Digital Reticular Chemistry

Experimental and Theoretical Insights on Gas Trapping of Noble Gases in MFU-4-Type Metal-Organic Frameworks

Isostructural metal-organic frameworks (MOFs), namely MFU-4 and MFU-4-Br, in which the pore apertures are defined by anionic side ligands (Cl- and Br-, respectively), were synthesized and loaded with noble gases. By selecting the type of side ligand, one can fine-tune the pore aperture size, allowing for precise regulation of the entry and release of gas guests. In this study, we conducted experiments to examine gas loading and release using krypton and xenon as model gases, and we complemented our findings with computational modeling. Remarkably, the loaded gas guests remained trapped inside the pores even after being exposed to air under ambient conditions for extended periods, in some cases for up to several weeks. Therefore, we focused on determining the energy barrier preventing gas release using both theoretical and experimental methods. The results were compared in relation to the types of hosts and guests, providing valuable insights into the gas trapping process in MOFs, as well as programmed gas release in air under ambient conditions. Furthermore, the crystal structure of MFU-4-Br was elucidated using the three-dimensional electron diffraction (3DED) technique, and the bulk purity of the sample was subsequently verified through Rietveld refinement.

Halogen-Driven Single-Crystal to Single-Crystal Transformation Engineering the Cluster-based Spin Crossover Frameworks

Cluster-based spin crossover (SCO) frameworks are a new class of smart metal-organic frameworks (MOFs) with diverse structures and topologies and unique bistable physicochemical properties. Here, we report a cluster-based SCO framework [Fe3{Ag4(CN)6(H2O)}2(TPBA)3](ClO4)2 ⋅ 7DMF (1) with an extremely rare 3,4,6-T108 topology, in which the tripodal [Ag{Ag(CN)2}3(H2O)]2- clusters axially link the Fe2+ ions to form 2D→3D n-fold Borromean entangled networks. Under the guidance of reticular chemistry, the post-synthetic modification (PSM) from 1 with 3,4,6-T108 topology to [Fe3{Ag8X8(CN)6}(TPBA)3] (2_X, X=Cl, Br, I) with urk topology is firstly achieved via single-crystal to single-crystal (SCSC) transformation. Moreover, the successive SCSC transformations from 2_Cl to 2_Br and then to 2_I are realized for the first time. Their SCO behaviors are also modified by halogen-driven stepwise cluster transformations. Hence, these findings provide new strategies for the development of cluster-based SCO MOFs towards the smart functional porous materials.

Computational Modeling of Reticular Materials: The Past, the Present, and the Future

Reticular materials rely on a unique building concept where inorganic and organic building units are stitched together giving access to an almost limitless number of structured ordered porous materials. Given the versatility of chemical elements, underlying nets, and topologies, reticular materials provide a unique platform to design materials for timely technological applications. Reticular materials have now found their way in important societal applications, like carbon capture to address climate change, water harvesting to extract atmospheric moisture in arid environments, and clean energy applications. Combining predictions from computational materials chemistry with advanced experimental characterization and synthesis procedures unlocks a design strategy to synthesize new materials with the desired properties and functions. Within this review, the current status of modeling reticular materials is addressed and supplemented with topical examples highlighting the necessity of advanced molecular modeling to design materials for technological applications. This review is structured as a templated molecular modeling study starting from the molecular structure of a realistic material towards the prediction of properties and functions of the materials. At the end, the authors provide their perspective on the past, present of future in modeling reticular materials and formulate open challenges to inspire future model and method developments.

Merged-nets enumeration for the systematic design of multicomponent reticular structures

Rational design of intricate multicomponent reticular structures is often hindered by the lack of suitable blueprint nets. We established the merged-net approach, proffering optimal balance between designability and complexity, as a systematic solution for the rational assembly of multicomponent structures. In this work, by methodically mapping node-net relationships among 53 basic edge-transitive nets, we conceived a signature net map to identify merging net pairs, resulting in the enumeration of 53 merged nets. We developed a practical design algorithm and proposed more than 100 multicomponent metal-organic framework platforms. The effectiveness of this approach is commended by the successful synthesis of four classes of materials, which is based on merging three-periodic nets with the four possible net periodicities. The construction of multicomponent materials based on derived nets of merged nets highlights the potential of the merged-net approach in accelerating the discovery of intricate reticular materials.

Inverse design of ZIFs through artificial intelligence methods

We report a tool combining a biologically inspired evolutionary algorithm with machine learning to design fine-tuned zeolitic-imidazolate frameworks (ZIFs), a sub-family of MOFs, for desired sets of diffusivities of species i (Di) and Di/Dj of any given mixture of species i and j. We display the efficacy and validitiy of our tool, by designing ZIFs that meet industrial performance criteria of permeability and selectivity, for CO2/CH4, O2/N2 and C3H6/C3H8 mixtures.

