Molecular Simulation Insights on Xe/Kr Separation in a Set of Nanoporous Crystalline Membranes

Fine-Tuning Microporosity of Crystalline Vanadomolybdate Frameworks for Selective Adsorptive Separation of Kr from Xe

Selective adsorptive capture and separation of chemically inert krypton (Kr) and xenon (Xe) noble gases with very low ppmv concentrations in air and industrial off-gases constitute an important technological challenge. Here, using a synergistic combination of experiment and theory, the microporous crystalline vanadomolybdates (MoVOx) as highly selective Kr sorbents are studied in detail. By varying the Mo/V ratios, we show for the first time that their one-dimensional (1D) pores can be fine-tuned for the size-selective adsorption of Kr over the larger Xe with selectivities reaching >100. Using extensive electronic structure calculations and grand canonical Monte Carlo simulations, the competition between Kr uptake with CO2 and N2 was also investigated. As most materials reported so far are selective toward the larger, more polarizable Xe than Kr, this work constitutes an important step toward robust Kr-selective sorbent materials. This work highlights the potential use of porous crystalline transition metal oxides as energy-efficient and selective noble gas capture sorbents for industrial applications.

Exploring the Potential of a Highly Scalable Metal-Organic Framework CALF-20 for Selective Gas Adsorption at Low Pressure

In this study, the ability of the highly scalable metal-organic framework (MOF) CALF-20 to adsorb polar and non-polar gases at low pressure was investigated using grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations. The results from the simulated adsorption isotherms revealed that the highest loading was achieved for SO2 and Cl2, while the lowest loading was found for F2 molecules. The analysis of interaction energies indicated that SO2 molecules were able to form the strongest adsorbent-adsorbate interactions and had a tight molecular packing due to their polarity and angular structure. Additionally, Cl2 gas was found to be highly adsorbed due to its large van der Waals surface and strong chemical affinity in CALF-20 pores. MD simulations showed that SO2 and Cl2 had the lowest mobility inside CALF-20 pores. The values of the Henry coefficient and isosteric heat of adsorption confirmed that CALF-20 could selectively adsorb SO2 and Cl2. Based on the results, it was concluded that CALF-20 is a suitable adsorbent for SO2 and Cl2 but not for F2. This research emphasizes the importance of molecular size, geometry, and polarity in determining the suitability of a porous material as an adsorbent for specific adsorbates.

Shell-like Xenon Nano-Traps within Angular Anion-Pillared Layered Porous Materials for Boosting Xe/Kr Separation

Adsorptive separation of xenon (Xe) and krypton (Kr) is a promising technique but remains a daunting challenge since they are atomic gases without dipole or quadruple moments. Herein we report a strategy for fabricating angular anion-pillared materials featuring shell-like Xe nano-traps, which provide a cooperative effect conferred by the pore confinement and multiple specific interactions. The perfect permanent pore channel (4-5 Å) of Ni(4-DPDS)₂ MO₄ (M=Cr, Mo, W) can host Xe atoms efficiently even at ultra-low concentration (400 ppm Xe), showing the second-highest selectivity of 30.2 in Ni(4-DPDS)₂ WO₄ and excellent Xe adsorption capacity in Ni(4-DPDS)₂ CrO₄ (15.0 mmol kg^-1 ). Crystallography studies and DFT-D calculations revealed the energy favorable binding sites and angular anions enable the synergism between optimal pore size and polar porosity for boosting Xe affinity. Dynamic breakthrough experiments demonstrated three MOFs as efficient adsorbents for Xe/Kr separation.

Separation of SO2 and NO2 with the Zeolite Membrane: Molecular Simulation Insights into the Advantageous NO2 Dimerization Effect

