Quantum-Chemical Characterization of the Properties and Reactivities of Metal–Organic Frameworks

Theoretical Analysis of Coordination Geometries in Transition Metal-Histidine Complexes Using Quantum Chemical Calculations

A theoretical investigation utilizing density functional theory (DFT) calculations was conducted to explore the coordination complexes formed between histidine (His) ligands and various divalent transition metal ions (Mn2+, Fe2+, Co2+, Ni2+, Cu2+, and Zn2+). Conformational exploration of the His ligand was initially performed to assess its stability upon coordination. Both 1:1 and 1:2 of metal-to-ligand complexes were scrutinized to elucidate their structural features and the relative stability of the complexes. This study examined the ability of His to act as a bidentate or tridentate coordinating ligand, along with the differences in coordination geometry when solvent effects were incorporated. The reduced density gradient (RDG) analysis and local electron attachment energy (LEAE) analysis were employed to elucidate the interaction planes and the nucleophilic and electrophilic properties. The electronic properties were analyzed through electrostatic potential (ESP) maps and natural population analysis (NPA) of atomic charge distributions. This computational study provides valuable insights into the diverse coordination modes of His and its interactions with divalent transition metal ions, contributing to a better understanding of the role of this amino acid ligand in the formation of transition metal complexes. The findings can aid in the design and construction of self-assembled structures involving His-metal coordination.

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.

Comprehensive Investigation of Cu2+ Adsorption from Wastewater Using Olive-Waste-Derived Adsorbents: Experimental and Molecular Insights

This study investigates the efficacy of adsorbents from locally sourced olive waste-encompassing olive skins, leaves, and pits, recovered from the initial centrifugation of olives (OWP)-and a composite with sodium alginate (OWPSA) for the removal of Cu2+ ions from synthetic wastewater. Experimental analyses conducted at room temperature, with an initial Cu2+ concentration of 50 mg/L and a solid/liquid ratio of 1 g/L, showed that the removal efficiencies were approximately 79.54% and 94.54% for OWP and OWPSA, respectively, highlighting the positive impact of alginate on adsorption capacity. Utilizing statistical physics isotherm models, particularly the single-layer model coupled to real gas (SLMRG), allowed us to robustly fit the experimental data, providing insights into the adsorption mechanisms. Thermodynamic parameters affirmed the spontaneity and endothermic nature of the processes. Adsorption kinetics were interpreted effectively using the pseudo-second-order (PSO) model. Molecular modeling investigations, including the conductor-like screening model for real solvents (COSMO-RS), density functional theory (DFT), and atom-in-molecule (AIM) analysis, unveiled intricate molecular interactions among the adsorbent components-cellulose, hemicellulose, lignin, and alginate-and the pollutant Cu2+, confirming their physically interactive nature. These findings emphasize the synergistic application of experimental and theoretical approaches, providing a comprehensive understanding of copper adsorption dynamics at the molecular level. This methodology holds promise for unraveling intricate processes across various adsorbent materials in wastewater treatment applications.

Electronic Structure and d-d Spectrum of Metal-Organic Frameworks with Transition-Metal Ions

The electronic structure of metal-organic frameworks (MOFs) containing transition metal (TM) ions represents a significant and largely unresolved computational challenge due to limited solutions to the quantitative description of low-energy excitations in open d-shells. These excitations underpin the magnetic and sensing properties of TM MOFs, including the observed remarkable spin-crossover phenomenon. We introduce the effective Hamiltonian of crystal field approach to study the d-d spectrum of MOFs containing TM ions; this is a hybrid QM/QM method based on the separation of crystal structure into d- and s,p-subsystems treated at different levels of theory. We test the method on model frameworks, carbodiimides, and hydrocyanamides and a series of M-MOF-74 (M = Fe, Co, Ni) and compare the computational predictions to experimental data on magnetic properties and Mössbauer spectra.

Impact of Overpressure on the Deep Shale Pore System-A Case Study of Wufeng-Longmaxi Formations from the Southern Sichuan Basin

This study investigated the effect of overpressure on the deep shale pore system in the Wufeng-Longmaxi Formation (WLF), a well-established shale gas reservoir in the southern Sichuan Basin, China. The Y1 well was drilled to explore deeper overpressured sections of the basin. Organic geochemistry, mineralogy analysis, field emission scanning electron microscopy (FE-SEM), and gas physisorption experiments were conducted to analyze the pore system. Results showed that despite strong compaction, deep organic-rich shale retained large pores. Compared to shallow shale, deep shale had a larger organic porosity with a smaller average pore size, although some pore sizes exceeded those in shallow shale. Nitrogen (N2) adsorption indicated that the abundance of organic matter (OM) affected mesoporous volume and specific surface area (SSA), while carbon dioxide (CO2) adsorption experiments suggested that micropores were not influenced by OM abundance. Comparing calculated pore SSA and volume via gas adsorption of shallower and deep shale samples revealed that, under similar OM abundance, pore SSA was nearly identical, but deep shale had a larger pore volume than shallow shale. The preservation of pores, particularly in deep shale, is attributed to overpressure, which protects against collapse; additionally, generated shale gas during thermal evolution of OM serves as pore support.

