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Proceeding Paper

Review of the Recent Advances in Nano-Biosensors and Technologies for Healthcare Applications †

by
Maha Wajeeh Aqra
1 and
Amall Ahmed Ramanathan
2,*
1
National Center for Research and Development, Amman 11941, Jordan
2
Department of Physics, University of Jordan, Amman 11942, Jordan
*
Author to whom correspondence should be addressed.
Presented at the 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry, 1–15 July 2021; Available online: https://csac2021.sciforum.net/.
Chem. Proc. 2021, 5(1), 76; https://doi.org/10.3390/CSAC2021-10473
Published: 30 June 2021

Abstract

:
The growing human population and the discovery of new diseases and emerging pandemics have increased the need for healthcare treatments and medications with innovative designs. The emergence of nanotechnology provides a platform for novel diagnostic and therapeutic in vivo non-invasive detection and treatment of ailments. It is now the era of the Internet of things (IoT), and data acquisition and interpretation from various parts of the human body in real time is possible with interconnected sensors and information transfer devices. Miniaturization, low power consumption and price with compatibility to existing network circuits are essential requirements in the IoT. Biosensors made of nanostructured materials are the ideal choice due to the unique structural, chemical and electronic properties of these materials with the advantage of a large surface-to-volume ratio, which makes them very successful for use as sensors for the detection of diseases, drug carriers, filters, fillers and reaction catalysts in healthcare applications. In this paper, we reviewed the recent progress made in the research and applications of biosensors in health and preventive medicine. The focus of the paper is biosensors made of nanostructured layered materials such as graphene and its structural analogs molybdenum disulphide (MoS2) and boron nitride (BN). We discussed and highlighted the present capabilities of the different nano-forms of these materials in the detection and analysis of diseases. Their efficiencies in terms of the detection limit, the sensitivity and the adaptability to different environments were be discussed. In addition, the challenges and future perspectives of using nano-biosensors to develop efficient diagnostic, therapeutic and cost-effective monitoring devices with smart technologies were explored.

1. Introduction

The detection of biological molecules, ions or species of interest (analyte) through the measurement and analysis of signals proportional to the concentration of the analyte is the basic function of a biosensor. The biological/chemical information needs to be transformed into readable outputs through the transducer. Biosensors used in the detection and prevention of diseases need to be non-invasive, highly selective, flexible and sensitive [1,2,3]. In addition in order to acquire and interpret signals from different parts of the body with interconnected or multifunctional sensors, the sensor design needs to be innovative and compatible with smart technologies that can transfer data with a high speed and accuracy [4,5]. Moreover, several constraints such as biocompatibility, reliability, stability, comfort, convenience, miniaturization and costs need to be considered [6]. The last decade has seen tremendous research on Two dimensional materials such as grapheme (Gr), graphene oxide (GrO) and molybdenum disulphide (MoS2) in different nano-forms for sensing applications in the healthcare, environment and other sectors [7,8,9,10,11,12,13,14].
Gr as the first 2D material discovered with its one-atomic-layer honeycomb structure has remarkable electronic, mechanical and optical properties and has seen a multitude of applications [15,16,17]. Gr analogs MoS2 and boron nitride (BN) also have a honeycomb lattice and a layered structure that allow for the easy fabrication of 2D and other nanostructures due to the weak inter-layer van der Waal interactions.
A lot of research has been going on in the area of Gr and beyond Gr nanomaterials (NMs) during the past decade, and it is necessary to put into perspective and highlight the progress of Gr, MoS2 and BN nanostructures in biosensing for the healthcare sector. This is a rapidly changing and highly researched field with new discoveries and innovation and requires the frequent updates of progresses and challenges. This motivated us to present a focused review with the literature survey of the recent developments (last five years) on Gr and its structural analogs MoS2 and BN nanostructures in the detection and analysis of diseases in terms of efficiency, detection limits, sensitivity and adaptability to different environments. We discussed and highlighted the present capabilities of the different nano-forms of these materials. In addition, the challenges and future perspectives of using nano-biosensors to develop efficient diagnostic, therapeutic and cost-effective monitoring devices with smart technologies for healthcare and preventive medicine were explored. The article was arranged under the main headings: Introduction, Nano-Biosensors, Smart Technologies and Challenges or Opportunities.

2. Nano-Biosensors

2.1. Biosensor Types

Biosensors are two component devices consisting of a receptor and a transducer. The receptor is a biological recognition element which could be an enzyme, micro-organism, tissue, antibody or nucleic acid. The transducer converts the physiochemical change due to the interaction of the analyte with the receptor into an analytical output signal, which is coupled to an appropriate data-processing system. A schematic diagram of the process is shown in Figure 1.
Electrical, optical, electrochemical, micromechanical, calorimetric, magnetic, thermoelectric and piezoelectric transducers can be employed in biosensors, and the choice depends on the sensing environment and needs. Materials have been researched widely by the materials science community for use to fabricate the best-suited biosensor.

