Silicon Nanoribbon FET Sensors : Fabrication, Surface Modification and Microfluidic Integration

Over the past decade, the field of medical diagnostics has seen an incredible amount of research towards the integration of one-dimensional nanostructures such as carbon nanotubes, metallic and semiconducting nanowires and nanoribbons for a variety of bio-applications. Among the mentioned one-dimens...

Full description

Bibliographic Details
Main Author: Afrasiabi, Roodabeh
Format: Doctoral Thesis
Language:English
Published: KTH, Material- och nanofysik 2016
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191178
http://nbn-resolving.de/urn:isbn:978-91-7729-075-9
Description
Summary:Over the past decade, the field of medical diagnostics has seen an incredible amount of research towards the integration of one-dimensional nanostructures such as carbon nanotubes, metallic and semiconducting nanowires and nanoribbons for a variety of bio-applications. Among the mentioned one-dimensional structures, silicon nanoribbon (SiNR) field-effect transistors (FET) as electro-chemical nanosensors hold particular promise for label-free, real-time and sensitive detection of biomolecules using affinity-based detection. In SiNR FET sensors, electrical transport is primarily along the nanoribbon axis in a thin sheet (&lt; 30 nm) serving as the channel. High sensitivity is achieved because of the large surface-to-volume ratio which allows analytes to bind anywhere along the NR affecting the entire conductivity by their surface charge. Unfortunately, sensitivity without selectivity is still an ongoing issue and this thesis aims at addressing the detection challenges and further proposing effective developments, such as parallel and multiple detection through using individually functionalized SiNRs.We present here a comprehensive study on design, fabrication, operation and device performance parameters for the next generation of SiNR FET sensors towards multiplexed, label-free detection of biomolecules using an on-chip microfluidic layer which is based on a highly cross-linked epoxy. We first study the sensitivity of different NR dimensions followed by analysis of the drift and hysteresis effects. We have also addressed two types of gate oxides (namely SiO2 and Al2O3) which are commonly used in standard CMOS fabrication of ISFETs (Ion sensitive FET). Not only have we studied and compared the hysteresis and response-time effects in the mentioned two types of oxides but we have also suggested a new integrated on-chip reference nanoribbon/microfluidics combination to monitor the long-term drift in the SiNR FET nanosensors. Our results show that compared to Al2O3, silicon-oxide gated SiNR FET sensors show high hysteresis and slow-response which limit their performance only to background electrolytes with low ionic strength. Al2O3 on the other hand proves more promising as the gate-oxide of choice for use in nanosensors. We have also illustrated that the new integrated sensor NR/Reference NR can be utilized for real-time monitoring of the above studied sources of error during pH-sensing. Furthermore, we have introduced a new surface silanization (using 3-aminopropyltriethoxysilane) method utilizing microwave-assisted heating which compared to conventional heating, yields an amino-terminated monolayer with high surface coverage on the oxide surface of the nanoribbons. A highly uniform and dense monolayer not only reduces the pH sensitivity of the bare-silicon oxide surface in a physiological media but also allows for more receptors to be immobilized on the surface. Protocols for surface functionalization and biomolecule immobilization were evaluated using model systems. Selective spotting of receptor molecules can be used to achieve localized functionalization of individual SiNRs, opening up opportunities for multiplexed detection of analytes.Additionally, we present here a novel approach by integrating droplet-based microfluidics with the SiNR FET sensors. Using the new system we are able to successfully detect trains of droplets with various pH values. The integrated system enables a wide range of label-free biochemical and macromolecule sensing applications based on detection of biological events such as enzyme-substrate interactions within the droplets. === <p>QC 20160825</p>