The electrochemical biosensors are a class of biosensors which convert biological information such as analyte concentration that is a biological recognition element (biochemical receptor) into current or voltage. Electrochemical biosensors depict propitious diagnostic technology which can detect biomarkers in body fluids such as sweat, blood, feces, or urine. Combinations of suitable immobilization techniques with effective transducers give rise to an efficient biosensor. They have been employed in the food industry, medical sciences, defense, studying plant biology, etc. While sensing complex structures and entities, a large data is obtained, and it becomes difficult to manually interpret all the data. Machine learning helps in interpreting large sensing data. In the case of biosensors, the presence of impurity affects the performance of the sensor and machine learning helps in removing signals obtained from the contaminants to obtain a high sensitivity. In this review, we discuss different types of biosensors along with their applications and the benefits of machine learning. This is followed by a discussion on the challenges, missing gaps in the knowledge, and solutions in the field of electrochemical biosensors. This review aims to serve as a valuable resource for scientists and engineers entering the interdisciplinary field of electrochemical biosensors. Furthermore, this review provides insight into the type of electrochemical biosensors, their applications, the importance of machine learning (ML) in biosensing, and challenges and future outlook.

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Herein, we report the electrochemical sensing of H2O2 in milk samples using an activated glassy carbon electrode (GCE). For this purpose, activation of GCE was carried out in 0.1 M H2SO4 by continuous potential sweeping between -0.7 to 1.8 V for 25 cycles. The activated glassy carbon electrode (AGCE) showed a redox peak at 0.1 V in the neutral medium corresponding to the quinone functional groups present on the electrode surface. The AGCE was studied in (pH 7.4) 0.1 M PBS for the electro-catalysis of H2O2. The surface of the activated electrode was analyzed by Raman spectroscopy and contact angle measurements. In addition, for the activated surface, the contact angle was found to be 85º which indicated the hydrophilic nature of the surface. The different optimization parameters such as effect of electrolyte ions, electrooxidation cycles, and oxidation potential windows were studied to improve the activation process. Finally, AGCE was used to detect H2O2 from 0.1 to 10 mM and the limit of detection was found to be 0.053 mM with a linear correlation coefficient of 0.9633. The selectivity of the sensor towards H2O2 was carried out in the presence of other interferents.

Herein, we demonstrated synthesis and application of silver nanoparticles (Ag-NPs) decorated nitrogen doped single-walled carbon nanotube through a one-step thermal-reduction method using melamine as the nitrogen source. Field-emission scanning electron microscopy (FE-SEM), Fourier-transform infrared spectroscopy (FT-IR) and X-ray diffraction data confirmed the successful synthesis of Ag-NPs functionalized nitrogen doped single-walled carbon nanotubes(Ag-N-SWCNTs). The nitrogen-doping notably modified the properties of the SWCNT and it showed stronger affinity for the attachment of Ag-NPs. By integrating the high surface area and electrical properties of N-SWCNTs with Ag-NPs, the obtained Ag-N-SWCNTs nanocomposite showed high catalytic activity than N-SWCNTs and pristine-SWCNTs. The enzyme-based methods have some disadvantages. For example, high fabrication cost and poor stability, due to these intrinsic disadvantages, non-enzymatic sensors have received more interest in fabrication of sensors. A non-enzymatic electrochemical urea sensor was developed by modifying glassy carbon electrode (GCE) with Ag-N-SWCNTs and a layer of Nafion (Nf). Thus, the fabricated sensor exhibited lower limit of detection (4.7 nM), with an enhanced sensitivity of 141 μAmM −1 cm −2 for urea detection in the range of 66 nM to 20.6 mM(R 2 = 0.966). The reliability of the as-fabricated sensor was successfully investigated by using it to detect urea in tap water and milk samples. The NF/Ag-N-SWCNTs based urea sensor offers several advantages such as simple fabrication procedure, non-enzymatic and low-cost, so this sensor can be applied to detect urea in various samples from food, fertilizer industries and environmental fields. Moreover, the modified electrode showed phenomenal stability with no loss in activity of storage under ambient conditions. In addition, the novel hybrid NF/Ag-N-SWCNTs/GCE showed high selectivity toward urea with good repeatability and reproducibility further confirmed that this method can be utilized for detection of urea.

Semiconducting single-walled carbon nanotubes (s-SWNTs) have emerged as a promising class of electronic materials, but the metallic (m)-SWNTs present in all as-synthesized nanotube samples must be removed for many applications. A high selectivity and high yield separation method has remained elusive. A separation process based on selective chemistry appears to be an attractive route since it is usually relatively simple, but more effective chemicals are needed. Here we demonstrate the first example of a new class of dual selective compounds based on polycyclic aromatic azo compounds, specifically Direct Blue 71 (I), for high-purity separation of s-SWNTs at high yield. Highly enriched (~93% purity) s-SWNTs are produced through the simple process of standing arc-discharge SWNTs with I followed by centrifugation. The s-SWNTs total yield is up to 41%, the highest yet reported for a solution-based separation technique that demonstrates applicability in actual transistors. 91% of transistor devices fabricated with these s-SWNTs exhibited on/off ratios of 10(3) to 10(5) with the best devices showing mobility as high as 21.8 cm(2)/V s with on/off ratio of 10(4). Raman and X-ray photoelectron spectroscopic shifts and ultraviolet-visible-near-infrared (UV-vis-NIR) show that I preferentially complexes with s-SWNTs and preferentially suspends them. Preferential reaction of naphthyl radicals (generated from I with ultrasonication) with m-SWNTs is confirmed by changes in the D-band in the Raman spectroscopy, matrix-assisted desorption-ionization time-of-flight mass spectrometry (MALDI-TOF-MS), and molecular simulation results. The high selectivity of I stems from its unique dual action as both a selective dispersion agent and the generator of radicals which preferentially attack unwanted metallic species.