Nanomaterials-Based Sensors for Respiratory Viral Detection: A Review.

Contagious diseases are the principal cause of mortality, particularly respiratory viruses, a real menace for public health and economic development worldwide. Therefore, timely diagnosis and treatments are the only life-saving strategy to overcome any epidemic and particularly the ongoing prevailing pandemic COVID-19 caused by SARS-CoV-2. A rapid identification, point of care, portable, highly sensitive, stable, and inexpensive device is needed which is exceptionally satisfied by sensor technology. Consequently, the researchers have directed their attention to employing sensors targeting multiple analyses of pathogenic detections across the world. Nanostructured materials (nanoparticles, nanowires, nanobundles, etc.), owing to their unique characteristics such as large surface-to-volume ratio and nanoscale interactions, are widely employed to fabricate facile sensors to meet all the immediate emerging challenges and threats. This review is anticipated to foster researchers in developing advanced nanomaterials-based sensors for the increasing number of COVID-19 cases across the globe. The mechanism of respiratory viral detection by nanomaterials-based sensors has been reported. Moreover, the advantages, disadvantages, and their comparison with conventional sensors are summarized. Furthermore, we have highlighted the challenges and future potential of these sensors for achieving efficient and rapid detection.

Nanomaterials-based sensors for the detection of COVID-19: A review.

With the threat of increasing SARS-CoV-2 cases looming in front of us and no effective and safest vaccine available to curb this pandemic disease due to its sprouting variants, many countries have undergone a lockdown 2.0 or planning a lockdown 3.0. This has upstretched an unprecedented demand to develop rapid, sensitive, and highly selective diagnostic devices that can quickly detect coronavirus (COVID-19). Traditional techniques like polymerase chain reaction have proven to be time-inefficient, expensive, labor intensive, and impracticable in remote settings. This shifts the attention to alternative biosensing devices that can be successfully used to sense the COVID-19 infection and curb the spread of coronavirus cases. Among these, nanomaterial-based biosensors hold immense potential for rapid coronavirus detection because of their noninvasive and susceptible, as well as selective properties that have the potential to give real-time results at an economical cost. These diagnostic devices can be used for mass COVID-19 detection to understand the rapid progression of the infection and give better-suited therapies. This review provides an overview of existing and potential nanomaterial-based biosensors that can be used for rapid SARS-CoV-2 diagnostics. Novel biosensors employing different detection mechanisms are also highlighted in different sections of this review. Practical tools and techniques required to develop such biosensors to make them reliable and portable have also been discussed in the article. Finally, the review is concluded by presenting the current challenges and future perspectives of nanomaterial-based biosensors in SARS-CoV-2 diagnostics.

Fourth-generation glucose sensors composed of copper nanostructures for diabetes management: A critical review.

More than five decades have been invested in understanding glucose biosensors. Yet, this immensely versatile field has continued to gain attention from the scientific world to better understand and diagnose diabetes. However, such extensive work done to improve glucose sensing devices has still not yielded desirable results. Drawbacks like the necessity of the invasive finger-pricking step and the lack of optimization of diagnostic interventions still need to be considered to improve the testing process of diabetic patients. To upgrade the glucose-sensing devices and reduce the number of intermediary steps during glucose measurement, fourth-generation glucose sensors (FGGS) have been introduced. These sensors, made using robust electrocatalytic copper nanostructures, improve diagnostic efficiency and cost-effectiveness. This review aims to present the essential scientific progress in copper nanostructure-based FGGS in the past 10 years (2010 to present). After a short introduction, we presented the working principles of these sensors. We then highlighted the importance of copper nanostructures as advanced electrode materials to develop reliable real-time FGGS. Finally, we cover the advantages, shortcomings, and prospects for developing highly sensitive, stable, and specific FGGS.

Recent Advances in Non-Enzymatic Glucose Sensors Based on Metal and Metal Oxide Nanostructures for Diabetes Management- A Review.

There is an undeniable growing number of diabetes cases worldwide that have received widespread global attention by many pharmaceutical and clinical industries to develop better functioning glucose sensing devices. This has called for an unprecedented demand to develop highly efficient, stable, selective, and sensitive non-enzymatic glucose sensors (NEGS). Interestingly, many novel materials have shown the promising potential of directly detecting glucose in the blood and fluids. This review exclusively encompasses the electrochemical detection of glucose and its mechanism based on various metal-based materials such as cobalt (Co), nickel (Ni), zinc (Zn), copper (Cu), iron (Fe), manganese (Mn), titanium (Ti), iridium (Ir), and rhodium (Rh). Multiple aspects of these metals and their oxides were explored vis-à-vis their performance in glucose detection. The direct glucose oxidation via metallic redox centres is explained by the chemisorption model and the incipient hydrous oxide/adatom mediator (IHOAM) model. The glucose electrooxidation reactions on the electrode surface were elucidated by equations. Furthermore, it was explored that an effective detection of glucose depends on the aspect ratio, surface morphology, active sites, structures, and catalytic activity of nanomaterials, which plays an indispensable role in designing efficient NEGS. The challenges and possible solutions for advancing NEGS have been summarized.