Microwave response characteristics and influencing factors of ores based on dielectric properties of synthetic samples

Abstract

In order to understand the influence of different factors on the microwave response characteristics of ores, the effects of electrical conductivity, metal mineral content, compactness, metal mineral distribution, microwave frequency and temperature on the dielectric properties of synthetic ores (metal mineral and quartz) were studied. Microwave heating tests were carried out on three types of natural ores (Hongtoushan copper ore, Sishanling iron ore and Dandong gold ore) with significant differences in metal mineral contents. The test results showed that under microwave irradiation, the stronger the electrical conductivity of the metal minerals, the smaller the penetration depth in synthetic ore. For those metal minerals with lower electrical conductivity, the microwave absorption coefficient of the synthetic samples increases with increasing metal mineral content. For those metal minerals with higher electrical conductivity, the microwave absorption coefficient of the samples first increases and then decreases as the metal mineral content increases. When the metal minerals are distributed in layers, the penetration depth is much less than that given a uniform distribution. The penetration depth in the sample at microwave frequency of 915 MHz is greater than that at 2.45 GHz. The higher the electrical conductivity of metal minerals used in synthetic ores, the higher the high-temperature sensitivity of electromagnetic shielding coefficient (0 °C–500 °C). The Hongtoushan copper ore with high metal mineral content exhibits obvious size effect. The effects of ore structure and crystal particle size on the distribution characteristics of microcracks were discussed. Based on the test results, a quantitative prediction model of microwave sensitivity of ore was proposed, which provides guidance for the prediction of ore heating effect and the selection of microwave heating sequence of ore.

Keywords

• Metal minerals
• Electrical conductivity
• Metal mineral content
• Synthetic ore
• Prediction model