Computational catalysis for metal-organic frameworks: An overview

Catalytic Ethylene Oligomerization over Imine-Linked Covalent-Organic Frameworks with Coordinative Ni(II) and Cr(III)

Covalent-organic frameworks (COFs) hold great promise for heterogeneous catalysis due to their porous structure for gas adsorption and tunable functionality for bond activation. This study reports two flower-like shaped imine-linked COFs with coordinative Ni-(II) and Cr-(III) species, to endow Ni/PD-TPA COF and Cr/PD-TPA COF, for catalytic ethylene oligomerization. The synergy between imine nitrogen atoms and coordinated metals enables an exceptional activity (16.70 × 105 and 19.90 × 105 g/(mol M·h)) with high selectivity of butene and hexane (∼98.5%) in long-span catalytic processes, respectively. To optimize multiple reaction parameters (e.g., cocatalyst dosage, temperature, and time), Box-Behnken design (BBD) is employed as a statistical tool to establish a precise model integrating process parameters, catalyst structures, and catalytic performance. The optimized models exhibit high precision (indicated by high R values) in predicting the activity and selectivity of ethylene oligomerization over Cr/PD-TPA COF and Ni/PD-TPA COF, indicating the promise of BBD in reaction engineering and process design. M/PD-TPA COFs are highly active after three recycles and deliver the highest activity at ambient temperature and low pressure with a minimal quantity of cocatalysts compared with other catalysts. These findings demonstrate the potential of metal-loaded COFs for sustainable heterogeneous catalysis and provide insights into the optimization of reaction parameters using statistical methods.

Evaluation of Semiempirical Quantum Mechanical Methods for Zr-Based Metal-Organic Framework Catalysts

Zr-based metal-organic frameworks (MOFs) are typically employed in heterogeneous catalysis due to their porosity, chemical and thermal stability, and well-defined active sites. Density functional theory (DFT) is the workhorse to compute their electronic structure; however, it becomes very costly when dealing with reaction mechanisms involving large unit cells and vast configurational spaces. Semiempirical quantum mechanical (SQM) methods appear as an alternative approach to simulate such chemical systems at low computational cost, but their feasibility to model catalysis with MOFs is still unexplored. Thus, here we present a benchmark study on UiO-66 to evaluate the performance of SQM methods (PM6, PM7, GFN1-xTB, GFN2-xTB) against hybrid DFT (M06). We evaluate defective nodes, ligand exchange reactions, barrier heights, and host-guest interactions with metal nanoclusters. Despite some caveats, GFN1-xTB on properly constrained models is the best SQM method across all studied properties. Under proper supervision, this protocol holds promise for application in exploratory high-throughput screenings of Zr-based MOF catalysts, subject to further refinement with more accurate methods.

Development and Application of Fe3+, Al3+, Cr3+ Dummy Atom Models for Metal-Organic Frameworks

Various metal-organic frameworks (MOFs) containing trivalent cations (such as Fe3+, Al3+, and Cr3+) have been reported and have shown great potential in applications. However, the high structural diversity and strong electronic interactions between metal centers and their ligands make the molecular dynamics simulations of MOFs challenging. In this work, we developed new dummy atom models for Fe3+, Al3+, and Cr3+ cations, which can be used in classical molecular dynamics simulations of MOFs. In our models, the correct solvation free energies and metal-ligand distances can be simultaneously reproduced. Furthermore, the usefulness and transferability of our models were validated using the commonly studied MIL-100(M) (M = Fe3+, Al3+, Cr3+) and MIL-88B(Fe3+) systems. Our developed models offer a valuable tool for simulating complex systems containing Fe3+, Al3+, and Cr3+ cations with octahedral coordination structures.

Multiphoton Excited Fluorescence Imaging over Metal-Organic Frameworks

Multiphoton excited fluorescence (MPEF) imaging has emerged as a powerful tool for visualizing biological processes with high spatial and temporal resolution. Metal-organic frameworks (MOFs), a class of porous materials composed of metal ions or clusters coordinated with organic ligands, have recently gained attention for their unique optical properties and potential applications in MPEF imaging. This review provides a comprehensive overview of the design, synthesis, and applications of multiphoton excited fluorescence imaging using MOFs. We discuss the principles behind the fluorescence behavior of MOFs, explore strategies to enhance their photophysical properties, and showcase their applications in bioimaging. Additionally, we address the current challenges and future prospects in this rapidly evolving field, highlighting the potential of multiphoton excited fluorescence imaging by MOFs for advancing our understanding of complex biological processes.

