Simulated Breakthrough Research Articles

Citric acid functionalized chitosan hydrogel beads for enhanced Cr(VI) removal: Experimental assessment and COMSOL modelling of adsorption in a fixed-bed system

Chitosan hydrogel beads (CHB) and cross-linked CHB functionalized with tricarboxylic citric acid (CA-GLA-CHB) were synthesized and used for the removal of Cr(VI) from aqueous solutions in batch and dynamic adsorption systems. Applicability of COMSOL Multiphysics software as a tool for predictive modelling of column dynamics using a minimum set of experimental parameters was tested and compared with experimental results. Batch experiments demonstrated that CA-GLA-CHB showed almost 20% higher adsorption capacity and wider operational pH range compared to non-functionalized CHB. In a dynamic system, CA-GLA-CHB was used as column packing material and the column dynamics was investigated at different conditions. The breakthrough and exhaustion time of the column increased with an increase in bed height and a decrease in feed flow rate and initial Cr(VI) concentration. Computational modeling by COMSOL software with implemented Advection-Dispersion-Reaction (ADR) equation was used to simulate breakthrough curves for the applied dynamic system in order to validate the possibility of its application for process design in the scaled-up fixed-bed column systems for wastewater treatment. The simulated breakthrough curves of Cr(VI) adsorption matched well with the experimental, thus proving that COMSOL Multiphysics software can be used for scaling-up fixed-bed column systems packed with low-cost and effective CA-GLA-CHB bioadsorbent.

Evaluation of a Volume-Averaged Species Transport Model with Micro-Macro Coupling for Breakthrough Curve Prediction.

In porous water filters, the transport and entrapment of contaminants can be modeled as a classic mass transport problem, which employs the conventional convection-dispersion equation to predict the transport of species existing in trace amounts. Using the volume-averaging method (VAM), the upscaling has revealed two possible macroscopic equations for predicting contaminant concentrations in the filters. The first equation is the classical convection-dispersion equation, which incorporates a total dispersion tensor. The second equation involves an additional transport coefficient, identified as the adsorption-induced vector. In this study, the aforementioned equations were solved in 1D for column tests using 3D unit cells. The simulated breakthrough curves (BTCs), using the proposed micro-macro-coupling-based VAM model, are compared with the direct numerical simulation (DNS) results based on BCC-type unit cells arranged one-after-another in a daisy chain manner, as well as with three previously reported experimental works, in which the functionalized zeolite and zero-valent iron fillings were used as an adsorbent to remove phosphorous and arsenic from water, respectively. The disagreement of VAM BTC predictions with DNS and experimental results reveals the need for an alternative closure formulation in VAM. Detailed investigations reveal time constraint violations in all the three cases, suggesting this as the main cause of VAM's failure.

Can Geometric Parameters Enable Direct Prediction of Non‐Fickian Transport in Rock Fractures Across Diverse Flow Regimes?

AbstractAnomalous solute migrations in fractured rocks are governed by geometric characteristics and flow regimes. Although existing inverse models can describe this behavior, the underlying physics for quantifying key transport coefficients remains largely unexplored. Here, we investigate the quantitative impacts of geometric heterogeneity and flow regimes on solute transport in rock fractures. We conduct numerical experiments to simulate water flow and conservative solute transport in 3D fractures with varying geometric features and Reynolds numbers. Our results show that the non‐Fickian transport is prevalent across the entire flow regime, with Darcy flows attributed to geometric heterogeneity and non‐Darcian flows influenced by additional eddy zones. We employ the mobile‐immobile (MIM) domain model and continuous time random walk (CTRW) model to inversely model simulated breakthrough curves. Inverse analyses demonstrate that both models effectively characterize anomalous transport behaviors. The fitted transport coefficients of the MIM model exhibit stronger quantitative relationships with aperture and roughness parameters, as well as Reynolds number, compared to the CTRW model. By incorporating parameterized transport coefficients, we propose physics‐ and statistics‐based models to directly predict anomalous transport behaviors under different flow regimes. These prediction models accurately reproduce solute transport processes of all simulated cases with acceptable errors. The feasibility of directly predicting solute transport under varying flow regimes using geometric information is thus validated. Our study not only supports the study of substance migration based on geometric structure features, but also serves as a foundation for investigating geological activities based on substance migration information.

