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At least 829 records · Page 46

Toward Metal–Organic Framework-Based Solar Cells: Enhancing Directional Exciton Transport by Collapsing Three-Dimensional Film Structures

Owing to their ability to act as light-harvesting scaffolds, porphyrin-containing metal-organic frameworks (MOFs) are in the forefront of research on the application of highly ordered molecular materials to problems in solar-energy conversion. In this work, solvent-assisted linker exchange (SALE) is performed on a pillared paddlewheel porphyrin containing MOF thin film to collapse a 3D framework to a 2D framework. The change in dimensionality of the framework is confirmed by a decrease in the film thickness, the magnitude of which is in agreement with crystallographic parameters for related bulk materials. Furthermore, NMR spectroscopy performed on the digested sample suggests a similar change in geometry is achieved in bulk MOF samples. The decreased distance between the porphyrin chromophores in the 2D MOF film compared to the 3D film results in enhanced energy transfer through the film. The extent of energy transport was probed by assembling MOF thin film where the outermost layers are palladium porphyrin (P2) units, which act as energy traps and fluorescence quenchers. Steady-state emission spectroscopy together with time-resolved emission spectroscopy indicates that excitons can travel through about 9-11 layers (porphyrin layers) in 2D films, whereas in 3D films energy transfer occurs through no more than about 6-8 layers. The results are difficult to understand if only changes in MOF interlayer spacing are considered but become much more understandable if dipole-dipole coupling distances are considered.

Goswami, Subhadip↗

Molecular Retrofitting Adapts a Metal–Organic Framework to Extreme Pressure

Despite numerous studies on chemical and thermal stability of metal-organic frameworks (MOFs), mechanical stability remains largely undeveloped. No strategy exists to control the mechanical deformation of MOFs under ultrahigh pressure, to date. We show that the mechanically unstable MOF-520 can be retrofitted by precise placement of a rigid 4,4'-biphenyldicarboxylate (BPDC) linker as a "girder" to afford a mechanically robust framework: MOF-520-BPDC. This retrofitting alters how the structure deforms under ultrahigh pressure and thus leads to a drastic enhancement of its mechanical robustness. While in the parent MOF-520 the pressure transmitting medium molecules diffuse into the pore and expand the structure from the inside upon compression, the girder in the new retrofitted MOF-520-BPDC prevents the framework from expansion by linking two adjacent secondary building units together. As a result, the modified MOF is stable under hydrostatic compression in a diamond-anvil cell up to 5.5 gigapascal. The increased mechanical stability of MOF-520-BPDC prohibits the typical amorphization observed for MOFs in this pressure range. Direct correlation between the orientation of these girders within the framework and its linear strain was estimated, providing new insights for the design of MOFs with optimized mechanical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design of a Metal–Organic Framework with Enhanced Back Bonding for Separation of N 2 and CH 4

Gas separations with porous materials are economically important and provide a unique challenge to fundamental materials design, as adsorbent properties can be altered to achieve selective gas adsorption. Metal–organic frameworks represent a rapidly expanding new class of porous adsorbents with a large range of possibilities for designing materials with desired functionalities. Given the large number of possible framework structures, quantum mechanical computations can provide useful guidance in prioritizing the synthesis of the most useful materials for a given application. Here, we show that such calculations can predict a new metal–organic framework of potential utility for separation of dinitrogen from methane, a particularly challenging separation of critical value for utilizing natural gas. In conclusion, an open V(II) site incorporated into a metal–organic framework can provide a material with a considerably higher enthalpy of adsorption for dinitrogen than for methane, based on strong selective back bonding with the former but not the latter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Buffered Coordination Modulation as a Means of Controlling Crystal Morphology and Molecular Diffusion in an Anisotropic Metal-Organic Framework

