Development and Evaluation of Porous Materials for Carbon Dioxide Separation and Capture

Leveraging experimental and computational tools for advancing carbon capture adsorbents research

CO2 emissions have been steadily increasing and have been a major contributor for climate change compelling nations to take decisive action fast. The average global temperature could reach 1.5 °C by 2035 which could cause a significant impact on the environment, if the emissions are left unchecked. Several strategies have been explored of which carbon capture is considered the most suitable for faster deployment. Among different carbon capture solutions, adsorption is considered both practical and sustainable for scale-up. But the development of adsorbents that can exhibit satisfactory performance is typically done through the experimental approach. This hit and trial method is costly and time consuming and often success is not guaranteed. Machine learning (ML) and other computational tools offer an alternate to this approach and is accessible to everyone. Often, the research towards materials focuses on maximizing its performance under simulated conditions. The aim of this study is to present a holistic view on progress in material research for carbon capture and the various tools available in this regard. Thus, in this review, we first present a context on the workflow for carbon capture material development before providing various machine learning and computational tools available to support researchers at each stage of the process. The most popular application of ML models is for predicting material performance and recommends that ML approaches can be utilized wherever possible so that experimentations can be focused on the later stages of the research and development.

Reactive capture and electrochemical conversion of CO2 with ionic liquids and deep eutectic solvents

Ionic liquids (ILs) and deep eutectic solvents (DESs) have tremendous potential for reactive capture and conversion (RCC) of CO2 due to their wide electrochemical stability window, low volatility, and high CO2 solubility. There is environmental and economic interest in the direct utilization of the captured CO2 using electrified and modular processes that forgo the thermal- or pressure-swing regeneration steps to concentrate CO2, eliminating the need to compress, transport, or store the gas. The conventional electrochemical conversion of CO2 with aqueous electrolytes presents limited CO2 solubility and high energy requirement to achieve industrially relevant products. Additionally, aqueous systems have competitive hydrogen evolution. In the past decade, there has been significant progress toward the design of ILs and DESs, and their composites to separate CO2 from dilute streams. In parallel, but not necessarily in synergy, there have been studies focused on a few select ILs and DESs for electrochemical reduction of CO2, often diluting them with aqueous or non-aqueous solvents. The resulting electrode-electrolyte interfaces present a complex speciation for RCC. In this review, we describe how the ILs and DESs are tuned for RCC and specifically address the CO2 chemisorption and electroreduction mechanisms. Critical bulk and interfacial properties of ILs and DESs are discussed in the context of RCC, and the potential of these electrolytes are presented through a techno-economic evaluation.

Carbon Dioxide Capture and Conversion Using Metal-Organic Framework (MOF) Materials: A Comprehensive Review

The escalating threat of anthropogenic climate change has spurred an urgent quest for innovative CO2 capture and utilization (CCU) technologies. Metal-organic frameworks (MOFs) have emerged as prominent candidates in CO2 capture and conversion due to their large specific surface area, well-defined porous structure, and tunable chemical properties. This review unveils the latest advancements in MOF-based materials specifically designed for superior CO2 adsorption, precise separation, advanced photocatalytic and electrocatalytic CO2 reduction, progressive CO2 hydrogenation, and dual functionalities. We explore the strategies that enhance MOF efficiency and examine the challenges of and opportunities afforded by transitioning from laboratory research to industrial application. Looking ahead, this review offers a visionary perspective on harnessing MOFs for the sustainable capture and conversion of CO2.

Amidation-Reaction Strategy Constructs Versatile Mixed Matrix Composite Membranes towards Efficient Volatile Organic Compounds Adsorption and CO2 Separation

Mixed matrix composite membranes (MMCMs) have shown advantages in reducing VOCs and CO2 emissions. Suitable composite layer, substrate, and good compatibility between the filler and the matrix in the composite layer are critical issues in designing MMCMs. This work develops a high-performance UiO-66-NA@PDMS/MCE for VOCs adsorption and CO2 permea-selectivity, based on a simple and facile fabrication of composite layer using amidation-reaction approach on the substrate. The composite layer shows a continuous morphological appearance without interface voids. This outstanding compatibility interaction between UiO-66-NH2 and PDMS is confirmed by molecular simulations. The Si─O functional group and UiO-66-NH2 in the layer leads to improved VOCs adsorption via active sites, skeleton interaction, electrostatic interaction, and van der Waals force. The layer and ─CONH─ also facilitate CO2 transport. The MMCMs show strong four VOCs adsorption and high CO2 permeance of 276.5 GPU with a selectivity of 36.2. The existence of VOCs in UiO-66-NA@PDMS/MCE increases the polarity and fine-tunes the pore size of UiO-66-NH2, improving the affinity towards CO2 and thus promoting the permea-selectivity for CO2, which is further verified by GCMC and EMD methods. This work is expected to offer a facile composite layer manufacturing method for MMCMs with high VOC adsorption and CO2 permea-selectivity.

Efficient Removal of Greenhouse Gases: Machine Learning-Assisted Exploration of Metal-Organic Framework Space

Global warming is a crisis that humanity must face together. With greenhouse gases (GHGs) as the main factor causing global warming, the adoption of relevant processes to eliminate them is essential. With the advantages of high specific surface area, large pore volume, and tunable synthesis, metal-organic frameworks (MOFs) have attracted much attention in GHG storage, adsorption, separation, and catalysis. However, as the pool of MOFs expands rapidly with new syntheses and discoveries, finding a suitable MOF for a particular application is highly challenging. In this regard, high-throughput computational screening is considered the most effective research method for screening a large number of materials to discover high-performance target MOFs. Typically, high-throughput computational screening generates voluminous and multidimensional data, which is well suited for machine learning (ML) training to improve the screening efficiency and explore the relationships between the multidimensional data in depth. This Review summarizes the general process and common methods for using ML to screen MOFs in the field of GHG removal. It also addresses the challenges faced by ML in exploring the MOF space and potential directions for the future development of ML for MOF screening. This aims to enhance the understanding of the integration of ML and MOFs in various fields and broaden the application and development ideas of MOFs.

