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Journal of Cluster Science

, Volume 29, Issue 6, pp 1151–1159 | Cite as

Modelling and Optimization of Biogenic Synthesis of Gold Nanoparticles from Leaf Extract of Swertia chirata Using Artificial Neural Network

  • Nirlipta Saha
  • Gonzalo Astray
  • S. Dutta Gupta
Original Paper
  • 82 Downloads

Abstract

Swertia chirata is a medicinal plant studied for its ability to synthesize polyshaped gold nanoparticles (AuNP). The process of AuNP biosynthesis was studied using artificial neural networks (ANN) with different activation function on output node (logistic or linear) and different training algorithm (back propagation or Levenberg–Marquardt). The maximum biosynthesis was checked under the optimized condition of 17.24% leaf extract, pH 4.61, gold chloride concentration 4 mM and temperature 53.61 °C. A significant improvement in the model efficiency for predicting AuNP biosynthesis around 37.60%, in terms of root mean square error was obtained with the developed ANN-linear2 model, compared to the traditional response surface methodology.

Keywords

Swertia chirata Green synthesis Gold nanoparticles Modelling Artificial neural networks 

Abbreviations

A

Absorbance

ANN

Artificial neural network

AAPD

Average absolute percentage deviation

AuNP

Gold nanoparticles

IPD

Individual percentage deviation

RMSE

Root mean square error

R2

Coefficient of determination

RSM

Response surface methodology

x1

Leaf extract concentration

x2

pH

x3

Gold chloride concentration

x4

Temperature

Notes

Acknowledgement

Astray G. thanks Xunta de Galicia, Consellería de Cultura, Educación e Ordenación Universitaria, for his postdoctoral Grant B, POS-B/2016/001, K645 P.P.0000 421S 140.08.

