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Kinetic study of nanorods self-assembly process based on logistic function model

Yan Zhao Zhao Wen-Jing Wang Rong-Yao

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Kinetic study of nanorods self-assembly process based on logistic function model

Yan Zhao, Zhao Wen-Jing, Wang Rong-Yao
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  • Understanding the complicated kinetic process involved in nanoparticle self-assembly is of considerable importance for designing and fabricating functional nanostructures with desired properties. In this work, using the stopped-flow absorption technique, we investigate kinetic behaviors involved in gold nanorod assembly mediated by cysteine molecules. Further combining with SEM microstructural analyses of the assembly structure of gold nanorods, we establish the correlations between the kinetic parameter and the assembled structure. The dynamical surface plasmonic absorptions of gold nanorods are monitored during the formation of GNRs chains with different assembly rates. And the acquired kinetic data are analyzed in the frame of the second-order theoretical model, which has been widely used in the literature for linear assembly of gold nanorods. We find that the second-order theoretical model for describing the kinetic behaviors is merely limited to the case of slow assembly process of gold nanorods, but shows large deviation when the assembly process is relatively fast. We, therefore, propose in this work a new kinetic model on the basis of the logistic function, to make kinetic analyses for the different assembly rates of gold nanorods. Compared with the second-order theoretical model, this new logistic function model possesses an extended validity in describing the kinetic behaviors of both the slow and relatively fast nanorods assembly. Particularly, due to introduction of a new parameter, i.e., the exponential parameter p, the logistic function model enables a more accurate description of the kinetic behavior at a very earlier assembly stage (e.g., on a millisecond scale), in addition to quantifying the assembly rate T0. More importantly, the value of p derived from the new logistic function model allows us to establish the kinetics-structure relationship. The slow assembly process that produces mainly the one-dimensional linear chains of nanorods, is featured by the value of kinetic parameter p close to 1. By contrast, for the relatively fast assembly process that results in the formations of irregular zigzag chains even two-dimensional assembled structures of nanorods, the value of kinetic parameter approaches to 2. Furthermore, in the present study, the kinetic parameter p based on the logistic model might be related to the fractal dimension (Df) of the aggregated structures of the gold nanorods self-assembly processes. These results suggest that the logistic function model could provide the kinetic features for directly quantifying the fractal structures of the nanorods assembly. We believe that the new kinetic analysis method presented in this work could be helpful for an in-depth understanding of the kinetics-structure-property relationship in self-assembled plasmonic nanostructures.
      Corresponding author: Wang Rong-Yao, wangry@bit.edu.cn
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 11174033) and the Innovation Project of College Students, China (Grant No. 201410007069).
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    Titoo J, Renee R, Nini E, Reeler A, Tom V, Knud J J, Thomas B, Kasper N 2012 J. Colloid Interface Sci. 376 83

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    Xiang Y J, Wu X C, Liu D F, Jiang X Y, Chu W G, Li Z Y, Ma Y, Zhou W Y, Xie S S 2008 J. Phys. Chem. C 112 3203

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    Lim I S, Derrick M, Mark H 2009 Anal. Chem. 81 689

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    Zhai D W, Wang P, Wang R Y 2015 Nanoscale 7 10690

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    Joseph S T S, Ipe B I, Pramod P, Thomas K G 2006 J. Phys. Chem. B 110 150

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    Zajek K, Gorek A 2010 Food Bioprod. Process. 88 55

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    Roush W B, Branton S L 2005 Poult. Sci. 84 494

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    Huang X H, Neretina S, Mostafa A 2009 Adv. Mater. 21 4880

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    Chen H J, Shao L, Li Q, Wang J F 2013 Chem. Soc. Rev. 42 2679

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  • [1]

    Sharon G, Michael S 2007 Nat. Mater. 6 557

    [2]

    Ma Y Q, Zou X W, Liu J X, Ouyang Z C 2006 Introduction to Soft Matter Physics (Beijing: Peking University Press) pp305-415 (in Chinese) [马余强, 邹宪武, 刘寄星,欧阳钟灿 2006 软物质物理学导论 (北京: 北京大学出版社) 第305-415页]

    [3]

    Kyle M, Christopher W, Siowling S, Bartosz G 2009 Small 5 1600

    [4]

    Liu K, Nie Z H, Zhao N N, Li W, Rubinstein M, Eugenia K 2010 Science 329 197

    [5]

    Liu K, Ahmed A, Chung S, Sugikawa K, Wu G X, Nie Z H 2013 ACS Nano. 7 7

    [6]

    Lim I S, Mott D, Njoki P, Pan Y, Zhou S, Zhong C J 2008 Langmuir 24 8857

    [7]

    Wang Y L, DePrince A E, Stephen K G, Lin X M, Matthew P 2010 J. Phys. Chem. Lett. 1 2692

    [8]

    Abdennour A, Ramesh K, Tian L M, Srikanth S 2013 Langmuir 29 56

    [9]

    Zhang J, Ge Z, Jiang X, Hassan P, Liu S 2007 J. Colloid Interface Sci. 316 796

    [10]

    Titoo J, Renee R, Nini E, Reeler A, Tom V, Knud J J, Thomas B, Kasper N 2012 J. Colloid Interface Sci. 376 83

    [11]

    Xiang Y J, Wu X C, Liu D F, Jiang X Y, Chu W G, Li Z Y, Ma Y, Zhou W Y, Xie S S 2008 J. Phys. Chem. C 112 3203

    [12]

    Lim I S, Derrick M, Mark H 2009 Anal. Chem. 81 689

    [13]

    Zhai D W, Wang P, Wang R Y 2015 Nanoscale 7 10690

    [14]

    Joseph S T S, Ipe B I, Pramod P, Thomas K G 2006 J. Phys. Chem. B 110 150

    [15]

    Zajek K, Gorek A 2010 Food Bioprod. Process. 88 55

    [16]

    Roush W B, Branton S L 2005 Poult. Sci. 84 494

    [17]

    Huang X H, Neretina S, Mostafa A 2009 Adv. Mater. 21 4880

    [18]

    Chen H J, Shao L, Li Q, Wang J F 2013 Chem. Soc. Rev. 42 2679

    [19]

    Weitz D A, Huang J S, Lin M Y, Sung J 1985 Phys. Rev. Lett. 54 1416

    [20]

    Mohraz A, Moler D B, Ziff R M, Solomon M J 2004 Phys. Rev. Lett. 92 155503

    [21]

    Li F, Josephson D P, Stein A 2011 Angew Chem., Int. Edit. 50 360

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Publishing process
  • Received Date:  13 February 2016
  • Accepted Date:  05 April 2016
  • Published Online:  05 June 2016

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