Tailoring ammonia capture in MOFs and COFs: A multi-scale and machine learning comprehensive investigation of functional group modification

Our study aims to examine the impact of ligand functionalization on the ammonia adsorption properties of MOFs and COFs, by combining multi-scale calculations with machine learning techniques. Density Functional Theory calculations were performed to investigate the interactions between ammonia (NH3) and a comprehensive set of 48 strategically chosen functional groups. In all of the cases, it is observed that functionalized rings exhibit a stronger interaction with ammonia molecule compared to unfunctionalized benzene, while -O2Mg demonstrates the highest interaction energy with ammonia (15 times stronger than the bare benzene). The trend obtained from the thorough DFT screening is verified via Grand Canonical Monte-Carlo calculations by employing interatomic potentials derived from quantum chemical calculations. Isosteric heat of adsorption plots provide a comprehensive elucidation of the adsorption process, and important insights can be taken for studies in fine-tuning materials for ammonia adsorption. Furthermore, a proof of concept machine learning (ML) analysis is conducted, which demonstrates that ML can accurately predict NH3 binding energies despite the limited amount of data. The findings derived from our multi-scale methodology indicate that the functionalization strategy can be utilized to guide synthesis towards MOFs, COFs, or other porous materials for enhanced NH3 adsorption capacity.

Effects of Fluorinated Functionalization of Linker on Quercetin Encapsulation, Release and Hela Cell Cytotoxicity of Cu-Based MOFs as Smart pH-Stimuli Nanocarriers

Controlled delivery of target molecules is required in many medical and chemical applications. For such purposes, metal-organic frameworks (MOFs), which possess desirable features such as high porosity, large surface area, and adjustable functionalities, hold great potential as drug carriers. Herein, Quercetin (QU), as an anticancer drug, was loaded on Cu2 (BDC)2 (DABCO) and Cu2 (F4 BDC)2 )DABCO) MOFs (BDC=1,4-benzenedicarboxylate and DABCO=1,4-diazabicyclo[2.2.2]octane). As these Cu-MOFs have a high surface area, an appropriate pore size, and biocompatible ingredients, they can be utilized to deliver QU. The loading efficiency of QU in these MOFs was 49.5 % and 41.3 %, respectively. The drug-loaded compounds displayed sustained drug release over 15 days, remarkably high drug loading capacities and pH-controlled release behavior. The prepared nanostructures were characterized by different characterization technics including FT-IR, PXRD, ZP, TEM, FE-SEM, UV-vis, and BET. In addition, MTT assays were carried out on the HEK-293 and HeLa cell lines to investigate cytotoxicity. Cellular apoptosis analysis was performed to investigate the cell death mechanisms. Grand Canonical Monte Carlo simulations were conducted to analyze the interactions between MOFs and QU. Moreover, the stability of MOFs was also investigated during and after the drug release process. Ultimately, kinetic models of drug release were evaluated.

Solvent-Directed Construction of a Nanoporous Metal-Organic Framework with Potential in Selective Adsorption and Separation of Gas Mixtures Studied by Grand Canonical Monte Carlo Simulations

In this report, a microporous metal-organic framework of [Ca(TDC)(DMA)]n (1) and a two-dimensional coordination polymer of [Ca(TDC)(DMF)2 ]n (2), (TDC2- =Thiophene-2,5-dicarboxylate, DMA=N, N'-dimethylacetamide and DMF=N, N'-dimethylformamide) based on Ca(II) were designed by the effect of solvent, and X-ray analysis was performed for the single crystals of 1 and 2. Then, compound 1 was synthesized in three different methods and identified with a set of analyses. Compared to other adsorbents, MOFs are widely used in the field of adsorption and separation of various gases due to a series of distinctive features such as diverse and adjustable structures pores with different dimensions, high porosity and surface area with regular distribution of active sites. Therefore, the ability of 1 to uptake single gases (CH4 , CO2 , C2 H2 , H2, and N2 ) and separation of several binary mixtures of gases (CO2 /CH4 , CO2 /N2 , CO2 /H2 and CO2 /C2 H2 ), were investigated using Grand Canonical Monte Carlo simulations. Volumetric and gravimetric adsorption isotherms in various operating conditions, the isosteric heat of adsorption (qst ), the chemical potential for each thermodynamic state, and snapshots during the simulation process were reported in all cases. The results obtained from the adsorption simulation indicate that compound 1 has a high capacity for uptake of H2 (16 mmol g-1 ) and N2 (12.5 mmol g-1 ), CO2 (6.6 mmol g-1 ), C2 H2 (5 mmol g-1 ) and CH4 (1.5 mmol g-1 ) gases at 1 bar. It also performs well in separating CO2 in binary mixtures, which can be attributed to the presence of open metal sites in nodes of 1 and their electrostatic tendency to interact with CO2 containing the higher quadrupole dipole moment compared to other components of the mixture.

