Author
Listed:
- Kamyar Behrouzi
(University of California
Berkeley Sensor and Actuator Center (BSAC))
- Zahra Khodabakhshi Fard
(University of California)
- Chun-Ming Chen
(University of California)
- Peisheng He
(University of California
Berkeley Sensor and Actuator Center (BSAC))
- Megan Teng
(University of California
Berkeley Sensor and Actuator Center (BSAC))
- Liwei Lin
(University of California
Berkeley Sensor and Actuator Center (BSAC))
Abstract
A major challenge in addressing global health issues is developing simple, affordable biosensors with high sensitivity and specificity. Significant progress has been made in at-home medical detection kits, especially during the COVID-19 pandemic. Here, we demonstrated a coffee-ring biosensor with ultrahigh sensitivity, utilizing the evaporation of two sessile droplets and the formation of coffee-rings with asymmetric nanoplasmonic patterns to detect disease-relevant proteins as low as 3 pg/ml, under 12 min. Experimentally, a protein-laden droplet dries on a nanofibrous membrane, pre-concentrating biomarkers at the coffee ring. A second plasmonic droplet with functionalized gold nanoshells is then deposited at an overlapping spot and dried, forming a visible asymmetric plasmonic pattern due to distinct aggregation mechanisms. To enhance detection sensitivity, a deep neural model integrating generative and convolutional networks was used to enable quantitative biomarker diagnosis from smartphone photos. We tested four different proteins, Procalcitonin (PCT) for sepsis, SARS-CoV-2 Nucleocapsid (N) protein for COVID-19, Carcinoembryonic antigen (CEA) and Prostate-specific antigen (PSA) for cancer diagnosis, showing a working concentration range over five orders of magnitude. Sensitivities surpass equivalent lateral flow immunoassays by over two orders of magnitude using human saliva samples. The detection principle, along with the device, and materials can be further advanced for early disease diagnostics.
Suggested Citation
Kamyar Behrouzi & Zahra Khodabakhshi Fard & Chun-Ming Chen & Peisheng He & Megan Teng & Liwei Lin, 2025.
"Plasmonic coffee-ring biosensing for AI-assisted point-of-care diagnostics,"
Nature Communications, Nature, vol. 16(1), pages 1-13, December.
Handle:
RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59868-y
DOI: 10.1038/s41467-025-59868-y
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