Effect of Leaching of Ionic Rare Earth Ores on the Permeability Coefficient of Mineral Soil and Its Correlation with the State Parameter

Abstract

The permeability of ionic rare is a crucial factor influencing the leaching rate of rare earth elements. In the Gannan region, many ionic rare earth ores exhibit poor permeability and high compressibility compared to sandy soils. The permeability coefficient is a key indicator of the hydraulic performance of these ores. Thus, this study investigates the permeability coefficients of ionic rare earth ores with varying fines contents during the leaching process, with a specific focus on analyzing the impact of fines on permeability performance. To provide a comprehensive assessment of the influence of fines, we prepared ionic rare earth ore samples with fines contents of 5%, 10%, 15%, 20%, 25%, and 30%, ensuring that the overall particle size distributions remained consistent with the original gradation. A constant head permeability test was employed to measure the permeability coefficients of these ore samples throughout the leaching process. We specifically examined how varying fines contents influenced permeability across the upper, middle, and lower layers of the ore body, as well as the overall permeability when subjected to both distilled water and magnesium sulfate solutions. To further elucidate the differences in permeability performance among the various rare earth ore samples, we performed a data fitting analysis of the initial permeability coefficients against fines content, uniformity coefficient, average particle diameter, and void ratio. This analysis aims to quantify the fines effect across different rare earth ores and establish correlations among state parameters, such as fines content, and the initial permeability coefficient.

1. Introduction

The permeability of ionic rare earth elements is a critical factor in determining their leaching rate. The permeability coefficient serves as an essential index for characterizing the permeability during the leaching process of ore bodies. This coefficient not only influences the leaching rate of rare earth ions and the recovery rate of cations in the leaching solution but also significantly affects the stability of the ore body.

During leaching, changes in pore structure, migration of micro-particles, and movement of rare earth ions can substantially impact the permeability coefficient [1]. The researchers conducted permeability experiments on sandy soil with different fine-grain content using a conventional permeameter as the experimental object and found that the overall permeability coefficient of sandy soil decreased continuously with the increase in fine-grain content in rare earth ores [2]. Other researchers performed permeability experiments on three types of fully weathered coarse-grained granite soils with varying fine-grain contents and found that ammonium sulfate solution had a greater and more pronounced effect on the permeability of the rare earth ores compared to water leaching [3]. Additionally, a group of researchers focused on ionic rare earths as the experimental subject, employing ammonium sulfate as the leaching agent. They carried out indoor column leaching experiments to study the variation of the permeability coefficient of both raw and screened samples during the leaching process with an ammonium sulfate solution. Their results indicated that during leaching, there was migration of microscopic soil particles as well as migration of ions, with the effects of these migratory behaviors on the permeability coefficient of the ore body being opposite [4]. Another set of researchers utilized a variable head permeability device to conduct permeation experiments, studying the permeability characteristics of six groups of rare earth ores with different grade ratios. They discovered that the permeability coefficient of rare earth ores with different particle grades varied significantly, with porosity and permeability coefficients showing “exponential” changes. The mechanism behind this result was analyzed, concluding that when the pore space of rare earth minerals was small, bound water occupying more effective pores had a pronounced blocking effect on the leaching solution, thereby affecting the permeability performance of rare earth minerals [5]. Furthermore, researchers studying ionic rare earths selected various concentrations of soluble leaching solutions for indoor column leaching experiments and found that an increase in the concentration of the leaching solution led to an increase in the permeability coefficient of rare earths [6]. Another group conducted indoor infiltration experiments using fine-grained graded soils, demonstrating that the variation range of the infiltration coefficient was closely related to the ionic concentration in the soil pore space and the potential on the surface of soil microparticles, influenced by the microelectric field [7]. The permeability coefficients of rare earth ores with different fine-grain contents exhibit complex variation patterns during the leaching process. This characteristic has profound implications for the efficiency and quality of leaching operations. A thorough study of the changes in permeability coefficients of rare earth ores with varying fine-grain contents during leaching can aid in optimizing leaching processes, thereby enhancing the extraction efficiency and recovery rate of rare earth resources [8].

