Double-layer Model Research Articles

Real-Time Optimal Scheduling of a Water Diversion System Using an Improved Wolf-Pack Algorithm and Scheme Library

A water diversion system (WDS) with cascade pumping stations (CPSs) plays an important role in the application of water resources. However, high energy consumption is reported due to unreasonable scheduling schemes and long decision times. Herein, this paper presents a new method to achieve optimal scheduling schemes effectively, including the head allocation of CPSs, the number of running pumps, and pump blade angles. A double-layer mathematical model for a WDS was established with the goal of achieving minimal energy consumption, considering the constraints of flow rate, water level, and the characteristics of pump units. The inner-layer model was used to obtain scheduling schemes of single-stage pumping stations, as well as the water levels and flow rates of water channels, while the outer-layer model was used to optimize inter-stage head allocation. An improved wolf-pack algorithm (IWPA) was proposed to solve the model, using a Halton sequence to obtain the uniform initial population distribution and introducing simulated annealing (SA) to improve the global searchability. Moreover, an idea for a pre-established scheme library was suggested for inner-layer models to obtain the solutions in real time with less calculation workload. Taking an actual project as a case, in contrast with the actual schemes, the optimal scheduling method could result in energy savings of 14.37–20.39%, a CO2 emission reduction of 13–32 tons per day, and water savings of 0.14–18.34%. Moreover, the time complexity decreased to square order, and the CPU time of the optimal method was about 1% that of the traditional method. This study provides an efficient method for the high-value utilization of energy and water resources for a WDS.

Machine learning-based acoustic emission technique for corrosion-induced damage monitoring in reinforced concrete structures

Early-stage detection of corrosion in reinforcement embedded inside concrete, generally considered as the major problem in structures under extreme marine environments, can help to schedule timely maintenance/repair and to avoid any catastrophic failure. However, quantitative evaluation of the degree of deterioration, especially at a very early stage, i.e., before its appearance on the surface, is extremely difficult due to the complex process in heterogeneous material. This study aims to characterize the critical damage stages in reinforced concrete specimens under accelerated conditions using the Acoustic emission (AE) damage quantification methods supported by machine learning (ML) techniques. The stages of corrosion-induced damage are predicted by a two-step predictive model that involve both regression and classification tasks. Three supervised regression models — support vector regression (SVR), relevance vector machine (RVM) and kernel ridge regression (KRR) —are first adopted to evaluate the amount of current. Then the output from regression model is given as an input to the classification problem to predict the discrete class label output. Characterized damage stages are validated based on mass loss and crack width measurements. The results show that the corrosion initiation (at day 3) and crack formation (at day 7) can be determined from the sudden change in acoustic parameters. Further, a double layer (supervised-unsupervised) model is proposed which is found be more effective in correctly detecting the progression of damage. The findings indicate that the proposed approach that combines corrosion detection by analysing AE signals with ML technique can accurately and robustly predict corrosion severity.

Leveraging electrochemical double layer structure to rationally control electrolysis

This perspective delves into the electrochemical microenvironment, uncovering entropic effects in CO2 reduction, revealing neutral molecule electrosorption under polarization, highlighting challenges in the classical double layer model, and proposing research approaches for future interface studies.

Optimal configuration of hydrogen storage capacity of hybrid microgrid considering peak regulation and frequency modulation requirements

This study proposes an innovative hydrogen storage capacity optimization configuration method that considers multiple demand factors, addressing the issue that traditional methods for optimizing hydrogen storage capacity in hybrid microgrids cannot simultaneously balance economic efficiency and grid connection quality. This method breaks through the traditional optimization framework and adopts a double-layer optimization model, combining the peak shaving operation cost of the hybrid microgrid with the interactive power deviation and power fluctuation penalty terms of the interconnection line during the frequency regulation stage, achieving dual optimization of economy and grid connection quality. Through precise mathematical modeling and efficient optimization algorithms, we have successfully obtained the minimum operating cost corresponding to the minimum power fluctuation, the minimum interconnection line interactive power deviation penalty term, and the optimal hydrogen storage capacity configuration scheme. Identify two typical days through cluster analysis. Option 1 (considering peak shaving, frequency regulation, and hydrogen electrolysis) has the lowest net load and a total operating cost of 3.0331 million yuan, which is better than Option 2 (3.0973 million yuan) and Option 3 (5.0398 million yuan). This plan effectively reduces wind and solar power waste, shortens the operating time of thermal power units, and demonstrates the rationality and economy of optimizing hydrogen storage capacity configuration.