Self-Assembly of Super-Uniform Covalent Organic Framework Colloidal Particles into Multi-Dimensional Ordered Superstructures

Precise self-assembly of colloidal particles is crucial for understanding their aggregation properties and preparing macroscopic functional devices. It is currently very challenging to synthesize and self-assemble super-uniform covalent organic framework (COF) colloidal particles into well-organized multidimensional superstructures. Here, simple and versatile strategies are proposed for synthesis of super-uniform COF colloidal particles and self-assembly of them into 1D supraparticles, 2D ordered mono/multilayers, and 3D COF films. For this purpose, several self-assembly techniques are developed, including emulsion solvent evaporation, air-liquid interfacial self-assembly, and drop-casting. These strategies enable the superstructural self-assembly of particles of varying sizes and species without any additional surfactants or chemical modifications. The assembled superstructures maintain the porosity and high specific surface area of their building blocks. The feasibility of the strategies is examined with different types of COFs. This research provides a new approach for the controllable synthesis of super-uniform COF colloidal particles capable of self-assembling into multidimensional superstructures with long-range order. These discoveries hold great promise for the design of emerging multifunctional COF superstructures.

Precision-engineered metal-organic frameworks: fine-tuning reverse topological structure prediction and design

Digital discoveries of metal-organic frameworks (MOFs) have been significantly advanced by the reverse topological approach (RTA). The node-and-linker assembly strategy allows predictable reticulations predefined by in silico coordination templates; however, reticular equivalents lead to substantial combinatorial explosion due to the infinite design space of building units (BUs). Here, we develop a fine-tuned RTA for the structure prediction of MOFs by integrating precise topological constraints and leveraging reticular chemistry, thus transcending traditional exhaustive trial-and-error assembly. From an extensive array of chemically realistic BUs, we subsequently design a database of 94 823 precision-engineered MOFs (PE-MOFs) and further optimize their structures. The PE-MOFs are assessed for post-combustion CO2 capture in the presence of H2O and top-performing candidates are identified by integrating three stability criteria (activation, water and thermal stabilities). This study highlights the potential of synergizing PE with the RTA to enhance efficiency and precision for computational design of MOFs and beyond.

Selective Removal of Denatured Proteins Using MOF Nanopores

Here we present, for the first time, the selective adsorption of denatured proteins using a metal-organic framework (MOF), demonstrating promising potential for protein purification. Typical proteins, such as lysozyme and carbonic anhydrase B, enter the pores of MIL-101 through their narrow apertures when they are denatured to an unfolded state. Selective adsorption is achieved by finely tuning two key features: the sizes of the aperture and cage of the MOF nanopores, which are responsible for sorting unfolded polypeptide chains and inhibiting the translocation of the native form into the pores, respectively. By leveraging this selective adsorption, we successfully purified a mixture of native and denatured proteins by adding MOF to the mixture, achieving a native purity of over 99%.

Construction of Layer-Blocked Covalent Organic Framework Heterogenous Films via Surface-Initiated Polycondensations with Strongly Enhanced Photocatalytic Properties

Imine-linked covalent organic frameworks (COFs) usually show high crystallinity and porosity, while vinyl-linked COFs have excellent semiconducting properties and stability. Therefore, achieving the advantages of imine- and vinyl-linkages in a single COF material is highly interesting but remains challenging. Herein, we demonstrate the fabrication of a layer-blocked COF (LB-COF) heterogeneous film that is composed of imine- and vinyl-linkages through two successive surface-initiated polycondensations. In brief, the bottom layer of imine-linked COF film was constructed on an amino-functionalized substrate via Schiff-base polycondensation, in which the unreacted aldehyde edges could be utilized for initiating aldol polycondensation to prepare the second layer of vinyl-linked COF film. The resultant LB-COF film displays excellent ordering due to the crystalline templating effect from the bottom imine-linked COF layer; meanwhile, the upper vinyl-linked COF layer could strongly enhance its stability and photocatalytic properties. The LB COF also presents superior performance in photocatalytic uranium extraction (320 mg g-1), which is higher than the imine-linked (35 mg g-1) and the vinyl-linked (295 mg g-1) counterpart. This study provides a novel surface-initiated strategy to synthesize layer-blocked COF heterogeneous films that combine the advantages of each building block.

pyCOFBuilder: A Python Package for Automated Creation of Covalent Organic Framework Models Based on the Reticular Approach

Covalent organic frameworks (COFs) have gained significant popularity in recent years due to their unique ability to provide a high surface area and customizable pore geometry and chemistry, making them an ideal choice for a wide range of applications. However, exploring COFs experimentally can be arduous and time-consuming due to their immense number of potential structures. As a result, computational high-throughput studies have become an attractive option. Nevertheless, generating COF structures can also be a challenging and time-consuming task. To address this challenge, here, we introduce the pyCOFBuilder, an open-source Python package designed to facilitate the generation of COF structures for computational studies. The pyCOFBuilder software provides an easy-to-use set of functionalities to generate COF structures following the reticular approach. In this paper, we describe the implementation, main features, and capabilities of the pyCOFBuilder, demonstrating its utility for generating COF structures with varying topologies and chemical properties. pyCOFBuilder is freely available on GitHub at https://github.com/lipelopesoliveira/pyCOFBuilder.