2.2. Nanostructured Materials for Biosensing

Gr and its analogs such as MoS2 and BN NMs have been the best materials for biosensing so far. The unique layered and honeycomb structure of these materials allows for the easy synthesis of monolayers (MLs), bilayers (BLs), nano-flakes, nanotubes and hetrostructures with a wide range of bandgaps and a diverse variety of optoelectronic properties. In addition, due to the weak inter-layer van der Waals forces, one can intercalate with atoms of different species and functionalize them easily to obtain the desired properties at will; moreover, NMs have the advantage of a large surface-to-volume ratio, which is important in the efficient immobilization of receptors on the surface of the NMs for good sensor performance [18]. All these factors make them prime candidates for use as biosensors in healthcare applications. In Figure 2, we give a graphical representation of NMs for biosensing that best describes the scope of this review.

2.2.1. Gr Nano-Biosensors

A Gr layer has a hexagonal symmetry with a honeycomb structure, and in-plane C atoms are bonded by strong covalent sp2 bonds with the nearest neighbours and an out-of-plane delocalised π bond, as shown in Figure 3a. It is the delocalised π electrons that are responsible for the extremely high room temperature mobility of 15,000–200,000 cm V−1 s−1 [19]. Moreover, Gr has an excellent mechanical strength on account of the strong covalent bonding and is optically transparent and highly flexible [20,21].
The high electrical and thermal conductivity, mechanical strength, flexibility, optical transparency and ultrathin feature (one-atom thickness) of Gr are ideal characteristics for sensing applications. The sensor selectivity plays a very important role in its design, and this is very closely related to NM sensors characteristics, so selectivity can only be improved by fine-tuning the NM properties. The NM interacts with target bio-molecules by either a physisorption or chemisorption process. Physisorption, although fast, is a non-covalent bonding reaction and is not preferred as the bio-molecules do not bind completely, thereby affecting the sensitivity. Chemisorption can be brought about by the presence of defects, vacancies, doping and chemical functionalization, all of which increase the reactivity and enhance the selectivity to the target species. Figure 3b depicts the band structure changes of Gr by changing the geometry, thickness and doping mechanisms. The GrO 2D material produced by the oxidation of Gr is semiconducting and has a finite gap as compared to Gr. It has the advantage of being stable in water and other solvents and can be easily functionalized. Reduced graphene oxide (rGrO) is obtained by the removal of the oxygen functional groups and has the advantages of Gr and GrO, which include being conducting and having chemically active defect sites. The bandgap engineering and chemical functionalizing of Gr through the use of Gr derivatives such as GrO and rGrO and composites have proved to work well as sensors (including wearable sensors and implantable devices) for human health monitoring, as reported in Table 1. The body temperature is an important indicator of abnormal body functions, and its measurement is one of the first lines of action in suspicious cases. We have seen ample evidence of this aspect during the current COVID-19 pandemic. It is also linked to our biological clock and can be used to monitor an individual’s sleep patterns, which is important in determining the overall health and mental fitness. Table 1 gives a summary of various Gr-based sensors along with body functions tested, the mechanisms of sensing, the sensitivities and the ranges when available and the references.

2.2.2. MoS2 and BN Nano-Biosensors

Similar to Gr, 2D MoS2 and hBN materials with a honeycomb structure have all the advantages of Gr for sensing mentioned in the previous section. These van der Waal structures exhibit unique optical and electronic properties that make them very appealing for biosensing [38]. Moreover, they have the added advantage of bandgaps unlike Gr which has a zero bandgap; this improves the sensitivity of sensor devices made of these materials, especially in sensors.
MoS2 is a prototype of a class of materials termed transition metal dichalcogenides (TMDs) and has markedly anisotropic properties, as seen from its electrical resistivity among other properties. The resistivity in a direction perpendicular to the planes is about 1000 times greater than in the parallel direction. Unlike Gr which is one-atom thick, an ML of MoS2 has three atomic layers sulfur–molybdenum–sulfur. The physical properties of MoS2 change markedly at the nanoscale. The bulk material has an indirect bandgap of ~1.2 eV, while the ML material has a direct and broader bandgap of ~1.8 eV [39]. Hence, it shows thickness-dependent bandgap properties, allowing for the production of tuneable optoelectronic devices with diversified spectral operation.
The electronic and optical properties of Gr and MoS2 are complemented by those of hBN, which is an insulator with a large indirect bandgap value of ~5.95 eV [40] in the bulk form and in the ML limit crossover to a direct-bandgap material with a gap of 6.1 eV [41]. The sensing mechanisms of these materials could be electrical-based sensing, through charge transfer which alters the resistance or optical sensing where due to the charge transfer the surface plasmon resonance (SPR) gets modified and can be detected; or biomolecules are detected by their spectral fingerprints.
The hybrid structures of Gr, MoS2 and BN have also been highly researched to increase the scope of the biosensing capabilities of these NMs. This is the topic of the next section.