Elastic heterogeneity governs asymmetric adsorption-desorption in a soft porous crystal

Metal-organic frameworks (MOFs), which possess a high degree of crystallinity and a large surface area with tunable inorganic nodes and organic linkers, exhibit high stimuli-responsiveness and molecular adsorption selectivity that enable various applications. The adsorption in MOFs changes the crystalline structure and elastic moduli. Thus, the coexistence of adsorbed/desorbed sites makes the host matrices elastically heterogeneous. However, the role of elastic heterogeneity in the adsorption-desorption transition has been overlooked. Here, we show the asymmetric role of elastic heterogeneity in the adsorption-desorption transition. We construct a minimal model incorporating adsorption-induced lattice expansion/contraction and an increase/decrease in the elastic moduli. We find that the transition is hindered by the entropic and energetic effects which become asymmetric in the adsorption process and desorption process, leading to the strong hysteretic nature of the transition. Furthermore, the adsorbed/desorbed sites exhibit spatially heterogeneous domain formation, implying that the domain morphology and interfacial area between adsorbed/desorbed sites can be controlled by elastic heterogeneity. Our results provide a theoretical guideline for designing soft porous crystals with tunable adsorption hysteresis and the dispersion and domain morphology of adsorbates using elastic heterogeneity.

Challenges in modelling dynamic processes in realistic nanostructured materials at operating conditions

The question is addressed in how far current modelling strategies are capable of modelling dynamic phenomena in realistic nanostructured materials at operating conditions. Nanostructured materials used in applications are far from perfect; they possess a broad range of heterogeneities in space and time extending over several orders of magnitude. Spatial heterogeneities from the subnanometre to the micrometre scale in crystal particles with a finite size and specific morphology, impact the material's dynamics. Furthermore, the material's functional behaviour is largely determined by the operating conditions. Currently, there exists a huge length-time scale gap between attainable theoretical length-time scales and experimentally relevant scales. Within this perspective, three key challenges are highlighted within the molecular modelling chain to bridge this length-time scale gap. Methods are needed that enable (i) building structural models for realistic crystal particles having mesoscale dimensions with isolated defects, correlated nanoregions, mesoporosity, internal and external surfaces; (ii) the evaluation of interatomic forces with quantum mechanical accuracy albeit at much lower computational cost than the currently used density functional theory methods and (iii) derivation of the kinetics of phenomena taking place in a multi-length-time scale window to obtain an overall view of the dynamics of the process. This article is part of a discussion meeting issue 'Supercomputing simulations of advanced materials'.

Computational Insights into the Mechanism of Nitric Oxide Generation from S-Nitrosoglutathione Catalyzed by a Copper Metal-Organic Framework

The controlled generation of nitric oxide (NO) from endogenous sources, such as S-nitrosoglutathione (GSNO), has significant implications for biomedical implants due to the vasodilatory and other beneficial properties of NO. The water-stable metal-organic framework (MOF) Cu-1,3,5-tris[1H-1,2,3-triazol-5-yl]benzene has been shown to catalyze the production of NO and glutathione disulfide (GSSG) from GSNO in aqueous solution as well as in blood. Previous experimental work provided kinetic data for the catalysis of the 2GSNO → 2NO + GSSG reaction, leading to various proposed mechanisms. Herein, this catalytic process is examined using density functional theory. Minimal functional models of the Cu-MOF cluster and glutathione moieties are established, and three distinct catalytic mechanisms are explored. The most thermodynamically favorable mechanism studied is consistent with prior experimental findings. This mechanism involves coordination of GSNO to copper via sulfur rather than nitrogen and requires a reductive elimination that produces a Cu(I) intermediate, implicating a redox-active copper site. The experimentally observed inhibition of reactivity at high pH values is explained in terms of deprotonation of a triazole linker, which decreases the structural stability of the Cu(I) intermediate. These fundamental mechanistic insights may be generally applicable to other MOF catalysts for NO generation.

A Review of Molecular Models for Gas Adsorption in Shale Nanopores and Experimental Characterization of Shale Properties

Shale gas, as a promising alternative energy source, has received considerable attention because of its broad resource base and wide distribution. The establishment of shale models that can accurately describe the composition and structure of shale is essential to perform molecular simulations of gas adsorption in shale reservoirs. This Review provides an overview of shale models, which include organic matter models, inorganic mineral models, and composite shale models. Molecular simulations of gas adsorption performed on these models are also reviewed to provide a more comprehensive understanding of the behaviors and mechanisms of gas adsorption on shales. To accurately understand the gas adsorption behaviors in shale reservoirs, it is necessary to be aware of the pore structure characteristics of shale reservoirs. Thus, we also present experimental studies on shale microstructure analysis, including direct imaging methods and indirect measurements. The advantages, disadvantages, and applications of these methods are also well summarized. This Review is useful for understanding molecular models of gas adsorption in shales and provides guidance for selecting experimental characterization of shale structure and composition.