NO₂ and SO₂, as valuable chemical feedstock, are worth being recycled from flue gases. The separation of NO₂ and SO₂ is a key process step to enable practical deployment. This work proposes SO₂ separation from NO₂ using chabazite zeolite (SSZ-13) membranes and provides insights into the feasibility and advantages of this process using molecular simulation. Grand canonical ensemble Monte Carlo and equilibrium molecular dynamics methods were respectively adopted to simulate the adsorption equilibria and diffusion of SO₂, NO₂, and N₂O₄ on SSZ-13 at varying Si/Al (1, 5, 11, 71, +∞), temperatures (248-348 K), and pressures (0-100 kPa). The adsorption capacity and affinity (SO₂ > N₂O₄ > NO₂) demonstrated strong competitive adsorption of SO₂ based on dual-site interactions and significant reduction in NO₂ adsorption due to dimerization in the ternary gas mixture. The simulated order of diffusivity (NO₂ > SO₂ > N₂O₄) on SSZ-13 demonstrated rapid transport of NO₂, strong temperature dependence of SO₂ diffusion, and the impermeability of SSZ-13 to N₂O₄. The membrane permeability of each component was simulated, rendering a SO₂/NO₂ membrane separation factor of 26.34 which is much higher than adsorption equilibrium (6.9) and kinetic (2.2) counterparts. The key role of NO₂-N₂O₄ dimerization in molecular sieving of SO₂ from NO₂ was addressed, providing a facile membrane separation strategy at room temperature.

Thermodynamic exploration of xenon/krypton separation based on a high-throughput screening

Nanoporous framework materials are a promising class of materials for energy-efficient technology of xenon/krypton separation by physisorption. Many studies on Xe/Kr separation by adsorption have focused on the determination of structure/property relationships, the description of theoretical limits of performance, and the identification of top-performing materials. Here, we provide a study based on a high-throughput screening of the adsorption of Xe, Kr, and Xe/Kr mixtures in 12 020 experimental MOF materials, to provide a better comprehension of the thermodynamics behind Xe/Kr separation in nanoporous materials and the microscopic origins of Xe/Kr selectivity at both low and ambient pressure.

Deep learning combined with IAST to screen thermodynamically feasible MOFs for adsorption-based separation of multiple binary mixtures

The structures of metal-organic frameworks (MOFs) can be tuned to reproducibly create adsorption properties that enable the use of these materials in fixed-adsorption beds for non-thermal separations. However, with millions of possible MOF structures, the challenge is to find the MOF with the best adsorption properties to separate a given mixture. Thus, computational, rather than experimental, screening is necessary to identify promising MOF structures that merit further examination, a process traditionally done using molecular simulation. However, even molecular simulation can become intractable when screening an expansive MOF database for their separation properties at more than a few composition, temperature, and pressure combinations. Here, we illustrate progress toward an alternative computational framework that can efficiently identify the highest-performing MOFs for separating various gas mixtures at a variety of conditions and at a fraction of the computational cost of molecular simulation. This framework uses a "multipurpose" multilayer perceptron (MLP) model that can predict single component adsorption of various small adsorbates, which, upon coupling with ideal adsorbed solution theory (IAST), can predict binary adsorption for mixtures such as Xe/Kr, CH₄/CH₆, N₂/CH₄, and Ar/Kr at multiple compositions and pressures. For this MLP+IAST framework to work with sufficient accuracy, we found it critical for the MLP to make accurate predictions at low pressures (0.01-0.1 bar). After training a model with this capability, we found that MOFs in the 95th and 90th percentiles of separation performance determined from MLP+IAST calculations were 65% and 87%, respectively, the same as MOFs in the simulation-predicted 95th percentile across several mixtures at diverse conditions (on average). After validating our MLP+IAST framework, we used a clustering algorithm to identify "privileged" MOFs that are high performing for multiple separations at multiple conditions. As an example, we focused on MOFs that were high performing for the industrially relevant separations 80/20 Xe/Kr at 1 bar and 80/20 N₂/CH₄ at 5 bars. Finally, we used the MOF free energies (calculated on our entire database) to identify privileged MOFs that were also likely synthetically accessible, at least from a thermodynamic perspective.

Multiscale Computational Screening of Metal-Organic Frameworks for Kr/Xe Adsorption Separation: A Structure-Property Relationship-Based Screening Strategy