Deep learning and big data mining for Metal-Organic frameworks with high performance for simultaneous desulfurization and carbon capture

Carbon capture and desulfurization of flue gases are crucial for the achievement of carbon neutrality and sustainable development. In this work, the "one-step" adsorption technology with high-performance metal-organic frameworks (MOFs) was proposed to simultaneously capture the SO2 and CO2. Four machine learning algorithms were used to predict the performance indicators (NCO2+SO2, SCO2+SO2/N2, and TSN) of MOFs, with Multi-Layer Perceptron Regression (MLPR) showing better performance (R2 = 0.93). To address sparse data of MOF chemical descriptors, we introduced the Deep Factorization Machines (DeepFM) model, outperforming MLPR with a higher R2 of 0.95. Then, sensitivity analysis was employed to find that the adsorption heat and porosity were the key factors for SO2 and CO2 capture performance of MOF, while the influence of open alkali metal sites also stood out. Furthermore, we established a kinetic model to batch simulate the breakthrough curves of TOP 1000 MOFs to investigate their dynamic adsorption separation performance for SO2/CO2/N2. The TOP 20 MOFs screened by the dynamic performance highly overlap with those screened by the static performance, with 76 % containing open alkali metal sites. This integrated approach of computational screening, machine learning, and dynamic analysis significantly advances the development of efficient MOF adsorbents for flue gas treatment.

High throughput screening of pure silica zeolites for CF4 capture from electronics industry gas

The capture and separation of CF4 from CF4/N2 mixture gas is a crucial issue in the electronics industry, as CF4 is a commonly used etching gas and the ratio of CF4 to N2 directly affects process efficiency. Utilizing high-throughput computational screening techniques and grand canonical Monte Carlo (GCMC) simulations, we comprehensively screened and assessed 247 types of pure silicon zeolite materials to determine their adsorption and separation performance for CF4/N2 mixtures. Based on screening, the relationships between the structural parameters and adsorption and separation properties were meticulously investigated. Four indicators including adsorption selectivity, working capacity, adsorbent performance score (APS), and regenerability (R%) were used to evaluate the performance of adsorbents. Based on the evaluation, we selected the top three best-performing zeolite structures for vacuum swing adsorption (LEV, AWW and ESV) and pressure swing adsorption (AVL, ZON, and ERI) processes respectively. Also, we studied the preferable adsorption sites of CF4 and N2 in the selected zeolite structures through centroid density distributions at the molecule level. We expect the study may provide some valuable guidance for subsequent experimental investigations on adsorption and separation of CF4/N2.

High-Capacity, Cooperative CO2 Capture in a Diamine-Appended Metal-Organic Framework through a Combined Chemisorptive and Physisorptive Mechanism

Diamine-appended Mg2(dobpdc) (dobpdc4- = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) metal-organic frameworks are promising candidates for carbon capture that exhibit exceptional selectivities and high capacities for CO2. To date, CO2 uptake in these materials has been shown to occur predominantly via a chemisorption mechanism involving CO2 insertion at the amine-appended metal sites, a mechanism that limits the capacity of the material to ∼1 equiv of CO2 per diamine. Herein, we report a new framework, pip2-Mg2(dobpdc) (pip2 = 1-(2-aminoethyl)piperidine), that exhibits two-step CO2 uptake and achieves an unusually high CO2 capacity approaching 1.5 CO2 per diamine at saturation. Analysis of variable-pressure CO2 uptake in the material using solid-state nuclear magnetic resonance (NMR) spectroscopy and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) reveals that pip2-Mg2(dobpdc) captures CO2 via an unprecedented mechanism involving the initial insertion of CO2 to form ammonium carbamate chains at half of the sites in the material, followed by tandem cooperative chemisorption and physisorption. Powder X-ray diffraction analysis, supported by van der Waals-corrected density functional theory, reveals that physisorbed CO2 occupies a pocket formed by adjacent ammonium carbamate chains and the linker. Based on breakthrough and extended cycling experiments, pip2-Mg2(dobpdc) exhibits exceptional performance for CO2 capture under conditions relevant to the separation of CO2 from landfill gas. More broadly, these results highlight new opportunities for the fundamental design of diamine-Mg2(dobpdc) materials with even higher capacities than those predicted based on CO2 chemisorption alone.

Innovative strategies for enhancing gas separation: Ionic liquid-coated PES membranes for improved CO2/N2 selectivity and permeance

As a cost-effective advancement in membrane technology, this study investigates the impact of PEG additive and CBT on the structural, stability, and gas permeance properties of PES-coated membranes, utilizing 1-dodecyl-3-methylimidazolium chloride ionic liquid ([DDMI][Cl] IL) as a carrier liquid. BET and FT-IR analyses highlight the significant enhancement in performance through the immobilization of pores with [DDMIM][Cl] IL. The investigation focuses on PES-M5-coated membranes, revealing excellent stability in finger-like pore structures prepared through direct immersion and nitrogen pressure immobilization. PES-M5-coated membranes with [DDMIM][Cl] IL via direct immersion experience lower weight loss than those coated using nitrogen pressure, with critical pressures at 1.4 and 1.25 bar, respectively. The study identifies PES-coated membranes, particularly PES-M25 (20.88 GPU) with macro-void pores and PES-M5 (29 GPU) with finger-like pores, exhibiting the highest CO2 permeance and CO2/N2 selectivity. As a cost-effective advancement in membrane technology, ionic liquids are employed in support membranes to enhance gas separation. Employing pure PES membranes with varying pore structures, created through the NIPS method, the study immobilizes [DDMI][Cl] IL in membrane pores through nitrogen pressure and direct immersion. Results underscore the successful application of porous support materials coated with ionic liquids for continuous CO2 and sulfur compound separation, showcasing competitive permeability and selectivity compared to traditional polymer membranes.

