journal article·2024-06-19Open access

Minimizing Contact Resistance and Flicker Noise in Micro Graphene Hall Sensors Using Persistent Carbene Modified Gold Electrodes

Honglin Sun, Ting Huang, Md Masruck Alam, Jingwei Li, Dong Wook Jang, Tianle Wang, Haohan Chen, Yi-Ping Ho, Zhaoli Gao

ACS Applied Materials & Interfaces· Volume 16· Issue 24

Abstract

High Resolution Image Download MS PowerPoint Slide Scalable micro graphene Hall sensors (μGHSs) hold tremendous potential for highly sensitive and label-free biomagnetic sensing in physiological solutions. To enhance the performance of these devices, it is crucial to optimize frequency-dependent flicker noise to reduce the limit of detection (LOD), but it remains a great challenge due to the large contact resistance at the graphene–metal contact. Here we present a surface modification strategy employing persistent carbene on gold electrodes to reduce the contact resistivity by a factor of 25, greatly diminishing μGHS flicker noise by a factor of 1000 to 3.13 × 10 –14 V 2 /Hz while simultaneously lowering the magnetic LOD S B 1/2 to 1440 nT/Hz 1/2 at 1 kHz under a 100 μA bias current. To the best of our knowledge, this represents the lowest S B 1/2 reported for scalable μGHSs fabricated through wafer-scale photolithography. The reduction in contact noise is attributed to the π–π stacking interaction between the graphene and the benzene rings of persistent carbene, as well as the decrease in the work function of gold as confirmed by Kelvin Probe Force Microscopy. By incorporating a microcoil into the μGHS, we have demonstrated the real-time detection of superparamagnetic nanoparticles (SNPs), achieving a remarkable LOD of ∼528 μg/L. This advancement holds great potential for the label-free detection of magnetic biomarkers, e.g., ferritin, for the early diagnosis of diseases associated with iron overload, such as hereditary hemochromatosis (HHC).
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Research context

OpenAlex topics: Molecular Junctions and Nanostructures · Advanced Sensor and Energy Harvesting Materials · Advanced Memory and Neural Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China

Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon 999077, Hong Kong SAR, China

School of Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China

Centre for Novel Biomaterials, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China

Hong Kong Branch of CAS Center for Excellence in Animal Evolution and Genetics, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China

State Key Laboratory of Marine Pollution, City University of Hong Kong, Kowloon Tong, Kowloon 999077, Hong Kong SAR, China

Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China

CUHK Shenzhen Research Institute, Nanshan, Shenzhen 518172, China

Funding

Research Grants Council, University Grants Committee · Shun Hing Institute of Advanced Engineering · National Natural Science Foundation of China · Chinese University of Hong Kong

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