquid Metals." Professor Kim’s presentation generated significant interest as he discussed innovative applications of liquid metal materials and advanced insights into fluid dynamics phenomena. The conference featured active scholarly exchanges through various special sessions, general presentations, and poster sessions. A total of 157 research presentations were delivered, including 126 oral presentations and 31 poster presentations, attracting approximately 300 participants who actively shared the latest developments in the fluid engineering field. Professor Jung-Il Choi from Yonsei University, chair of the conference organizing committee, commented, "This event provided a meaningful opportunity to share academic achievements and promote industry-academic collaboration in fluid engineering." The conference was well-received, with positive evaluations highlighting its role in broadly promoting the research capabilities of Korea's fluid engineering sector and providing an excellent academic networking platform for next-generation researchers.
- 기계공학부 2025.04.07
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179
- Yonsei University Successfully Concludes YES2025 International Symposium Celebrating its 140th Anniversary
- Yonsei University Successfully Concludes YES2025 International Symposium Celebrating its 140th Anniversary The YES2025 International Symposium, held from March 23 to 25, 2025, at Baekyang Nuri, Yonsei University, successfully concluded. Celebrating the 140th anniversary of Yonsei University, this event gathered world-renowned scholars who discussed future technological developments and facilitated active academic exchanges. Notably, keynote speeches by Professor George Malliaras from the University of Cambridge, Professor Jun Zhang from the Hong Kong University of Science and Technology, Professor Atsuo Yamada from the University of Tokyo, Professor Liwei Lin from UC Berkeley, and Professor Jung-ho Hwang from Yonsei University received significant acclaim. Throughout the symposium, participants presented recent research findings across diverse fields and engaged in in-depth discussions and Q&A sessions, enhancing their academic understanding and gaining new insights. Graduate students from Yonsei University's Department of Mechanical Engineering garnered attention with their exceptional research presentations during the poster sessions. In particular, collaboration among four departments from the College of Engineering, including Mechanical Engineering, was highly praised for elevating the quality and scale of the event. Participants expressed satisfaction, remarking, "The symposium provided substantial academic stimulation and meaningful exchanges." YES2025 is anticipated to serve as an exemplary model for sustainable international academic exchange initiatives within engineering colleges.
- 기계공학부 2025.04.01
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178
- Development of a Machine Learning-Based Model for Analyzing the Joint Effects of Temperature and Humidity on Airborne Ba
- Development of a Machine Learning-Based Model for Analyzing the Joint Effects of Temperature and Humidity on Airborne Bacteria and Mold in Indoor Environments Professor Jungho Hwang's research team from the Department of Mechanical Engineering at Yonsei University (first author Doheon Kim, Ph.D. candidate, and co-researchers Professor Dohyeong Kim and Professor Seongchul Seo) conducted a study utilizing a machine learning-based model to analyze the biological behavior of microorganisms in indoor air and the joint effects of temperature and humidity. The team developed a machine learning-based model capable of quantitatively determining the complex influences of temperature and relative humidity on the concentration of airborne mold and bacteria in indoor environments. This research is the world's first to investigate the joint effect of temperature and relative humidity on indoor bioaerosols in actual environments using machine learning. Unlike previous studies conducted under laboratory conditions, this research significantly enhanced effectiveness and accuracy by utilizing real indoor environmental data. The study was conducted in collaboration with the University of Texas at Dallas, Seokyeong University, and Korea University, with Yonsei University leading the research. These institutions collaborated in collecting indoor environmental data, analyzing the data, and developing the model, thereby enhancing the depth and accuracy of the research. The research findings were published in February 2025 in the internationally renowned journal 'Building and Environment' (Impact Factor: 7.1). The results are expected to contribute to the establishment of policies and technologies for indoor air quality management. Furthermore, the sophisticated machine learning-based predictive model is anticipated to enhance the accuracy of predicting changes in indoor microbial concentrations and provide effective management strategies by identifying air quality deterioration factors in advance. The model is also expected to be actively utilized in establishing customized air quality management strategies tailored to various indoor environmental conditions. The link: https://www.sciencedirect.com/science/article/pii/S0360132325000307
