Secondary building units as the turning point in the development of the reticular chemistry of MOFs

A comparative study of moisture adsorption on GO, MOF-5, and GO/MOF-5 composite for applications in atmospheric water harvesting

Water scarcity is an alarming situation across the globe. Several methods have been reported in the literature to minimize the water shortage problem. Sorbent-based atmospheric water harvesting (SBAWH) is considered an energy-efficient, low-cost strategy, and sustainable approach. In the present study, the synthesis of graphene oxide (GO) was carried out using a modified Hummers' method, while the synthesis of MOF-5 and a GO/MOF-5 composite was carried out using a solvothermal approach. The synthesized materials were characterized by X-ray diffraction analysis (XRD), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR). The phase composition and crystallinity of all synthesized samples were confirmed by XRD analysis. SEM analysis provided information about the surface morphology of all synthesized samples. The adsorption of water vapors on surfaces of GO, MOF-5, and the GO/MOF-5 composite was evaluated by FTIR analysis. The negative charge was explored by the PZC technique on the surface of all synthesized materials. The water adsorption characteristics of GO, MOF-5, and the GO/MOF-5 composite were evaluated using an atmospheric water harvesting (AWH) plant. The maximum adsorption capacity of 542 mg g-1 was achieved by the MOF at 55% RH (relative humidity), while a low adsorption capacity of the MOF was observed at higher humidity values. This problem was overcome by making a GO/MOF-5 composite. GO imparts structural stability to the MOF-5 structure at higher humidity values. The maximum adsorption capacity of 1137 mg g-1 was achieved by the GO/MOF-5 composite at 75% RH. Several isotherm models, such as Langmuir, Freundlich, and Temkin, were applied to confirm the single-site occupation by water molecules and chemisorption behavior. Several thermodynamic properties were calculated, including isosteric heat (Q st), Gibbs free energy (ΔG), and sorption entropy (ΔS). The overall thermodynamics study confirms that the adsorption process is spontaneous and exothermic. In addition, second-order kinetics confirms that all synthesized material shows chemisorption behavior.

PACMAN: A Robust Partial Atomic Charge Predicter for Nanoporous Materials Based on Crystal Graph Convolution Networks

We report a fast and easy method (PACMAN) to assign partial atomic charges on metal-organic framework (MOF) and covalent-organic framework (COF) crystal structures based on graph convolution networks (GCNs) trained on >1.8 million high-fidelity partial atomic charge data obtained from the Quantum Metal-Organic Framework (QMOF) database. The developed model shows outstanding performance, achieving a mean absolute error (MAE) of 0.0055 e (test set performance) while maintaining consistency with DDEC6, Bader, and CM5 charges across diverse chemistry and topologies of MOFs and COFs. We find that the new method accurately assigns partial atomic charges for ion-containing nanoporous materials, which has not been possible in previous machine learning (ML) models. Grand canonical Monte Carlo (GCMC) simulation results for CO2 and N2 uptakes and the Widom particle insertion calculation for Henry's law constant of water results based on PACMAN and the original DDEC6 charges show excellent agreements compared to other ML models reported in the literature. The runtime analysis of the new method demonstrates that the partial atomic charges of MOF and COF structures with up to 500 atoms can be obtained in less than 10 s. An easy-to-use web interface has been developed to facilitate the adoption of the developed model.

MOFs for next-generation cancer therapeutics through a biophysical approach-a review

Metal-organic frameworks (MOFs) have emerged as promising nanocarriers for cancer treatment due to their unique properties. Featuring high porosity, extensive surface area, chemical stability, and good biocompatibility, MOFs are ideal for efficient drug delivery, targeted therapy, and controlled release. They can be designed to target specific cellular organelles to disrupt metabolic processes in cancer cells. Additionally, functionalization with enzymes mimics their catalytic activity, enhancing photodynamic therapy and overcoming apoptosis resistance in cancer cells. The controllable and regular structure of MOFs, along with their tumor microenvironment responsiveness, make them promising nanocarriers for anticancer drugs. These carriers can effectively deliver a wide range of drugs with improved bioavailability, controlled release rate, and targeted delivery efficiency compared to alternatives. In this article, we review both experimental and computational studies focusing on the interaction between MOFs and drug, explicating the release mechanisms and stability in physiological conditions. Notably, we explore the relationship between MOF structure and its ability to damage cancer cells, elucidating why MOFs are excellent candidates for bio-applicability. By understanding the problem and exploring potential solutions, this review provides insights into the future directions for harnessing the full potential of MOFs, ultimately leading to improved therapeutic outcomes in cancer treatment.

Photocatalytic Hydrosilylation over Pt@UiO-66-NH2: Enhanced Activity and Polymerization Kinetics

Metal-organic frameworks (MOFs) have shown great research and application value in various types of hydrosilylation reactions. However, studies on photocatalysis-induced hydrosilylation using MOFs are extremely rare. Metal nanoparticles (MNPs)@MOFs are extensively studied for their excellent structural tunability and photocatalytic activity, but there are few reports on their application in photocatalytic hydrosilylation. Here, a novel photocatalyst consisting of platinum (Pt) nanoparticles immobilized in a MOF framework is synthesized and used for photocatalytic hydrosilylation. The effects of various factors on hydrosilylation conversion are investigated, including catalyst concentration, substrate ratio, and irradiation intensity. Furthermore, the photoreactivity of the synthesized Pt catalyst is evaluated in the presence of different concentrations of 2-chlorothixanthone as a photosensitizer. It is noteworthy that the conversion of the reaction increases with increasing catalyst concentration or photosensitizer concentration, whereas increasing the polymethylhydrosiloxane content does not lead to a significant increase in conversion. This study demonstrates the potential of MNPs@MOFs as efficient photocatalysts for photoinduced hydrosilylation reactions and paves the way for future applications in this area.

Transition Behaviors of Isostructural Hydrogen-Bonded Frameworks Composed of Naphthalene, Quinoxaline, and Pyrazinopyrazine Derivatives

A series of isostructural reticular frameworks with systematic differences on chemical structures allows us to disclose correlations between specific structural factors and properties, providing insights for designing novel porous materials. However, even slight differences in the molecular structure often lead to non-isostructural polymorphic frameworks particularly in the case of hydrogen-bonded organic frameworks (HOFs) because the structures of HOFs are based on a subtle balance of reversible interactions. In this study, we found that three simple analogues of tetracarboxylic acids with naphthalene, quinoxaline, and pyrazinopyrazine cores (NT, QX, and PP, respectively) yielded isostructural solvated HOFs (NT-1, QX-1, and PP-1, respectively), where hydrogen-bonded sql-networked sheets were slip-stacked with closely similar manners. More importantly, these isostructural HOFs underwent structural transformations in different manners upon removal of the guest solvents. Comparison of the crystal structures of the HOFs before and after the transformation revealed that intermolecular interactions of the core significantly affected on rearrangements of hydrogen bonds in the transformation. The results suggest the potential to control the properties and functions of isostructural HOFs by elements in the core.

