Iron is obtained from the primary ores hematite, magnetite, siderite and chamosite, among which the most abundant are hematite and magnetite. The iron extracted by beneficiation is mostly used to produce steel but a small amount of hematite is also used to manufacture dyes and pigments, as well as other magnetite-related products. The selection of the processes used in beneficiation depends upon the cost, the composition, the magnetic characteristics, and the source.
Magnetite is strongly magnetic, as is hematite, though relatively less so, and this enables the use of magnetic separators to extract iron from them. Further processing is carried out downstream to demagnetize the iron, ensuring that agglomerates do not persist, so that the next step, flotation, can be performed at an optimal rate for the removal of silica impurities and isolate as well as purify iron oxide.
Achieving Energy Efficiency
The cost of the production cycle is always among the most important factors in any process. In general, electric power demands are greatest for crushing the ore, grinding it and for magnetic separation, using about 70% of the power used. Ore sizing, screening and final classification are other processes that account for further costs. The items which cost the most during beneficiation are:
- Achieving a final particle size of minus 325 mesh or 45 microns, from particles about 0.4 m in diameter, by crushing and grinding them. This is typically carried out to achieve particles between 25 and 150 microns, varying with the country and the specific process chosen to separate these ores from silica and other impurities
- The grade of ore, as higher concentrations of iron are found in high-grade ore, lowering the overall cost of extraction and purification
This shows that if the particle size can be determined both before and after demagnetization, the readiness of the ore for conditioning in order to proceed to flotation can be assessed. Both size and shape can be analyzed to ramp up the efficiency of the process by avoiding or at least restricting the use of equipment that requires high power levels.
Moreover, the sensitivity of size and shape measurements directs the best use of energy. Diffraction for particle size determination has been adopted industry-wide. When DIA is added to the measurement, the tool becomes more comprehensive with respect to detecting the achievement of demagnetization and re-magnetization, as well as correct particle size. This leads to better energy utilization and reduction of the carbon footprint.
This article describes the benefits of using diffraction for particle size measurement simultaneously with image analysis to conserve energy. The use of combined measurements by two technologies with the same sample helps achieve correct decisions by avoiding errors due to lack of sample representation and imperfect sampling, and having to use multiple samples for different measurement techniques using different instruments.
The samples were treated both chemically and physically. This was because they dispersed well at first but showed a tendency to increase in size and form agglomerations again during the measurement process. The use of a magnetic field showed that the samples had magnetic characteristics.
The measurements were made over a short period to ensure that the particles had limited interaction and there was little opportunity for agglomeration and magnetic attraction. The graphical representation of the diffraction particle size distribution compares two samples of magnetite at different demagnetization periods.
The graph shows a size difference which proves the occurrence of demagnetization in the sample that is labeled “less magnetized”, which allows the process to proceed to the next step of flotation. The finer particles are seen on the left side of the curve due to what seems to be agglomeration, due to magnetic properties. This is because the curve itself has shifted to the right.
The point to be examined is whether the difference in size distribution is because of changes in magnetic properties or just because the particle size distribution itself has changed, as may occur if the sample was not a true representation of the whole batch, a constant issue in all analytic techniques. If proved that the difference is due to the magnetic shift, there is no need to repeat the sample processing and saving of costs.
The examination can be speeded up by microscopy, but this would entail the adoption of a third sample and increase the possibility of sampling issues, while it does not really solve the problem of why comparative data is different for the two samples. It is also not possible to examine very large samples using microscopy, which restricts the number of particles examined.
On the other hand, image analysis and diffraction can measure and describe at least 150,000 particles, which ensures the results are statistically valid. Demagnetization can be distinguished from deagglomeration due to other causes by combining these two measurements in the same cycle on the same sample. This experiment used the Microtrac Sync for this purpose, and the resulting information was detailed enough to allow specifications and quality control actions to be planned in a definite and assured manner. The figure below shows image analysis graphs showing size distribution based on the Da in the upper part, as compared to the diffraction-based distributions shown above.
The data on size distribution displayed below is obtained using different methods, diffraction and image analysis, with the same instrument, the Microtrac Sync, used for both, allowing the same sample to be tested under indistinguishable conditions.
The table below contains data which allows percentiles to be compared for the two samples labeled “More Magnetic” and “Less Magnetic”. The trends are similar for both methods, although the two samples show a small but clear difference. The comparability of both particle distribution reports indicates that they are accurate. The data yields similar values for size distributions, whether obtained by diffraction or image analysis.
Another parameter, Solidity, on the Sync image analysis data for the pair of samples, allows more quantification of the difference in morphology between them. When all particles with a Solidity value below 0.9 are searched for, the magnetic sample is found to be agglomerated as indicated by the higher volume percent.
Solidity is a measure of the roughness of the particle texture and is indicated by a value on the scale from 0 to 1, calculated by dividing the total area by the CHull area. Perfect smoothness is indicated by 1 and is accompanied by insignificant agglomeration, while a rough texture as in the present experiment indicates the presence of agglomeration, as the extreme surface irregularity is due to grouping of particles. The image shows part of the particles selected by the use of the search feature, for each of the samples.
In cases where demagnetization is decided to be adequate, final confirmation of agglomeration is obtained from the images. When a search is run for Solidity, for each of the samples, the “Less Magnetic” sample results in about 4% of the particles showing Solidity parameters below 0.9 compared to 10% of the sample volume being made up of “More Magnetic” particles with the same Solidity.
A large number of other particles are also detected by the search, but as their number exceeds 150,000, they cannot be shown. Particles with Solidity above 0.9 have a more even and smooth profile with less misshapen outlines. The third of the following diagrams shows the images resulting from this search.
Particle size distributions, along with particle imaging and shape analysis, can be used to direct the use of energy efficiently during ore processing and beneficiation. The Microtrac Sync combines particle size measurements with image analysis to yield particle values associated with measured parameters that can help specify the attainment of required particle sizes and magnetic properties.
Such tests help to limit energy expenditure to the minimum, and thus the carbon footprint as well. The use of both diffraction and imaging technologies to measure particle size and shape within the same sample under the same conditions at the same time allows a more comprehensive particle characterization.
The diffraction technique gives rapid and time-tested measurements of particle size which is complemented by the use of image analysis data. The near-impossibility of obtaining duplicate samples which are perfectly representative of the whole batch enhances the usefulness of this combination of simultaneous measurements on the same sample.
This information has been sourced, reviewed and adapted from materials provided by Microtrac, Inc.
For more information on this source, please visit Microtrac, Inc.