2.2.3. Hetrostructures

2D Gr, GrO, rGrO, MoS2 and hBN can all be used like Lego blocks to build interesting hetrostructures by mixing and matching for the increased selectivity and sensitivity of the nano-biosensensors. This process of electrostatic doping by the stacking of these van der Waal structures can be used to obtain unique and tuneable electronic properties. Figure 4 shows a graphical representation of a hetrostructure that can be made with the basic single layers of Gr, hBN and MoS2.
Hetrostructures, although highly desirable, require careful considerations of the lattice mismatch, the misalignment of layers and the introduction of unforeseen defects during the deposition and the epitaxial growth. Hexagonal BN is an insulating analogue of graphite with a small lattice mismatch (~1.8%), so it is an ideal substrate for graphene and a key building block in many van der Waals hetrostructures. Gr–hBN-integrated devices have been recently used for DNA sequencing by current modulation [43] and distinguishing nucleotides in DNA [44]. An SPR-based biosensor consisting of Gr/hBN hybrid structures for the detection of biomolecules was reported in 2019 [45]. The SPR technique is also used in a biosensor consisting of a MoS2/Gr hybrid structure with Au, as a substrate, used to detect biomolecules using SPR [46]. Again in 2017, an angle-based SPR biosensor made of a MoS2/Al film/MoS2/Gr heterostructure was used to detect biomolecules [47]. In Table 2, we summarized various nano-biosensors made of MoS2, hBN, Gr, Gr derivatives and hetrostructures of these NMs in the recent years. Table 2 gives the NMs used, the species detected, the sensing mechanisms, the sensitivities, the detection ranges, publications and the years of publications.

3. Smart Technologies

The early-stage detection and prevention of chronic and fatal diseases requires continuous monitoring. Data acquisition and interpretation from various parts of the human body in real time is possible with interconnected sensors and information transfer devices in today’s era of the Internet of things (IoT). The unprecedented advancements in electronics and sensor technologies coupled with Big Data and AI offer exciting opportunities in the field of smart and sustainable healthcare. The stage is now set to shift from old medical procedures and protocols and adapt smart integrated medical testing with nano-devices for diagnosis and therapeutics [61,62]. We need to discard costly and bulky equipment and old fashioned laboratories and embrace wearable and miniaturised sensors that use interstitial fluid (ISF), instead of blood, to detect minute changes in biomarkers with sweat, tears and breath analysis that contain a wealth of information about body malfunctions [1,2,3]. Wireless, powerless nano-devices made of biocompatible materials that can be worn on the skin (patches, tattoos, watches, etc.), in textiles, the eye, mouth, teeth (miniaturised implants) and other innovative means using non-invasive probes are the need of the day. Electronic nose, tongues and skin are the new innovative smart technologies that are the future of healthcare monitoring and preventive medicine [63,64,65,66,67].

4. Challenges or Opportunities

A challenge, limitation or drawback is an opportunity for improvement, change in strategy or chance for innovation. Although the nano-biosensors research shows that considerable improvements in healthcare monitoring can be made, commercial products are few and from small companies [68]. Before large-scale and widespread manufacturing of 2D and other nanostructured devices for health-related applications can be realized, uniformity and controlled synthesis is necessary to rule out the device-to-device variability. This is crucial for large-scale commercialization, and the challenge has been met as indicated by the recent research and publications addressing this issue [69,70].
In addition, in vivo and point-of-care diagnostics require biocompatibility and toxicity issues to be addressed. The precise control of NMs properties and biocompatibility is required, especially in the local biological environment, where the devices are to be used with a thorough understanding of complex physiochemical interactions. The recent years have seen tremendous work in this direction with good progresses [71,72,73].

Author Contributions

A.A.R. conceived, designed and wrote the project manuscript; M.W.A. contributed towards literature survey, curation of data and writing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors have no conflict of interests to declare.