Evaluation of the Hydrophilic/Hydrophobic Balance of 13X Zeolite by Adsorption of Water, Methanol, and Cyclohexane as Pure Vapors or as Mixtures

Adsorption isotherms of pure vapors and vapor mixtures of water, methanol, and cyclohexane were studied using a synthesized 13X zeolite (FAU topology), by means of a DVS gravimetric vapor analyzer. These results were validated by GCMC calculations. The surface chemistry of the adsorbent was characterized by the thermodesorption of ammonia, and its textural properties were studied using nitrogen physisorption. The 13X zeolite was found to be strongly acidic (BrØnsted acid sites, Si/Al = 1.3) and its specific surface area around 1100 m2·g-1. Water was found to be able to diffuse within both the supercages and the sodalite cavities of the FAU structure, whereas methanol and cyclohexane were confined in the supercages only. The water/methanol sorption selectivity of the 13X zeolite was demonstrated by co-adsorption measurements. The composition of the water/methanol adsorbed phase could be calculated by assuming IAST hypotheses. This model failed in the case of the water/cyclohexane co-adsorption system, which is in line with the non-miscibility of the components in the adsorbed state. The sorption isotherms could be successfully simulated, confirming the robustness of the forcefields used. The 13X zeolite confirmed its a priori expected hydrophilic nature, which is useful for the selective adsorption of water in a methanol-water vapor mixture.

Importance of Bridging Molecular and Process Modeling to Design Optimal Adsorbents for Large-Scale CO2 Capture

ConspectusCarbon capture, utilization, and storage have been identified as key technologies to decarbonize the energy and industrial sectors. Although postcombustion CO2 capture by absorption in aqueous amines is a mature technology, the required high regeneration energy, losses due to degradation and evaporation, and corrosion carry a high economic cost, precluding this technology to be used today at the scale required to mitigate climate change. Solid adsorbent-based systems with high CO2 capacities, high selectivity, and lower regeneration energy are becoming an attractive alternative for this purpose. Conscious of this opportunity, the search for optimal adsorbents for the capture of CO2 has become an urgent task. To accurately assess the performance of CO2 separation by adsorption at the needed scale, adsorbents should be synthesized and fully characterized under the required operating conditions, and the proper design and simulation of the process should be implemented along with techno-economic and environmental assessments. Several works have examined pure CO2 single-component adsorption or binary mixtures of CO2 with nitrogen for different families of adsorbents, primarily addressing their CO2 adsorption capacity and selectivity; however, very limited data is available under other conditions and/or with impurities, mainly due to the intensive experimental (modeling) efforts required for the large number of adsorbents to be studied, posing a challenge for their assessment under the needed conditions. In this regard, molecular simulations can be employed in synergy with experiments, reliably generating missing adsorption properties of mixtures while providing understanding at the molecular level of the mechanism of the adsorption process.This Account provides an outlook on strategies used for the rational design of materials for CO2 capture from different sources from the understanding of the adsorption mechanism at the molecular level. We illustrate with practical examples from our work and others' work how molecular simulations can be reliably used to link the molecular knowledge of novel adsorbents for which limited data exist for CO2 capture adsorption processes. Molecular simulation results of different adsorbents, including MOFs, zeolites, and carbon-based and silica-based materials, are discussed, focusing on understanding the role of physical and chemical adsorption obtained from simulations and quantifying the impact of impurities in the performance of the materials. Furthermore, simulation results can be used for screening adsorbents from basic key performance indicators, such as cycling the working capacity, selectivity, and energy requirement, or for feeding detailed dynamic models to assess their performance in swing adsorption processes on the industrial scale, additionally including monetized performance indicators such as operating expenses, equipment sizes, and compression cost. Moreover, we highlight the role of molecular simulations in guiding strategies for improving the performance of these materials by functionalization with amines or creating hybrid solid materials. We show how integrating models at different scales provides a robust and reliable assessment of the performance of the adsorbent materials under the required industrial conditions, rationally guiding the search for best performers. Trends in additional computational resources that can be used, including machine learning, and perspectives on practical requirements for leveraging CO2 capture adsorption technologies on the needed scale are also discussed.

Natural Products Derived Porous Carbons for CO2 Capture

As it is now established that global warming and climate change are a reality, international investments are pouring in and rightfully so for climate change mitigation. Carbon capture and separation (CCS) is therefore gaining paramount importance as it is considered one of the powerful solutions for global warming. Sorption on porous materials is a promising alternative to traditional carbon dioxide (CO2 ) capture technologies. Owing to their sustainable availability, economic viability, and important recyclability, natural products-derived porous carbons have emerged as favorable and competitive materials for CO2 sorption. Furthermore, the fabrication of high-quality value-added functional porous carbon-based materials using renewable precursors and waste materials is an environmentally friendly approach. This review provides crucial insights and analyses to enhance the understanding of the application of porous carbons in CO2 capture. Various methods for the synthesis of porous carbon, their structural characterization, and parameters that influence their sorption properties are discussed. The review also delves into the utilization of molecular dynamics (MD), Monte Carlo (MC), density functional theory (DFT), and machine learning techniques for simulating adsorption and validating experimental results. Lastly, the review provides future outlook and research directions for progressing the use of natural products-derived porous carbons for CO2 capture.

