Pristine and Pd doped Carbon Nanotube as a Lung Cancer Biomarker for CO₂ and Rn gas: A DFT Analysis

Kirtesh Pratap Khare^1,2*, Reena Srivastava², Anurag Srivastava²

¹Department of Biosciences, Acropolis Institute of Management Studies and Research, Madhya Pradesh, Indore.

²Advanced Materials Research Group, Materials Synthesis and Sensor Design Laboratory,

ABV-Indian Institute of Information Technology and Management, Gwalior.

*Corresponding Author E-mail: kirteshkhare01@gmail.com

ABSTRACT:

Lung cancer has the highest mortality rate over the years. According to the American Cancer Society, around 1,620 individuals were predicted to die of cancer every day in the United States in 2015 this is roughly equivalent to nearly 590,000 individuals. The death level of lung cancer among males has fallen by 29% over the previous 39 years, while it has risen by 102% among females. There are many methods to sense lung cancer early, but they all are very costly and not user friendly. We develop a carbon nano tube (CNT) based pristine and palladium (Pd) doped sensors for lung cancer pre-diagnosis. There are carbon dioxide (CO₂) and radon (Rn) two leading lung cancer gases. To improve the sensing behavior of pristine CNT, Pd is used as a doping agent. The performance of the sensor is evaluated by using DFT based quantum ATK method, in terms of band gap, density of state (DOS), adsorption energy (E_ads), recovery time (τ), charge transfer, conductance, and sensitivity. The calculated negative adsorption energy confirms the stability of pristine and pd doped CNT and observes the type of interaction with CO₂ and Rn, as physical adsorption, that also confirms the reusability of the sensor and its low operational temperature. It has also been observed that the pd-doped CNT has favorable stability with and without presence of CO₂ and Rn gas molecules in comparison to pristine CNT, whereas the pd-doped CNT has a better recovery time, sensitivity, and better range of detection.

KEYWORDS: DFT, DOS, CNT, Cancer, Electronic properties.

INTRODUCTION:

Lung cancer is the leading source of women’s cancer casualties in the United States, accounting for nearly twice as many casualties as breast cancer^1–3. Men have a higher level of lung cancer than females, but females are picking up^4–6. It was estimated that lung cancer would be diagnosed to 117,920 men and 106,470 women in 2018^7,8. Due to the high mortality rate lung cancer requires early detection. Only 14% cases of lung cancer detect on the early stage^9,10.

At an early stage, there are many ways to detect lung cancer such as x-ray, computerized tomography, chest X-ray, and biopsy, but they are all very expensive and time-consuming^11,12. Therefore the detection of lung cancer requires a quick and simple method. Sensing technique provides a bright and promising future by identifying the exhaled gases of alleged people with lung cancer because people with this disease have already recorded exhaling some typical chemicals in the air^13–18. The diagnosis can be done at home and it is also user-friendly. The sensors based on CNT provide good sensing, low cost and quick response^19,20. CNT is the world’s strongest material and has unique electrical and mechanical properties, accompanied by other nanoparticles^21,22. Carbon di oxide (CO₂) and Radon (Rn) are the two main exhaled gases for lung cancer that will be detected^23–25. Radon is a noble gas that is radioactive, colorless, odorless and tasteless. Transition metal (TM) decoration on CNT will stimulate its absorbing properties due to strong transition metal (TM) electron acceptance and widowing behaviors^26,27. The 70% cases of lung cancer are caused by smoke and another 30% are caused by exposure of various gases and materials^28–30. The Pd-doped single-walled carbon nanotube (SWCNT) has been Selected for detection in this work^31,32. Pd (palladium) is a transition metal that is used as a doping element to examine the performance of the device by transferring charge, adsorption energy, and sensitivity. Calculation is done by quantum ATK based DFT approach.

