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At least 1,279 records · Page 71

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DOE OSTI2014

Selective Propene Oligomerization with Nickel(II)-Based Metal–Organic Frameworks

Two Ni 2+ -containing metal-organic frameworks, Ni 2 (dobdc) and Ni 2 (dobpdc), are shown to be active for the oligomerization of propene in the gas phase. The metal-organic frameworks exhibit activity comparable to Ni 2+ -exchanged aluminosilicates but maintain high selectivity for linear oligomers. Thus, these frameworks should enable the high yielding synthesis of linear propene oligomers for use in detergent and diesel fuel applications.

alkyls↗

DOE OSTI2020

Tunable and Cooperative Thermomechanical Properties of Protein-Metal-Organic Frameworks

We recently introduced protein-metal-organic frameworks (protein-MOFs) as chemically designed protein crystals, composed of ferritin nodes that predictably assemble into 3D lattices upon coordination of various metal ions and ditopic, hydrox-amate-based linkers. Owing to their unique tripartite construction, protein-MOFs possess extremely sparse lattice connectivi-ty, suggesting that they might display unusual thermomechanical properties. Leveraging the synthetic modularity of ferritin-MOFs, we investigated the temperature-dependent structural dynamics of six distinct frameworks. Our results show that the thermostabilities of ferritin-MOFs can be tuned through the metal component or the presence of crowding agents. Our stud-ies also reveal a framework that undergoes a reversible and isotropic first-order phase transition near-room temperature, corre-sponding to a 4% volumetric change within ≤1 deg C and a hysteresis window of ~10 deg C. Here, this highly cooperative crystal-to-crystal transformation, which stems from the soft crystallinity of ferritin-MOFs, illustrates the advantage of modular con-struction strategies in discovering tunable–and unpredictable–material properties.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Critical Role of Framework Flexibility and Disorder in Driving High Ionic Conductivity in LiNbOCl 4

Understanding Li-ion transport is key for the rational design of superionic solid electrolytes with exceptional ionic conductivities. LiNbOCl 4 is reported to be one of the most highly conducting materials in the recently realized new class of soft oxyhalide solid electrolytes, exhibiting an ionic conductivity of ~11 mS·cm -1 . Here, we apply X-ray/neutron diffraction and pair distribution function analysis - coupled with density functional theory/ab-initio molecular dynamics - to determine a structural model that provides a rationale for the high conductivity that we observe experimentally in this nanocrystalline solid. We show that it arises from unusually high framework flexibility at room temperature. This owes to isolated 1-D [NbOCl 4 ] - anionic chains which exhibit energetically favorable orientational disorder that is - in turn - correlated to multiple, disordered and equi-energetic Li + sites in the lattice. As the Li-ions sample the 3-D energy landscape with a fast predicted diffusion coefficient of 5.1 x 10 -7 cm 2 /s at room temperature (σ i calc = 17.4 mS·cm -1 ), the inorganic polymer chains can reorient or vice versa. The activation energy barrier for Li migration through the frustrated energy landscape is especially reduced by the elastic nature of the NbO 2 Cl 4 octahedra evident from very widely dispersed Cl-Nb-Cl bond angles in AIMD snapshots at 300 K. The phonon spectra are predominantly influenced by Cl vibrations in the low energy range, and there is strong overlap between the framework (Cl, Nb) and Li partial pDOS in the region between 1.2 - 4.0 THz. The framework flexibility is also reflected in a relatively low bulk modulus of 22 GPa. In conclusion, our findings pave the way for investigation of future “flex-ion” inorganic solids and open up a new direction for the design of high conductivity, soft solid electrolytes for all-solid-state batteries.

