Transmission Properties of Microwave Multiresonant Modes to Pathogenic Bacteria and Their Discrimination

• Published in: IEEE sensors journal Vol. 24; no. 7; pp. 9982 - 9988
• Main Authors: Lee, Hee-Jo, Dey, Debasish Kumar, Kang, Sun Chul
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Bacteria; Coliforms; Coupled microstrip line resonator (CMLR); E coli; Fluorescence; Frequency ranges; Microorganisms; Microstrip resonators; Microstrip transmission lines; Microwave imaging; microwave multiresonant modes (MMRMs); Microwave theory and techniques; pathogenic bacterium; Resonant frequency; Sensors; transmission coefficient
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2024.3366505

In this study, we report the transmission characteristics based on microwave multiresonant modes (MMRMs) for the pathogenic bacteria, Escherichia coli and Bacillus cereus, in the frequency range from 0.5 to 10 GHz. In particular, we deeply analyze the differentiation between these microorganisms via transmission coefficient (<inline-formula> <tex-math notation="LaTeX">{T} </tex-math></inline-formula>) at a specific concentration (~0.5 OD600/mL). The bacteria were evaluated on a coupled microstrip line resonator with the four MMRMs in the observed frequency region. According to the measured results, the transmission coefficient difference (<inline-formula> <tex-math notation="LaTeX">\Delta {T} </tex-math></inline-formula>) between the bacteria in a Luria-Bertani medium indicated a distinct level and displayed linear characteristics for the MMRMs from the first to third resonant modes. Based on the sensing results, these bacteria with lower concentrations (0.1, 0.05, and 0.01 OD600/mL) were detectable and distinguished from MMRMs. Consequently, we showed that the <inline-formula> <tex-math notation="LaTeX">\Delta {T} </tex-math></inline-formula> could discriminate harmful germs at a given concentration using the MMRMs technique. In the future, we anticipate that the sensing approach will lead to advancements in traditional, time-consuming, and expensive bio-sensing systems for harmful bacteria detection and identification.