CO Inversion on a NaCl(100) Surface: A Multireference Quantum Embedding Study

We develop a multireference quantum embedding model to investigate a recent experimental observation of the isomerization of vibrationally excited CO molecules on a NaCl(100) surface [Science 2020, 367, 175-178]. To explore this mechanism, we built a reduced potential energy surface of CO interacting with NaCl(100) using a second-order multireference perturbation theory, modeling the adsorbate-surface interaction with our previously developed active space embedding theory (ASET). We considered an isolated CO molecule on NaCl(100) and a high-coverage CO monolayer (1/1), and for both we generated potential energy surfaces parametrized by the CO stretching, adsorption, and inversion coordinates. These surfaces are used to determine stationary points and adsorption energies and to perform a vibrational analysis of the states relevant to the inversion mechanism. We found that for near-equilibrium bond lengths, CO adsorbed in the C-down configuration is lower in energy than in the O-down configuration. Stretching of the C-O bond reverses the energetic order of these configurations, supporting the accepted isomerization mechanism. The vibrational constants obtained from these potential energy surfaces show a small (< 10 cm^-1) blue- and red-shift for the C-down and O-down configurations, respectively, in agreement with experimental assignments and previous theoretical studies. Our vibrational analysis of the monolayer case suggests that the O-down configuration is energetically more stable than the C-down one beyond the 16th vibrational excited state of CO, a value slightly smaller than the one from quasi-classical trajectory simulations (22nd) and consistent with the experiment. Our analysis suggests that CO-CO interactions in the monolayer play an important role in stabilizing highly vibrationally excited states in the O-down configuration and reducing the barrier between the C-down and O-down geometries, therefore playing a crucial role in the inversion mechanism.

Preparation and photocatalytic performance of UIO-66/La-MOF composite

To improve the photocatalytic degradation efficiency of photocatalytic materials UIO-66 and La-MOFs under visible-light irradiation, a series of photocatalytic materials with La and Zr as metal centers and terephthalic acid (H₂BDC) and 2-amino terephthalic acid (H₂ATA) as organic ligands were prepared by solvothermal method. The photocatalytic materials were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), UV-visible (UV-vis) spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, and Mott-Schottky test. The photocatalytic degradation performance to Rhodamine B of the catalysts was fully investigated. Results show that the H₂ATA series had stronger visible-light absorption capacity and better photocatalytic performance. The 0.35 La/Zr-H₂ATA composite showed the best photocatalytic degradation. The quenching experiments confirmed that the active species in the photocatalytic degradation were the holes and superoxide radicals. The possible mechanisms of the carrier migration paths in the energy level matching for La/Zr-H₂BDC and La/Zr-H₂ATA were also discussed in detail.

Synergistic Effects in the Activity of Nano-Transition-Metal Clusters Pt12M (M = Ir, Ru or Rh) for NO Dissociation

The dissociation of environmentally hazardous NO through dissociative adsorption on metallic clusters supported by oxides, is receiving growing attention. Building on previous research on monometallic M 13  clusters [J. Phys. Chem. C, 2019, 123(33), 20314-20318], this work considers bimetallic Pt 12 M (M = Rh, Ru or Ir) clusters. The adsorption energy and activation energy of NO dissociation on the clusters have been calculated in vacuum using Koh,-Sham DFT, while their trends were rationalized using reactivity indices such as molecular electrostatic potential and global Fermi softness. The results shown that doping of the Pt clusters lowered the adsorption energy as well as the activation energy for NO dissociation. Furthermore, reactivity indices were calculated as a first estimate of the performance of the clusters in realistic amorphous silica pores (MCM-41) through  ab initio  molecular dynamics simulations.

Combined Deep Learning and Classical Potential Approach for Modeling Diffusion in UiO-66

Modeling of diffusion of adsorbates through porous materials with atomistic molecular dynamics (MD) can be a challenging task if the flexibility of the adsorbent needs to be included. This is because potentials need to be developed that accurately account for the motion of the adsorbent in response to the presence of adsorbate molecules. In this work, we show that it is possible to use accurate machine learning atomistic potentials for metal-organic frameworks in concert with classical potentials for adsorbates to accurately compute diffusivities though a hybrid potential approach. As a proof-of-concept, we have developed an accurate deep learning potential (DP) for UiO-66, a metal-organic framework, and used this DP to perform hybrid potential simulations, modeling diffusion of neon and xenon through the crystal. The adsorbate-adsorbate interactions were modeled with Lennard-Jones (LJ) potentials, the adsorbent-adsorbent interactions were described by the DP, and the adsorbent-adsorbate interactions used LJ cross-interactions. Thus, our hybrid potential allows for adsorbent-adsorbate interactions with classical potentials but models the response of the adsorbent to the presence of the adsorbate through near-DFT accuracy DPs. This hybrid approach does not require refitting the DP for new adsorbates. We calculated self-diffusion coefficients for Ne in UiO-66 from DFT-MD, our hybrid DP/LJ approach, and from two different classical potentials for UiO-66. Our DP/LJ results are in excellent agreement with DFT-MD. We modeled diffusion of Xe in UiO-66 with DP/LJ and a classical potential. Diffusion of Xe in UiO-66 is about a factor of 30 slower than that of Ne, so it is not computationally feasible to compute Xe diffusion with DFT-MD. Our hybrid DP-classical potential approach can be applied to other MOFs and other adsorbates, making it possible to use an accurate DP generated from DFT simulations of an empty adsorbent in concert with existing classical potentials for adsorbates to model adsorption and diffusion within the porous material, including adsorbate-induced changes to the framework.