Carbon dioxide adsorption to UiO-66: theoretical analysis of binding energy and NMR properties

UiO-66 is one of the most valuable metal-organic frameworks because of its excellent adsorption capability for gas molecules and its high stability towards water. Herein we investigated adsorption of carbon dioxide (CO2), acetone, and methanol to infinite UiO-66 using DFT calculations on an infinite system under periodic-boundary conditions and post-Hartree-Fock (SCS-MP2 and MP2.5) calculations on cluster models. Three to four molecules are adsorbed at each of four μ-OH groups bridging three Zr atoms in one unit cell (named Site I). Six molecules are adsorbed around three pillar ligands, where the molecule is loosely surrounded by three terephthalate ligands (named Site II). Also, six molecules are adsorbed around the pillar ligand in a different manner from that at Site II, where the molecule is surrounded by three terephthalate ligands (named Site III). Totally fifteen to sixteen CO2 molecules are adsorbed into one unit cell of UiO-66. The binding energy (BE) decreases in the order Site I > Site III > Site II for all three molecules studied here and in the order acetone > methanol ≫ CO2 in the three adsorption sites. At the site I, the protonic H atom of the μ-OH group interacts strongly with the negatively charged O atom of CO2, acetone and methanol, which is the origin of the largest BE value at this site. Although the DFT calculations present these decreasing orders of BE values correctly, the correction by post-Hartree-Fock calculations is not negligibly small and must be added for obtaining better BE values. We explored NMR spectra of UiO-66 with adsorbed CO2 molecules and found that the isotropic shielding constants of the 1H atom significantly differ among no CO2, one CO2 (at Sites I, II, or III), and fifteen CO2 adsorption cases (Sites I to III) but the isotropic 17O and 13C shielding constants change moderately by adsorption of fifteen CO2 molecules. Thus, 1H NMR measurement is a useful experiment for investigating CO2 adsorption.

Graph Transformer with Convolution Parallel Networks for Predicting Single and Binary Component Adsorption Performance of Metal-Organic Frameworks

Metal-organic frameworks (MOFs) are considered one of the most important materials for carbon capture and storage (CCS) due to the advantages of porosity, multifunction, diverse structure, and controllable chemical composition. With the continuous development of artificial intelligence (AI) technology, more and more machine learning models are used to identify MOFs with high performance within a massive search space. However, current works have yet to form a model that uses graph-structured data only, which can predict the adsorption properties of single and binary components. In this work, we proposed and developed a graph transformer, combined with convolution parallel networks, called GC-Trans. The model can accurately and efficiently predict the adsorption performance of MOFs under the single- and binary-component adsorption conditions using only the features of the crystal diagram as inputs. By extracting and fusing local and global feature information, the model has stronger expression and generalization abilities. Thus, we used it to screen the ARC-MOF database and analyze the MOF structures that meet the target requirements. Additionally, to demonstrate the transferability of the model, we applied transfer learning methods to predict the CO2/CH4 separations and CH4 uptake, both of which showed good predictive performance.

Intermetallic Compound with CuNi Sites for Enhancing the Selectivity of Electrochemical CO2 Conversion

Although single-metal-site (SMS) catalysts have long been explored for the electrochemical CO2 reduction reaction (EC-CO2RR), the reactivity and selectivity of SMS catalysts remain rather low due to the competing hydrogen evolution reaction (HER). To improve the selectivity, in this work, a novel intermetallic particle of CuNi is decorated on the N-doped carbon substrate, which was first precisely fabricated by scarifying the bimetal-doped metal-organic framework (MOF). Thanks to the neighboring synergistic functions of Cu and Ni sites, CuNi/NC prominently boosts the electroreduction of CO2, far more than the SMS catalysts of Cu/NC and Ni/NC. Further, CuNi/NC presents superior selectivity toward CO with faradaic efficiency over a wide range of potentials (surpassing 90% at 0.6-1.0 V vs RHE, up to 98% at 0.6 V vs RHE) and excellent durability. The experimental results and theoretical calculations reveal that the Ni species can be highly activated due to the neighboring Cu species, which considerably facilitates the formation of an intermediate of COOH* and consequently enhances the selectivity of the reduction of CO2 to CO. This work paves a general way to precisely fabricate catalysts with multiple metal species and also demonstrates the significant synergetic efficiency between the neighboring sites to improve the catalytic performance.

Covalent organic frameworks for CO2 capture: from laboratory curiosity to industry implementation

CO2 concentration in the atmosphere has increased by about 40% since the 1960s. Among various technologies available for carbon capture, adsorption and membrane processes have been receiving tremendous attention due to their potential to capture CO2 at low costs. The kernel for such processes is the sorbent and membrane materials, and tremendous progress has been made in designing and fabricating novel porous materials for carbon capture. Covalent organic frameworks (COFs), a class of porous crystalline materials, are promising sorbents for CO2 capture due to their high surface area, low density, controllable pore size and structure, and preferable stabilities. However, the absence of synergistic developments between materials and engineering processes hinders achieving the qualitative leap for net-zero emissions. Considering the lack of a timely review on the combination of state-of-the-art COFs and engineering processes, in this Tutorial Review, we emphasize the developments of COFs for meeting the challenges of carbon capture and disclose the strategies of fabricating COFs for realizing industrial implementation. Moreover, this review presents a detailed and basic description of the engineering processes and industrial status of carbon capture. It highlights the importance of machine learning in integrating simulations of molecular and engineering levels. We aim to stimulate both academia and industry communities for joined efforts in bringing COFs to practical carbon capture.

