Abstract
The temporal growth and aging of ZnO nanoparticles (NP's) in colloidal solution were investigated both experimentally and theoretically. UV–Vis spectroscopy revealed that the nucleation and growth of NP’s in solution occurs in less than 2 min. Transmission electron microscopy images depict the morphology of aggregated NP’s. In atomically balanced reaction (for sample S1), first growth takes place and then aging were observed. However, in the case of the atomically unbalanced reaction (for sample S2), decoupling of nucleation from growth was seen after 20 min. This result was confirmed by the slopes of dEg/dt (Eg = band gap) and dαmax/dt (αmax = absorption maximum) with time, which remains constant for sample S1 but shows abrupt decrease for sample S2 after 20 min. Thereafter, growth was found to be controlled by the diffusion and reaction parameters. The growth of NP’s was modelled using the phase-field model. The result from the current work reveals that the nucleation, growth and aging of NP’s occur in the atomically balanced reaction whereas decoupling of nucleation from growth happens in atomically unbalanced reaction.
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J. Zhang, C. Li, Y. Zhang, M. Yang, D. Jia, G. Liu, Y. Hou, R. Li, N. Zhang, Q. Wu, and H. Cao (2018). J. Clean. Prod. 193, 236–248. https://doi.org/10.1016/j.jclepro.2018.05.009.
M. Yang, C. Li, L. Luo, R. Li, and Y. Long (2021). Int. Commun. Heat Mass Transf. 125, 105317. https://doi.org/10.1016/j.icheatmasstransfer.2021.105317.
M. Yang, C. Li, Y. Zhang, D. Jia, R. Li, Y. Hou, and H. Cao (2019). Int. J. Adv. Manuf. Technol. 102, 2617–2632. https://doi.org/10.1007/s00170-019-03367-0.
M. Yang, C. Li, Y. Zhang, D. Jia, X. Zhang, Y. Hou, R. Li, and J. Wang (2017). Int. J. Mach. Tools Manuf. 122, 55–65. https://doi.org/10.1016/j.ijmachtools.2017.06.003.
S. Guo, C. Li, Y. Zhang, Y. Wang, B. Li, M. Yang, X. Zhang, and G. Liu (2017). J. Clean. Prod. 140, 1060–1076. https://doi.org/10.1016/j.jclepro.2016.10.073.
M. Yang, C. Li, Y. Zhang, D. Jia, R. Li, Y. Hou, H. Cao, and J. Wang (2019). Ceram. Int. 45, 14908–14920. https://doi.org/10.1016/j.ceramint.2019.04.226.
B. Li, C. Li, Y. Zhang, Y. Wang, D. Jia, and M. Yang (2016). Chin. J. Aeronaut. 29, 1084–1095. https://doi.org/10.1016/j.cja.2015.10.012.
K. Kaviyarasu, N. Geetha, K. Kanimozhi, C. Maria Magdalane, S. Sivaranjani, A. Ayeshamariam, J. Kennedy, and M. Maaza (2017). Mater. Sci. Eng. C. 74, 325–333. https://doi.org/10.1016/j.msec.2016.12.024.
K. Kaviyarasu, C. Maria Magdalane, K. Kanimozhi, J. Kennedy, B. Siddhardha, E. Subba Reddy, N. K. Rotte, C. S. Sharma, F. T. Thema, D. Letsholathebe, G. T. Mola, and M. Maaza (2017). J. Photochem. Photobiol. B Biol. 173, 466–475. https://doi.org/10.1016/j.jphotobiol.2017.06.026.
J. Kennedy, A. Markwitz, Z. Li, W. Gao, C. Kendrick, S. M. Durbin, and R. Reeves (2006). Curr. Appl. Phys. 6, 495–498. https://doi.org/10.1016/j.cap.2005.11.046.
J. Kennedy, P. P. Murmu, E. Manikandan, and S. Y. Lee (2014). J. Alloys Compd. 616, 614–617. https://doi.org/10.1016/j.jallcom.2014.07.179.
J. Kennedy, P. P. Murmu, J. Leveneur, A. Markwitz, and J. Futter (2016). Appl. Surf. Sci. 367, 52–58. https://doi.org/10.1016/j.apsusc.2016.01.160.
K. Davis, R. Yarbrough, M. Froeschle, J. White, and H. Rathnayake (2019). RSC Adv. 9, 14638–14648. https://doi.org/10.1039/c9ra02091h.
T. E. P. Alves, C. Kolodziej, C. Burda, and A. Franco (2018). Mater. Des. 146, 125–133. https://doi.org/10.1016/j.matdes.2018.03.013.
