Publications
8 results found
Salinas-Farran L, Neethling SJ, 2023, Modelling the curing of agglomerated ores with comparison to micro-CT, Minerals Engineering, Vol: 202, ISSN: 0892-6875
Agglomeration and the associated curing process are critical as they both improve heap permeability and provide initial intimate contact between the leaching solution and the minerals. The evaporation of water from the agglomerate surface will drive liquid motion within agglomerates, redistributing dissolved species and increasing their concentration with the resultant potential for precipitation of previously dissolved species.Models have been proposed for the particle scale leach behaviour during the active irrigation phase of heap leaching, however no models currently exist for the leach behaviour during the curing process. The aim of this paper is therefore to propose and validate such a model by including important processes such as evaporation, unsaturated liquid transport, advective and diffusive transport of dissolved species, dissolution of mineral grains, and precipitation of species once saturation is reached.A set of small-scale column leaching tests were carried out, with the system being repeated scanned using X-ray Microtomography (micro-CT) over the course of the 65 day long curing experiments. Image analysis allowed the spatial distribution of both the initial mineral grains, as well as the precipitates to be tracked as a function of time. These were then used to demonstrate that the model captured the key features of the behaviour during the leaching process, as well as providing plausible ranges for the model parameters that could not be directly measured as input parameters.Both the model and the experiments showed that reprecipitation occurs preferentially towards the surface of the agglomerates. The model was also used to carry out a sensitivity analysis, with a key finding being that leach performance during curing improves with larger agglomerates and decreased evaporation rates. This is because of decreased loss of water. The particle size effect is the opposite of what would be expected during the subsequent leaching where mass transport in
Ouyang M, Guo Z, Salinas Farran L, et al., 2023, Co-Electrospin-Electrosprayed High Areal-Loading Sodium-Ion Battery Electrodes, 244th ECS Meeting
Salinas Farran L, Brownscombe W, Brito Parada P, 2022, Combining micro-CT and BSE/SEM to assess the surface exposure of antimony sulphide ores and estimate metallurgical performance, Process Mineralogy
Daemi SR, Tan C, Tranter TG, et al., 2022, Computer‐vision‐based approach to classify and quantify flaws in Li‐ion electrodes, small methods, Vol: 6, ISSN: 2366-9608
X-ray computed tomography (X-ray CT) is a non-destructive characterization technique that in recent years has been adopted to study the microstructure of battery electrodes. However, the often manual and laborious data analysis process hinders the extraction of useful metrics that can ultimately inform the mechanisms behind cycle life degradation. This work presents a novel approach that combines two convolutional neural networks to first locate and segment each particle in a nano-CT LiNiMnCoO2 (NMC) electrode dataset, and successively classifies each particle according to the presence of flaws or cracks within its internal structure. Metrics extracted from the computer vision segmentation are validated with respect to traditional threshold-based segmentation, confirming that flawed particles are correctly identified as single entities. Successively, slices from each particle are analyzed by a pre-trained classifier to detect the presence of flaws or cracks. The models are used to quantify microstructural evolution in uncycled and cycled NMC811 electrodes, as well as the number of flawed particles in a NMC622 electrode. As a proof-of-concept, a 3-phase segmentation is also presented, whereby each individual flaw is segmented as a separate pixel label. It is anticipated that this analysis pipeline will be widely used in the field of battery research and beyond.
Salinas-Farran L, Batchelor A, Neethling SJ, 2022, Multimodal assessment of the curing of agglomerated ores in the presence of chloride ions, Hydrometallurgy, Vol: 207, ISSN: 0304-386X
Agglomeration and subsequent curing are widely used as pre-treatment for ore prior to heap leaching as it both improve the permeability of the heap and brings leaching solution into close contact with the ore, initializing the leaching reactions. Despite its widespread use there have been limited studies into the processes occurring within the agglomerates over the curing process. In this study both destructive and non-destructive imaging techniques are used to assess both the physical and chemical changes occurring within the agglomerates as they cure.The SEM/EDX is one of the most popular imaging techniques for mineral samples. It can only be carried out once for a given sample due to its destructive preparation method but provides detailed mineralogical information. A complementary tool is X-ray Microtomography (XMT), which is non-destructive and can be used to image the same object multiple times over the course of the experiment. Its main limitation, though, is that the acquired images are of X-ray attenuation values and need to be independently assigned to different mineral classifications based on, for instance, the corresponding SEM images. Combining the ability of SEM/EDX measurements to identify different mineral phases with the 3D time resolved XMT measurements can thus produce superior results to those achievable using either of the modalities on their own.In this study, we propose a methodology for quantifying the formation and depletion of mineral components of agglomerates. These methodologies will be demonstrated in ores agglomerated using a combination of sulphuric acid and ferric sulphate as well as in samples in which sodium chloride is added to the agglomeration recipe. The curing process was tracked beyond the typical time scales used industrially, highlighting that the presence of chloride ions makes a substantial difference to the chemical and structural evolution of the sample. Over this curing process most of the observed leaching occurs dur
Salinas Farran L, Neethling S, 2021, Measuring and Modelling Agglomerate Performance using X-ray Micro Tomography, Hydroprocess
Salinas Farran L, Neethling S, 2020, Micro-CT-based assessment of the performance of agglomerated sulphide ores: The impact of long curing times and the addition of chloride ions, International Mineral Processing Congress
Salinas Farran L, Neethling S, 2019, Quantifying the effects of mass transport and mineralogy in the curing and leaching of agglomerated ores, Procemin-Geomet
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