Computational Design of Functionalized Metal-Organic Framework Nodes for Catalysis

AgAu-modified quasi-MIL-53 hybrid nanozymes with triple enzyme-like activities for boosting biocatalytic disinfection

Metal-organic frameworks (MOFs) have great potential for combating pathogenic bacterial infections and are expected to become an alternative to antibiotics. However, organic linkers obstruct and saturate the inorganic nodes of MOF structures, making it challenging to utilize the applied potential of metal centers. Here, we combined controlled ligand decarboxylation with noble metal nanoparticles to rationally remodel MIL-53, resulting in a hybrid nanozyme (AgAu@QMIL-53, AAQM) with excellent multiple enzyme-like activities that both eradicate bacteria and promote diabetic wound healing. Specifically, benefitting from oxidase (OXD)-like and peroxidase (POD)-like activities, AAQM converts oxygen (O2) and hydrogen peroxide (H2O2) into superoxide anion radicals (O2-) and hydroxyl radicals (OH) to eradicate bacteria. In in vitro antibacterial experiments, AAQM exhibited favorable killing efficacy against Pseudomonas aeruginosa (P. aeruginosa) and methicillin-resistant Staphylococcus aureus (MRSA) (>99 %). Notably, due to its superoxide (SOD)-like activity and outstanding reactive nitrogen species (RNS) elimination capacity, AAQM can produce adequate O2 and alleviate oxidative stress in diabetic wounds. Benefiting from the rational modification of MIL-53, the synthesized hybrid nanozyme can effectively kill bacteria while alleviating oxidative stress and ultimately promote infected diabetic wound healing. Overall, this biomimetic enzyme-catalyzed strategy will bring enlightenment to the design of self-antibacterial agents for efficient disinfection and wound healing simultaneously.

Powders to Thin Films: Advances in Conjugated Microporous Polymer Chemical Sensors

Chemical sensing of harmful species released either from natural or anthropogenic activities is critical to ensuring human safety and health. Over the last decade, conjugated microporous polymers (CMPs) have been proven to be potential sensor materials with the possibility of realizing sensing devices for practical applications. CMPs found to be unique among other porous materials such as metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) due to their high chemical/thermal stability, high surface area, microporosity, efficient host-guest interactions with the analyte, efficient exciton migration along the π-conjugated chains, and tailorable structure to target specific analytes. Several CMP-based optical, electrochemical, colorimetric, and ratiometric sensors with excellent selectivity and sensing performance were reported. This review comprehensively discusses the advances in CMP chemical sensors (powders and thin films) in the detection of nitroaromatic explosives, chemical warfare agents, anions, metal ions, biomolecules, iodine, and volatile organic compounds (VOCs), with simultaneous delineation of design strategy principles guiding the selectivity and sensitivity of CMP. Preceding this, various photophysical mechanisms responsible for chemical sensing are discussed in detail for convenience. Finally, future challenges to be addressed in the field of CMP chemical sensors are discussed.

A US perspective on closing the carbon cycle to defossilize difficult-to-electrify segments of our economy

Electrification to reduce or eliminate greenhouse gas emissions is essential to mitigate climate change. However, a substantial portion of our manufacturing and transportation infrastructure will be difficult to electrify and/or will continue to use carbon as a key component, including areas in aviation, heavy-duty and marine transportation, and the chemical industry. In this Roadmap, we explore how multidisciplinary approaches will enable us to close the carbon cycle and create a circular economy by defossilizing these difficult-to-electrify areas and those that will continue to need carbon. We discuss two approaches for this: developing carbon alternatives and improving our ability to reuse carbon, enabled by separations. Furthermore, we posit that co-design and use-driven fundamental science are essential to reach aggressive greenhouse gas reduction targets.

Advances in Computational Methods for Modeling Photocatalytic Reactions: A Review of Recent Developments

Photocatalysis is a fascinating process in which a photocatalyst plays a pivotal role in driving a chemical reaction when exposed to light. Its capacity to harness light energy triggers a cascade of reactions that lead to the formation of intermediate compounds, culminating in the desired final product(s). The essence of this process is the interaction between the photocatalyst's excited state and its specific interactions with reactants, resulting in the creation of intermediates. The process's appeal is further enhanced by its cyclic nature-the photocatalyst is rejuvenated after each cycle, ensuring ongoing and sustainable catalytic action. Nevertheless, comprehending the photocatalytic process through the modeling of photoactive materials and molecular devices demands advanced computational techniques founded on effective quantum chemistry methods, multiscale modeling, and machine learning. This review analyzes contemporary theoretical methods, spanning a range of lengths and accuracy scales, and assesses the strengths and limitations of these methods. It also explores the future challenges in modeling complex nano-photocatalysts, underscoring the necessity of integrating various methods hierarchically to optimize resource distribution across different scales. Additionally, the discussion includes the role of excited state chemistry, a crucial element in understanding photocatalysis.

