Nowadays, several neurological disorders and neurocrine tumours are associated with dopamine (DA) concentrations in various biological fluids. Highly accurate and ultrasensitive detection of DA levels in different biological samples in real-time can change and improve the quality of a patient’s life in addition to reducing the treatment cost. Therefore, the design and development of diagnostic tool for in vivo and in vitro monitoring of DA is of considerable clinical and pharmacological importance. In recent decades, a large number of techniques have been established for DA detection, including chromatography coupled to mass spectrometry, spectroscopic approaches, and electrochemical (EC) methods. These methods are effective, but most of them still have some drawbacks such as consuming time, effort, and money. Added to that, sometimes they need complex procedures to obtain good sensitivity and suffer from low selectivity due to interference from other biological species such as uric acid (UA) and ascorbic acid (AA). Advanced materials can offer remarkable opportunities to overcome drawbacks in conventional DA sensors. This review aims to explain challenges related to DA detection using different techniques, and to summarize and highlight recent advancements in materials used and approaches applied for several sensor surface modification for the monitoring of DA. Also, it focuses on the analytical features of the EC and optical-based sensing techniques available.

For a healthy life, the human biological system should work in order. Scheduled lifestyle and lack of nutrients usually lead to fluctuations in the biological entities levels such as neurotransmitters (NTs), proteins, and hormones, which in turns put the human health in risk. Dopamine (DA) is an extremely important catecholamine NT distributed in the central nervous system. Its level in the body controls the function of human metabolism, central nervous, renal, hormonal, and cardiovascular systems. It is closely related to the major domains of human cognition, feeling, and human desires, as well as learning. Several neurological disorders such as schizophrenia and Parkinson’s disease are related to the extreme abnormalities in DA levels. Therefore, the development of an accurate, effective, and highly sensitive method for rapid determination of DA concentrations is desired. Up to now, different methods have been reported for DA detection such as electrochemical strategies, high-performance liquid chromatography, colorimetry, and capillary electrophoresis mass spectrometry. However, most of them have some limitations. Surface plasmon resonance (SPR) spectroscopy was widely used in biosensing. However, its use to detect NTs is still growing and has fascinated impressive attention of the scientific community. The focus in this concise review paper will be on the principle of SPR sensors and its operation mechanism, the factors that affect the sensor performance. The efficiency of SPR biosensors to detect several clinically related analytes will be mentioned. DA functions in the human body will be explained. Additionally, this review will cover the incorporation of nanomaterials into SPR biosensors and its potential for DA sensing with mention to its advantages and disadvantages.

In today's technologically advanced era, the demand for swift and precise analyses spans scientific research and industrial applications alike. Surface plasmon resonance (SPR) technology has surged in popularity, due to its real‐time measurement capabilities with exceptional sensitivity and label‐free operation. These attributes have propelled SPR into prominence across diverse fields including medical diagnostics, pharmaceuticals, food safety, and environmental monitoring of hazardous compounds. Here the key principles behind SPR are delved, and the workings of SPR‐based sensors are elucidated. Additionally, the latest advancements in SPR biosensors tailored for detecting a variety of analytes, with a focus on dopamine (DA) and α‐synuclein, which hold particular significance in the context of neurological disorders, are examined. Here potential breakthroughs of SPR technology are discussed, thanks to the integration with nanomaterials, lab‐on‐a‐chip devices, multiplexing formats, and machine learning. Finally, new resonance modes are discussed based on subwavelength structures leveraging guided mode resonance (GMR), surface lattice resonance (SLR), and bound state in the continuum (BIC) mode resonance and their potential applications, particularly in nonplasmonic refractive index biosensors.

Abnormality of dopamine (DA), a vital neurotransmitter in the brain’s neuronal pathways, causes several neurological diseases. Rapid and sensitive sensors for DA detection are required for early diagnosis of such disorders. Herein, a carbon quantum dot (CQD)-based refractive index surface plasmon resonance (SPR) sensor was designed. The sensor performance was evaluated for various concentrations of DA. Increasing DA levels yielded blue-shifted SPR dips. The experimental findings revealed an excellent sensitivity response of 0.138°/pM in a linear range from 0.001 to 100 pM and a high binding affinity of 6.234 TM⁻¹. The effects of varied concentrations of DA on the optical characteristics of CQD thin film were further proved theoretically. Increased DA levels decreased the thickness and real part of the refractive index of CQD film, according to fitting results. Furthermore, the observed reduction in surface roughness using AFM demonstrated that DA was bound to the sensor layer. This, in turn, explained the blue shift in SPR reflectance curves. This optical sensor offers great potential as a trustworthy solution for direct measurement due to its simple construction, high sensitivity, and other sensing features.

In the present work, graphene oxide (GO)–polyvinyl alcohol (PVA) composites thin film has been successfully synthesized and prepared by spin coating techniques. Then, the properties and morphology of the samples were characterized using Fourier transform infrared spectroscopy (FTIR), ultraviolet-visible spectroscopy (UV-Vis), and atomic force microscopy (AFM). Experimental FTIR results for GO–PVA thin film demonstrated the existence of important functional groups such as -CH₂ stretching, C=O stretching, and O–H stretching. Furthermore, UV-Vis analysis indicated that the GO–PVA thin film had the highest absorbance that can be observed at wavelengths ranging from 200 to 500 nm with a band gap of 4.082 eV. The surface morphology of the GO–PVA thin film indicated the thickness increased when in contact with carbaryl. The incorporation of the GO–PVA thin film with an optical method based on the surface plasmon resonance (SPR) phenomenon demonstrated a positive response for the detection of carbaryl pesticide as low as 0.02 ppb. This study has successfully proposed that the GO–PVA thin film has high potential as a polymer nanomaterial-based SPR sensor for pesticide detection.

In this study, graphene quantum dots (GQDs) and polyvinyl alcohol (PVA) composite was prepared and then coated on the surface of gold thin film via the spin coating technique. Subsequently, Fourier transform infrared spectroscopy (FT-IR), atomic force microscopy (AFM), and ultraviolet-visible spectroscopy (UV–Vis) were adopted to understand the structure, surface morphology, and optical properties of the prepared samples. The FT-IR spectral analysis revealed important bands, such as O–H stretching, C=O stretching, C-H stretching, and O=C=O stretching vibrations. The surface roughness of the GQDs-PVA composite thin film was found to be increased after exposure to carbaryl. On the other hand, the optical absorbance of the GQDs-PVA thin film was obtained and further analysis was conducted, revealing a band gap E_g value of 4.090 eV. The sensing potential of the thin film was analyzed using surface plasmon resonance (SPR) spectroscopy. The findings demonstrated that the developed sensor’s lowest detection limit for carbaryl was 0.001 ppb, which was lower than that previously reported, i.e., 0.007 ppb. Moreover, other sensing performance parameters, such as full width at half maximum, detection accuracy, and signal-to-noise ratio, were also investigated to evaluate the sensor’s efficiency.