In this study, samples of rare earth minerals with fine particle contents of 5%, 10%, 15%, 20%, 25%, and 30% were prepared, along with other particle size ranges similar to the cumulative grading curves of original particles. Infiltration experiments were conducted using water and magnesium sulfate solutions to determine the overall and stratified (upper, middle, and lower) permeability coefficients during the column leaching process [9]. Data fitting was employed to analyze state parameters and initial permeability coefficients.

2. Materials and Methods

2.1. Properties of Experimental Materials

The rare earth samples for all the experiments were taken from a rare earth mine in Dingnan County, Jiangxi Province, China. In order to obtain the basic physical parameters of the mine more accurately, the samples for this experiment were taken from three different ore blocks in the mine without in-situ leaching, with a sampling depth of 2~3 m. The sampling type was divided into in-situ soil samples and bulk soil samples. The sampling type was divided into in-situ soil samples and bulk soil samples. After the sampling location was selected, the surface decayed layer was plowed away first, and then a 16 cm diameter Luoyang shovel was used to drill holes to a position of 2~3 m. A number of bulk natural mineral soils were bagged and packaged, and a number of ring-knife samples were taken by the ring-knife method and sealed with plastic wrap [10]. The final step is to determine the moisture content, density, particle specific gravity, particle gradation, void ratio, and porosity of the soil sample in the laboratory. XRD (Empyream PANalytical) patterns can be seen in Figure 1.

Table 1. Physical parameters of ionic rare earth ores.

Parameter Type	Value
moisture content (%)	20.47
dry density (g/cm3)	1.35
specific gravity of particles	2.70
porosity ratio	0.995
porosity (%)	49.87

shows the basic physical parameters of rare earth minerals,

Table 2. Percentage of each particle size of mineral soil.

Particle Size (mm)	>5	5~2	2~1	1~0.5	0.5~0.25	0.25~0.075	<0.075
percentage content (%)	5	24	15	18	15	10	13

presents the percentage content of various particle sizes in the ore soil, and

Table 3. Oxide content of mineral soil.

Oxide	Na2O	MgO	AL2O3	SiO2	SO3	K2O	CaO
Content (%)	0.146	0.127	34.975	48.251	0.029	1.847	0.098
Oxide	TiO2	MnO	Fe2O3	NiO	ZnO	Ga2O3	Rb2O
Content (%)	0.037	0.080	1.994	0.004	0.019	0.009	0.041
Oxide	Y2O3	ZrO2	Nd2O3	Yb2O3	WO3	PbO	ThO2
Content (%)	0.097	0.028	0.031	0.014	0.007	0.041	0.007

lists the oxide content in the ore soil.

2.2. Experimental Process

Sample preparation: The rare earth sample was reshaped according to the physical properties of the original material. After drying and sieving, the raw ore particles were classified into the following size fractions: 10–5 mm, 5–2 mm, 2–1 mm, 1–0.5 mm, 0.5–0.25 mm, 0.25–0.075 mm, and <0.075 mm [11]. Each fraction was stored separately. Rare earth samples with fine particle contents (as a percentage of total sample mass) of 5%, 10%, 15%, 20%, 25%, and 30% were prepared by mixing these fractions in proportions that mimic the coarse grain distribution of the raw ore soil [12]. These experimental soils are denoted as FC₀₅, FC₁₀, FC₁₅, FC₂₀, FC₂₅, and FC₃₀, where “FC” stands for fines content and the number represents the specific percentage. The basic physical properties of rare earth minerals with varying fine particle content are summarized in

Table 4. Basic physical properties of rare earth minerals with different fines content.

Fines Content (%)	Pore Ratio (e)	Average Particle Size D50 (mm)	Curvature Coefficient Cc	Coefficient of Inhomogeneity Cu
5	0.97	0.87	0.93	9.15
10	1.06	0.80	1.13	12.20
15	1.23	0.79	3.59	45.41
20	1.31	0.72	3.84	53.93
25	1.37	0.65	2.42	60.29
30	1.45	0.55	0.77	63.12

.