The separation of radioactive noble gases, such as Xe and Kr, has attracted special attention in the context of used nuclear fuel (UNF). In this study, 180 metal-organic frameworks (MOFs) formally used for selective adsorptions of ethane and ethylene, with a similar kinetic diameter to Kr and Xe, were initially screened for the Kr/Xe separation using the grand canonical Monte Carlo (GCMC) method. Then, the structure-adsorption property relationships were generalized, that is, the MOFs of higher Kr/Xe selectivity are with the porosity at 0.2-0.4 and the ratio of the largest cavity diameter/pore limiting diameter at 1.0-2.4. Based on the relationships, six reported MOFs with large Kr uptakes and Kr/Xe selectivities were experimentally screened out and validated by GCMC simulations within the CoRE-MOF database, which are higher than most reported MOFs under conditions pertinent to nuclear fuel reprocessing of an 80/20 v/v mixture of Kr/Xe at normal temperature and pressure. Further simulations reveal that higher Kr uptakes and Kr/Xe selectivities of six MOFs result from the confinement effect of the pores. Molecular dynamic simulations showed that the six MOFs are ideal membrane separation materials of Kr from Xe, which are driven by adsorption and diffusion. Analyses of electronic structure-based density functional theory calculations showed that the main interaction between Kr and the six MOFs is van der Waals force dominated by dispersion and induction interactions. Therefore, the generalized structure-adsorption property relationships may assist the screening of MOFs for the separation and production of Kr/Xe from UNF industrially.

High-Silica CHA Zeolite Membrane with Ultra-High Selectivity and Irradiation Stability for Krypton/Xenon Separation

Capture and storage of the long‐lived ⁸⁵Kr is an efficient approach to mitigate the emission of volatile radionuclides from the spent nuclear fuel reprocessing facilities. However, it is challenging to separate krypton (Kr) from xenon (Xe) because of the chemical inertness and similar physical properties. Herein we prepared high‐silica CHA zeolite membranes with ultra‐high selectivity and irradiation stability for Kr/Xe separation. The suitable aperture size and rigid framework endures the membrane a strong size‐exclusion effect. The ultrahigh selectivity of 51–152 together with the Kr permeance of 0.7–1.3×10⁻⁸ mol m⁻² s⁻¹ Pa⁻¹ of high‐silica CHA zeolite membranes far surpass the state‐of‐the‐art polymeric membranes. The membrane is among the most stable polycrystalline membranes for separation of humid Kr/Xe mixtures. Together with the excellent irradiation stability, high‐silica CHA zeolite membranes pave the way to separate radioactive Kr from Xe for a notable reduction of the volatile nuclear waste storage volume.

Pore Size Control via Multiple-Site Alkylation to Homogenize Sub-Nanoporous Covalent Organic Frameworks for Efficient Sieving of Xenon/Krypton

Among various fission products generated in nuclear reactors, xenon and krypton are two important fission gases with high flow, diffusivity, and radioactivity. Moreover, xenon isolated from these products is an expensive industrial resource with wide applications in medicine and lighting, which makes the development of efficient methods for separation of xenon/krypton significant. However, it is usually difficult for xenon/krypton to be adsorbed by chemical adsorbents due to their inert gas properties, and sub-nanoporous adsorbents proven to be workable for the separation of xenon/krypton are still hard to prepare and regulate the pore size. Herein, we report two novel sub-nanoporous covalent organic frameworks (COFs), which were applied to the sieving of xenon/krypton for the first time. The sub-nanoporous COFs were synthesized via aldehyde-amine polycondensation reactions and the subsequent pore size regulation and homogenization process by using a facile, operational, and efficient multiple-site alkylation strategy. Impressively, the as-prepared sub-nanoporous COFs realized the efficient adsorption and sieving of xenon/krypton owing to their slightly larger pore sizes (∼7 Å) than the dynamic diameters of xenon/krypton and their larger pore volumes. The maximum adsorption capacity for xenon is up to 85.6 cm³/g, and the xenon/krypton selectivity can reach to 9.7. Moreover, the as-prepared COFs possess good γ-ray irradiation stability, which endows them with great potentials for the sieving of radioactive xenon/krypton in the practical application. The multiple-site alkylation strategy proposed in this study provides a valuable approach for the pore construction and control of the porous materials, especially the sub-nanoporous adsorption materials.

A mini-review on recent developments in SAPO-34 zeolite membranes and membrane reactors

Schematic diagram of a SAPO-34 membrane for various gas separation.