T. Udayabhaskararao, M. Kazes, L. Houben, H. Lin, and D. Oron (2017). Chem. Mater. 29, 1302–1308. https://doi.org/10.1021/acs.chemmater.6b04841.
M. Herbst and E. Hofmann (2019). ACS 35, 11702–11709. https://doi.org/10.1021/acs.langmuir.9b01149.
P. Montero De Hijes, J. R. Espinosa, E. Sanz, and C. Vega (2019). J. Chem. Phys. 151, 144501. https://doi.org/10.1063/1.5121026.
L. Qu, W. W. Yu, and X. Peng (2004). Nano Lett. 4, 465–469. https://doi.org/10.1021/nl035211r.
E. C. Vreeland, J. Watt, G. B. Schober, B. G. Hance, M. J. Austin, A. D. Price, B. D. Fellows, T. C. Monson, N. S. Hudak, L. Maldonado-Camargo, A. C. Bohorquez, C. Rinaldi, and D. L. Huber (2015). Chem. Mater. 27, 6059–6066. https://doi.org/10.1021/acs.chemmater.5b02510.
G. S. Redner, C. G. Wagner, A. Baskaran, and M. F. Hagan (2016). Phys. Rev. Lett. 117, 1–7. https://doi.org/10.1103/PhysRevLett.117.148002.
D. V. Alexandrov and I. V. Alexandrova (2020). Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 378, 20190247. https://doi.org/10.1098/rsta.2019.0247.
M. Yang and L. Wang (2021). Npj Comput Mater. https://doi.org/10.1038/s41524-021-00524-6.
L. Gránásy, F. Podmaniczky, G. I. Tóth, G. Tegze, and T. Puszta (2014). Chem. Soc. Rev. 43, 2159–2173. https://doi.org/10.1039/C3CS60225G.
K. Chockalingam, V. G. Kouznetsova, O. Van Der Sluis, and M. G. D. Geers (2016). Comput. Methods Appl. Mech. Engrg. 312, 492–508. https://doi.org/10.1016/j.cma.2016.07.002.
T. Q. Ansari (2021). Npj Comput Mater. https://doi.org/10.1038/s41524-021-00612-7.
A. G. Vega-Poot, G. Rodríguez-Gattorno, O. E. Soberanis-Domínguez, R. T. Patiño-Díaz, M. Espinosa-Pesqueira, and G. Oskam (2010). Nanoscale. 2, 2710–2717. https://doi.org/10.1039/c0nr00439a.
C. Lizandara-Pueyo, M. W. E. Van Den Berg, A. De Toni, T. Goes, and S. Polarz (2008). J. Am. Chem. Soc. 130, 16601–16610. https://doi.org/10.1021/ja804071h.
S. Repp and E. Erdem (2016). Spectrochim. Acta Part A Mol. Biomol. Spectrosc. 152, 637–644. https://doi.org/10.1016/j.saa.2015.01.110.
D. Valiente, S. F. de Avila, F. Rodríguez-Mas, J. C. Ferrer, and J. L. Alonso (2020). Cryst. MDPI. 10, 226. https://doi.org/10.3390/cryst10030226.
A. V. Shapovalov and V. V. Obukhov (2018). Symmetry (Basel). 10, 53. https://doi.org/10.3390/SYM10030053.
C. Valla (2017). Nonlinear Anal. Real World Appl. 36, 249–266. https://doi.org/10.1016/j.nonrwa.2017.01.013.
S. Meng, A. Zhang, Z. Guo, and Q. Wang (2020). Comput. Mater. Sci. 184, 109784. https://doi.org/10.1016/j.commatsci.2020.109784.
S. Sakane, T. Takaki, R. Rojas, M. Ohno, Y. Shibuta, T. Shimokawabe, and T. Aoki (2017). J. Cryst. Growth. 474, 154–159. https://doi.org/10.1016/j.jcrysgro.2016.11.103.
X. Yang and J. Zhao (2019). Comput. Phys. Commun. 235, 234–245. https://doi.org/10.1016/j.cpc.2018.08.012.
S. B. Biner, Programming Phase-Field Modeling. (Springer International Publishing, Cham, 2017), pp. 156–168. https://doi.org/10.1007/978-3-319-41196-5. .
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The authors would like to thank the Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh, India for financial and infrastructural support for current work.
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Sharma, P., Tiwari, S.K. & Barman, P.B. Temporal Growth and Aging of ZnO Nanoparticles in Colloidal Solution: Phase Field Model. J Clust Sci 34, 1381–1389 (2023). https://doi.org/10.1007/s10876-022-02309-3
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DOI: https://doi.org/10.1007/s10876-022-02309-3