DL_POLY Quantum 2.0: A modular general-purpose software for advanced path integral simulations

DL_POLY Quantum 2.0, a vastly expanded software based on DL_POLY Classic 1.10, is a highly parallelized computational suite written in FORTRAN77 with a modular structure for incorporating nuclear quantum effects into large-scale/long-time molecular dynamics simulations. This is achieved by presenting users with a wide selection of state-of-the-art dynamics methods that utilize the isomorphism between a classical ring polymer and Feynman's path integral formalism of quantum mechanics. The flexible and user-friendly input/output handling system allows the control of methodology, integration schemes, and thermostatting. DL_POLY Quantum is equipped with a module specifically assigned for calculating correlation functions and printing out the values for sought-after quantities, such as dipole moments and center-of-mass velocities, with packaged tools for calculating infrared absorption spectra and diffusion coefficients.

Quest for Multifunctionality: Current Progress in the Characterization of Heterometallic Metal-Organic Frameworks

Metal-organic frameworks (MOFs) are a class of porous, crystalline materials that have been systematically developed for a broad range of applications. Incorporation of two or more metals into a single crystalline phase to generate heterometallic MOFs has been shown to lead to synergistic effects, in which the whole is oftentimes greater than the sum of its parts. Because geometric proximity is typically required for metals to function cooperatively, deciphering and controlling metal distributions in heterometallic MOFs is crucial to establish structure-function relationships. However, determination of short- and long-range metal distributions is nontrivial and requires the use of specialized characterization techniques. Advancements in the characterization of metal distributions and interactions at these length scales is key to rapid advancement and rational design of functional heterometallic MOFs. This perspective summarizes the state-of-the-art in the characterization of heterometallic MOFs, with a focus on techniques that allow metal distributions to be better understood. Using complementary analyses, in conjunction with computational methods, is critical as this field moves toward increasingly complex, multifunctional systems.

Characterization, Structure, and Reactivity of Hydroxyl Groups on Metal-Oxide Cluster Nodes of Metal-Organic Frameworks: Structural Diversity and Keys to Reactivity and Catalysis

Among the most stable metal-organic frameworks (MOFs) are those incorporating nodes that are metal oxide clusters with frames such as Zr6 O8 . This review is a summary of the structure, bonding, and reactivity of MOF node hydroxyl groups, emphasizing those bonded to nodes containing aluminum and zirconium ions. Hydroxyl groups are often present on these nodes, sometimes balancing the charges of the metal ions. They arise during MOF syntheses in aqueous media or in post-synthesis treatments. They are identified with infrared and 1 H nuclear magnetic resonance spectroscopies and characterized by their reactivities with polar compounds such as alcohols. Terminal OH, paired µ2 -OH, and aqua groups on nodes are catalytic sites in numerous reactions. Relatively unreactive hydroxyl groups (such as isolated µ2 -OH groups) may replace reactive groups and inhibit catalysis; some node hydroxyl groups (e.g., µ3 -OH) are mere spectators in catalysis. There are similarities between MOF node hydroxyl groups and those on the surfaces of bulk metal oxides, zeolites, and enzymes, but the comparisons are mostly inexact, and much remains to be understood about MOF node hydroxyl group chemistry. It is posited that understanding and controlling this chemistry will lead to tailored MOFs and improved adsorbents and catalysts.

Combined DFT and Kinetic Monte Carlo Study of UiO-66 Catalysts for γ-Valerolactone Production

Zr-based metal-organic frameworks (MOFs) are excellent heterogeneous porous catalysts due to their thermal stability. Their tunability via node and linker modifications makes them amenable for theoretical studies on catalyst design. However, detailed benchmarks on MOF-based reaction mechanisms combined with kinetics analysis are still scarce. Thus, we here evaluate different computational models and density functional theory (DFT) methods followed by kinetic Monte Carlo studies for a case reaction relevant in biomass upgrading, i.e., the conversion of methyl levulinate to γ-valerolactone catalyzed by UiO-66. We show the impact of cluster versus periodic models, the importance of the DF of choice, and the direct comparison to experimental data via simulated kinetics data. Overall, we found that Perdew-Burke-Ernzerhof (PBE), a widely employed method in plane-wave periodic calculations, greatly overestimates reaction rates, while M06 with cluster models better fits the available experimental data and is recommended whenever possible.

