Not Only Graphene Two-Dimensional Nanomaterials: Recent Trends in Electrochemical (Bio)sensing Area for Biomedical and Healthcare Applications
Abstract
:1. Introduction
2. Two-Dimensional Nanomaterials
2.1. MXenes
2.2. TMDs
2.3. MOFs
2.4. COFs
3. Applications of 2D Nanomaterials to Electrochemical (Bio)Sensors for Healthcare and Biomedical Field
3.1. Glucose
3.2. Neurotransmitters
3.2.1. Dopamine
3.2.2. Serotonin
3.3. Hormones
3.4. Pathogens
3.4.1. Bacteria
3.4.2. Viruses
3.5. Cancer Biomarkers
3.6. Antibiotics
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Electrode | 2D Nanomaterial | Format | Technique | Sample | Linearity (μM) | LOD (μM) | Recovery % | Reference Method | Ref. |
---|---|---|---|---|---|---|---|---|---|
GCE | ZIF-67 | sensor based on Ag@ZIF-67 nanocomposite | A | - | 2–1000 | 0.66 | - | - | [50] |
GCE | ZIF-67 | sensor based on Ag@TiO2@ZIF-67 nanocomposite | A | - | 48–1000 | 0.99 | - | - | [51] |
rGO/PU fiber | Ni–Co MOF | sensor based on Ni–Co MOF/Ag nanocomposite | A | Human sweat | 10–660 | 3.28 | - | Glucometer blood test | [52] |
SPCPE | NC-ZIF | biosensor based on GOX/Hemin@NC-ZIF | A | Human sweat | 50–600 | 2 | - | Glucometer blood test | [53] |
CC | ZIF-67 | sensor based on ZIF-67@GO/NiCo2O4 | A | - | 0.3–157.4 | 0.16 | - | - | [54] |
NF | Cu1Co2-MOF | sensor based on Cu1Co2-MOF | CA | - | 50–500 | 23 | - | - | [55] |
GCE | Ni-MOF | sensor based on Ni-MOF@Ni-HHTP-5 NSs core@shell structures | A | - | 500–2,665,500 | 48.5 | - | - | [56] |
BCSB | Ni-Co MOF as sacrificial template | sensor based on NiO/Co3O4/C nanocomposite | A | Human blood serum | 0.2–10,000 | 0.045 | 98.3–102.4 | - | [57] |
CFE | Ni-MOF | sensor based on Ni-MOF/rGO nanocomposite | A | Orange juice | 6–2090 | 0.6 | - | - | [59] |
GCE | N-doped-Co- MOF | sensor based on N-Co-MOF@PDA-Ag nanocomposite | A | Human serum | 1–2000 | 0.5 | 96–110 | - | [60] |
AuE | Ni-Co-MOF | sensor based on Ni–Co MOF/Au/PDMS nanocomposite | A | Human sweat | 20–790 | 4.25 | - | Glucometer blood test | [61] |
SPCE | MXene (Ti3C2Tx) | biosensor based on ZnO TPs/MXene/GOX | CA | Human sweat | 50–700 | 17 | - | Glucometer blood test | [62] |
Cr/AuE | MXene (Ti3C2Tx) | biosensor based on MXene/GOX | A | - | 100–10,000 | 12.1 | - | - | [63] |
GCE | MXene (Ti3C2Tx) | biosensor based on PEDOT:SCX/MXene/GOX | A | Fruit juice | 500–8000 | 22.5 | 96–99 | - | [64] |
AuE | MXene (Ti3C2Tx) | biosensor based on GOX/PtNPs/NPC/MXene | CA | Human sweat | 3–21,000 | 7 | - | Glucometer blood test | [65] |
GCE | MXene | sensor based on MXene/CHI/Cu2O | CV | Human serum | 52.4–2000 | 52.4 | 98.04–102.94 | - | [66] |