The Promise and Potential of Metal-Organic Frameworks and Covalent Organic Frameworks in Vaccine Nanotechnology

The immune system's complexity and ongoing evolutionary struggle against deleterious pathogens underscore the value of vaccination technologies, which have been bolstering human immunity for over two centuries. Despite noteworthy advancements over these 200 years, three areas remain recalcitrant to improvement owing to the environmental instability of the biomolecules used in vaccines─the challenges of formulating them into controlled release systems, their need for constant refrigeration to avoid loss of efficacy, and the requirement that they be delivered via needle owing to gastrointestinal incompatibility. Nanotechnology, particularly metal-organic frameworks (MOFs) and covalent organic frameworks (COFs), has emerged as a promising avenue for confronting these challenges, presenting a new frontier in vaccine development. Although these materials have been widely explored in the context of drug delivery, imaging, and cancer immunotherapy, their role in immunology and vaccine-related applications is a recent yet rapidly developing field. This review seeks to elucidate the prospective use of MOFs and COFs for biomaterial stabilization, eliminating the necessity for cold chains, enhancing antigen potency as adjuvants, and potentializing needle-free delivery of vaccines. It provides an expansive and critical viewpoint on this rapidly evolving field of research and emphasizes the vital contribution of chemists in driving further advancements.

Coarse-Grained Crystal Graph Neural Networks for Reticular Materials Design

Reticular materials, including metal-organic frameworks and covalent organic frameworks, combine the relative ease of synthesis and an impressive range of applications in various fields from gas storage to biomedicine. Diverse properties arise from the variation of building units─metal centers and organic linkers─in almost infinite chemical space. Such variation substantially complicates the experimental design and promotes the use of computational methods. In particular, the most successful artificial intelligence algorithms for predicting the properties of reticular materials are atomic-level graph neural networks, which optionally incorporate domain knowledge. Nonetheless, the data-driven inverse design involving these models suffers from the incorporation of irrelevant and redundant features such as a full atomistic graph and network topology. In this study, we propose a new way of representing materials, aiming to overcome the limitations of existing methods; the message passing is performed on a coarse-grained crystal graph that comprises molecular building units. To highlight the merits of our approach, we assessed the predictive performance and energy efficiency of neural networks built on different materials representations, including composition-based and crystal-structure-aware models. Coarse-grained crystal graph neural networks showed decent accuracy at low computational costs, making them a valuable alternative to omnipresent atomic-level algorithms. Moreover, the presented models can be successfully integrated into an inverse materials design pipeline as estimators of the objective function. Overall, the coarse-grained crystal graph framework is aimed at challenging the prevailing atom-centric perspective on reticular materials design.

Machine learning guided tuning charge distribution by composition in MOFs for oxygen evolution reaction

Traditional design/optimization of metal-organic frameworks (MOFs) is time-consuming and labor-intensive. In this study, we utilize machine learning (ML) to accelerate the synthesis of MOFs. We have built a library of over 900 MOFs with different metal salts, solvent ratios, reaction durations and temperatures, and utilize zeta potentials as target variables for ML training. A total of four ML models have been used to train the collected dataset and assess their convergence performances, where Random Forest Regression (RFR) and Gradient Boosting Regression (GBR) models show strong correlation and accurate predictions. We then predicted two kinds of MOFs from RFR and GBR models. Remarkably, the experimentally data of the synthesized MOFs closely matched the predicted results, and these MOFs exhibited excellent electrocatalytic performances for oxygen evolution. This study would have general implications in the utilization of machine learning for accelerating the synthesis of MOFs for diverse applications.

Hierarchical Self-Assembly of Capsule-Shaped Zirconium Coordination Cages with Quaternary Structure

Biological macromolecules exhibit emergent functions through hierarchical self-assembly, a concept that is extended to design artificial supramolecular assemblies. Here, the first example of breaking the common parallel arrangement of capsule-shaped zirconium coordination cages is reported by constructing the hierarchical porous framework ZrR-1. ZrR-1 adopts a quaternary structure resembling protein and contains 12-connected chloride clusters, representing the highest connectivity for zirconium-based cages reported thus far. Compared to the parallel framework ZrR-2, ZrR-1 demonstrated enhanced stability in acidic aqueous solutions and a tenfold increase in BET surface area (879 m2  g-1 ). ZrR-1 also exhibits excellent proton conductivity, reaching 1.31 × 10-2 S·cm-1 at 353 K and 98% relative humidity, with a low activation energy of 0.143 eV. This finding provides insights into controlling the hierarchical self-assembly of metal-organic cages to discover superstructures with emergent properties.

