Sains Malaysian 36(2): 189-194 (2007)

Analisis Kuantitatif Aluminium (III) Menggunakan Reagen

Alizarin Red S dan Jaringan Neural Tiruan (ANN)

(Quantitative  Analysis of Aluminium (III) Ion Using Alizarin

Red Sand Artificial Neural Network )

Nurul Izzaty Hassan & Musa Ahmad

Pusat Pengajian Sains Kimia dan Teknologi Makanan

Fakulti Sains dan Teknologi, Universiti Kebangsaan Malaysia

43600 UKM Bangi, Selangor D.E., Malaysia

Diserahkan: 10 Januari 2007 / Diterima: 2 Mac 2007

ABSTRAK

Analisis kuantitatif untuk penentuan kepekatan ion Al³⁺ dalam larutan akueus telah dilakukan menggunakan reagen alizarin red S (ARS) melalui pembentukan kompleks ARS-Al(III) yang dianalisis menggunakan kaedah spektrofotometri UL-Nampak. Kompleks ARS-Al(III) memberikan puncak serapan pada panjang gelombang 484 nm pada pH 5. Kajian kestabilan foto bagi reagen ARS memberikan nilai RSD sebanyak 0.46 %. Analisis kebolehulangan memberikan nilai RSD sebanyak 1.07 % dan 0.67 % masing-masingnya bagi kepekatan Al(III) 0.2 ppm dan 9 ppm. Gangguan kation Cu²⁺ dan Fe³⁺ pada nisbah mol 1:10 adalah minimum. Kebanyakan anion penggangu tidak memberikan kesan gangguan kecuali F^- pada nisbah mol 1:1 dan 1:10. Sistem ini memberikan julat kepekatan dinamik Al³⁺ antara 0.1 – 1.0 ppm. Arkitektur ANN dengan bilangan neuron terlindung, bilangan kitaran dan kadar pembelajaran adalah masing-masingnya 23, 40000 dan 0.001 telah berjaya memanjangkan julat dinamik kepekatan Al(III) daripada 0.1 – 8.0 ppm. Reagen ARS berjaya dipegunkan  pada permukaan ko-polimer XAD 4 dan mampu memberikan respon optik yang baik terhadap ion Al³⁺.

Kata kunci : Alizarin red S; aluminium; jaringan neural tiruan

ABSTRACT

A quantitative analysis  for determination of Al³⁺ concentration in aqueous solution has been carried out using alizarin red S (ARS) as a reagent to form ARS-Al(III) complex. The analysis was conducted using UV-Vis spectrophotometry method. ARS-Al(III) complex showed a maximum absorption peak at wavelength of 484 nm and optimum pH 5. The photostability study showed a RSD value of 0.46 %. The repeatability study at two different concentrations of 0.2 ppm and 9 ppm was found to give RSD values of 1.07 % and 0.67 %, respectively. Cu²⁺ and Fe³⁺ cations at the ratio of 1:10 slightly interfered. The study showed a low interfering effect for almost all of the interfering anions except for F^- at the ratio of 1:1 and 1:10. This system was found to give dynamic Al³⁺ concentration range of  0.1 – 1.0 ppm. ANN architectur with 23 hidden neurons, 40000 epochs and training rate of 0.001 has successfully extended the dynamic range of Al³⁺ concentration from 0.1 – 8.0 ppm. ARS reagent was successfully immobilized onto XAD 4 and showed a good optical response toward Al³⁺ ion.

Keywords :  Alizarin red S; aluminium; artificial neural network

REFERENCES/RUJUKAN

Cirovic, D.A. 1997. Feed-forward artificial neural networks :application to spectroscopy Trends in Analytical Chemistry  16: 148-155.

Crabtree, R.H. 2001. The organometallic chemistry of the transition metals. Ed. Ke-3. New York: John Wiley & Sons. Inc.

Despagne, F. & Massart, D.L. (1998). Neural networks in multivariate calibration, Analyst 123 :157R-178R.

Gasteiger, J. & Zupan, J. 1993. Neural network for Chemists: An introduction, VCH, New York.

Marczenko, Z. 1986. Separation and spectrophotometric determination of elements. New York: John Wiley & Sons. Inc.

Musa Ahmad & Narayanaswamy, R. 1995. Development of an optical fibre Al(III) sensor based on immobilized chrome azurol S. Talanta 42: 1337-1344.

Musa Ahmad & Narayanaswamy, R. 1995. A flow-cell optosensor for monitoring aluminium (III) based on immobilised eriochrome cyanine R (ECR) and reflectance spectrophotometry. The Science of The Total Environment 163 : 221-227.

Robert, C.W. 1972. Handbook of chemistry and physics. Ed. Ke-53. Cranwood Parkway: The Chemical Rubber Co.