Chile produced 5.7 million metric tons of copper in 2021, making it the top global producer. Peru and China were the second and third largest producers, respectively, with 2.3 and 1.9 million tons [
1]. This production is reached in two ways: (i) concentration by flotation for copper sulfide ores and (ii) hydrometallurgic leaching, solvent extraction, and electrowinning for oxidized copper ores [
2,
3]. Chile also leads the production of copper through hydrometallurgy, reaching 1.4 million metric tons in 2022 [
4]. For oxidized copper ores, the most widely used method for processing consists of reducing the size of the ore, agglomeration and curing, heap leaching, solvent extraction, and electrowinning. Heap leaching is a widely used hydrometallurgical process within the mining industry. Due to its economic and environmental advantages, it has been considered a common treatment route for extracting low-grade ores. Given its significance, various investigations have been conducted to enhance its performance and predict the process outcomes. One approach has been to develop mathematical models that simulate heap leaching and can effectively demonstrate the effect of input variables on leaching performance. These models have revealed that choosing the appropriate input parameters can significantly impact leaching performance, highlighting the importance of careful consideration when optimizing the process [
5,
6]. In addition to the study of variables involved in the leaching phenomenon, efficiently optimizing costs is critical to leaching ores, mainly when dealing with low-grade ores. These pose various complexities that need to be appropriately addressed, and any deviations could result in significant implications. In this way, it is essential to balance the effects of the variables on metal recovery (and other process indicators) and the costs associated with the recovery of the metal [
7]. Heap leach pad irrigation involves various sub-processes such as advection, inter-particle diffusion, intra-particle diffusion, and chemical reactions [
8,
9]. Ore beds have heterogeneous hydrodynamic conditions, and dual porosity models have been developed to describe the flow. However, most leach models simplify the ore bed as a single phase governed by either advection or diffusion [
10,
11,
12].
On the other hand, before leaching copper oxide and secondary sulfide ores, acid curing and agglomeration techniques are commonly employed to enhance copper extraction. Agglomeration is the process of binding fine particles to coarser ones, which ultimately increases the permeability of an ore heap. On the other hand, acid curing inhibits the dissolution of certain silicates and accelerates the copper extraction process [
13,
14,
15]. Curing causes the sulfation of solid particles of copper ore with concentrated sulfuric acid, which promotes favorable conditions for leaching [
16,
17]. In curing, sulfation in leaching is an important process because preparing ores by sulfating the copper causes copper dissolution in a shorter time, increasing the extraction speed and decreasing the leaching cycle times. Today, this stage is always present in the leaching processes of oxidized copper minerals due to its proven effects, mainly in the early days of leaching kinetics.
Concerning pilot tests in columns, heap leach test work involve loading the ore into columns and irrigating it with a leach solution. Daily drainage solution measurements calculate metal extraction over time. Columns of the same height as commercial heaps in the lab are used to represent a small segment [
18]. This type of study is essential for scaling up from the laboratory to industrial applications. Column leaching tests are necessary to obtain relevant parameters and the effect of variables in a relevant environment [
19]. Gómez studied the oxidized copper recovery kinetics in column tests on a sample without sulfation and another with sulfuric acid. On day 1 of leaching, copper recovery reached 3.40% for the mineral sample without sulfation vs. 25.72% for the sulfated mineral sample. On day 3 of leaching, it was 19.75% vs. 41.46%, and on day 5, it was 33.32% vs. 48.95% [
20]. The mathematical modeling of columnar leaching is a helpful tool for predicting and evaluating the kinetics of copper extraction. There are two main models that describe this process: the Progressive Conversion Model and the Shrinking Core Model. However, the sulfation factor is not incorporated in any of them. The first model considers a porous spherical solid particle. It also considers that the mineralogical species present in the sample react with the acid continuously and progressively throughout the particle [
21]. The other model, the shrinking core model, better explains the behavior of mineral leaching processes that present relatively homogeneous mineralization and is widely used [
22,
23].