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dc.contributor.advisorPalacios, Tomás
dc.contributor.authorXue, Mantian
dc.date.accessioned2023-03-31T14:41:18Z
dc.date.available2023-03-31T14:41:18Z
dc.date.issued2023-02
dc.date.submitted2023-02-28T14:39:30.783Z
dc.identifier.urihttps://hdl.handle.net/1721.1/150232
dc.description.abstractGraphene and other two-dimensional materials have garnered significant attention as potential biochemical and chemical sensors due to their unique physical and electrical properties. However, their use has been limited by significant device-to-device variation resulting from non-uniform synthesis and fabrication processes. To overcome this challenge, we have developed a bioelectronic sensing platform comprising thousands of integrated sensing units, custom-designed high-speed readout electronics, and machine-learning-based inference. This platform has demonstrated reconfigurable sensing capability in both the liquid and gas phases, with highly sensitive, reversible, and real-time responses to potassium, sodium, and calcium ions in complexed solutions. Additionally, using a biomimetic "dual-monolayer" construct, we have observed nature-like specific interactions with the CXCL12 ligand and HIV-coat glycoprotein in 100% human serum. Furthermore, the platform is capable of providing highly distinguishable fingerprints of relevant biomarkers in breath. Machine learning models trained on multi-dimensional data collected by the multiplexed sensor array is used to enhance the sensing system’s functionality. In summary, our bioelectronic sensing platform represents an end-to-end, versatile, robust, and high-performing solution for the detection of biochemical species, with potential applications in health monitoring and disease diagnosis.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright MIT
dc.rights.urihttp://rightsstatements.org/page/InC-EDU/1.0/
dc.titleGraphene-based Biochemical Sensing Array: Materials, System Design and Data Processing
dc.typeThesis
dc.description.degreePh.D.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
mit.thesis.degreeDoctoral
thesis.degree.nameDoctor of Philosophy


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