|Kevin Cleary Wanta||-Department of Chemical Engineering, Faculty of Industrial Technology, Parahyangan Catholic University, Jl. Ciumbuleuit 94, Bandung, 40141, Indonesia - Department of Chemical Engineering, Faculty of|
|Widi Astuti||Research Unit for Mineral Technology, National Research and Innovation Agency (BRIN), Jl. Ir. Sutami Km. 15, Tanjung Bintang, 35361, Indonesia|
|Himawan Tri Bayu Murti Petrus||Department of Chemical Engineering, Faculty of Engineering, Universitas Gadjah Mada, Jl. Grafika 2, Bulaksumur, Yogyakarta, 55281, Indonesia|
|Indra Perdana||Department of Chemical Engineering, Faculty of Engineering, Universitas Gadjah Mada, Jl. Grafika 2, Bulaksumur, Yogyakarta, 55281, Indonesia|
This work studies the leaching kinetics of nickel laterite in a citric acid solution. A new kinetics model that considers a reversible chemical reaction and internal diffusion of a product is proposed. The experiment was conducted at various temperatures (303, 333, and 358 K) and particle sizes (< 70 to 250 ?m). Whereas acid concentration, pulp density, and leaching time were constant at 0.1 M, 20% w/v, and 120 min, respectively. The experimental results showed that the leaching process was dependent on temperature and particle size. In the case of Ni, Al, and Fe leachings, the formation of complex molecules might lead to a steric hindrance of product diffusion; however, this was not observable for Mg. The proposed model was found to be much better than the conventional shrinking core models (SCM). Using the proposed model, the activation energy for nickel was found to be 121.38 ± 0.0324 kJ/mol, 78.98 ± 0.4157 kJ/mol, 1,022.62 ± 9.6507 J/mol for forward reaction, backward reaction, and diffusion, respectively.
Citric acid; Diffusion model; Leaching kinetics; Nickel laterite; Shrinking core model
In extractive metallurgy, atmospheric pressure acid leaching (APAL) and bioleaching have been highlighted as options for recovering valuable metals, such as base metals and rare earth elements (Mirwan et al., 2017; Basuki et al., 2020; Trisnawati et al., 2020). These methods have been established and are ready for application on an industrial scale, especially if an intermediate product is preferable for further downstream applications (Rao et al., 2012; Ash et al., 2020). An in-depth study of leaching kinetics is essential to design process equipment for a better industrial-scale application.
Most studies have shown that leaching or bioleaching process kinetics can
be approached using the shrinking core model (SCM) (Ayanda
et al., 2011; Abilash et al., 2013; Dong et al., 2017; Wang et al., 2017).
The SCM is a kinetics model that explains the mechanism of heterogeneous
processes, especially for solid-gas reactions (Amiri
et al., 2014). The development of this model was mainly based on a
single step that controls the process (Wanta et al., 2016). As a heterogeneous process,
the leaching process might consist of a sequence of simultaneous steps. A
different assumption might result in a different model, which generates the question of whether the model could
explain the actual physical phenomenon. The most common models are derived on
the assumption that the kinetics are controlled by the reaction and/or
diffusion of the reactant entity (Su et al., 2010;
Ayanda et al., 2011; Gharabaghi et al., 2012; Astuti et al., 2016; Mashifana et
al., 2019); meanwhile, the limitation of the product entity is rarely
explained. Some studies on the leaching process have used inorganic and organic
leachates and shown inconsistent results, proving that SCMs would be insufficient to
describe the corresponding physical phenomena (Mirwan
et al., 2017; Setiawan et al., 2019; Wanta et al., 2020).
The kinetics model of the leaching process has become of interest, as the resulting information can be used for further process development and scale-up purposes. In a leaching process that involves organic acid leachates, there are two unique and different conditions: (1) the formation of metal-organic complex compounds (ligand) (Zelenin, 2007; Jean–Soro et al., 2012; Guilpain et al., 2018), which have a larger molecule size than that of inorganic acid leachates, and (2) reversible reactions associated with acid dissociation and product formation (see Equations 1 and 4) (Zelenin, 2007; Simate et al., 2010; Behera et al., 2011; Horeh et al., 2016). These two conditions can cause the failure of the existing SCM to explain the kinetics of the leaching process, which involves organic acid leachates. This study focuses on developing an alternative and novel mathematical model to describe the kinetics of the leaching process in which organic acid (citric acid solution) is used as a leachate. This model involves the steps that most probably control the leaching process with organic acid leachates: 1) product molecule internal diffusion and 2) reversible chemical reactions. This model is called the product diffusion-controlled model.
Figure 1 Illustration of the leaching mechanism controlled by the chemical reaction and diffusion of product molecules
The product diffusion-controlled model is arranged according to the mechanism of the leaching process using organic acid (citric acid in this work), as illustrated in Figure 1. Reactant molecules (white spheres in Figure 1a) diffuse through particle pores from the main liquid body. Since the pore size is much larger compared to the reactant molecule diameter, molecular diffusion-type transport is assumed to prevail in the pores. Reactant molecules are then adsorbed into the interior surface to form the adsorbed species (black spheres in Figure 1b), which are always assumed to be in an equilibrium phase. Chemical reactions occur on the solid surface (Figure 1c), as shown in Equations 1–4 (Simate et al., 2010; Behera et al., 2011; Prihutami et al., 2021):
Element M in Equation 3 consists of other metal elements, such as Fe, Mg, Al, and so on.
In the case of complex compounds formed as products (black parallelograms in Figure 1c), the adsorbed product molecules will desorb to produce liquid-like free molecules in the pore system (Figure 1d). The concentration of the free molecules is assumed to always be in equilibrium with that of the adsorbed molecules. The equilibrium can be expressed as follows Equations 5:
where H is a constant, xp is the concentration of the adsorbed product molecules (ppm), and Cp is the concentration of the free product molecules (ppm). The last step is the movement of product molecules (white parallelograms in Figure 1e) through the pores to the main liquid body. The movement is assumed to be due mainly to molecular diffusion.
In the present work, the proposed model was verified for the leaching of nickel laterite in a low concentration of citric acid. The leaching product of interest is a nickel compound. The development of the material balance for the leached nickel compound inside the solid particle results in Equations 6–8:
where xmo is the initial concentration of nickel in the solid phase. The low concentration of the citric acid solution used in this work allows the proposed model to be used for further application in the bioleaching process. The proposed model is expected to be more accurate for determining the kinetics parameters needed for further designing the scaled-up extractor.
This work presented a study to experimentally prove that the diffusion of products determines the rate of the leaching process of nickel laterite. In the case of leaching Ni, Al, and Fe from the mineral, the resulting products consisted of relatively large molecules, whose transport was sterically hindered in the pore channels. Meanwhile, leached Mg was present in ionic forms; hence, its transport through the pores did not determine the leaching process. The proposed mathematical model, considering the steps of reaction and transport of product molecules, was suitable for describing the Ni leaching process phenomenon. The model will be applicable to a similar process that incorporates large product molecules.
The authors gratefully acknowledge the Department of Chemical Engineering, Universitas Gadjah Mada, for assistance with the sample analysis. In addition, the authors acknowledge Research Unit for Mineral Technology, National Research and Innovation Agency (BRIN) for providing samples and chemical analysis.
|R1-CE-4641-20211004093548.docx||Docs File of Manuscript with Highlights and Annotations|
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