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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Hydroclimate-coupled framework for assessing power system resilience under summer drought and climate change

Extreme drought, exacerbated by climate change, increasingly threatens power system resilience, and a systematic assessment of such impacts is challenging due to the unpredictability of drought and their associated modeling complexity. Here, to address the challenge, this research develops a hydroclimate-coupled power system resilience assessment framework that enables systematic modeling of drought and climate change impacts on generation, transmission, and demand sectors. Applying the framework to the 2025 Eastern U.S. power grid — comprising 6,055 at-risk generators — under climate-induced summer drought scenarios (including SSP126, SSP245, SSP370, and SSP585) from 2023 to 2100, the study finds that climate-induced droughts could jeopardize the power system’s reliability to a greater extent than historical events, potentially leading to widespread load shedding. More specifically, the study reveals that under the twenty-one representative drought scenarios, the loss of load expectation (LOLE) of the grid could range from 34.77 to 91.48 days per summer. The simulations indicate that implementing resilience enhancement strategies is crucial to ensure reliable system operation, which encompasses initiatives such as demand response, upgrading open cooling systems, and transmission expansion. In all, these findings underscore the urgent need for proactive planning and investment in resilient U.S. power systems to mitigate the impacts of extreme drought events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

A distributed voltage inference framework for cyber-physical attacks detection and localization in active distribution grids

The transition to active distribution grids with real-time monitoring and control depends on the proliferation of advanced communication networks and devices. This paradigm shift towards a cyber-physical architecture also introduces new vulnerabilities for adversaries to exploit and launch sophisticated cyber-physical attacks targeting grid observability. Current research highlights the challenges in distinguishing attacks on voltage phasor or nodal injection measurements and isolating multi-source attack locations in a multiphase distribution grid. The attack detection and localization methods in literature face accuracy issues, applications across diverse attack scenarios, or scalability limits. Here, to bridge these gaps, this paper proposes a distributed Voltage Inference framework for real-time detection and localization of cyber-physical attacks, addressing scalability, adaptability, and accuracy challenges in state-of-the-art methods. The proposed methodology leverages the distributed nature of the Voltage Inference framework through a two-step process of prediction and correction, together with a tractable graph partitioning approach, providing a reliable solution to identify compromised measurement sources and facilitate isolation. Extensive testing on IEEE 13 and 123-node distribution feeders underscores the algorithm’s efficacy, enhancing the security and resilience of active distribution grids against evolving cyber threats. Additionally, Hardware-in-the-Loop (HIL) implementation validates the proposed strategy’s practical applicability in real-world scenarios.

active distribution grids↗
DOE OSTI2025

A Bayesian framework to investigate radiation reaction in strong fields

Recent experiments aiming to measure phenomena predicted by strong-field quantum electrodynamics (SFQED) have done so by colliding relativistic electron beams and high-power lasers. In such experiments, measurements of collision parameters are not always feasible. However, precise knowledge of these parameters is required to accurately test SFQED. Here, we present a novel Bayesian inference procedure that infers collision parameters that could not be measured on-shot. This procedure is applicable to all-optical non-linear Compton scattering experiments investigating radiation reaction. The framework allows multiple diagnostics to be combined self-consistently and facilitates the inclusion of known information pertaining to the collision parameters. Using this Bayesian analysis, the relative validity of the classical, quantum-continuous and quantum-stochastic models of radiation reaction was compared for several test cases, which demonstrates the accuracy and model selection capability of the framework and highlight its robustness if the experimental values of fixed parameters differ from their values in the models.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Encapsulation of Ba in InSb Framework Introduces Chirality in Clathrate-Like BaIn 4 Sb 4

