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.

In the last three decades, a lot of scientific research has been carried out in the field of Carbon nanomaterials all over the world due to their significant electronic, optical, mechanical, chemical and thermal properties. The zero, one, two and three dimensional Carbon nanomaterials (i.e. fullerenes, Carbon nanotubes, Graphene, Carbon quantum dots, Carbon Nanohorns, Nanodiamonds, Carbon Nanofibres and Carbon black) have exhibited such inherent features that can be easily exploited in the development of advanced technology for sensing applications. The employment of nanomaterials within sensors has paved new way and opportunities for the detection of analytes or target molecules. Carbon nanomaterials based electrochemical biosensors have reported biocompatibility, better sensitivity, better selectivity and lower limits of detection to detect a wide range of chemical to biological molecules. In this paper, a comprehensive review has been made to cover recent developments in the field of Carbon based nanomaterials as electrochemical biosensors. The characteristic features of a variety of nanomaterials like fullerenes, Carbon nanotubes, Graphene, Carbon quantum dots, Carbon Nanohorns, Carbon Nanodiamonds, Carbon Nanofibres, Carbon black etc. have been discussed along with their synthesis methods. The recent application of all these nanomaterials as electrochemical biosensors for the detection of various biomolecules have been highlighted; the future prospects and possibilities in this field have been outlined.

Hybrid functional materials, constituting both inorganic and organic components, are considered potential platforms for applications in extremely diverse fields such as optics, micro-electronics, transportation, health, energy, energy storage, diagnosis, housing, environment and the highly relevant area is Internet of Things (IoT). Material properties of hybrid materials can be tuned by modification of the composition on the molecular scale to produce smart materials. Cross-cutting approaches, to synergistically couple molecular engineering and processing allows to tailor complex hybrid systems of various shapes with perfect control over size, composition, functionality, and morphology. The detailed description and discussion of variety of hybrid functional organic-inorganic materials and their contribution in the designing of specific modern technologies is the prime focus of this review.

ZnO has several potential applications into its credit. This review article focuses on the influence of processing parameters involved during the synthesis of ZnO nanoparticles by sol-gel method. During the sol-gel synthesis technique, the processing parameters/experimental conditions can affect the properties of the synthesized material. Processing parameters are the operating conditions that are to be kept under consideration during the synthesis process of nanoparticles so that various properties exhibited by the resulting nanoparticles can be tailored according to the desired applications. Effect of parameters like pH of the sol, additives used (like capping agent, surfactant), the effect of annealing temperature and calcination on the morphology and the optical properties of ZnO nanoparticles prepared via sol-gel technique is analyzed in this study. In this study, we tried to brief the experimental investigations done by various researchers to analyze the influence of processing parameters on ZnO nanoparticles. This study will provide a platform to understand and establish a correlation between the experimental conditions and properties of ZnO nanoparticles prepared through sol-gel route which will be helpful in meeting the desired needs in various application areas.