Recent Advances in Metal-Organic Framework (MOF)-Based Photocatalysts: Design Strategies and Applications in Heavy Metal Control

The heavy metal contamination of water systems has become a major environmental concern worldwide. Photocatalysis using metal-organic frameworks (MOFs) has emerged as a promising approach for heavy metal remediation, owing to the ability of MOFs to fully degrade contaminants through redox reactions that are driven by photogenerated charge carriers. This review provides a comprehensive analysis of recent developments in MOF-based photocatalysts for removing and decontaminating heavy metals from water. The tunable nature of MOFs allows the rational design of composition and features to enhance light harvesting, charge separation, pollutant absorptivity, and photocatalytic activities. Key strategies employed include metal coordination tuning, organic ligand functionalization, heteroatom doping, plasmonic nanoparticle incorporation, defect engineering, and morphology control. The mechanisms involved in the interactions between MOF photocatalysts and heavy metal contaminants are discussed, including light absorption, charge carrier separation, metal ion adsorption, and photocatalytic redox reactions. The review highlights diverse applications of MOF photocatalysts in treating heavy metals such as lead, mercury, chromium, cadmium, silver, arsenic, nickel, etc. in water remediation. Kinetic modeling provides vital insights into the complex interplay between coupled processes such as adsorption and photocatalytic degradation that influence treatment efficiency. Life cycle assessment (LCA) is also crucial for evaluating the sustainability of MOF-based technologies. By elucidating the latest advances, current challenges, and future opportunities, this review provides insights into the potential of MOF-based photocatalysts as a sustainable technology for addressing the critical issue of heavy metal pollution in water systems. Ongoing efforts are needed to address the issues of stability, recyclability, scalable synthesis, and practical reactor engineering.

Computational Discovery of Stable Metal-Organic Frameworks for Methane-to-Methanol Catalysis

The challenge of direct partial oxidation of methane to methanol has motivated the targeted search of metal-organic frameworks (MOFs) as a promising class of materials for this transformation because of their site-isolated metals with tunable ligand environments. Thousands of MOFs have been synthesized, yet relatively few have been screened for their promise in methane conversion. We developed a high-throughput virtual screening workflow that identifies MOFs from a diverse space of experimental MOFs that have not been studied for catalysis, yet are thermally stable, synthesizable, and have promising unsaturated metal sites for C-H activation via a terminal metal-oxo species. We carried out density functional theory calculations of the radical rebound mechanism for methane-to-methanol conversion on models of the secondary building units (SBUs) from 87 selected MOFs. While we showed that oxo formation favorability decreases with increasing 3d filling, consistent with prior work, previously observed scaling relations between oxo formation and hydrogen atom transfer (HAT) are disrupted by the greater diversity in our MOF set. Accordingly, we focused on Mn MOFs, which favor oxo intermediates without disfavoring HAT or leading to high methanol release energies─a key feature for methane hydroxylation activity. We identified three Mn MOFs comprising unsaturated Mn centers bound to weak-field carboxylate ligands in planar or bent geometries with promising methane-to-methanol kinetics and thermodynamics. The energetic spans of these MOFs are indicative of promising turnover frequencies for methane to methanol that warrant further experimental catalytic studies.

High-Throughput Experimentation, Theoretical Modeling, and Human Intuition: Lessons Learned in Metal-Organic-Framework-Supported Catalyst Design

We have screened an array of 23 metals deposited onto the metal-organic framework (MOF) NU-1000 for propyne dimerization to hexadienes. By a first-of-its-kind study utilizing data-driven algorithms and high-throughput experimentation (HTE) in MOF catalysis, yields on Cu-deposited NU-1000 were improved from 0.4 to 24.4%. Characterization of the best-performing catalysts reveal conversion to hexadiene to be due to the formation of large Cu nanoparticles, which is further supported by reaction mechanisms calculated with density functional theory (DFT). Our results demonstrate both the strengths and weaknesses of the HTE approach. As a strength, HTE excels at being able to find interesting and novel catalytic activity; any a priori theoretical approach would be hard-pressed to find success, as high-performing catalysts required highly specific operating conditions difficult to model theoretically, and initial simple single-atom models of the active site did not prove representative of the nanoparticle catalysts responsible for conversion to hexadiene. As a weakness, our results show how the HTE approach must be designed and monitored carefully to find success; in our initial campaign, only minor catalytic performances (up to 4.2% yield) were achieved, which were only improved following a complete overhaul of our HTE approach and questioning our initial assumptions.