Adsorption of sulfamethoxazole and ciprofloxacin on chitosan foam: Isotherms modeling and binding mechanisms

The paper investigates the adsorption of two pharmaceutical compounds (PCs) from polluted water, namely sulfamethoxazole (STZ) and ciprofloxacin (CRA), onto a new adsorbent formed by dispersion of chitosan on polyurethane (PU/C). Adsorption isotherms were determined on the investigated adsorbent as a function of temperature, in the range 298–328 K. For each temperature, PU/C showed higher affinity toward STZ with a maximum adsorption capacity at the maximum investigated temperature. A double-layer model was adopted for the interpretation of the entire adsorption data set. The number of adsorbate molecules bound per active site allowed for determining that an aggregation process occurs upon adsorption. The retrieved values for the CRA- PU/C system are 1.37, 1.61, 1.68, and 0.606 at 298, 308, 318, and 328 K, respectively, while for the STZ- PU/C system, the corresponding values are 0.76, 1.07, 1.23 and 1.36 at T = 298, 308, 318 and 328 K respectively. Finally, the values of adsorption energy define the phenomenon under investigation as a physisorption.

(Invited) Modeling of the Electric Double Layer (EDL) Structures of Localized High-Concentration Electrolytes (LHCE)

Various electrical double layer (EDL) models have been proposed but mainly for homogenous solutions. Recently, the so-called Localized high-concentration electrolytes (LHCE) have shown many benefits to high-capacity electrodes. Recently, we have proposed micelle-like structures to enable a complete understanding of microstructures in LHCE, which contains a salt, solvent, and non-ion-solvating diluent, analogical to the roles of oil, surfactant, and water as in micelles. [1] As the solid electrolyte interphase (SEI) formation is sensitive to the EDL structure, [2] it is critical to understand the EDL structures for LHCE with heterogeneous structures.Molecular dynamics simulations were performed in several electrolytes with heterogeneous structures on negatively charged surfaces. It was found the Stern model with an absorbed cation layer adsorption layer and a more diffused layer with cation, anion, solvent, and diluents, should be used to describe the EDL of this type of electrolyte.For the system consisting of LiFSI salt, DME solvent, and TFEO diluent at a concentration of LiFSI-1.2DME-2TFEO, the heterogeneous micelle-like structures in LHCE are maintained in the EDL, with the Li+-rich salt-solvent clusters and the Li+-poor diluent regions. The diluent region contains Li+ near the negatively charged surface but does not have any ions in the bulk of LHCE. This is because TFEO cannot form a complete solvation shell in the bulk electrolyte due to the steric effect, however, only a partial solvation shell is needed in the Stern layer in the EDL. The appearance of Li+ in the diluent is also necessary for the EDL, as TFEO alone cannot screen the charge.The chemical and concentration design space for the three components is very large. To obtain a more general picture, we also explored different salt-solvent ratios and different diluent-salt interactions. As the salt solvent ratio increases from low (LCE), to medium (MCE) to high concentration electrolytes (HCE), where all solvents are coordinated with ions, the salt-solvent structures evolve from fully solvated ions or ion pairs in LCE, 3D branched networks in MCE, to fully connected salt aggregates in HCE. The salt-diluent interactions and diluent concentration further modify the micelle-like structures. The EDL for both LHCE and LMCE are heterogenous. [1] Nature Materials 22, 1531–1539 (2023)[2] J. Am. Chem. Soc. 145, 4, 2473–2484 (2023)

Ionic liquid–electrode interface: Classification of ions, saturation of layers, and structure-determined potentials

Progress in electrochemical applications of ionic liquids builds on an understanding of electrical double layer. This computational study focuses on structure-determined quantities – maximum packing density, potentials, and capacitances – evaluated using a one-electrode electrical double layer model. Interfaces of the 40 studied ions are grouped into four distinct classes according to their characteristic packing at the model surface. The simulations suggest that the exact screening by a monolayer of counter-ions (preceding the crowding of ions) is unlikely for ions in known air- and water-stable ionic liquids within their electrochemical stability window. This work discusses how the assessed structure-determined quantities can guide the experimental tuning of (electro/mechano)chemical properties and characterize the structure of ionic liquid–electrode interfaces.

