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PhD Defence Mohammad Saghafi | Everything Must Either Be or Not Be - Proof of Concept for Stochastic Digital Biosensing with CMOS-based Nanocapacitor Arrays

Everything Must Either Be or Not Be - Proof of Concept for Stochastic Digital Biosensing with CMOS-based Nanocapacitor Arrays

The PhD defence of Mohammad Saghafi will take place in the Waaier Building of the University of Twente and can be followed by a live stream.
Live Stream

Mohammad Saghafi is a PhD student in the Department of Bio electronics. (Co)Promotors are prof.dr. S.J.G. Lemay from the Faculty of Science & Technology and prof.dr.ir. F.P. Widdershoven from Delft University of Technology.

This dissertation explores CMOS-based nanocapacitor arrays (CMOS-NCAs) as a powerful new platform for biosensing. By leveraging high-frequency impedance measurements and massively parallel nanosensors, CMOS-NCAs offer unmatched spatial resolution and sensitivity to nanoscale biological processes—addressing longstanding challenges in surface chemistry, molecular recognition, and detection in complex media.

The research highlights the advantages of CMOS-NCAs over traditional biosensing techniques, including their ability to detect single nano-analytes under physiological conditions. Experiments demonstrate sensitivity to molecular events in self-assembled monolayers and real-time monitoring of vesicle fusion in supported lipid bilayers—critical for studying membrane dynamics and protein-lipid interactions.

Further innovations include digital detection of single-stranded DNA via toehold-mediated strand displacement with nanoparticles, as well as selective, label-free detection of SARS-CoV-2 using aptamer-functionalized sensors. The platform also probes inside lipid vesicles, enabling non-invasive detection of encapsulated particles like exosomes and mitochondria.

With robust microfluidic integration, optimized chip design, and advanced data analysis, this work establishes CMOS-NCAs as a scalable, cost-effective solution for biosensing in clinical diagnostics, biological research, and beyond. Future directions include platform miniaturization, AI integration, and applications in personalized medicine and environmental monitoring.