Reticular chemistry guided precise construction of zirconium-pentacarboxylate frameworks with 5-connected Zr6 clusters

Zirconium-based metal-organic frameworks (Zr-MOFs) have been extensively studied due to their very rich structural chemistry. The combination of nearly unlimited carboxylic acid-based linkers and Zr6 clusters with multiple connectivities has led to diverse structures and specific properties of resultant Zr-MOFs. Herein, we demonstrate the successful use of reticular chemistry to construct two novel Zr-MOFs, HIAM-4040 and HIAM-4040-OH, with zfu topology. Based on a thorough structural analysis of (4,4)-connected lvt-type Zr-tetracarboxylate frameworks and a judicious linker design, we have obtained the first example of a Zr-pentacarboxylate framework featuring unprecedented 5-connected organic linkers and 5-connected Zr6 clusters. Compared with HIAM-4040, a larger Stokes shift is achieved in HIAM-4040-OH via hydroxyl group induced excited-state intramolecular proton transfer (ESIPT). HIAM-4040-OH exhibits high chemical and thermal stability and is used for HClO detection in aqueous solution with excellent sensitivity and selectivity.

Covalent Organic Frameworks: Opportunities for Rational Materials Design in Cancer Therapy

Nanomedicines are extensively used in cancer therapy. Covalent organic frameworks (COFs) are crystalline organic porous materials with several benefits for cancer therapy, including porosity, design flexibility, functionalizability, and biocompatibility. This review examines the use of COFs in cancer therapy from the perspective of reticular chemistry and function-oriented materials design. First, the modification sites and functionalization methods of COFs are discussed, followed by their potential as multifunctional nanoplatforms for tumor targeting, imaging, and therapy by integrating functional components. Finally, some challenges in the clinical translation of COFs are presented with the hope of promoting the development of COF-based anticancer nanomedicines and bringing COFs closer to clinical trials.

The future of metal-organic frameworks and covalent organic frameworks: rational synthesis and customized applications

Metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) are designable and tunable functional crystalline porous materials that have been explored for applications such as catalysis, chemical sensing, water harvesting, gas storage, and separation. On the basis of reticular chemistry, the rational design and synthesis of MOFs and COFs allows us to have unprecedented control over their structural features and functionalities. Given the vast number of possible MOF and COF structures and the flexibility of modifying them, it remains challenging to navigate the infinite chemical space solely through a trial-and-error process. This Opinion Article provides a brief perspective of the current state and future prospects of MOFs and COFs. We envision that emerging technologies based on machine learning and robotics, such as high-throughput computational screening and fully automatic synthesis, can potentially address some challenges facing this field, accelerating the discovery of porous framework materials and the development of rational synthetic strategies for customized applications.

A GPT-4 Reticular Chemist for Guiding MOF Discovery

We present a new framework integrating the AI model GPT-4 into the iterative process of reticular chemistry experimentation, leveraging a cooperative workflow of interaction between AI and a human researcher. This GPT-4 Reticular Chemist is an integrated system composed of three phases. Each of these utilizes GPT-4 in various capacities, wherein GPT-4 provides detailed instructions for chemical experimentation and the human provides feedback on the experimental outcomes, including both success and failures, for the in-context learning of AI in the next iteration. This iterative human-AI interaction enabled GPT-4 to learn from the outcomes, much like an experienced chemist, by a prompt-learning strategy. Importantly, the system is based on natural language for both development and operation, eliminating the need for coding skills, and thus, make it accessible to all chemists. Our collaboration with GPT-4 Reticular Chemist guided the discovery of an isoreticular series of MOFs, with each synthesis fine-tuned through iterative feedback and expert suggestions. This workflow presents a potential for broader applications in scientific research by harnessing the capability of large language models like GPT-4 to enhance the feasibility and efficiency of research activities.

A roadmap to enhance gas permselectivity in metal-organic framework-based mixed-matrix membranes

Performing gas separation at high efficiency with minimum energy input and reduced carbon footprint is a major challenge. While several separation methods exist at various technology readiness levels, porous membrane-based separation is considered as a disruptive technology. To attain sustainability and required efficiency, different approaches of membrane design have been explored. However, the selectivity-permeation trade-off and membrane aging have restricted further advancement. In this regard, a new generation composite made of organic polymers and metal-organic framework (MOF) fillers shows substantial promise. Organic polymer matrix allows easy processibility, but it has poor permselectivity for gas molecules. Metal-organic frameworks are excellent sieving materials; however, they suffer from poor processibility issues. A combination of these two components makes an ideal sieving membrane, which can potentially outnumber the existing energy intensive distillation strategies. In this perspective, we have discussed key indices that regulate gas permselectivity by a careful selection of the existing literature. While the target gas flux and selectivity values have been a part of many previous reviews and articles, we have presented a concise discussion on the interface design of the MOF-polymer membrane, morphology, and orientation control of MOF fillers in the matrix. Following this, a future roadmap to overcome challenges related to MOF-polymer interfacial defects is outlined.