Multiscale Theoretical Study of Sulfur Dioxide (SO2) Adsorption in Metal–Organic Frameworks

In the present work, we used DFT in order to study the interaction of SO2 with 41 strategically functionalized benzenes that can be incorporated in MOF linkers. The interaction energy of phenyl phosphonic acid (–PO3H2) with SO2 was determined to be the strongest (−10.1 kcal/mol), which is about 2.5 times greater than the binding energy with unfunctionalized benzene (−4.1 kcal/mol). To better understand the nature of SO2 interactions with functionalized benzenes, electron redistribution density maps of the relevant complexes with SO2 were created. In addition, three of the top performing functional groups were selected (–PO3H2, –CNH2NOH, –OSO3H) to modify the IRMOF-8 organic linker and calculate its SO2 adsorption capacity with Grand Canonical Monte Carlo (GCMC) simulations. Our results showed a great increase in the absolute volumetric uptake at low pressures, indicating that the suggested functionalization technique can be used to enhance the SO2 uptake capability not only in MOFs but in a variety of porous materials.

Water-Stable etb-MOFs for Methane and Carbon Dioxide Storage

We utilized the etb platform of MOFs for the synthesis of two new water-stable compounds based on amide functionalized trigonal tritopic organic linkers H₃BTBTB (L1), H₃BTCTB (L2) and Al³⁺ metal ions, namely, Al(L1) and Al(L2). The mesoporous Al(L1) material exhibits an impressive methane (CH₄) uptake at high pressures and ambient temperature. The corresponding values of 192 cm³ (STP) cm^-3, 0.254 g g^-1 at 100 bar, and 298 K are among the highest reported for mesoporous MOFs, while the gravimetric and volumetric working capacities (between 80 bar and 5 bar) can be well compared to the best MOFs for CH₄ storage. Furthermore, at 298 K and 50 bar, Al(L1) adsorbs 50 wt % (304 cm³ (STP) cm^-3) CO₂, values among the best recorded for CO₂ storage using porous materials. To gain insight into the mechanism accounting for the resultant enhanced CH₄ storage capacity, theoretical calculations were performed, revealing the presence of strong CH₄ adsorption sites near the amide groups. Our work demonstrates that amide functionalized mesoporous etb-MOFs can be valuable for the design of versatile coordination compounds with CH₄ and CO₂ storage capacities comparable to ultra-high surface area microporous MOFs.

Surface Modification Strategy for Enhanced NO2 Capture in Metal-Organic Frameworks

The interaction strength of nitrogen dioxide (NO₂) with a set of 43 functionalized benzene molecules was investigated by performing density functional theory (DFT) calculations. The functional groups under study were strategically selected as potential modifications of the organic linker of existing metal–organic frameworks (MOFs) in order to enhance their uptake of NO₂ molecules. Among the functional groups considered, the highest interaction energy with NO₂ (5.4 kcal/mol) was found for phenyl hydrogen sulfate (-OSO₃H) at the RI-DSD-BLYP/def2-TZVPP level of theory—an interaction almost three times larger than the corresponding binding energy for non-functionalized benzene (2.0 kcal/mol). The groups with the strongest NO₂ interactions (-OSO₃H, -PO₃H₂, -OPO₃H₂) were selected for functionalizing the linker of IRMOF-8 and investigating the trend in their NO₂ uptake capacities with grand canonical Monte Carlo (GCMC) simulations at ambient temperature for a wide pressure range. The predicted isotherms show a profound enhancement of the NO₂ uptake with the introduction of the strongly-binding functional groups in the framework, rendering them promising modification candidates for improving the NO₂ uptake performance not only in MOFs but also in various other porous materials.