We know significant advances have been made in the synthesis of chemically selective environments within metal-organic frameworks, yet materials development and industrial implementation have been hindered by the inability to predictively control crystallite size and shape. One common strategy to control crystal growth is the inclusion of coordination modulators, which are molecular species designed to compete with the linker for metal coordination during synthesis. However, these modulators can simultaneously alter the pH of the reaction solution, an effect that can also significantly influence crystal morphology. Herein, noncoordinating buffers are used to independently control reaction pH during metal-organic framework synthesis, enabling direct interrogation of the role of the coordinating species on crystal growth. We demonstrate the efficacy of this strategy in the synthesis of low-dispersity single-crystals of the framework Co 2 (dobdc) (dobdc 4- = 2,5-dioxido-1,4-benzenedicarboxylate) in a pH 7-buffered solution using cobalt(II) acetate as the metal source. Density functional theory calculations reveal that acetate competitively binds to Co during crystallization, and by using a series of cobalt(II) salts with carboxylate anions of varying coordination strength, it is possible to control crystal growth along the c -direction. Finally, we use zero length column chromatography to show that crystal morphology has a direct impact on guest diffusional path length for the industrially important hydrocarbon m -xylene. Together, these results provide molecular-level insight into the use of modulators in governing crystallite morphology and a powerful strategy for the control of molecular diffusion rates within metal-organic frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electronic properties of bimetallic metal–organic frameworks (MOFs): Tailoring the density of electronic states through MOF modularity

The development of porous well-defined hybrid materials (e.g., metal-organic frameworks or MOFs) will add a new dimension to a wide number of applications ranging from supercapacitors and electrodes to 'smart' membranes and thermoelectrics. From this perspective, the understanding and tailoring of the electronic properties of MOFs are key fundamental challenges that could unlock the full potential of these materials. In this work, we focused on the fundamental insights responsible for the electronic properties of three distinct classes of bimetallic systems, M x-y M' y -MOFs, M x M' y - MOFs, and M x (ligand-M' y )-MOFs, in which the second metal (M') incorporation occurs through (i) metal (M) replacement in the framework nodes (type I), (ii) metal node extension (type II), and (iii) metal coordination to the organic ligand (type III), respectively. We employed microwave conductivity, X-ray photoelectron spectroscopy, diffuse reflectance spectroscopy, powder X-ray diffraction, inductively coupled plasma atomic emission spectroscopy, pressed-pellet conductivity, and theoretical modeling to shed light on the key factors responsible for the tunability of MOF electronic structures. Experimental prescreening of MOFs was performed based on changes in the density of electronic states near the Fermi edge, which was used as a starting point for further selection of suitable MOFs. As a result, we demonstrated that the tailoring of MOF electronic properties could be performed as a function of metal node engineering, framework topology, and/or the presence of unsaturated metal sites while preserving framework porosity and structural integrity. Finally, these studies unveil the possible pathways for transforming the electronic properties of MOFs from insulating to semiconducting, as well as provide a blueprint for the development of hybrid porous materials with desirable electronic structures.

36 MATERIALS SCIENCE↗

Creating Hierarchical Pores by Controlled Linker Thermolysis in Multivariate Metal–Organic Frameworks

Sufficient pore size, appropriate stability, and hierarchical porosity are three prerequisites for open frameworks designed for drug delivery, enzyme immobilization, and catalysis involving large molecules. In this work, we report a powerful and general strategy, linker thermolysis, to construct ultrastable hierarchically porous metal–organic frameworks (HP-MOFs) with tunable pore size distribution. Linker instability, usually an undesirable trait of MOFs, was exploited to create mesopores by generating crystal defects throughout a microporous MOF crystal via thermolysis. The crystallinity and stability of HP-MOFs remain after thermolabile linkers are selectively removed from multivariate metal–organic frameworks (MTV-MOFs) through a decarboxylation process. A domain-based linker spatial distribution was found to be critical for creating hierarchical pores inside MTV-MOFs. Furthermore, linker thermolysis promotes the formation of ultrasmall metal oxide nanoparticles immobilized in an open framework that exhibits high catalytic activity for Lewis acid-catalyzed reactions. Lastly and most importantly, this work provides fresh insights into the connection between linker apportionment and vacancy distribution, which may shed light on probing the disordered linker apportionment in multivariate systems, a long-standing challenge in the study of MTV-MOFs.

36 MATERIALS SCIENCE↗

Predicting Thermal Performance of an Enhanced Geothermal System From Tracer Tests in a Data Assimilation Framework