References

  1. Tricoli, A.; Nasiri, N.; De, S. Wearable and Miniaturized Sensor Technologies for Personalized and Preventive Medicine. Adv. Funct. Mater. 2017, 27, 1605271. [Google Scholar] [CrossRef]
  2. Wang, X.; Liu, Z.; Zhang, T. Flexible sensing electronic for wearable/attachable health monitoring. Adv. Sci. 2017, 13, 1602790. [Google Scholar] [CrossRef]
  3. Yao, S.; Swetha, P.; Zhu, Y. Nanomaterial-enabled wearable sensors for healthcare. Adv. Healthc. Mater. 2017, 7, 1700889. [Google Scholar] [CrossRef] [PubMed]
  4. Li, X.; Yang, J. First-principles design of spintronics materials. Natl. Sci. Rev. 2016, 3, 365–381. [Google Scholar] [CrossRef]
  5. Ramanathan, A.A.; Khalifeh, J.M. Electronic, magnetic and optical properties of XScO3 (X = Mo, W) perovskites. PeerJ Mater. Sci. 2021, 3, e15. [Google Scholar] [CrossRef]
  6. Pantelopoulos, A.; Bourbakis, N.G. Prognosis—A wearable health monitoring system for people at risk: Methodology and modeling. IEEE Trans. Inf. Technol. Biomed. 2010, 14, 613–621. [Google Scholar] [CrossRef] [PubMed]
  7. Lu, C.; Huang, P.J.J.; Liu, B.; Ying, Y.; Liu, J. Comparison of Graphene Oxide and Reduced Graphene Oxide for DNA Adsorption and Sensing. Langmuir 2016, 32, 10776–10783. [Google Scholar] [CrossRef] [PubMed]
  8. Hu, K.; Tsukruk, V.V. Tuning the Electronic Properties of Robust Bio-Bond Graphene Papers by Spontaneous Electrochemical Reduction: From Insulators to Flexible Semi-Metals. Chem. Mater. 2015, 27, 6717–6729. [Google Scholar] [CrossRef]
  9. Chong, Y.; Ge, C.; Yang, Z.; Garate, J.A.; Gu, Z.; Weber, J.K.; Liu, J.; Zhou, R. Reduced Cytotoxicity of Graphene Nanosheets Mediated by Blood-Protein Coating. ACS Nano 2015, 9, 5713–5724. [Google Scholar] [CrossRef] [PubMed]
  10. Ramanathan, A.A. Defect Functionalization of MoS2 nanostructures as toxic gas sensors: A review. IOP Conf. Ser. Mater. Sci. Eng. 2018, 305, 012001. [Google Scholar] [CrossRef] [Green Version]
  11. Wang, Y.H.; Huang, K.J.; Wu, X. Recent advances in transition-metal dichalcogenides based electrochemical biosensors: A review. Biosens. Bioelectron. 2017, 97, 305. [Google Scholar] [CrossRef] [PubMed]
  12. Chen, Y.; Tan, C.; Zhang, H.; Wang, L. Two-Dimensional Graphene Analogues for Biomedical Applications. Chem. Soc. Rev. 2015, 44, 2681–2701. [Google Scholar] [CrossRef] [PubMed]
  13. Ji, D.K.; Ménard-Moyon, C.; Bianco, A. Physically-triggered nanosystems based on two-dimensional materials for cancer theranostics. Adv. Drug Deliv. Rev. 2019, 138, 211–232. [Google Scholar] [CrossRef] [PubMed]
  14. Ramanathan, A.A.; Aqra, M.W.; Al-Rawajfeh, A.E. Recent advances in 2D-nanopores for desalination. Environ. Chem. Lett. 2018, 16, 1217–1231. [Google Scholar] [CrossRef]
  15. Yang, T.; Lin, H.; Loh, K.P.; Jia, B. Fundamental Transport Mechanisms and Advancements of Graphene Oxide Membranes for Molecular Separation. Chem. Mater. 2019, 31, 1829–1846. [Google Scholar] [CrossRef]
  16. Li, M.; Liu, C.; Zhao, H.; An, H.; Cao, H.; Zhang, Y.; Fan, Z. Tuning Sulfur Doping in Graphene for Highly Sensitive Dopamine Biosensors. Carbon 2015, 86, 197–206. [Google Scholar] [CrossRef]
  17. Aqra, M.W.; Ramanathan, A.A. Graphene and related 2D materials for desalination: A review of recent patents. Jordan J. Phys. 2020, 13, 233–242. [Google Scholar]
  18. Szunerits, S.; Boukherroub, R. Graphene-based biosensors. Interface Focus 2018, 8, 20160132. [Google Scholar] [CrossRef] [PubMed]
  19. Lemme, M.C. Current Status of Graphene Transistors. Solid State Phenom. 2010, 156–158, 499–509. [Google Scholar] [CrossRef]
  20. Xiang, L.; Ma, S.Y.; Wang, F.; Zhang, K. Nano indentation models and young’s modulus of few-layer graphene: A molecular dynamics simulation study. J. Phys. D Appl. Phys. 2015, 48, 395305. [Google Scholar] [CrossRef]
  21. Yang, H.; Xue, T.; Li, F.; Liu, W.; Song, Y. Graphene: Diversified flexible 2D material for wearable vital signs monitoring. Adv. Mater. Technol. 2018, 4, 1800574. [Google Scholar] [CrossRef]
  22. Schwierz, F. Graphene Transistors. Nat. Nanotechnol. 2010, 5, 487–496. [Google Scholar] [CrossRef] [PubMed]
  23. Trung, T.Q.; Le, H.S.; Dang, T.M.L.; Ju, S.; Park, S.Y.; Lee, N.-E. Freestanding, fiber-based, wearable temperature sensor with tunable thermal index for healthcare monitoring. Adv. Healthc. Mater. 2018, 7, 1800074. [Google Scholar] [CrossRef]