The discovery of Zintl compounds remains a powerful strategy for identifying materials with tunable electronic and thermal transport properties. During a concerted search for new inorganic clathrates with In–Sb frameworks, we discovered BaIn 4 Sb 4 . The composition of this phase deviates from that expected for a type-I clathrate with tetrahedral coordination of all In and Sb atoms (Ba 8 In 31 Sb 15 ). Instead, in the chiral structure of BaIn 4 Sb 4 (space group P 3 1 21, No. 152), a part of the In atoms have a trigonal planar coordination of 1In + 2Sb, forming Sb 2 –In–In–Sb 2 nonplanar fragments isostructural to diborane(4) B 2 H 4 with D 2 d symmetry. Ba atoms are located inside 16-vertex In 8 Sb 8 polyhedra, which share vertices and edges to form a chiral framework around the 3 1 screw axes. The title compound is electron-balanced, [Ba 2+ ][In 2+ ] 2 [In 3+ ] 2 [Sb3–] 4 , which was confirmed by characterization of the charge and heat transport properties. BaIn 4 Sb 4 exhibits a low thermal conductivity and high Seebeck coefficient, suggesting its untapped potential for thermoelectric applications. Finally, density functional theory (DFT) calculations indicate that chemical doping may enhance carrier concentration and improve the originally low electrical conductivity, thus enhancing thermoelectric performance.

electrical properties↗
DOE OSTI2025

High-Loading Single-Atom Catalyst via On-Surface Synthesis of a Metal-Covalent Organic Framework for Oxygen Reduction Reaction

The development of active catalysts with both high metal efficiency and use of earth abundant metals is the ultimate goal for advancing the required commercially viable and sustainable energy conversion technologies of the future. Metal-organic frameworks (MOFs) have emerged as promising candidates due to their high surface area and tunable active sites. Here, this study aims to fabricate a new type of high metal loading single-atom catalysts (SACs) based on 2D metal-organic covalent organic frameworks (MCOFs) with uniform, active and stable Fe-N 3 sites. The MCOFs were synthesized through an on-surface polymerization process using Fe and melamine as precursors. The polymerization steps were characterized using operando high-pressure scanning tunneling microscopy (HP-STM), in situ X-ray photoelectron spectroscopy (XPS), low-temperature STM (LT-STM), and computational calculations. The synthesized MCOFs demonstrated favorable adsorption and activation of O 2 at the Fe-N 3 sites, and it is predicted to be active for the oxygen reduction reaction (ORR). The surface chemistry and functionality of 2D MCOFs can be rationally designed by varying the metal atoms and organic linkers, offering a versatile platform for diverse applications.

25 ENERGY STORAGE↗
DOE OSTI2026

Mo 4 FeGa 17.25– x Ge x : Complementary Point Substitutions, Buffering Frameworks, and Merging of the 18-n and Octet Bonding Schemes

We present the discovery of Mo 4 FeGa 17.25–x Ge x (x ∼ 2.1(4), based on determination of Ge content), a complex gallide featuring a variety of point substitution phenomena. Its crystal structure is derived from the Ti 2 Ni type, in which a diamond network of face-sharing octahedra is interpenetrated by a second diamond network of vertex-sharing stella quadrangula. However, while in the ideal Ti 2 Ni type these two frameworks run uninterrupted through the crystal, Mo 4 FeGa 17.25–x Ge x shows three variations. First, the inner tetrahedron of every other stella quadrangula is replaced with a main group atom, creating tetrahedra reminiscent of the Zintl phase NaTl. Next, a selection of Ga 6 octahedra are filled with Fe atoms, in a manner analogous to the stuffed AuCu 3 -type phases. Finally, the refined crystal structure shows that in each unit cell a single Ga2 atom in the octahedral network is substituted with a dumbbell of Ga/Ge atoms. Electronic structure calculations on ordered models of Mo 4 FeGa 17.25–x Ge x reveal a narrow band near the Fermi energy, which is explained in terms of the 18-n and octet bonding schemes using reversed approximation Molecular Orbital analysis. A DFT-chemical pressure analysis connects the tetrahedron/atom and atom/dumbbell substitutions to the relief of atomic packing tensions and highlights soft atomic motions within the octahedral framework and driving forces for atom/dumbbell substitution. The combination of soft vibrational modes, disorder, and a narrow band gap could make this phase of interest for potential thermoelectric properties.

