From Words to Frameworks: Transformer Models for Metal–Organic Framework Design in Nanotheranostics

Rational design of metal-organic frameworks to deliver methotrexate for targeted rheumatoid arthritis therapy

Crystalline frameworks including primarily metal organic frameworks (MOF) and covalent organic frameworks (COF) have received much attention in the field of heterogeneous catalysts recently. Beyond providing large surface area and spatial confinement, these crystalline frameworks can be designed to either directly act as or influence the catalytic sites at molecular level. This approach offers a unique advantage to gain deeper insights of structure-activity correlations in solid materials, leading to new guiding principles for rational design of advanced solid catalysts for potential important applications related to energy and fine chemical synthesis. In this review, recent key progress achieved in designing MOF- and COF-based molecular solid catalysts and the mechanistic understanding of the catalytic centers and associated reaction pathways are summarized. The state-of-the-art rational design of MOF- and COF-based solid catalysts in this review is grouped into seven different areas: (i) metalated linkers, (ii) metalated moieties anchored on linkers, (iii) organic moieties anchored on linkers, (iv) encapsulated single sites in pores, and (v) metal-mode-based active sites in MOFs. Along with this, some attention is paid to theoretical studies about the reaction mechanisms. Finally, technical challenges and possible solutions in applying these catalysts for practical applications are also presented.

The vastness of materials space, particularly that which is concerned with metal-organic frameworks (MOFs), creates the critical problem of performing efficient identification of promising materials for specific applications. Although high-throughput computational approaches, including the use of machine learning, have been useful in rapid screening and rational design of MOFs, they tend to neglect descriptors related to their synthesis. One way to improve the efficiency of MOF discovery is to data-mine published MOF papers to extract the materials informatics knowledge contained within journal articles. Here, by adapting the chemistry-aware natural language processing tool, ChemDataExtractor (CDE), we generated an open-source database of MOFs focused on their synthetic properties: the DigiMOF database. Using the CDE web scraping package alongside the Cambridge Structural Database (CSD) MOF subset, we automatically downloaded 43,281 unique MOF journal articles, extracted 15,501 unique MOF materials, and text-mined over 52,680 associated properties including the synthesis method, solvent, organic linker, metal precursor, and topology. Additionally, we developed an alternative data extraction technique to obtain and transform the chemical names assigned to each CSD entry in order to determine linker types for each structure in the CSD MOF subset. This data enabled us to match MOFs to a list of known linkers provided by Tokyo Chemical Industry UK Ltd. (TCI) and analyze the cost of these important chemicals. This centralized, structured database reveals the MOF synthetic data embedded within thousands of MOF publications and contains further topology, metal type, accessible surface area, largest cavity diameter, pore limiting diameter, open metal sites, and density calculations for all 3D MOFs in the CSD MOF subset. The DigiMOF database and associated software are publicly available for other researchers to rapidly search for MOFs with specific properties, conduct further analysis of alternative MOF production pathways, and create additional parsers to search for additional desirable properties.

Recently, there has been intense scientific interest in metal–organic frameworks (MOFs) also called porous coordination polymers (PCPs) owing to their designability in terms of the combination of their organic bridging ligands and metal nodes. The applications of MOFs that began with gas sorption materials have been rapidly extended to include sensing, drug delivery, and catalysis. We review herein the recent progress in designing MOFs for photocatalytic applications. The rational design of MOFs provides the development of visible-light-responsive photocatalysts for the hydrogen evolution reaction, and bifunctional catalysts for a UV-light-promoted unique one-pot reaction. In the former system, the photocatalytic reaction proceeds through light absorption by the organic bridging ligand and the following electron transfer to the catalytically active metal-oxo cluster. The latter system is based on the integration of the photocatalytic ability of the metal-oxo cluster and the basicity of the organic bridging ligand in a single MOF material, which allows for the progression of one-pot sequential photocatalytic oxidation and Knoevenagel condensation reaction.

Metal-organic frameworks (MOFs) have emerged as a novel category of porous materials. Currently, rational design of MOFs provides a convenient method to design MOFs with desired properties. After a short introduction of traditional metal MOFs, this chapter discusses the development, properties, and applications of Lanthanide MOFs (Ln-MOFs). Ln-MOFs have garnered much interest due to a wide array of features from the marriage of lanthanide ions with traditional MOFs. An introduction to the Ln-MOF field is presented with several well-known structures to demonstrate various synthetic strategies. Furthermore, interesting structural and chemical properties including porosity, chirality, magnetism, and luminescence are highlighted from recent studies, as well as, a brief overview of potential applications including gas storage, catalysis, and chemical sensing.