Structure and Site Evolution of Framework Ni Species in MIL-127 MOFs for Propylene Oligomerization Catalysis

A mixed-valence oxotrimer metal-organic framework (MOF), Ni-MIL-127, with a fully coordinated nickel atom and two iron atoms in the inorganic node, generates a missing linker defect upon thermal treatment in helium (>473 K) to engender an open coordination site on nickel which catalyzes propylene oligomerization devoid of any cocatalysts or initiators. This catalyst is stable for ∼20 h on stream at 500 kPa and 473 K, unprecedented for this chemistry. The number of missing linkers on synthesized and activated Ni-MIL-127 MOFs is quantified using temperature-programmed oxidation, ¹H nuclear magnetic resonance spectroscopy, and X-ray absorption spectroscopy to be ∼0.7 missing linkers per nickel; thus, a majority of Ni species in the MOF framework catalyze propylene oligomerization. In situ NO titrations under reaction conditions enumerate ∼62% of the nickel atoms as catalytically relevant to validate the defect density upon thermal treatment. Propylene oligomerization rates on Ni-MIL-127 measured at steady state have activation energies of 55-67 kJ mol^-1 from 448 to 493 K and are first-order in propylene pressures from 5 to 550 kPa. Density functional theory calculations on cluster models of Ni-MIL-127 are employed to validate the plausibility of the missing linker defect and the Cossee-Arlman mechanism for propylene oligomerization through comparisons between apparent activation energies from steady-state kinetics and computation. This study illustrates how MOF precatalysts engender defective Ni species which exhibit reactivity and stability characteristics that are distinct and can be engineered to improve catalytic activity for olefin oligomerization.

Effectively Decontaminating Protein-Bound Uremic Toxins in Human Serum Albumin Using Cationic Metal-Organic Frameworks

In the field of replacement of conventional dialysis treatment, searching superior materials for removal of protein-bound uremic toxins is a challenge on account of strong interactions between proteins and uremic toxins. Herein, we first adopted cationic metal-organic frameworks (MOFs), ZJU-X6 and ZJU-X7, as sorbents to decontaminate uremic toxins (p-cresyl sulfate and indoxyl sulfate). ZJU-X6 and ZJU-X7 exhibited innate advantage for sequestration of uremic toxins by utilizing a positive charge framework with exchangeable anions. Especially, ZJU-X6 showed a higher sorption capacity and faster sorption kinetics than those of most reported materials. Moreover, the cationic MOF materials could selectively remove uremic toxins even if in the presence of competitive chloride ions and proteins. Meanwhile, pair distribution function (PDF) and density functional theory (DFT) were employed to elucidate the sorption mechanism between uremic toxins and sorbents. This work suggests an attractive avenue for constructing new types of sorbents to eliminate uremic toxins for uremia treatment.

Adapting UFF4MOF for Heterometallic Rare-Earth Metal-Organic Frameworks

Heterometallic metal-organic frameworks based on rare-earth metals (RE-MOFs) have potential in a number of applications where energy transfer between nearby metal atoms is required. This observation implies that it is important to understand the level of local mixing that is achieved between metals of different types during synthesis of RE-MOFs. Density functional theory calculations can give quantitative information on the relative energy of different configurations of RE-MOFs, but these calculations cannot be applied to the full range of medium- and long-range orderings that are possible in heterometallic materials. This limitation can be overcome using force field (FF)-based calculations if appropriate FFs are available. We show that an existing generic FF for MOFs, UFF4MOF, does not accurately predict energies of mixing in heterometallic Nd/Yb MOFs and introduce a modified FF to address this shortcoming. The resulting FF is used to explore metal orderings in large simulation volumes for a Nd/Yb MOF, illustrating the complexities that can arise in the structure of heterometallic RE-MOFs.