Continuous Breathing Rare-Earth MOFs Based on Hexanuclear Clusters with Gas Trapping Properties

Guest responsive porous materials represent an important and fascinating class of multifunctional solids that have attracted considerable attention in recent years. An understanding of how these structures form is essential toward their rational design, which is a prerequisite for the development of tailor-made materials for advanced applications. We herein report a novel series of stable rare-earth (RE) MOFs that show a rare continuous breathing behavior and an unprecedented gas-trapping property. We used an asymmetric 4-c tetratopic carboxylate-based organic ligand that is capable of affording highly crystalline materials upon controlled reaction with RE cations. These MOFs, denoted as RE-thc-MOF-1 (RE: Y³⁺, Sm³⁺, Eu³⁺, Tb³⁺, Dy³⁺, Ho³⁺, and Er³⁺), feature hexanuclear RE₆ clusters that display a highly unusual connectivity and serve as unique 8-c hemi-cuboctahedral secondary building block, resulting in a new (3,3,8)-c thc topology. Extensive single-crystal to single-crystal structural analyses coupled with detailed gas (N₂, Ar, Kr, CO₂, CH₄, and Xe) and vapor (EtOH, CH₃CN, C₆H₆, and C₆H₁₄) sorption studies, supported by accurate theoretical calculations, shed light onto the unique swelling behavior. The results reveal a synergistic action involving steric effects, associated with coordinated solvent molecules and 2-fluorobenzoate (2-FBA) nonbridging ligands, as well as cation-framework electrostatic interactions. We were able to probe the individual role of the coordinated solvent molecules and 2-FBA ligands and found that both cooperatively control the gas-breathing and -trapping properties, while 2-FBA controls the vapor adsorption selectivity. These findings provide unique opportunities toward the design and development of tunable RE-based flexible MOFs with tailor-made properties.

Expanding the NUIG MOF family: synthesis and characterization of new MOFs for selective CO2 adsorption, metal ion removal from aqueous systems, and drug delivery applications

Metal organic frameworks (MOFs) have attracted considerable attention in recent years due to their use in a wide range of environmental, industrial and biomedical applications. The employment of benzophenone-4,4'-dicarboxylic acid (bphdcH2) in MOF chemistry provided access to the 3D mixed metal MOFs [CoNa2(bphdc)2(DMF)2]n (NUIG2) and [ZnK2(bphdc)2(DMF)2]n (NUIG3), and the 2D homometallic MOF [Co2(OH)(bphdcH)2(DMF)2(H2O)2]n(OH)·DMF (1·DMF). 1·DMF is based on a dinuclear SBU and consists of interpenetrating networks with an sql topology. Dc magnetic susceptibility studies were carried out in 1·DMF and revealed the presence of weak antiferomagnetic exchange interactions between the metal centres. NUIG2 and NUIG3 are structural analogues of [ZnNa2(bphdc)2(DMF)2]n (NUIG1), which has shown an exceptionally high encapsulation for ibuprophen (Ibu), NO and metal ions. Both NUIG2 and NUIG3 display high metal ion (CoII, NiII, CuII) adsorption capacity, comparable to that of NUIG1, with NUIG2 exhibiting good performance in Ibu uptake (780 mg Ibu per g NUIG2). Monte Carlo simulations were conducted in NUIG1 in order to assess its adsorption capacity for other guest molecules, and revealed that it possesses an outstanding CO2 uptake at ambient pressure, which is larger than that of the previously reported best functioning species (104 vs. 100 cm3 (stp) per cm3). Furthermore, NUIG1 exhibits high selectivity for CO2 over CH4.

A Universal Machine Learning Algorithm for Large-Scale Screening of Materials

Application of machine learning (ML) methods for the determination of the gas adsorption capacities of nanomaterials, such as metal-organic frameworks (MOF), has been extensively investigated over the past few years as a computationally efficient alternative to time-consuming and computationally demanding molecular simulations. Depending on the thermodynamic conditions and the adsorbed gas, ML has been found to provide very accurate results. In this work, we go one step further and we introduce chemical intuition in our descriptors by using the "type" of the atoms in the structure, instead of the previously used building blocks, to account for the chemical character of the MOF. ML predictions for the methane and carbon dioxide adsorption capacities of several tens of thousands of hypothetical MOFs are evaluated at various thermodynamic conditions using the random forest algorithm. For all cases examined, the use of atom types instead of building blocks leads to significantly more accurate predictions, while the number of MOFs needed for the training of the ML algorithm in order to achieve a specified accuracy can be reduced by an order of magnitude. More importantly, since practically there are an unlimited number of building blocks that materials can be made of but a limited number of atom types, the proposed approach is more general and can be considered as universal. The universality and transferability was proved by predicting the adsorption properties of a completely different family of materials after the training of the ML algorithm in MOFs.

