Skip to main content
Log in

Analytical investigation of CO2 sensor based on carbon strand

  • Original Paper
  • Published:
International Journal of Environmental Science and Technology Aims and scope Submit manuscript


This experimental study attempts to design and develop a novel carbon-based material fabrication method that implements high voltage AC arc discharge. The carbon-based material is to be used in an electric circuit to build up a gas sensing mechanism. After applying a high AC voltage to the graphite electrodes employed in the experiment, an arc ignites between the electrodes as the gas between them is iodized. In the carbon decomposition process, the arc is employed and results in the fabricated carbon strands. Thereafter, carbon monoxide (CO2) in the atmospheric pressure is passed over the electrodes in the Pyrex glass tube chamber where the carbon strand fabrication process takes place. An increment appears in the measured current voltage (IV) between the two sides of the carbon strand as the carrier concentration of CO2 gas is increased from 200 to 800 ppm. Support vector regression (SVR) algorithm was used for data processing with statistical analysis for errors and quality control.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others


  • Akbari E, Ahmadi M, Yusof R, Ghadiry M, Saeidmanesh M (2013) Gas concentration effect on channel capacitance in graphene based sensors. J Comput Theor Nanosci 10(10):2449–2452

    Article  CAS  Google Scholar 

  • Akbari E, Buntat Z, Ahmad MH, Enzevaee A, Yousof R, Iqbal SMZ, Karimi H (2014a) Analytical calculation of sensing parameters on carbon nanotube based gas sensors. Sensors 14(3):5502–5515

    Article  CAS  Google Scholar 

  • Akbari E, Buntat Z, Enzevaee A, Mirazimiabarghouei SJ, Bahadoran M, Shahidi A, Nikoukar A (2014b) Correction: an analytical model and ANN simulation for carbon nanotube based ammonium gas sensors. RSC Adv 4(80):42581

    Article  CAS  Google Scholar 

  • Anthony M (1997) Computational learning theory. Cambridge University Press, Cambridge

    Google Scholar 

  • Craig H, Chou C, Welhan J, Stevens C, Engelkemeir A (1988) The isotopic composition of methane in polar ice cores. Science 242(4885):1535–1539

    Article  CAS  Google Scholar 

  • Cristianini N, Shawe-Taylor J (2000) An introduction to support vector machines and other kernel-based learning methods. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Davidson EA, Ishida FY, Nepstad DC (2004) Effects of an experimental drought on soil emissions of carbon dioxide, methane, nitrous oxide, and nitric oxide in a moist tropical forest. Glob Change Biol 10(5):718–730

    Article  Google Scholar 

  • Gunn, S. R. (1998). Support vector machines for classification and regression. ISIS technical report 14

  • Gupta VK, Saleh TA (2013) Sorption of pollutants by porous carbon, carbon nanotubes and fullerene—an overview. Env Sci Pollut Res 20(5):2828–2843

    Article  CAS  Google Scholar 

  • Gupta VK, Ali I, Saleh TA, Nayak A, Agarwal S (2012) Chemical treatment technologies for waste-water recycling—an overview. RSC Adv 2(16):6380–6388

    Article  CAS  Google Scholar 

  • Gupta VK, Kumar R, Nayak A, Saleh TA, Barakat M (2013) Adsorptive removal of dyes from aqueous solution onto carbon nanotubes: a review. Adv Colloid Interface Sci 193:24–34

    Article  Google Scholar 

  • Huttunen JT, Alm J, Liikanen A, Juutinen S, Larmola T, Hammar T, Martikainen PJ (2003) Fluxes of methane, carbon dioxide and nitrous oxide in boreal lakes and potential anthropogenic effects on the aquatic greenhouse gas emissions. Chemosphere 52(3):609–621

    Article  CAS  Google Scholar 

  • Iqbal SMZ (2014) Decomposition of methane into carbonaceous material using arc discharge method. UTM thesis

  • Krcma F, Klohnova K, Polachova L, Horvath G (2010) Optical emission spectroscopy of abnormal glow discharge in nitrogen-methane mixtures at atmospheric pressure. Publications de l’Observatoire Astronomique de Beograd 89:371–374

    Google Scholar 

  • Lee EK, Lee SY, Han GY, Lee BK, Lee T-J, Jun JH, Yoon KJ (2004) Catalytic decomposition of methane over carbon blacks for CO2-free hydrogen production. Carbon 42(12–13):2641–2648

    Article  CAS  Google Scholar 

  • Moon YK, Lee J, Lee JK, Kim TK, Kim SH (2009) Synthesis of length-controlled aerosol carbon nanotubes and their dispersion stability in aqueous solution. Langmuir 25(3):1739–1743

    Article  CAS  Google Scholar 

  • Müller K-R., Smola AJ, Rätsch G, Schölkopf B, Kohlmorgen J, Vapnik V. (1997). Predicting time series with support vector machines artificial neural networks—ICANN’97 (pp. 999–1004): Springer

  • Patel N, Bazzanella RFN, Miotello A (2011) Enhanced hydrogen production by hydrolysis of NaBH4 using “Co-B nanoparticles supported on Carbon film” catalyst synthesized by pulsed laser deposition. Elsevier 170(1):20–26

    CAS  Google Scholar 

  • Patacsil C, Malapit G, Ramos H (2006) Optical emission spectroscopy of low temperature CVD diamond. J Plasma Fusion Res Ser 7:145–149

    Google Scholar 

  • Schoell M (1980) The hydrogen and carbon isotopic composition of methane from natural gases of various origins. Geochim Cosmochim Acta 44(5):649–661

    Article  CAS  Google Scholar 

  • Smola AJ, Schölkopf B (2004) A tutorial on support vector regression. Stat Comput 14(3):199–222

    Article  Google Scholar 

  • Stahlbock R, Lessmann S (2004) Potential von Support Vektor Maschinen im analytischen Customer Relationship Management. Universität Hamburg, Hamburg

    Google Scholar 

  • Stevens CM, Engelkemeir A (1988) Stable carbon isotopic composition of methane from some natural and anthropogenic sources. J Geophys Res Atmos 93(D1):725–733

    Article  CAS  Google Scholar 

  • Welling M (2004) Support vector regression. Department of Computer Science, University of Toronto, Toronto

    Google Scholar 

  • Zhang J, Jin L, Li Y, Si H, Qiu B, Hu H (2013) Hierarchical porous carbon catalyst for simultaneous preparation of hydrogen and fibrous carbon by catalytic methane decomposition. Int J Hydrog Energy 38(21):8732–8740

    Article  CAS  Google Scholar 

Download references


The authors would like to thank Ministry of Higher Education (MOHE), Malaysia (Grant Vot. No. 4F382), and the Universiti Teknologi Malaysia (Grants Vot. No. 03H86 and Postdoc Grant No. 02E11) for the financial support received during the investigation.

Author information

Authors and Affiliations


Corresponding author

Correspondence to E. Akbari.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Akbari, E., Buntat, Z., Afroozeh, A. et al. Analytical investigation of CO2 sensor based on carbon strand. Int. J. Environ. Sci. Technol. 13, 339–348 (2016).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: