| Literature DB >> 33321693 |
Mohammed M Rahman1, Md M Alam2, Abdullah M Asiri1, Firoz A D M Opo3,4.
Abstract
The facile wet-chemical technique was used to prepare the low-dimensional nano-formulated porous mixed metal oxide nanomaterials (CuO.Mn2O3.NiO; CMNO NMs) in an alkaline medium at low temperature. Detailed structural, morphological, crystalline, and functional characterization of CMNO NMs were performed by X-ray photoelectron spectroscopy (XPS), powder X-ray diffraction (XRD), ultraviolet-visible spectroscopy (UV-vis), Fourier-transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM), and energy-dispersive X-ray spectroscopy (EDS) analyses. An efficient and selective creatine (CA) sensor probe was fabricated by using CMNO NMs decorated onto glassy carbon electrode (GCE) as CMNO NMs/GCE by using Nafion adhesive (5% suspension in ethanol). The relation of current versus the concentration of CA was plotted to draw a calibration curve of the CMNO NMs/GCE sensor probe, which was found to have a very linear value (r2 = 0.9995) over a large dynamic range (LDR: 0.1 nM~0.1 mM) for selective CA detection. The slope of LDR by considering the active surface area of GCE (0.0316 cm2) was applied to estimate the sensor sensitivity (14.6308 µAµM-1 cm-2). Moreover, the detection limit (21.63 ± 0.05 pM) of CMNO MNs modified GCE was calculated from the signal/noise (S/N) ratio at 3. As a CA sensor probe, it exhibited long-term stability, good reproducibility, and fast response time in the detection of CA by electrochemical approach. Therefore, this research technique is introduced as a promising platform to develop an efficient sensor probe for cancer metabolic biomarker by using nano-formulated mixed metal oxides for biochemical as well as biomedical research for the safety of health care fields.Entities:
Keywords: clinical research; creatine sensor; glassy carbon electrode; health care field; porous nano-formulated CMNO nanomaterials; wet-chemical technique
Mesh:
Substances:
Year: 2020 PMID: 33321693 PMCID: PMC7763360 DOI: 10.3390/s20247060
Source DB: PubMed Journal: Sensors (Basel) ISSN: 1424-8220 Impact factor: 3.576