Due to the increasing global energy demands, scarce fossil fuel supplies, and environmental issues, the pursued goals of energy technologies are being sustainable, more efficient, accessible, and produce near zero greenhouse gas emissions. Electrochemical water splitting is considered as a highly viable and eco-friendly energy technology. Further, electrochemical carbon dioxide (CO2 ) reduction reaction (CO2 RR) is a cleaner strategy for CO2 utilization and conversion to stable energy (fuels). One of the critical issues in these cleaner technologies is the development of efficient and economical electrocatalyst. Among various materials, metal-organic frameworks (MOFs) are becoming increasingly popular because of their structural tunability, such as pre- and post- synthetic modifications, flexibility in ligand design and its functional groups, and incorporation of different metal nodes, that allows for the design of suitable MOFs with desired quality required for each process. In this review, the design of MOF was discussed for specific process together with different synthetic methods and their effects on the MOF properties. The MOFs as electrocatalysts were highlighted with their performances from the aspects of hydrogen evolution reaction (HER), oxygen evolution reaction (OER), and electrochemical CO2 RR. Finally, the challenges and opportunities in this field are discussed.

The photocatalytic conversion of CO 2 to valuable fuels is hampered by intrinsic challenges in charge separation and product selectivity. Therefore, the construction of single active sites (SASs) within metal organic frameworks (MOFs) and covalent organic frameworks (COFs) has emerged as an effective approach to address these limitations. These materials leverage well‐defined porous structures to create confined reactive microenvironments and incorporate atomically dispersed active sites that maximize metal utilization and enhance product selectivity. This review systematically summarizes recent advances in the rational design of MOF and COF confined SASs, with emphasis on key strategies, including atomic‐level engineering of active sites, modulation of the electronic and optical landscape and confinement effects, and reaction microenvironment engineering. These approaches collectively enhance light absorption, charge carrier dynamics, and intermediate stabilization. Special attention is given to the critical roles of pore confinement, local electric fields, and coordination microenvironments in steering reaction pathways and regulating key intermediates. By combining advanced in situ/operando spectroscopy with theoretical simulations, this review elucidates the fundamental structure–activity relationships governing photocatalytic behavior. Finally, this review outlines future research direction aimed at advancing MOF and COF confined SASs toward practical applications in efficient and stable CO 2 photoconversion.

Metal-organic frameworks (MOFs) promise to engender technology-enabling properties for numerous applications. However, one significant challenge in MOF development is their overwhelmingly large design space, which is intractable to fully explore even computationally. To find diverse optimal MOF designs without exploring the full design space, we develop Vendi Bayesian optimization (VBO), a new algorithm that combines traditional Bayesian optimization with the Vendi score, a recently introduced interpretable diversity measure. Both Bayesian optimization and the Vendi score require a kernel similarity function, we therefore also introduce a novel similarity function in the space of MOFs that accounts for both chemical and structural features. This new similarity metric enables VBO to find optimal MOFs with properties that may depend on both chemistry and structure. We statistically assessed VBO by its ability to optimize three NH3-adsorption dependent performance metrics that depend, to different degrees, on MOF chemistry and structure. With ten simulated campaigns done for each metric, VBO consistently outperformed random search to find high-performing designs within a 1000-MOF subset for (i) NH3 storage, (ii) NH3 removal from membrane plasma reactors, and (iii) NH3 capture from air. Then, with one campaign dedicated to finding optimal MOFs for NH3 storage in a "hybrid" ∼10 000-MOF database, we identify twelve extant and eight hypothesized MOF designs with potentially record-breaking working capacity ΔN NH3 between 300 K and 400 K at 1 bar. Specifically, the best MOF designs are predicted to (i) achieve ΔN NH3 values between 23.6 and 29.3 mmol g-1, potentially surpassing those that MOFs previously experimentally tested for NH3 adsorption would have at the proposed operation conditions, (ii) be thermally stable at the operation conditions and (iii) require only ca. 10% of the energy content in NH3 to release the stored molecule from the MOF. Finally, the analysis of the generated simulation data during the search indicates that a pore size of around 10 Å, a heat of adsorption around 33 kJ mol-1, and the presence of Ca could be part of MOF design rules that could help optimize NH3 working capacity at the proposed operation conditions.