AIMD↗

DOE OSTI2025

Electrochemical CO 2 Capture by a Quinone-Based Covalent Organic Framework

Electrochemical CO 2 capture is an emerging technology that promises to be more energy-efficient than traditional thermal or pressure-swing processes. Herein, the first evidence of electrochemical capture of CO 2 using a covalent organic framework (COF) is presented. We hypothesized that the assembly of anthraquinone units into a well-defined porous framework electrode would lead to enhanced electrochemical CO 2 capture compared to previous approaches that grafted anthraquinones on carbon supports and suffered from low CO 2 capacities and stabilities. To test this, an anthraquinone-based COF is employed, and it is found that the quinones are electrochemically accessible for reversible CO 2 capture in an ionic liquid electrolyte. The system achieves a high electrochemical CO 2 uptake capacity >2.6 mmol g –1 COF, reaching half of the theoretical CO 2 capacity of the material and surpassing the capacities of anthraquinone-functionalized carbons. The stability and CO 2 uptake rate issues encountered with the ionic liquid system are also addressed by using aqueous electrolytes where we attained stable carbon capture for 500 cycles with a 99.6% Coulombic efficiency and an electrical energy consumption of 31 kJ mol CO 2 –1 . The use of covalent organic framework electrodes can become a general strategy for understanding and enhancing the electrochemical CO 2 capture.

carbon capture and storage↗

DOE OSTI2016

Structural Transitions of the Metal-Oxide Nodes within Metal–Organic Frameworks: On the Local Structures of NU-1000 and UiO-66

In situ pair distribution function (PDF) analyses and density functional theory (DFT) computations are used to probe local structural transitions of M6O8 nodes found in two metal organic frameworks (MOFs), NU-1000 and UiO-66, for M = Zr, Hf. Such transitions are found to occur without change to the global framework symmetry at temperatures within a range relevant to many potential MOF applications. For the particular M6(O)8 nodes studied here, the observed distortions can be mapped to polymorphic forms known for bulk ZrO2. In the MOF framework, however, node distortions are found to occur at substantially lower temperature than analogous distortions in bulk ZrO2 owing to the nanoscale nature of the former.

Platero-Prats, Ana E.↗

DOE OSTI2026

Toward Hydrogen Isotope Separations through Strong Hydrogen Adsorption at Open Copper(I) Sites in an Ultramicroporous Metal-Organic Framework

Metal-organic frameworks with coordinatively unsaturated metal sites (open metal sites) capable of engaging in orbital interactions with pi-acidic gases are of interest for enabling ambient-temperature gas separations, such as hydrogen isotope separations. In view of the weakly pi-acidic nature of H2, we sought to strengthen pi-backbonding-mediated H2 adsorption through pore confinement effects. Toward that end, we synthesized and characterized the ultramicroporous metal-organic framework CuxZn5-xCl4-yHz(bbta)3 (CuIZn-MFU-4; H2bbta = 1H,5H-benzo(1,2-d:4,5-d')bistriazole), featuring pi-basic trigonal pyramidal CuI sites that reside within 7 A of one another at their closest. Gas adsorption measurements reveal an H2 adsorption enthalpy of -38 kJ/mol, exceeding that of the larger-pore analog (CuIZn-MFU-4l; -33 kJ/mol) and representing the strongest H2 adsorption yet achieved in a metal-organic framework. The stronger H2 adsorption in CuIZn-MFU-4 is attributed to a combination of pore confinement effects and the increased ..sigma..-accepting nature of the CuI sites caused by a more electron-withdrawing bbta2- linker, as supported by structural, spectroscopic, and computational evidence. With the strongest H2 adsorption, equilibrium isotope effects in CuIZn-MFU-4 lead to a D2/H2 selectivity (as estimated by ideal adsorbed solution theory) of 1.35 even at 298 K, approaching the values reported below 200 K for conventional porous materials.