GCE | MXene (Ti3C2Tx) ZIF-67 | sensor based on Ti3C2Tx/ZIF-67 nanocomposite | A | - | 5–7500 | 3.81 | - | - | [67] |
GCE | Ti2C-MXene | sensor based on Ti2C-TiO2-MXene nanocomposite | DPV | Human serum | 0.1–200 | 0.12 | 99.80–100.23 | Glucometer blood test | [68] |
CFE | MXene | sensor based on Co3O4/MXene nanocomposite | A | Human blood serum, urine | 0.05–7440 | 0.010 | 97.80–101.60 | Glucometer blood test | [69] |
GCE | MXene (Ti3C2Tx) | sensor based on MXene-Cu2O nanocomposite | CA | Human serum | 10–30,000 | 2.83 | - | Glucometer blood test | [70] |
AuE | c-MOF (Cu3(HHTP)2) | sensor based on c-MOF | A | - | 0.2–7 mM | 10 | - | - | [71] |
Electrode | 2D Nanomaterial | Format | Technique | Sample | Linearity | LOD | Recovery (%) | Ref. |
---|---|---|---|---|---|---|---|---|
GCE | MXene (Ti3C2Tx) | sensor based on Ti3C2Tx/PtNPs | A | - | Up to 750 μM | 10 nM | - | [74] |
PGS | TMD (MoS2) | sensor based on MoS2 | DPV | DA | 0.05–5 nM 5 nM–5 mM | 50 pM | - | [75] |
GCE | MXene (Ti-C-Tx) | sensor based on Ti-C-Tx | DPV | DA,AA,UA | DA: 0.5–4 μM AA: 0.5–50 μM UA: 0.1–1.5 μM | DA: 0.06 μM AA: 4.6 μM UA: 0.075 μM | - | [76] |
CC | TMD (MoS2) | sensor based on MoS2 nanosheets | CV | DA | 250–4000 μM | 0.3 μM | - | [77] |
GCE | TS-COF | sensor based on AuNPs@TS-COF/rGO | DPV | DA,AA,UA in human urine | DA: 20–100 μM AA: 8–900 μM UA: 25–80 μM | DA: 0.03 μM AA: 4.30 μM UA: 0.07 μM | 97–104.4 | [78] |
GCE | Fe-based MOF MIL-100(Fe) | sensor based on POM- MOF/PVP | DPV | DA,UA in human serum | DA: 1–247 μM UA: 5–406 μM | DA: 1 μM UA: 5 μM | DA: 97.67–102.16 UA: 97.81–102.89 | [79] |
LPE | MOF (ZIF-67) | sensor based on ZIF-67/PEDOT | A | DA in human blood | 15–240 μM | 0.04 μM | - | [80] |
GPE | MXene (Ti3C2Cl2) | sensor based on IL-MXene | A | DA in human serum | 100–2000 μM | 702 nM | 98.3–100 | [81] |
GCE | MXene (Ti3C2) MOF (UIO-66-NH2) | sensor based on Ti3C2/UIO-66-NH2 | DPV | DA in human serum | 1–250 fM | 0.81 fM | 101.2–103.5 | [82] |
AuE | MXene (Ti3C2Tx) | sensor based on ZnO NPs/Ti3C2Tx | CA | DA in human serum | 0.1–1200 μM | 0.076 μM | 97.8–102.2 | [83] |
GCE | MXene (Ti3C2) | sensor based on Ti3C2/g-MWCNTs/ ZnO NSPs | DPV | DA in human serum | 0.01–30 μM | 3.2 nM | 98.6–105.9 | [84] |
SPCE | MXene (Ti3C2) | sensor based on Ti3C2 | DPV | DA in human urine Tyr in drug | 0.5–600 μM | 0.15 μM | DA: 97.1–104.0 Tyr: 96.7–102.5 | [85] |
GCE | TMD (MoS2) | sensor based on Ni-MoS2 | DPV | DA in bovine serum | 1 pM–1 mM | 1 pM | 97.0–105.0 | [87] |
FTO SPE | TMD (MoS2) | sensor based on MoS2 | DPV | DA | Up to 300 μM | 260 nM | - | [90] |