Robust cooperative of cadmium sulfide with highly ordered hollow microstructure coordination polymers for regulating the photocatalytic performance

Accurately controlling and achieving selective reactivity at difficult-to-access reaction sites in organic molecules is challenging owing to the similar local and electronic environments of multiple reaction sites. In this work, we regulated multiple reaction sites in a highly selective and active manner using cobalt coordination polymers (Co-CP) 1 and 1a with various particle sizes and morphologies ranging from large granular to ordered hollow hemispheres by introducing sodium dodecyl sulfate (SDS) as a surfactant. The size and morphology of the catalysts could be tuned by controlling the amount of SDS. An SDS concentration of 0.03 mmol generated 1a having a highly ordered hollow hemispherical microstructure with a well-defined platform as a pre-made building unit. Cadmium sulfide (CdS), as a typical photocatalyst, was subsequently uniformly anchored in-situ on the premade building unit 1a to produce CdS@1a composites, that inherited the originally ordered hollow hemispherical microstructure while integrating CdS as well-dispersed catalytic active sites. Furthermore, the well-established CdS@1a composites were used as photocatalysts in selective oxidation reactions under air atmosphere with blue irradiation. The CdS0.109@1a composite with unique structural characteristics, including uniformly distributed and easily accessible catalytic sites and excellent photoelectrochemical performance, served as a highly efficient heterogeneous photocatalyst for promoting the selective oxidation of sulfides to sulfoxides as the sole products. This work presents an approach for fabricating CPs as premade building units that function as well-defined platforms for integration with photocatalysts, enabling tuning of the structure-selectivity-activity relationships.

Topology Prediction of Gas-Separating Metal-Organic Frameworks with Low Symmetry Vertices

Topology serves as a blueprint for the construction of reticular structures such as metal-organic frameworks, especially for those based on building blocks with highly symmetrical shapes. However, it remains a challenge to predict the topology of the frameworks from less symmetrical units, because their corresponding vertex figures are largely deformed from the perfect geometries with no "default" net embedding. Furthermore, vertices involving flexible units may have multiple shape choices, and the competition among their designated topologies makes the structure prediction in large uncertainty. Herein, the deformation index is proposed to characterize the symmetry loss of the vertex figure by comparing it with its ideal geometry. The mathematical index is employed to predict the shapes of two in situ formed Co-based metalloligands (pseudo-tetrahedron and pseudo-square), which further dictate the framework topology (flu and scu) when they are joined with the [Zr6O8]-based cuboid units. The two frameworks with very similar constituents provide an ideal platform to investigate how the pore shapes and interconnectivity influence the gas separation. The net with cylindrical channels outperforms the other with discreate cages in C3H8/C2H6/CH4 separation, benefiting from the facile accessibility of its interaction sites to the guests imposed by the specific framework topology.

Fine-regulation of gradient gate-opening in nanoporous crystals for sieving separation of ternary C3 hydrocarbons

The adsorptive separation of ternary propyne (C3H4)/propylene (C3H6)/propane (C3H8) mixtures is of significant importance due to its energy efficiency. However, achieving this process using an adsorbent has not yet been accomplished. To tackle such a challenge, herein, we present a novel approach of fine-regulation of the gradient of gate-opening in soft nanoporous crystals. Through node substitution, an exclusive gate-opening to C3H4 (17.1 kPa) in NTU-65-FeZr has been tailored into a sequential response of C3H4 (1.6 kPa), C3H6 (19.4 kPa), and finally C3H8 (57.2 kPa) in NTU-65-CoTi, of which the gradient framework changes have been validated by in situ powder X-ray diffractions and modeling calculations. Such a significant breakthrough enables NTU-65-CoTi to sieve the ternary mixtures of C3H4/C3H6/C3H8 under ambient conditions, particularly, highly pure C3H8 (99.9%) and C3H6 (99.5%) can be obtained from the vacuum PSA scheme. In addition, the fully reversible structural change ensures no loss in performance during the cycling dynamic separations. Moving forward, regulating gradient gate-opening can be conveniently extended to other families of soft nanoporous crystals, making it a powerful tool to optimize these materials for more complex applications.

Topological Analysis and Structural Determination of 3D Covalent Organic Frameworks

3D covalent organic frameworks (3D COFs) constitute a new type of crystalline materials that consist of a range of porous structures with numerous applications in the fields of adsorption, separation, and catalysis. However, because of the complexity of the three-periodic net structure, it is desirable to develop a thorough structural comprehension, along with a means to precisely determine the actual structure. Indeed, such advancements would considerably contribute to the rational design and application of 3D COFs. In this review, the reported topologies of 3D COFs are introduced and categorized according to the configurations of their building blocks, and a comprehensive overview of diffraction-based structural determination methods is provided. The current challenges and future prospects for these materials will also be discussed.

Probing ligand conformation and net dimensionality in a series of tetraphenylethene-based metal-organic frameworks

Tetraphenylethene-based ligands with lowered symmetry are promising building blocks for the construction of novel luminescent metal-organic frameworks (MOFs). However, few examples have been reported, and predicting the ligand conformation and the dimensionality of the resulting MOF remains challenging. In order to uncover how synthetic conditions and accessible ligand conformations may affect the resulting MOF structure, four new MOF structures were synthesized under solvothermal conditions using the meta-coordinated tetraphenylethene-based ligand m-ETTC and paddlewheel SBUs composed of Co(II), Cu(II), and Zn(II). WSU-10 (WSU = Washington State University) is formed with either Zn or Cu comprising stacked psuedo-2D layers. The dimensionality of WSU-10 can be intentionally increased through the addition of pyrazine as a pillar ligand into the synthesis, forming the 3D structure WSU-11. The third structure, WSU-20, is formed by the combination of Zn or Co with m-ETTC and is intrinsically 3D without the use of a pillar ligand; interestingly, this is the result of a distortion in the paddlewheel SBU. Finally, Cu was also found to form a new structure (WSU-12), which displays an m-ETTC conformation unique from that found in the other isolated MOFs. Structural features are compared across the series and a mechanistic relationship between WSU-10 and -20 is proposed, providing insight into the factors that can encourage the generation of frameworks with increased dimensionality.

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.

Influence of Humidity on Layer-by-Layer Growth and Structure in Coordination Networks

Metal-organic frameworks (MOFs) are promising materials because of their high designability of pores and functionalities. Especially, MOF thin films and their properties have been investigated toward applications in nanodevices. Typically, MOF thin films are fabricated by using a bottom-up method such as layer-by-layer (LbL) growth in air. Because the water molecules can coordinate and be replaced with organic linkers during synthesis, humidity conditions will be expected to influence the LbL growth processes. In this study, we fabricated MOF thin films composed of Zn2+, tetrakis-(4-carboxyphenyl)-porphyrin (TCPP), and 4,4'-bipyridyl (bpy) at 10 and 40% relative humidity (RH) conditions. Then, we investigated the humidity effects on chemical compositions of TCPP and bpy, periodic structure, orientation, and surface morphology. At high RH, coordination replacement of water with the organic linkers becomes more competitive than that at low RH, resulting in a different TCPP/bpy composition ratio between the two RH conditions. Also, more frequent coordination replacements of water with the organic linkers at high RH led to the formation of phases other than that observed at low RH, loss of growth orientation, and rough surface. The findings clarified the importance of controlling the RH condition during LbL growth to obtain the desired coordination networks.