Engineering photocatalytic ammonia synthesis

Photocatalytic ammonia synthesis (PAS) is an emerging zero carbon emission technology, which is critical for mitigating energy crises and achieving carbon neutrality. Herein, we summarize the recent advances and challenges in PAS from an engineering perspective based on its whole chain process, i.e., materials engineering, structure engineering and reaction engineering. For materials engineering, we discuss the commonly used photocatalytic materials including metal oxides, bismuth oxyhalides and graphitic carbon nitride and emerging materials, such as organic frameworks, along with the analysis of their characteristics and regulation methods to enhance the PAS performance. For structure engineering, the design of photocatalysts is described in terms of morphology, vacancy and band, corresponding to the crystal, atom and electron scales, respectively. Moreover, the structure-performance relationship of photocatalysts has been deeply explored in this section. For reaction engineering, we identify three key processes from the chemical reaction and mass transfer, i.e., nitrogen activation, molecule transfer and electron transfer, to intensify and optimize the PAS reaction. Hopefully, this review will provide a novel paradigm for the design and preparation of high-efficiency ammonia synthesis photocatalysts and inspire the practical application of PAS.

Recent Advances in Multifunctional Reticular Framework Nanoparticles: A Paradigm Shift in Materials Science Road to a Structured Future

Porous organic frameworks (POFs) have become a highly sought-after research domain that offers a promising avenue for developing cutting-edge nanostructured materials, both in their pristine state and when subjected to various chemical and structural modifications. Metal-organic frameworks, covalent organic frameworks, and hydrogen-bonded organic frameworks are examples of these emerging materials that have gained significant attention due to their unique properties, such as high crystallinity, intrinsic porosity, unique structural regularity, diverse functionality, design flexibility, and outstanding stability. This review provides an overview of the state-of-the-art research on base-stable POFs, emphasizing the distinct pros and cons of reticular framework nanoparticles compared to other types of nanocluster materials. Thereafter, the review highlights the unique opportunity to produce multifunctional tailoring nanoparticles to meet specific application requirements. It is recommended that this potential for creating customized nanoparticles should be the driving force behind future synthesis efforts to tap the full potential of this multifaceted material category.

Beyond Solvothermal: Alternative Synthetic Methods for Covalent Organic Frameworks

Covalent organic frameworks (COFs) are crystalline porous organic materials that hold a wealth of potential applications across various fields. The development of COFs, however, is significantly impeded by the dearth of efficient synthetic methods. The traditional solvothermal approach, while prevalent, is fraught with challenges such as complicated processes, excessive energy consumption, long reaction times, and limited scalability, rendering it unsuitable for practical applications. The quest for simpler, quicker, more energy-efficient, and environmentally benign synthetic strategies is thus paramount for bridging the gap between academic COF chemistry and industrial application. This Review provides an overview of the recent advances in alternative COF synthetic methods, with a particular emphasis on energy input. We discuss representative examples of COF synthesis facilitated by microwave, ultrasound, mechanic force, light, plasma, electric field, and electron beam. Perspectives on the advantages and limitations of these methods against the traditional solvothermal approach are highlighted.

ChatGPT Chemistry Assistant for Text Mining and the Prediction of MOF Synthesis

We use prompt engineering to guide ChatGPT in the automation of text mining of metal-organic framework (MOF) synthesis conditions from diverse formats and styles of the scientific literature. This effectively mitigates ChatGPT's tendency to hallucinate information, an issue that previously made the use of large language models (LLMs) in scientific fields challenging. Our approach involves the development of a workflow implementing three different processes for text mining, programmed by ChatGPT itself. All of them enable parsing, searching, filtering, classification, summarization, and data unification with different trade-offs among labor, speed, and accuracy. We deploy this system to extract 26 257 distinct synthesis parameters pertaining to approximately 800 MOFs sourced from peer-reviewed research articles. This process incorporates our ChemPrompt Engineering strategy to instruct ChatGPT in text mining, resulting in impressive precision, recall, and F1 scores of 90-99%. Furthermore, with the data set built by text mining, we constructed a machine-learning model with over 87% accuracy in predicting MOF experimental crystallization outcomes and preliminarily identifying important factors in MOF crystallization. We also developed a reliable data-grounded MOF chatbot to answer questions about chemical reactions and synthesis procedures. Given that the process of using ChatGPT reliably mines and tabulates diverse MOF synthesis information in a unified format while using only narrative language requiring no coding expertise, we anticipate that our ChatGPT Chemistry Assistant will be very useful across various other chemistry subdisciplines.