  24. Wang, Z.; Gao, W.; Zhang, Q.; Zheng, K.; Xu, J.; Xu, W.; Shang, E.; Jiang, J.; Zhang, J.; Liu, Y. 3D printed graphene/polydimethylsiloxane composites for stretchable and strain insensitive temperature sensors. ACS Appl. Mater. Interfaces 2018, 11, 1344–1352. [Google Scholar] [CrossRef] [PubMed]
  25. Kou, H.; Zhang, L.; Tan, Q.; Liu, G.; Lv, W.; Lu, F.; Dong, H.; Xiong, J. Wireless flexible pressure sensor based on micro-patterned Graphene/PDMS composite. Sens. Actuators A Phys. 2018, 277, 150–156. [Google Scholar] [CrossRef]
  26. Yang, Z.; Pang, Y.; Han, X.; Yang, Y.; Ling, J.; Jian, M.; Zhang, Y.; Yang, Y.; Ren, T.L. Graphene textile strain sensor with negative resistance variation for human motion detection. ACS Nano 2018, 12, 9134–9141. [Google Scholar] [CrossRef]
  27. Karim, N.; Afroj, S.; Malandraki, A.; Butterworth, S.; Beach, C.; Rigout, M.; Novoselov, K.S.; Casson, A.J.; Yeates, S.G. All inkjet-printed graphene-based conductive patterns for wearable e-textile applications. J. Mater. Chem. C 2017, 5, 11640–11648. [Google Scholar] [CrossRef] [Green Version]
  28. Yang, T.; Jiang, X.; Zhong, Y.; Zhao, X.; Lin, S.; Li, J.; Li, X.; Xu, J.; Li, Z.; Zhu, H. A wearable and highly sensitive graphene strain sensor for precise home-based pulse wave monitoring. ACS Sens. 2017, 2, 967–974. [Google Scholar] [CrossRef] [PubMed]
  29. Pang, Y.; Zhang, K.; Yang, Z.; Jiang, S.; Ju, Z.; Li, Y.; Wang, X.; Wang, D.; Jian, M.; Zhang, Y.; et al. Epidermis microstructure inspired graphene pressure sensor with random distributed spinosum for high sensitivity and large linearity. ACS Nano 2018, 12, 2346–2354. [Google Scholar] [CrossRef] [PubMed]
  30. Boland, C.S.; Khan, U.; Backes, C.; O’Neill, A.; McCauley, J.; Duane, S.; Shanker, R.; Liu, Y.; Jurewicz, I.; Dalton, A.B.; et al. Sensitive, high-strain, high-rate bodily motion sensors based on graphene–rubber composites. ACS Nano 2014, 8, 8819–8830. [Google Scholar] [CrossRef] [PubMed]
  31. Xu, M.; Qi, J.; Li, F.; Zhang, Y. Highly stretchable strain sensors with reduced graphene oxide sensing liquids for wearable electronics. Nanoscale 2018, 10, 5264–5271. [Google Scholar] [CrossRef]
  32. Pang, Y.; Tian, H.; Tao, L.; Li, Y.; Wang, X.; Deng, N.; Yang, Y.; Ren, T.L. Flexible, highly sensitive, and wearable pressure and strain sensors with graphene porous network structure. ACS Appl. Mater. Interfaces 2016, 8, 26458–26462. [Google Scholar] [CrossRef] [PubMed]
  33. Pu, Z.; Tu, J.; Han, R.; Zhang, X.; Wu, J.; Fang, C.; Wu, H.; Zhang, X.; Yu, H.; Li, D. A flexible enzyme-electrode sensor with cylindrical working electrode modified with a 3D nanostructure for implantable continuous glucose monitoring. Lab Chip 2018, 18, 3570–3577. [Google Scholar] [CrossRef]
  34. Toi, P.T.; Trung, T.Q.; Dang, T.M.L.; Bae, C.W.; Lee, N.E. Highly electrocatalytic, durable, and stretchable nano hybrid fiber for on body sweat glucose detection. ACS Appl. Mater. Interfaces 2019, 11, 10707–10717. [Google Scholar] [CrossRef]
  35. Ameri, S.K.; Singh, P.K.; D’Angelo, R.; Stoppel, W.; Black, L.; Sonkusale, S.R. Three dimensional graphene scaffold for cardiac tissue engineering and in-situ electrical recording. In Proceedings of the 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 16–20 August 2016; pp. 4201–4203. [Google Scholar] [CrossRef]
  36. Yun, Y.J.; Ju, J.; Lee, J.H.; Moon, S.-H.; Park, S.-J.; Kim, Y.H.; Hong, W.G.; Ha, D.H.; Jang, H.; Lee, G.H.; et al. Highly elastic graphene-based electronics toward electronic skin. Adv. Funct. Mater. 2017, 27, 1701510–1701513. [Google Scholar] [CrossRef]
  37. Sun, B.; McCay, R.N.; Goswami, S.; Xu, Y.; Zhang, C.; Ling, Y.; Lin, J.; Yan, Z. Gas-permeable, multifunctional on-skin electronics based on laser-induced porous graphene and sugar-templated elastomer sponges. Adv. Mater. 2018, 30, 1804327–1804328. [Google Scholar] [CrossRef] [PubMed]
  38. Gupta, A.; Sakthivel, T.; Seal, S. Recent development in 2D materials beyond graphene. Prog. Mater. Sci. 2015, 73, 44–126. [Google Scholar] [CrossRef]
  39. Kadantsev, E.S.; Hawrylak, P. Electronic structure of a single MoS2 monolayer. Solid State Commun. 2012, 152, 909–913. [Google Scholar] [CrossRef]
