Relationship between Ionic Conductivity and Composition of Li 2 O-ZrO 2 -SiO 2 Glasses Determined from Mixture Design. -SiO 2

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1 Journal of the Korean Ceramic Society Vol. 44, No. 4, pp. 19~3, 007. Relationship between Ionic Conductivity and Composition of Glasses Determined from Mixture Design Eun-Tae Kang, Myoung-Joong Kim,* and Jae-Dong Kim** Division of Nano & Advanced Materials Science and Engineering, Engineering Research Institute, Gyeongsang National University, Jinju , Korea *R&D center, Gonggan Ceramic Co., Ltd., Ansung , Korea **ATT Ltd., Ansan , Korea (Received March, 007; Accepted March 6, 007) yw z w k Á½ *Á½ ** w ù Á œw, w œw *œ» **ATT (007 3 ; ) ABSTRACT The ionic conductivity of glasses has been designed and analyzed on the basis of a mixture design experiment with constraints. Fitted models for the activation energy and the ionic conductivity are as follows: QkJmol ( ) = x x x x 1 x x x 3 logσ( 300K) = x x x x 1 x 3 The electrical properties are very sensitive to the ratio of O/SiO. The effect of is less than that of this ratio but component attributes to the reduction of the activation energy. The optimal composition for best ionic conduction based on these fitted models is 55 OÁ10 Á35SiO. Its activation energy and ionic conductivity at 300 K are kj/mol and Ω 1 Ácm 1, respectively. Key words : Experimental design, Mixture design, glass, Ionic conductivity, Optimal composition 1. p p š w ƒ w. p w, p x» ü pz k ƒ. w w» w wù r p 1) LIPON yd x k. ù RF rl w LIPON -3 +5¾ y k ùkü ³ w w»ƒ š. ) yd ̃ 1000ç Ω 1 cm ƒ v w, ƒ Ì w w. 3) Corresponding author : Eun-Tae Kang etkang gsnu.ac.kr Tel : Fax : p» Li ƒ + ƒw w ù, yw ü y. 4,5) ƒ w yw ü y w. Oliveria 6) 30 O 70SiO ƒ yw ü w k š šw. w Miyauchi 7) lithium silicate zirconia ƒƒ ƒ k š w. l d w, w š x ƒ ww ù, w m w z ƒ š. Mazurin 8,9) w š y w w m w ƒ š šw. x p q w» w w w m ƒ ƒ w x z w. x z 19

2 0 ká½ Á½ Fig. 1. Glass compositions determined by extreme vertices design. w yw z w - SiO q wš, y ww w ü ƒ w.. x x 10) Kitaigorodskii w 10 O 55, 0 14, 35 SiO 60(mol%). ù ww : 30 O 55, 0 14, 35 SiO 60. w yw z w Fig. 1 ƒx Õ 6, ü ƒx Õ 6 ƒx sww 13 w. Table 1 ùkü, y w. CO 3 (Aldrich, 99.99%), (Aldrich, 99.5%), SiO (junsei) w ƒ s w z, 1 yww e. e ƒ» 1400~1600 o C 1~1.5 w z, þƒ q w w. y q w 1µm j» ù ¾ w. r rl w z, HP 419A Impedance Analyzer w 5Hz~10MHz q 50 C¾ y gƒ o d w. d v x 11) fittingw w. 3. š d ü ùkü, σt = σ 0 exp( Q RT). Table 1 ƒ w, y y (Q) š ü 300 K ùkü. y y m q w» w z sƒw. x l 6 w, O,, SiO, ( O ), ( ), ( O ) m z fitw. t y y ( O ) y w 300 K ( O ) ( ) y w. wr z w Table 1. Glass Compositions Determined by DOE, Its Ionic Conduction Parameters (log σ 0 and Q) and Its Conductivities at 300 K O w wz SiO log σ 0 (Ω 1 cm 1 K) Q (kj/mol) Q pred (kj/mol) Log σ 300K Log σ 300K (pred.) Log σ 300K *

3 yw z w 1 Table. Estimated Regression Coefficients for Activation Energy Term Coef. SE Coef. T P VIF O * * * * SiO * * O S= R =96.7% R a =94.40% Coef.: Least square estimator of regression coefficient, T: Test statistic, P: p-value, VIF: variance inflation factor, s= MSE (error mean of squares), R p : predicted R, R a : adjusted R Table 3. Analysis of Variance for Activation Energy Source DF Seq SS Adj SS Adj MS F P Regression Linear Quadratic Residual error Total DF: Degrees of freedom, SS: Sum of squares, MS: Mean square, F: Test statistic, P: p-value» x 1, x, x 3 ƒ» O,, SiO. l d y y 300 K» Table ùkü. Table d d ew. Tables ~5 d z m t ùkü. z w ùkü R. y y 300 K w ƒ» 96.7% 99.18%. y y 300 K l ƒ» 96.7% 99.18%ƒ z w. v w w ƒ j R f, w m R w. d š w d w R w. y y 300 K w z ƒ» 94.40% 98.91% w š. z l dw w R d R y y 300 K w ƒ» 91.1% Table 4. Estimated Regression Coefficients for Ionic Conductivity at 300 K Term Coef. SE Coef. T P VIF O * * * * 7.66 SiO * * O S=0.098 R =99.18% R a =98.91% Table 5. Analysis of Variance for Conductivity at o C Source DF Seq SS Adj SS Adj MS F P Regression Linear Quadratic x x z fitting (pseudo) w, l z y g. z. QkJmol ( ) = x x x x 1 x x x Residual error Total logσ( 300K) = x x x x 1 x 3 Fig.. Cox response trace plots for (a) activation energy and (b) log σ at 300 K. 44«4y(007)