Highly Cooperative CO2 Adsorption via a Cation Crowding Mechanism on a Cesium-Exchanged Phillipsite Zeolite

An understanding of the CO2 adsorption mechanisms on small-pore zeolites is of practical importance in the development of more efficient adsorbents for the separation of CO2 from N2 or CH4 . Here we report that the CO2 isotherms at 25-75 °C on cesium-exchanged phillipsite zeolite with a Si/Al ratio of 2.5 (Cs-PHI-2.5) are characterized by a rectilinear step shape: limited uptake at low CO2 pressure (PCO2 ) is followed by highly cooperative uptake at a critical pressure, above which adsorption rapidly approaches capacity (2.0 mmol g-1 ). Structural analysis reveals that this isotherm behavior is attributed to the high concentration and large size of Cs+ ions in dehydrated Cs-PHI-2.5. This results in Cs+ cation crowding and subsequent dispersal at a critical loading of CO2 , which allows the PHI framework to relax to its wide pore form and enables its pores to fill with CO2 over a very narrow range of PCO2 . Such a highly cooperative phenomenon has not been observed for other zeolites.

Fabrication and properties of Sn(iv) porphyrin-linked porous organic polymer for environmental applications

A robust porous organic polymer cross-linked by Sn(iv) porphyrin (SnPOP) was fabricated by reacting trans-dihydroxo-[5,15,10,20-tetrakis(phenyl)porphyrinato]tin(iv) (SnP) with fluorinated polyimide (FPI) via sol-gel formation, followed by supercritical CO2 drying. The structural and porous properties of SnPOP were characterized using FT-IR, UV-vis, and fluorescence spectroscopies, along with field-emission scanning electron microscopy and gas sorption experiments. The reaction between the SnP's oxophilic Sn(iv) center and FPI's carboxylic acid moiety resulted in a controllable cross-linked porous texture. This material features the desirable physical properties of porphyrin and exhibits mesoporous structures with a relatively high surface area. SnPOP is thermally stable at temperatures up to 600 °C and highly resistant to boiling water, strong acids, and bases, owing to its assembly via formation of covalent bonds instead of typically weaker hydrogen bonds. The modified chemical and morphological structures of SnPOP showed an impressive CO2 uptake capacity of 58.48 mg g-1 at 273 K, with a preference for CO2 over N2. SnPOP showed significant efficiency in removing pollutant dyes, such as methylene blue and methyl orange, from dye-contaminated water. Additionally, SnPOP was a photocatalyst for fabricating silver nanoparticles of regular shape and size. All these properties make SnPOP a potential candidate for environmental applications like pollutant removal, gas storage, and separation.

Porphyrinic Porous Aromatic Frameworks for Carbon Dioxide Adsorption and Separation

The capture of carbon dioxide (CO2 ) from industrial process emissions is increasingly important for the mitigation and prevention of the disruptive effects of global warming. In this study, PAF (porous aromatic frameworks)-TPB(1,3,5-triphenylbenzene) and three-dimensional PAF-TPM (tetraphenylmethane) porphyrin-based aromatic porous materials were synthesized through the Scholl reaction. The CO2 and N2 adsorption isotherms at 273 K and 298 K were studied to determine the performance in carbon dioxide capture at flue gas conditions. There is a significant difference in the adsorption capacity of the two materials for CO2 and N2 , so they can be used for CO2 /N2 adsorption separation. PAF-TPM has better CO2 /N2 separation at low pressure (150 mbar), while PAF-TPB has the advantage of greater CO2 /N2 separation at high pressure (1 bar). It can be applied to CO2 adsorption separation at low and high pressure, respectively. In particular, PAF-TPB has a CO2 /N2 separation efficiency of up to 100.9 at 1 bar and 273 K. This work provides ideas for the design and synthesis of organic porous materials for the adsorption separation of CO2 and N2 .

Superior Selective CO2 Adsorption and Separation over N2 and CH4 of Porous Carbon Nitride Nanosheets: Insights from GCMC and DFT Simulations

Development of high-performance materials for the capture and separation of CO₂ from the gas mixture is significant to alleviate carbon emission and mitigate the greenhouse effect. In this work, a novel structure of C₉N₇ slit was developed to explore its CO₂ adsorption capacity and selectivity using Grand Canonical Monte Carlo (GCMC) and Density Functional Theory (DFT) calculations. Among varying slit widths, C₉N₇ with the slit width of 0.7 nm exhibited remarkable CO₂ uptake with superior CO₂/N₂ and CO₂/CH₄ selectivity. At 1 bar and 298 K, a maximum CO₂ adsorption capacity can be obtained as high as 7.06 mmol/g, and the selectivity of CO₂/N₂ and CO₂/CH₄ was 41.43 and 18.67, respectively. In the presence of H₂O, the CO₂ uptake of C₉N₇ slit decreased slightly as the water content increased, showing better water tolerance. Furthermore, the underlying mechanism of highly selective CO₂ adsorption and separation on the C₉N₇ surface was revealed. The closer the adsorption distance, the stronger the interaction energy between the gas molecule and the C₉N₇ surface. The strong interaction between the C₉N₇ nanosheet and the CO₂ molecule contributes to its impressive CO₂ uptake and selectivity performance, suggesting that the C₉N₇ slit could be a promising candidate for CO₂ capture and separation.