08 HYDROGEN↗

DOE OSTI2026

Field-Coupled Water Splitting with Metal-Free Donor–Acceptor Covalent Organic-Framework Junctions

Advancing metal-free electrocatalysts for hydrogen and oxygen evolution reactions (HER/OER) across acidic and alkaline media requires coordinated control of intermediate binding thermodynamics, interfacial charge delivery, and near-electrode transport dynamics. Here, we design amide-linked benzene–triazine covalent organic frameworks (BTA/TzTA-Hz COFs) and integrate them with carbon nanotubes (CNTs) to form COF–CNT junctions that establish a built-in interfacial electric field. Density functional theory (DFT) and electrostatic potential maps indicate complementary active motifs, with benzene-proximal fragments associated with HER and triazine-proximal motifs associated with OER. CNT integration shifts the contact-potential difference by ≈0.20 V, while operando electrochemical impedance spectroscopy suggests partially separable high-frequency junction-charging and lower-frequency Faradaic/transport responses. A 300 mT static magnetic field lowers the HER and OER overpotentials by tens of millivolts. Under anodic bias, the effective interfacial charging capacitance increases, and Mott–Schottky analysis shows an apparent ∼0.15 V flat-band shift with an essentially unchanged slope. Together, these observations are consistent with field-perturbed interfacial charging and altered bias partitioning. Field-dependent impedance and bubble imaging are consistent with magnetohydrodynamic convection that promotes bubble detachment and near-electrode mass transport for both half-reactions, and they reveal an OER-specific high-frequency perturbation under anodic bias. Under field, the heterostructure reaches an OER onset overpotential of ∼261 mV and requires an overpotential of 366 mV at 10 mA cm –2 in alkaline electrolyte. These results illustrate how reticular-framework chemistry, junction engineering, and both built-in and applied fields can program reactivity through interfacial electrostatics and near-electrode transport in organic-framework electrocatalysts.

Garcia-Enriquez, Lissette [Univ. of Texas at El Pa↗

DOE OSTI2018

Unexpected Diffusion Anisotropy of Carbon Dioxide in the Metal–Organic Framework Zn 2 (dobpdc)

Metal–organic frameworks are promising materials for energy-efficient gas separations, but little is known about the diffusion of adsorbates in materials featuring one-dimensional porosity at the nanoscale. An understanding of the interplay between framework structure and gas diffusion is crucial for the practical application of these materials as adsorbents or in mixed-matrix membranes, since the rate of gas diffusion within the adsorbent pores impacts the required size (and therefore cost) of the adsorbent column or membrane. In this paper, we investigate the diffusion of CO 2 within the pores of Zn 2 (dobpdc) (dobpdc 4– = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) using pulsed field gradient (PFG) nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) simulations. The residual chemical shift anisotropy for pore-confined CO 2 allows PFG NMR measurements of self-diffusion in different crystallographic directions, and our analysis of the entire NMR line shape as a function of the applied field gradient provides a precise determination of the self-diffusion coefficients. In addition to observing CO 2 diffusion through the channels parallel to the crystallographic c axis (self-diffusion coefficient D ∥ = (5.8 ± 0.1) × 10 –9 m 2 s –1 at a pressure of 625 mbar CO 2 ), we unexpectedly find that CO 2 is also able to diffuse between the hexagonal channels in the crystallographic ab plane (D ⊥ = (1.9 ± 0.2) × 10 –10 m 2 s –1 ), despite the walls of these channels appearing impermeable by single-crystal X-ray crystallography and flexible lattice MD simulations. Finally, observation of such unexpected diffusion in the ab plane suggests the presence of defects that enable effective multidimensional CO 2 transport in a metal–organic framework with nominally one-dimensional porosity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Direct Observation of Node-to-Node Communication in Zeolitic Imidazolate Frameworks

Zeolitic imidazolate frameworks (ZIFs) with open-shell transition metal nodes represent a promising class of highly ordered light harvesting antennas for photoenergy applications. However, their charge transport properties within the framework, the key criterion to achieve efficient photoenergy conversion, are not yet explored. Herein, we report the first direct evidence of a charge transport pathway through node-to-node communication in both ground state and excited state ZIFs using the combination of paramagnetic susceptibility measurements and time-resolved optical and X-ray absorption spectroscopy. These findings provide unprecedented new insights into the photoactivity and charge transport nature of ZIF frameworks, paving the way for their novel application as light harvesting arrays in diverse photoenergy conversion devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Creating Well-Defined Hexabenzocoronene in Zirconium Metal–Organic Framework by Postsynthetic Annulation

