Jeong-Yeol Yoon

Interests

Teaching

Biosensor, Biomaterial, Nanotechnology

Research

Biosensor, Food Safety, Lab-on-a-Chip, Organ-on-a-Chip

Courses

Scholarly Contributions

Books

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  Machine Learning and Artificial Intelligence in Chemical and Biological Sensing covers the theoretical background and practical applications of various ML/AI methods toward chemical and biological sensing. No comprehensive reference text has been available previously to cover the wide breadth of this topic. The book's editors have written the first three chapters to firmly introduce the reader to fundamental ML theories that can be used for chemical/biosensing. Subsequent chapters then cover the practical applications with contributions by various experts in the field. Sections show how ML and AI-based techniques can provide solutions for: 1) identifying and quantifying target molecules when specific receptors are unavailable 2) analyzing complex mixtures of target molecules, such as gut microbiome and soil microbiome 3) analyzing high-throughput and high-dimensional data, such as drug screening, molecular interaction, and environmental toxicant analysis, 4) analyzing complex data sets where fingerprinting approach is needed This book is written primarily for upper undergraduate students, graduate students, research staff, and faculty members at teaching and research universities and colleges who are working on chemical sensing, biosensing, analytical chemistry, analytical biochemistry, biomedical imaging, medical diagnostics, environmental monitoring, and agricultural applications.

Chapters

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  Zika virus (ZIKV) infection may cause serious birth defects and is a critical concern for women of child-bearing age in affected regions. A simple, portable, and easy-to-use ZIKV detection method would enable point-of-care testing, which may aid in prevention of the spread of the virus. Herein, we describe a reverse transcription isothermal loop-mediated amplification (RT-LAMP) method that detects the presence of ZIKV RNA in complex samples (e.g., blood, urine, and tap water). Phenol red is the colorimetric indicator of successful amplification. Color changes based on the amplified RT-LAMP product from the presence of viral target are monitored using a smartphone camera under ambient light conditions. A single viral RNA molecule per μL can be detected in as quickly as 15 min using this method with 100% sensitivity and 100% specificity in blood and tap water, while 100% sensitivity and 67% specificity in urine. This platform can also be used to identify other viruses including SARS-CoV-2 and improve the current state of field-based diagnostics.

Journals/Publications

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  This study presents a novel smartphone-based, machine-learning-assisted multispectral classification method for identifying airborne micro- and nanoplastics (MNPs). Instead of commercial polymeric microspheres, coffee grinder-based cryogrinding generated nonuniform MNPs from real-world plastic products with highly irregular shapes and heterogenous size distributions. The low-cost handheld device comprises a smartphone, a spectral mask array made from plastic color films, and a discrete multiplexed illumination device. A stack of images was captured across multiple wavelength ranges, and the RGB ratios were extracted without using morphological information. An XGBoost model was trained on two datasets: dry and wet MNP samples passively collected on a glass slide, simulating two types of airborne MNPs. The model successfully distinguished plastics from clay with 89-99 % accuracy and classified six plastic types with 79-87 % accuracy for dry and wet MNPs. This method offers a promising toolkit for airborne MNP monitoring.

Proceedings Publications

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  Sensitive detection of PFOA, type of PFAS (perfluorinated-alkyl substances), was demonstrated on paper-based microfluidic chip utilizing competitive binding with albumin or casein and cellulose fibers. It altered the capillary flow rate profile and monitored by a smartphone camera. Detection limit was 1-10 fg/µL (1-10 ppt).

Presentations

Poster Presentations

Reviews