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Surface and Size Effects in TGS, NaNO2, and DKDP Nanocrystals

Published online by Cambridge University Press:  21 March 2011

Juan D. Romero
Affiliation:
Department of Physics, University of Puerto Rico, San Juan PR 00931-3343
Luis F. Fonseca
Affiliation:
Department of Physics, University of Puerto Rico, San Juan PR 00931-3343
Rafael Ramos
Affiliation:
Department of Physics, University of Puerto Rico, Mayaguez PR 00681
Manuel I. Marqués
Affiliation:
Departamento de Física de Materiales C-IV. Universidad Autónoma de Madrid, Spain
Julio A. Gonzalo
Affiliation:
Departamento de Física de Materiales C-IV. Universidad Autónoma de Madrid, Spain
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Abstract

Monte Carlo simulations of some typical order-disorder ferroelectrics such as TGS, NaNO2 and DKDP nanocrystals were studied using a Transverse Ising Model Hamiltonian with four-spins interactions. The microscopic parameters corresponding to this Hamiltonian were adjusted to fit the experimental polarization-temperature curves for each one of the materials in the bulk phase. Then the dependences of the ferroelectric-paraelectric phase transition temperatures, Tc, on the sizes of those crystals were studied with Monte Carlo simulations of the order-disorder system. We report a weak dependence of Tc on the size of the crystal (d) for these materials above d∼6nm. The addition of surface effects showed that the expected lowtemperature shift of Tc due to size effects, can be reverted.

Type
Research Article
Copyright
Copyright © Materials Research Society 2001

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References

1. Jaccard, A., Känzig, W., and Peter, M.. Helv. Phys. Acta 26, 521 (1953).Google Scholar
2. Anliker, M., Brugger, H. R., and Känzig, W.. Helv. Phys. Acta 27, 99 (1954).Google Scholar
3. Kneikamp, H. and Heywang, W.. Zeit. Angew. Phys. 6, 385 (1954).Google Scholar
4. Shih, W. Y., Shih, W., and Aksay, I. A.. Phys. Rev. B50, 15575 (1994).10.1103/PhysRevB.50.15575Google Scholar
5. Handi, A. and Thomas, A.. Ferroelectrics 59, 221 (1984).Google Scholar
6. Batra, I. P. and Silverman, G. D.. Solid State Commum. 11, 291 (1972).10.1016/0038-1098(72)91180-5Google Scholar
7. Ishikawa, K., Yoshikawa, K., and Okada, N.. Phys. Rev. B37, 5852 (1988).10.1103/PhysRevB.37.5852Google Scholar
8. Uchino, K., Sadanaga, E., and Hirose, T.. J. Am. Ceram. Soc. 72, 1555 (1989).10.1111/j.1151-2916.1989.tb07706.xGoogle Scholar
9. Romero, J. and Fonseca, L. F.. Mat. Res. Soc. Symp. Proc. 493, 99 (1998).10.1557/PROC-493-99Google Scholar
10. Romero, J. and Fonseca, L. F.. Integrated Ferroelectrics 29, 149 (2000).10.1080/10584580008216682Google Scholar
11. Wang, Y. G., Zhong, W. L., and Zhang, P. L.. Phys. Rev. B53, 11439 (1996).10.1103/PhysRevB.53.11439Google Scholar
12. Gould, H. and Tobochnik, J., “Introduction to Computer Simulation Methods”. University of California, Berkeley (Oxford University Press, New York, 1987), p. 573583.Google Scholar
13. Hellwege, K. H., and Hellwege, A. M. (eds.). “Landolt-Bornstein numerical data and functional relationships in science and technology”.Vol. III/16b. Springer Verlag, 1982.Google Scholar
14. Hill, R. M. and Ichiqui, S. K.. Phys. Rev. 132, 1603 (1963).10.1103/PhysRev.132.1603Google Scholar
15. Sheshadri, K., Lahiri, R., Ayyub, P., Bhattacharya, S.. J. Phys: Conden. Matter 11, 2459 (1999).Google Scholar
16. Colla, E. V., Fokin, A. V., and Kumzerov, Y. A.. Solid State Commun. 103, 127 (1997).10.1016/S0038-1098(97)00132-4Google Scholar
17. Zhong, W. L., Wang, Y. G., Zhang, P. L., and Qu, B. D.. Phys. Rev. B50, 698 (1994).10.1103/PhysRevB.50.698Google Scholar