Metal organic frameworks (MOFs) are assembled from metal ions or clusters and organic ligands. The high tunability of these components offers a solid structural foundation for achieving efficient gas chromatography (GC) separation. This review demonstrates that the design of high performance MOFs with suitable stationarity should consider both the thermodynamic interactions provided by these MOFs and the kinetic diffusion of analytes. Thermodynamic parameters are basic indicators for describing the interactions between various analytes and the stationary phase. Thermodynamic parameters such as retention factors, McReynolds constants, enthalpy changes, and entropy changes can reflect the relative intensity of thermodynamic interactions. For example, a larger enthalpy change indicates a stronger thermodynamic interaction between the analytes and stationary phase, whereas a smaller enthalpy change indicates a weaker interaction. In addition, the degree of entropy change reflects the relative degrees of freedom of analytes in the stationary phase. A larger entropy change indicates that the analytes have fewer degrees of freedom in the stationary phase. The higher the degree of restriction, the closer the adsorption of the analytes and, thus, the longer the retention time. Thermodynamic interactions, such as metal affinity, π-π interactions, polarity, and chiral sites, can be rationally introduced into MOF structures by pre- or post-modifications depending on the target analytes. These tailored thermodynamic interactions create a favorable environment with subtle differences for efficient analyte separation. For example, MOF stationarity may require large conjugation centers to provide specific π-π interactions to separate benzenes. Chiral groups may be required in the MOF structure to provide sufficient interactions to separate chiral isomers. The kinetic diffusion rate of the analytes is another critical factor that affects the separation performance of MOFs. The diffusion coefficients of analytes in the stationary phase (Ds) can be used to evaluate their diffusion rates. The chromatographic dynamics equation illustrates that the chromatographic peak of analytes tends to be sharper and more symmetrical when the Ds is large, whereas a wider trailing peak may appear when the Ds is small. The Van Deemter equation also proves that a low Ds may lead to a high theoretical plate height and low column efficiency, whereas a high Ds may lead to a low theoretical plate height and increased column efficiency. Analyte diffusion can be significantly influenced by the pore size, shape, particle size, and packing mode of MOFs. For instance, an excessively small pore size results in increased mass transfer resistance, which affects the diffusion of analytes in the stationary phase, probably leading to serious peak trailing. Thus, a suitable pore size is required to enhance the kinetic diffusion of analytes and improve the separation performance of MOFs. Theoretically, the design of a high performance MOF stationary phase requires the creation of routes for the rapid diffusion of analytes. However, the separation ability of an MOF is determined by not only the kinetic diffusion rate of the analytes but also the thermodynamic interactions it provides. An excessively fast diffusion rate may lead to insufficient interactions between the analytes and MOFs, compromising their ability to effectively separate different analytes. The thermodynamic interactions and kinetic diffusion of analytes are synergistic and mutually essential. Therefore, this review concludes with research on the influence of both the thermodynamic interactions and kinetic diffusion of analytes on the performance of MOF stationary phases. Based on the findings of this review, we propose that high performance MOF stationary phases can be achieved by balancing the thermodynamic interactions and kinetic diffusion of analytes in these phases through the rational design of the MOF structure. We believe that this review provides useful guidelines for the design of high performance MOF stationary phases.

Metal-organic frameworks (MOFs) show important potential in applications such as gas storage, catalysis, and drug delivery. However, the vast chemical space of MOFs makes experimental exploration impractical. While existing computational models often require the full MOF structure to predict key properties, we introduce a deep learning approach that predicts the pore limiting diameter (PLD) using only the metal-linker building blocks. Our method employs a 3D convolutional neural network (CNN) trained on spatial features derived from the 3D coordination of atoms within metal-linker complexes. We constructed a dataset of 25,529 MOFs from CoREMOF-2019 and Tobacco databases, deconstructed them into metal-linker units, and applied voxelization to generate 3D features. These features were then used to train a 3D CNN model, achieving an R² value of 0.86 on an unseen test set. By enabling accurate PLD prediction without requiring the full MOF structure, our approach facilitates early-stage screening and rational design of MOFs. The data and source code for our model are available at https://github.com/ClinicalAI/MOF_LPD_Prediction.