Loading sample: The experimental setup primarily consists of a transparent PVC cylinder (diameter 110 mm), pressure measuring tubes, a plastic base plate, and a liquid supply system. The cylinder has openings at the bottom, sides, and top for drainage, overflow, and installation of pressure measuring tubes, respectively. The base plate and pressure measuring tubes are sealed with hot melt adhesive to ensure the air-tightness required for the permeability test. The dimensions and structure of the experimental device are detailed in Figure 2. For each fine particle content, approximately 3–4 kg of rare earth samples were weighed accurately to 1.0 g. Based on the natural moisture content of the raw ore, the samples were mixed with water and placed in sealed bags for 24 h to ensure uniform moisture distribution. During loading, to prevent the loss of fine particles, a 20 mm thick layer of coarse sand (particle size 10 mm) was added to the base plate as a transition layer [13]. Subsequently, a 2566 g sample was divided into six equal portions of 427.7 g each and loaded into the PVC cylinder. Each layer was gently compacted with a wooden hammer until it reached a thickness of 3 cm. To avoid distinct layering, the surface of the soil sample was treated with a “hair” texture before adding the next layer. After loading, a layer of qualitative filter paper was placed on top as a buffer layer [14].

The entire rare earth permeability experiment was divided into two groups: a water group and a magnesium sulfate solution group. Each group of experiments was independently repeated three times. The data is presented as mean ± standard error. Experimental errors mainly arise from minor variations in sample preparation and measurement precision of the instruments. Each rare earth sample’s leaching experiment consisted of two stages. In the first stage, the sample was saturated by slowly injecting water from the bottom outlet, displacing air from the bottom to the top. Once saturation was achieved, the second stage commenced, during which water and a 3% magnesium sulfate solution were injected to initiate the leaching process [15]. At the beginning of the experiment, when the water level in the pressure measuring tube stabilized for the first time, the initial permeability coefficient was calculated and recorded using the data from the pressure measuring tubes. Thereafter, the pressure measuring tube data for each sample were recorded every other day [16].

3. Result

3.1. Effect of Clear Water Seepage on Permeability Coefficient of Different Layers of Rare Earth Ore with Different Fines Content

The permeability coefficient of each layer during the water leaching process of rare earth ore with different fine particle contents is shown in Figure 3a–f. It can be observed that the permeability coefficients follow the relationship: upper layer > middle layer > whole > lower layer. This trend is attributed to the decreasing hydraulic gradient with depth [17]. The upper layer experiences a larger hydraulic gradient, which facilitates the migration of micro-particles and enhances pore connectivity, leading to a rapid and substantial increase in the permeability coefficient. Conversely, the lower layer has a smaller hydraulic gradient, resulting in limited fine particle migration, reduced pore connectivity, and, consequently, a lower permeability coefficient. The overall permeability coefficient is theoretically the average value of the individual layers, placing it between the extremes [18]. Generally, the permeability coefficient of each layer shows an upward trend due to enhanced pore connectivity caused by water seepage, but variations exist based on the degree of porosity connectivity.

From the comparison of the permeability coefficients of each layer at different fine particle contents, it is evident that higher fine particle content results in more compact permeability coefficient curves for the middle and lower layers. This is because a higher fine particle content leads to fewer coarse particles, a more complex pore structure, fewer pore throats, and hindered fine particle migration, obstructing pore connectivity [19]. Additionally, the lower layer has a smaller hydraulic gradient, weaker hydrodynamic force, and lower porosity connectivity, resulting in a smaller difference in permeability coefficients between the middle and lower layers and a more compact curve [20].

3.2. Influence of Magnesium Sulfate Leaching on the Permeability Coefficient of Each Layer of Rare Earth Ores with Different Fines Content