Chemical structure↗
DOE OSTI2025

A Practical Framework for Simulating Time-Resolved Spectroscopy Based on a Real-Time Dyson Expansion

Time-resolved spectroscopy is a powerful tool for probing electron dynamics in molecules and solids, revealing transient phenomena on subfemtosecond time scales. The interpretation of experimental results is often enhanced by parallel numerical studies, which can provide insight and validation for experimental hypotheses. However, developing a theoretical framework for simulating time-resolved spectra remains a significant challenge. The most suitable approach involves the many-body nonequilibrium Green's function formalism, which accounts for crucial dynamical many-body correlations during time evolution. While these dynamical correlations are essential for observing emergent behavior in time-resolved spectra, they also render the formalism prohibitively expensive for large-scale simulations. Substantial effort has been devoted to reducing this computational cost─through approximations and numerical techniques─while preserving the key dynamical correlations. The ultimate goal is to enable first-principles simulations of time-dependent systems ranging from small molecules to large, periodic, multidimensional solids. Here, in this perspective, we outline key challenges in developing practical simulations for time-resolved spectroscopy, with a particular focus on Green's function methodologies. We highlight a recent advancement toward a scalable framework: the real-time Dyson expansion (RT-DE) [Phys. Rev. Lett. 2024, 133, 226902]. We introduce the theoretical foundation of RT-DE and discuss strategies for improving scalability, which have already enabled simulations of system sizes beyond the reach of previous fully dynamical approaches. We conclude with an outlook on future directions for extending RT-DE to first-principles studies of dynamically correlated, nonequilibrium systems.

Reeves, Cian C. [Univ. of California, Santa Barbar↗
DOE OSTI2025

Computational Optimization of Room Temperature Usable Capacity for Hydrogen Storage in MFU-4-Type Metal–Organic Frameworks via Pairwise Metal Substitutions

The efficient storage of hydrogen is a critical challenge in the quest for sustainable energy solutions. Current adsorbent-based methods achieve satisfactory storage densities predominantly under cryogenic temperatures and/or high pressures, which imposes problems with cost-efficient and safe implementation of this technology. Materials that can bind hydrogen gas reversibly at ambient temperatures and more moderate pressures could play a pivotal role in enabling hydrogen-powered technologies. In this study, we use reliable computational modeling to investigate two synthetically feasible paths for tuning the enthalpy of H2 binding in MFU-4-type metal–organic frameworks (MOFs), aiming to maximize usable capacity. This study examines MIM4 IICl3(bta)6 (bta– = benzotriazolate) Kuratowski-type clusters as a model for strong binding sites in MFU-4l frameworks. We systematically evaluate the impact of separately tuning the central MII metal ion (which plays a structural role) and the peripheral MI metal ion (which binds the substrate) on the energetics of H2 binding. Our computational study reveals that H2 binding at an MI site mostly follows the trend AgI < CuI < NiI < CoI < AuI while a larger central MII site generally weakens the H2 binding at a MI site. Importantly, we have identified three new combinations of MI and MII to achieve high fractional usable capacities of the total H2 adsorbed under a pressure swing from 5 to 100 bar at room temperature. Additionally, we examine the nature of the binding interaction between the peripheral metal atom and the hydrogen molecule. While charge transfer predominantly induces this interaction, for several atom combinations, a change in the polarization (associated with variations in the ionic radius of the MI binding atom) is another important factor for adjusting the strength of the interaction. We suggest that the proposed compositions of Kuratowski-type clusters are highly desirable synthetic targets for future laboratory study.

Tkachenko, Nikolay V↗
DOE OSTI2026

Machine Learning Framework for Characterizing Processing–Structure Relationship in Block Copolymer Thin Films

The morphology of block copolymers (BCPs) critically influences material properties and applications. This work introduces a machine learning (ML)-enabled, high-throughput framework for analyzing grazing incidence small-angle X-ray scattering (GISAXS) data and atomic force microscopy (AFM) images to characterize BCP thin film morphology. A convolutional neural network was trained to classify AFM images by surface features, achieving 97% testing accuracy. Classified images were then analyzed to extract 2D grain size measurements from the samples in a high-throughput manner. ML models were trained to predict domain orientation based on processing parameters such as solvent ratio, additive type, and additive ratio. GISAXS-based properties were predicted with strong performances (R 2 > 0.75), while AFM-based property predictions were less accurate (R 2 < 0.60), likely due to the localized nature of AFM measurements compared to the bulk information captured by GISAXS. Beyond model performance, interpretability was addressed using SHapley Additive exPlanations (SHAP). SHAP analysis revealed that the additive ratio had the largest impact on morphological predictions, where additive provides the BCP chains with increased volume to rearrange into thermodynamically favorable morphologies. This interpretability helps validate model predictions and offers insight into parameter importance. Altogether, the presented framework combining high-throughput characterization and interpretable ML offers an approach to exploring and optimizing BCP thin film morphology across a broad processing landscape.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Heterogeneous and Framework-Bound Copper Species Contribute to Catalytic Partial Methane Oxidation in Cu–Chabazite Zeolites