Abstract Predicting the thermal performance of an enhanced geothermal system (EGS) requires a comprehensive characterization of the underlying fracture flow patterns from practically available data such as tracer data. However, due to the inherent complexities of subsurface fractures and the generally insufficient geological/geophysical data, interpreting tracer data for fracture flow characterization and thermal prediction remains a challenging task. The present study aims to tackle the challenge by leveraging a data assimilation method to maximize the utilization of information inherently contained in tracer data, and meanwhile maintain the flexibility to handle various uncertainties. A tracer data interpretation framework was proposed with the following three components integrated: (a) We use principal component analysis (PCA) to reduce the dimensionality of model parameter space. (b) We use ES‐MDA (ensemble smoother with multiple data assimilation) to invert for fracture aperture/flow fields and obtain posterior model ensembles for uncertainty quantification. Various data types are assimilated jointly to improve the predictive ability of the posterior ensemble. (c) The inverted fracture aperture fields are then incorporated into reservoir models to predict thermal performance. We developed a field‐scale EGS model to verify the ability of the framework to characterize highly heterogeneous fracture aperture/flow fields and predicting thermal performance. We also applied the framework to a mesoscale field experiment to demonstrate its potential application in real‐world geothermal reservoirs. The results indicate that the proposed framework can effectively retrieve fracture flow information from tracer data for thermal prediction and uncertainty quantification, and thus provide informative guidance for EGS optimization and risk management.

15 GEOTHERMAL ENERGY↗

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 1. Characterizing Thermal–Hydrological–Mechanical Processes

Abstract Bentonite clay is widely used in engineered barrier systems for the permanent disposal of high‐level radioactive waste due to its low permeability, high swelling capacity, and thermal stability. However, the complex thermal‐hydrological‐mechanical (THM) processes induced by heating from decaying radioactive waste and hydration from surrounding rock can lead to heterogeneous changes that are difficult to measure and predict. This study develops an Electrical Resistivity Tomography (ERT)‐based framework for monitoring THM processes, progressing from sample‐scale to bench‐scale tests, to inform field‐scale applications. Sample‐scale tests analyzed small bentonite samples under controlled variations in water content, temperature, and porosity to establish fundamental resistivity relationships. Bench‐scale tests involved larger bentonite columns subjected to heating (up to 200°C) and hydration under controlled pressure, simulating repository conditions. ERT measurements, complemented by X‐ray CT imaging, temperature monitoring, and tracing sensors, revealed coupled THM processes, such as hydration‐induced compression, swelling, and thermal gradients, leading to complex resistivity patterns. The results demonstrate the potential of ERT for capturing THM‐induced resistivity changes, though challenges remain in upscaling and quantitative analysis. This study evaluates laboratory test capabilities and proposes future improvements for understanding THM‐induced resistivity responses. A conceptual framework for ERT implementation in field‐scale monitoring is presented, synthesizing findings from both scales and exploring how ERT data can inform long‐term modeling and reduce prediction uncertainties. Overall, this ERT‐based framework offers a robust method for monitoring bentonite buffers, aiding in early issue detection and supporting the safe long‐term disposal of radioactive waste in geological repositories, while highlighting the need for future development. Plain Language Summary Bentonite clay is crucial in engineered barrier systems (EBS) for containing high‐level radioactive waste due to its ability to absorb water, swell, seal and remain stable under high temperatures. When bentonite absorbs water and heats up from radioactive decay, it experiences complex changes in its physical and mechanical properties. Understanding these changes is important for ensuring the long‐term safety and effectiveness of EBS. This study used Electrical Resistivity Tomography (ERT), a non‐invasive method that measures electrical conductivity to monitor these changes during laboratory experiments. The ERT data revealed significant variations in resistivity corresponding to changes in water content, temperature, and density, providing detailed spatial and temporal insights into the behavior of bentonite. These findings enhance our ability to predict the long‐term performance of bentonite barriers, ensuring the safe containment of radioactive waste. By improving our understanding of bentonite's behavior, this research supports the development of more reliable and effective barrier systems for radioactive waste disposal, protecting the environment and public health. Key Points ERT monitoring was employed to capture resistivity changes in bentonite during controlled heating and hydration experiments, providing insights into THM processes ERT data reveal significant resistivity changes correlated with water content, temperature, and mechanical effects, enhancing the understanding of THM dynamics in bentonite This study explores the potential of the framework for application in field‐scale EBS monitoring, emphasizing the need for integrating additional geophysical methods for comprehensive subsurface imaging

Chen, Hang↗

A Scale‐Adaptive Urban Hydrologic Framework: Incorporating Network‐Level Storm Drainage Pipes Representation