Ichor: A Python library for computational chemistry data management and machine learning force field development

We present ichor, an open-source Python library that simplifies data management in computational chemistry and streamlines machine learning force field development. Ichor implements many easily extensible file management tools, in addition to a lazy file reading system, allowing efficient management of hundreds of thousands of computational chemistry files. Data from calculations can be readily stored into databases for easy sharing and post-processing. Raw data can be directly processed by ichor to create machine learning-ready datasets. In addition to powerful data-related capabilities, ichor provides interfaces to popular workload management software employed by High Performance Computing clusters, making for effortless submission of thousands of separate calculations with only a single line of Python code. Furthermore, a simple-to-use command line interface has been implemented through a series of menu systems to further increase accessibility and efficiency of common important ichor tasks. Finally, ichor implements general tools for visualization and analysis of datasets and tools for measuring machine-learning model quality both on test set data and in simulations. With the current functionalities, ichor can serve as an end-to-end data procurement, data management, and analysis solution for machine-learning force-field development.

Heterogenous Epoxidation of Isobutene Selectively Enabled by MoSe2 in Hexafluoroisopropanol (HFIP)

Herein, a high selective epoxidation of isobutene was achieved by heterogeneously dispersed MoSe2 with tert-butyl hydroperoxide (TBHP), which further showed versatile substrate scopes and well-retained activity among recycling tests. A rational mechanism is proposed based on extensive control experiments and electron paramagnetic resonance spectroscopy, surprisingly unveiling the metal-oxo and radical mediated pathways dramatically accelerated by hydrogen bonds of hexafluoroisopropanol (HFIP).

Electrostatically Designing Materials and Interfaces

Collective electrostatic effects arise from the superposition of electrostatic potentials of periodically arranged (di)polar entities and are known to crucially impact the electronic structures of hybrid interfaces. Here, it is discussed, how they can be used outside the beaten paths of materials design for realizing systems with advanced and sometimes unprecedented properties. The versatility of the approach is demonstrated by applying electrostatic design not only to metal-organic interfaces and adsorbed (complex) monolayers, but also to inter-layer interfaces in van der Waals heterostructures, to polar metal-organic frameworks (MOFs), and to the cylindrical pores of covalent organic frameworks (COFs). The presented design ideas are straightforward to simulate and especially for metal-organic interfaces also their experimental implementation has been amply demonstrated. For van der Waals heterostructures, the needed building blocks are available, while the required assembly approaches are just being developed. Conversely, for MOFs the necessary growth techniques exist, but more work on advanced linker molecules is required. Finally, COF structures exist that contain pores decorated with polar groups, but the electrostatic impact of these groups has been largely ignored so far. All this suggest that the dawn of the age of electrostatic design is currently experienced with potential breakthroughs lying ahead.

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.

Application and prospects of metal–organic frameworks in photocatalytic self-cleaning membranes for wastewater treatment

By loading photocatalytic MOF onto the separation membrane, the self-cleaning function of the membrane can be realized. This paper discusses the structure, synthesis, and properties of photocatalytic MOFs.

Mechanisms of interaction between metal-organic framework-based material and persulfate in degradation of organic contaminants (OCs): Activation, reactive oxygen generation, conversion, and oxidation

Metal-organic frameworks (MOFs)-based materials have been of great public interest in persulfate (PS)-based catalytic oxidation for wastewater purification, because of their excellent performance and selectiveness in organic contaminants (OCs) removal in complex water environments. The formation, fountainhead and reaction mechanism of reactive oxygen species (ROSs) in PS-based catalytic oxidation are crucial for understanding the principles of PS activation and the degradation mechanism of OCs. In the paper, we presented the quantitative structure-activity relationship (QSAR) of MOFs-based materials for PS activation, including the relationship of structure and removal efficiency, active sites and ROSs as well as OCs. In various MOFs-based materials, there are many factors will affect their performances. We discussed how various surface modification projects affected the characteristics of MOFs-based materials used in PS activation. Moreover, we revealed the process of ROSs generation by active sites and the oxidation of OCs by ROSs from the micro level. At the end of this review, we putted forward an outlook on the development trends and faced challenges of MOFs for PS-based catalytic oxidation. Generally, this review aims to clarify the formation mechanisms of ROSs via the active sites on the MOFs and the reaction mechanism between ROSs and OCs, which is helpful for reader to better understand the QSAR in various MOFs/PS systems.