Monomer Symmetry-Regulated Defect Engineering: In Situ Preparation of Functionalized Covalent Organic Frameworks for Highly Efficient Capture and Separation of Carbon Dioxide

Developing crystalline porous materials with highly efficient CO₂ selective adsorption capacity is one of the key challenges to carbon capture and storage (CCS). In current studies, much more attention has been paid to the crystalline and porous properties of crystalline porous materials for CCS, while the defects, which are unavoidable and ubiquitous, are relatively neglected. Herein, for the first time, we propose a monomer-symmetry regulation strategy for directional defect release to achieve in situ functionalization of COFs while exposing uniformly distributed defect-aldehyde groups as functionalization sites for selective CO₂ capture. The regulated defective COFs possess high crystallinity, good structural stability, and a large number of organized and functionalized aldehyde sites, which exhibit one of the highest selective separation values of all COF sorbing materials in CO₂/N₂ selective adsorption (128.9 cm³/g at 273 K and 1 bar, selectivity: 45.8 from IAST). This work not only provides a new strategy for defect regulation and in situ functionalization of COFs but also provides a valuable approach in the design and preparation of new adsorbents for CO₂ adsorption and CO₂/N₂ selective separation.

Accelerated screening and assembly of promising MOFs with open Cu sites for isobutene/isobutane separation using a data-driven approach

As the by-products of catalytic cracking or alkane dehydrogenation, isobutene (2-methyl-propylene) and isobutane (2-methyl-propane) are important chemical feedstocks, but the separation of their mixture is a challenging issue in the petrochemical industry. Herein, we report the first example of large-scale computational screening of metal-organic frameworks (MOFs) with copper open metal sites (Cu-OMS) on the adsorptive separation of isobutene/isobutane using configuration-bias Monte Carlo (CBMC) simulations and machine learning among >330 000 MOFs data. We discovered that the optimal structural features governing the MOFs-based separation of isobutene/isobutane were density (ρ) and porosity (φ), with ranges of 0.2-0.5 g cm^-3 and 0.8-0.9, respectively. Furthermore, the key genes (metal nodes or linkers of frameworks) contributing to such adsorptive separation were data-mined by feature engineering of ML. These genes were cross-assembled into novel frameworks using a material-genomics strategy. The screened AVAKEP, XAHPON, HUNCIE, Cu₂O₈-mof177-TDPAT_No730 and assembled Cu₂O₈-BTC_B-core-4_No1 possessed high isobutene uptake and isobutene/isobutane selectivity of >19.5 mmol g^-1 and 4.7, with high thermal stability (as validated by molecular-dynamics simulations) overcoming the critical "trade-off" problem to some extent. The macroporous structures (pore-limiting diameter >12 Å) of these five promising frameworks with multi-layer adsorption on isobutene resulted in high isobutene loading, as validated by adsorption isotherms and CBMC simulations. The higher adsorption energy and heat of adsorption of isobutene than those of isobutane indicated that the thermodynamic equilibrium drove their selective adsorption. Generalized charge decomposition analysis and localized orbit locator calculations based on density functional theory wavefunctions suggested that high selectivity was due to complexation of feedback π bonds between isobutene and Cu-OMS, but also the strong π-π stacking interaction induced by the CC bond of isobutene with the multiple aromatic rings and unsaturated bonds of frameworks. Our theoretical results and data-driven approach may provide insights into the development of efficient MOF materials for the separation of isobutene/isobutane and other mixtures.

Ligand-Functional Groups Induced Tuning MOFs' 2D into 1D Pore Channels for Pipeline Natural Gas Purification

The solvothermal reactions of CoCl₂  ⋅ 6H₂ O, 3,5-pyridinedicarboxylic acid (H₂ L) and isonicotinic acid (HL₁ )/3-amino isonicotinic acid (HL₂ )/3-chloro isonicotinic acid (HL₃ ) successfully led to three tfz-d topological pillar-layer [Co₄ (μ-F)₂ (COO)₆ (NC₅ H₄ )₄ ] cluster-based MOFs, namely, [Co₄ (μ-F)₂ (L)₂ (L₁ )₂  ⋅ 2DMA] ⋅ DMA ⋅ 2H₂ O (SNNU-Bai76, SNNU-Bai=Shaanxi Normal University Bai's group), [Co₄ (μ-F)₂ (L)₂ (L₂ )₂  ⋅ 2H₂ O] ⋅ 2DMA ⋅ 2H₂ O (SNNU-Bai77) and [Co₄ (μ-F)₂ (L)₂ (L₃ )₂  ⋅ 2H₂ O] ⋅ 2DMF ⋅ 2H₂ O (SNNU-Bai78). With the 2D pore channels in SNNU-Bai76 and SNNU-Bai77 being tuned to the 1D pore channel in SNNU-Bai78, C₃ H₈ and C₂ H₆ adsorption uptakes are apparently improved and the IAST selectivities of C₃ H₈ /CH₄ and C₂ H₆ /CH₄ almost remain, which indicate that SNNU-Bai78 may be one potential separation material for the pipeline natural gas purification. These were further confirmed by the breakthrough experiments for the simulated pipeline natural gas (C₃ H₈ /C₂ H₆ /CH₄  : 5/10/85 gas mixture) of three isostructural MOFs. Furthermore, GCMC simulations revealed that due to one of the pore channels blocked by Cl atoms in a couple of 3-chloro isonicotinic acid with the changed conformation as the pillar, the pore wall of the formed 1D pore channel in SNNU-Bai78 may interact with the adsorbed C₃ H₈ or C₂ H₆ molecule more strongly, for which more atoms of framework at the new adsorption site will interact with the adsorbed gas molecule by more intermolecular interactions. This was also evidenced by the increased binding energies, being consistent with the tuning of adsorption enthalpies for C₃ H₈ and C₂ H₆ gas molecules, and the reduced C₃ H₈ and C₂ H₆ gas diffusion coefficients in SNNU-Bai78. Very interestingly, this work is the first example of finely tuning the pore connectivity of MOFs toward strengthened host-guest interactions for the gas adsorption and separation.