A Robust Machine Learning Algorithm for the Prediction of Methane Adsorption in Nanoporous Materials

In the present study, we propose a new set of descriptors that, along with a few structural features of nanoporous materials, can be used by machine learning algorithms for accurate predictions of the gas uptake capacities of these materials. All new descriptors closely resemble the helium atom void fraction of the material framework. However, instead of a helium atom, a particle with an appropriately defined van der Waals radius is used. The set of void fractions of a small number of these particles is found to be sufficient to characterize uniquely the structure of each material and to account for the most important topological features. We assess the accuracy of our approach by examining the predictions of the random forest algorithm in the relative small dataset of the computation-ready, experimental (CoRE) MOFs (∼4700 structures) that have been experimentally synthesized and whose geometrical/structural features have been accurately calculated before. We first performed grand canonical Monte Carlo simulations to accurately determine their methane uptake capacities at two different temperatures (280 and 298 K) and three different pressures (1, 5.8, and 65 bar). Despite the high chemical and structural diversity of the CoRE MOFs, it was found that the use of the proposed descriptors significantly improves the accuracy of the machine learning algorithm, particularly at low pressures, compared to the predictions made based solely on the rest structural features. More importantly, the algorithm can be easily adapted for other types of nanoporous materials beyond MOFs. Convergence of the predictions was reached even for small training set sizes compared to what was found in previous works using the hypothetical MOF database.

Multiscale simulations reveal IRMOF-74-III as a potent drug carrier for gemcitabine delivery

Kotzabasaki et al. use a multiscale computational approach to investigate the microscopic behaviour of gemcitabine stored in (OH)-IRMOF-74-III. The principles can be exploited for nano-carrier screening purposes prior to experimental investigation.

Multi-scale theoretical investigation of hydrogen storage in covalent organic frameworks

The quest for efficient hydrogen storage materials has been the limiting step towards the commercialization of hydrogen as an energy carrier and has attracted a lot of attention from the scientific community. Sophisticated multi-scale theoretical techniques have been considered as a valuable tool for the prediction of materials storage properties. Such techniques have also been used for the investigation of hydrogen storage in a novel category of porous materials known as Covalent Organic Frameworks (COFs). These framework materials are consisted of light elements and are characterized by exceptional physicochemical properties such as large surface areas and pore volumes. Combinations of ab initio, Molecular Dynamics (MD) and Grand Canonical Monte-Carlo (GCMC) calculations have been performed to investigate the hydrogen adsorption in these ultra-light materials. The purpose of the present review is to summarize the theoretical hydrogen storage studies that have been published after the discovery of COFs. Experimental and theoretical studies have proven that COFs have comparable or better hydrogen storage abilities than other competitive materials such as MOF. The key factors that can lead to the improvement of the hydrogen storage properties of COFs are highlighted, accompanied with some recently presented theoretical multi-scale studies concerning these factors.

Designing 3D COFs with enhanced hydrogen storage capacity

Hydrogen storage properties have been studied on newly designed three-dimensional covalent-organic framework (3D-COF). The design of these materials was based on the ctn network of the ultralow density COF-102. The structures were optimized by multiscale techniques and the optimized structures were checked for their storage capacities by grand canonical Monte Carlo simulations. Our simulations demonstrate that the gravimetric uptake of one of these new COFs can overpass the value of 25 wt % in 77 K and reach the Department of Energy's target of 6 wt % in room temperature, classifying them between the top hydrogen storage materials.

The effect of structural and energetic parameters of MOFs and COFs towards the improvement of their hydrogen storage properties

Open-framework materials have been proposed as potential materials for hydrogen storage. Metal-organic framework (MOF) and covalent-organic framework (COF) materials are under extensive study to discover their storage abilities. In particular the IRMOF family of materials have been considered as ideal to study the effect of different factors that affect the hydrogen storage capacity. In this paper, we analyse the effect of different factors such as surface area, pore volume and the interaction of hydrogen with the molecular framework on the hydrogen uptake of such materials. Through this analysis we propose guidelines to enhance hydrogen storage capacity of already synthesized materials and recommend advanced materials for this application.