Hydrogen bond unlocking-driven pore structure control for shifting multi-component gas separation function

Purification of ethylene (C2H4) as the most extensive and output chemical, from complex multi-components is of great significance but highly challenging. Herein we demonstrate that precise pore structure tuning by controlling the network hydrogen bonds in two highly-related porous coordination networks can shift the efficient C2H4 separation function from C2H2/C2H4/C2H6 ternary mixture to CO2/C2H2/C2H4/C2H6 quaternary mixture system. Single-crystal X-ray diffraction revealed that the different amino groups on the triazolate ligands resulted in the change of the hydrogen bonding in the host network, which led to changes in the pore shape and pore chemistry. Gas adsorption isotherms, adsorption kinetics and gas-loaded crystal structure analysis indicated that the coordination network Zn-fa-atz (2) weakened the affinity for three C2 hydrocarbons synchronously including C2H4 but enhanced the CO2 adsorption due to the optimized CO2-host interaction and the faster CO2 diffusion, leading to effective C2H4 production from the CO2/C2H2/C2H4/C2H6 mixture in one step based on the experimental and simulated breakthrough data. Moreover, it can be shaped into spherical pellets with maintained porosity and separation performance.

Simulation on the Breakthrough Curve During CO2 Adsorption from Biogas in a Fixed Bed Column

Separation of CO2 gas from the biogas can be accomplished by adsorption process. An adsorbent has a maximum capacity, so the adsorbent will eventually be saturated at a certain time. Therefore, it is necessary to simulate the adsorption mass transfer to produce a breakthrough curve. The breakthrough curve from the simulation of adsorption mass transfer was validated with the experimental data. The research was conducted using variations in temperature and pressure. The mass transfer simulation was solved using the finite difference method. The adsorbent used in this research was 13X zeolite and the biogas was obtained from cow dung waste. Convergent curves can be obtained in numerical simulations as breakthrough curves. This research shows that adsorption should occur at low temperatures and high pressure. Column height and flow velocity also influence the breakthrough time. The comparison of the simulated breakthrough time with experimental data is not much different with R2 0.9969. The striking difference is in the adsorption zone with average relative error (ARE) values ranging from 9.57% to 20.49%. From the results of entropy, enthalpy, and Gibbs free energy calculations, the biogas adsorption research on the 13x zeolite column is an exothermic and spontaneous process

Predictive mechanistic modeling of loading and elution in protein A chromatography

Protein A chromatography is an enabling technology in current manufacturing processes of monoclonal antibodies (mAbs) and mAb derivatives, largely due to its ability to reduce the levels of process-related impurities by several orders of magnitude. Despite its widespread application, the use of mathematical modeling capable of accurately predicting the full protein A chromatographic process, including loading, post-loading wash and elution stages, has been limited. This work describes a mechanistic modeling approach utilizing the general rate model (GRM), the capabilities of which are explored and optimized using two isotherm models. Isotherm parameters were estimated by inverse-fitting simulated breakthrough curves to experimental data at various pH values. The parameter values so obtained were interpolated across the relevant pH range using a best-fit curve, thus enabling their use in predictive modeling, including of elution over a range of pH. The model provides accurate predictions (< 3% mean error in 10% dynamic binding capacity predictions and ∼ 5% mean error in elution mass and pool volume predictions, both on scale-up) for various residence times, buffer conditions and elution schemes and its effectiveness for use in scale-up and process development is shown by applying the same parameters to larger columns and a wider range of residence times.