Covalent organic frameworks (COFs): a promising CO2 capture candidate material

Covalent organic frameworks (COFs) are an emerging kind of porous crystal material.

MOF-Derived Robust and Synergetic Acid Sites Inducing C-N Bond Disruption for Energy-Efficient CO2 Desorption

Amine-based scrubbing technique is recognized as a promising method of capturing CO₂ to alleviate climate change. However, the less stability and poor acidity of solid acid catalysts (SACs) limit their potential to further improve amine regeneration activity and reduce the energy penalty. To address these challenges, here, we introduce two-dimensional (2D) cobalt-nitrogen-doped carbon nanoflakes (Co-N-C NSs) driven by a layered metal-organic framework that work as SACs. The designed 2D Co-N-C SACs can exhibit promising stability, superhydrophilic surface, and acidity. Such 2D structure also contains well-confined Co-N₄ Lewis acid sites and -OH Brønsted acid sites to have a synergetic effect on C-N bond disruption and significantly increase CO₂ desorption rate by 281% and reduce the reaction temperatures to 88 °C, minimizing water evaporation by 20.3% and subsequent regeneration energy penalty by 71.7% compared to the noncatalysis.

Metal-Organic Frameworks as Photocatalysts for Solar-Driven Overall Water Splitting

Metal-organic frameworks (MOFs) have been frequently used as photocatalysts for the hydrogen evolution reaction (HER) using sacrificial agents with UV-vis or visible light irradiation. The aim of the present review is to summarize the use of MOFs as solar-driven photocatalysts targeting to overcome the current efficiency limitations in overall water splitting (OWS). Initially, the fundamentals of the photocatalytic OWS under solar irradiation are presented. Then, the different strategies that can be implemented on MOFs to adapt them for solar photocatalysis for OWS are discussed in detail. Later, the most active MOFs reported until now for the solar-driven HER and/or oxygen evolution reaction (OER) are critically commented. These studies are taken as precedents for the discussion of the existing studies on the use of MOFs as photocatalysts for the OWS under visible or sunlight irradiation. The requirements to be met to use MOFs at large scale for the solar-driven OWS are also discussed. The last section of this review provides a summary of the current state of the field and comments on future prospects that could bring MOFs closer to commercial application.

High-Selective CO2 Capture in Amine-Decorated Al-MOFs

Amine-functionalized metal-organic framework (MOF) material is a promising CO₂ captor in the post-combustion capture process owing to its large CO₂ working capacity as well as high CO₂ selectivity and easy regeneration. In this study, an ethylenediamine (ED)-decorated Al-based MOFs (named ED@MOF-520) with a high specific area and permanent porosity are prepared and evaluated to study the adsorption and separation of CO₂ from N₂. The results show that ED@MOF-520 adsorbent displays a superior CO₂ capture performance with a CO₂/N₂ separation factor of 50 at 273 K, 185% times increase in the CO₂/N₂ separation efficiency in comparison with blank MOF-520. Furthermore, ED@MOF-520 exhibits a moderate-strength interaction with 29 kJ mol^-1 adsorption heat for CO₂ uptake, which not only meets the requirement of CO₂ adsorption but also has good cycle stability. This work provides a promising adsorbent with a high CO₂/N₂ separation factor to deal with carbon peak and carbon neutrality.

Hierarchical Metal-Organic Aerogel as a Highly Selective and Sustainable CO2 Adsorbent

Typical amorphous aerogels pose great potential for CO₂ adsorbents with high surface areas and facile diffusion, but they lack well-defined porosity and specific selectivity, inhibiting utilization of their full functionality. To assign well-defined porous structures to aerogels, a hierarchical metal-organic aerogel (HMOA) is designed, which consists of well-defined micropores (d ∼ 1 nm) by coordinative integration with chromium(III) and organic ligands. Due to its hierarchical structure with intrinsically flexible coordination, the HMOA has excellent porous features of a high surface area and a reusable surface with appropriate binding energy for CO₂ adsorption. The HMOA features high CO₂ adsorption capacity, high CO₂/N₂ IAST selectivity, and vacuum-induced surface regenerability (100% through 20 cycles). Further, the HMOA could be prepared via simple ambient drying methods while retaining the microporous network. This unique surface-tension-resistant micropore formation and flexible coordination systems of HMOA make it a potential candidate for a CO₂ adsorbent with industrial scalability and reproducibility.

