Search Results - "Ryu, Jihyun"
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Portable, Disposable, Paper-Based Microbial Fuel Cell Sensor Utilizing Freeze-Dried Bacteria for In Situ Water Quality Monitoring
Published in ACS omega (16-06-2020)“…Water quality monitoring is becoming an essential part of our lives as increasing human activities continue to spill unknown and unexpected contaminants into…”
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Journal Article -
2
Bioelectricity production from sweat-activated germination of bacterial endospores
Published in Biosensors & bioelectronics (15-08-2021)“…A microbial fuel cell is created that uses a bacterium's natural ability to revive from dormancy to provide on-demand power for next-generation wearable…”
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Journal Article -
3
A sweat-activated, wearable microbial fuel cell for long-term, on-demand power generation
Published in Biosensors & bioelectronics (01-06-2022)“…In this work, we enabled on-demand, long-functioning, sweat-based power generation through a wearable paper-based microbial fuel cell (MFC) using a novel…”
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4
A simple, inexpensive, and rapid method to assess antibiotic effectiveness against exoelectrogenic bacteria
Published in Biosensors & bioelectronics (15-11-2020)“…A sufficiently fast and simple antimicrobial susceptibility testing (AST) is urgently required to guide effective antibiotic usages and to surveil the…”
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Journal Article -
5
Horizontally structured microbial fuel cells in yarns and woven fabrics for wearable bioenergy harvesting
Published in Journal of power sources (01-02-2021)“…Integration of advanced microbial fuel cell technology with conventional textile processes enables the emergence of wearable bioenergy harvesting techniques…”
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6
A scalable yarn-based biobattery for biochemical energy harvesting in smart textiles
Published in Nano energy (01-08-2020)“…Fiber-based and fiber-formed power sources that can be seamlessly integrated into fabrics are of great importance to the development of smart textiles. In this…”
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7
Moisture-Responsive Paper Robotics
Published in Journal of microelectromechanical systems (01-10-2020)“…Origami structures held promise for their flexibility, simultaneous responsiveness, and adaptability, yet they are vulnerable due to the hygroscopic property…”
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Journal Article -
8
Additive Manufacturing of Living Electrodes
Published in Journal of microelectromechanical systems (01-10-2020)“…The combination of electrochemically active microorganisms with miniaturized electronics has immense potential for augmenting a wide range of practical…”
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Journal Article -
9
A 1-D Yarn-Based Biobattery for Scalable Power Generation in 2-D and 3-D Structured Textiles
Published in Journal of microelectromechanical systems (01-10-2020)“…The next generation of textile-based wearable batteries will be built on 1-D fiber/yarn through a bottom-up approach. Functional yarn fibers will be weaved or…”
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10
Wearable Microbial Fuel Cells
Published 01-01-2021“…Sweat-based wearable electronics are attracting tremendous attention for the real-time, non-invasive collection of personalized information contained in human…”
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Dissertation -
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Obtaining Thickness-Limited Electrospray Deposition for 3D Coating
Published in ACS applied materials & interfaces (04-04-2018)“…Electrospray processing utilizes the balance of electrostatic forces and surface tension within a charged spray to produce charged microdroplets with a narrow…”
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Journal Article -
12
Paper Robotics: Self‐Folding, Gripping, and Locomotion
Published in Advanced materials technologies (01-04-2020)“…Soft robotics driven by origami can fundamentally advance robotic functionalities by significantly improving continuum, compliance, and configurability. Here,…”
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Journal Article -
13
Disintegrating paper-based touch sensors
Published 01-01-2016“…This thesis investigates the disintegrating properties of compacted cellulose-based material used as touch sensors. Pressurized compaction of powdered…”
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Dissertation -
14
Early Diagnosis and Prediction of Wafer Quality Using Machine Learning on sub-10nm Logic Technology
Published in 2020 IEEE International Reliability Physics Symposium (IRPS) (01-04-2020)“…This paper proposes to use machine learning (ML) methods to predict wafer quality using Fab inline measured items, DC measurements, and DVS (Dynamic Voltage…”
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