Phase equilibria determination in complex slag systems

被引:45
作者
Jak, E. [1 ]
Hayes, P. [1 ]
机构
[1] Univ Queensland, Pyromet Res Ctr, Brisbane, Qld 4072, Australia
来源
TRANSACTIONS OF THE INSTITUTIONS OF MINING AND METALLURGY SECTION C-MINERAL PROCESSING AND EXTRACTIVE METALLURGY | 2008年 / 117卷 / 01期
关键词
Slags; Phase equilibria; Experimental techniques;
D O I
10.1179/174328508X272344
中图分类号
TD [矿业工程];
学科分类号
0819 ;
摘要
Despite the wealth of information available on phase equilibria of oxide systems, there remain many gaps and inconsistencies in the knowledge base. From an industry perspective, there is an ongoing need to adequately describe the phase chemistry of slag systems in order to optimise process performance and improve productivity. Since this chemical behaviour cannot be predicted from first principles it follows, there is also an ongoing need for accurate experimental data. The advancements made in recent years in the capabilities of sophisticated analytical and measurement equipment have made it possible to develop new experimental techniques for the direct determination of phase equilibria in low order and complex multicomponent slag systems. In addition, the development of powerful computer modelling tools makes it possible to provide more comprehensive descriptions of the phase chemistry, to present the information in a range of perspectives, and to critically analyse the various types of related thermodynamic and structural information available. This review provides an overview of the types of information that can be used to determine phase equilibria in slag systems, analyses the influence of uncertainty and the relative importance of these types of data, and describes the advantages and limitations of the various experimental techniques that can be employed to obtain this information. Examples of recent studies are provided that demonstrate how an integrated approach to the determination of phase equilibria in complex systems, involving the use of targeted experimental studies and systematic thermodynamic model development, can lead to a better utilisation of the current research capabilities and resources, and more accurate descriptions of these systems.
引用
收藏
页码:1 / 17
页数:17
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