- 기계공학부 2025.03.17
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177
- Next-Generation Zinc-Ion Capacitor Development: Dendrite Suppression and High Energy Density Enhancement
- Next-Generation Zinc-Ion Capacitor Development: Dendrite Suppression and High Energy Density Enhancement Sushanta K. Das) conducted a study on the development of a "high-capacity dendrite-suppressing zinc-ion capacitor." This research aimed to address the low energy density of conventional capacitors and the safety issues of lithium-ion batteries by developing a high-performance and highly safe zinc-ion capacitor. Zinc-ion batteries utilize aqueous electrolytes, making them environmentally friendly and cost-effective; however, their commercialization has been hindered by side reactions between the zinc anode and the electrolyte, as well as the formation of dendrites. To overcome these challenges, the research team successfully coated the zinc anode with a two-dimensional nanomaterial, MXene, and introduced sodium (Na) ions as electrolyte additives to effectively suppress dendrite formation. As a result, the electrochemical stability of the anode was significantly enhanced, leading to improved long-term cycling performance. Additionally, the team utilized a novel niobium (Nb)-based MXene composite as the cathode material, which had not been previously reported, enabling the realization of a high-capacity, high-energy-density zinc-ion capacitor. This technology holds significant potential for applications requiring high power, long lifespan, and high safety. In particular, it can be applied to wearable devices, IoT sensors, grid energy storage systems, electric vehicles, and micromobility solutions as a stable energy storage technology. This research establishes the foundation for next-generation energy storage technologies that overcome the limitations of lithium-ion batteries and is expected to enhance competitiveness in the alternative battery market through future industrial and commercialization efforts. The study was published in Advanced Energy Materials (Impact Factor: 27.8), a globally renowned academic journal, and was recognized for its excellence by being selected as a cover paper. The link: https://doi.org/10.1002/aenm.202570013
- 기계공학부 2025.03.17
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176
- Enhancing the Performance of 3D Printed Bio-photoelectrochemical Cells Through Multi-objective Bayesian Optimization
- Enhancing the Performance of 3D Printed Bio-photoelectrochemical Cells Through Multi-objective Bayesian Optimization Attaching thylakoid Membranes (TM) on bio-photo-electro-chemical cells (BPEC) enables energy harvesting through photoelectrode extraction. However, the attachment methods rely on thin coating methods such as dip-coating, drop-casting, or electrospray deposition. We herein demonstrate the use of direct ink writing in coating TM on BPEC cells, aiming for rapid prototyping and mass production of BPEC cells. As photoelectron extraction through high TM loadings is not feasible, we investigate previously reported conducting materials to be used in mixture with TM. The conductive TM composite ink, referred to as BPEC ink in this study, is optimized through multi-objective Bayesian optimization (MOBO) with the two objectives of maximizing current density and maximizing printability. 14 initial searches were taken, followed by 15 MOBO searches. We confirm that after MOBO, current density and printability enhanced by 162% and 149%, respectively. Using the optimized BPEC ink, we demonstrate the 3D printing of fully integrated BPEC cells arranged in series. The link: https://www.tandfonline.com/doi/full/10.1080/17452759.2024.2449565
- 기계공학부 2025.03.17
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175
- Development of a Crosstalk-Free Strain-Insensitive Flexible Tactile Sensor Array Utilizing a Highly Stretchable Mesh Str
- Development of a Crosstalk-Free Strain-Insensitive Flexible Tactile Sensor Array Utilizing a Highly Stretchable Mesh Structure Professor Jongbaeg Kim’s research team in the Department of Mechanical Engineering at Yonsei University has developed a strain-insensitive flexible tactile sensor array that eliminates crosstalk by leveraging a highly stretchable mesh structure. Flexible tactile sensors have garnered significant attention for their applications in wearable technologies, including robotics, human-machine interfaces, and health monitoring. However, conventional tactile sensors face challenges in accurately measuring pressure due to vertical deformation induced by Poisson's ratio when subjected to lateral strain. To overcome this limitation, the research team integrated a highly stretchable mesh structure with a liquid metal-based stretchable electrode layer, ensuring precise pressure measurement regardless of external strain conditions. This study demonstrated the feasibility of strain-insensitive pressure monitoring for the prevention of carpal tunnel syndrome and cubital tunnel syndrome. The findings were published in Small Methods, a prestigious international journal in the field of nanoscience. The link: https://onlinelibrary.wiley.com/doi/10.1002/smtd.202401730