Computational design of magnetic molecules and their environment using quantum chemistry, machine learning and multiscale simulations

Having served as a playground for fundamental studies on the physics of d and f electrons for almost a century, magnetic molecules are now becoming increasingly important for technological applications, such as magnetic resonance, data storage, spintronics and quantum information. All of these applications require the preservation and control of spins in time, an ability hampered by the interaction with the environment, namely with other spins, conduction electrons, molecular vibrations and electromagnetic fields. Thus, the design of a novel magnetic molecule with tailored properties is a formidable task, which does not only concern its electronic structures but also calls for a deep understanding of the interaction among all the degrees of freedom at play. This Review describes how state-of-the-art ab initio computational methods, combined with data-driven approaches to materials modelling, can be integrated into a fully multiscale strategy capable of defining design rules for magnetic molecules.

UiO-66 metal organic frameworks with high contents of flexible adipic acid co-linkers

Adipic acid, an industrially-important chemical that can be sustainably derived from biomass and post-consumer nylon, is traditionally overlooked as a linker for MOFs. Herein, we report the first direct one-pot method for synthesising UiO-66 MOFs with an unprecedented 69 mol% adipate content, as well as the feasibility of these materials for MOF defect engineering by rapid and selective adipate thermolysis.

Simple Approximation for the Ideal Reference State of Gases Adsorbed on Solid-State Surfaces

Reference states are useful as models for facilitating calculations of equilibrium constants, and they may also serve as standard states that are convenient for organizing and tabulating thermodynamic data; however, standard state conventions and appropriate reference states for adsorbed species have received less attention than those for pure substances and solutes. Here, we compare seven choices of reference states for calculations of equilibrium constants and transition state theory rate constants for flat surfaces, in particular (1) an ideal 2D harmonic oscillator, (2) an ideal rigid-molecule harmonic oscillator, (3) an ideal 2D harmonic oscillator with separable surface modes, (4) a 2D ideal gas, (5) an ideal 2D hindered translator, (6) an ideal 2D hindered translator with lowest-order barriers, and (7) a simple ideal 2D hindered translator proposed in this work. The advantage of models 5-7 is that they can treat both mobile and localized adsorbates in a consistent way, whereas models 1-3 are only appropriate for localized adsorbates, and model 4 is only appropriate for a freely translating adsorbate. Furthermore, models 6 and 7 reduce the computational cost without the user having to calculate barrier heights for diffusion. An advantage of the simple ideal 2D hindered translator is that it has a physical high-temperature limit. We also propose a reference state for nonflat surfaces. The user is encouraged to choose a reference state based on the appropriateness of the model and the practicality of the calculations.

Biocatalytic conversion of sunlight and carbon dioxide to solar fuels and chemicals

This review discusses the progress in the assembly of photosynthetic biohybrid systems using enzymes and microbes as the biocatalysts which are capable of utilising light to reduce carbon dioxide to solar fuels. We begin by outlining natural photosynthesis, an inspired biomachinery to develop artificial photosystems, and the rationale and motivation to advance and introduce biological substrates to create more novel, and efficient, photosystems. The case studies of various approaches to the development of CO2-reducing microbial semi-artificial photosystems are also summarised, showcasing a variety of methods for hybrid microbial photosystems and their potential. Finally, approaches to investigate the relatively ambiguous electron transfer mechanisms in such photosystems are discussed through the presentation of spectroscopic techniques, eventually leading to what this will mean for the future of microbial hybrid photosystems.

Highly Efficient and Stable Eu3+-Doped CsPbBr3/Cs4PbBr6 Perovskites for White Light-Emitting Diodes

All-inorganic halide perovskite nanomaterials have a high application potential in the field of display and lighting because of unique photoelectric properties. However, these materials suffer from problems related to poor water and thermal stabilities. In this study, green Eu3+-doped CsPbBr3/Cs4PbBr6 perovskite composites that were synthesized by a saturated recrystallization method at room temperature showed an enhanced photoluminescence quantum yield of 87% and superior water and thermal stabilities to that of undoped perovskites. Finally, green Eu3+-doped CsPbBr3/Cs4PbBr6 perovskite composites were fabricated into white light-emitting diodes (WLEDs) with a wide color gamut (124% of the National Television System Committee standard) and a high efficiency of 43.06 lm/W.