Investigation of the surface charge behaviour of ettringite: Influence of pH, calcium, and sulphate ions

Ettringite is an important mineral that contributes to the overall performance of cementitious materials. Knowledge of the surface charge behaviour of a solid is necessary for a mechanistic description of surface processes such as adsorption or particle-particle interactions. The objective of this study was to develop a model capable of reproducing ettringite surface charge as a function of calcium, sulphate, and pH.Ettringite was synthesised and characterised using different analytical, microscopic, and spectroscopic techniques with the help of density functional theory. Electrophoretic mobility was measured using laser Doppler electrophoresis in alkaline waters representative of the cementitious environment.The behaviour of the ettringite surface charge was shown to be quite complex as sulphate and calcium acted in a competitive manner on the overall charge. The ζ-potential increases when the calcium content increases, whereas it decreases when sulphate increases. This is due to the possible adsorption of these ions at the surface, and the extent of the effect depends on the relative concentrations of Ca and SO42−.An electrostatic double layer model (DLM) was used to calculate the surface potential, considering the adsorption of both calcium and sulphate, as possible ions determining the potential (IDP), and formation of different complexes with ettringite surface functional groups (SOH). The variations of the ζ-potential could be satisfactorily predicted under the different chemical conditions of interest in a cementitious environment.

Deciphering BSA adsorption onto COL-BC: Interpretations from statistical physics modeling

In this current study, a single-energy double layer model was employed to inspect the adhesion mechanism of bovine serum albumin (BSA) on porous microsphere of cellulose (BC) collagen (COL) bacterium (COL-BC). Six physicochemical variables defining the retention mechanism, :the number of anchored BSA protein per site (n), the amount of (COL-BC) available pores (NM), the capacity of adsorbed quantity (Qa), the specific surface area (As), the concentrations at half saturation (C1/2) and the molar binding energy (ΔE1) are determined. Calculations revealed that n ≥ 1 indicating that an average of one BSA per site is linked to one (COL-BC) receptor site with forming two layers. The BSA/(COL-BC) docking system exhibits a weak binding affinity as evidenced by the computed molar adsorption energy (ΔE1) which is below 40 kJ/mol. This energetic observation aligns with the characteristics of a physical and exothermic binding mechanism. Analysis of the (COL-BC) surface using the Kelvin equation revealed a pore size distribution (PSDs) extending across 0.05 μm–2 μm, providing insights into the stereochemistry of its receptor sites. Discussion of the BSA/COL-BC adhesion reaction through Polanyi equation unveils an adsorption energy distribution (AED) localized between 0 and 15 kJ/mol, consistent with a weak interaction profile characteristic of a physisorption mechanism. Finally, three thermodynamic functions were estimated in order to macroscopically study the BSA/(COL-BC) adsorption systems.This work is involved to provide more information about the adsorption of BSA on the COL-BC microsphere and investigate a theorical approach for the application of the controlled release technology.

Potentiometric Studies on Ion-Transport Selectivity in Charged Gold Nanotubes.

Under ideal conditions, nanotubes with a fixed negative tube-wall charge will reject anions and transport-only cations. Because many proposed nanofluidic devices are optimized in this ideally cation-permselective state, it is important to know the experimental conditions that produce ideal responses. A parameter called Ccrit, the highest salt concentration in a contacting solution that still produces ideal cation permselectivity, is of particular importance. Pioneering potentiometric studies on gold nanotubes were interpreted using an electrostatic model that states that Ccrit should occur when the Debye length in the contacting salt solution becomes equivalent to the tube radius. Since this "double-layer overlap model" (DLOM), treats all same-charge ions as identical point charges, it predicts that all same-charged cations should produce the same Ccrit. However, the effect of cation on Ccrit in gold nanotubes was never investigated. This knowledge gap has become important because recent studies with a polymeric cation-permselective nanopore membrane showed that DLOM failed for every cation studied. To resolve this issue, we conducted potentiometric studies on the effect of salt cation on Ccrit for a 10 nm diameter gold nanotube membrane. Ccrit for all cations studied were, within experimental error, the same and identical, with values predicted by DLOM. The reason DLOM prevailed for the gold nanotubes but failed for the polymeric nanopores stems from the chemical difference between the fixed negative charges of these two membranes.