Mercury removal from aqueous media by aminated polyacrylonitrile beads impregnated with nano-urchin bismuth sulfide particles: Experimental and theoretical analysis under batch and continuous mode

The present study encompasses a thorough analysis of aqueous Hg (II) adsorption using aminated polyacrylonitrile beads incorporated with high-capacity surfactant assisted bismuth sulfide nanoparticles. The porous beads provided effective contact between aqueous Hg and the inorganic nano-adsorbent (PBS2) that was encapsulated in the matrix. The macro-sized beads served as suitable packing material for designing a fixed bed adsorption column for continuous mode analysis without significant pressure build up and offered an easy solid–liquid separation after treatment. A marginal negative zeta potential of the adsorbent beads improved the interaction with Hg2+ facilitating the sorption. The incorporation of amine groups into the polymeric bead surface via amination increased the adsorption capacity further from 83.30 mg/g to 130.00 mg/g (∼56.00%) at 303 K. The associated parameters of batch kinetics (effective pore diffusivity and mass transfer coefficient) were determined using a first principle-based model available in literature. Mercury was chemisorbed via synergistic lone pair interactions of S and N atoms with Hg, leading to formation of coordination bonds (Hg-S and Hg-N). An established mass transfer model was utilized to generate simulated breakthrough curves for the continuous analysis using synthetic feed. Additionally, the adsorption column showed comparable performance using both synthetic and real water samples (synthetically spiked) maintaining high selectivity. The optimized values of axial dispersion coefficient (Ez) and fixed bed mass transfer coefficient (kfb) were estimated and subsequently used for the scale up studies to predict column life. The adsorbent beads were regenerated using 0.05 M EDTA aqueous solution and showed good reusability (>95.00%) after 5 cycles of operation. Overall, this work highlights a reusable Hg adsorbent possessing good selectivity and capacity and simultaneously demonstrating real-field applicability.

Optimization of multi flow rate loading strategy for process intensification of Protein A chromatography

Monoclonal antibody (mAb) is a widely used therapeutic modality that is being used for treatment of chronic diseases like cancer, psoriasis, and other auto immune diseases. The affordability of these therapeutics is presently low because of their high manufacturing cost. Protein A chromatography step is a major contributor to the cost of manufacturing of mAbs. The proposed study is an attempt to improve process performance of the protein A chromatography step using multi-flow loading strategy. Although continuous chromatography is an efficient tool to improve resin utilization and process productivity, implementation of continuous chromatography warrants additional capital investment. Use of dual flow rate or multi flow rate offers the potential of attaining similar benefit without this additional investment. For optimization of multi flow rate loading strategy, it is necessary to understand the range of operating flow rate, switch time for changing flow rate to next flow rate and the delta change in the flow rate. In the current study, an alternate, industrially feasible and scalable multi flow rate strategy has been developed, which optimizes the switch time for a given set of flow rates. The algorithm uses LDF (linear driving force) model to predict the breakthrough curve. Further, the method optimizes flow trajectory based on simulated breakthrough curves using estimated diffusion coefficients at specific residence times and suggests a switch time strategy leading to a multi-step loading of increasing residence times. It was observed that by operating the process at multiple flow rates, a near maxima of both adsorbent capacity and the productivity can be achieved. Although variable flow rate approaches have been proposed in literature in recent times, our method for multi-step loading is simpler, practical and has been demonstrated both at lab and pilot scales. The results showed that this simple multi-flow loading approach increased loading capacities by ∼20% and resin utilization by ∼15% as compared to regular batch process; with new generation protein A resin, mAb Select PrismATM, as capture chromatography. Approximately 60% reduction in $COGS/g has been demonstrated when compared to constant flow batch process, similar to the benefits obtained with multi-column continuous chromatography.

Mechanochemical synthesis of a robust cobalt-based metal–organic framework for adsorption separation methane from nitrogen

Efficient capture dilute methane (CH4) from nitrogen (N2) is of significant importance in both environment and economical aspects. However, CH4/N2 separation is still a great challenge in gas separation field limited by their close physical properties. Herein, we developed the mechanochemical synthesis of a cobalt-based pillar-layer metal–organic framework, Co(AIP)(BPY)0.5, for adsorption separation of CH4/N2 mixture. This synthetic method allowed Co(AIP)(BPY)0.5 accessible rapidly and sustainably at the gram scale. By varying the grinding time, a series of mechanochemically synthesized Co(AIP)(BPY)0.5 products were obtained and CO2 adsorption measurements confirmed that Co(AIP)(BPY)0.5–25 obtained by grinding for 25 min had the highest porosity. Then CH4/N2 adsorption and separation of the resulting Co(AIP)(BPY)0.5–25 was studied. CH4 and N2 uptakes of Co(AIP)(BPY)0.5–25 were 1.03 and 0.26 mmol/g at 298 K and 5 bar, showing preferential adsorption of CH4 over N2 and the CH4/N2 selectivity with 7.3. Meanwhile, the excellent potential separation ability of CH4/N2 mixtures with different concentrations on Co(AIP)(BPY)0.5–25 was confirmed by simulated breakthrough experiments. Molecular simulations revealed that spheroidal CH4 molecules were located in the center of the pores while most of linear N2 molecules were only distributed near the walls of the pores due to the difference in geometrical structures. This work provides an example of rapid mechanochemical synthesis of Co(AIP)(BPY)0.5 within short time for separating CH4/N2 mixture.