The permeability coefficients of each layer during the magnesium sulfate solution leaching process of rare earth ores with different fine particle contents are shown in Figure 4a–f. Similar to water leaching, the relationship between the upper, middle, and lower layers and the overall permeability coefficient follows the pattern: upper > middle > whole > lower layer. However, a key difference is observed: the permeability coefficient of each layer decreases rapidly within 1–2 days and then stabilizes [21]. This rapid decrease is attributed to the chemical replacement reaction between the magnesium sulfate solution and rare earth particles over the initial 1–2 days. Specifically, as an electrolyte solution, magnesium sulfate redistributes charged ions on the surface of rare earth particles, forming a double electric layer. The net charge of this double layer generates a potential difference with the seepage flow. The resulting negative electric field causes the net charge to move backward, dragging part of the solution along and reducing the seepage speed and permeability coefficient [22]. Additionally, during the reaction, high-valence rare earth ions are replaced by low-valence magnesium ions, leading to an increase in high-valence cations. This results in a decrease in the Zeta potential and thickness of the double electric layer, reducing electrostatic repulsion. Consequently, van der Waals attraction dominates, causing an increase in small pores and a decrease in large pores, thereby limiting pore channel development and decreasing the permeability coefficient. After the reaction, the permeability coefficient tends to stabilize [23].

Furthermore, it can be observed from the curves that the upper and middle layers of FC₀₅, FC₁₀, and FC₁₅ samples exhibit relatively more compact permeability coefficient curves during leaching. In contrast, the layers of FC₂₀, FC₂₅, and FC₃₀ samples are relatively compact. When the fine particle content is low, there are more skeleton particles, resulting in higher dynamic water pressure in the upper and middle layers. This leads to the downward migration of fine particles, increasing connected pores in the upper and middle layers and differentiating their permeability coefficients from those of the lower layer. As the fine particle content increases to a certain degree, the number of skeleton particles decreases, the pore structure becomes more complex, and the number of pore throats reduces [24]. The hydraulic gradient falls below the critical value, making fine particle migration difficult, and thus the permeability coefficients of each layer become closer [25].

3.3. Variation of the Overall Permeability Coefficient of the Sample

The overall changes in the permeability coefficient of rare earth ores with varying fine particle content during leaching, from top to bottom, under different leaching conditions (using clean water and magnesium sulfate), are illustrated in Figure 5a,b. It is evident that a higher content of fine particles corresponds to a lower overall permeability coefficient, a narrower range of variation, and a longer duration to achieve a stable permeability coefficient. This is because the migration of fine particles requires coarse particles to create a sufficient number of pore throats [26]. A high fine particle content leads to a reduced number of coarse particles, resulting in a complex pore structure with fewer pore throats. This complicates the migration of fine particles, hinders pore connectivity, and consequently results in minimal changes and lower values of the permeability coefficient [27].

Additionally, when leaching with magnesium sulfate solution, the overall permeability coefficient of the ore body decreases due to the combined effects of percolation and chemical displacement. The impact of chemical displacement on the permeability coefficient is greater than that of clean water percolation, leading to a reduction in the permeability coefficient following chemical displacement [28].

4. Discussion

Porosity characteristics, as the core factor determining the permeability performance of rare earth materials, are influenced by a combination of factors such as the composition and grading of rare earth particles. The fine-grain content, uniformity coefficient, and average particle diameter can comprehensively and effectively describe the particle composition characteristics of rare earths from different perspectives [29].

4.1. Correlation Between Fine Grain Content and Initial Permeability Coefficient

The initial permeability coefficients of different fine-grained content rare earth ores are shown in

Table 5. Fine-grained content and initial permeability coefficients.

Fine Grain Content (%)	Initial Permeability Coefficient (10−4 cm/s)
5	10.30
10	8.40
15	4.55
20	1.99
25	1.57
30	1.01

, and the relationship between different fine-grained content rare earth ores and their initial permeability coefficients is shown in Figure 6. It can be seen that in semi-logarithmic coordinates, with the increase in fine-grained content, the permeability coefficient of the ore body decreases, and the curve is divided into three segments: (a), (b), and (c). When the fines content is <10%, i.e., in section (a), the permeability coefficient of the ore body decreases slowly with the increase in fines; when the fines content is between 10% and 20%, i.e., the fines content is in section (b), the permeability coefficient of the ore body decreases sharply with the increase in fines content; when the fines content is >20%, i.e., in section (c), the permeability coefficient of the ore body decreases slowly with the increase in fines again. In Figure 6, the fitted equations are:

$$k=0.846+{\displaystyle \frac{9.536}{1+{\left(\frac{FC}{13.467}\right)}^{4.590}}}\hspace{1em}\hspace{1em}{R}^2=0.999$$

(1)

4.2. Correlation of Inhomogeneity Coefficient with Initial Permeability Coefficient

The inhomogeneity coefficient Cu is the ratio of the restricted particle size to the effective particle size, which reflects the good degree of soil grading; the higher the inhomogeneity coefficient of the rare earth ores, the wider the range of the particle size distribution, the better the grading, and it is used as one of the important indexes for evaluating the infiltration performance of the rare earth ores. The inhomogeneity coefficients and initial permeability coefficients of rare earth ores with different fine-grained contents are shown in

Table 6. Unevenness coefficients and initial permeability coefficients.