References

  1. 1.
    S. Ahmed, M. Ahmad, B. L. Swami, and S. Ikram (2016). J. Adv. Res. 7, 17.CrossRefPubMedGoogle Scholar
  2. 2.
    P. Singh, Y. J. Kim, D. Zhang, and D. C. Yang (2016). Trends Biotechnol. 34, 588.CrossRefPubMedGoogle Scholar
  3. 3.
    M. Noruzi (2015). Bioprocess Biosyst. Eng. 38, 1.CrossRefPubMedGoogle Scholar
  4. 4.
    M. M. Poojary, P. Passamonti, and A. V. Adhikari (2016). BioNanoScience. 6, 110.CrossRefGoogle Scholar
  5. 5.
    K. J. Rao and S. Paria (2015). ACS Sustain. Chem. Eng. 3, 483.CrossRefGoogle Scholar
  6. 6.
    N. Saha and S. Dutta Gupta (2016). Synthesis, characterization and bioactivity of nanoparticles from medicinal plants, in M. Pathak and J. N. Govil (eds.), Recent Progress in Medicinal Plants (pp. 471–501). Studium Press, USA.Google Scholar
  7. 7.
    K. Saha, S. S. Agasti, C. Kim, X. Li, and V. M. Rotello (2012). Chem. Rev. 112, 2739.CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    J. F. Hainfeld, D. N. Slatkin, T. M. Focella, and H. M. Smilowitz (2006). Br. J. Radiol. 79, 248.CrossRefPubMedGoogle Scholar
  9. 9.
    A. Oluwasanmi, M. Malekigorji, S. Jones, A. Curtis, and C. Hoskins (2016). RSC Adv. 6, 95044.CrossRefGoogle Scholar
  10. 10.
    S. K. Balakrishnan and P. V. Kamat (2017). ACS Energy Lett. 2, 88.CrossRefGoogle Scholar
  11. 11.
    M. Bonarowska, Z. Kaszkur, G. Slowik, J. Ryczkowski, and Z. Karpinski (2016). ChemCatChem 8, 2625.CrossRefGoogle Scholar
  12. 12.
    T. Kubota, S. Kuroda, T. Morihiro, H. Tazawa, S. Kagawa, and T. Fujiwara (2016). Cancer Res. 76, 4747.CrossRefGoogle Scholar
  13. 13.
    P. Lin, F. Chai, R. Zhang, G. Xu, X. Fan, and X. Luo (2016). Microchim. Acta 183, 1235.CrossRefGoogle Scholar
  14. 14.
    M. Cordeiro, F. Ferreira Carlos, P. Pedrosa, A. Lopez, and P. Viana Baptista (2016). Diagnostics 6, 43.CrossRefPubMedCentralGoogle Scholar
  15. 15.
    E. Hao, G. C. Schatz, and J. T. Hupp (2004). J. Fluoresc. 14, 331.CrossRefPubMedGoogle Scholar
  16. 16.
    N. Saha, P. Trivedi, and S. Dutta Gupta (2016). J. Cluster Sci. 27, 1893.CrossRefGoogle Scholar
  17. 17.
    T. B. Devi and M. Ahmaruzzaman (2017). Chem. Eng. J. 317, 726.CrossRefGoogle Scholar
  18. 18.
    N. Saha and S. Dutta Gupta (2016). J. Cluster Sci. 27, 1419.CrossRefGoogle Scholar
  19. 19.
    M. Rahimi-Nasrabadi, S. M. Pourmortazavi, Z. Rezvani, K. Adib, and M. R. Ganjali (2015). Mater. Manuf. Process. 30, 34.CrossRefGoogle Scholar
  20. 20.
    M. Rohini, P. Reyes, S. Velumani, M. Latha, G. Oza, I. Becerril-Juarez, et al. (2015). Mater. Sci. Semicond. Process. 37, 151.CrossRefGoogle Scholar
  21. 21.
    D. Bas and I. H. Boyaci (2007). J. Food Eng. 78, 846.CrossRefGoogle Scholar
  22. 22.
    A. M. Akintunde, S. O. Ajala, and E. Betiku (2015). Ind. Crops Prod. 67, 387.CrossRefGoogle Scholar
  23. 23.
    G. Astray, B. Gullón, J. Labidi, and P. Gullón (2016). Ind. Crop. Prod. 92, 290.CrossRefGoogle Scholar
  24. 24.
    G. E. P. Box and K. B. Wilson (1951). J. R. Stat. Soc 13, 1.Google Scholar
  25. 25.
    M. J. Zhu, J. Yao, W. B. Wang, X. Q. Yin, W. Chen, and X. Y. Wu (2016). Desalin. Water Treat. 57, 15314.CrossRefGoogle Scholar
  26. 26.
    S. Ghosh, R. Chakraborty, A. Chatterjee, and U. Raychaudhuri (2014). J. Inst. Brew. 120, 550.Google Scholar
  27. 27.
    T. Kikhavani, S. N. Ashrafizadeh, and B. Van Der Bruggen (2014). J. Appl. Polym. Sci. 131, 39888.CrossRefGoogle Scholar
  28. 28.