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.

A comprehensive transformer-based approach for high-accuracy gas adsorption predictions in metal-organic frameworks

Gas separation is crucial for industrial production and environmental protection, with metal-organic frameworks (MOFs) offering a promising solution due to their tunable structural properties and chemical compositions. Traditional simulation approaches, such as molecular dynamics, are complex and computationally demanding. Although feature engineering-based machine learning methods perform better, they are susceptible to overfitting because of limited labeled data. Furthermore, these methods are typically designed for single tasks, such as predicting gas adsorption capacity under specific conditions, which restricts the utilization of comprehensive datasets including all adsorption capacities. To address these challenges, we propose Uni-MOF, an innovative framework for large-scale, three-dimensional MOF representation learning, designed for multi-purpose gas prediction. Specifically, Uni-MOF serves as a versatile gas adsorption estimator for MOF materials, employing pure three-dimensional representations learned from over 631,000 collected MOF and COF structures. Our experimental results show that Uni-MOF can automatically extract structural representations and predict adsorption capacities under various operating conditions using a single model. For simulated data, Uni-MOF exhibits remarkably high predictive accuracy across all datasets. Additionally, the values predicted by Uni-MOF correspond with the outcomes of adsorption experiments. Furthermore, Uni-MOF demonstrates considerable potential for broad applicability in predicting a wide array of other 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.

Increasing the stability of calixarene-capped porous cages through coordination sphere tuning

Chemically and thermally stable permanently porous coordination cages are appealing candidates for separations, catalysis, and as the porous component of new porous liquids. However, many of these applications have not turned to microporous cages as a result of their poor solubility and thermal or hydrolytic stability. Here we describe the design and modular synthesis of iron and cobalt cages where the carboxylate groups of the bridging ligands of well-known calixarene capped coordination cages have been replaced with more basic triazole units. The resultingly higher M-L bond strengths afford highly stable cages that are amenable to modular synthetic approaches and potential functionalization or modification. Owing to the robust nature of these cages, they are highly processable and are isolable in various physical states with tunable porosity depending on the solvation methods used. As the structural integrity of the cages is maintained upon high activation temperatures, apparent losses in porosity can be mediated by resolvation and crystallization or precipitation.

Graph attention neural networks for mapping materials and molecules beyond short-range interatomic correlations

Bringing advances in machine learning to chemical science is leading to a revolutionary change in the way of accelerating materials discovery and atomic-scale simulations. Currently, most successful machine learning schemes can be largely traced to the use of localized atomic environments in the structural representation of materials and molecules. However, this may undermine the reliability of machine learning models for mapping complex systems and describing long-range physical effects because of the lack of non-local correlations between atoms. To overcome such limitations, here we report a graph attention neural network as a unified framework to map materials and molecules into a generalizable and interpretable representation that combines local and non-local information of atomic environments from multiple scales. As an exemplary study, our model is applied to predict the electronic structure properties of metal-organic frameworks (MOFs) which have notable diversity in compositions and structures. The results show that our model achieves the state-of-the-art performance. The clustering analysis further demonstrates that our model enables high-level identification of MOFs with spatial and chemical resolution, which would facilitate the rational design of promising reticular materials. Furthermore, the application of our model in predicting the heat capacity of complex nanoporous materials, a critical property in a carbon capture process, showcases its versatility and accuracy in handling diverse physical properties beyond electronic structures.

Finely Tuning Metal Ion Valences of [Fe3-xMx(μ3-OH)(Carboxyl)6(pyridyl)2] Cluster-Based ant-MOFs for Highly Improved CO2 Capture Performances

Solvothermal reactions of different trinuclear precursors and 5-(pyridin-4-yl)isophthalic acid (H2L) successfully led to four anionic ant topological MOFs as Fe3-xMx(μ3-OH)(CH3COO)2(L)2·(DMA+)·DMF [M = Mn(II), Fe(II), Co(II), x = 0, 1, 2 and 3], namely, NJTU-Bai79 [NJTU-Bai = Nanjing Tech University Bai's group, Mn3(μ3-OH)], NJTU-Bai80 [Fe2Mn(μ3-OH)], NJTU-Bai81 [Fe3(μ3-OH)], and NJTU-Bai82 [Fe2Co(μ3-OH)], which possess the narrow pores (2.5-6.0 Å). NJTU-Bai80-82 is able to be tuned to the neutral derivatives [NJTU-Bai80-82(-ox), ox = oxidized] with M2+ ions oxidized to M3+ ones in the air and the OH- ions coordinated on M3+ ions. Very interestingly, selective CO2/N2 adsorptions of NJTU-Bai80-82(-ox) are significantly enhanced with the CO2 adsorption uptakes more than about 6 times that of NJTU-Bai79. GCMC simulations further revealed that neutral NJTU-Bai80-82(-ox) supplies more open frameworks around the -CH3 groups at separate spaces to the CO2 gas molecules with relatively more pores available to them after the removal of counterions. For the first time, finely tuning metal ion valences of metal clusters of ionic MOFs and making them from electrostatic to neutral were adopted for greatly improving their CO2 capture properties, and it would provide another promising strategy for the exploration of high-performance CO2 capture materials.

A generative artificial intelligence framework based on a molecular diffusion model for the design of metal-organic frameworks for carbon capture

Metal-organic frameworks (MOFs) exhibit great promise for CO2 capture. However, finding the best performing materials poses computational and experimental grand challenges in view of the vast chemical space of potential building blocks. Here, we introduce GHP-MOFassemble, a generative artificial intelligence (AI), high performance framework for the rational and accelerated design of MOFs with high CO2 adsorption capacity and synthesizable linkers. GHP-MOFassemble generates novel linkers, assembled with one of three pre-selected metal nodes (Cu paddlewheel, Zn paddlewheel, Zn tetramer) into MOFs in a primitive cubic topology. GHP-MOFassemble screens and validates AI-generated MOFs for uniqueness, synthesizability, structural validity, uses molecular dynamics simulations to study their stability and chemical consistency, and crystal graph neural networks and Grand Canonical Monte Carlo simulations to quantify their CO2 adsorption capacities. We present the top six AI-generated MOFs with CO2 capacities greater than 2m mol g-1, i.e., higher than 96.9% of structures in the hypothetical MOF dataset.

Stepwise construction of coordinative linkages and dynamic covalent linkages for a porous metal-organic framework

A cyclic trinuclear complex is synthesized from AgI and 1H-pyrazole-4-carbaldehyde. Reticulation of the complex with 1,3,5-tris(4-aminophenyl)benzene through Schiff-base reaction affords a porous FDM-72 framework. Amine choice is systematically investigated as it may initiate metal reduction. This study proposes a new route and its amine selection criterion to synthesize Ag-based frameworks.

A Critical Assessment on Calculating Vibrational Spectra in Nanostructured Materials

Vibrational spectroscopy is an omnipresent spectroscopic technique to characterize functional nanostructured materials such as zeolites, metal-organic frameworks (MOFs), and metal-halide perovskites (MHPs). The resulting experimental spectra are usually complex, with both low-frequency framework modes and high-frequency functional group vibrations. Therefore, theoretically calculated spectra are often an essential element to elucidate the vibrational fingerprint. In principle, there are two possible approaches to calculate vibrational spectra: (i) a static approach that approximates the potential energy surface (PES) as a set of independent harmonic oscillators and (ii) a dynamic approach that explicitly samples the PES around equilibrium by integrating Newton's equations of motions. The dynamic approach considers anharmonic and temperature effects and provides a more genuine representation of materials at true operating conditions; however, such simulations come at a substantially increased computational cost. This is certainly true when forces and energy evaluations are performed at the quantum mechanical level. Molecular dynamics (MD) techniques have become more established within the field of computational chemistry. Yet, for the prediction of infrared (IR) and Raman spectra of nanostructured materials, their usage has been less explored and remain restricted to some isolated successes. Therefore, it is currently not a priori clear which methodology should be used to accurately predict vibrational spectra for a given system. A comprehensive comparative study between various theoretical methods and experimental spectra for a broad set of nanostructured materials is so far lacking. To fill this gap, we herein present a concise overview on which methodology is suited to accurately predict vibrational spectra for a broad range of nanostructured materials and formulate a series of theoretical guidelines to this purpose. To this end, four different case studies are considered, each treating a particular material aspect, namely breathing in flexible MOFs, characterization of defects in the rigid MOF UiO-66, anharmonic vibrations in the metal-halide perovskite CsPbBr3, and guest adsorption on the pores of the zeolite H-SSZ-13. For all four materials, in their guest- and defect-free state and at sufficiently low temperatures, both the static and dynamic approach yield qualitatively similar spectra in agreement with experimental results. When the temperature is increased, the harmonic approximation starts to fail for CsPbBr3 due to the presence of anharmonic phonon modes. Also, the spectroscopic fingerprints of defects and guest species are insufficiently well predicted by a simple harmonic model. Both phenomena flatten the potential energy surface (PES), which facilitates the transitions between metastable states, necessitating dynamic sampling. On the basis of the four case studies treated in this Review, we can propose the following theoretical guidelines to simulate accurate vibrational spectra of functional solid-state materials: (i) For nanostructured crystalline framework materials at low temperature, insights into the lattice dynamics can be obtained using a static approach relying on a few points on the PES and an independent set of harmonic oscillators. (ii) When the material is evaluated at higher temperatures or when additional complexity enters the system, e.g., strong anharmonicity, defects, or guest species, the harmonic regime breaks down and dynamic sampling is required for a correct prediction of the phonon spectrum. These guidelines and their illustrations for prototype material classes can help experimental and theoretical researchers to enhance the knowledge obtained from a lattice dynamics study.

Influence of donor point modifications on the assembly of chalcogen-bonded organic frameworks

Incremental, single-atom substitutions of Se-based chalcogen bond (Ch-bond) donors with stronger donating Te centers were implemented in two new triptycene tris(1,2,5-chalcogenadiazole) tectons. The appreciably more favorable Ch-bonding ability of the Te-based donors promotes assembly of low-density networks and more stable Ch-bonded organic frameworks (ChOFs).

Optimizing Porous Metal-Organic Layers for Stable Zinc Anodes

Aqueous zinc-ion batteries (ZIBs) have been considered as alternative stationary energy storage systems, but the dendrite and corrosion issues of Zn anodes hinder their practical applications. Here we report a series of two-dimensional (2D) metal-organic frameworks (MOFs) with Zr12 clusters, which act as artificial solid electrolyte interphase (SEI) layers to prevent dendrites and corrosion of Zn anodes. The Zr12-based 2D MOF layers were formed by incubating 3D layer-pillared Zr-MOFs in ZnSO4 aqueous electrolytes, which replaced the pillar ligands with terminal SO42-. Furthermore, the pore sizes of Zr12-based 2D MOF layers were systematically tuned, leading to optimized Zn2+ conduction properties and protective performance for Zn anodes. In contrast to the traditional 2D-MOFs with Zr6 clusters, Zr12-based 2D MOF layers as artificial SEI significantly reduced the polarization and increased the stability of Zn anodes in MOF@Zn||MOF@Zn symmetric cells and MOF@Zn||MnO2 full cells. In situ experiments and DFT computations reveal that the enhanced cell performance is attributed to the unique Zr12-based layered structure with intrinsic pores to allow fast Zn2+ diffusion, surface Zr-SO4 zincophilic sites to induce uniform Zn deposition, and inhibited hydrogen evolution by 2D MOF Zr12 layers.

Enhanced CO2 Electroreduction Selectivity toward Ethylene on Pyrazolate-Stabilized Asymmetric Ni-Cu Hybrid Sites

Metal-organic frameworks (MOFs) possess well-defined, designable structures, holding great potential in enhancing product selectivity for electrochemical CO2 reduction (CO2R) through active site engineering. Here, we report a novel MOF catalyst featuring pyrazolate-stabilized asymmetric Ni/Cu sites, which not only maintains structural stability under harsh electrochemical conditions but also exhibits extraordinarily high ethylene (C2H4) selectivity during CO2R. At a cathode potential of -1.3 V versus RHE, our MOF catalyst, denoted as Cu1Ni-BDP, manifests a C2H4 Faradaic efficiency (FE) of 52.7% with an overall current density of 0.53 A cm-2 in 1.0 M KOH electrolyte, surpassing that on prevailing Cu-based catalysts. More remarkably, the Cu1Ni-BDP MOF exhibits a stable performance with only 4.5% reduction in C2H4 FE during 25 h of CO2 electrolysis. A suite of characterization tools─such as high-resolution transmission electron microscopy, X-ray absorption spectroscopy, operando X-ray diffraction, and infrared spectroscopy─and density functional theory calculations collectively reveal that the cubic pyrazolate-metal coordination structure and the asymmetric Ni-Cu sites in the MOF catalyst synergistically facilitate the stable formation of C2H4 from CO2.

Target Design of Multinary Metal-Organic Frameworks for Near-Infrared Imaging and Chemodynamic Therapy

Imaging-guided chemodynamic therapy is widely considered a promising modality for personalized and precision cancer treatment. Combining both imaging and chemodynamic functions in one system conventionally relies on the hybrid materials approach. However, the heterogeneous, ill-defined, and dissociative/disintegrative nature of the composites tends to complicate their action proceedings in biological environments and thus makes the treatment imprecise and ineffective. Herein, a strategy to employ two kinds of inorganic units with different functions─reactive oxygen species generation and characteristic emission─has achieved two single-crystalline metal-organic frameworks (MOFs), demonstrating the competency of reticular chemistry in creating multifunctional materials with atomic precision. The multinary MOFs could not only catalyze the transformation from H2O2 to hydroxyl radicals by utilizing the redox-active Cu-based units but also emit characteristic tissue-penetrating near-infrared luminescence brought by the Yb4 clusters in the scaffolds. Dual functions of MOF nanoparticles are further evidenced by pronounced cell imaging signals, elevated intracellular reactive oxygen species levels, significant cell apoptosis, and reduced cell viabilities when they are taken up by the HeLa cells. In vivo NIR imaging is demonstrated after the MOF nanoparticles are further functionalized. The independent yet interconnected modules in the intact MOFs could operate concurrently at the same cellular site, achieving a high spatiotemporal consistency. Overall, our work suggests a new method to effectively accommodate both imaging and therapy functions in one well-defined material for precise treatment.

Net-clipping as a top-down approach for the prediction of topologies of MOFs built from reduced-symmetry linkers

Reticular materials constructed from regular molecular building blocks (MBBs) have been widely explored in the past three decades. Recently, there has been increasing interest in the assembly of novel, intricate materials using less-symmetric ligands; however, current methods for predicting structure are not amenable to this increased complexity. To address this gap, we propose herein a generalised version of the net-clipping approach for anticipating the topology of metal-organic frameworks (MOFs) assembled from organic linkers and different polygonal and polyhedral MBBs. It relies on the generation of less-symmetric nets with less-connected linkers, via the rational deconstruction of more-symmetric and more-connected linkers in edge-transitive nets. We applied our top-down strategy to edge-transitive nets containing 4-c tetrahedral, 6-c hexagonal, 8-c cubic or 12-c hexagonal prism linkers, envisaging the formation of 102 derived and 46 clipped nets. Among these, we report 33 new derived nets (icn7-icn39) and 6 new clipped nets (icn1-icn6). Importantly, the feasibility of using net-clipping to anticipate clipped nets is supported by literature examples and new experimental additions. Finally, we suggest and illustrate that net-clipping can be extended to less-regular, non-edge transitive nets as well as to covalent-organic frameworks (COFs), thus opening new avenues for the rational design of new reticular materials exhibiting unprecedented topologies.

Mechanistic Insights into a Co(II)-Coordinated "Free" Metal Site of 2D Zinc-Based MOFs for β-Alkylation of Secondary Alcohols with Primary Alcohols

Through in-depth study of the properties and reaction mechanisms of catalysts, it is possible to better optimize catalytic systems and improve reaction efficiency and selectivity. This remains one of the challenges in the field of catalysis. Therefore, the research and design of catalysts play crucial roles in understanding and optimizing catalytic reaction mechanisms. A robust 2D zinc-based MOFs (Zn-HA) supported Co(II) ion catalyst (Zn-HA@Co) has been designed and synthesized via a coordination-assisted strategy for β-alkylation of secondary alcohols with primary alcohols. The characterization demonstrated that the anchoring of Co(II) on Zn-HA via coordination could efficiently enhance the Co(II) ion dispersity and interaction between Co(II) and Zn-HA MOFs. Importantly, the density functional theory results have provided mechanistic insights into the energy of the HOMO and LUMO of the Zn-HA@Co catalyst as well as the energy change of the entire process after interacting with the reactants and the specific energy changes of each orbital. The synthesized Zn-HA@Co MOFs effectively lower the energy barrier of the catalytic reaction process. We expect that our research and design of catalysts will serve as valuable guideline for understanding and optimizing catalytic reaction mechanisms.

Direct prediction of gas adsorption via spatial atom interaction learning

Physisorption relying on crystalline porous materials offers prospective avenues for sustainable separation processes, greenhouse gas capture, and energy storage. However, the lack of end-to-end deep learning model for adsorption prediction confines the rapid and precise screen of crystalline porous materials. Here, we present DeepSorption, a spatial atom interaction learning network that realizes accurate, fast, and direct structure-adsorption prediction with only information of atomic coordinate and chemical element types. The breakthrough in prediction is attributed to the awareness of global structure and local spatial atom interactions endowed by the developed Matformer, which provides the intuitive visualization of atomic-level thinking and executing trajectory in crystalline porous materials prediction. Complete adsorption curves prediction could be performed using DeepSorption with a higher accuracy than Grand canonical Monte Carlo simulation and other machine learning models, a 20-35% decline in the mean absolute error compared to graph neural network CGCNN and machine learning models based on descriptors. Since the established direct associations between raw structure and target functions are based on the understanding of the fundamental chemistry of interatomic interactions, the deep learning network is rationally universal in predicting the different physicochemical properties of various crystalline materials.

Electrically conductive [Fe4S4]-based organometallic polymers

Tailoring the molecular components of hybrid organic-inorganic materials enables precise control over their electronic properties. Designing electrically conductive coordination materials, e.g. metal-organic frameworks (MOFs), has relied on single-metal nodes because the metal-oxo clusters present in the vast majority of MOFs are not suitable for electrical conduction due to their localized electron orbitals. Therefore, the development of metal-cluster nodes with delocalized bonding would greatly expand the structural and electrochemical tunability of conductive materials. Whereas the cuboidal [Fe4S4] cluster is a ubiquitous cofactor for electron transport in biological systems, few electrically conductive artificial materials employ the [Fe4S4] cluster as a building unit due to the lack of suitable bridging linkers. In this work, we bridge the [Fe4S4] clusters with ditopic N-heterocyclic carbene (NHC) linkers through charge-delocalized Fe-C bonds that enhance electronic communication between the clusters. [Fe4S4Cl2(ditopic NHC)] exhibits a high electrical conductivity of 1 mS cm-1 at 25 °C, surpassing the conductivity of related but less covalent materials. These results highlight that synthetic control over individual bonds is critical to the design of long-range behavior in semiconductors.

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.

Understanding and controlling the nucleation and growth of metal-organic frameworks

Metal-organic frameworks offer a diverse landscape of building blocks to design high performance materials for implications in almost every major industry. With this diversity stems complex crystallization mechanisms with various pathways and intermediates. Crystallization studies have been key to the advancement of countless biological and synthetic systems, with MOFs being no exception. This review provides an overview of the current theories and fundamental chemistry used to decipher MOF crystallization. We then discuss how intrinsic and extrinsic synthetic parameters can be used as tools to modulate the crystallization pathway to produce MOF crystals with finely tuned physical and chemical properties. Experimental and computational methods are provided to guide the probing of MOF crystal formation on the molecular and bulk scale. Lastly, we summarize the recent major advances in the field and our outlook on the exciting future of MOF crystallization.