Unevenness Coefficient Cu	Initial Permeability Coefficient (10−4 cm/s)
9.15	10.30
12.20	8.40
45.41	4.55
53.93	1.99
60.29	1.57
63.12	1.01

, and the fitting relationship between the inhomogeneity coefficients and permeability coefficients is shown in Figure 7. It can be seen that the larger the inhomogeneity coefficient of a rare earth ore, the smaller its permeability coefficient and the performance of its linear relationship, indicating that the particle gradation of rare earth ores has an extremely important effect on the permeability coefficient of rare earth ores. Although the higher inhomogeneity coefficient represents the better rare earth gradation, its permeability coefficient is smaller, which is not conducive to the mining of rare earth ore. In Figure 7, the fitted equation is:

$$k=11.148-0.160\times {\mathrm{C}}_{\mathrm{u}}\hspace{1em}\hspace{1em}{R}^2=0.977$$

(2)

4.3. Correlation Between Average Particle Size D₅₀ and Initial Permeability Coefficient

The particle size value corresponding to the cumulative particle size distribution percentage of the soil that reaches 50% is called the average particle size, which can reflect the particle size distribution of the particles in the soil and can be used as an important index for the analysis of the soil particle size and gradation analysis. The relationship between the average particle size D₅₀ and the initial permeability coefficients of different fine-grained rare earth minerals is shown in

Table 7. Average particle size D₅₀ and initial permeability coefficient.

Average Particle Size D50 (mm)	Initial Permeability Coefficient (10−4 cm/s)
0.87	10.30
0.80	8.40
0.79	4.55
0.72	1.99
0.65	1.57
0.55	1.01

, and the fitted curves are shown in Figure 8, which shows that the permeability coefficients of the rare earth minerals are higher as the average particle size of the rare earth minerals is larger. When the average particle size D₅₀ < 0.76 and D₅₀ > 0.82, i.e., in regions (a) and (c), the permeability coefficient grows more gently with the larger average particle size of rare earth ores; when the average particle size 0.76 < D₅₀ < 0.82, i.e., in region (b), the rare earth ores with large average particle sizes have more coarse particles, the seepage channel connectivity is better, and the permeability coefficient grows rapidly with the increase in the average particle size of rare earth ores. In Figure 8, the fitted equation is:

$$k=10.300+{\displaystyle \frac{\left(-8.777\right)}{1+{\left(\frac{D_{50}}{0.793}\right)}^{131.340}}}\hspace{1em}{R}^2=0.994$$

(3)

4.4. Correlation of Intergranular Porosity with Initial Permeability Coefficient

As can be seen from the above, there is still a large error in describing the permeability properties of rare earths by using the state coefficients such as Cu and D₅₀, and the error is especially obvious when the fine-grained content of rare earths is greater than 20%. Therefore, in order to better describe the permeability of rare earth ores with different fine-grained content, the concept of intergranular state parameter is introduced in the following. When the soil body is under the action of an external force, Thevanayagam called the connection between soil particles or agglomerates as “force chain”, but the existing pore ratio e cannot accurately describe the significance of the “force chain”, which has a certain degree of “force chain”. “Force chain” has a certain particle size effect, and using this effect can better characterize the permeability of sandy soils, so Thevanayagam divided the coarse particles and fine particles, with 74 μm as the dividing line, expanding the concept of the soil skeleton porosity ratio, defined as the intergranular state parameter [30,31]. Later, Kong [2] and others cited the intergranular state parameter to sandy soils, and in order to apply uniformity in fine-grained sandy soils, it was also called intergranular porosity ratio e_s, i.e., the pore ratio between soil particles with grain sizes larger than 74 μm. The relationship between intergranular porosity ratio and permeability coefficient of sandy soils with different fine-grain contents was obtained in this study with good representativeness, and its formula is as follows:

$$e_s={\displaystyle \frac{e+f_c}{1-f_c}}$$

(4)

where

• e = Porosity ratio
• e_s = Intergranular porosity ratio
• f_c = Fine grain volume (cm³)
• 1 − f_c = Coarse Grain Volume (cm³)