High-Throughput Computational Exploration of MOFs with Open Cu Sites for Adsorptive Separation of Hydrogen Isotopes

Effective separation of hydrogen isotopes still remains one of the extremely challenging tasks in industry. Compared to the present methods that are energy- and cost-intensive, quantum sieving technology based on nanostructured materials offers a more efficient alternative approach, where metal-organic frameworks (MOFs) featuring open metal sites (OMS) can serve as an ideal platform. Herein, a combination of periodic density functional theory (DFT) with dispersive correction and high-throughput molecular simulation was employed from thermodynamic viewpoints to explore the D₂/H₂ separation properties of 929 experimental MOFs bearing a copper-paddlewheel unit. The DFT calculations showed that there is a negligible rotational energy barrier for the molecule adsorbed at the OMS, and the movement of the Cu atoms along the Cu-Cu axis vector almost has no influence on the interaction energy. On the basis of the DFT results, a new force field with a proposed cutoff scheme was developed to accurately describe the strong isotope-OMS interaction. Under practical conditions (40 K and 1.0 bar), large-scale computational material screening demonstrated that the OMS interaction plays a more important role in highly selective materials and ignoring such interactions can lead to completely wrong identification of the most promising materials. Using the adsorption selectivity and adsorbent performance score as evaluation metrics, this work demonstrated that the materials with sql topology notably outperform many benchmark adsorbents reported so far.

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.

Unlocking the computational design of metal-organic cages

Metal-organic cages are macrocyclic structures that can possess an intrinsic void that can hold molecules for encapsulation, adsorption, sensing, and catalysis applications. As metal-organic cages may be comprised from nearly any combination of organic and metal-containing components, cages can form with diverse shapes and sizes, allowing for tuning toward targeted properties. Therefore, their near-infinite design space is almost impossible to explore through experimentation alone and computational design can play a crucial role in exploring new systems. Although high-throughput computational design and screening workflows have long been known as powerful tools in drug and materials discovery, their application in exploring metal-organic cages is more recent. We show examples of structure prediction and host-guest/catalytic property evaluation of metal-organic cages. These examples are facilitated by advances in methods that handle metal-containing systems with improved accuracy and are the beginning of the development of automated cage design workflows. We finally outline a scope for how high-throughput computational methods can assist and drive experimental decisions as the field pushes toward functional and complex metal-organic cages. In particular, we highlight the importance of considering realistic, flexible systems.

Second-Order Active-Space Embedding Theory

Quantum embedding schemes are a promising way to extend multireference computations to large molecules with strong correlation effects localized on a small number of atoms. This work introduces a second-order active-space embedding theory [ASET(2)] which improves upon mean-field frozen embedding by treating fragment-environment interactions via an approximate canonical transformation. The canonical transformation employed in ASET(2) is formulated using the driven similarity renormalization group. The ASET(2) scheme is benchmarked on the N═N bond dissociation in pentyldiazene, the S₀ to S₁ excitation in 1-octene, and the interaction energy of the O₂-benzene complex. The ASET(2) explicit treatment of fragment-environment interactions beyond the mean-field level generally improves the accuracy of embedded computations, and it becomes necessary to achieve an accurate description of excitation energies of 1-octene and the singlet-triplet gap of the O₂-benzene complex.

Redox Hyperactive MOF for Li+, Na+ and Mg2+ Storage

To create both greener and high-power metal-ion batteries, it is of prime importance to invent an unprecedented electrode material that will be able to store a colossal amount of charge carriers by a redox mechanism. Employing periodic DFT calculations, we modeled a new metal-organic framework, which displays energy density exceeding that of conventional inorganic and organic electrodes, such as Li- and Na-rich oxides and anthraquinones. The designed MOF has a rhombohedral unit cell in which an Ni(II) node is coordinated by 2,5-dicyano-p-benzoquinone linkers in such a way that all components participate in the redox reaction upon lithiation, sodiation and magnesiation. The spatial and electronic changes occurring in the MOF after the interaction with Li, Na and Mg are discussed on the basis of calculated electrode potentials versus Li⁰/Li⁺, Na⁰/Na⁺ and Mg⁰/Mg²⁺, respectively. In addition, the specific capacities and energy densities are calculated and used as a measure for the electrode applicability of the designed material. Although the highest capacity and energy density are predicted for Li storage, the greater structural robustness toward Na and Mg uptake suggests a higher cycling stability in addition to lower cost. The theoretical results indicate that the MOF is a promising choice for a green electrode material (with <10% heavy metal content) and is well worth experimental testing.