Isoreticular Expansion and Linker-Enabled Control of Interpenetration in Titanium-Organic Frameworks

Titanium-organic frameworks offer distinctive opportunities in the realm of metal-organic frameworks (MOFs) due to the integration of intrinsic photoactivity or redox versatility in porous architectures with ultrahigh stability. Unfortunately, the high polarizing power of Ti4+ cations makes them prone to hydrolysis, thus preventing the systematic design of these types of frameworks. We illustrate the use of heterobimetallic cluster Ti2Ca2 as a persistent building unit compatible with the isoreticular design of titanium frameworks. The MUV-12(X) and MUV-12(Y) series can be all synthesized as single crystals by using linkers of varying functionalization and size for the formation of the nets with tailorable porosity and degree of interpenetration. Following the generalization of this approach, we also gain rational control over interpenetration in these nets by designing linkers with varying degrees of steric hindrance to eliminate stacking interactions and access the highest gravimetric surface area reported for titanium(IV) MOFs (3000 m2 g-1).

Two-Dimensional Copper/Nickel Metal-Organic Framework Nanosheets for Non-Enzymatic Electrochemical Glucose Detection

Metal-organic frameworks (MOFs) have broad potential applications in electrochemical glucose detection. Herein, a green ultrasonic synthesis process is presented for preparing two-dimensional (2D) copper-nickel metal-organic framework nanosheets (CuNi-MOFNs) for glucose detection. The synthesized CuNi-MOFNs were characterized using scanning electron microscopy (SEM), scanning transmission electron microscope (STEM), X-ray diffractometer (XRD), and X-ray photoelectron spectrometer (XPS). The CuNi-MOFN nanocomposites were used to cover the glassy carbon electrode (GCE) and the CuNi-MOFNs-modified electrode was studied in alkaline media. Cyclic voltammetry (CV) and amperometric i-t curves indicated that the CuNi-MOFNs-modified electrode revealed great electrochemical performances towards glucose oxidation. Due to the ease of access to active metal sites in large specific surface of nanosheets, the CuNi-MOFNs-modified electrode can effectively improve the electronic transfer rate and enhance electrocatalytic activity of the CuNi-MOFNs-modified electrode. The CuNi-MOFNs-modified electrode showed electrochemical performances for glucose detection with a linear range from 0.01 mM to 4 mM, sensitivity of 702 μAmM-1cm-2, and detection limit of 3.33 μΜ (S/N = 3). The CuNi-MOFNs-modified electrode exhibited excellent anti-interference ability and high selectivity in glucose measurements. Hence, the CuNi-MOFNs-modified electrode has good, promising prospects in non-enzymatic electrochemical glucose detection.

Room-Temperature Monitoring of CH4 and CO2 Using a Metal-Organic Framework-Based QCM Sensor Showing Inherent Analyte Discrimination

The detection of methane and carbon dioxide is of growing importance due to their negative impact on global warming. This is true for both environmental monitoring and leak detection in industrial processes. Although solid-state sensors are technologically mature, they have limitations that prohibit their use in certain situations, e.g., explosive atmospheres. Thus, there is a need to develop new types of sensor materials. Herein, we demonstrate a simple, low-cost, metal-organic framework (MOF)-based gas leak detection sensor. The system is based on gravimetric sensing by using a quartz crystal microbalance. The quartz crystal is functionalized by layer-by-layer growth of a thin metal-organic framework film. This film shows selective uptake of methane or carbon dioxide under atmospheric conditions. The hardware has low cost, simple operation, and theoretically high sensitivity. Overall, the sensor is characterized by simplicity and high robustness. Furthermore, by exploiting the different adsorption kinetics as measured by multiple harmonic analyses, it is possible to discriminate whether the response is due to methane or carbon dioxide. In summary, we demonstrate data relevant toward new applications of metal-organic frameworks and microporous hybrid materials in sensing.

Induced Production of Atypical Naturally Nonpreferred Metal-Organic Frameworks and Their Detachment via Provoking Post-Mismatching

The structures of metal-organic frameworks (MOFs) are typically determined by the building blocks that compose them and the conditions under which they are formed. MOFs tend to adopt a thermodynamically and/or kinetically stable structure (naturally preferred form). Thus, constructing MOFs with naturally nonpreferred structures is a challenging task, as it requires avoiding the easier pathway toward a naturally preferred MOF. Herein, an approach to construct naturally nonpreferred dicarboxylate-linked MOFs employing reaction templates is reported. This strategy relies on the registry between the surface of the template and the cell lattice of a target MOF, which reduces the effort required to form naturally nonpreferred MOFs. Reactions of p-block trivalent metal ions (Ga3+ and In3+ ) with dicarboxylic acids typically produce preferred MIL-53 or MIL-68. However, the surface of UiO-67 (and UiO-66) template exhibits the well-defined hexagonal lattice, which induce the selective formation of a naturally nonpreferred MIL-88 structure. Inductively grown MIL-88s are purely isolated from the template via provoking a post-mismatch in their lattices and weakening the interfacial interaction between product and template. It is also discovered that an appropriate template for effective induced production of naturally nonpreferred MOFs shall be properly selected based on the cell lattice of a target MOF.

Room Temperature Synthesis Mediated Porphyrinic NanoMOF Enables Benchmark Electrochemical Biosensing

Leveraging size effects, nanoparticles of metal-organic frameworks, nanoMOFs, have recently gained traction, amplifying their scopes in electrochemical sensing. However, their synthesis, especially under eco-friendly ambient conditions remains an unmet challenge. Herein, an ambient and fast secondary building unit (SBU)-assisted synthesis (SAS) route to afford a prototypal porphyrinic MOF, Fe-MOF-525 is introduced. Albeit the benign room temperature conditions, Fe-MOF-525(SAS) nanocrystallites obtained are of ≈30 nm size, relatively smaller than the ones conventional solvothermal methods elicit. Integrating Fe-MOF-525(SAS) as a thin film on a conductive indium tin oxide (ITO) surface affords Fe-MOF-525(SAS)/ITO, an electrochemical biosensor. Synergistic confluence of modular MOF composition, analyte-specific redox metalloporphyrin sites, and crystal downsizing contribute to its benchmark voltammetric uric acid (UA) sensing. Showcasing a wide linear range of UA detection with high sensitivity and low detection limit, this SAS strategy coalesces ambient condition synthesis and nanoparticle size control, paving a green way to advanced sensors.

Construction of Photoreactive Chiral Metal-Organic Frameworks and Their [2 + 2] Photocycloaddition Reactions

Chiral metal-organic frameworks (CMOFs) and solid-state [2 + 2] photocyclization have been explored as independent areas in crystal engineering. We herein report the photoreactive CMOFs that undergo a [2 + 2] photocycloaddition reaction for the first time. Through the incorporation of a dipyridyl olefin ligand, 1,4-bis[2-(4-pyridyl)ethenyl]benzene, and d-camphoric acid or l-camphoric acid, we constructed a pair of homochiral Zn(II) CMOFs (d-1 or l-1) with a two-dimensional sql topology via a two-step procedure to avoid racemization. Both d-1 and l-1 were photoinert due to the large olefin bond separation. The removal of the solvent molecules between layers enabled them (d-1a and l-1a) to undergo [2 + 2] cycloaddition reactions; d-1a is more reactive (70%) than l-1a (20%) probably due to proper desolvation-induced rearrangement. The photoluminescence properties are also discussed. This work presents a new perspective on photoreactive homochiral network materials with diverse topologies and applications.