Modeling of Ion Exchange Processes to Optimize Metal Removal from Complex Mine Water Matrices

The modeling of ion exchange processes could significantly enhance their applicability in mine water treatment, as the modern synthetic resins give unique advantages for the removal of metals. Accurate modeling improves the predictability of the process, minimizing the time and costs involved in laboratory column testing. However, to date, the development and boundary conditions of such ion exchange systems with complex mine waters are rarely studied and poorly understood. A representative ion exchange model requires the definition of accurate parameters and coefficients. Therefore, theoretical coefficients estimated from natural exchange materials that are available in geochemical databases often need to be modified. A 1D reactive transport model was developed based on PhreeqC code, using three case scenarios of synthetic mine waters and varying the operating conditions. The first approach was defined with default exchange coefficients from the phreeqc.dat database to identify and study the main parameters and coefficients that govern the model: cation exchange capacity, exchange coefficients, and activity coefficients. Then, these values were adjusted through iterative calibration until a good approximation between experimental and simulation breakthrough curves was achieved. This study proposes a suitable methodology and challenges for modeling the removal of metals from complex mine waters using synthetic ion exchange resins.

Performance optimization of an industrial natural gas dehydration process to reduce energy consumption and greenhouse gases (GHGs) emission

AbstractNatural gas dehydration using multi‐layer adsorption beds is one of the most essential processes in gas processing plants, where the water molecule is removed from raw gas by a continuous cyclic temperature swing adsorption operation. In the present research, a commercial adsorption unit for dehydration of natural gas has been studied, and the effects of the volume of adsorbents in the multi‐layer adsorption beds on the overall performance of the process have been investigated using a precise mathematical model. The numerical method of lines (NMOL) has been applied to solve the partial differential equations (PDEs) demonstrating the fixed bed. The real plant data from the industrial unit have been used for validation of the model. The simulated breakthrough time, bed pressure drop, and dried gas temperature are found to be in good agreement with experimental measurements with an error of less than 4%. The modelling results are applied to obtain the optimum adsorbents layers' configuration using response surface methodology (RSM). The objective functions are pressure drop and water breakthrough time, while variables are the length of two molecular sieve layers with different particle sizes, which are loaded in each adsorption column. The results indicated that an 18.45% reduction in the direct and indirect greenhouse gases (GHGs) emission (35 369.59 MT/year) during the regeneration cycle and a significant decrease in energy consumption (623 609 GJ/year) can be achieved by applying the optimal configuration. Moreover, 1 year of longer continuous operation (by avoiding nearly 45 regenerations) is another desirable outcome of the optimization.

Modeling and computational fluid dynamic simulation of acetaminophen adsorption using sugarcane bagasse

In this work, the mathematical modeling of acetaminophen (ACT) removal in a fixed-bed adsorption column using sugarcane bagasse (SB) as adsorbent was studied. Experimental data were fitted to six analytical models: Thomas, modified dose-response, Yoon-Nelson, Bohart-Adams, Wang, and Wolborska. Three experimental tests were carried out at 2.5 mL/min of flow rate, 57 mg/L of ACT concentration, and bed heights of 23, 33, and 43 cm. The predicted breakthrough curve by modified dose-response model agreed acceptably (R2 > 0.91) with experimental curves. Besides, a computational fluid dynamic (CFD) model was developed to simulate and analyze the ACT concentration inside of the adsorption column and the wall channeling effect. The simulated breakthrough curve had a good reproducibility with experimental data, the maximum error between experimental and predicted points was 7.03%. In addition, the CFD model shows a high mass transfer zone and a slow adsorption rate in all three tests of ACT adsorption; the mass transfer zone grew as the bed height increased, whereas the wall channeling effects disappeared with increasing bed height. Also, the diffusion resistances and axial dispersion phenomenon were relevant. The results of this research work demonstrate the usefulness of computational fluid dynamics analysis to understand better the adsorption process.