Performance of GFN1-xTB for periodic optimization of Metal Organic Frameworks

Tight-binding approaches bridge the gap between force field methods and Density Functional Theory (DFT). Density Functional Tight Binding (DFTB) has been employed for a wide range of systems containing up...

β-Cyclodextrin-functionalized graphene and metal–organic framework composites for ultrasensitive electrochemical detection of chloramphenicol

Novel β-CD@functionalized graphene /Cu-BTC composites were in situ prepared using β-CD functionalized graphene and Cu-BTC, and a new electrochemical sensor for sensitive detection of chloramphenicol was developed based on the composites.

Parametrization of Nonbonded Force Field Terms for Metal-Organic Frameworks Using Machine Learning Approach

The enormous structural and chemical diversity of metal-organic frameworks (MOFs) forces researchers to actively use simulation techniques as often as experiments. MOFs are widely known for their outstanding adsorption properties, so a precise description of the host-guest interactions is essential for high-throughput screening aimed at ranking the most promising candidates. However, highly accurate ab initio calculations cannot be routinely applied to model thousands of structures due to the demanding computational costs. Furthermore, methods based on force field (FF) parametrization suffer from low transferability. To resolve this accuracy-efficiency dilemma, we applied a machine learning (ML) approach: extreme gradient boosting. The trained models reproduced the atom-in-material quantities, including partial charges, polarizabilities, dispersion coefficients, quantum Drude oscillator, and electron cloud parameters, with accuracy similar to the reference data set. The aforementioned FF precursors make it possible to thoroughly describe noncovalent interactions typical for MOF-adsorbate systems: electrostatic, dispersion, polarization, and short-range repulsion. The presented approach can also readily facilitate hybrid atomistic simulation/ML workflows.

Concluding remarks: current and next generation MOFs

This paper describes the content of my "Concluding remarks" talk at the Faraday Discussion meeting on "MOFs for energy and the environment" (online, 23-25 June 2021). The panel consisted of sessions on the design of MOFs and MOF hybrids (synthetic chemistry), their applications (e.g., capture, storage, separation, electrical devices, photocatalysis), advanced characterization (e.g., transmission electron microscopy, solid-state nuclear magnetic resonance), theory and modeling, and commercialization. MOF chemistry is undergoing a significant evolution from simply network chemistry to the chemistry of synergistic integration with heterogeneous materials involving other disciplines (we call this the fourth generation type). As reflected in the papers of the invited speakers and discussions with the participants, the present and future of this field will be described in detail.

Synthesis of nanocellulose aerogels and Cu-BTC/nanocellulose aerogel composites for adsorption of organic dyes and heavy metal ions

MOFs compounds with open metal sites, particularly Cu-BTC, have great potential for adsorption and catalysis applications. However, the powdery morphology limits their applications. One of the almost new ways to overcome this problem is to trap them in a standing and flexible aerogel matrix to form a hierarchical porous composite. In this work, Cu-BTC/CNC (crystalline nanocellulose) and Cu-BTC/NFC (nanofibrillated cellulose) aerogel composites were synthesized using a direct mixing method by the addition of Cu-BTC powder to the liquid precursor solution followed by gelation and freeze-drying. Also, pure nanocellulose aerogels (CNC and NFC aerogels) have been synthesized from cellulose isolated from peanut shells. Scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectra, and X-ray diffraction (XRD) were utilized to evaluate the structure and morphology of the prepared materials. The adsorption ability of pure CNC aerogel and Cu-BTC/NFC aerogel composite for organic dye (Congo Red) and heavy metal ion (Mn⁷⁺) was studied and determined by the UV-Vis spectrophotometry and inductively-coupled plasma optical emission spectrometry (ICP-OES), respectively. It was concluded that Cu-BTC/NFC aerogel composite shows excellent adsorption capacity for Congo Red. The adsorption process of this composite is better described by the pseudo-second-order kinetic model and Langmuir isotherm, with a maximum monolayer adsorption capacity of 39 mg/g for Congo Red. Nevertheless, CNC aerogel shows no adsorption for Congo Red. Both CNC aerogel and Cu-BTC/NFC aerogel composite act as a monolith standing solid reducer, which means they could remove permanganate ions from water by reducing it into manganese dioxide without releasing any secondary product in the solution.

Complexes of Platinum Group Metals with a Conformationally Locked Scorpionate in a Metal-Organic Framework: An Unusually Close Apical Interaction of Palladium(II)

We report synthetic strategies for installing platinum group metals (PGMs: Pd, Rh, Ir, and Pt) on a scorpionate-derived linker (TpmC*) within a metal-organic framework (MOF), both by room-temperature postsynthetic metalation and by direct solvothermal synthesis, with a wide range of metal loadings relevant for fundamental studies and catalysis. In-depth studies for the palladium adduct Pd(II)@Zr-TpmC* by density-functional-theory-assisted extended X-ray absorption fine structure spectroscopy reveals that the rigid MOF lattice enforces a close Pd(II)-N_apical interaction between the bidentate palladium complex and the third uncoordinated pyrazole arm of the TpmC* ligand (Pd-N_apical = 2.501 ± 0.067 Å), an interaction that is wholly avoided in molecular palladium scorpionates.