The past 20 years have witnessed tremendous advances in the field of porous materials, including the development of novel metal-organic frameworks (MOFs) that show great potential for practical applications aimed at addressing global environmental and industrial challenges. A critical tool enabling this progress has been reticular chemistry, through which researchers can design materials that exhibit highly regular (i.e., edge-transitive) topologies, based on the assembly of geometrically matched building blocks into specific nets. However, innovation sometimes demands that researchers steer away from default topologies to instead pursue unusual geometries. In this Perspective, we cover this aspect and introduce the concept of geometry mismatch, in which seemingly incompatible building blocks are combined to generate non-default structures. We describe diverse MOF assemblies built through geometry mismatch generated by use of ligand bend angles, twisted functional groups, zigzag ligands and other elements, focusing on carboxylate-based MOFs combined with common inorganic clusters. We aim to provide a fresh perspective on rational design of MOFs and to help readers understand the countless options now available to achieve greater structural complexity in MOFs.

Rational design of metal-organic framework (MOF)-based materials for catalysis, gas capture and storage, requires deep understanding of the host-guest interactions between the MOF and the adsorbed molecules. Solid-State NMR spectroscopy is an established tool for obtaining such structural information, however its low sensitivity limits its application. This limitation can be overcome with dynamic nuclear polarization (DNP) which is based on polarization transfer from unpaired electrons to the nuclei of interest and, as a result, enhancement of the NMR signal. Typically, DNP is achieved by impregnating or wetting the MOF material with a solution of nitroxide biradicals, which prevents or interferes with the study of host-guest interactions. Here we demonstrate how Gd(iii) ions doped into the MOF structure, LaBTB (BTB = 4,4',4''-benzene-1,3,5-triyl-trisbenzoate), can be employed as an efficient polarization agent, yielding up to 30-fold 13C signal enhancement for the MOF linkers, while leaving the pores empty for potential guests. Furthermore, we demonstrate that ethylene glycol, loaded into the MOF as a guest, can also be polarized using our approach. We identify specific challenges in DNP studies of MOFs, associated with residual oxygen trapped within the MOF pores and the dynamics of the framework and its guests, even at cryogenic temperatures. To address these, we describe optimal conditions for carrying out and maximizing the enhancement achieved in DNP-NMR experiments. The approach presented here can be expanded to other porous materials which are currently the state-of-the-art in energy and sustainability research.

Design, synthesis, and applications of metal-organic frameworks (MOFs) are among the most salient fields of research in modern inorganic and materials chemistry. As the structure and physical properties of MOFs are mostly dependent on the organic linkers or ligands, the choice of ligand system is of utmost importance in the design of MOFs. One such crucial organic linker/ligand is terpyridine (tpy), which can adopt various coordination modes to generate an enormous number of metal-organic frameworks. These frameworks generally carry physicochemical characteristics induced by the π-electron-rich (basically N-electron-rich moiety) terpyridines. In this minireview, the construction of 3D MOFs associated with symmetrical terpyridines is discussed. These ligands can be easily derivatized at the lateral phenyl (4'-phenyl) position and incorporate additional organic functionalities. These functionalities lead to some different binding modes and form higher dimensional (3D) frameworks. Therefore, these 3D MOFs can carry multiple features along with the characteristics of terpyridines. Some properties of these MOFs, like photophysical, chemical selectivity, photocatalytic degradation, proton conductivity, and magnetism, etc. have also been discussed and correlated with their frameworks.

Reticular chemistry for the rational design of mechanically robust mesoporous merged-net metal-organic frameworks

Functional porous metal-organic frameworks (MOFs) have been explored for a number of potential applications in catalysis, chemical sensing, water capture, gas storage, and separation. MOFs are among the most promising candidates to address challenges facing our society related to energy and environment, but the successful implementation of functional porous MOF materials are contingent on their stability; therefore, the rational design of stable MOFs plays an important role towards the development of functional porous MOFs. In this Focus article, we summarize progress in the rational design and synthesis of stable MOFs with controllable pores and functionalities. The implementation of reticular chemistry allows for the rational top-down design of stable porous MOFs with targeted topological networks and pore structures from the pre-selected building blocks. We highlight the reticular synthesis and applications of stable MOFs: (1) MOFs based on high valent metal ions (e.g., Al3+, Cr3+, Fe3+, Ti4+ and Zr4+) and carboxylate ligands; (2) MOFs based on low valent metal ions (e.g., Ni2+, Cu2+, and Zn2+) and azolate linkers. We envision that the synthetic strategies, including modulated synthesis and post-synthetic modification, can potentially be extended to other more complex systems like metal-phosphonate framework materials.