The incorporation of large π-conjugated ligands into metal–organic frameworks (MOFs) can present interesting photophysical and electrochemical properties into the framework. However, these effects are often hindered by the strong π–π interaction and the low solubility of the arylated ligands. Herein, we report the synthesis of a porous zirconium-based MOF, Zr 6 (μ 3 -O) 4 (μ 3 -OH) 4 (OH) 6 (H 2 O) 6 (HCHC) (PCN-136, HCHC = hexakis(4-carboxyphenyl)hexabenzocoronene), which is composed of a hexacarboxylate linker with a π-conjugated hexabenzocoronene moiety. Direct assembly of the Zr 4+ metal centers and the HCHC ligands was unsuccessful due to the low solubility and the unfavorable conformation of the arylated HCHC ligand. Hence, PCN-136 was obtained from aromatization-driven postsynthetic annulation of the hexaphenylbenzene fragment in a preformed framework (pbz-MOF-1) to avoid π–π stacking. This postsynthetic modification was done through a single-crystal-to-single-crystal transformation and was clearly observable utilizing single -crystal X-ray crystallography. The formation of large π-conjugated systems on the organic linker dramatically enhanced the photoresponsive properties of PCN-136. With isolated hexabenzocoronene moieties as photosensitizers and Zr–oxo clusters as catalytic sites, PCN-136 was employed as an inherent photocatalytic system for CO 2 reduction under visible-light irradiation, which showed increased activity compared with pbz-MOF-1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Multistep Solid-State Organic Synthesis of Carbamate-Linked Covalent Organic Frameworks.

Herein, we demonstrate the first example of a multistep solid-state organic synthesis, in which a new imine-linked two-dimensional covalent organic framework (COF-170, 1) was transformed through three consecutive postsynthetic modifications into porous, crystalline cyclic carbamate and thiocarbamate-linked frameworks. These linkages are previously unreported and inaccessible through de novo synthesis. While not altering the overall connectivity of the framework, these chemical transformations induce significant conformational and structural changes at each step, highlighting the key importance of noncovalent interactions and conformational flexibility to COF crystallinity and porosity. These transformations were assessed using 15 N multiCP-MAS NMR spectroscopy, providing the first quantitation of yields in COF postsynthetic modification reactions, as well as of amine defect sites in imine-linked COFs. This multistep COF linkage postsynthetic modification represents a significant step toward bringing the precision of organic solution-phase synthesis to extended solid-state compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Guest-induced emergent properties in Metal–Organic Frameworks

Metal–Organic frameworks (MOFs) are crystalline nanoporous materials comprised of organic electron donors linked to metal ions by strong coordination bonds. Applications such as gas storage and separations are currently receiving considerable attention, but if the unique properties of MOFs could be extended to electronics, magnetics, and photonics, the impact on material science would greatly increase. Recently, we obtained “emergent properties,” such as electronic conductivity and energy transfer, by infiltrating MOF pores with “guest” molecules that interact with the framework electronic structure. In this Perspective, we define a path to emergent properties based on the Guest@MOF concept, using zinc-carboxylate and copper-paddlewheel MOFs for illustration. Energy transfer and light harvesting are discussed for zinc carboxylate frameworks infiltrated with triplet-scavenging organometallic compounds and thiophene- and fullerene-infiltrated MOF-177. In addition, we discuss the mechanism of charge transport in TCNQ-infiltrated HKUST-1, the first MOF with electrical conductivity approaching conducting organic polymers. Lastly, these examples show that guest molecules in MOF pores should be considered not merely as impurities or analytes to be sensed but also as an important aspect of rational design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Modeling Land-Atmosphere Coupling at Cloud-Resolving Scale Within the Multiple Atmosphere Multiple Land (MAML) Framework in SP-E3SM