Analytical Solution for Contaminant Transport through a Soil–Bentonite (SB)/Geosynthetic Clay Liner (GCL)/Soil–Bentonite (SB) Composite Cutoff Wall and an Aquifer

This study develops a one-dimensional analytical solution for contaminant advection, diffusion and adsorption through a soil–bentonite (SB)/geosynthetic clay liner (GCL)/SB–aquifer composite cutoff wall (CCW) system. The solution agrees well with an existing double-layer model. Adopting toluene as a representative contaminant, using the present solution, the analysis systematically investigates the impact of hydraulic gradient (i) and the hydraulic conductivities of GCL (kgcl) and SB (ksb). The results show the following: (1) Increasing i from 0.1 to 1 reduces the concentration breakthrough time (tcb) from 20 to 11 years and mass flux breakthrough time (tfb) from infinite to 11 years, indicating lower i significantly extend both tcb and tfb, which is crucial for optimizing CCW barrier performance; (2) lowering kgcl from 5.0 × 10−11 m/s to 1 × 10−12 m/s and reducing ksb from 1.0 × 10−9 m/s to 1.0 × 10−11 m/s, would increase the tcb by 36% and 100%, respectively. It demonstrates that reducing kgcl and ksb could enhance barrier performance. (3) To achieve equivalent barrier performance, soil–bentonite cutoff wall (SBCW) requires greater thickness compared to SB/GCL/SB CCW, indicating that GCL reduces the required amount of bentonite; and (4) CCWs can use SB with lower adsorption capacity to achieve equivalent performance, further reducing bentonite requirements. The present solution can aid in the design and optimization of GCL-enhanced CCWs.

Rationally Improved Surface Charge Density of Triboelectric Nanogenerator with TiO2-MXene/Polystyrene Nanofiber Charge Trapping Layer for Biomechanical Sensing and Wound Healing Application.

Triboelectric nanogenerators (TENGs) have become reliable green energy harvesters by converting biomechanical motions into electricity. However, the inevitable charge leakage and poor electric field (EF) of conventional TENG result in inferior tribo-charge density on the active layer. In this paper, TiO2-MXene incorporated polystyrene (PS) nanofiber membrane (PTMx NFM) charge trapping interlayer is introduced into single electrode mode TENG (S-TENG) to prevent electron loss at the electrode interface. Surprisingly, this charge-trapping mechanism augments the surface charge density and electric output performance of TENGs. Polyvinylidene difluoride (PVDF) mixed polyurethane (PU) NFM is used as tribo-active layer, which improves the crystallinity and mechanical property of PVDF to prevent delamination during long cycle tests. Herein, the effect of this double-layer capacitive model is explained experimentally and theoretically. With optimization of the PTMx interlayer thickness, S-TENG exhibits a maximum open-circuit voltage of (280V), short-circuit current of (20µA) transfer charge of (120 nC), and power density of (25.2 µW cm-2). Then, this energy is utilized to charge electrical appliances. In addition, the influence of AC/DC EF simulation in wound healing management (vitro L929 cell migration, vivo tissue regeneration) is also investigated by changing the polarity of trans-epithelial potential (TEP) distribution in the wounded area.

A Novel Double-Layer Plastic Zone Elastoplastic Model and Analytical Solutions Considering the Freezing Temperature Gradient of Surrounding Rock in Cold Region Tunnels

The frost heave force and the plastic zone caused by the frost heave of the surrounding rock are the primary causes of tunnel frost damage. Current research mainly focuses on the plastic damage caused by the frost heave rock zone on the inner layer rock, while neglecting the damage caused by the outer layer rock. It will not accurately evaluate the stability of tunnels in cold regions. A new elastoplastic calculation model of the tunnel surrounding rock double-layer plastic zone in cold regions is proposed to reveal the failure law of the surrounding rock under frost heave based on thermodynamics and elastic-plastic mechanics theory. The stress field and radius of the surrounding rock in the two-layer plastic zone are determined using the Unified Strength Theory. The radius and stress distribution of the double-layer plastic zone obtained by the theoretical solution are in accordance agreement with the numerical calculation, which verifies the correctness of the theoretical solution. The case analysis of the Yuximolegai Tunnel shows that the thicknesses of the inner and outer plastic zones of the surrounding rock reach 0.57 and 2.34 m, respectively. The outer plastic zone caused by non-uniform frost heaving of the surrounding rock has a larger influencing range than the inner plastic zone. The double-layer plastic zone expands rapidly with the increase in the volumetric frost heave coefficient and elastic modulus of the surrounding rock, but are significantly suppressed by the in-situ stress. The influence of lining thickness and non-uniform frost heave coefficient on the plastic zones is relatively minor, yet their impact on the frost heave force should not be overlooked.