The relationship between continuous partial methane oxidation (PMO) rates and Cu site speciation in Cu-CHA zeolite catalysts is explored through differential rate measurements across a series of samples of varying compositions combined with density functional theory, first-principles thermodynamics, and statistical models that characterize Cu speciation. Under continuous PMO conditions (573 K, 0.07 kPa O 2 , 3 kPa H 2 O), Cu ions are shown to anchor to the CHA framework in both monomeric (Z 2 Cu and Z 2 CuH 2 O) and dimeric (O- and OH-bridged Cu) forms that are sensitive to the identity of the local framework anchoring site. Consequently, across the studied compositional range, Cu-CHA catalysts are predicted to contain a mixture of monomeric and dimeric Cu sites. Cu-normalized CH 3 OH formation rates extrapolated to zero conversion reflect contributions from multiple site types. Predicted CH 3 OH formation rates indicate that the Cu site reactivity toward CH 4 is influenced by zeolite composition and is likely limited by the reduction half-cycle.

03 NATURAL GAS↗
DOE OSTI2026

Covalent Organic Framework Photocatalysts for Water Oxidation and Overall Artificial Photosynthesis

Artificial photosynthesis through proton reduction or CO 2 reduction to generate chemical fuels has gained increasing attention as an attractive strategy for solar-to-fuel conversion. In these systems, the oxygen evolution reaction (OER) provides the necessary electrons and protons for driving the overall reaction but represents the rate-limiting step due to its inherently sluggish kinetics. Therefore, efficient overall artificial photosynthesis requires photocatalysts that can drive both the oxidation and reduction half-reactions, which impose stringent demands on catalyst design. Covalent organic frameworks (COFs) offer a versatile platform for designing such photocatalysts, owing to their strong light-harvesting capabilities , periodic architectures, and highly tunable frameworks that allow programmable catalytic sites and adjustable electronic band structures. While notable progress has been made in developing COF photocatalysts for the OER and overall artificial photosynthesis, these advances remain scattered across the literature and existing reviews, and a dedicated, systematic overview of the OER and its central role in integrated artificial photosynthetic processes is still lacking. This Review systematically summarizes recent advances in COF-based photocatalysts for the OER half-reaction and overall artificial photosynthesis. Our aim is to offer a comprehensive roadmap that establishes fundamental design principles for next-generation COF-based photocatalysts toward efficient and sustainable artificial photosynthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Online LIBS–ML Framework for Dynamic Characterization of Heterogeneous Waste-Derived Gasification Feedstocks

LIBS−ML framework for real time feedstock characterization during continuous conveyor transport Heterogeneous waste derived feedstocks (e.g., waste coal, biomass and blends) introduce rapid variability in heating value and ash chemistry that affect gasifier operation, yet conventional laboratory characterization techniques are too slow to support proactive control. To address this gap, this study reports on an online, in situ, dynamic characterization framework that couple’s laser-induced breakdown spectroscopy (LIBS) with leakage safe machine learning (ML) regression to deliver real time, decision quality predictions of gasifier relevant properties. A controlled sample matrix spanning two different waste coals, two different biomasses, and engineered blends under two particle size conditions were constructed and benchmarked using standardized laboratory analyses for proximate/ultimate properties and ash composition. LIBS spectra were acquired dynamically as material flowed on a conveyor belt, using high energy 1064 nm laser ablation and shot averaging to improve repeatability and precision. Supervised regression models (multi layer perceptron (MLP) /artificial neural network (ANN), random forest (RF), and support vector regression (SVR)) and an optimized weighted ensemble were trained on emission line feature sets using nested cross validation with Bayesian hyperparameter tuning and validated against an independent hold out set. The proposed LIBS−ML workflow achieves near laboratory predictive fidelity across parametric targets (including higher heating value (HHV), ash content, fixed carbon, sulfur, major ash forming oxides, and initial deformation temperature (IDT)), with the weighted ensemble providing a robust default predictor under dynamic measurement conditions. These results demonstrate a practical pathway for real time feedstock characterization that can enable feedforward adjustments and more resilient gasifier operation for variable quality waste derived fuels.