A more effective catalysis of the CO2 fixation with aziridines: computational screening of metal-substituted HKUST-1

A vital issue for the fixation and conversion of CO₂ into useful chemical products is to find effective catalysts. In this work, in order to develop more effective and diverse catalysts, we implemented the first computational screening study (at M06-2X//B3LYP level) on the cycloaddition of CO₂ with aziridines under eighteen metal-substituted HKUST-1 MOFs and tetrabutylammonium bromide (TBAB) as a co-catalyst. For all considered catalytic systems, the ring-opening of aziridine is calculated to be the rate-determining step. Up to 11 M-HKUST-1 systems, i.e., Rh (31.87 kcal mol^-1), Y (31.02), Sc (30.50), V (30.02), Tc (29.90), Cd (29.80), Ti (29.32), Mn (29.05), Zn (28.29), Fe (27.85) and Zr (25.09), possess lower ring-opening barrier heights than the original Cu-HKUST-1 (32.90), indicative of their superior catalytic ability to the original Cu-HKUST-1 in theory. With the lowest ring-opening barrier, Zr-HKUST-1 is strongly advocated for future synthetic and catalytic studies.

Porous MoWN/MoWC@NC Nano-octahedrons synthesized via confined carburization and vapor deposition in MOFs as efficient trifunctional electrocatalysts for oxygen reversible catalysis and hydrogen production in the same electrolyte

We used a simple MOFs-assisted synthesis strategy based on the encapsulation and in-situ carburizing reaction of Cu-based metallic organic frameworks (NENU-5) to synthesize porous nano-octahedral materials, MoWN/MoWC@NCTs (T = 700, 800, and 900). Together with the vapor deposition strategy, the volatile nitrogen species from the pyrolysis of dicyandiamide were captured by the nano-octahedral materials, and formed tungsten-molybdenum-based carbonitride nanocrystals encapsulated in nitrogen-doped carbon. The porous nano-octahedron has a unique heterostructure composed of Mo₂N/MoC/W₂N/WC. The representative MoWN/MoWC@NC800 showed trifunctional electrocatalytic activity in oxygen reduction reaction/oxygen evolution reaction/hydrogen evolution reaction (ORR/OER/HER) in an alkaline medium (0.1 M KOH). The total oxygen electrode activity index ΔE = 0.795 V (vs. RHE) was found in OER/ORR, and the material also exhibits excellent HER performance. The minimum potential of -0.17 V (vs. RHE) was provided at a current density of -10 mA cm^-2. MoWN/MoWC@NC800 showed excellent cycle stability and durability in ORR/OER/HER with the same electrolyte (0.1 M KOH). More importantly, MoWN/MoWC@NC800 could be used to construct high-performance zinc-air batteries and sued for driving electrocatalytic water splitting in a self-powered manner. The successful preparation of the materials indicate that the synthetic strategy provides new reference ideas for developing functional materials with high catalytic properties for various applications.

Incorporation of Al3+ Sites on Brønsted Acid Metal-Organic Frameworks for Glucose-to-Hydroxylmethylfurfural Transformation

5-hydroxylmethylfurfural (HMF) is a bio-based chemical that can be prepared from natural abundant glucose by using combined Brønsted-Lewis acid catalysts. In this work, Al³⁺ catalytic site has been grafted on Brønsted metal-organic frameworks (MOFs) to enhance Brønsted-Lewis acidity of MOF catalysts for a one-pot glucose-to-HMF transformation. The uniform porous structure of zirconium-based MOFs allows the optimization of both acid strength and density of acid sites in MOF-based catalysts by incorporating the desired amount of Al³⁺ catalytic sites at the organic linker. Al³⁺ sites generated via a post-synthetic modification act as Lewis acid sites located adjacent to the Brønsted sulfonated sites of MOF structure. The local structure of the Al³⁺ sites incorporated in MOFs has been elucidated by X-ray absorption near-edge structure (XANES) combined with density functional theory (DFT) calculations. The cooperative effect from Brønsted and Lewis acids located in close proximity and the high acid density is demonstrated as an important factor to achieve high yield of HMF.

Strongly Bound Excitons in Metal-Organic Framework MOF-5: A Many-Body Perturbation Theory Study

During the past years, one of the most iconic metal-organic frameworks (MOFs), MOF-5, has been characterized as a semiconductor by theory and experiments. Here we employ the GW many-body perturbation theory in conjunction with the Bethe-Salpeter equation to compute the electronic structure and optical properties of this MOF. The GW calculations show that MOF-5 is a wide-band-gap insulator with a fundamental gap of ∼8 eV. The strong excitonic effects, arising from highly localized states and low screening, result in an optical gap of 4.5 eV and in an optical absorption spectrum in excellent agreement with experiments. The origin of the incorrect conclusion reported by past studies and the implication of this result are also discussed.

Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks

Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an end-to-end machine learning model that automatically generates descriptors that capture a complex representation of a material’s structure and chemistry. This approach builds on computational topology techniques (namely, persistent homology) and word embeddings from natural language processing. It automatically encapsulates geometric and chemical information directly from the material system. We demonstrate our approach on multiple nanoporous metal–organic framework datasets by predicting methane and carbon dioxide adsorption across different conditions. Our results show considerable improvement in both accuracy and transferability across targets compared to models constructed from the commonly-used, manually-curated features, consistently achieving an average 25–30% decrease in root-mean-squared-deviation and an average increase of 40–50% in R² scores. A key advantage of our approach is interpretability: Our model identifies the pores that correlate best to adsorption at different pressures, which contributes to understanding atomic-level structure–property relationships for materials design.

Spectroscopic Evidence of Hyponitrite Radical Intermediate in NO Disproportionation at a MOF-Supported Mononuclear Copper Site

Dianionic hyponitrite (N₂ O₂ ^2- ) is often proposed, based on model complexes, as the key intermediate in reductive coupling of nitric oxide to nitrous oxide at the bimetallic active sites of heme-copper oxidases and nitric oxide reductases. In this work, we examine the gas-solid reaction of nitric oxide with the metal-organic framework Cu^I -ZrTpmC* with a suite of in situ spectroscopies and density functional theory simulations, and identify an unusual chelating N₂ O₂ ^.- intermediate. These results highlight the advantage provided by site-isolation in metal-organic frameworks (MOFs) for studying important reaction intermediates, and provide a mechanistic scenario compatible with the proposed one-electron couple in these enzymes.

The Effect of Auxiliary Nitrogenated Linkers on the Design of New Cadmium-Based Coordination Polymers as Sensors for the Detection of Explosive Materials

Three new cadmium-based coordination polymers, denoted [Cd(hfipbb)(4,4'-bipy)] (CdPF-1), [Cd(hfipbb)(2,2'-bipy)] (CdPF-2), and [Cd(hfipbb)(1,10-phen)] (CdPF-3), have been hydrothermally synthesized by using the well-known V-shaped organic linker 4,4'-(hexafluoroisopropylidene)bis(benzoic acid) (H₂ hfipbb), together with different nitrogenated auxiliary linkers. Considering the d¹⁰ configuration of the transition metal selected, the luminescent properties for these CdPF-n materials were explored, finding that materials CdPF-2 and CdPF-3 act as excellent sensors in the detection of explosive nitro aromatic compounds. The photoluminescence properties of CdPF-2 and CdPF-3 revealed that significant and sensitive fluorescence quenching was observed toward NP (nitrophenol) for CdPF-2 and PA (picric acid) for CdPF-3 in MeOH suspensions.

Dual Intrareticular Oxidation of Mixed-Ligand Metal-Organic Frameworks for Stepwise Electrochemiluminescence

This work presents a mixed-ligand metal-organic framework (m-MOF) integrated with two ligands, one as a luminophore and the other as a coreactant, on one metal node for self-enhanced electrochemiluminescence (ECL). Both 9,10-di(p-carboxyphenyl)anthracene (DPA) and 1,4-diazabicyclo[2.2.2]octane (D-H₂) ligands can be oxidized, generating the cation radicals DPA^+• and D-H₂^+•, respectively. The latter can be deprotonated to form the neutral radical (D-H^•) and then react with DPA^+• to produce excited DPA* for ECL emission without exogenous coreactants. As a result of the incorporation into the MOF framework and the intrareticular charge transfer between the two ligands, the ECL intensity of the m-MOF was increased 26.5-fold compared with that of the mixture of DPA and D-H₂ in aqueous solution. Moreover, with the process of second oxidation of D-H₂, stepwise ECL emission was observed as a result of local excitation in the DPA unit, which was identified through density functional theory calculations. Overall, the implementation of the mixed-ligand approach, which combines the luminophore and coreactant as linkers in reticular materials, enriches the fundamentals and applications of ECL systems.

New immunoprobe: Dual-labeling ZIF-8 embellished with multifunctional bovine serum albumin lamella for electrochemical immunoassay of tumor marker

A new immunoprobe, which can initiate the sedimentation of Ag nanoparticles (NPs) on an electrode surface, was developed for the electrochemical detection of carbohydrate antigen 72-4 (CA 72-4). To design the immunoprobe, zeolitic imidazolate frameworks (ZIFs) were employed as the carrier to enrich thionine molecules, then bovine serum albumin (BSA) was modified on the electrode surface. Advantageously, BSA, served as an anchor to further attach the labeling antibodies (Ab₂) and alkaline phosphatase (ALP) to also be modified on the surface through covalent bonding. To construct the immunosensor, multiwalled carbon nanotube-graphene oxide composites were employed to provide active sites, and the electrodeposited Au NPs were used to immobilize coating antibodies. In the presence of CA 72-4, a sandwich immunosensor was established, and a cascade reaction was initiated to deposit Ag NPs under the catalysis, which can further improve the conductivity of electrode interface. Under the optimal conditions, the immunosensor displayed excellent performance with a wide linear range from 1 μU mL^-1 to 10 U mL^-1 and an ultralow detection limit of 0.438 μU mL^-1 (S/N = 3).