  40. Cassabois, G.; Valvin, P.; Gil, B. Hexagonal boron nitride is an indirect bandgap semiconductor. Nat. Photon 2016, 10, 262–266. [Google Scholar] [CrossRef] [Green Version]
  41. Elias, C.; Valvin, P.; Pelini, T.; Summerfield, A.; Mellor, C.J.; Cheng, T.S.; Eaves, L.; Foxon, C.T.; Beton, P.H.; Novikov, S.V.; et al. Direct band-gap crossover in epitaxial monolayer boron nitride. Nat. Commun. 2019, 10, 2639. [Google Scholar] [CrossRef] [Green Version]
  42. Geim, A.K.; Grigorieva, I.V. Van der Waals heterostructures. Nature 2013, 499, 419–425. [Google Scholar] [CrossRef] [PubMed]
  43. Panahi, S.F.K.S.; Namiranian, A.; Jamaati, M. Graphene-hBN hybrid nanogap for boosting DNA nucleobases recognition sensitivity. ChemNanoMat 2019, 5, 488–498. [Google Scholar] [CrossRef]
  44. de Souza, F.A.; Amorim, R.G.; Scopel, W.L.; Scheicher, R.H. Electrical detection of nucleotides via nanopores in a hybrid graphene/h-BN sheet. Nanoscale 2017, 9, 2207–2212. [Google Scholar] [CrossRef] [PubMed]
  45. Jiang, H.; Choudhury, S.; Kudyshev, Z.A.; Wang, D.; Prokopeva, L.J.; Xiao, P.; Jiang, Y.; Kildishev, A.V. Enhancing sensitivity to ambient refractive index with tunable few-layer graphene/hBN nanoribbons. Photonics Res. 2019, 7, 815–822. [Google Scholar] [CrossRef]
  46. Zeng, S.; Hu, S.; Xia, J.; Anderson, T.; Dinh, X.-Q.; Meng, X.-M.; Coquet, P.; Yong, K.-T. Graphene-MoS2 hybrid nanostructures enhanced surface plasmon resonance biosensors. Sens. Actuators B 2015, 207, 801–810. [Google Scholar] [CrossRef]
  47. Wu, L.; Jia, Y.; Jiang, L.; Guo, J.; Dai, X.; Xiang, Y.; Fan, D. Sensitivity improved SPR biosensor based on the MoS2/graphene–aluminum hybrid structure. J. Lightwave Technol. 2016, 35, 82–87. [Google Scholar] [CrossRef]
  48. Huang, Y.; Shi, Y.; Yang, H.Y.; Ai, Y. A novel single-layered MoS2 nanosheet based microfluidic biosensor for ultrasensitive detection of DNA. Nanoscale 2015, 7, 2245–2249. [Google Scholar] [CrossRef] [PubMed]
  49. Huang, K.-J.; Wang, L.; Li, J.; Liu, Y.-M. Electrochemical sensing based on layered MoS2-graphene composites. Sens. Actuators B 2013, 178, 671–677. [Google Scholar] [CrossRef]
  50. Loan, P.T.K.; Zhang, W.; Lin, C.-T.; Wei, K.-H.; Li, L.-J.; Chen, C.-H. Graphene/MoS2 heterostructures for ultrasensitive detection of DNA hybridization. Adv. Mater. 2014, 26, 4838–4844. [Google Scholar] [CrossRef]
  51. Li, Y.; Yan, H.; Farmer, D.B.; Meng, X.; Zhu, W.; Osgood, R.M.; Heinz, T.F.; Avouris, P. Graphene plasmon enhanced vibrational sensing of surface-adsorbed layers. Nano Lett. 2014, 14, 1573–1577. [Google Scholar] [CrossRef]
  52. Zeng, S.; Sreekanth, K.V.; Shang, J.; Yu, T.; Chen, C.K.; Yin, F.; Baillargeat, D.; Coquet, P.; Ho, H.P.; Kabashin, A.V.; et al. Graphene-gold metasurface architectures for ultrasensitive plasmonic biosensing. Adv. Mater. 2015, 27, 6163–6169. [Google Scholar] [CrossRef]
  53. Zhang, M.; Liao, C.; Mak, C.H.; You, P.; Mak, C.L.; Yan, F. Highly sensitive glucose sensors based on enzyme-modified whole-graphene solution-gated transistors. Sci. Rep. 2015, 5, 8311. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Zhou, L.; Mao, H.; Wu, C.; Tang, L.; Wu, Z.; Sun, H.; Zhang, H.; Zhou, H.; Jia, C.; Jin, Q.; et al. Label-free graphene biosensor targeting cancer molecules based on non-covalent modification Biosens. Bioelectron. 2017, 87, 701–707. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Chen, S.; Autore, M.; Li, J.; Li, P.; Alonso-Gonzalez, P.; Yang, Z.; Martin-Moreno, L.; Hillenbrand, R.; Nikitin, A.Y. Acoustic graphene plasmon nanoresonators for field-enhanced infrared molecular spectroscopy. ACS Photonics 2017, 4, 3089–3097. [Google Scholar] [CrossRef] [Green Version]
  56. Xu, S.; Zhan, J.; Man, B.; Jiang, S.; Yue, W.; Gao, S.; Guo, C.; Liu, H.; Li, Z.; Wang, J.; et al. Real-time reliable determination of binding kinetics of DNA hybridization using a multi-channel graphene biosensor. Nat. Commun. 2017, 8, 14902. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  57. Seber, G.; Muñoz, J.; Sandoval, S.; Rovira, C.; Tobias, G.; Mas-Torrent, M.; Crivillers, N. Synergistic exploitation of the superoxide scavenger properties of reduced graphene oxide and a trityl organic radical for the impedimetric sensing of xanthine. Adv. Mater. Interface 2018, 5, 1701072. [Google Scholar] [CrossRef] [Green Version]
