A modeling approach for the purification of group III metals (Ga and In) by zone refining

Abstract

An “experimental friendly” model for zone refining process is proposed which predicts effective zone length in each refining passes that would lead to maximal solute removal, thereby leading to ultrapurification of the material for use in high-end electronic applications. The effectiveness of the model is experimentally tested and validated by purifying gallium from 4N (99.99%) to 6N5 (99.99995%) purity level at 30% yield and ∼6 N at 70% yield with respect to targeted metallic impurities such as, Zn, Cu, Al, Ca, Bi, Si, Pb, Ni, Mn, and Fe, as analyzed by inductively coupled plasma optical emission spectrometry, graphite furnace atomic absorption spectrometry, and high resolution inductively coupled plasma mass spectrometry techniques. The distribution coefficient (k) of all the targeted impurities, detected in the purified gallium, was found to be less than 1. By comparing the experimentally obtained axial concentration profiles with the theoretical calculations, the k values of some detected impurities, such as Ca and Al, are determined to be ∼0.8, Pb and Bi to be 0.7, Cu to be 0.65, and Fe to be 0.68, which prove the efficiency of the proposed model in reducing the concentration of these vulnerable impurities significantly. Following the model and as evidenced from the theoretical predictions, degradation of material purification containing a mixture of impurities having k less than as well as greater than 1 was elucidated experimentally by zone refining of 4N6 indium. Only a 40% yield of 5N6 indium was obtained, thereby highlighting the intricacies and problem areas in ultrapurification of these types of material.

Numerical study and experimental investigation of zone refining in ultra-high purification of gallium and its use in the growth of GaAs epitaxial layers

“…In our previous paper [6], we studied the total impurity concentration distribution for two types of materials. For the first type of material, we considered that every impurity in that material have ko1.…”

“…We also developed a zone refining process model describing effective zone length for each pass for the optimum removal of impurities [6]. In this paper we describe a further extension of the work for the optimization of other zone refining parameters, such as, molten zone travel rate, effect on the rate of stirring of the molten zone and the number of passes required for each impurity to reach the ultimate distribution at which no further reduction of impurity concentration take place.…”

“…To meet the stringent requirement of ultra-high pure materials, different crystal growth techniques were adopted, among which, zone refining technique was extensively and most successfully used for the ultra-purification of materials [2][3][4][5][6][7][8][9][10][11][12]. Zone refining, as described by Pfann, is used to reduce impurity density in materials to extremely low levels by establishing a molten zone in the material ingot, which is moved from one end of the same to the other end one or more times at controlled translation rate and temperature [13].…”

Characterization and Interpretation of the Aluminum Zone Refining through Infrared Thermographic Analysis

“…The purification takes place by redistributing the impurities at the freezing interface when one or a series of molten zone(s) move through a solid bar. Many experimental and theoretical investigations have been conducted in recent decades with focus on improving refining and/or production efficiencies [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. Two general categories, as characterized by different emphases, can be summarized from these investigations.…”

Production of High Purity Metals: A Review on Zone Refining Process

“…With the aim of maximizing the separation of impurities in the first half of the bar in each pass, Ho, et al [47] and Ghosh, et al [48] have conducted more practical optimization approaches, in which an optimal zone length is quantitatively evaluated in every single pass. The biggest difference between these two approaches was the dependence (in [47]) or independence (in [48]) of the optimum zone length from distribution coefficients of impurities. In contrast to the above mentioned works, Spim, et al [28] simulated a model of zone length adaption during different passes.…”