- 기계공학부 2025.03.17
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174
- Exaplainable Deep Learning Approaches for Risk Screening of Periodontitis
- Exaplainable Deep Learning Approaches for Risk Screening of Periodontitis The MLCS research team from the School of Mechanical Engineering, led by Professor Jongeun Choi (co-first authors of this study are Bogyeong Suh and Dr. Heejin Yu), have developed a new deep learning-based diagnostic model that can detect the risk of periodontitis at an early stage. This deep learning model diagnoses the risk of periodontitis with higher accuracy than existing clinical diagnostic tools and machine learning models. Utilizing an explainable artificial intelligence (XAI) model, the research team verified the reliability of the model and provided personalized risk assessments for individuals. The study demonstrates that deep learning and XAI models can contribute to the early detection and prevention of periodontitis in dental check-ups. The paper was published in the renowned international journal 'Journal of Dental Research' (Impact Factor: 5.7, Ranks in the top 2.2%) in January 2025. The link: https://journals.sagepub.com/doi/full/10.1177/00220345241286488
- 기계공학부 2025.03.17
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173
- Keio-Yonsei Joint Industrial Visit Program Successfully Completed
- Keio-Yonsei Joint Industrial Visit Program Successfully Completed The Keio-Yonsei Joint Industrial Visit Program was successfully completed, co-hosted by Keio University and Yonsei University's Department of Mechanical Engineering. The program took place from February 16 to 20 (four nights and five days), with nine undergraduate students, two graduate students, and two professors from Keio University visiting Yonsei University for academic exchange. On the Yonsei side, 14 undergraduate students, two graduate students, and seven professors participated, visiting major mechanical industry sites in South Korea. Participants toured HD Hyundai Infracore (Incheon), InBody (Cheonan), Doosan Enerbility (Changwon), and DN Solutions (Changwon), observing advanced manufacturing processes and learning about the latest technological trends in the industry. This program, which began in 2011, is an established international exchange initiative held annually, with hosting duties alternating between the two countries. Last year, Yonsei students visited Keio University and toured industrial sites in Japan, and this year, Keio students explored industrial sites in Korea, broadening their global perspectives. Yonsei’s Department of Mechanical Engineering plans to continue developing this program to provide students with direct industry exposure and expand their international outlook.
- 기계공학부 2025.02.21
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172
- Recent progress in Arduino- and smartphone-based sensors for biochemical and environmental analysis
- Recent progress in Arduino- and smartphone-based sensors for biochemical and environmental analysis Professor WonHyoung Ryu's research team from the Department of Mechanical Engineering, in collaboration with the research team from the Department of Pharmaceutical Sciences at Pharmaceutical Technical University in Uzbekistan, has published a comprehensive review titled "Recent progress in Arduino- and smartphone-based sensors for biochemical and environmental analysis." This review was featured in the prestigious journal "TrAC Trends in Analytical Chemistry" (Impact Factor: 11.8, Top 0.5%, Volume 183) in February 2025. The manuscript analyzes recent advancements in Arduino- and smartphone-based sensors, focusing on their applications in biochemical and environmental analysis. Additionally, the study offers insights into future goals and potential developments in this rapidly evolving field, based on both reported research and the authors' expertise. The link: doi.org/10.1016/j.trac.2024.118103
- 기계공학부 2025.02.04
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171
- Development of high-current density triboelectric nanogenerators based on stacked grating structures (December 1, 2024)
- Development of high-current density triboelectric nanogenerators based on stacked grating structures Professor Jongbaeg Kim’s research team from the Department of Mechanical Engineering (co-first authors of this study are Hee-jin Ko and Heejun Seong) has developed a triboelectric nanogenerator (TENG) featuring a stackable grating structure. By converting vertical displacement into lateral sliding motion, the newly developed TENG achieves a high output current density while minimizing the increase in stack height. Moreover, thanks to its robust design, the device maintained stable performance even after 45,000 consecutive cycles. Remarkably, with fewer than six mechanical deformations, it successfully powered and transmitted data from a wireless environmental sensor, demonstrating strong potential for applications in small-scale vertical vibration-based energy harvesting. These research findings were published in Nano Energy (Impact Factor: 16.8) in December 2024 The link: https://www.sciencedirect.com/science/article/pii/S2211285524010103
- 기계공학부 2025.01.21