2017
DOI: 10.1155/2017/7974545
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Adsorption Properties of Typical Lung Cancer Breath Gases on Ni-SWCNTs through Density Functional Theory

Abstract: A lot of useful information is contained in the human breath gases, which makes it an effective way to diagnose diseases by detecting the typical breath gases. This work investigated the adsorption of typical lung cancer breath gases: benzene, styrene, isoprene, and 1-hexene onto the surface of intrinsic and Ni-doped single wall carbon nanotubes through density functional theory. Calculation results show that the typical lung cancer breath gases adsorb on intrinsic single wall carbon nanotubes surface by weak … Show more

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Cited by 11 publications
(4 citation statements)
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“…Lu et al, detected methane (CH4) gas using highly sensitive palladium doped carbon nanotube (Pd-CNT) [20]. In the same way, Wan et al, studied sensing of hazardous gases such as benzene, styrene, isoprene, and 1-hexene on the surface of Ni decorated single walled carbon nanotube (Ni-SWCNT) [21]. Penza et al, detected the NO2 and NH3 with separately doping of Ni and Pd on the single wall carbon nanotube [22].…”
Section: Introductionmentioning
confidence: 99%
“…Lu et al, detected methane (CH4) gas using highly sensitive palladium doped carbon nanotube (Pd-CNT) [20]. In the same way, Wan et al, studied sensing of hazardous gases such as benzene, styrene, isoprene, and 1-hexene on the surface of Ni decorated single walled carbon nanotube (Ni-SWCNT) [21]. Penza et al, detected the NO2 and NH3 with separately doping of Ni and Pd on the single wall carbon nanotube [22].…”
Section: Introductionmentioning
confidence: 99%
“…Nevertheless, it is time consuming and expensive and requires proficient professionals, thus stimulating the need of biosensors for lung cancer biomarkers with rapid and effective detection. , Within the past few decades, there is an increasing interest in utilizing nanomaterials for C 3 H 6 O, C 6 H 6 , and C 5 H 8 sensing due to their naturally active surface, small size and cost-effectiveness . Carbon nanotubes (CNT) have shown high potential for sensing these three gases thanks to their large specific surface area, small tip ratios and high conductivity. , Besides, other nanomaterials such as metal–organic frameworks (MOFs) and metal oxide semiconductors (MOS) are also desirable for sensing the three molecules due to their tunability, low cost and small size. Meanwhile, zeolite layers are capable of catalyzing the sensing performance of MOS upon C 3 H 6 O, C 6 H 6 , and C 5 H 8 gases . In recent years, 2D materials have attracted much attention for lung cancer biomarker capturing due to their extremely high surface area–volume ratio, high sensitivity, rapid response, and the smaller size and other characteristics that could not be identified from other nanomaterials. , …”
Section: Introductionmentioning
confidence: 99%
“… 19 Carbon nanotubes (CNT) have shown high potential for sensing these three gases thanks to their large specific surface area, small tip ratios and high conductivity. 16 , 20 Besides, other nanomaterials such as metal–organic frameworks (MOFs) and metal oxide semiconductors (MOS) are also desirable for sensing the three molecules due to their tunability, low cost and small size. 21 23 Meanwhile, zeolite layers are capable of catalyzing the sensing performance of MOS upon C 3 H 6 O, C 6 H 6 , and C 5 H 8 gases.…”
Section: Introductionmentioning
confidence: 99%
“…The results showed that the sensors based on carbon nanotubes, graphene and its derivatives are capable for detecting individual molecules with a relatively high sensitivity. Furthermore, these materials are suggested as highly sensitive biosensors to detect the expression of typical biological molecules at early stage of cancer [27][28][29]. In terms of the application of nanomaterials as sensors, sheets and nanotubes based on phosphorene, silicene, germanene, antimonene, and arsenene are also receiving great attentions from both the academic and industrial communities [30][31][32][33][34].…”
Section: Introductionmentioning
confidence: 99%