Smart materials-integrated sensor technologies for COVID-19 diagnosis

Abstract

After the first case has appeared in China, the COVID-19 pandemic continues to pose an omnipresent threat to global health, affecting more than 70 million patients and leading to around 1.6 million deaths. To implement rapid and effective clinical management, early diagnosis is the mainstay. Today, real-time reverse transcriptase (RT)-PCR test is the major diagnostic practice as a gold standard method for accurate diagnosis of this disease. On the other side, serological assays are easy to be implemented for the disease screening. Considering the limitations of today's tests including lengthy assay time, cost, the need for skilled personnel, and specialized infrastructure, both strategies, however, have impediments to be applied to the resource-scarce settings. Therefore, there is an urgent need to democratize all these practices to be applicable across the globe, specifically to the locations comprising of very limited infrastructure. In this regard, sensor systems have been utilized in clinical diagnostics largely, holding great potential to have pivotal roles as an alternative or complementary options to these current tests, providing crucial fashions such as being suitable for point-of-care settings, cost-effective, and having short turnover time. In particular, the integration of smart materials into sensor technologies leverages their analytical performances, including sensitivity, linear dynamic range, and specificity. Herein, we comprehensively review major smart materials such as nanomaterials, photosensitive materials, electrically sensitive materials, their integration with sensor platforms, and applications as wearable tools within the scope of the COVID-19 diagnosis.

Keywords: COVID-19; Diagnostics; Point-of-care; Sensors; Smart materials.

Fig. 1

A graphene-based biosensor for the detection of Zika virus. a Illustration of the sensor elements. b The entire sensor platform comprising of a reader, digital control, PC running control, and software. c AFM view of graphene surface of the sensor, where the proteins were captured (scale bar is 1 μm). Copyright permission for reuse from the ref. [86]

Fig. 2

a Schematic representation of SIPs-GO composites on the gold surface to detect Zika virus by creating cavities on polymer to recognize virus. Reprinted with permission from the ref. [89] Copyright 2019 American Chemical Society. b (i) AuNP-G nanocomposites fabrication, (ii) PAb-AgNP-G bioconjugates fabrication. (iii) Illustration of the detection mechanism. Copyright permission for reuse from the ref. [32]. c Schematic representation of microfluidics-integrated electrochemical immunosensor, antibody immobilization on rGO via EDC/NHS linkers. Copyright permission for reuse from the ref. [70]

Fig. 3

Lateral flow assay format. Copyright permission for reuse from the ref. [169]

Fig. 4

a A portable fluorescence detection equipment. b Ready to use immunoassay chip. c Schematic illustration of the microfluidic fluorescence immunoassay biomarkers of SARS-CoV-2. Copyright permission for reuse from the ref. [34]