Opening the Toolbox: 18 Experimental Techniques for Measurement of Mixed Gas Adsorption

Mind the Gap: The Role of Mass Transfer in Shaped Nanoporous Adsorbents for Carbon Dioxide Capture

Adsorptive separations by nanoporous materials are major industrial processes. The industrial importance of solid adsorbents is only expected to grow due to the increased focus on carbon dioxide capture technology and energy-efficient separations. To evaluate the performance of an adsorbent and design a separation process, the adsorption thermodynamics and kinetics must be known. However, although diffusion kinetics determine the maximum production rate in any adsorption-based separation, this aspect has received less attention due to the challenges associated with conducting diffusion measurements. These challenges are exacerbated in the study of shaped adsorbents due to the presence of porosity at different length scales. As a result, adsorbent selection typically relies mainly on adsorption properties at equilibrium, i.e., uptake capacity, selectivity and adsorption enthalpy. In this Perspective, based on an extensive literature review on mass transfer of CO2 in nanoporous adsorbents, we discuss the importance and limitations of measuring diffusion in nanoporous materials, from the powder form to the adsorption bed, considering the nature of the process, i.e., equilibrium-based or kinetic-based separations. By highlighting the lack of and discrepancies between published diffusivity data in the context of CO2 capture, we discuss future challenges and opportunities in studying mass transfer across scales in adsorption-based separations.

Adsorption of Natural Gas in Metal-Organic Frameworks: Selectivity, Cyclability, and Comparison to Methane Adsorption

Evaluation of metal-organic frameworks (MOFs) for adsorbed natural gas (ANG) technology employs pure methane as a surrogate for natural gas (NG). This approximation is problematic, as it ignores the impact of other heavier hydrocarbons present in NG, such as ethane and propane, which generally have more favorable adsorption interactions with MOFs compared to methane. Herein, using quantitative Raman spectroscopic analysis and Monte Carlo calculations, we demonstrate the adsorption selectivity of high-performing MOFs, such as MOF-5, MOF-177, and SNU-70, for a methane and ethane mixture (95:5) that mimics the composition of NG. The impact of selectivity on the storage and deliverable capacities of these adsorbents during successive cycles of adsorption and desorption, simulating the filling and emptying of an ANG tank, is also demonstrated. The study reveals a gradual reduction in the storage performance of MOFs, particularly with smaller pore volumes, due to ethane accumulation over long-term cycling, until a steady state is reached with substantially degraded storage performance.

The Challenge of Water Competition in Physical Adsorption of CO2 by Porous Solids for Carbon Capture Applications - A Short Perspective

With ever-increasing efforts to design sorbent materials to capture carbon dioxide from flue gas and air, this perspective article is provided based on nearly a decade of collaboration across science, engineering, and industry partners. A key point learned is that a holistic view of the carbon capture problem is critical. While researchers can be inclined to value their own fields and associated metrics, often, key parameters are those that enable synergy between materials and processes. While the role of water in the chemisorption of CO2 is well-studied, in this perspective, it is hoped to highlight the often-overlooked but critical role of water in assessing the potential of a physical adsorbent for CO2 capture. This is a challenge that requires interdisciplinarity. As such, this document is written for a general audience rather than experts in any specific discipline.

Does Mixed Linker-Induced Surface Heterogeneity Impact the Accuracy of IAST Predictions in UiO-66-NH2?

To move toward more energy-efficient adsorption-based processes, there is a need for accurate multicomponent data under realistic conditions. While the Ideal Adsorbed Solution Theory (IAST) has been established as the preferred prediction method due to its simplicity, limitations and inaccuracies for less ideal adsorption systems have been reported. Here, we use amine-functionalized derivatives of the UiO-66 structure to change the extent of homogeneity of the internal surface toward the adsorption of the two probe molecules carbon dioxide and ethylene. Although it might seem plausible that more functional groups lead to more heterogeneity and, thus, less accurate predictions by IAST, we find a mixed-linker system with increased heterogeneity in terms of added adsorption sites where IAST predictions and experimental loadings agree exceptionally well. We show that incorporating uncertainty analysis into predictions with IAST is important for assessing the accuracy of these predictions. Energetic investigations combined with Grand Canonical Monte Carlo simulations reveal almost homogeneous carbon dioxide but heterogeneous ethylene adsorption in the mixed-linker material, resulting in local, almost pure phases of the individual components.

Efficient Exploration of Adsorption Space for Separations in Metal-Organic Frameworks Combining the Use of Molecular Simulations, Machine Learning, and Ideal Adsorbed Solution Theory

Adsorption-based separations using metal-organic frameworks (MOFs) are promising candidates for replacing common energy-intensive separation processes. The so-called adsorption space formed by the combination of billions of possible molecules and thousands of reported MOFs is vast. It is very challenging to comprehensively evaluate the performance of MOFs for chemical separation through experiments. Molecular simulations and machine learning (ML) have been widely applied to make predictions for adsorption-based separations. Previous ML approaches to these issues were typically limited to smaller molecules and often had poor accuracy in the dilute limit. To enable exploration of a wider adsorption space, we carefully selected a diverse set of 45 molecules and 335 MOFs and generated single-component isotherms of 15,075 MOF-molecule pairs by grand canonical Monte Carlo. Using this database, we successfully developed accurate (r2 > 0.9) machine learning models predicting adsorption isotherms of diverse molecules in large libraries of MOFs. With this approach, we can efficiently make predictions of large collections of MOFs for arbitrary mixture separations. By combining molecular simulation data and ML predictions with Ideal Adsorbed Solution Theory, we tested the ability of these approaches to make predictions of adsorption selectivity and loading for challenging near-azeotropic mixtures.