Exploring mechanistic routes for light alkane oxidation with an iron-triazolate metal-organic framework

In this work, we computationally explore the formation and subsequent reactivity of various iron-oxo species in the iron-triazolate framework Fe₂(μ-OH)₂(bbta) (H₂bbta = 1H,5H-benzo(1,2-d:4,5-d')bistriazole) for the catalytic activation of strong C-H bonds. With the direct conversion of methane to methanol as the probe reaction of interest, we use density functional theory (DFT) calculations to evaluate multiple mechanistic pathways in the presence of either N₂O or H₂O₂ oxidants. These calculations reveal that a wide range of transition metal-oxo sites - both terminal and bridging - are plausible in this family of metal-organic frameworks, making it a unique platform for comparing the electronic structure and reactivity of different proposed active site motifs. Based on the DFT calculations, we predict that Fe₂(μ-OH)₂(bbta) would exhibit a relatively low barrier for N₂O activation and energetically favorable formation of an [Fe(O)]²⁺ species that is capable of oxidizing C-H bonds. In contrast, the use of H₂O₂ as the oxidant is predicted to yield an assortment of bridging iron-oxo sites that are less reactive. We also find that abstracting oxo ligands can exhibit a complex mixture of both positive and negative spin density, which may have broader implications for relating the degree of radical character to catalytic activity. In general, we consider the coordinatively unsaturated iron sites to be promising for oxidation catalysis, and we provide several recommendations on how to further tune the catalytic properties of this family of metal-triazolate frameworks.

Ab Initio Study of Hydrostable Metal-Organic Frameworks for Postsynthetic Modification and Tuning toward Practical Applications

Metal-organic frameworks (MOFs), a subclass of nanoporous coordination polymers, have emerged as one of the most promising next-generation materials. The postsynthetic modification method, a strategy that provides tunability and control of these materials, plays an important role in enhancing its properties and functionalities. However, knowing adjustments which leads to a desired structure-function a priori remains a challenge. In this comprehensive study, the intermolecular interactions between 21 industrially important gases and a hydrostable STAM-17-OEt MOF were investigated using density functional theory. Substitutions on its 5-ethoxy isophthalate linker included two classes of chemical groups, electron-donating (-NH₂, -OH, and -CH₃) and electron-withdrawing (-CN, -COOH, and -F), as well as the effect of mono-, di-, and tri-substitutions. This resulted in 651 unique MOF-gas complexes. The adsorption energies at the ground state and room temperature, bond lengths, adsorption geometry, natural bond orbital analysis of the electric structure, HOMO-LUMO interactions, and the predicted zwitterionic properties are presented and discussed. This study provides a viable strategy for the functionalization, which leads to the strongest affinity for each gas, an insight into the role of different chemical groups in adsorbing various gas molecules, and identifies synthetic routes for moderating the gas adsorption capacity and reducing water adsorption. Recommendations for various applications are discussed. A custom Python script to assess and visualize the hypothetical separation of two equal gas mixtures of interest is provided. The methodology presented here provides new opportunities to expand the chemical space and physical properties of STAM-17-OEt and advances the development of other hydrostable MOFs.

Strength and Nature of Host-Guest Interactions in Metal-Organic Frameworks from a Quantum-Chemical Perspective

Metal‐organic frameworks (MOFs) offer a convenient means for capturing, transporting, and releasing small molecules. Their rational design requires an in‐depth understanding of the underlying non‐covalent host‐guest interactions, and the ability to easily and rapidly pre‐screen candidate architectures in silico. In this work, we devised a recipe for computing the strength and analysing the nature of the host‐guest interactions in MOFs. By assessing a range of density functional theory methods across periodic and finite supramolecular cluster scale we find that appropriately constructed clusters readily reproduce the key interactions occurring in periodic models at a fraction of the computational cost. Host‐guest interaction energies can be reliably computed with dispersion‐corrected density functional theory methods; however, decoding their precise nature demands insights from energy decomposition schemes and quantum‐chemical tools for bonding analysis such as the quantum theory of atoms in molecules, the non‐covalent interactions index or the density overlap regions indicator.

PoreMatMod.jl: Julia Package for in Silico Postsynthetic Modification of Crystal Structure Models

PoreMatMod.jl is a free, open-source, user-friendly, and documented Julia package for modifying crystal structure models of porous materials such as metal-organic frameworks (MOFs). PoreMatMod.jl functions as a find-and-replace algorithm on crystal structures by leveraging (i) Ullmann's algorithm to search for subgraphs of the crystal structure graph that are isomorphic to the graph of a query fragment and (ii) the orthogonal Procrustes algorithm to align a replacement fragment with a targeted substructure of the crystal structure for installation. The prominent application of PoreMatMod.jl is to generate libraries of hypothetical structures for virtual screenings. For example, one can install functional groups on the linkers of a parent MOF, mimicking postsynthetic modification. Other applications of PoreMatMod.jl to modify crystal structure models include introducing defects with precision and correcting artifacts of X-ray structure determination (adding missing hydrogen atoms, resolving disorder, and removing guest molecules). The find-and-replace operations implemented by PoreMatMod.jl can be applied broadly to diverse atomistic systems for various in silico structural modification tasks.