Enhanced Frequency Containment Reserve provision from battery hybridized hydropower plants: Theory and experimental validation

This paper presents a solution to address wear and tear of Run-of-River (RoR) Hydropower Plants (HPPs) providing enhanced Frequency Containment Reserve (FCR). In this respect, the study proposes the integration of a Battery Energy Storage System (BESS) with RoR HPPs controlled by a double-layer Model Predictive Control (MPC). The upper layer MPC acts as a state of energy manager for the BESS, employing a forecast of the required regulating energy for the next hour. The lower-layer MPC optimally allocates the power set-point between the turbine and the BESS. Reduced-scale experiments are performed on a one-of-a-kind testing platform to validate the proposed MPC-based control considering a comparison with different control strategies and different BESS sizes. The results demonstrate superior performance of the proposed framework, compared to simpler techniques like dead-band control or to the standalone RoR scenario, leading to improved FCR provision, reduced servomechanism stress, and extended hydropower asset lifespan.

Understanding the Competition Mechanism between Na2O and CaO for the Formation of the Initial Layer of Zhundong Coal Ash

The contents of alkali and alkaline earth metals are higher in Zhundong coal, and there are serious problems of slagging and fouling during the combustion process. Therefore, it is of great significance to reveal the mechanism of slagging and fouling in the boiler of Zhundong coal. In this paper, first-principle calculations based on density functional theory are used to study the competition mechanism of alkaline metal oxides during the combustion process in Zhundong coal by establishing the Na2O(110)/CaO(100)-SiO2(100) double-layer interface model. The results show that the bond lengths of the surface of Na2O(110) and CaO(100) with SiO2(100) after adsorption were generally lengthened and the value of bond population became smaller, which formed a stable binding energy during the reaction. The electron loss of Na is 0.05 e, the electron loss of Ca is 0.03 e, and the electron loss of Na2O is greater than that of CaO. The charge transfer on the surface of Na2O with SiO2 is obviously higher than that of CaO and the orbital hybridization on the surface of CaO with SiO2 is weaker than that on the surfaces of Na2O with SiO2. Na2O is easier to react with SiO2 than CaO. The adsorption energies on the surface of Na2O and CaO with SiO2 are −5.56 eV and −0.72 eV, respectively. The adsorption energy of Na2O is higher than that of CaO, indicating that Na2O is more prone to adsorption reactions and formation of Na-containing minerals and other minerals, resulting in more serious slagging. In addition, the XRD analyses at different temperatures showed that Na-containing compounds appeared before Ca-containing ones, and the reaction activity of Na2O is stronger than that of CaO in the reaction process. The experimental results have good agreement with the calculation results. This provides strong evidence to reveal the slagging and fouling of Zhundong coal.

Effect of strut microstructure on multiscale radiation properties of porous foams

Porous materials, widely used in engineering due to their excellent physical properties, have significant engineering and academic research value in their mechanism of radiation heat transfer. Micro-cellular foams are composed of a large number of struts and walls with micro-scale radiation effect, making it difficult to analyze the influence of strut micro-structure on radiation properties. In this study, the radiation parameters of the curved triangular prism-shaped struts are calculated using the finite element electromagnetic method, and the influence of the strut micro-structure parameters and the macroscopic parameters of the foam on the radiation characteristics is analyzed. The results demonstrate that the radiation properties of the equal-volume cylinder model, compared to the double-layer cylinder model, are closer to those of the curved triangular prism struts. The incidence angle has a negligible impact on the radiation parameter deviation of the struts. It is difficult to ignore the radiation parameter deviation of concave-curved triangular prism-shaped struts. The macroscale radiation properties of the foam are significantly influenced by the microscale radiation properties of the struts in the situation of low porosity, large pore size, and high strut volume ratio.