Highly Sensitive Ratiometric Fluorescent Flexible Sensor Based on the RhB@ZIF-8@PVDF Mixed-Matrix Membrane for Broad-Spectrum Antibiotic Detection

Antibiotics play an essential role in the treatment of various diseases. However, the overuse of antibiotics has led to the pollution of water bodies and food safety, affecting human health. Herein, we report a dual-emission MOF-based flexible sensor for the detection of antibiotics in water, which was prepared by first encapsulating rhodamine B (RhB) by a zeolite imidazolium ester skeleton (ZIF-8) and then blending it with polyvinylidene difluoride (PVDF). The luminescent properties, structural tunability, and flexible porosity of the MOF-based composites were combined with the processability and flexibility of polymers to prepare luminescent membranes. The sensor is capable of dual-emission ratiometric fluorescence sensing of nitrofurantoin (NFT) and oxytetracycline (OTC), exhibiting sensitive detection of fluorescence burst and fluorescence enhancement, respectively, with detection limits of 0.012 μM and 8.9 nM. With the advantages of visual detection, high sensitivity, short detection time, and simplicity, the highly sensitive ratiometric fluorescent flexible sensor has great potential for detecting antibiotics in an aqueous environment. It will further stimulate interest in luminescent MOF-based mixed matrix membranes and their sensing applications.

Automated Graph Neural Networks Accelerate the Screening of Optoelectronic Properties of Metal-Organic Frameworks

The numerous organic and inorganic components of metal-organic framework (MOF) materials provide intriguing optoelectronic properties. Accurately predicting the electronic structural properties of MOFs has become the main focus. This work establishes two graph neural network models, crystal graph convolutional neural networks and a materials graph network, for predicting the band gaps of more than 10 000 MOF structures and promotes to improve the prediction accuracy through automatic hyperparameter tuning algorithms. Subsequently, for exploring machine learning-assisted screening of MOFs for the broader electronic properties, the screened copper-based MOFs are compared with lead-based MAPbI₃ solar cells with respect to the band gaps, densities of states, and charge density distributions, and the results have demonstrated that the overlap of the wave functions between the initial and final states of MOFs is weakened, which is conducive to the improvement of photoelectric performance. The chlorine doping strategy further enhances the advantage. The tuning of the machine learning model and hyperparameters and the doping strategy of halogen elements furnish empirical rules for the design of MOFs with excellent optoelectronic properties.

Connecting the dots for fundamental understanding of structure-photophysics-property relationships of COFs, MOFs, and perovskites using a Multiparticle Holstein Formalism

Photoactive organic and hybrid organic-inorganic materials such as conjugated polymers, covalent organic frameworks (COFs), metal-organic frameworks (MOFs), and layered perovskites, display intriguing photophysical signatures upon interaction with light. Elucidating structure-photophysics-property relationships across a broad range of functional materials is nontrivial and requires our fundamental understanding of the intricate interplay among excitons (electron-hole pair), polarons (charges), bipolarons, phonons (vibrations), inter-layer stacking interactions, and different forms of structural and conformational defects. In parallel with electronic structure modeling and data-driven science that are actively pursued to successfully accelerate materials discovery, an accurate, computationally inexpensive, and physically-motivated theoretical model, which consistently makes quantitative connections with conceptually complicated experimental observations, is equally important. Within this context, the first part of this perspective highlights a unified theoretical framework in which the electronic coupling as well as the local coupling between the electronic and nuclear degrees of freedom can be efficiently described for a broad range of quasiparticles with similarly structured Holstein-style vibronic Hamiltonians. The second part of this perspective discusses excitonic and polaronic photophysical signatures in polymers, COFs, MOFs, and perovskites, and attempts to bridge the gap between different research fields using a common theoretical construct - the Multiparticle Holstein Formalism. We envision that the synergistic integration of state-of-the-art computational approaches with the Multiparticle Holstein Formalism will help identify and establish new, transformative design strategies that will guide the synthesis and characterization of next-generation energy materials optimized for a broad range of optoelectronic, spintronic, and photonic applications.

Nitric oxide detection using catalytic properties of CuCo-PTC metal organic framework

As a vital gaseous signal molecule involved in various physiological and pathological processes, nitric oxide (NO) has attracted extensive attention in the last few decades. In this work, a copper and cobalt element-doped, biphenyl-(3, 4', 5)-tricarboxylic acid (H₃PTC)-synthesized metal organic framework (CuCo-PTC MOF) composite with catalytic ability was synthesized by solvothermal method. The material can catalyse the oxidation of o-phenylenediamine (OPD) groups by hydrogen peroxide (H₂O₂) to form fluorophores (OPDox) with yellow fluorescence emission and greatly improves its reaction rate. In the presence of NO, OPD will react with NO to produce N-(2-hydrazinophenyl) methylamine, and the group will not react with H₂O₂. Therefore, the concentration of NO can be measured indirectly by comparing the changes of fluorescence intensity in the presence and absence of NO. As the concentration of NO changes, the change of solution colour (from bright yellow to colourless) can also be observed under a 365-nm UV lamp. Furthermore, the method represents high selectivity for NO and shows a fast (within 5 min) and specific fluorescence response toward NO with a linear range from 0.25 to 2.0 μM; the strategy has a limit of detection (LOD) of  0.15 μM. More importantly, the probe was successfully used to detect NO in cell lysate. The recovery was between 98.5 and 103.6%, and the relative standard deviation was between 0.4 and 1.8%. The endogenous NO in cells was successfully detected under the stimulation of L-arginine, which proved the possibility of the probe in real-time and rapid sensing in actual samples and cells. The results indicate that this sensing strategy has the potential to detect NO in the internal environment. Schematic of fluorescence detection of NO.