Temperature Extrapolation of Henry's Law Constants and the Isosteric Heat of Adsorption

Computational screening of adsorbent materials often uses the Henry's law constant (K_H) (at a particular temperature) as a first discriminator metric due to its relative ease of calculation. The isosteric heat of adsorption in the limit of zero pressure (q_st^∞) is often calculated along with the Henry's law constant, and both properties are informative metrics of adsorbent material performance at low-pressure conditions. In this article, we introduce a method for extrapolating K_H as a function of temperature, using series-expansion coefficients that are easily computed at the same time as K_H itself; the extrapolation function also yields q_st^∞. The extrapolation is highly accurate over a wide range of temperatures when the basis temperature is sufficiently high, for a wide range of adsorbent materials and adsorbate gases. Various results suggest that the extrapolation is accurate when the extrapolation range in inverse-temperature space is limited to |β - β₀ | < 0.5 mol/kJ. Application of the extrapolation to a large set of materials is shown to be successful provided that K_H is not extremely large and/or the extrapolation coefficients converge satisfactorily. The extrapolation is also able to predict q_st^∞ for a system that shows an unusually large temperature dependence. The work provides a robust method for predicting K_H and q_st^∞ over a wide range of industrially relevant temperatures with minimal effort beyond that necessary to compute those properties at a single temperature, which facilitates the addition of practical operating (or processing) conditions to computational screening exercises.

Demonstration of High-Throughput Building Block and Composition Analysis of Metal-Organic Frameworks

Metal-organic frameworks (MOFs) are composed of inorganic metal-containing nodes and organic linker groups and are promising porous materials for a wide range of applications. More than 90 000 different MOFs have been synthesized with different inorganic nodes, organic linkers, and node-linker connectivity patterns. While databases have been created to catalog this enormous number of structures, they generally do not provide functionality to easily search, sort, and understand MOFs based on composition and building blocks. Because structure-property relationships are critical to identify, here we outline our new program MOFseek and demonstrate that it can perform high-throughput structure and composition analyses of MOF structures. This program enables the fast analysis of tens of thousands of MOFs in databases based on the local chemical environment. We demonstrate the unique capabilities of MOFseek by analyzing the CoRE MOF database of structures.

A Machine Learning-Aided Equilibrium Model of VTSA Processes for Sorbents Screening Applied to CO2 Capture from Diluted Sources

The large design space of the sorbents’ structure and the associated capability of tailoring properties to match process requirements make adsorption-based technologies suitable candidates for improved CO₂ capture processes. This is particularly of interest in novel, diluted, and ultradiluted separations as direct CO₂ removal from the atmosphere. Here, we present an equilibrium model of vacuum temperature swing adsorption cycles that is suitable for large throughput sorbent screening, e.g., for direct air capture applications. The accuracy and prediction capabilities of the equilibrium model are improved by incorporating feed-forward neural networks, which are trained with data from rate-based models. This allows one, for example, to include the process productivity, a key performance indicator typically obtained in rate-based models. We show that the equilibrium model reproduces well the results of a sophisticated rate-based model in terms of both temperature and composition profiles for a fixed cycle as well as in terms of process optimization and sorbent comparison. Moreover, we apply the proposed equilibrium model to screen and identify promising sorbents from the large NIST/ARPA-E database; we do this for three different (ultra)diluted separation processes: direct air capture, y_CO2 = 0.1%, and y_CO2 = 1.0%. In all cases, the tool allows for a quick identification of the most promising sorbents and the computation of the associated performance indicators. Also, in this case, outcomes are very well in line with the 1D model results. The equilibrium model is available in the GitHub repository https://github.com/UU-ER/SorbentsScreening0D.

Multifunctional Lanthanide-Based Metal-Organic Frameworks Derived from 3-Amino-4-hydroxybenzoate: Single-Molecule Magnet Behavior, Luminescent Properties for Thermometry, and CO2 Adsorptive Capacity

Herein, we describe and study a new family of isostructural multifunctional metal–organic frameworks (MOFs) with the formula {[Ln₅L₆(OH)₃(DMF)₃]·5H₂O}_n (where (H₂L) is 3-amino-4-hydroxybenzoic acid ligand) for magnetism and photoluminescence. Interestingly, three of the materials (Dy-, Er-, and Yb-based MOFs) present single-molecule magnet (SMM) behavior derived from the magnetic anisotropy of the lanthanide ions as a consequence of the adequate electronic distribution of the coordination environment. Additionally, photoluminescence properties of the ligand in combination with Eu and Tb counterparts were studied, including the heterometallic Eu–Tb mixed MOF that shows potential as ratiometric luminescent thermometers. Finally, the porous nature of the framework allowed showing the CO₂ sorption capacity.

A new family of isostructural multifunctional metal−organic frameworks has been described and studied for magnetism and photoluminescence. Interestingly, some materials present single-molecule magnet behavior, and photoluminescence properties of the ligand in combination with Eu and Tb counterparts were studied, including the heterometallic Eu−Tb mixed MOF that shows potential as ratiometric luminescent thermometers. Finally, the porous nature of the framework allowed showing the CO₂ sorption capacity.

Gate Opening without Volume Change Triggers Cooperative Gas Interactions, Underpins an Isotherm Step in Metal-Organic Frameworks

Three halogenated metal-organic frameworks (MOFs) reported recently exhibited a second step in their CO₂ gas adsorption isotherms. The emergence of halogen-bonding interactions beyond a threshold gas pressure between the framework halogen and the CO₂ guest was conjectured to be the underlying reason for the additional step in the isotherm. Our investigation employing periodic density functional theory calculations did not show significant interactions between the halogen and CO₂ molecules. Further, using a combination of DFT-based ab initio molecular dynamics and grand canonical Monte Carlo simulations, we find that the increased separation of framework nitrate pairs facing each other across the pore channel enables the accommodation of an additional CO₂ molecule which is further stabilized by cooperative interactions─an observation that facilely explains the second isotherm step. The increased separation between the nitrate groups can occur without any lattice expansion, consistent with experiments. The results point to a structural feature to achieve this isotherm step in MOFs that neither possess large pores nor exhibit large-scale structural changes such as breathing.