Three dimensional cyclic trinuclear units based metal-covalent organic frameworks for electrochemical CO2RR

A three-dimensional metal-covalent organic framework (3D-MCOF) based on cyclic trinuclear units was synthesized using organic tetrahedral linkers and copper-based cyclic trinuclear complexes. The novel type of 3D-MCOF, named 3D-CTU-MCOF, with the ctn topology, is reported herein for the first time. Our study demonstrated enhanced electrocatalytic capacity for CO2 reduction reaction of 3D-CTU-MCOF compared to independent cyclic trinuclear units.

Three-dimensional covalent organic frameworks with pto and mhq-z topologies based on Tri- and tetratopic linkers

Three-dimensional (3D) covalent organic frameworks (COFs) possess higher surface areas, more abundant pore channels, and lower density compared to their two-dimensional counterparts which makes the development of 3D COFs interesting from a fundamental and practical point of view. However, the construction of highly crystalline 3D COF remains challenging. At the same time, the choice of topologies in 3D COFs is limited by the crystallization problem, the lack of availability of suitable building blocks with appropriate reactivity and symmetries, and the difficulties in crystalline structure determination. Herein, we report two highly crystalline 3D COFs with pto and mhq-z topologies designed by rationally selecting rectangular-planar and trigonal-planar building blocks with appropriate conformational strains. The pto 3D COFs show a large pore size of 46 Å with an extremely low calculated density. The mhq-z net topology is solely constructed from totally face-enclosed organic polyhedra displaying a precise uniform micropore size of 1.0 nm. The 3D COFs show a high CO₂ adsorption capacity at room temperature and can potentially serve as promising carbon capture adsorbents. This work expands the choice of accessible 3D COF topologies, enriching the structural versatility of COFs.

An Ecosystem for Digital Reticular Chemistry

The vastness of the materials design space makes it impractical to explore using traditional brute-force methods, particularly in reticular chemistry. However, machine learning has shown promise in expediting and guiding materials design. Despite numerous successful applications of machine learning to reticular materials, progress in the field has stagnated, possibly because digital chemistry is more an art than a science and its limited accessibility to inexperienced researchers. To address this issue, we present mofdscribe, a software ecosystem tailored to novice and seasoned digital chemists that streamlines the ideation, modeling, and publication process. Though optimized for reticular chemistry, our tools are versatile and can be used in nonreticular materials research. We believe that mofdscribe will enable a more reliable, efficient, and comparable field of digital chemistry.

CRAFTED: An exploratory database of simulated adsorption isotherms of metal-organic frameworks

Grand Canonical Monte Carlo is an important method for performing molecular-level simulations and assisting the study and development of nanoporous materials for gas capture applications. These simulations are based on the use of force fields and partial charges to model the interaction between the adsorbent molecules and the solid framework. The choice of the force field parameters and partial charges can significantly impact the results obtained, however, there are very few databases available to support a comprehensive impact evaluation. Here, we present a database of simulations of CO₂ and N₂ adsorption isotherms on 690 metal-organic frameworks taken from the CoRE MOF 2014 database. We performed simulations with two force fields (UFF and DREIDING), six partial charge schemes (no charges, Qeq, EQeq, MPNN, PACMOF, and DDEC), and three temperatures (273, 298, 323 K). The resulting isotherms compose the Charge-dependent, Reproducible, Accessible, Forcefield-dependent, and Temperature-dependent Exploratory Database (CRAFTED) of adsorption isotherms.

Possibilities and Limitations in Monomer Combinations for Ternary Two-Dimensional Covalent Organic Frameworks

The diversity and complexity of covalent organic frameworks (COFs) can be largely increased by incorporating multiple types of monomers with different topologies or sizes. However, an increase in the number of monomer types significantly complicates the COF formation process. Accordingly, much remains unclear regarding the viability of monomer combinations for ternary or higher-arity COFs. Herein, we show that, through an extensive examination of 12 two-nodes-one-linker ([2 + 1]) combinations, monomer-set viability is determined primarily by the conformational strain originating from disordered monomer arrangements, rather than other factors such as the difference in COF formation kinetics between monomers. When monomers cannot accommodate the strain associated with the formation of a locally disordered, yet crystalline framework, the corresponding [2 + 1] condensation yields a mixture of different COFs or an amorphous polymer. We also demonstrate that a node-linker pair that does not form a binary COF can be integrated to generate a single-phase framework upon addition of a small amount of the third component. These results will clarify the factors behind the successful formation of multicomponent COFs and refine their design by enabling accurate differentiation between allowed and disallowed monomer combinations.

Construction of Covalent Organic Frameworks via Multicomponent Reactions

Multicomponent reactions (MCRs) combine at least three reactants to afford the desired product in a highly atom-economic way and are therefore viewed as efficient one-pot combinatorial synthesis tools allowing one to significantly boost molecular complexity and diversity. Nowadays, MCRs are no longer confined to organic synthesis and have found applications in materials chemistry. In particular, MCRs can be used to prepare covalent organic frameworks (COFs), which are crystalline porous materials assembled from organic monomers and exhibit a broad range of properties and applications. This synthetic approach retains the advantages of small-molecule MCRs, not only strengthening the skeletal robustness of COFs, but also providing additional driving forces for their crystallization, and has been used to prepare a series of robust COFs with diverse applications. The present perspective article provides the general background for MCRs, discusses the types of MCRs employed for COF synthesis to date, and addresses the related critical challenges and future perspectives to inspire the MCR-based design of new robust COFs and promote further progress in this emerging field.