Abstract Below‐ground urban stormwater networks (BUSNs) significantly influence urban flood dynamics, yet their representation at the watershed or larger scales remains challenging. We introduce a scalable urban hydrologic framework that centers on a novel network‐level BUSN representation, balancing the needs for physical basis, parameter parsimony, and computational efficiency. Our framework conceptualizes an urban watershed into four interacting zones: hillslopes (natural), storm‐sewersheds (urban), a sub‐network channel (tributaries), and a main channel. We develop an innovative Graph Theory‐based algorithm to derive network‐level BUSN parameters from publicly available datasets, enabling efficient, scalable parameterization. We demonstrate this framework's applicability at nine representative watersheds in the Houston metropolitan region, USA, with urban imperviousness ranging from 0% to 64% and drainage areas ranging from 24 to 302 . Our model achieves satisfying computational efficiency, completing hourly time step simulations for 18 years in less than 5 sec per watershed on a standard PC. Validation against observed daily streamflow confirms that the model can capture small‐to‐large flood peaks and seasonal and annual water balance over these watersheds. Comparisons with the National Water Model show better performance in predicting flood peaks and overall water balance, underscoring the promises of our new framework for urban hydrologic modeling at large scales. Furthermore, analysis reveals nonlinear relationships between BUSNs' designed capacities and flood reduction effects. Our approach bridges the gap between detailed hydraulic and large‐scale hydrologic models, providing a valuable tool for urban flood prediction and management across broader spatial and temporal scales.

54 ENVIRONMENTAL SCIENCES↗

A ModEx Framework for Watershed Subsurface Investigation With Limited Geophysical Data Using Machine Learning and Hydrologic Modeling

Abstract Subsurface heterogeneity influences watershed hydrology strongly but remains difficult to characterize at catchment scales with sparse and costly field data. Geophysical surveys such as electromagnetic induction (EMI) provide local spatial subsurface images yet scaling them to watershed scales and converting EMI‐derived resistivity into hydraulic properties remains a challenge. We present a Model–Experiment (ModEx) framework that integrates limited EMI data with machine learning (ML) and hydrologic modeling to improve process representation and guide field investigations. Sparse EMI surveys were scaled to the catchment scale using a Random Forest model, and the resulting resistivity fields were combined with nearby borehole constraints to parameterize a hydrologic model. The EMI‐informed hydrological simulations improved predictions of streamflow sustained by subsurface flow and shallow saturation patterns. By combining EMI data and ML with hydrologic modeling, the ModEx framework guides future subsurface surveys, providing a transferable and efficient strategy for data–model integration across diverse watersheds. Plain Language Summary Mapping the underground network of soil and rock that controls water is essential for predicting floods and droughts, but seeing underground is difficult and expensive. We cannot drill everywhere, so scientists use geophysical tools to scan broad areas. There are two key challenges: these geophysical scans are often sparse across the whole watershed, and the geophysical data is hard to translate into water‐related properties. We used artificial intelligence to solve these problems. We taught a computer to find patterns linking the limited geophysical data to the land surface properties. This allowed it to fill in the gaps and create a complete, useful subsurface map for the entire watershed. This new map improves hydrologic simulations, leading to more accurate predictions of water movement in the watershed. It also helps scientists build better models with less data and generates a priority map showing where to measure next, making future investigations more efficient. Key Points Limited EMI scaled with ML improves catchment‐scale subsurface parameterization for hydrologic models The framework integrates hydrologic modeling with limited geophysical data to support subsurface investigation design ModEx framework offers a transferable data–model integration strategy that quantifies and reduces uncertainty guiding watershed studies

Chen, Hang↗

Large-scale 2D heterostructures from hydrogen-bonded organic frameworks and graphene with distinct Dirac and flat bands

The current strategies for building 2D organic-inorganic heterojunctions involve mostly wet-chemistry processes or exfoliation and transfer, leading to interface contaminations, poor crystallizing, or limited size. Here we show a bottom-up procedure to fabricate 2D large-scale heterostructure with clean interface and highly-crystalline sheets. As a prototypical example, a well-ordered hydrogen-bonded organic framework is self-assembled on the highly-oriented-pyrolytic-graphite substrate. The organic framework adopts a honeycomb lattice with faulted/unfaulted halves in a unit cell, resemble to molecular “graphene”. Interestingly, the topmost layer of substrate is self-lifted by organic framework via strong interlayer coupling, to form effectively a floating organic framework/graphene heterostructure. The individual layer of heterostructure inherits its intrinsic property, exhibiting distinct Dirac bands of graphene and narrow bands of organic framework. Our results demonstrate a promising approach to fabricate 2D organic-inorganic heterostructure with large-scale uniformity and highly-crystalline via the self-lifting effect, which is generally applicable to most of van der Waals materials.