The effects of porosity and permeability changes on simulated supercritical CO2 migration front in tight glutenite under different effective confining pressures from 1.5 MPa to 21.5 MPa

AbstractDepending on rock pore compressibility, a change in effective confining pressure (ECP) can have a significant influence on supercritical CO2 (SC‐CO2) migration characteristics in natural reservoirs. In this study, a tight glutenite sample was used to conduct porosity/permeability measurements under different ECPs of 1.5, 5.5, 9.5, 13.5, 17.5 and 21.5 MPa. Then a SC‐CO2 drainage core flooding experiment, which was monitored using nuclear magnetic resonance (NMR) technique, was conducted at an ECP of 5.5 MPa. Measurement results show that the porosity and permeability of the sample were comparatively low (at an ECP of 1.5 MPa, 8.3% and 2.4 mD, respectively). With increasing ECP, the porosity/permeability decreased rapidly initially then more slowly at the larger ECP value. NMR results shows that SC‐CO2 preferentially displaced water creating flow channels inside the sample. At SC‐CO2 breakthrough, the average residual water saturation was 69.86%. Following breakthrough, SC‐CO2 continued to displace the water creating more substantial flow channels until they were sufficient to transport the SC‐CO2 at the fixed flow rate, resulting in a residual water saturation of 42.72%. A two‐dimensional computational model was then established based on these experimental results to simulate the fluid behaviors at an ECP of 5.5 MPa, and then the model was extended to different ECP values ranging from 1.5 to 21.5 MPa. Numerical simulation results show that SC‐CO2 displaced water in an inverted triangle‐like shape. Under different ECPs of 1.5, 5.5, 9.5, 13.5, 17.5 and 21.5 MPa, the simulated breakthrough times were 36.8, 44.6, 54.8, 56.4, 59.0 and 59.4 mins with an average SC‐CO2 saturation of 13.18, 16.71, 18.71, 19.72, 21.99 and 22.19%, respectively. SC‐CO2 breakthrough occurred quicker for lower ECP values resulting in a smaller SC‐CO2 saturation. Likewise, with larger ECP value, SC‐CO2 breakthrough occurred later, and a higher SC‐CO2 saturation was seen. © 2020 Society of Chemical Industry and John Wiley &amp; Sons, Ltd.

Numerical simulation of low-concentration CO2 adsorption on fixed bed using finite element analysis

Accurately predicting distributions of concentration and temperature field in fixed-bed column is essential for designing adsorption processes. In this study, a two-dimensional (2D), axisymmetric, nonisothermal, dynamic adsorption model was established by coupling equations of mass, momentum and energy balance, and solved by finite element analysis. The simulation breakthrough curves fit well with the low-concentration CO 2 adsorption experimental data, indicating the reliability of the established model. The distributions of concentration and temperature field in the column for CO 2 adsorption and separation from CO 2 /N 2 were obtained. The sensitivity analysis of the adsorption conditions shows that the operation parameters such as feed flow rate, feed concentration, pellet size, and column height-to-diameter ratio produce a significant effect on the dynamic adsorption performance. The multi-physics coupled 2D axisymmetric model could provide a theoretical foundation and guidance for designing CO 2 fixed-bed adsorption and separation processes, which could be extended to other mixed gases as well.