Recent progress of metal-organic frameworks as sensors in (bio)analytical fields: towards real-world applications

The deployment of metal-organic frameworks (MOFs) in a plethora of analytical and bioanalytical applications is a growing research area. Their unique properties such as high but tunable porosity, well-defined channels or pores, and ease of post-synthetic modification to incorporate additional functional units make them ideal candidates for sensing applications. This is possible because the interaction of analytes with a MOF often results in a change in its structure, eventually leading to a modification of the intrinsic physicochemical properties of the MOF which is then transduced into a measurable signal. The high porosity allows for the adsorption of analytes very efficiently, while the tunable pore sizes/nature and/or installation of specific recognition groups allow modulating the affinity towards different classes of compounds, which in turn lead to good sensor sensitivity and selectivity, respectively. Some figures are given to illustrate the potential of MOF-based sensors in the most relevant application fields, and future challenges and opportunities to their possible translation from academia (i.e., laboratory testing of MOF sensing properties) to industry (i.e., real-world analytical sensor devices) are critically discussed.

Saiz P, Reizabal A, Wuttke S, Celaya-Azcoaga L, Valverde A, Fernández de Luis R. A State-of-the-Art of Metal-Organic Frameworks for Chromium Photoreduction vs. Photocatalytic Water Remediation

Hexavalent chromium (Cr(VI)) is a highly mobile cancerogenic and teratogenic heavy metal ion. Among the varied technologies applied today to address chromium water pollution, photocatalysis offers a rapid reduction of Cr(VI) to the less toxic Cr(III). In contrast to classic photocatalysts, Metal-Organic frameworks (MOFs) are porous semiconductors that can couple the Cr(VI) to Cr(III) photoreduction to the chromium species immobilization. In this minireview, we wish to discuss and analyze the state-of-the-art of MOFs for Cr(VI) detoxification and contextualizing it to the most recent advances and strategies of MOFs for photocatalysis purposes. The minireview has been structured in three sections: (i) a detailed discussion of the specific experimental techniques employed to characterize MOF photocatalysts, (ii) a description and identification of the key characteristics of MOFs for Cr(VI) photoreduction, and (iii) an outlook and perspective section in order to identify future trends.

ZIF-L to ZIF-8 Transformation: Morphology and Structure Controls

The control of the structure, shape, and components of metal-organic frameworks, in which metal ions and organic ligands coordinate to form crystalline nanopore structures, plays an important role in the use of many electrochemical applications, such as energy storage, high-performance photovoltaic devices, and supercapacitors. In this study, systematic controls of synthesis variables were performed to control the morphology of ZIF-8 during the ZIF-L-to-ZIF-8 transformation of ZIF-L, which has the same building block as ZIF-8 but forms a two-dimensional structure. Furthermore, additional precursors or surfactants (Zn2+, 2mIm, and CTAB) were introduced during the transition to determine whether the alteration could be regulated. Lastly, the partial substitution insertion of a new organic precursor, 2abIm, during the ZIF-L-to-ZIF-8 transformation of ZIF-L was achieved, and modulation of the adsorption and pore characteristics (suppression of gate-opening properties of ZIF-8) has been confirmed.

Progress in Hybridization of Covalent Organic Frameworks and Metal-Organic Frameworks

Metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) hybrid materials are a class of porous crystalline materials that integrate MOFs and COFs with hierarchical pore structures. As an emerging porous frame material platform, MOF/COF hybrid materials have attracted tremendous attention, and the field is advancing rapidly and extending into more diverse fields. Extensive studies have shown that a broad variety of MOF/COF hybrid materials with different structures and specific properties can be synthesized from diverse building blocks via different chemical reactions, driving the rapid growth of the field. The allowed complementary utilization of π-conjugated skeletons and nanopores for functional exploration has endowed these hybrid materials with great potential in challenging energy and environmental issues. It is necessary to prepare a "family tree" to accurately trace the developments in the study of MOF/COF hybrid materials. This review comprehensively summarizes the latest achievements and advancements in the design and synthesis of MOF/COF hybrid materials, including COFs covalently bonded to the surface functional groups of MOFs (MOF@COF), MOFs grown on the surface of COFs (COF@MOF), bridge reaction between COF and MOF (MOF+COF), and their various applications in catalysis, energy storage, pollutant adsorption, gas separation, chemical sensing, and biomedicine. It concludes with remarks concerning the trend from the structural design to functional exploration and potential applications of MOF/COF hybrid materials.