  58. Chiu, N.-F.; Kuo, C.-T.; Lin, T.-L.; Chang, C.-C.; Chen, C.-Y. Ultra-high sensitivity of the non-immunological affinity of graphene oxide-peptide-based surface plasmon resonance biosensors to detect human chorionic gonadotropin. Biosens. Bioelectron. 2017, 94, 351–357. [Google Scholar] [CrossRef] [PubMed]
  59. Nurunnabi, M.; Nafiujjaman, M.; Lee, S.-J.; Park, I.-K.; Huh, K.M.; Lee, Y.-k. Preparation of ultra-thin hexagonal boron nitride nanoplates for cancer cell imaging and neurotransmitter sensing. Chem. Commun. 2016, 52, 6146–6149. [Google Scholar] [CrossRef] [PubMed]
  60. Autore, M.; Li, P.; Dolado, I.; Alfaro-Mozaz, F.J.; Esteban, R.; Atxabal, A.; Casanova, F.; Hueso, L.E.; Alonso-González, P.; Aizpurua, J.; et al. Boron nitride nanoresonators for phonon-enhanced molecular vibrational spectroscopy at the strong coupling limit. Light Sci. Appl. 2018, 7, 17172. [Google Scholar] [CrossRef] [PubMed]
  61. Kostarelos, K.; Vincent, M.; Hebert, C.; Garrido, J.A. Graphene in the Design and Engineering of Next-Generation Neural Interfaces. Adv. Mater. 2017, 29, 1700909. [Google Scholar] [CrossRef] [PubMed]
  62. Sazonov, E. Wearable Sensors: Fundamentals, Implementation and Applications; Technology & Engineering; Academic Press: Cambridge, MA, USA, 2020; 660p. [Google Scholar]
  63. Belizário, J.E.; Faintuch, J.; Malpartida, M.G. Breath Biopsy and Discovery of Exclusive Volatile Organic Compounds for Diagnosis of Infectious Diseases. Front. Cell. Infect. Microbiol. 2021, 10, 564194. [Google Scholar] [CrossRef]
  64. Scarlata, S.; Finamore, P.; Meszaros, M.; Dragonieri, S.; Bikov, A. The Role of Electronic Noses in Phenotyping Patients with Chronic Obstructive Pulmonary Disease. Biosensors 2020, 10, 171. [Google Scholar] [CrossRef] [PubMed]
  65. Al Ramahi, R.; Zaid, A.N.; Abu-Khalaf, N. Evaluating the potential use of electronic tongue in early identification and diagnosis of bacterial infections. Infect. Drug Resist. 2019, 12, 2445–2451. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  66. Yang, J.C.; Mun, J.; Kwon, S.Y.; Park, S.; Bao, Z.; Park, S. Electronic Skin: Recent Progress and Future Prospects for Skin-Attachable Devices for Health Monitoring, Robotics, and Prosthetics. Adv. Mater. 2019, 31, 1904765. [Google Scholar] [CrossRef] [Green Version]
  67. Behera, B.; Joshi, R.; Anil Vishnu, G.K.; Bhalerao, S.; Pandya, H.J. Electronic nose: A non-invasive technology for breath analysis of diabetes and lung cancer patients. J. Breath Res. 2019, 13, 024001–024023. [Google Scholar] [CrossRef] [PubMed]
  68. Briggs, N.; Subramanian, S.; Lin, Z.; Li, X.; Zhang, X.; Zhang, K.; Xiao, K.; Geohegan, D.; Wallace, R.; Chen, L.Q.; et al. A Roadmap for Electronic Grade 2Dimensional Materials. 2D Mater. 2019, 6, 022001. [Google Scholar] [CrossRef]
  69. Magda, G.Z.; Peto, J.; Dobrik, G.; Hwang, C.; Biro, L.P.; Tapaszto, L. Exfoliation of Large-Area Transition Metal Chalcogenide Single Layers. Sci. Rep. 2015, 5, 14714. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  70. Ramanathan, A.A. and Aqra, M.W. An Overview of the Green Road to the Synthesis of Nanoparticles. J. Mater. Sci. Res. Rev. 2019, 2, 1–11. [Google Scholar]
  71. Wang, S.; Li, K.; Chen, Y.; Chen, H.; Ma, M.; Feng, J.; Zhao, Q.; Shi, J. Biocompatible PEGylated MoS2 nanosheets: Controllable bottom-up synthesis and highly efficient photothermal regression of tumor. Biomaterials 2015, 39, 206–217. [Google Scholar] [CrossRef] [PubMed]
  72. Zielińska, A.; Costa, B.; Ferreira, M.V.; Miguéis, D.; Louros, J.; Durazzo, A.; Lucarini, M.; Eder, P.; Chaud, M.V.; Morsink, M.; et al. Nanotoxicology and Nanosafety: Safety-By-Design and Testing at a Glance. Int. J. Environ. Res. Public Health 2020, 17, 4657. [Google Scholar] [CrossRef]
  73. Ramanathan, A.A. Toxicity of nanoparticles_challenges and opportunities. Appl. Microsc. 2019, 49, 2. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1. Schematics of a biosensor unit.
Figure 1. Schematics of a biosensor unit.
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Figure 2. Graphical representation of nanostructured materials for biosensing.
Figure 2. Graphical representation of nanostructured materials for biosensing.