Biomass↗
DOE OSTI2025

Mechanochemical Solid Form Screening of Zeolitic Imidazolate Frameworks Using Structure-Directing Liquid Additives

We demonstrate a systematic application of the mechanochemical liquid-assisted grinding (LAG) methodology to screen for forms of zinc imidazolate (ZnIm 2 ), of fundamental importance as the simplest member of the zeolitic imidazolate framework materials family. The exploration of 45 different liquid additives, selected based on their molecular structure and physicochemical properties has resulted in eight different ZnIm 2 topological forms, appearing in 13 crystallographically distinct solid forms (including two previously unknown forms of the crb (BCT) topology), amorphous phases, and the interrupted moc-Zn 4 Im 8 HIm. All prepared topological forms were also explored computationally, using dispersion-corrected periodic density functional theory (DFT) calculations, enabling the rationalization of screening outcomes, and setting the stage for future prediction of additive-directed metal–organic framework (MOF) synthesis. This first systematic exploration of LAG in screening for three-dimensional MOFs demonstrates the potential of the liquid additive to not only accelerate materials synthesis, but also to direct it toward topologically different MOFs. The discovery of novel forms of a material that already exhibits at least 21 crystallographically and functionally different forms provides a strong testimony on the power of mechanochemistry in metal–organic materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Mechanistic Studies of Oxidative Degradation in Diamine-Appended Metal–Organic Frameworks Exhibiting Cooperative CO 2 Capture

Understanding the impact of O 2 during a carbon capture process is vital for designing robust, cost-effective materials for carrying it out. However, mechanistic studies of the O 2 -induced degradation of materials are not easily undertaken owing to the complex sequential reaction pathways that arise. Here, we report comprehensive mechanistic investigations of the O 2 -induced degradation of diamine-appended metal−organic frameworks (MOFs) exhibiting cooperative CO 2 adsorption. Oxygen exposure experiments were performed on seven different diamine-appended MOFs, including e-2−Mg 2 (dobpdc) (e-2 = N-ethylethylenediamine, dobpdc 4− = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate), under various temperatures and O 2 pressures. These experiments show that diamine degradation inhibits CO 2 chemisorption and that the degradation rate is significantly influenced by the diamine structure. In contrast, the parent frameworks remain essentially intact upon O 2 exposure. Detailed characterization of O 2 -exposed e-2−Mg 2 (dobpdc) revealed the formation of various degradation products, including acetaldehyde, carbon dioxide, water, ethylamine, and other aldehyde- and imine-containing species. Together, these observations suggest that diamine degradation occurs via C−N bond cleavage through pathways involving C-centered radicals. Furthermore, computational evaluation of the initiation and propagation pathways for amine degradation in diamine-appended MOFs indicates that (i) degradation is likely initiated by OH • , (ii) carbon-centered radicals generated via radical transfer reactions react with O 2 , leading to amine degradation, and (iii) the ratelimiting step of the degradation reactions likely involves O−O bond cleavage. Overall, these mechanistic insights could inform strategies for mitigating O 2 -induced amine degradation in next-generation carbon capture technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

CO Adsorbates Induced Framework-Associated Low-Valence Co δ+ Sites in Co-ZSM-5 for Ethane Dehydrogenation

The dynamic structural evolution of heterogeneous catalysts is a ubiquitous phenomenon that has attracted a lot of interest. Catalyst reconstruction can occur after appropriate pretreatment, resulting in more efficient active catalysts, which is an attractive but challenging issue. Here, we reveal a CO activation strategy that controls the microenvironment of the Co sites in the high-silica Co-ZSM-5 catalyst (denoted as 0.50Co-Z5(340)), resulting in three times higher initial conversion and superior regeneration durability in the ethane dehydrogenation reaction compared to the same catalyst without CO pretreatment. In situ spectroscopy and metadynamics simulations reveal that the Co 2+ sites in 0.50Co-Z5(340) dislodge from the framework and move toward the nearby Brønsted acid sites, forming framework-associated low-valence Co δ+ species. Mechanistic studies indicate that the Co δ+ species catalyze ethane C–H bond cleavage via an oxidative addition mechanism, and ethylene is produced simultaneously with H* coupling (direct pathway). The promoted C–H bond activation and facile ethylene desorption explain the superior ethane dehydrogenation performance of the herein CO preactivated 0.50Co-Z5(340) catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Isolation of a Terminal Cobalt Nitride in a Metal–Organic Framework