High-Pressure Gravimetric Measurements for Binary Gas Adsorption Equilibria and Comparisons with Ideal Adsorbed Solution Theory (IAST)

Measurements of gas mixture adsorption equilibria at high pressures are important for assessing actual adsorbent selectivities but are often out of reach, given the challenging nature of the required experiments. Here, we report a high-pressure gravimetric binary gas adsorption equilibrium measurement system based on simultaneous gas density and mixture adsorption measurements in a single gas cell coupled to a magnetic-suspension balance. Compared to traditional techniques which rely on analytical measurements of gas composition, this approach does not require any sampling. Adsorption measurements of two gas mixtures (0.500 N2 + 0.500 CH4 and 0.400 N2 + 0.600 CO2, mole fraction) on a commercially available molecular sieve (NaY, sodium molecular sieve type Y) were carried out in the temperature range 282 to 325 K with a pressure up to 10 MPa. A prediction method for the gas mixture adsorption equilibria in a closed system using the ideal adsorbed solution theory (IAST) model was used to compare the experimental results. For binary mixtures of components with similar adsorption capacities (here N2 and CH4), the system can measure the adsorption equilibria at pressures higher than 1.0 MPa and the result agrees well with the IAST model prediction. For two gases with very different adsorption capacities, the uncertainty in the adsorption equilibrium measurement is much larger. The dominant uncertainty source is the gas density measurement, whose uncertainty could potentially be cut to half if the current titanium sinker is replaced with a sinker made of single-crystal silicon and with a larger volume.

Carbon dioxide separation and capture by adsorption: a review

Rising adverse impact of climate change caused by anthropogenic activities is calling for advanced methods to reduce carbon dioxide emissions. Here, we review adsorption technologies for carbon dioxide capture with focus on materials, techniques, and processes, additive manufacturing, direct air capture, machine learning, life cycle assessment, commercialization and scale-up.

Sorption of CO2, CH4 and Their Mixtures in Amorphous Poly(2,6-dimethyl-1,4-phenylene)oxide (PPO)

Sorption of pure CO₂ and CH₄ and CO₂/CH₄ binary gas mixtures in amorphous glassy Poly(2,6-dimethyl-1,4-phenylene) oxide (PPO) at 35 °C up to 1000 Torr was investigated. Sorption experiments were carried out using an approach that combines barometry with FTIR spectroscopy in the transmission mode to quantify the sorption of pure and mixed gases in polymers. The pressure range was chosen to prevent any variation of the glassy polymer density. The solubility within the polymer of the CO₂ present in the gaseous binary mixtures was practically coincident with the solubility of pure gaseous CO₂, up to a total pressure of the gaseous mixtures equal to 1000 Torr and for CO₂ mole fractions of ~0.5 mol mol^-1 and ~0.3 mol mol^-1. The Non-Equilibrium Thermodynamics for Glassy Polymers (NET-GP) modelling approach has been applied to the Non-Random Hydrogen Bonding (NRHB) lattice fluid model to fit the solubility data of pure gases. We have assumed here that no specific interactions were occurring between the matrix and the absorbed gas. The same thermodynamic approach has been then used to predict the solubility of CO₂/CH₄ mixed gases in PPO, resulting in a deviation lower than 9.5% from the experimental results for CO₂ solubility.

Prospects for Simultaneously Capturing Carbon Dioxide and Harvesting Water from Air

Mitigation of anthropogenic climate change is expected to require large-scale deployment of carbon dioxide removal strategies. Prominent among these strategies is direct air capture with sequestration (DACS), which encompasses the removal and long-term storage of atmospheric CO₂  by purely engineered means. Because it does not require arable land or copious amounts of freshwater, DACS is already attractive in the context of sustainable development, but opportunities to improve its sustainability still exist. Leveraging differences in the chemistry of CO₂  and water adsorption within porous solids, here, the prospect of simultaneously removing water alongside CO₂  in direct air capture operations is investigated. In many cases, the co-adsorbed water can be desorbed separately from chemisorbed CO₂  molecules, enabling efficient harvesting of water from air. Depending upon the material employed and process conditions, the desorbed water can be of sufficiently high purity for industrial, agricultural, or potable use and can thus improve regional water security. Additionally, the recovered water can offset a portion of the costs associated with DACS. In this Perspective, molecular- and process-level insights are combined to identify routes toward realizing this nascent yet enticing concept.

Simultaneous Estimation of Gas Adsorption Equilibria and Kinetics of Individual Shaped Adsorbents

Shaped adsorbents (e.g., pellets, extrudates) are typically employed in several gas separation and sensing applications. The performance of these adsorbents is dictated by two key factors, their adsorption equilibrium capacity and kinetics. Often, adsorption equilibrium and textural properties are reported for materials. Adsorption kinetics are seldom presented due to the challenges associated with measuring them. The overarching goal of this work is to develop an approach to characterize the adsorption properties of individual shaped adsorbents with less than 100 mg of material. To this aim, we have developed an experimental dynamic sorption setup and complemented it with mathematical models, to describe the mass transport in the system. We embed these models into a derivative-free optimizer to predict model parameters for adsorption equilibrium and kinetics. We evaluate and independently validate the performance of our approach on three adsorbents that exhibit differences in their chemistry, synthesis, formulation, and textural properties. Further, we test the robustness of our mathematical framework using a digital twin. We show that the framework can rapidly (i.e., in a few hours) and quantitatively characterize adsorption properties at a milligram scale, making it suitable for the screening of novel porous materials.