36 MATERIALS SCIENCE↗

Creating free standing covalent organic framework membranes by nanocrystal suturing in sol gel solutions

The sol-gel synthesis represents a versatile platform to fabricate ceramic inorganic membranes. However, it is still a grand challenge to push the boundary of sol-gel chemistry towards high-quality organic membrane construction. Herein, a facile and controlled nanocrystal suturing strategy in sol-gel solutions is developed to afford highly crystalline and free-standing covalent organic framework membranes. The key chemistry design lies in deploying tiny threads (1 mol% dual-NH 2 -tail linear polymer) to efficiently suture the highly charged covalent organic framework nanocrystals stabilized and confined in sol-gel solutions, creating a continuous and intact membrane surface. A subsequent treatment heals the sutured covalent organic framework nanocrystals, yielding a free-standing membrane with high crystallinity and ordered pores. The structure evolution and role of the thread linker are elucidated via operando spectroscopy and microscopy. The as-afforded covalent organic framework membranes demonstrate attractive proton transport performance in high temperature and anhydrous fuel cell applications.

36 MATERIALS SCIENCE↗

Mesoporous peptide frameworks engineered from crystallizable collagen-mimetic peptide amphiphiles

The rational design of porous frameworks with tunable pore dimensions and chemical functionalities is a critical step toward their implementation in diverse applications. While traditional porous materials are typically constructed from abiotic components, there is increasing interest in employing biologically derived building blocks (e.g., peptides and proteins) that offer unmatched structural and functional diversity. Here, we report the construction of crystalline mesoporous frameworks that are self-assembled from amphiphilic collagen-mimetic peptides. Comprehensive structural characterization via microscopy, spectroscopy, and computational techniques provides insights into the assembly packing model, in which hexagonally packed channels are interconnected by antiparallel-aligned collagen triple helices via hydrophobic and electrostatic interactions. Lastly, we demonstrate the functional potential of aCMP frameworks through the encapsulation of various molecular guests, including doxorubicin, an anti-cancer drug. Overall, this work establishes a class of mesoporous frameworks, derived from synthetically engineerable peptide conjugates, marking a significant step forward in broadening the architectural scope and application potential of peptide-based materials.

Perez, Anthony R↗

PRISMS-PF: A general framework for phase-field modeling with a matrix-free finite element method

Abstract A new phase-field modeling framework with an emphasis on performance, flexibility, and ease of use is presented. Foremost among the strategies employed to fulfill these objectives are the use of a matrix-free finite element method and a modular, application-centric code structure. This approach is implemented in the new open-source PRISMS-PF framework. Its performance is enabled by the combination of a matrix-free variant of the finite element method with adaptive mesh refinement, explicit time integration, and multilevel parallelism. Benchmark testing with a particle growth problem shows PRISMS-PF with adaptive mesh refinement and higher-order elements to be up to 12 times faster than a finite difference code employing a second-order-accurate spatial discretization and first-order-accurate explicit time integration. Furthermore, for a two-dimensional solidification benchmark problem, the performance of PRISMS-PF meets or exceeds that of phase-field frameworks that focus on implicit/semi-implicit time stepping, even though the benchmark problem’s small computational size reduces the scalability advantage of explicit time-integration schemes. PRISMS-PF supports an arbitrary number of coupled governing equations. The code structure simplifies the modification of these governing equations by separating their definition from the implementation of the numerical methods used to solve them. As part of its modular design, the framework includes functionality for nucleation and polycrystalline systems available in any application to further broaden the phenomena that can be used to study. The versatility of this approach is demonstrated with examples from several common types of phase-field simulations, including coarsening subsequent to spinodal decomposition, solidification, precipitation, grain growth, and corrosion.

36 MATERIALS SCIENCE↗

A neural master equation framework for multiscale modeling of molecular processes: application to atomic-scale plasma processes

Plasma-surface interactions (PSI) play a crucial role in microelectronics fabrication; however, their multiscale nature and array of complex, often unknown interactions make computational modeling of PSIs extremely difficult. To this end, we propose a general neural master equation (NME) framework that uses master equations to describe the dynamics of a molecular process, wherein neural networks learned from atomistic simulations represent unknown transitions between different system states. By leveraging the physics-based structure of master equations and data-driven state transitions, the NME framework promotes generalizability and physics interpretability, and can bridge disparate length and time scales. The framework is demonstrated for multiscale modeling of Si atomic layer etching and reactive ion etching, where the learned NME-based surface kinetic models exhibit good predictive and extrapolative capabilities for predicting experimentally relevant observables as a function of process parameters. The NME-based surface kinetic models obey physical constraints, which are violated in models based on neural ordinary differential equations. The proposed NME framework for multiscale modeling of molecular processes can pave the way for the discovery of new chemistries and materials in atomic-scale plasma processes.