Transition metal nitrides are reactive intermediates in biological and industrial processes. Chemists have synthesized molecular model complexes of such reactive species to understand their function and electronic requirements for new applications. However, molecular chemistry can suffer from intra- and intermolecular decomposition pathways, which preclude further discovery of unknown reactive species. Metal-organic frameworks offer an opportunity for creating long-lived forms of such species with the vacuum of the pore suppressing degradation while simultaneously enabling substrate access for controlled reactivity studies. Here, in this study, we report the characterization of an elusive terminal cobalt nitride species generated through photolysis or thermolysis of a site-isolated cobalt azide within the evacuated metal-organic framework CoN 3 -MFU-4l. The first crystal structure of such a species is presented, with vibrational, X-ray absorption, and electron paramagnetic resonance spectroscopies providing further direct evidence for its formation while elucidating its electronic structure. The system additionally enables subsequent reactivity studies with selected substrates, revealing a unique ambiphilic behavior for a metal nitride species.

Börgel, Jonas [University of California, Berkeley,↗
DOE OSTI2026

Multimodal Nanoscale Mapping of Local Structure and CO 2 Adsorption in Metal–Organic Frameworks

Diamine functionalization of the metal−organic framework Mg 2 (dobpdc) (dobpdc 4− = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate) significantly enhances its selectivity for CO 2 capture from flue gases and air. The structure and CO 2 capacity of such materials are typically assessed using bulk techniques that rely on averaging signal over large ensembles of unit cells, obscuring local heterogeneities, such as variations in CO 2 occupancy across individual nanocrystals. To resolve this limitation, we demonstrate a multimodal, nanoscale characterization of Mg 2 (dobpdc) appended with 1,3-diaminopropane. By employing recently developed characterization techniques at progressively smaller length scales, we uncover insights from correspondingly smaller populations of unit cells. First, we use parallel-beam 3D electron diffraction (3D ED) to identify a prominent expansion in lattice parameters upon desorption of CO 2 , as observed at the level of single nanocrystals. Second, we use convergent-probe 4D scanning transmission electron microscopy (4D-STEM) to quantify associated differences in lattice strain as a function of gas loading and diamine appending. These measurements sample small subvolumes within individual nanocrystals. Finally, we apply infrared scattering scanning near-field optical microscopy (IR s- SNOM) to confirm variable CO 2 chemisorption across adsorption sites at the surface of single nanocrystals. This multimodal, multiscale approach allows us to map heterogeneity within individual nanocrystals. Collectively, these findings emphasize the importance of local, nanoscale characterization of metal−organic frameworks in revealing previously unresolvable features that impact their performance.

Karstens, Sarah L. [University of California, Berk↗
DOE OSTI2026

Regulation of Energy and Mass Transport in a Hydrogen-Bonded Framework for Visible-Light-Driven CO2 Reduction in Water

Photoenzymatic reduction of CO2 to formate is a promising strategy for carbon valorization, yet its efficiency is still limited by inefficient energy and mass transport. Here, we design a series of isostructural hydrogen-bonded organic frameworks (HOFs) that establish confinement effects to promote photocatalytic NADH regeneration and the subsequent NADH-dependent enzymatic CO2-to-formate reduction. We demonstrate that spatial confinement within the framework channels localizes exciton migration to nanoscale domains and promotes interfacial dissociation. Additionally, Rh-induced electronic-structure modulation enables ultrafast electron transfer, while the intrinsic hydrogen-bond network furnishes directional proton conduction to NAD+. These synergistic regulations afford a photocatalytic NADH regeneration efficiency of 99.8% with a record apparent quantum efficiency of 32.8%, and drive formate production at a rate of 3020 μmol g-1 h-1 with 100% selectivity─the highest rate reported to date for all light-driven systems in water. The HOF-based catalyst retains 86.3% of its initial activity over five cycles, highlighting its robustness. This work offers mechanistic insight into how microenvironment engineering within HOF architectures regulates energy and mass transport in photoenzymatic catalysis, paving the way for the rational design of advanced hybrid catalytic systems.

Xu, Jiaxing↗