Numerical Modeling of Phenol Adsorption on Granular Activated Carbon Fixed Bed: Comparison of Two Numerical Methods to Solve the Advection-dispersion Equation

Abstract This paper presents a comparison between some numerical methods and techniques for solving the nonlinear advection-dispersion equation, which may be used to describe the adsorption of phenol into a granular activated carbon fixed bed under local equilibrium conditions. The adsorption is described by the Langmuir isotherm, which makes the advection-dispersion equation nonlinear. This equation is solved successively by using the approximation and linearization techniques. For each technique, two types of numerical algorithms are used. Concerning the first one, the Implicit and the Runge Kutta schemes are used. As for the second one, the Modified Picard iteration and the Newton Raphson scheme are applied. Simulation results have been compared to each other and to the experimental data as well. Both of the Implicit and the Runge Kutta algorithms have led to superimposed simulated breakthrough curves. Both of the modified Picard and Newton Raphson schemes have given identical results too. However, comparing to the experimental data, the obtained solution, using the approximation technique, has underestimated the retardation of solute and failed in fitting the experimental breakthrough. The Obtained solution, using the linearization technique, has correctly fitted the experimental results under all the conditions of: feed flow rate, activated carbon bed height and the inlet phenol concentration.

Developing a novel biofiltration treatment system by coupling high-rate infiltration trench technology with a plug-flow porous-media bioreactor

The sequence of two infiltration steps combined with an intermediate aeration named ‘sequential managed aquifer recharge technology (SMART)’ proved to be a promising approach to replenish groundwater using treated wastewater effluents or impaired surface waters due to efficient inactivation of pathogens and improved removal of many trace organic chemicals. To minimize the physical footprint of such systems and overcome limitations through site-specific heterogeneity at conventional MAR sites, an engineered approach was taken to further advance the SMART concept. This study investigated the establishment of plug-flow conditions in a pilot scale subsurface bioreactor by providing highly controlled hydraulic conditions. Such a system, with a substantially reduced physical footprint in comparison to conventional MAR systems, could be applied independent of local hydrogeological conditions. The desired redox conditions in the bioreactor are achieved by in-situ oxygen delivery, to maintain the homogenous flow conditions and eliminate typical pumping costs. For the time being, this study investigated hydraulic conditions and the initial performance regarding the removal of chemical constituents during baseline operation of the SMARTplus bioreactor. The fit of the observed and simulated breakthrough curves from the pulse injection tracer test indicated successful establishment of plug-flow conditions throughout the bioreactor. The performance data obtained during baseline operation confirmed similar trace organic chemical biotransformation as previously observed in lab- and field-scale MAR systems during travel times of <13 h.

Co-transport and competitive retention of different ionic rare earth elements (REEs) in quartz sand: Effect of kaolinite

The increasing excavation and utilization of rare earth elements (REEs) have resulted in an elevated release of these elements into the environment. Therefore, investigating the transport behavior of REEs is critical for a comprehensive understanding of their geochemical cycles and to propose potential pollution control strategies. This study investigated the transport, co-transport, and competitive retention of three REEs: La (a light REE), Gd (a middle REE), and Yb (a heavy REE), as well as the co-transport of REEs and kaolinite (a representative clay mineral) in porous media. Both observed and simulated breakthrough curves and retention profiles demonstrated that all ionic REEs exhibited considerable breakthrough and slight retention with almost uniform shapes in quartz sand (QS) owing to the weak affinity of ionic REEs to QS. The breakthrough of REEs in all experiments followed the order of La > Gd > Yb, indicating that REE breakthrough increased with decreasing atomic number. The same elements exhibited their highest breakthrough during the co-transport of the three REEs, followed by co-transport of two REEs, and finally single transport. Furthermore, mathematical modeling indicated that the retention of REEs in QS was a predominantly kinetic process, whereby competitive blocking was the dominant mechanism for the enhanced breakthrough of REEs during co-transport, as compared to single transport. The co-transport of REEs and kaolinite demonstrated that kaolinite has a slight influence on the transport of REEs in QS under adsorption kinetics. However, REEs inhibited the transport and strongly enhanced the retention of kaolinite in QS due to a decreasing electrostatic repulsion between kaolinite and QS in the presence of REEs, even if the adsorption of REEs onto kaolinite was weak under adsorption kinetics. Therefore, this study increases our understanding of the transport mechanisms of REEs in the environment.

Robust Bimetallic Ultramicroporous Metal-Organic Framework for Separation and Purification of Noble Gases.