A new release of MOPAC incorporating the INDO/S semiempirical model with CI excited states

The semiempirical INDO/S Hamiltonian is incorporated into a new release of MOPAC2016. The MOPAC2016 software package has long been at the forefront of semiempirical quantum chemical methods (SEQMs) for small molecules, proteins, and solids and until this release has included only NDDO-type SEQMs. The new code enables the calculation of excited states using the INDO/S Hamiltonian combined with a configuration interaction (CI) approach using single excitations (CIS), single and double excitations (CISD), or multiple reference determinants (MRCI) where reference determinants are generated using a complete active space (CAS) approach. The capacity to perform excited-state calculations beyond the CIS level makes INDO/CI one of the few low-cost computational methods capable of accurately modeling states with substantial double-excitation character. Solvent corrections to the ground-state and excited-state energies can be computed using the COSMO implicit solvent model, incorporating state-specific corrections to the excited states based on the solvent refractive index. This code produces physically reasonable electronic structures, absorption spectra, and solvatochromic shifts at low computational costs for systems up to hundreds of atoms, and for both organic molecules and metal clusters.

The micromechanical model to computationally investigate cooperative and correlated phenomena in metal-organic frameworks

Computational insight into the impact of cooperative phenomena and correlated spatial disorder on the macroscopic behaviour of metal-organic frameworks (MOFs) is essential in order to consciously engineer these phenomena for targeted applications. However, the spatial extent of these effects, ranging over hundreds of nanometres, limits the applicability of current state-of-the-art computational tools in this field. To obtain a fundamental understanding of these long-range effects, the micromechanical model is introduced here. This model overcomes the challenges associated with conventional coarse-graining techniques by exploiting the natural partitioning of a MOF material into unit cells. By adopting the elastic deformation energy as the central quantity, the micromechanical model hierarchically builds on experimentally accessible input parameters that are obtained from atomistic quantum mechanical or force field simulations. As a result, the here derived micromechanical equations of motion can be adopted to shed light on the effect of long-range cooperative phenomena and correlated spatial disorder on the performance of mesoscale MOF materials.

Analytical Approach to Screen Semiconducting MOFs Using Bloch Mode Analysis and Spectroscopic Measurements

A rapid and simple analytical approach is developed to screen the semiconducting properties of metal organic frameworks (MOFs) by modeling the band structure and predicting the density of state of isoreticular MOFs (IRMOFs). One can consider the periodic arrangement of metal nodes linked by organic subunits as a 1D periodic array crystal model, which can be aligned with any unit-cell axis included in the IRMOF's primitive cubic lattice. In such a structure, each valence electron of a metal atom feels the potential field of the entire periodic array. We allocate the 1D periodic array in a crystal unit cell to three IRMOFs-n (n = 1, 8, and 10) of the Zn₄O(L)₃ IRMOF series and apply the model to their crystal lattices with unit-cell constants a = 25.66, 30.09, and 34.28 Å, respectively. By solving Schrödinger's equation with a Kronig-Penney periodic potential and fitting the computed energy spectra to IRMOFs' experimental spectroscopic data, we model electronic band structures and obtain densities of state. The band diagram of each IRMOF reveals the nature of its electronic structures and density of state, allowing one to identify its n- or p-type semiconducting behavior. This novel analytical approach serves as a predictive and rapid screening tool to search the MOF database to identify potential semiconducting MOFs.

Defects as catalytic sites for the oxygen evolution reaction in Earth-abundant MOF-74 revealed by DFT

The oxygen evolution reaction (OER) is the bottleneck of hydrogen production via water splitting and understanding electrocatalysts at atomic level becomes paramount to enhance the efficiency of this process.

Influence of linkers on the Kuratowski-type secondary building unit in nickel single-site MOFs for ethylene oligomerization catalysis: a computational study

Ni-Kuratowski-type MOFs were studied computationally for ethylene oligomerization and the catalytic performance of sterically different linkers was elucidated.

Indirect differential pulse voltammetric analysis of cyanide at porous copper based metal organic framework modified carbon paste electrode: Application to different water samples

Carbon paste electrode (CPE) modified with porous copper based metal organic framework (Cu-MOF) nanocomposite is described for analysis of cyanide (CN^-) for the first time. The electrochemical performance of the proposed electrode was investigated by differential pulse voltammetry (DPV), electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The Cu-MOF nanocomposite was characterized using scanning electron microscope (SEM), N₂-adsorption-desorption isotherms, powder X-ray powder diffraction (PXRD), Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis (TGA). Under optimal conditions of measurements, the anodic peak (Ipa) decreases linearly in the range of 1.87-25 μM with LOD of 0.60 μM (at S/N = 3). The Cu-MOF/CPE showed good selectivity towards CN^- measurement with no significant interference in pH 7.0 using 0.25 M KCl to increase the medium conductivity and to stabilize the analyte and prevents its volatility. Moreover, the method was successfully applied for determination of CN^- in different environmental water samples.