Detection and analysis of arsenic-bearing particles in atmospheric dust using Mineral Liberation Analysis

Author(s):  
M Gasparon ◽  
I Delbem ◽  
M Elmes ◽  
V Ciminelli
2014 ◽  
Vol 123 (3) ◽  
pp. 184-189 ◽  
Author(s):  
Dirk Sandmann ◽  
Sabine Haser ◽  
Jens Gutzmer

Minerals ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 536 ◽  
Author(s):  
Sarbast Ahmad Hamid ◽  
Pura Alfonso ◽  
Josep Oliva ◽  
Hernan Anticoi ◽  
Eduard Guasch ◽  
...  

In this paper, the modeling of the liberation of scheelite is presented. A pattern of concentration experiments was performed to investigate the scheelite liberation and distribution density calculation procedure. In this work, one sample from a Mittersill tungsten ore was studied. This work describes a method for determining the downstream milling energy requirements for rod mill products based on a Bond mill test performance. The grade distribution of particles at a given size fraction was calculated using a predictive liberation model. The concentration behavior of these particles in size fractions was evaluated using batch concentrate tests. The recovery of particles in size/grade classes, image analysis using mineral liberation analysis (MLA), and function calculations were implemented for the modeling of the liberation. By describing the size, grade, and recovery data of particles in size/grade classes, a technique for the measurement of distribution functions was developed that relates beta distribution, a model for the function based on the incomplete beta function, and a solution to produce liberation modeling. It was shown that the predicted results agreed well with the observed results. With a procedure for measuring the liberation, it was possible to carry out the first experimental measurement of the beta distribution. This liberation/concentrate model has wide potential applications for metallurgy and plant design, where the liberation modeling is to be determined with the distribution density solution to the predictive mineral liberation function equation, which includes the liberation of ore samples and their liberation characteristics.


Minerals ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 262 ◽  
Author(s):  
Xiaosheng Yang ◽  
Hannu Tapani Makkonen ◽  
Lassi Pakkanen

Rare earth elements (REEs) are defined as lanthanides with Y and Sc. Rare earth occurrences including the REE-bearing phases and their distributions, measured by rare earth oxides (REOs), in the streams of processing a phosphate ore were determined by using MLA, the mineral liberation analysis and EPMA, the electron probe microanalysis. The process includes an apatite ore beneficiation by flotation and further processing of the beneficiation concentrate with sulfuric acid. Twenty-six, sixty-two and twelve percent of the total REOs (TREO) contents from the ore end up in the products of beneficiation tailings, phosphogypsum (PG) and phosphoric acid, respectively. Apatite, allanite, monazite and pyrochlore are identified as REE-bearing minerals in the beneficiation process. In the beneficiation tailings, the REEs are mainly distributed in monazite (10.3% TREO), apatite (5.9% TREO), allanite (5.4% TREO) and pyrochlore (4.3% TREO). Gypsum, monazite, apatite and other REE-bearing phases were found to host REEs in the PG and the REEs distributions are 44.9% TREO in gypsum, 15.8% TREO in monazite, 0.6% TREO in apatite and 0.6% TREO in other REE-bearing phases. Perspectives on the efficient recovery of REEs from the beneficiation tailings and the PG are discussed.


2018 ◽  
Vol 126 ◽  
pp. 74-81 ◽  
Author(s):  
Zhen Li ◽  
Yanhong Fu ◽  
Chao Yang ◽  
Wei Yu ◽  
Lijun Liu ◽  
...  

Minerals ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 527 ◽  
Author(s):  
Bernhard Schulz ◽  
Gerhard Merker ◽  
Jens Gutzmer

Many rare earth element (REE) deposits have experienced multistage geological enrichment processes resulting in REE bearing mineral assemblages of considerable complexity and variability. Automated scanning electron microscopy (SEM) mineral liberation analysis of such REE ores is confronted by the difficult assignment of energy-dispersive X-ray (EDX) spectra to REE mineral names. To overcome and bypass this problem, a generic and reliable labelling of EDX reference spectra obtained from REE-bearing minerals based on their contents of Si, Ca, F and P in a bulk normalised analysis is proposed. The labelled spectra are then combined into groups of REE-P (~monazite), REE-Ca-Si-P (~britholite), REE-Ca-F (~synchysite) and REE-F (~bastnaesite, parisite, fluocerite). Mixed spectra with low counts for REE from minute REE mineral grains are combined into a separate group. This classification scheme is applied to automated SEM mineral liberation analysis (MLA) data from beneficiation products by comminution and multistage flotation of REE carbonatite ores. Mineral modes, mineral grain size distribution, mineral liberation, mineral locking and mineral grade versus recovery curves based on the analysis of >200,000 particles in a sample can be recognised and interpreted in virtual grain size fractions. The approach as proposed here will allow future process mineralogical studies of REE deposits to be robust and comparable.


2011 ◽  
Vol 35 (4) ◽  
pp. 431-448 ◽  
Author(s):  
Hans-Eike Gäbler ◽  
Frank Melcher ◽  
Torsten Graupner ◽  
Andreas Bahr ◽  
Maria A. Sitnikova ◽  
...  

2019 ◽  
Vol 189 ◽  
pp. 105106 ◽  
Author(s):  
Oktay Celep ◽  
Ersin Y. Yazici ◽  
Pelin Altinkaya ◽  
Haci Deveci

2018 ◽  
Vol 66 ◽  
pp. 02002
Author(s):  
Joanna Pszonka ◽  
Dariusz Sala

The mineral liberation analysis setup (MLA) consists of a scanning electron microscope (SEM) - based backscattered electron (BSE) image with an energy dispersive X-ray system (EDX) for elemental analysis and a computer software that integrates images and X-ray identification of minerals and maps their distribution. Thereby, various quantitative and qualitative data sets are collected including grain size distribution and shape parameters such as aspect ratio, shape factor and angularity. Other techniques, e.g. the Gazzi-Dickinson point counting method or frequently questionable image analysis software to extract data for textural analysis are time consuming, strenuous and with limitations that need to be addressed. Significant productivity of the mineral liberation analysis provides statistical representation and thereby stringent arguments to detect and suggest some potential solving in uncertainty and complexity of the submarine gravity flows phenomenon that is extremely difficult to monitor, however volumetrically the most significant processes moving sediments on Earth. The mineral liberation analysis seems to be one of the most suitable method to acquire such data set.


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