In this paper, the adsorption process of copper ions on activated carbon (AC) was simulated in a column test. It was deduced that it is consistent with the pseudo-second-order model. Cation exchange was observed to be the major mechanism of Cu–AC interactions through scanning electron microscopy–energy dispersive X-ray spectroscopy (SEM–EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) measurements. Adsorption isotherms were fitted well using the Freundlich model. Adsorption thermodynamics at 298, 308, 318 K demonstrated that the adsorption process is spontaneous and endothermic. Spectral induced polarization (SIP) technique was used to monitor the adsorption process, and the double Cole–Cole model was used to analyze the SIP results. The normalized chargeability was proportional to the adsorbed copper content. Two measured relaxation times from the SIP testing were converted into the average pore sizes of 2, 0.8, 0.6, 100–110, 80–90, and 53–60 µm by the Schwartz equation, which are consistent with the measured pore sizes from both mercury intrusion porosimetry and scanning electron microscopy (SEM). The reduction in the pore sizes by SIP during the flow-through tests suggested that the adsorbed Cu²⁺ gradually migrated into small pores as with continued permeation of the influent. These results showcased the feasibility of using SIP technique in engineering practice involving the monitoring of copper contamination in land near a mine waste dump or in adjacent permeable reactive barriers.

Understanding nanoparticles, like carbon nanotube (CNT), transport and retention in porous media is critical for environmental risk assessment and remediation. Millifluidic visualization, spectral induced polarization (SIP), and deep neural network (DNN) were integrated to resolve spatio‐temporal CNT deposition dynamics under complex geochemical conditions. Millifluidic visualization revealed concentration‐dependent retention mechanisms: irreversible straining dominated at high CNT concentrations, while site‐blocking enabled delayed redistribution during flushing. SIP detected real‐time retention by chargeability (R² = 0.82–0.96), while a DNN decoded SIP signals to predict spatially resolved CNT deposition (R² = 0.926), outperforming phenomenological Cole‐Cole modeling. Surface coatings (e.g., montmorillonite, MMT) and divalent cations modulate retention by electrostatic repulsion and pore‐throat constriction, with CNT concentration governing transport efficiency. The hierarchy of controlling factors: CNT concentration > surface properties > cation valence > ionic strength (IS), provides a predictive framework for nanoparticle fate in subsurface environments. This integrated system bridges lab‐scale insights to field‐scale monitoring, advancing non‐invasive SIP applications for nanomaterial management.

To limit the oxidation of waste rocks that originates from mining operations and the subsequent leaching of acidic solutions with high concentration of metal ions, a tailing–rock–clay triple layer capillary cover system was developed to prevent rainwater infiltration in humid climatic regions. The fine grained soil (FGS) layer consists of mine tailing and a hydrodesulfurization (HDS) clay from waste-water treatment with a 95:5 mass ratio. The coarse grained soil (CGS) layer consists of local waste rock granules with a size of 1–10 mm. Methyltrimethoxysilane (MTMS), an oxidation-inhibiting agent with strong hydrophobicity, was passivated on the rock grains to further reduce water infiltration and leaching of metal ions. Prototype-scale column tests were performed with matric suction and water content measurements under 680 min rainfall of 60 mm/h, the most severe annual precipitation case scenario for the Dexing Copper Mine (Jiangxi Province, China, 28.95° N, 117.57° E, humid climate). Both the uncoated and the coated covers exhibited zero leakage throughout the experiment. The passivation on rock granules in the coated cover increased the water entry value (WEV) of the CGS layer to −0.56 kPa. This led to a 15 mm water storage increment in the overlain FGS layer as compared to that in the uncoated cover, and induced lateral drainage (5% of the precipitation) in the FGS layer, which was not overserved in the uncoated cover. The concentrations of the leached Fe²⁺, Cu²⁺, Zn²⁺, Mn²⁺ and Mg²⁺ cations drained from the CGS layers of the uncoated cover were 0, 0.4, 0.8, 73.5, and 590.5 mg/L, which are all within the regulation limits of industrial discharge water standards. The concentrations of Cu²⁺, Mn²⁺ and Mg²⁺ cations drained from the coated CGS layer were reduced by 1–3 orders of magnitude. The abovementioned laboratory studies validated the water retention and leaching prevention abilities of the proposed three-layer capillary covers and the MTMS coating, which hold promises in engineering applications.

Bentonite and polymer‐modified bentonites, as ubiquitous clay minerals in geological formations and widely utilized barrier materials in engineered systems, significantly influence the hydraulic properties of porous media due to their high swelling capacity and ultralow hydraulic conductivity ( k ). Accurate prediction of k is crucial not only for critical natural processes, such as rainfall infiltration, groundwater flow, and solute transport in subsurface aquifers, but also for engineering applications, such as contaminant containment, nuclear waste disposal, and CO ₂ geological storage. However, existing predictive models often rely on empirical assumptions and non‐physical fitting parameters. This study employs large‐scale molecular dynamics simulations integrated with the original Kozeny‐Carman (K‐C) equation to predict k across a wide range of dry densities for both pure montmorillonite (MMT, = 134.6–1759.4 kg/m ³ ) and carboxymethyl cellulose‐modified MMT (CMC‐MMT, = 147.5–1550.7 kg/m ³ ). Our approach fundamentally challenges the conventional understanding that original K‐C equation is unsuitable for clayey soils: molecular‐scale parameterization of free water porosity (), tortuosity (), and water‐accessible surface area ( S ₀ ) yields predictions within a factor of five of experimental data. Critically, k reduction was proven to stem from bound water immobilization, where polymer modification amplifies this effect through three synergistic mechanisms: (a) enhanced water adsorption thickens bound layers (reducing by 18%–76%), (b) pore filling increases by up to 6 times, and (c) elevated S ₀ further restricts flow pathways. This work establishes a physically rigorous framework for hydraulic conductivity prediction in clay‐rich porous media, resolving long‐standing controversies in clay hydraulics and offering insights applicable to both natural and engineered systems.