Pillared graphene: a new 3-D network nanostructure for enhanced hydrogen storage

A multiscale theoretical approach was used to investigate hydrogen storage in a novel three-dimensional carbon nanostructure. This novel nanoporous material has by design tunable pore sizes and surface areas. Its interaction with hydrogen was studied thoroughly via ab initio and grand canonical Monte Carlo calculations. Our results show that, if this material is doped with lithium cations, it can store up to 41 g H2/L under ambient conditions, almost reaching the DOE volumetric requirement for mobile applications.

Improving hydrogen storage capacity of MOF by functionalization of the organic linker with lithium atoms

A combination of quantum and classical calculations have been performed in order to investigate hydrogen storage in metal-organic frameworks (MOFs) modified by lithium alkoxide groups. Ab initio calculations showed that the interaction energies between the hydrogen molecules and this functional group are up to three times larger compared with unmodified MOF. This trend was verified by grand canonical Monte Carlo (GCMC) simulations in various thermodynamic conditions. The gravimetric capacity of the Li-modified MOFs reached the value of 10 wt % at 77 K and 100 bar, while our results are very promising at room temperature, too, with 4.5 wt %.

Carbon nanoscrolls: a promising material for hydrogen storage

A multiscale theoretical approach was used for the investigation of hydrogen storage in the recently synthesized carbon nanoscrolls. First, ab initio calculations at the density functional level of theory (DFT) were performed in order to (a) calculate the binding energy of H2 molecules at the walls of nanoscrolls and (b) fit the parameters of the interatomic potential used in Monte Carlo simulations. Second, classical Monte Carlo simulations were performed for estimating the H2 storage capacity of "experimental size" nanoscrolls containing thousands of atoms. Our results show that pure carbon nanoscrolls cannot accumulate hydrogen because the interlayer distance is too small. However, an opening of the spiral structure to approximately 7 A followed by alkali doping can make them very promising materials for hydrogen storage application, reaching 3 wt % at ambient temperature and pressure.

A multi scale theoretical study of Li+ interaction with carbon nanotubes

We investigated the effect of the curvature in lithium storage at single-walled carbon nanotubes, with both ab-initio and Molecular Dynamics simulations. Our results show that the carbon rings of nanotubes develop strong cation-pi- interactions with Li ion. These interactions result in positioning the alkali metal cation on top of a phenyl group. By using different types of carbon nanotubes it was revealed that the interaction is not affected by the type or the curvature of the nanotubes. Molecular Dynamics simulations of lithium intercalated nanotube bundles pointed at the fact that the cations remain attached to the nanotubes even at room temperature, with a maximum Li to C ratio of 1:2.1.

13C Nuclear magnetic relaxation study of segmental dynamics of hyaluronan in aqueous solutions

(13)C spin-lattice relaxation times (T(1)) and nuclear Overhauser enhancements (NOE) were measured as a function of temperature and magnetic field strength for the hetero-polysaccharide hyaluronan in water solutions. The relaxation data of the endocyclic ring carbons were successfully interpreted in terms of chain segmental motions by using the bimodal time-correlation function of Dejean de la Batie, Laupretre and Monnerie. On the basis of the calculated correlation times for segmental motion and amplitudes of librational motions of the C-H vectors at the various carbon sites of the HA repeating unit, we concluded that intramolecular hydrogen bonding of the secondary structure of HA plays a major role in the conformational flexibility of this carbohydrate molecule. The internal rotation of the free hydroxymethyl groups about the exocyclic C-5-C-6 bonds superimposed on segmental motion has been described as a diffusion process of restricted amplitude. The rate and amplitude of the internal rotation indicate that the hydroxymethyl groups are not involved in intramolecular hydrogen bonding. Finally, the motional parameters describing the local dynamics of the HA chain were correlated with the secondary structure of HA in aqueous solutions.

Hydrogen storage in carbon nanotubes: a multi-scale theoretical study

A Combination of quantum and classical calculations has been performed to investigate the hydrogen storage in single-walled carbon nanotubes (SWNTs). The ab-initio calculations at the Density Functional level of Theory (DFT) show the nature of hydrogen interaction in selected sites of a (5,5) tube walls. On top of this, Molecular Dynamics simulations model large scale nanotube systems and reproduce the storage capacity under variant temperature conditions. Our results indicate that the interaction of hydrogen with SWNTs is very weak and slightly increase of temperature, causes hydrogen diffusion from the tube walls.