Representing subgrid variabilities of land surface processes and their upscaled effects is crucial for global climate modeling. Here, we implement a Multiple Atmosphere Multiple Land (MAML) framework in the superparamaterized version of E3SM (SP32 E3SM) to explicitly simulate the subgrid variabilities of land states and fluxes at cloud-resolving scale and their interactions with atmosphere. Comparing to the standard SP-E3SM in which all the atmospheric columns of the cloud resolving model embedded within the global atmospheric model grid interact with the same land surface (i.e., Multiple Atmosphere Single Land (MASL)), the impact of MAML on the strength of land-atmosphere coupling is limited, partly because the current implementation mainly facilitates one-way coupling between the cloud-resolving model and the land surface model. Despite such limitation, MAML increases the surface latent heat flux at the expense of sensible heat flux, and increases precipitation in India, Amazon, and Central Africa, reducing the model dry bias compared to the standard SP-E3SM. By employing a normalized gross moist stability (NGMS) diagnostic framework, we find that the increase in precipitation minus evaporation (PE) is primarily driven by the change in large-scale moisture convergence, particularly by the increase of water vapor in the lower atmosphere, while the local effect of total surface energy flux plays a minor role in the P-E change. More specifically, MAML changes the surface energy partitioning (evaporative fraction), increases the atmosphere water vapor, and further increases P-E by decreasing the NGMS. Finally, future development in the MAML framework is discussed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Bridging 20 Years of Soil Organic Matter Frameworks: Empirical Support, Model Representation, and Next Steps

Abstract In the past few decades, there has been an evolution in our understanding of soil organic matter (SOM) dynamics from one of inherent biochemical recalcitrance to one deriving from plant‐microbe‐mineral interactions. This shift in understanding has been driven, in part, by influential conceptual frameworks which put forth hypotheses about SOM dynamics. Here, we summarize several focal conceptual frameworks and derive from them six controls related to SOM formation, (de)stabilization, and loss. These include: (a) physical inaccessibility; (b) organo‐mineral and ‐metal stabilization; (c) biodegradability of plant inputs; (d) abiotic environmental factors; (e) biochemical reactivity and diversity; and (f) microbial physiology and morphology. We then review the empirical evidence for these controls, their model representation, and outstanding knowledge gaps. We find relatively strong empirical support and model representation of abiotic environmental factors but disparities between data and models for biochemical reactivity and diversity, organo‐mineral and ‐metal stabilization, and biodegradability of plant inputs, particularly with respect to SOM destabilization for the latter two controls. More empirical research on physical inaccessibility and microbial physiology and morphology is needed to deepen our understanding of these critical SOM controls and improve their model representation. The SOM controls are highly interactive and also present some inconsistencies which may be reconciled by considering methodological limitations or temporal and spatial variation. Future conceptual frameworks must simultaneously refine our understanding of these six SOM controls at various spatial and temporal scales and within a hierarchical structure, while incorporating emerging insights. This will advance our ability to accurately predict SOM dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A New Framework for the Attribution of Air‐Sea CO 2 Exchange

Abstract The air‐sea transfer of carbon dioxide can be viewed as a dynamic system through which atmospheric and oceanic processes push surface waters away from thermodynamic equilibrium, while diffusive gas transfer pulls them back toward local equilibrium. These push/pull processes drive significant sub‐seasonal, seasonal, and interannual variability in air‐sea carbon fluxes, the quantification of which is critical both for diagnosing the ocean response to fossil fuel emissions and for attempts to mitigate anthropogenic climate disruption through intentional modification of surface ocean biogeochemistry. In this study, we present a new approach for attributing air‐sea carbon fluxes to specific mechanisms. The new framework is first applied to a two‐box ocean nutrient and carbon cycle model as an illustrative example. Next, outputs from a regional eddy‐resolving model of the Southern Ocean are analyzed. The roles of multiple physical and biogeochemical processes are identified. The decomposition of the seasonal air‐sea carbon flux shows the dominant role of biological carbon pumps that are partially compensated by the transport convergence. Finally, the framework is used to diagnose the response to mesoscale iron and alkalinity release, explicitly quantifying transport feedback and eventual impacts on net air‐sea carbon flux. Ocean carbon transport has divergent influences between iron and alkalinity release, due to opposing near‐surface gradients of dissolved inorganic carbon. We suggest that our attribution framework may be a useful analytical technique for monitoring natural ocean carbon fluxes and quantifying the impacts of human intervention on the ocean carbon cycle.