MOF-enabled confinement and related effects for chemical catalyst presentation and utilization

A defining characteristic of nearly all catalytically functional MOFs is uniform, molecular-scale porosity. MOF pores, linkers and nodes that define them, help regulate reactant and product transport, catalyst siting, catalyst accessibility, catalyst stability, catalyst activity, co-catalyst proximity, composition of the chemical environment at and beyond the catalytic active site, chemical intermediate and transition-state conformations, thermodynamic affinity of molecular guests for MOF interior sites, framework charge and density of charge-compensating ions, pore hydrophobicity/hydrophilicity, pore and channel rigidity vs. flexibility, and other features and properties. Collectively and individually, these properties help define overall catalyst functional behaviour. This review focuses on how porous, catalyst-containing MOFs capitalize on molecular-scale confinement, containment, isolation, environment modulation, energy delivery, and mobility to accomplish desired chemical transformations with potentially superior selectivity or other efficacy, especially in comparison to catalysts in homogeneous solution environments.

Theoretical evaluation of the performance of IRMOFs and M-MOF-74 in the formation of 5-fluorouracil@MOF

Drug delivery systems are a viable resource to be used in medical treatments that tend to be very aggressive to patients, increasing the bioavailability. In this context, porous structures such as MOFs emerge as promising for this type of application, in which a specific drug is adsorbed onto the structure for further release. MOFs such as IRMOFs and M-MOF-74 are investigated in many applications, including use as a drug carrier. In this work, the Monte Carlo grand canonical simulation was used for obtaining insights on the behaviour of 5-fluorouracil adsorption on IRMOF-1, IRMOF-8, IRMOF-10, Mg-MOF74, Fe-MOF74, Cu-MOF74 and Zn-MOF74. We have evaluated the influence of the adsorption of changing organic and inorganic units, which resulted in different chemical environments. It was seen that the drug interacts more efficiently with M-MOF-74, where the metallic centre plays an important role. For IRMOFs, a larger pore volume increases the amount of adsorbed molecules. This effect is mainly due to the contribution of the efficient interaction between 5-fluorouracil molecules.

Drug delivery systems are a viable resource to be used in medical treatments that tend to be very aggressive to patients, increasing the bioavailability.

Computational Investigation of Adsorptive Removal of Pb

Adsorption using metal–organic frameworks (MOFs) such as UiO-66 has shown great promise in remediating water sources contaminated with toxic heavy metals such as Pb2+, but detailed information about the adsorption process remains limited. In this article, we gained mechanistic insights into Pb2+ adsorption using both functionalised and defective UiO-66 by performing density functional theory calculations using cluster models. Our benchmarked approach led to a computational model of solvated Pb2+ (a hemidirected Pb(H2O)62+ complex) fully consistent with experimental reports. The analysis of Pb2+ adsorption using functionalised UiO-66 determined that factors such as electrostatic attraction, chelation, and limited constraints on the Pb2+ coordination geometry lead to enhanced binding affinity. For these reasons, UiO-66-COO– was identified as the most promising functionalised MOF, consistent with experimental literature. We additionally explored a novel aspect of Pb2+ adsorption by UiO-66: the role of missing linker defects that often characterise this MOF. We found that the defects expected to form in an aqueous environment can act as excellent adsorption sites for Pb2+ and the preferred adsorption geometry is again determined by electrostatic attraction, chelation, and constraints on the Pb2+ coordination geometry. Overall, we conclude that functional groups and defect sites can both contribute to Pb2+ adsorption and our study provides crucial design principles for improving the UiO-66 MOF performance in toxic Pb2+ removal from water.