Adsorption Isotherm Predictions for Multiple Molecules in MOFs Using the Same Deep Learning Model

Tailoring the structure and chemistry of metal-organic frameworks (MOFs) enables the manipulation of their adsorption properties to suit specific energy and environmental applications. As there are millions of possible MOFs (with tens of thousands already synthesized), molecular simulation has frequently been used to rapidly evaluate the adsorption performance of a large set of MOFs. This allows subsequent experiments to focus only on a small subset of the most promising MOFs. In many instances, however, even molecular simulation becomes prohibitively time-consuming, underscoring the need for alternative screening methods, such as machine learning, to precede molecular simulation efforts. In this study, as a proof of concept, we trained a neural network-specifically, a multilayer perceptron (MLP)-as the first example of a machine learning model capable of predicting full adsorption isotherms of different molecules not included in the training of the model. To achieve this, we trained our MLP on "alchemical" species, represented only by variables derived from their force-field parameters, to predict the loadings of real adsorbates. Alchemical species used for training were small, near-spherical, and nonpolar, enabling the prediction of analogous real molecules relevant for chemical separations such as argon, krypton, xenon, methane, ethane, and nitrogen. MOFs were also represented by simple descriptors (e.g., geometric properties and chemical moieties). The trained model was shown to make accurate adsorption predictions for these six adsorbates in both hypothetical and existing MOFs. The MLP presented here is not expected to be applied "as is" to more complex adsorbates with properties not considered during its training. However, our results illustrate a new philosophy of training that can be built upon with the goal of predicting adsorption isotherms in not only a database of MOFs but also a database of adsorbates and over a range of relevant operating conditions.

Squeezing the box: isoreticular contraction of pyrene-based linker in a Zr-based metal–organic framework for Xe/Kr separation

A new Zr-based metal–organic framework with ftw topology, NU-1106, was synthesized using 1,3,6,8-pyrene tetracarboxylate and studied for its Xe/Kr separation capabilities.

Micro-scale effects of nano-SiO2 modification with silane coupling agents on the cellulose/nano-SiO2 interface

In this study, molecular dynamics simulations were used to investigate the micro-scale effects of modification of nano-SiO₂ with commonly used silane coupling agents (KH550, KH560, KH570, and KH792) on the cellulose/nano-SiO₂ interface. The relative optimum silane coupling agent and grafting density for nano-SiO₂ modification to improve the cellulose/nano-SiO₂ interface were determined. The results showed that at the same grafting density, modification of nano-SiO₂ with KH792 yielded the highest interfacial binding energy and binding energy density, the largest number of hydrogen bonds at the cellulose/nano-SiO₂ interface, the strongest binding to the cellulose chains, and the largest overlapping area at the cellulose/nano-SiO₂ interface. We found that the non-bonding interaction energy played a decisive role in the energy of the model system and the interfacial interaction force mainly consisted of van der Waals forces and the hydrogen-bonding energy. When silane coupling agents with amino groups (KH550 and KH792) were used to modify nano-SiO₂, the number of hydrogen bonds at the cellulose/nano-SiO₂ interface was larger than that for unmodified nano-SiO₂. When silane coupling agents without amino groups (KH560 and KH570) were used to modify nano-SiO₂, the number of hydrogen bonds at the cellulose/nano-SiO₂ interface was lower than the case for unmodified nano-SiO₂. Nano-SiO₂ modification with various amounts of KH792 was investigated. The results showed that the interfacial bonding energy increased with grafting density. When the grafting density was 1.57 nm^-2, the interfacial bonding energy and number of hydrogen bonds formed at the cellulose/nano-SiO₂ interface was relatively stable, which indicates that the interface had reached a relatively stable state. Modification of nano-SiO₂ with KH792 achieved the greatest improvement of the cellulose/nano-SiO₂ interface; this interface reached a relatively stable state when the grafting density of KH792 was 1.57 nm^-2.

Fast and selective fluoride ion conduction in sub-1-nanometer metal-organic framework channels

Biological fluoride ion channels are sub-1-nanometer protein pores with ultrahigh F⁻ conductivity and selectivity over other halogen ions. Developing synthetic F⁻ channels with biological-level selectivity is highly desirable for ion separations such as water defluoridation, but it remains a great challenge. Here we report synthetic F⁻ channels fabricated from zirconium-based metal-organic frameworks (MOFs), UiO-66-X (X = H, NH₂, and N⁺(CH₃)₃). These MOFs are comprised of nanometer-sized cavities connected by sub-1-nanometer-sized windows and have specific F⁻ binding sites along the channels, sharing some features of biological F⁻ channels. UiO-66-X channels consistently show ultrahigh F⁻ conductivity up to ~10 S m⁻¹, and ultrahigh F⁻/Cl⁻ selectivity, from ~13 to ~240. Molecular dynamics simulations reveal that the ultrahigh F⁻ conductivity and selectivity can be ascribed mainly to the high F⁻ concentration in the UiO-66 channels, arising from specific interactions between F⁻ ions and F⁻ binding sites in the MOF channels.