COMPUTATIONAL DETAILS :

A powerful set of modeling tools, the Atomistix Tool-Kit (ATK) Virtual Nano-Lab is used for investigating a variety of Nano scale systems as molecules, bulk and two probe systems. We have applied the quantum ATK based DFT approach with exchange-correlation functional GGA with Perdew-Burkew-Ernzerhof (PBE) ³³ parameterization based on density functional theory (DFT) through first-principle approach for simulation of the pristine and pd-doped CNT. The optimized structures of pristine and pd-doped CNT have been optimized and analyzed prior to the estimations. In the present calculation, we have calculated the physical properties like total energy, adsorption energy, and band gap, density of states, conductance, and sensitivity using k point sampling 1×1×10. Double zeta double polarized basis (DZDP) sets are used for core and valence electronic states. We have chosen the basic settings such as electron temperature 300K, grid mesh cut off 75, exchange correlation GGA through ATK-DFT toolkit ^34–36. During the optimization of geometries, the maximum stress tolerance has been set to 0.05 eV/Å³ with maximum force of 0.05 eV/Å respectively.

(a) (b)

Figure 1. Optimized geometries of (a) Pristine CNT, (b) pd-CNT, (c) CO₂, and (d) Rn

RESULT AND DISCUSSION:

Structural stability Analysis:

Fig. 1 and Fig. 2 show the optimized geometries of pristine and pd-doped CNT with and without presence of CO₂ and Rn gas molecules. Table 1, reports the total energy of the optimized geometries in structural and stability analysis. The value of total energy indicate the pd-doped CNT in the presence and absence of CO₂ and Rn gas molecules is minimum in comparison to pristine CNT because the value of total energy gets decreased in pristine and pd-doped CNT in the presence of CO₂ and Rn gas molecule. In the present work simulate the sensing behavior of pristine and pd-doped CNT for the detection of CO₂ and Rn gas molecules for the treatment of lung cancer. The computed total energy confirms that the pd-doped CNT shows the better stability with and without presence of CO2 and Rn gas molecules in comparison to pristine CNT.

Table 1. Total energy of pristine and pd-doped CNT with and without presence of CO₂and Rn gas molecule.

System	Total energy (eV)
CNT	-1888.79
Pd-CNT	-19566.24
CNT_CO₂	-19911.17
CNT_Rn	-20081.98
Pd-CNT_CO₂	-20593.8
Pd-CNT_Rn	-20764.8

(a) (b)

Figure 2. (a-d) Optimized geometries of (a,b) Pristine and (c,d) pd-doped adsorbing system with CO₂ and Rn gas molecules.

Electronic properties:

To understand the electronic behavior of pristine and pd-doped CNT with and without the presence of CO₂ and Rn gas molecules, band gap has been computed. When a single molecule of CO₂ and Rn gas is brought in vicinity of the surface of pristine and pd-doped CNT, the band gap has been changed due to presence of CO₂ and Rn gas molecules, confirmed through its band structure profile, shown in Fig. 3 (a-f). The band gap of pristine CNT in the presence of CO₂ and Rn gas molecules has been computed and compared with pd-doped CNT. The computed band gap of pristine and pd-doped CNT in the absence of CO₂ and Rn gas molecules is 0.689 eV and 0.397 eV. Whereas, the band gap of the same sets in the presence of CO₂ and Rn gas molecules has been reduced to 0.685 eV and 0.683 eV in pristine CNT and 0.388 eV and 0.391 eV in pd-doped CNT respectively, as reported in Table 2.

Table 2. Band gap, conductance, sensitivity, and charge transfer for adsorbing system.

System	Band-	Conductance (S)	Sensitivity (%)	QT (e)
System	gap	Conductance (S)	Sensitivity (%)	QT (e)
CNT (10,0)	0.689	5.458e-10	-	-
CNT (10,0)_CO₂	0.685	5.458e-10	0	0.005
CNT (10,0)_Rn	0.683	5.458e-10	0	0.02
CNT (10,0)-Pd	0.397	8.111e-08	-	-
CNT (10,0)-Pd_CO₂	0.388	1.335e-07	83.54	-0.13
CNT (10,0)-Pd_Rn	0.391	1.33e-07	83.602	-0.282

In addition, to understand the variation in electronic properties of pristine and pd-doped CNT with and without presence of CO₂ and Rn gas molecules, density of state (DOS) profile has also been computed, as depicted in Fig. 3 (a-f). DOS profiles of pristine and pd-doped CNT in the presence of CO₂ and Rn gas molecules has transformed.