Spatially isolated cobalt oxide sites derived from MOFs for direct propane dehydrogenation

The "active site isolation" strategy has been proved to be efficient for enhancing the catalytic performance in propane dehydrogenation (PDH). Herein, spatially isolated cobalt oxide sites within nitrogen-doped carbon (NC) layers supported on silicalite-1 zeolite (CoO_x@NC/S-1) were synthesized by a two-step process consisting of the pyrolysis of bimetallic Zn/Co zeolitic imidazole frameworks loaded on silicalite-1 (ZnCo-ZIF/S-1) under N₂ and the subsequent calcination in air atmosphere. This catalyst possesses exceptional catalytic performance for PDH with the propane conversion of 40% and the propene selectivity of >97%, and no apparent deactivation is observed after 10 h PDH reaction at 600 °C. With intensive characterizations and experiments, it is indicated that the real active sites of CoO_x@NC/S-1 are isolated CoO sites during the PDH process. In situ FT-IR spectroscopy shows the same intermediate product (Co-C₃H₇) during both propane dehydrogenation and propene hydrogenation, indicating that they have a reverse reaction process, and a reaction mechanism for PDH is proposed accordingly.

Zr-MOFs Integrated with a Guest Capturer and a Photosensitizer for the Simultaneous Adsorption and Degradation of 4-Chlorophenol

A bifunctional metal-organic framework (MOF) was successfully designed to realize the purification of 4-chlorophenol (4-CP) under simulated sunlight irradiation. Owing to the large-size mesopores of the MOF matrix NU-1000, β-CMCD (carboxylic β-cyclodextrin) could be incorporated into the frameworks with a density of 2.4% to pre-enrich the pollutant of 4-CP. Meanwhile, the photodegradation promoter [Pd(II) meso-tetra(4-carboxyphenyl)porphine] was in situ co-assembled with the organic ligand to realize its synchronous degradation. As for the current integrator, a Langmuir model was used to explain the adsorption isotherm, and the Langmuir-Hinshelwood model exhibited a better fit to its catalytic degradation behavior. Thanks to the simultaneous presence of a capturer and a photodegradation promoter, the adsorption capacity of 4-CP reached as high as 296 mg g^-1, which was further completely detoxified within 60 min under simulated sunlight irradiation with a half-life time of only 5.98 min. Such excellent integrated decontamination properties prefigure the great promising potential of multifunctional MOFs in the field of pollution purification.

Beyond structural motifs: the frontier of actinide-containing metal-organic frameworks

In this perspective, we feature recent advances in the field of actinide-containing metal-organic frameworks (An-MOFs) with a main focus on their electronic, catalytic, photophysical, and sorption properties. This discussion deviates from a strictly crystallographic analysis of An-MOFs, reported in several reviews, or synthesis of novel structural motifs, and instead delves into the remarkable potential of An-MOFs for evolving the nuclear waste administration sector. Currently, the An-MOF field is dominated by thorium- and uranium-containing structures, with only a few reports on transuranic frameworks. However, some of the reported properties in the field of An-MOFs foreshadow potential implementation of these materials and are the main focus of this report. Thus, this perspective intends to provide a glimpse into the challenges, triumphs, and future directions of An-MOFs in sectors ranging from the traditional realm of gas sorption and separation to recently emerging areas such as electronics and photophysics.

Heterogenisation of polyoxometalates and other metal-based complexes in metal–organic frameworks: from synthesis to characterisation and applications in catalysis

This review provides a thorough overview of composites with molecular catalysts (polyoxometalates, or organometallic or coordination complexes) immobilised into MOFs via non-covalent interactions.

Syntheses of a series of lanthanide metal–organic frameworks for efficient UV-light-driven dye degradation: experiment and simulation

Three Ln-MOFs show unique 3,8-connected 3D networks and have been used as photocatalysts for the degradation of organic dye methyl violet under UV light.

A facile cucurbit[8]uril-based porous assembly: utilization in the adsorption of drugs and their controlled release

Cucurbit[n]urils (Q[n]s) are essential members of the supramolecular organic framework family owing to their distinct structure.

In silico investigation of Cu(In,Ga)Se2-based solar cells

Photovoltaics is one of the most promising and fastest-growing renewable energy technologies. Although the price-performance ratio of solar cells has improved significantly over recent years, further systematic investigations are needed to achieve higher performance and lower cost for future solar cells. In conjunction with experiments, computer simulations are powerful tools to investigate the thermodynamics and kinetics of solar cells. Over the last few years, we have developed and employed advanced computational techniques to gain a better understanding of solar cells based on copper indium gallium selenide (Cu(In,Ga)Se2). Furthermore, we have utilized state-of-the-art data-driven science and machine learning for the development of photovoltaic materials. In this Perspective, we review our results along with a survey of the field.