手法を比較

	スラグ塩基度	エリンガム線図	収縮コアモデル
分野	鉱山工学	鉱山工学	鉱山工学
系統	Process / pipeline	Process / pipeline	Process / pipeline
提唱年	1950	1944	1976
提唱者	Pyrometallurgical Practice	Harold Jeffrey Torreyson Ellingham	Szekely, Evans, and Sohn
種類	Slag composition parameter for controlling roast/smelt conditions	Gibbs free energy diagram for high-temperature reactions	Reaction kinetics model for solid-fluid reactions
原典	Barnes, J. F., Edwards, C. C., & Sims, R. L. (2010). Copper smelting and refining: pyrometallurgical fundamentals. JOM, 52(12), 38-43.	Ellingham, H. J. T. (1944). Reducibility of oxides and sulfides. Journal of the Society of Chemical Industry, 63(5), 125-160.	Szekely, J., Evans, J. W., & Sohn, H. Y. (1976). Gas-solid reactions. Academic Press, New York.
別名	Basicity Index, Slag Chemistry Parameter	Gibbs Free Energy Diagram, High-Temperature Reduction Diagram	Shrinking Unreacted Core Model, SCM, Leaching Kinetics Model
関連	3	3	3
概要	Slag basicity is a measure of the composition of slag formed during smelting and roasting operations. It is typically expressed as the ratio of basic oxides (CaO, MgO) to acidic oxides (SiO2). Basicity controls slag fluidity, viscosity, and reactivity, directly affecting metal recovery, processing temperature, and product quality. It is a critical parameter in copper, nickel, and lead smelting.	The Ellingham Diagram, introduced by Harold Ellingham in 1944, is a graphical representation of the Gibbs free energy change for oxide formation and reduction as a function of temperature. It is an essential tool for predicting the thermodynamic feasibility of ore reduction and selecting appropriate reducing agents and temperatures for smelting and roasting operations.	The Shrinking Core Model, formalized by Szekely, Evans, and Sohn in 1976, describes the kinetics of chemical reactions between solid ore particles and surrounding fluids (leaching solutions, roasting gases). As the reaction proceeds from the particle surface inward, an unreacted core shrinks while products accumulate in a product layer. The model enables prediction of leaching times and optimization of hydrometallurgical processes.