    J. S. Min, S. O. Lee, M. I. Khan, D. G. Yim, K. H. Seol, M. Lee, et al. (2015). Lipids Health Dis. 14, 77.CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    M. Martínez, B. Gullón, R. Yáñez, J. L. Alonso, and J. C. Parajó (2009). J. Agric. Food Chem. 57, 5510.CrossRefPubMedGoogle Scholar
  30. 30.
    K. M. Desai, S. A. Survase, P. S. Saudagar, S. S. Lele, and R. S. Singhal (2008). Biochem. Eng. J. 41, 266.CrossRefGoogle Scholar
  31. 31.
    S. K. Ashan, M. A. Behnajady, N. Ziaeifar, and R. Khalilnezhad (2017). Neural Comput. Appl. 1, (29), 969.Google Scholar
  32. 32.
    Y. Huang (2009). Algorithms 2, 973.CrossRefGoogle Scholar
  33. 33.
    E. A. Perpetuo, D. N. Silva, I. R. Avanzi, L. H. Gracioso, M. P. G. Baltazar, and C. A. O. Nascimento (2012). Environ. Technol. 33, 1739.CrossRefPubMedGoogle Scholar
  34. 34.
    R. Hosseini Nia, M. Ghaedi, and A. M. Ghaedi (2014). J. Mol. Liq. 195, 219.CrossRefGoogle Scholar
  35. 35.
    K. Salehi, H. Daraei, P. Teymouri, B. Shahmoradi, and A. Maleki (2016). Desalin. Water Treat. 57, 22074.CrossRefGoogle Scholar
  36. 36.
    Y. Li, M. R. Abbaspour, P. V. Grootendorst, A. M. Rauth, and X. Y. Wu (2015). Eur. J. Pharm. Biopharm. 94, 170.CrossRefPubMedGoogle Scholar
  37. 37.
    J. X. Gao, X. F. Xu, K. X. Song, P. Q. Li, X. H. Guo, and R. H. Liu (2006). Chin. J. Aeronaut. 19, S36.CrossRefGoogle Scholar
  38. 38.
    T. Murashige and F. Skoog (1962). Physiol. Plant. 15, 473.CrossRefGoogle Scholar
  39. 39.
    D. Kriesel, A brief introduction to neural networks (2007). http://www.dkriesel.com. Accessed 20 Nov 2017.
  40. 40.
    G. Astray, J. F. Gálvez, J. C. Mejuto, O. A. Moldes, and I. Montoya (2013). J. Comput. Chem. 34, 355.CrossRefPubMedGoogle Scholar
  41. 41.
    G. Astray, B. Soto, D. Lopez, M. A. Iglesias, and J. C. Mejuto (2016). Water Sci. Technol. 73, 1756.CrossRefPubMedGoogle Scholar
  42. 42.
    G. Astray, M. Fernández-González, F. J. Rodríguez-Rajo, D. López, and J. C. Mejuto (2016). Sci. Total Environ. 548–549, 110.CrossRefPubMedGoogle Scholar
  43. 43.
    M. Hernández Suárez, G. Astray Dopazo, D. Larios López, and F. Espinosa (2015). PLoS ONE 10, e0128566.CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    V. Venkatasubramanian, R. Rengaswamy, S. N. Kavuri, and K. Yin (2003). Comput. Chem. Eng. 27, 327.CrossRefGoogle Scholar
  45. 45.
    K. Metaxiotis, A. Kagiannas, D. Askounis, and J. Psarras (2003). Energy Convers. Manag. 44, 1525.CrossRefGoogle Scholar
  46. 46.
    J. V. Tu (1996). J. Clin. Epidemiol. 49, 1225.CrossRefPubMedGoogle Scholar
  47. 47.
    A. Witek-Krowiak, K. Chojnacka, D. Podstawczyk, A. Dawiec, and K. Pokomeda (2014). Bioresour. Technol. 160, 150.CrossRefPubMedGoogle Scholar
  48. 48.
    A. Sharma, S. Kumari, P. Wongputtisin, M. J. R. Nout, and P. K. Sarkar (2015). J. Appl. Microbiol. 119, 162.CrossRefPubMedGoogle Scholar
  49. 49.
    M. Rakshit, A. Sharma, J. Saha, and P. K. Sarkar (2015). LWT Food Sci. Technol. 63, 814.CrossRefGoogle Scholar
  50. 50.
    Z. M. Lu, J. Y. Lei, H. Y. Xu, J. S. Shi, and Z. H. Xu (2011). Appl. Microbiol. Biotechnol. 92, 371.CrossRefPubMedGoogle Scholar
  51. 51.
    T. Guo, J. Q. Wei, Y. Wang, D. Su, Z. Zhang, and Y. L. Yao (2015). Adv. J. Food Sci. Technol. 7, 67.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Agricultural and Food EngineeringIndian Institute of Technology KharagpurKharagpurIndia
  2. 2.Department of Physical Chemistry, Faculty of ScienceUniversity of VigoOurenseSpain

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