3D Covalent Organic Framework as a Metastable Intermediate in the Formation of a Double-Stranded Helical Covalent Polymer

The design and development of intricate artificial architectures have been pursued for decades. Helical covalent polymer (HCP) was recently reported as an unexpected topology that consists of chiral 1D polymers assembled through weak hydrogen bonds from achiral building blocks. However, many questions remained about the formation, driving force, and the single-handedness observed in each crystal. In this work, we reveal a metastable, racemic, fully covalently cross-linked, 3D covalent organic framework (COF) as an intermediate in the early stage of polymerization, which slowly converts into single-handed HCP double helices through partial fragmentation and self-sorting with the aid of a series of hydrogen bonding. Our work provides an intriguing example where weak noncovalent bonds serve as the determining factor of the overall product structure and facilitate the formation of a sophisticated polymeric architecture.

Engineering Two-Dimensional Multilevel Supramolecular Assemblies from a Bifunctional Ligand on Au(111)

Herein, we demonstrate the supramolecular assemblies from a bifunctional ligand on Au(111), towards engineering two-dimensional (metal-) organic multilevel nanostructures. The bifunctional ligand employed, including two Br atoms and one carboxylic terminal, offers multiple bonding motifs with different configurations and binding energies. These bonding motifs are highly self-selective and self-recognizable, and thus afford the formation of subunits that contribute to engineering multilevel self-assemblies. Our scanning tunneling microscopy experiments, in combination with the density functional theory calculations, revealed various hydrogen, halogen and alkali-carboxylate bonding motifs dictating the different levels of the assemblies. The multilevel assembly protocol based on a judicious choice of multiple bonding motifs guarantees a deliberate control of surface-confined (metal-) organic nanostructures. Our findings may present new opportunities for the fabrication of complex two-dimensional (metal-) organic nanostructures with potential in applications of functionally diverse nanomaterials.

Phosphine-based metal-organic layers to construct single-site heterogeneous catalysts for arene borylation

Metal-organic layers (MOLs) are versatile platforms for creating single-site heterogeneous catalysts. Incorporating molecular functionalities into MOLs is crucial for catalysis. In this study, we synthesized phosphine-containing MOLs constructed from Hf₆-oxo secondary building units (SBUs) and phosphine ligands. The mono(phosphine)-Ir complexes generated by the metalation of TPP-MOL were highly active as heterogeneous catalysts for the C(sp²)-H borylation of a range of arenes. This research expands the diversity of MOL-based catalysts.

Natural components as surface engineering agents for CRISPR delivery

This perspective article discusses the potential of using natural and environmentally friendly components as surface engineering agents for CRISPR delivery. Traditional delivery methods for CRISPR components have limitations and safety concerns, and surface engineering has emerged as a promising approach. The perspective provides an overview of current research, including the use of lipids, proteins, natural components (like leaf extracts), and polysaccharides to modify the surface of nanoparticles and improve delivery efficiency. The advantages of using natural components include biocompatibility, biodegradability, engineered functionality, cost-effectiveness, and environmental friendliness. The author also discusses the challenges and future perspective of this field, such as a better understanding of underlying mechanisms and optimization of delivery methods for different cell types and tissues, as well as the generation of novel inorganic nanomaterials, including MOF and MXene, for CRISPR delivery, and their synergistic potentials using leaf extracts and natural components. The use of natural components as surface engineering agents for CRISPR delivery has the potential to overcome the limitations of traditional delivery methods, eliminating the biological challenges, and represents a promising area of research.

Efficient adsorption and photocatalytic degradation of water emerging contaminants through nanoarchitectonics of pore sizes and optical properties of zirconium-based MOFs

Over the past decades, the presence of pharmaceutical emerging contaminants in water bodies is receiving increasing attention due to the high concentration detected from wastewater effluent. Water systems contain a wide range of components coexisting together, which increases the difficulty of removing pollutants from the water. In order to achieve selective photodegradation and to enhance the photocatalytic activity of the photocatalyst on emerging contaminants, a Zr-based metal-organic framework (MOF), termed VNU-1 (VNU represents Vietnam National University) constructed with ditopic linker 1,4-bis(2-[4-carboxyphenyl]ethynyl)benzene (H₂CPEB), with enlarged pore size and ameliorated optical properties, was synthesized and applied in this study. When compared to UiO-66 MOFs, which only had 30% photodegradation of sulfamethoxazole, VNU-1 had 7.5 times higher adsorption and reached 100% photodegradation in 10 min. The tailored pore size of VNU-1 resulted in size-selective properties between small-molecule antibiotics and big-molecule humic acid, and VNU-1 maintained high photodegradation performance after 5 cycles. Based on the toxicity test and the scavenger test, the products after photodegradation had no toxic effect on V. fischeri bacteria, and the superoxide radical (·O₂^-) and holes (h⁺) generated from VNU-1 dominated the photodegradation reaction. These results demonstrate that VNU-1 is a promising photocatalyst and provide a new insight for developing MOF photocatalyst to remove emerging contaminants in the wastewater systems.

Principles of Design and Synthesis of Metal Derivatives from MOFs

Materials derived from metal-organic frameworks (MOFs) have demonstrated exceptional structural variety and complexity and can be synthesized using low-cost scalable methods. Although the inherent instability and low electrical conductivity of MOFs are largely responsible for their low uptake for catalysis and energy storage, a superior alternative is MOF-derived metal-based derivatives (MDs) as these can retain the complex nanostructures of MOFs while exhibiting stability and electrical conductivities of several orders of magnitude higher. The present work comprehensively reviews MDs in terms of synthesis and their nanostructural design, including oxides, sulfides, phosphides, nitrides, carbides, transition metals, and other minor species. The focal point of the approach is the identification and rationalization of the design parameters that lead to the generation of optimal compositions, structures, nanostructures, and resultant performance parameters. The aim of this approach is to provide an inclusive platform for the strategies to design and process these materials for specific applications. This work is complemented by detailed figures that both summarize the design and processing approaches that have been reported and indicate potential trajectories for development. The work is also supported by comprehensive and up-to-date tabular coverage of the reported studies.

In Situ FTIR Spectroscopy for Scanning Accessible Active Sites in Defect-Engineered UiO-66

Three UiO-66 samples were prepared by solvothermal synthesis using the defect engineering approach with benzoic acid as a modulator. They were characterized by different techniques and their acidic properties were assessed by FTIR spectroscopy of adsorbed CO and CD₃CN. All samples evacuated at room temperature contained bridging μ₃-OH groups that interacted with both probe molecules. Evacuation at 250 °C leads to the dehydroxylation and disappearance of the μ₃-OH groups. Modulator-free synthesis resulted in a material with open Zr sites. They were detected by low-temperature CO adsorption on a sample evacuated at 200 °C and by CD₃CN even on a sample evacuated at RT. However, these sites were lacking in the two samples obtained with a modulator. IR and Raman spectra revealed that in these cases, the Zr⁴⁺ defect sites were saturated by benzoates, which prevented their interaction with probe molecules. Finally, the dehydroxylation of all samples produced another kind of bare Zr sites that did not interact with CO but formed complexes with acetonitrile, probably due to structural rearrangement. The results showed that FTIR spectroscopy is a powerful tool for investigating the presence and availability of acid sites in UiO-66, which is crucial for its application in adsorption and catalysis.