4 ká½ Á½ Fig. 3. Mixture contour plots for (a) activation energy and (b) log σ at 300 K %. fit de sƒ w 1) m VIF(variance inflation factor)ƒ. Marquardt VIFƒ 10 j deƒ š 13) w ù, Cornell j VIF z d e x ü d w ù d t x w j VIF w š w. y y 300 K w 10 w ù j š ù, (response trace) ùkü ù š ùkü š. t F wwš l p w z m w z w w. y y 300 K w z y y 300 K z ƒ w. Tables 3 5 α=0.05 w p 0.05 z w š. Fig. x» w ƒ e w. O SiO ƒ» j z ùkü w z ƒ j. w ƒ» w z ùký š. Fig. 3 y y 300 K š. Ow 65 mol% w š ƒ ƒ w p š dw, t ü x ƒ w w O w w p w š. z» p yw w w. w z yw D- y 14) w x ü w. 55 O 10 35SiO, y y 300K ƒ» kj/mol Ω 1 cm 1. d t w (desirability) d y y 300K ƒ» kj/mol Ω 1 cm 1. y d x ü û y y w. 4. w, 30 O 55, 0 14, 35 SiO 60 w p x z yw z w m w. y y 300 K z ù, m. z w m O SiO w p j w e w O SiO w p w» w. y mw d 55 O 10 35SiO, y y 300 K ƒ» kj/mol Ω 1 cm 1 d kj/mol Ω 1 cm 1 yw ew. w wz

5 yw z w 3 Acknowledgment 004 w w w. REFERENCES 1. J. B. Bates, N. J. Dudney, G. R. Gruzalski, R. A. Zuhr, A. Choudhury, C. F. Luck, and J. D. Roberston, Electrical Properties of Amorphous Lithium Electrolyte Thin Films, Solid State Ionics, (199).. P. Birke, W. F. Chu, and W. Weppner, Materials for Lithium Thin-Film Batteries for Application in Silicon Technology, Solid State Ionics, (1997). 3. S. J. Visco and M. Y. Chu, Protective Coatings for Negative Electrodes, U.S. Patent 6, 05, 094 (000). 4. M. Yoshiyagawa and M. Tomozawa, Electrical Properties of Rapidly Quenched Lithium-Silicate Glasses, J. de Phys., C (198). 5. M. Tatsumisago, K. Yoneda, N. Machida, and T. Minami, Ionic Conductivity of Rapidly Quenched Glasses with High Concentration of Lithium Ions, J. Non-Cryst. Solids, 95 & (1987). 6. A. P. Novaes de Oliveira, C. Leonelli, T. Manfredini, G. C. Pellacani, C. Ramis, M. Trombetta, and G. Busca, Properties of Glasses belonging to the System, Phys. Chem. Glasses, 39 [4] 13-1 (1998). 7. K. Miyauchi, K. Matsumoto, K. Kanehori, and T. Kudo, New Amorphous Thin Films Ion Conductive Solid Electrolyte, Solid State Ionics, 9& (1983). 8. O. V. Mazurin, M. V. Strel tsina, T. P. Shvaiko-Shvaik- Ovskaya, and A. O. Mazurina, Determination of the Most Probable Concentration Dependences of the Properties of Binary Glasses with the Use of the SciGlass Information System, Glass Physics and Chemistry, 9 [6] (003). 9. O. V. Mazurin, Glass Properties: Compliation, Evaluation, and Prediction, J. Non-Cryst. Solids, (005). 10. I. I. Kitaigorodskii, I. I., and G. A. Ellern, Research of the Glass Formations B Alkaline Zirconium Silicate Systems, Tr. Mosk. Khim. Teknol. Inst., (1966). 11. J. R. Macdonald, and J. A. Garber, Analysis of Impedance and Admittance Data for Solids and Liquids, J. Electrochem. Soc., 14 [7] (1977). 1. D. W. Marquardt, Generalized Inverses, Ridge Regression, Biased Linear Estimation and Nonlinear Estimation, Technometrics, (1970). 13. J. A. Cornell, Experimental with Mixture; pp. 481, Wiley- Interscience Publication, T. J. Mitchell, An Algorithm for Construction of Doptimal Experimental Designs, Technometrics, (1974). 44«4y(007)