During the interaction between adsorbate and adsorbent, the Fermi level shifts towards balance/conduction band as shown in Fig. 3 (a-f). In case of pristine CNT in the presence of CO₂ and Rn gas molecules few extra peaks appeared in valance as well as conduction band and the length of peaks have also been altered in the valence as well as conduction band. While in case of pd-doped CNT some extra peaks are appeared in valence band as well as conduction band and the length of peaks are also changed was observed.

Adsorption Energy:

Adsorption energy is hitherto an alternate important parameter to understand the interaction between the interacting entities. In this work we have calculate the

adsorption energy with the help of equation 1. Calculated adsorption energy is negative in all cases, reported in Table 3.

E_ads = ET _(system) – ET _(CNT) – ET _(gas)1

Where ET_(System) is the total energy of the optimized adsorbed system, ET_(CNT) is the total energy of optimized pristine and pd-doped CNT, and ET_(gas) is the total energy of optimized CO₂ and Rn gas molecules. Negative adsorption energy indicates physical adsorption and exothermic reaction between adsorbate and adsorbent in pristine as well as pd-doped CNT, which confirmed the adsorption system is stable and stronger. The adsorption energy in case of pd-doped CNT is the minimum and in case of pristine CNT is the maximum for its interaction with Rn gas molecule. To support the inference of physical adsorption, energy is also verified by optimized geometries, as shown in Fig. 2 (a-d), denote that no chemical bond formed between pristine and pd-doped CNT with CO₂ and Rn gas molecules.

To understand the interaction between adsorbate and adsorbent, recovery time (τ), as a function of adsorption energy (E_ads)in equation 2, stands another important sensor parameter³⁷.

(τ) = υ^-1exp (-E_ads/K_bT) 2

Where, (υ) is the attempt frequency, (K_b) the Boltzmann constant and (T) is operational temperature. Adsorption energy (E_ads) and recovery time (τ) are inversely proportional. The adsorption energy shows the trend of pristine and pd-doped CNT as CNT_Rn > CNT_CO₂> pd-doped CNT_CO₂ > pd-doped CNT_Rn and the recovery time shows the trend CNT_Rn < CNT_CO₂< pd-doped CNT_CO₂ < pd-doped CNT_Rn. Recovery time of pd-doped CNT in the presence of Rn gas molecule is fast with less operational temperature in comparison to other adsorbed systems.

Table 3. Optimized distance and Adsorption energy of CO₂ and Rn adsorbed system.

System	Optimized distance (Å)	Adsorption Energy (eV)	Type of Interaction
CNT (10,0)_CO₂	3.07	-0.203	Physisorption
CNT (10,0)_Rn	3.63	-0.186	Physisorption
CNT (10,0)-Pd_CO₂	2.57	-0.3	Physisorption
CNT (10,0)-Pd_Rn	3.05	-0.556	Physisorption

Charge Transfer Analysis:

To understand in depth the behavior of interaction between pristine and pd-doped CNT with CO2 and Rn gas molecules, the charge transfer parameter have been worked out through Mulliken population analysis, reported in Table 2. The negative values of charge transfer indicate the charge transfers from adsorbate to adsorbent and the positive value indicate the reverse. In the present work, the charge transfers from CO2 and Rn gas molecules to pd-doped CNT. While, in case of pristine CNT the charge transfers from pristine CNT to CO₂ and Rn gas molecules. The charge transfers values in pristine and pd-doped CNT with CO₂ and Rn gas molecules, shows the following trends pd-doped CNT Rn (-0.282) > pd-doped CNT_CO₂ (-0.13) > pristine CNT Rn (0.02) > pristine CNT_CO₂ (0.005).

Range of detection Analysis:

The adsorption mechanism of pristine and pd-doped CNT, observed in case of CO₂ and Rn gas molecules has been analysed in terms of the adsorption distance and the type of interaction between pristine and pd-doped CNT with CO₂ and R_n gas molecules.