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Figure 3. (a) Graphene geometry (i), bonding (ii) and the related band diagram (iii) [19]. (b) Schematic diagram showing the Dirac Fermi cone (i), the modification of the band by chemical or geometry restrictive doping (ii), the modification of the band by bilayer graphene (iii) and, finally, the modification of the bands in doped bilayer graphene (iv) [22].
Figure 3. (a) Graphene geometry (i), bonding (ii) and the related band diagram (iii) [19]. (b) Schematic diagram showing the Dirac Fermi cone (i), the modification of the band by chemical or geometry restrictive doping (ii), the modification of the band by bilayer graphene (iii) and, finally, the modification of the bands in doped bilayer graphene (iv) [22].
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Figure 4. Graphical representation of possible hetrostructures that can be made by stacking multiple van der Waal layered structures in different orderings. Adapted from [42].
Figure 4. Graphical representation of possible hetrostructures that can be made by stacking multiple van der Waal layered structures in different orderings. Adapted from [42].
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Table 1. Summary of the details of graphene (Gr)-based sensors in health monitoring.
Table 1. Summary of the details of graphene (Gr)-based sensors in health monitoring.
NMBody FunctionSensing MechanismSensitivityRangeReference
Freestanding single reduced graphene oxide (rGrO);
3D Gr–PDS composite
Body temperatureResistance-based--
-
[23]
[24]
Gr/PDMS;
Gr
Body movementsPiezo-capacitive strain; textile strain0.24 kPa−1
0.0078 kPa−1
0–10 kPa
10–100 kPa
[25]
[26]
Inkjet-printed GrHeart rateElectronic--[27]
Wrist pulseStrain; pressure--[28]
[29]
Gr–rubber composite;
rGrO
Body movements + respiration rateStrain-
-
-
-
[30]
[31]
Gr porous networkBlood pressurePressure + strain--[32]
3D nano-implant;
Nano-hybrid fiber
Blood glucose
Sweat glucose
Electrode
Electrocatalytic
-
-
-
-
[33]
[34]
3D Gr scaffoldECGImplant--[35]
Gr;
Porous Gr
EMGElectronic skin-
-
-
-
[36]
[37]
3D Gr scaffold;
Gr
EEGImplant
Electronic skin
-
-
-
-
[35]
[36]
Table 2. Summary of nano-biosensors with references and the years of research.
Table 2. Summary of nano-biosensors with references and the years of research.
Nanomaterial (NM)AnalyteSensing MechanismDetection LimitRangeReference + Year
MoS2DNAFluorescence quenching500 pM0–50 nM[48]; 2014
MoS2/GrAcetaminophenElectrochemical20 nM0.1–100 μM[49]; 2013
Gr/MoS2DNA hybridizationPhotoluminescence1 attomolar [50]; 2014
MoS2/Gr on AuBiomoleculeSurface plasmon resonance (SPR) 10−6 RIU[46]; 2015
MoS2/Gr–Al hybridBiomoleculeAngle-based SPR190.83° RIU−1 [47]; 2017
GrPMMA, PVPIR transmission spectroscopy--[51]; 2014
GrssDNAPhase-based SPR1 attomolar-[52]; 2015
GrGlucoseFET0.5 μM-[53]; 2015
GrCarcinoembryonic antigen (CEA)FET100 pg mL−1 [54]; 2016
GrProteinAcoustic Gr plasmons--[55]; 2017
Multichannel GrDNAFET10 pM-[56]; 2017
rGrO + trityl organic radicalXanthineElectrode-based0.52 nM-[57]; 2017
GrOhCGAngle-based SPR0.06 mM-[58]; 2017
hBNDopamineNeurotransmittor10 μM-[59]; 2016
hBNCBPIR vibrational spectroscopy--[60]; 2018
Gr/hBNDNA sequencingCurrent Modulation--[44]; 2017
Gr/hBNDNA sequencingCurrent Modulation--[43]; 2019
Gr/hBNBiomoleculeSPR4.207 µm RIU−1 [45]; 2019
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Aqra, M.W.; Ramanathan, A.A. Review of the Recent Advances in Nano-Biosensors and Technologies for Healthcare Applications. Chem. Proc. 2021, 5, 76. https://doi.org/10.3390/CSAC2021-10473

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Aqra MW, Ramanathan AA. Review of the Recent Advances in Nano-Biosensors and Technologies for Healthcare Applications. Chemistry Proceedings. 2021; 5(1):76. https://doi.org/10.3390/CSAC2021-10473

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Aqra, Maha Wajeeh, and Amall Ahmed Ramanathan. 2021. "Review of the Recent Advances in Nano-Biosensors and Technologies for Healthcare Applications" Chemistry Proceedings 5, no. 1: 76. https://doi.org/10.3390/CSAC2021-10473

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Aqra, M. W., & Ramanathan, A. A. (2021). Review of the Recent Advances in Nano-Biosensors and Technologies for Healthcare Applications. Chemistry Proceedings, 5(1), 76. https://doi.org/10.3390/CSAC2021-10473

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