Chong Hyun Lee

Prof. Chong Hyun Lee

orcid

Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2016 in Carbon
Verified
Journal Article
Closed access
SAShawkat Ali
Shawkat Ali
AHArshad Hassan
Arshad Hassan
GHGul Hassan
Gul Hassan
Jinho BaeJinho Bae
Jinho Bae
CLChong Hyun Lee
Chong Hyun Lee

1 April 2018 in Composites Part A: Applied Science and Manufacturing
Verified
Journal Article
Closed access
GHGul Hassan
Gul Hassan
Jinho BaeJinho Bae
Jinho Bae
AHArshad Hassan
Arshad Hassan
SAShawkat Ali
Shawkat Ali
CLChong Hyun Lee
Chong Hyun Lee
YCYohan Choi
Yohan Choi

12 April 2018 in Scientific Reports
Verified
Journal Article
Open access
PDF file
SAShawkat Ali
Shawkat Ali
AHArshad Hassan
Arshad Hassan
GHGul Hassan
Gul Hassan
CEChang-Ho Eun
Chang-Ho Eun
Jinho BaeJinho Bae
Jinho Bae
IKIn-Jung Kim
In-Jung Kim
A novel disposable all-printed electronic biosensor is proposed for a fast detection and classification of bacteria. This biosensor is applied to classify three types of popular pathogens: Salmonella typhimurium, and the Escherichia coli strains JM109 and DH5-α. The proposed sensor consists of inter-digital silver electrodes fabricated through an inkjet material printer and silver nanowires uniformly decorated on the electrodes through the electrohydrodynamic technique on a polyamide based polyethylene terephthalate substrate. The best sensitivity of the proposed sensor is achieved at 200 µm teeth spaces of the inter-digital electrodes along the density of the silver nanowires at 30 × 103/mm2. The biosensor operates on ±2.5 V and gives the impedance value against each bacteria type in 8 min after sample injection. The sample data are measured through an impedance analyzer and analyzed through pattern recognition methods such as linear discriminate analysis, maximum likelihood, and back propagation artificial neural network to classify each type of bacteria. A perfect classification and cross-validation is achieved by using the unique fingerprints extracted from the proposed biosensor through all the applied classifiers. The overall experimental results demonstrate that the proposed disposable all-printed biosensor is applicable for the rapid detection and classification of pathogens.

19 October 2016 in Langmuir
Verified
Journal Article
Closed access
SAShawkat Ali
Shawkat Ali
AHArshad Hassan
Arshad Hassan
Jinho BaeJinho Bae
Jinho Bae
CLChong Hyun Lee
Chong Hyun Lee
JKJuho Kim
Juho Kim

9 June 2022 in Advanced Energy Materials
Verified
Journal Article
Closed access
JAJunseong Ahn
Junseong Ahn
JKJi‐Seok Kim
Ji‐Seok Kim
YJYoonsang Jeong
Yoonsang Jeong
SHSoonhyoung Hwang
Soonhyoung Hwang
HYHyunjoon Yoo
Hyunjoon Yoo
IPInkyu Park
Inkyu Park

1 October 2015 in Organic Electronics
Verified
Journal Article
Closed access
SAShawkat Ali
Shawkat Ali
Jinho BaeJinho Bae
Jinho Bae
CLChong Hyun Lee
Chong Hyun Lee
KCKyung Hyun Choi
Kyung Hyun Choi
YDYang Hoi Doh
Yang Hoi Doh