GCE | MXene (Ti3C2Tx) | sensor based on Tri-AgNPs/L-Cys/ MXene | DPV | 5-HT in human serum | 0.5–150 μM | 0.08 μM | 95.38–102.3 | [92] |
WGPE | TMD (WS2) | sensor based on WGP | DPV | DA, 5-HT in artificial CSF | DA: 1.21–13.37 μM 5-HT: 9.9–0.249 μM | DA: 1.24 μM 5-HT: 0.24 μM | 95.2–104.1 | [93] |
GCE | MXene (Ti3C2) | sensor based on MXene/SWCNTs | CA | 5-HT produced by living cells | 0.004–103.2 μM | 1.5 nM | - | [94] |
GCE | MXene (Ti3C2) | sensor based on MXene/rGO | DPV | 5-HT in human plasma | 0.025–147 μM | 10 nM | 96.4–107 | [95] |
Electrode | 2D Nanomaterial | Format | Technique | Sample | Linearity | LOD | Recovery % | Reference Method | Ref. |
---|---|---|---|---|---|---|---|---|---|
Thread Conductive E | MXene | immunosensor immobilizing anti-cortisol on L-cys/AuNPs/ MXene | A | Cortisol in sweat | 5–180 ng mL−1 | 0.54 ng mL−1 | 94.47–102 | - | [99] |
LBG/PDMS | MXene (Ti3C2Tx) | immunosensorimmobilizing anti-cortisol on Ti3C2Tx/LBG/ PDMS | EIS | Cortisol in sweat | 0.01–100 nM | 3.88 pM | 93.68–99.1 | - | [100] |
ITOE | MXene (Ti3C2Tx) | sensor based on GMA | DPV | EP in human urine | 1–60 μM | 3.5 nM | 95.7–105.7 | - | [102] |
GCE | MOF (CoMn-ZIF) | sensor based on CoMnZIF-CNF | DPV | EP in human urine | 5–1000 μM | 1.667μM | 97.51–102.53 | - | [103] |
DGE | MOF (ZIF-L) | aptasensor immobilizing insulin aptamer on Cu-BTC/ZIF-L | DPV | Insulin in human serum | 0.1 pM–5 μM | 0.027 pM | 97.2–98.5 | ELISA | [105] |
Electrode | 2D Nanomaterial | Format | Technique | Sample | Linearity | LOD | Recovery (%) | Reference Method | Ref. |
---|---|---|---|---|---|---|---|---|---|
SPCE | m-COF | immunosensor immobilizing IgY antibody on m-COF | SWV | E. coli in milk, beef, shrimps | 10–108 CFU mL−1 | 3 CFU mL−1 | 90–103 | ELISA | [108] |
IDEA | COP (CATN) | sensor based on CATN | EIS | E. coli | Up to 10 CFU mL−1 | 2 CFU mL−1 | - | - | [109] |
AuE | COF (Tph-TDC-COF) | aptasensor based on E. coli aptamer immobilized on Tph-TDC-COF | EIS/DPV | E. coli in bread, milk | 10–108 CFU mL−1 | 0.17 CFU mL−1 (EIS) 0.38 CFU mL−1 (DPV) | 100.09–103.97 (bread) 99.61–100.71 (milk). | - | [111] |
GCE | MXene | sensor based on MPBIP | EIS | Salmonella in drinking water | 103–107 CFU mL−1 | 23 CFU mL−1 | 96–109.4 | - | [112] |
GCE | MXene (Ti3C2) | genosensor immobilizing ssDNA on PPY/MXene | DPV | M.tb in human sputum | 100 fM- 25 nM | 11.24 fM | 90.52–100.8 | PCR | [113] |
MGCE | MXene (Ti3C2Tx) | ECL immunosensor based on Fe3O4@Ab1-VV-R6G-Ti3C2Tx@AuNRs-Ab2/ABEI | ECL | VV in seawater | 1–108 CFU mL−1 | 1 CFU mL−1 | 94.8–110.3 | - | [115] |
AuSPE | MXene | sandwich-type aptasensor involving PBA-Fc@Pt@MXenes | DPV | VP in shrimps | 10–108 CFU mL−1 | 5 CFU mL−1 | 95.0–104.3 | - | [116] |