Here, the variation of the conductance has been computed as a function of distance between CO₂ and Rn gas molecules to pristine and pd-doped CNT, within the optimized adsorption distance. These variations of the conductance as a function of distance of the CO₂ and Rn gas molecules from pristine and pd-doped CNT within the optimized distance are shown in Fig. 2 (a-d), demonstrate that the conductance has a linear relationship with distance between gas molecule and pristine CNT in case of CO₂, it increases up to a certain distance and then decreases, with increasing the distance between molecule and CNT. In case of Rn adsorbed pristine CNT, the conductance decreases upto a certain distance after which it, confirms the sensitivity of pristine CNT for considered Rn gas molecule. Whereas, the conductance has an inverse relationship with the distance between molecule and pd-doped CNT, in case of CO₂ and Rn gas molecules. The computed zero bias conductance for the pristine CNT is found be 5.458e-10 and after adsorption of CO2 and Rn gas molecules it is 5.458e-10 and 5.458e-10. While, the zero bias conductance for the pd-doped CNT is 8.111e-08 and after adsorption of CO2 and Rn gas molecules it is 1.335e-07 and 1.33e-07. The computed conductance has also been used to specifically analyse the sensitivity of pristine and pd-dope CNT for CO2 and Rn gas molecules, by using equation (3) and reported in table 2.

𝐒 = 𝐆 – 𝐆_𝐨/𝐆_o (3)

Where G_o is the conductance of pristine and pd-doped CNT and G is the conductance of CO₂ and Rn gas molecule adsorbed system. Where, the sensitivity has estimated as a function of conductance, are 0 %, 0 % in case of CO2 and Rn adsorbed pristine CNT, whereas, in case of pd-doped CNT 83.540 % and 83.602 % for CO₂ and Rn. These findings confirm that the sensitivity for CO2 and Rn gas molecule with pd-doped CNT is sufficiently remarkable, in comparison to pristine CNT.

Current-Voltage Analysis:

Current-voltage has been calculated by using two probe model of pristine and pd-doped CNT by extending its scattering region as left and right electrode, shown in Fig. 6 (a,b) at zero bias in the presence of CO₂ and Rn gas molecules. Fig. 7 shows the current-voltage characteristics of CO₂ and Rn gas molecules adsorbed pristine CNT in comparison to pd-doped CNT. Where, the maximum current has been observed in case of CO₂ and Rn gas molecules adsorbed pd-doped CNT and CO₂ adsorbed pristine CNT, in comparison to Rn gas molecule adsorbed pristine CNT. In case of CO₂ adsorbed pristine CNT and CO2, Rn gas molecules adsorbed pd-doped CNT current increases after applied voltage of 0.5 V and in case of CO2 and Rn adsorbed pristine CNT, the current increases after applied voltage of 0.6 V, where, this voltage a small current is observed. As the variation in the current voltage characteristics at voltage are not distinct, the same has been presented in the enlarged view in Fig. 4, hence the variation in the I-V characteristics also verifies the sensitivity of pristine and pd-doped CNT towards considered CO₂ and Rn gas molecules.

Figure 4. I-V analysis of Pristine CNT (10,0), and Pd doped CNT (10,0) adsorbing system with CO₂, and Rn gas molecule.

CONCLUSION:

This study simulates the adsorption activity of pristine and pd-CNT on two typical gases of lung cancer (CO₂ and Radon) to assess the specific sensitivity of this material for lung cancer treatment. The band gap, Density of state, adsorption energy, recovery time, Mulliken population, sensitivity, and current-voltage have been analyzed for the proposed pristine and pd-doped CNT based sensor. The remarkable variation in electronic properties of pristine and pd-doped CNT confirmed the sensing of CO₂ and Rn gas molecule. The observations reveal that pd-doped CNT is better sensing material in terms of band gap, sensitivity, adsorption energy, and range of detection towards CO2 and Rn gas molecule in comparison to pristine CNT. The purpose of this research is to provide an effective approach to lung cancer patients using exhaled gas detection for the prediagnosis of lung cancer.

CONFLICT OF INTEREST:

The authors have no conflicts of interest regarding this work.

ACKNOWLEDGMENTS:

The authors put on record, the gratitude to Advanced Materials Research Group of Materials Synthesis and Sensor Design Laboratory, ABV-IIITM, Gwalior for providing the computational resources and access to the e-library for the present piece of research work.

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Received on 07.08.2025 Revised on 28.08.2025

Accepted on 15.09.2025 Published on 30.09.2025

Available online from October 07, 2025

Asian J. Research Chem.2025; 18(5):331-336.

DOI: 10.52711/0974-4150.2025.00051

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