Computational Mechanism of Methyl Levulinate Conversion to γ-Valerolactone on UiO-66 Metal Organic Frameworks

Metal-organic frameworks (MOFs) are gaining importance in the field of biomass conversion and valorization due to their porosity, well-defined active sites, and broad tunability. But for a proper catalyst design, we first need detailed insight of the system at the atomic level. Herein, we present the reaction mechanism of methyl levulinate to γ-valerolactone on Zr-based UiO-66 by means of periodic density functional theory (DFT). We demonstrate the role of Zr-based nodes in the catalytic transfer hydrogenation (CTH) and cyclization steps. From there, we perform a computational screening to reveal key catalyst modifications to improve the process, such as node doping and linker exchange.

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.

Single-Atoms on Covalent or Metal-Organic Frameworks: Current Findings and Perspectives for Pollutants Abatement, Hydrogen Evolution, and Reduction of CO2

Nowadays, attention to single-atoms and also porous structures like metal-organic frameworks (MOFs) and covalent-organic frameworks (COFs) for the preparation of high-performance material is expanding rapidly. These dazzling materials with unprecedented properties have lots of applications, especially as promising catalysts for organic pollutants abatement, hydrogen evolution, reduction of CO₂, etc. To provide an in-depth understanding, in this mini-review, we begin with a brief description and a general background about single-atoms, COFs, as well as MOFs. After considering some fundamentals, the synergism effects, advantages, and their applications are discussed.

Metal-organic framework-encapsulated nanoparticles for synergetic chemo/chemodynamic therapy with targeted H2O2 self-supply

Nanocatalytic cancer therapy based on chemodynamic therapy, which converts hydrogen peroxide (H2O2) into toxic reactive oxygen species via the Fenton-like reaction, is regarded as a promising therapeutic strategy due to its specific response toward the tumor microenvironment (TME). However, the H2O2 concentration in TME (100 μM to 1 mM) is insufficient and introducing enough H2O2 or H2O2-generating agents is challenging. In view of this, we report a drug delivery system, CaO2/DOX@Cu/ZIF-8@HA (CDZH), which is capable of targeted H2O2 self-supply and exhibits outstanding chemo/chemodynamic synergetic therapy capability. CaO2/DOX@Cu/ZIF-8@HA is synthesized by fabricating biodegradable Cu/ZIF-8 shell-encapsulated CaO2 nanoparticles, loading chemotherapy drug doxorubicin, and coating a hyaluronic acid shell. In an acidic tumor microenvironment, the CDZH nanostructures targeted the release of doxorubicin, Cu2+, and CaO2. Doxorubicin affects chemotherapy and bioimaging, and CaO2 supplies H2O2 through a Cu-Fenton-like reaction to generate hydroxyl radicals with high oxidation activity for chemodynamic therapy. In brief, the drug delivery system combined targeted H2O2 self-supply and targeted bioimaging possess the potential of an efficient synergistic strategy for chemodynamic therapy and chemotherapy.

High-throughput virtual screening for organic electronics: a comparative study of alternative strategies

We present a review of the field of high-throughput virtual screening for organic electronics materials focusing on the sequence of methodological choices that determine each virtual screening protocol. These choices are present in all high-throughput virtual screenings and addressing them systematically will lead to optimised workflows and improve their applicability. We consider the range of properties that can be computed and illustrate how their accuracy can be determined depending on the quality and size of the experimental datasets. The approaches to generate candidates for virtual screening are also extremely varied and their relative strengths and weaknesses are discussed. The analysis of high-throughput virtual screening is almost never limited to the identification of top candidates and often new patterns and structure-property relations are the most interesting findings of such searches. The review reveals a very dynamic field constantly adapting to match an evolving landscape of applications, methodologies and datasets.

The crystalline sponge method: quantum chemical in silico derivation and analysis of guest binding energies

Computational techniques combined with single-crystal structural data provide a means to further analyse MOF-based crystalline sponge complexes.