Noble gases, especially krypton (Kr) and xenon (Xe), are widely applied in diverse fields. Developing new techniques and adsorbents to separate and purify Kr and Xe is in high demand. Herein, we reported a bimetallic metal-organic framework (MOF) (NKMOF-1-Ni) which possesses a narrow pore size (5.36 Å) and ultrahigh stability (e.g., stable in water for 1.5 years). Gas sorption measurements revealed that this MOF possessed much higher uptake for Xe than for Kr, Ar, or N2 at room temperature in all pressure ranges. The calculation of adsorption isosteric heat and Grand Canonical Monte Carlo simulation verified that NKMOF-1-Ni had a stronger interaction with Xe than other tested gases. The results of ideal adsorbed solution theory selectivity and simulated breakthrough further showed that NKMOF-1-Ni had an outstanding separation performance of Xe/Kr, Xe/Ar, and Xe/N2. This study provides important guidance for future research to synthesize ideal sorbents to separate noble gases.

Understanding How Ligand Functionalization Influences CO2 and N2 Adsorption in a Sodalite Metal-Organic Framework.

In this work, a detailed study is conducted to understand how ligand substitution influences the CO2 and N2 adsorption properties of two highly crystalline sodalite metal-organic frameworks (MOFs) known as Cu-BTT (BTT-3 = 1,3,5-benzenetristetrazolate) and Cu-BTTri (BTTri-3 = 1,3,5-benzenetristriazolate). The enthalpy of adsorption and observed adsorption capacities at a given pressure are significantly lower for Cu-BTTri compared to its tetrazole counterpart, Cu-BTT. In situ X-ray and neutron diffraction, which allow visualization of the CO2 and N2 binding sites on the internal surface of Cu-BTTri, provide insights into understanding the subtle differences. As expected, slightly elongated distances between the open Cu2+ sites and surface-bound CO2 in Cu-BTTri can be explained by the fact that the triazolate ligand is a better electron donor than the tetrazolate. The more pronounced Jahn-Teller effect in Cu-BTTri leads to weaker guest binding. The results of the aforementioned structural analysis were complemented by the prediction of the binding energies at each CO2 and N2 adsorption site by density functional theory calculations. In addition, variable temperature in situ diffraction measurements shed light on the fine structural changes of the framework and CO2 occupancies at different adsorption sites as a function of temperature. Finally, simulated breakthrough curves obtained for both sodalite MOFs demonstrate the materials' potential performance in dry postcombustion CO2 capture. The simulation, which considers both framework uptake capacity and selectivity, predicts better separation performance for Cu-BTT. The information obtained in this work highlights how ligand substitution can influence adsorption properties and hence provides further insights into the material optimization for important separations.

Highly rapid mechanochemical synthesis of a pillar-layer metal-organic framework for efficient CH4/N2 separation

Efficient capture of methane (CH4) from nitrogen (N2) by adsorption separation remains a challenge. In this work, we demonstrate the first solvent-free mechanochemical synthesis of a zinc-based pillar-layer MOF Zn2(5-aip)2(bpy) (1) within minutes, making 1 accessible via a rapid and green route. By rational control of grinding time, the resulting product of 1–4 (which stands for grinding 4 min) has the optimal porosity confirmed by using CO2 as the probe gas. For the recovery of CH4 from N2 at 5.0 bar and 298 K, the adsorption uptakes of CH4 and N2 for 1–4 are 1.10 and 0.27 mmol/g, exhibiting preferential adsorption CH4 over N2 with high CH4/N2 selectivity of 7.0. The high selectivity of CH4/N2 in 1–4 is mainly ascribed to the difference in affinity interactions between the pore walls and gas molecules, confirmed by experimental adsorption heat and molecular simulation. Two CH4 molecules can enter in the same pores, but most of the pores can only adsorb one N2 molecule. Furthermore, the dynamic separation performance for CH4/N2 mixture in 1–4 is verified by simulated breakthrough curves. The unprecedentedly rapid solvent-free mechanochemical synthesis within minutes makes 1 easily accessible at the gram scale via an environmentally friendly method for accelerating potential application of CH4/N2 separation.