In view of this, the concept of intergranular porosity ratio is introduced in this paper, and the intergranular porosity ratios and permeability coefficients of rare earth ores with different fine-grained contents were obtained according to the formula, as shown in

Table 8. Intergranular Pore Ratio and Permeability Coefficient.

Intergranular Porosity Ratio es	Initial Permeability Coefficient (10−4 cm/s)
1.07	10.30
1.29	8.40
1.62	4.55
1.89	1.99
2.16	1.57
2.50	1.01

. The fitting relationship between the intergranular porosity ratio and the initial permeability coefficient is shown in Figure 9. The permeability of the rare earth ores decreases as the fines content of the ore body increases, i.e., e_s increases, which causes a blockage to the internal pores of the ore body. The turning point of the curve occurs near e_s = 1.29 and e_s = 1.89. For e_s < 1.29 and e_s > 1.89, i.e., regions (a) and (c) in the figure, the permeability coefficient decreases slowly with the increase in intergranular pore ratio, but when 1.29 < e_s < 1.89, i.e., region (b), the permeability coefficient of the ore body appears to decrease drastically with the increase in intergranular pore ratio. In Figure 9, the fitted equation is:

$$k=0.819+{\displaystyle \frac{11.021}{1+{\left(\frac{e_s}{1.493}\right)}^{7.596}}}\hspace{1em}\hspace{1em}{R}^2=0.998$$

(5)

5. Conclusions

This study systematically analyzes the permeability characteristics of rare earth ores with varying fine particle contents under both clear water and magnesium sulfate leaching conditions. The conclusions are as follows:

(1)

Experimental results indicate that during clear water infiltration, the permeability coefficients of the various layers of rare earth ores follow the order: upper layer > middle layer > overall > lower layer. This phenomenon can be attributed to the higher hydraulic gradient present in the upper layer, which enhances the migration of fine particles and improves pore connectivity. Consequently, as the fine particle content increases, particularly when it exceeds 10%, the permeability coefficients of the middle and lower layers become increasingly similar, indicating a significant suppressive effect of fine particles on pore connectivity.

(2)

Under magnesium sulfate leaching conditions, the permeability coefficients of each layer exhibit a similar hierarchical relationship as observed with clear water. However, during the initial 1 to 2 days of treatment, permeability coefficients decrease rapidly and subsequently stabilize. This variation is closely associated with the chemical exchange reactions between the magnesium sulfate solution and the rare earth particles. Such reactions alter the surface charge distribution of the particles, thereby affecting the electrostatic repulsion among particles and the pore structure, leading to a reduction in overall permeability.

(3)

A comparison of the initial permeability coefficients of different fine particle samples reveals a significant negative correlation between increasing fine particle content and permeability coefficients. Specifically, when the fine particle content is below 10%, the permeability coefficient decreases gradually; however, once the fine particle content reaches the range of 10% to 20%, the permeability coefficient declines sharply, demonstrating strong sensitivity. Additionally, an increase in the uniformity coefficient suggests that an improved particle size distribution can limit permeability, despite the fact that a high uniformity coefficient generally indicates better particle grading.

(4)

To accurately assess the permeability performance when fine particle content exceeds 20%, this study introduces the concept of inter-particle void ratio (es). The analysis indicates that an increase in the inter-particle void ratio leads to a significant reduction in the permeability coefficient of the ore body, especially when es values are between 1.29 and 1.89, at which point a drastic decline in permeability is observed. This reflects changes in the connectivity of internal pores within the ore. Therefore, the inter-particle void ratio effectively captures the spatial relationships among fine particles and provides new insights into understanding permeability variations.