Graphene-based Biochemical Sensing Array: Materials, System Design and Data Processing

Graphene 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.

Name thesis:degree_name

Doctoral

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2023

Author dc:creator

• Xue, Mantian

Advisor dc:contributor.advisor

• Palacios, Tomás

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/150232

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/150232