AuE | MOF (MIL-53 (Al)) | sandwich-type aptasensor using 2 aptamers immobilized on AuE and Au@Pt/MIL-53 (Al) nanocomposite modified with HRP and hemin/Gquadruplex DNAzyme as signal nanoprobe | DPV | SARS-CoV-2 NP | 0.025–50 ng mL−1 | 8.33 pg mL−1 | 92–110 | ELISA | [123] |
SPCE | MOF (SiO2@UIO-66) | label-free immunosensor including SiO2@UiO-66 nanocomposite | EIS | SARS-CoV-2 SP in nasal fluid samples | 100.0 fg∙mL−1–10.0 ng∙mL−1 | 100.0 fg mL−1 | 91.6–93.2 | PCR | [124] |
SPCE | MOF Ni3(BTC)2 | label-free aptasensor using Ni3(BTC)2, SARS-CoV-2 aptamer, ePDA | EIS | SARS-CoV-2 virus in saliva, oropharyngeal swab | 10–108 PFU mL−1 | 3.3 PFU mL−1 | 98–104 | PCR | [125] |
IGE | MXene (Ti3C2Tx) | genosensor using ssDNA/Ti3C2Tx | EIS | SARS-CoV-2 N gene | 105–109 copies mL−1 | 103 copies mL−1 | - | - | [127] |
GCE | Cu-MOF | genosensor including Cu-MOF/ErGO | DPV | HBV in human serum, urine | 50.0 fM– 10.0 nM | 5.2 fM | 95.2–99.8 | - | [128] |
GCE | Cu-MOF | label-free immunosensor using Cu-MOF nanospheres | DPV | HBV in human serum | 1–500 ng mL−1 | 730 pg mL−1 | 76.93–92.18 | - | [129] |
Electrode | 2D Nanomaterial | (Bio)Sensor Format | Technique | Sample | Linearity | LOD | Recovery% | Ref. |
---|---|---|---|---|---|---|---|---|
SPCE | MXene (Ti3C2) | Aptasensor including He@CCNT/Ti3C2 | DPV | CEA in human serum | 10–106 pg mL−1 | 2.88 pg mL−1 | 95.29–105.19 | [133] |
FTOE | MXene (Ti3C2) | Immunosensor including Au-β-CD/MXene@ PANI | DPV | CEA in human serum | 0.5–350 ng mL−1 | 42.9 pg mL−1 | 97.52–103.98 | [134] |
GCE | Mxene (Ti3C2Tx) | Aptasensor involving Au-Pd-Pt/Ti3C2Tx | DPV | CEA in human serum | 1 fg mL−1 –1 ng mL−1 | 0.32 fg mL−1 | 98.8–104.1 | [135] |
GCE | COF-LZU1 | Sandwich-type Immunosensor involving COF-LZU1, MrGOF, AgNPs | DPV | CA 125 in human serum | 0.001–40 U mL−1 | 0.00023 U mL−1 | 91.54–105.21 | [137] |
GCE | COF BCN | Sandwich-type immunosensor involving MnO2@COF, AuPtNPs, BCN, PDA | DPV | PSA in human serum | 0.00005–10 ng mL−1 | 16.7 fg mL−1 | 98.9–100.2 | [138] |
AuE | COF (p-COF) | Aptasensor based on EGFR aptamer immobilized on p-COF | DPV EIS | EGFR in human serum | 0.05–100 pg mL−1 | 7.54 × 10−3 pg mL−1 (EIS) 5.64 × 10−3 pg mL−1 (DPV). | 96.2–103.2 | [139] |
AuE | COF (p-COF) | Aptasensor based on EGFR aptamer immobilized on p-COF | EIS | MCF-7/- | 5 × 102–1 × 105 cell·mL−1 | 61 cells·mL−1 | - | [139] |
Electrode | 2D Nanomaterial | Format | Technique | Sample | Linearity | LOD | Recovery % | Reference Method | Ref. |
---|---|---|---|---|---|---|---|---|---|