Research on concentration dosing control based on the ISSA-LSTM model and dynamic concentration detection

ABSTRACT During the thickening process, the dosage of flocculant has a great influence on the overflow concentration and filter cake moisture. The dosage of flocculant cannot be automatically updated according to the feeding situation, especially when the properties of the concentrated feeding material change, and the overflow concentration detection feedback cannot be adjusted in time. To address these problems, a dynamic concentration detection device was designed. In addition, a dosage of flocculant correction model based on dynamic concentration detection was constructed, and a feed-forwards flocculant additioncontrol model based on the ISSA-LSTM neural network was proposed. The results showed that the relationship between the linear slope of the dynamic concentration and the dosage of flocculant was in line with that obtained using the ExpAssoc model. Then, a double-layer LSTMslime water feedforward flocculant addition control model was proposed based on the multistrategy jointly improved Sparrow SearchAlgorithm (SSA). This model can determine the optimal dosage according to the condition of the infeeding during the thickening process. This new method can improve the intelligence of coal preparation plants and reduce the cost of washing. The scientific application of these research results will help to realize intelligent solid – liquid separation.

Improved robust model predictive control for residential building air conditioning and photovoltaic power generation with battery energy storage system under weather forecast uncertainty

The rising demands for comfort alongside energy conservation underscore the importance of intelligent air conditioning control systems. Model Predictive Control (MPC) stands out as an advanced control strategy capable of addressing these demands. However, accurate prediction of all relevant variables remains a challenge in practical scenarios, complicating MPC’s ability to devise effective control actions amid prediction inaccuracies. To counteract this issue, this paper introduces an enhanced Double-Layer Model Predictive Control (DLMPC) algorithm. This innovative approach adjusts for discrepancies between forecasted and actual values without the need for additional variables and models, thereby reducing the adverse effects of prediction errors. Additionally, we develop precise models for room temperature simulation and for calculating air conditioning (AC) load and energy consumption, grounded in empirical data from residential settings and AC performance tests. Validation of these models demonstrates their efficacy in enabling MPC to formulate efficacious control strategies. When juxtaposed with a baseline model, the DLMPC algorithm significantly improves temperature regulation accuracy by up to 15.12% and achieves a 10.50% reduction in energy consumption over the heating season.

Electrolyte effects on the alkaline hydrogen evolution reaction: A mean-field approach

This paper introduces the combination of an advanced double-layer model with electrochemical kinetics to explain electrolyte effects on the alkaline hydrogen evolution reaction. It is known from experimental studies that the alkaline hydrogen evolution current shows a strong dependence on the concentration and identity of cations in the electrolyte, but is independent of pH. To explain these effects, we formulate the faradaic current in terms of the electric potential in the double layer, which is calculated using a mean-field model that takes into account the cation and anion sizes as well as the electric dipole moment of water molecules. We propose that the Volmer step consists of two activated processes: a water reduction sub-step, and a sub-step in which OH− is transferred away from the reaction plane through the double layer. Either of these sub-steps may limit the rate. The proposed models for these sub-steps qualitatively explain experimental observations, including cation effects, pH-independence, and the trend reversal between gold and platinum electrodes. We also assess the quantitative accuracy of the water-reduction-limited current model; we suggest that the predicted functional relationship is valid as long as the hydrogen bonding structure of water near the electrode is sufficiently maintained.

Exploring diclofenac potassium adsorption on activated carbon: A comprehensive statistical physics and experimental approach

This study aims to contribute to understanding the removal processes of diclofenac potassium (DP) medicine in wastewater treatment systems, employing activated carbon (AC) as an adsorbent. To achieve this goal, a multidisciplinary approach was adopted, integrating experimental and theoretical analyses of equilibrium data regarding the adsorption of DP on AC. Five statistical physics models were applied to determine the model best for the adsorption process. The selection of the most appropriate model considered both the performance of the models and the analysis of the estimated parameters. Statistically, all models exhibited satisfactory results. However, when analyzing the estimated parameters, the double-layer model with single adsorption energy emerged as the most suitable model to describe the analyzed process. Based on the chosen model’s parameters, we observed that as the temperature increases, the number of active sites occupied during adsorption and their availability on the adsorbent also increases. However, the number of available adsorption sites decreases as the temperature rises. The half-saturation concentration, in turn, increases with increasing temperature, suggesting that the process is favored when temperatures above room temperature are used. Additionally, higher temperatures provide better removal results, indicating that DP molecules’ non-parallel and parallel orientations on the AC surface favor the adsorption process. Finally, our combined results led to the proposal of a mechanism for DP adsorption on AC, which is based on physical adsorption interactions between adsorbate-adsorbent and adsorbate–adsorbate.