Stepwise Amplification of Circularly Polarized Luminescence in Chiral Metal Cluster Ensembles

Chiral metal-organic frameworks (MOFs) are usually endowed by chiral linkers and/or guests. The strategy using chiral secondary building units in MOFs for solving the trade-off of circularly polarized luminescence (CPL)-active materials, high photoluminescence quantum yields (PLQYs) and high dissymmetry factors (|g_lum |) has not been demonstrated. This work directionally assembles predesigned chiral silver clusters with ACQ linkers through reticular chemistry. The nanoscale chirality of the cluster transmits through MOF's framework, where the linkers are arranged in a quasi-parallel manner and are efficiently isolated and rigidified. Consequently, this backbone of chiral cluster-based MOFs demonstrates superb CPL, high PLQYs of 50.3%, and |g_lum | of 1.2 × 10^-2 . Crystallographic analyses and DFT calculations show the quasi-parallel arrangement manners of emitting linkers leading to a large angle between the electric and magnetic transition dipole moments, boosting CPL response. As compared, an ion-pair-direct assembly without interactions between linkers induces one-ninth |g_lum | and one-sixth PLQY values, further highlighting the merits of directional arrangement in reticular nets. In addition, a prototype CPL switching fabricated by a chiral framework is controlled through alternating ultraviolet and visible light. This work is expected to inspire the development of reticular chemistry for high-performance chiroptical materials.

Energy-structure-property relationships in uranium metal-organic frameworks

Located at the foot of the periodic table, uranium is a relatively underexplored element possessing rich chemistry. In addition to its high relevance to nuclear power, uranium shows promise for small molecule activation and photocatalysis, among many other powerful functions. Researchers have used metal-organic frameworks (MOFs) to harness uranium's properties, and in their quest to do so, have discovered remarkable structures and unique properties unobserved in traditional transition metal MOFs. More recently, (e.g. the last 8-10 years), theoretical calculations of framework energetics have supplemented structure-property studies in uranium MOFs (U-MOFs). In this Perspective, we summarize how these budding energy-structure-property relationships in U-MOFs enable a deeper understanding of chemical phenomena, enlarge chemical space, and elevate the field to targeted, rather than exploratory, discovery. Importantly, this Perspective encourages interdisciplinary connections between experimentalists and theorists by demonstrating how these collaborations have elevated the entire U-MOF field.

Stable Lanthanide-Organic Frameworks: Crystal Structure, Photoluminescence, and Chemical Sensing of Vanillylmandelic Acid as a Biomarker of Pheochromocytoma

Several isostructural lanthanide metal-organic frameworks, viz. [Ln(DCHB)_1.5phen]_n (Ln-MOFs, where Ln = Eu for 1, Tb for 2, Sm for 3 and Dy for 4), are successfully synthesized through the hydrothermal reactions of 4'-di(4-carboxylphenoxy)hydroxyl-2, 2'-bipyridyl (H₂DCHB) and lanthanide nitrates as well as chelator 1,10-phenantroline (phen). These structures are characterized by single-crystal X-ray diffraction, and the representative Ln-MOF 1 is a fivefold interpenetrated framework with the uncoordinated Lewis base N sites form DCHB^2- ligands. The photoluminescence research studies reveal that Ln-MOFs 1-4 exhibit characteristic fluorescent emissions from ligand-induced lanthanide Ln(III) ions, while the single-component emission spectra of Ln-MOF 4 are all located in a white region under different excitations. The absence of coordinated water and the interpenetration property of the structures are conducive to the structure rigidity, and the results display that Ln-MOF 1 has high thermal/chemical stabilities in common solvents and a wide pH range as well as the boiling water. Notably, luminescent sensing studies reveal that Ln-MOF 1 with prominent fluorescence properties can perform in highly sensitive and selective sensing of vanillylmandelic acid (VMA) in aqueous systems (K_SV = 562.8 L·mol^-1; LOD = 4.6 × 10^-4 M), which can potentially establish a detection platform for the diagnosis of pheochromocytoma via multiquenching mechanisms. Moreover, the 1@MMMs sensing membranes comprised of Ln-MOF 1 and a poly(vinylidene fluoride) (PVDF) polymer can also be facilely developed for VMA detection in aqueous media, suggesting the enhanced convenience and efficiency of practical sensing applications.

Microkinetic insights into the role of catalyst and water activity on the nucleation, growth, and dissolution during COF-5 synthesis

The chemical pathway for synthesizing covalent organic frameworks (COFs) involves a complex medley of reaction sequences over a rippling energy landscape that cannot be adequately described using existing theories. Even with the development of state-of-the-art experimental and computational tools, identifying primary mechanisms of nucleation and growth of COFs remains elusive. Other than empirically, little is known about how the catalyst composition and water activity affect the kinetics of the reaction pathway. Here, for the first time, we employ time-resolved in situ Fourier transform infrared spectroscopy (FT-IR) coupled with a six-parameter microkinetic model consisting of ∼10 million reactions and over 20 000 species. The integrated approach elucidates previously unrecognized roles of catalyst pK_a on COF yield and water on growth rate and size distribution. COF crystalline yield increases with decreasing pK_a of the catalysts, whereas the effect of water is to reduce the growth rate of COF and broaden the size distribution. The microkinetic model reproduces the experimental data and quantitatively predicts the role of synthesis conditions such as temperature, catalyst, and precursor concentration on the nucleation and growth rates. Furthermore, the model also validates the second-order reaction mechanism of COF-5 and predicts the activation barriers for classical and non-classical growth of COF-5 crystals. The microkinetic model developed here is generalizable to different COFs and other multicomponent systems.

Reticular Chemistry in Pore Engineering of a Y-Based Metal-Organic Framework for Xenon/Krypton Separation

The fine-tuning of metal-organic framework (MOF) pore structures is of critical importance in developing energy-efficient xenon/krypton (Xe/Kr) separation techniques. Capitalizing on reticular chemistry, we constructed a robust Y-based MOF (NU-1801) that is isoreticular to NPF-500 with a shortened organic ligand and a larger metal radius while maintaining the 4,8-connected flu topology, giving rise to a narrowed pore structure for the efficient separation of a Xe/Kr mixture. At 298 K and 1 bar, NU-1801 possessed a moderate Xe uptake of 2.79 mmol/g but exhibited a high Xe/Kr selectivity of 8.2 and an exceptional Xe/Kr uptake ratio of about 400%. NU-1801 could efficiently separate a Xe/Kr mixture (20:80, v/v), as validated by breakthrough experiments, due to the outstanding discrimination in van der Waals interactions of Xe and Kr toward the framework confirmed by grand canonical Monte Carlo simulations. This work highlights the importance of reticular chemistry in designing structure-specific MOFs for gas separation.