Ionic Conduction Mechanism and Design of Metal-Organic Framework Based Quasi-Solid-State Electrolytes

We report the theoretical and experimental investigation of two polyoxometalate-based metal-organic frameworks (MOFs), [(MnMo6)2(TFPM)]imine and [(AlMo6)2(TFPM)]imine, as quasi-solid-state electrolytes. Classical molecular dynamics coupled with quantum chemistry and grand canonical Monte Carlo are utilized to model the corresponding diffusion and ionic conduction in the two materials. Using different approximate levels of ion diffusion behavior, the primary ionic conduction mechanism was identified as solvent-assisted hopping (>77%). Detailed static and dynamic solvation structures were obtained to interpret Li+ motion with high spatial and temporal resolution. A rationally designed noninterpenetrating MOF-688(one-fold) material is proposed to achieve 6-8 times better performance (1.6-1.7 mS cm-1) than the current state-of-the-art (0.19-0.35 mS cm-1).

Automated Rational Design of Metal-Organic Polyhedra

Metal-organic polyhedra (MOPs) are hybrid organic-inorganic nanomolecules, whose rational design depends on harmonious consideration of chemical complementarity and spatial compatibility between two or more types of chemical building units (CBUs). In this work, we apply knowledge engineering technology to automate the derivation of MOP formulations based on existing knowledge. For this purpose we have (i) curated relevant MOP and CBU data; (ii) developed an assembly model concept that embeds rules in the MOP construction; (iii) developed an OntoMOPs ontology that defines MOPs and their key properties; (iv) input agents that populate The World Avatar (TWA) knowledge graph; and (v) input agents that, using information from TWA, derive a list of new constructible MOPs. Our result provides rapid and automated instantiation of MOPs in TWA and unveils the immediate chemical space of known MOPs, thus shedding light on new MOP targets for future investigations.

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.

MOF Synthesis Prediction Enabled by Automatic Data Mining and Machine Learning

Despite rapid progress in the field of metal–organic frameworks (MOFs), the potential of using machine learning (ML) methods to predict MOF synthesis parameters is still untapped. Here, we show how ML can be used for rationalization and acceleration of the MOF discovery process by directly predicting the synthesis conditions of a MOF based on its crystal structure. Our approach is based on: i) establishing the first MOF synthesis database via automatic extraction of synthesis parameters from the literature, ii) training and optimizing ML models by employing the MOF database, and iii) predicting the synthesis conditions for new MOF structures. The ML models, even at an initial stage, exhibit a good prediction performance, outperforming human expert predictions, obtained through a synthesis survey. The automated synthesis prediction is available via a web‐tool on https://mof‐synthesis.aimat.science.

Modulating Chemical Environments of Metal-Organic Framework-Supported Molybdenum(VI) Catalysts for Insights into the Structure-Activity Relationship in Cyclohexene Epoxidation

Solid supports are crucial in heterogeneous catalysis due to their profound effects on catalytic activity and selectivity. However, elucidating the specific effects arising from such supports remains challenging. We selected a series of metal-organic frameworks (MOFs) with 8-connected Zr₆ nodes as supports to deposit molybdenum(VI) onto to study the effects of pore environment and topology on the resulting Mo-supported catalysts. As characterized by X-ray absorption spectroscopy (XAS) and single-crystal X-ray diffraction (SCXRD), we modulated the chemical environments of the deposited Mo species. For Mo-NU-1000, the Mo species monodentately bound to the Zr₆ nodes were anchored in the microporous c-pore, but for Mo-NU-1008 they were bound in the mesopore of Mo-NU-1008. Both monodentate and bidentate modes were found in the mesopore of Mo-NU-1200. Cyclohexene epoxidation with H₂O₂ was probed to evaluate the support effect on catalytic activity and to unveil the resulting structure-activity relationships. SCXRD and XAS studies demonstrated the atomically precise structural differences of the Mo binding motifs over the course of cyclohexene epoxidation. No apparent structural change was observed for Mo-NU-1000, whereas the monodentate mode of Mo species in Mo-NU-1008 and the monodentate and bidentate Mo species in Mo-NU-1200 evolved to a new bidentate mode bound between two adjacent oxygen atoms from the Zr₆ node. This work demonstrates the great advantage of using MOF supports for constructing heterogeneous catalysts with modulated chemical environments of an active species and elucidating structure-activity relationships in the resulting reactions.

Water adsorption in porous organic crystals of adamantane-bearing macrocycles

Adamantane-based macrocycles with pyrazine or tetrazine units afforded porous crystals with distinct surface properties of 1D pores, which captured multiple water molecules from the air or liquid water in a single-crystal-to-single-crystal fashion.

Tuning the lattice parameters and porosity of 2D imine covalent organic frameworks by chemically integrating 4-aminobenzaldehyde as a bifunctional linker

4-Aminobenzaldehyde can be used as a linker to construct a series of new COFs and can also tune the lattice parameters, crystallinity, and porosity of these COFs.