Chemical engineering↗

In situ visualization of loading-dependent water effects in a stable metal-organic framework

Competitive water adsorption can have a significant impact on metal-organic framework performance properties, ranging from occupying active sites in catalytic reactions to co-adsorbing at the most favourable adsorption sites in gas separation and storage applications. Here, we investigate, for a metal-organic framework that is stable after moisture exposure, what are the reversible, loading-dependent structural changes that occur during water adsorption. Herein, a combination of in situ synchrotron powder and single-crystal diffraction, infrared spectroscopy and molecular modelling analysis was used to understand the important role of loading-dependent water effects in a water stable metal-organic framework. Through this analysis, insights into changes in crystallographic lattice parameters, water siting information and water-induced defect structure as a response to water loading were obtained. This work shows that, even in stable metal-organic frameworks that maintain their porosity and crystallinity after moisture exposure, important molecular-level structural changes can still occur during water adsorption due to guest-host interactions such as water-induced bond rearrangements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A plant–microbe interaction framework explaining nutrient effects on primary production

In most terrestrial ecosystems, plant growth is limited by nitrogen and phosphorus. Adding either nutrient to soil usually affects primary production, but their effects can be positive or negative. Here we provide a general stoichiometric framework for interpreting these contrasting effects. First, we identify nitrogen and phosphorus limitations on plants and soil microorganisms using their respective nitrogen to phosphorus critical ratios. Second, we use these ratios to show how soil microorganisms mediate the response of primary production to limiting and non-limiting nutrient addition along a wide gradient of soil nutrient availability. Using a meta-analysis of 51 factorial nitrogen–phosphorus fertilization experiments conducted across multiple ecosystems, we demonstrate that the response of primary production to nitrogen and phosphorus additions is accurately predicted by our stoichiometric framework. The only pattern that could not be predicted by our original framework suggests that nitrogen has not only a structural function in growing organisms, but also a key role in promoting plant and microbial nutrient acquisition. We conclude that this stoichiometric framework offers the most parsimonious way to interpret contrasting and, until now, unresolved responses of primary production to nutrient addition in terrestrial ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Electrocatalytic water oxidation performance in an extended porous organic framework with a covalent alliance of distinct Ru sites

The rational synthesis of durable, earth-abundant efficient electrocatalysts for the oxygen evolution reaction (OER) from water is one of the most important routes for storing renewable energy and minimizing fossil fuel combustion. The prime hurdles for effectively utilizing commercial RuO 2 as (OER) electrocatalysts are its very low stability, catalyst deactivation, and high cost. In this work, we explored a Ru-integrated porous organic polymer (Ru@Bpy-POP) by a facile one-pot Friedel–Crafts alkylation strategy between redox-active (Ru(demob) 3 Cl 2 ) and a carbazole unit, which is composed of unique features including an extended framework unit, isolated active sites, and tunable electrode kinetics. Ru@Bpy-POP can serve as a bridge between a Metal–Organic Framework (MOF) and POP-based catalytic systems with a balanced combination of covalent bonds (structural stability) and open metal sites (single site catalysis). Ru@Bpy-POP, deposited on a three-dimensional nickel foam electrode support, exhibits a promising electrocatalytic OER activity with an ultra-low ruthenium loading compared to a benchmark RuO 2 catalyst, providing an overpotential of about 270 mV to reach 10 mA cm –2 in an alkaline medium. Moreover, a high current density of 248 mA cm –2 was achieved for the Ru@Bpy-POP catalyst at only 1.6 V (vs. RHE), which is much higher than 91 mA cm –2 for commercial RuO 2 . The robust, albeit highly conjugated, POP framework not only triggered facile electro-kinetics but also suppressed aggregation and metallic corrosion during electrolysis. In particular, the benefits of covalent integration of distinct Ru sites into the framework can modulate intermediate adsorption and charge density, which contributes to its exceptional OER activity. All of the critical steps involved in OER are complemented by Density Functional Theory (DFT) calculations, which suggest that electrocatalytic water oxidation proceeds from a closed-shell configuration to open-shell electronic configurations with high-spin states. Finally, these open-shell configurations are more stable than their closed-shell counterparts by 1 eV, improving the overall catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