Development of gold nanoparticles decorated 3D graphene foam as an ultra-sensitive and label-free neutrophil gelatinase associated lipocalin electrochemical sensor for acute kidney injury detection | |
| Author | Pobporn Danvirutai |
| Call Number | AIT Diss. no.ISE-21-05 |
| Subject(s) | Electrochemical sensors Raman spectroscopy Nanoparticles |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering in Microelectronics and Embedded Systems, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Dissertation ; no. ISE-21-05 |
| Abstract | This dissertation reports an investigation of an ultra-sensitive and highly-specific electrochemical immunosensor development based on three-dimensional graphene/nickel foam (GF) decorated with gold nanoparticles (AuNPs) for the detection of Neutrophil Gelatinase Associated Lipocalin (NGAL), a biomarker of Acute Kidney Injury (AKI). A low NGAL limit of detection (LOD) of 42 pg/ml and a linear range (LR) of 0.05-210 ng/ml were achieved. Though several electrode platforms have been proposed, either LOD or LR are limited for each method. Our platform can achieve low LOD while keeping broad LR of sensing. Specificity was tested for NGAL detection against uric acid and creatinine interference. The attained performances might be ascribed to large specific surface area of GF and AuNPs, improved electron transfer from analyte via graphene-nickel-gold electric dipole enhancement. The results demonstrated the proposed platform was potential for ultra-sensitive, highly specific, non-invasive and real-time electrochemical detection of NGAL. At the first stage, concentrated NGAL solution was purchased to test sensitivity and specificity and was reported in Danvirutai et al (2020). Finally, this platform has been tested with 5 genuine urine samples of NGAL sensing which form a trend of the sensor at the trace amount of urine NGAL. This platform presents a promising approach for non-invasive and near real-time renal state monitoring. |
| Year | 2021 |
| Corresponding Series Added Entry | Asian Institute of Technology. Dissertation ; no. ISE-21-05 |
| Type | Dissertation |
| School | School of Engineering and Technology (SET) |
| Department | Department of Industrial Systems Engineering (DISE) |
| Academic Program/FoS | Industrial Systems Engineering (ISE) |
| Chairperson(s) | Mongkol Ekpanyapong; |
| Examination Committee(s) | Adisorn Tuantranont;Huynh Trung Luong; |
| Scholarship Donor(s) | Asian Institute of Technology Fellowship; |
| Degree | Thesis (Ph. D.) - Asian Institute of Technology, 2021 |