AuE | Py-M-COF | Aptasensor including Py-M-COF | EIS | ENR in human serum | 0.01–2000 pg mL−1 | 6.07 fg mL−1 | 101.0–112.4 | - | [141] |
AuE | Py-M-COF | Aptasensor including Py-M-COF | EIS | AMP in human serum | 0.001–1000 pg mL−1 | 0.04 fg mL−1 | 99.5–103.0 | - | [141] |
GCE | Zr-amide-Por- based 2D COF | TC-MIECS | ECL | TC in milk | 5–60 pM | 2.3 pM | 94.0–103.5 | - | [142] |
AuE | MOF (PCN-222) | Aptasensor including PCN-222/GO | EIS | CAP in milk, human serum, urine | 0.01–50 ng mL−1 | 7.04 pg mL−1 | 94.6–107.2 | - | [144] |
GCE | COF | Electrochemical sensor based on Pd2+@P-CDPs/COFs | DPV | NF in eye drops | 0.08–7.0 µM 7.0–100.0 µM | 0.031 µM | 97.8–101.7 | HPLC | [145] |
GCE | COF | Electrochemical sensor based on MIP/CuS/Au@COF | DPV | STZ in mutton, fodder, chicken liver, pig liver | 0.001–100,000 nM | 0.0043 nM | 83.0–107.3 | HPLC | [147] |
CPE | MOF (ZIF-67) | Electrochemical sensor based on Fe3O4/ZIF-67/IL | DPV | Sulfamethoxazole in river, tap water, urine | 0.01–520.0 μM | 5.0 nM | 97.1–103.3 | - | [149] |
GCE | COF | Electrochemical sensor based on GO@COF nanocomposite and MIP | DPV | SDZ/beef, pork, chicken, fodder | 0.5–200 μM | 0.16 μM | 82.0–108.0 | HPLC | [150] |
AuE | MOF (PCN-222(Fe) NS) | Aptasensor including PCN-222 (Fe) NS | EIS | TOB/milk | 1.1 × 10−4–10.7 nM | 1.3 × 10−4 nM | 97.5–104.8 | - | [151] |
AuE | COF (Tp-Bpy COF NS) | Aptasensor including Tp-Bpy COF NS | EIS | TOB/milk, river water | 2.1 × 10−4–10.7 nM | 6.57 fM | 95.4–105.2% milk 96.1–104.4% river | - | [152] |
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Di Matteo, P.; Petrucci, R.; Curulli, A. Not Only Graphene Two-Dimensional Nanomaterials: Recent Trends in Electrochemical (Bio)sensing Area for Biomedical and Healthcare Applications. Molecules 2024, 29, 172. https://doi.org/10.3390/molecules29010172
Di Matteo P, Petrucci R, Curulli A. Not Only Graphene Two-Dimensional Nanomaterials: Recent Trends in Electrochemical (Bio)sensing Area for Biomedical and Healthcare Applications. Molecules. 2024; 29(1):172. https://doi.org/10.3390/molecules29010172
Chicago/Turabian StyleDi Matteo, Paola, Rita Petrucci, and Antonella Curulli. 2024. "Not Only Graphene Two-Dimensional Nanomaterials: Recent Trends in Electrochemical (Bio)sensing Area for Biomedical and Healthcare Applications" Molecules 29, no. 1: 172. https://doi.org/10.3390/molecules29010172
APA StyleDi Matteo, P., Petrucci, R., & Curulli, A. (2024). Not Only Graphene Two-Dimensional Nanomaterials: Recent Trends in Electrochemical (Bio)sensing Area for Biomedical and Healthcare Applications. Molecules, 29(1), 172. https://doi.org/10.3390/molecules29010172