While biological fluoride ion channels display excellent F⁻ conductivity and selectivity, designing synthetic analogues remains highly challenging. Here the authors show that zirconium-based metal–organic frameworks with F⁻ binding sites and sub-1-nanometer channels exhibit ultrahigh F⁻ conductivity and selectivity.

Selective separation of Xe/Kr and adsorption of water in a microporous hydrogen-bonded organic framework

We have studied the adsorption properties of Xe and Kr in a highly microporous hydrogen-bonded organic framework based on 1,3,5-tris(4-carboxyphenyl)benzene, named HOF-BTB. HOF-BTB can reversibly adsorb both noble gases, and it shows a higher affinity for Xe than Kr. At 1 bar, the adsorption amounts of Xe were 3.37 mmol g⁻¹ and 2.01 mmol g⁻¹ at 273 K and 295 K, respectively. Ideal adsorbed solution theory (IAST) calculation predicts selective separation of Xe over Kr from an equimolar binary Xe/Kr mixture, and breakthrough experiments demonstrate the efficient separation of Xe from the Xe/Kr mixture under a dynamic flow condition. Consecutive breakthrough experiments with simple regeneration treatment at 298 K reveal that HOF-BTB would be an energy-saving adsorbent in an adsorptive separation process, which could be attributed to the relatively low isosteric heat (Q_st) of adsorption of Xe. The activated HOF-BTB is very stable in both water and aqueous acidic solutions for more than one month, and it also shows a well-preserved crystallinity and porosity upon water/acid treatment. Besides, HOF-BTB adsorbs about 30.5 wt%, the highest value for HOF materials, of water vapor during the adsorption–desorption cycles, with a 19% decrease in adsorption amounts of water vapor after five cycles.

A highly robust microporous hydrogen-bonded organic framework selectively separates Xe from Kr, as well as efficiently adsorbs water vapor.

Increasing topological diversity during computational “synthesis” of porous crystals: how and why

Effectively tuning the properties of porous crystals could lead to breakthroughs in areas such as molecular separation, chemical sensing, and catalysis.

Computational Exploration of IRMOFs for Xenon Separation from Air

Metal-organic frameworks (MOFs) found their well-deserved position in the field of gas adsorption and separation because of their unique properties. The separation of xenon from different gas mixtures containing this valuable and essential noble gas is also benefited from the exciting nature of MOFs. In this research, we chose a series of isoreticular MOFs as our study models to apply advanced molecular simulation techniques in the context of xenon separation from air. We investigated the separation performance of our model set through simulation of ternary gas adsorption isotherms and consequent calculation of separation performance descriptors, finding out that IRMOF-7 shows better recovering capabilities compared to the other studied MOFs. We benefited from visualization of xenon energy landscape within MOFs to obtain valuable information on possible reasoning behind our observations. We also examined temperature-based separation performance boosting strategy. Additionally, we noted that although promising candidates are present among the studied MOFs for xenon recovery from air, they are not suitable for xenon recovery from exhaled anesthetic gas mixture.

One-Pot Synthesis of High-Flux b-Oriented MFI Zeolite Membranes for Xe Recovery

We demonstrate that b-oriented MFI (Mobil Five) zeolite membranes can be manufactured by in situ crystallization using an intermediate amorphous SiO₂ layer. The improved in-plane growth by using a zeolite growth modifier leads to fusion of independent crystals and eliminates boundary gaps, giving good selectivity in the separation of CO₂/Xe mixtures. The fast diffusion of CO₂ dominates the overall membrane selectivity toward the CO₂/Xe mixture. Because of the straight and short [010] channels, the obtained CO₂ permeation fluxes are several orders of magnitude higher than those of carbon molecular sieving membranes and polymeric membranes, opening opportunities for Xe recovery from waste anesthetic gas.

Recovery of xenon from air over ZIF-8 membranes

ZIF-8 membranes effectively separated air/Xe gas mixtures via molecular sieving, preferential adsorption, and diffusivity differences.