Ito, Takamitsu [School of Earth and Atmospheric Sc↗

DOE OSTI2025

Dual‐Transformer Deep Learning Framework for Seasonal Forecasting of Great Lakes Water Levels

Abstract The Great Lakes of North America form one of the largest freshwater systems on Earth, and their lake‐wide average water levels (lake levels) can fluctuate by more than 0.5 m on a seasonal scale. These fluctuations pose substantial challenges for coastal resilience, flood risk management, and navigation planning. Accurate seasonal forecasting of lake levels using traditional mechanistic models is challenging due to the complex physical mechanisms and coupled hydroclimatic processes involved. Recently, deep learning has gained prominence in geoscience applications for its ability to recognize intricate patterns within multiphysical data sets. Here, we introduce a novel Dual‐Transformer deep learning framework, tested on the Great Lakes. This architecture integrates two modified Transformer models: the Prophet, which predicts underlying trends, and the Critic, which refines the Prophet's predictions. The final lake level prediction is derived by weighting the outputs of both models through a multi‐layer perceptron, jointly trained with the Prophet and Critic to enhance overall accuracy. Our results demonstrate that the innovative learning framework achieves the highest prediction accuracy compared to established deep learning models when using identical input features. It attains a root mean square error of 4–7 cm in predicting lake levels up to 6 months in advance across the lakes. Additionally, the Dual‐Transformer model runs six orders of magnitude faster than conventional mechanistic models, producing results in less than one second on a typical personal computer. These findings suggest that our deep learning framework has strong potential to advance lake level prediction and carries important implications for water management and disaster mitigation, thereby enhancing the quality of life in coastal regions.

Chen, Yi [Great Lakes Research Center Michigan Tec↗

DOE OSTI2026

A Field Guide to Corralling the Chaos: A Conceptual Framework for Using Models to Guide Opportunistic Field Studies of Natural Disturbances

Watersheds regulate biogeochemical processes and provide ecosystem services to human societies, but disturbances can fundamentally alter these processes across space and time. Determining when and where to sample to capture disturbance impacts in watersheds remains a central challenge. Manipulation studies and long-term monitoring are often constrained by scope, and opportunistic studies often lack pre-disturbance data needed to statistically determine disturbance impacts. We identify a persistent knowledge gap: the absence of a clear, transferable framework to guide opportunistic disturbance research where pre-disturbance data collection is not a feasible option. To address this gap, we present a conceptual framework that intentionally integrates modeling and empirical observation in an iterative, stepwise model–experiment workflow. We demonstrate its application through two contrasting case studies: wildfire impacts on headwater streams using a pre-disturbance preparedness approach, and saltwater flooding impacts on coastal forests using an ‘ex-post-facto’ approach. From these applications, we assess strengths, limitations, and the critical role of team science for transferability across disturbance types and study designs. Broadly, this framework offers a scalable path towards more rigorous, timely, and actionable disturbance science that can inform watershed management, hazard risk reduction, and ecosystem resilience.

Coastal Biogeochemistry↗

DOE OSTI2026

A Framework for Parametric and Predictive Uncertainty Quantification in the E3SM Land Model: Assessing Site and Observable Generalizability

Quantifying parametric uncertainty using observations from individual sites provides a critical foundation for Earth system modeling, serving as a necessary first step before scaling up to regional or global applications. This study introduces a novel computational framework designed to enhance model predictability by reducing parametric uncertainty and assessing site and observable generalizability using various observational constraints. The framework integrates five components: Model Simulation, Statistical Emulation, Global Sensitivity Analysis (GSA), Model Calibration, and Model Prediction. Using the E3SM land model, we simulated site-level land-atmosphere carbon and energy fluxes from 2003 to 2007 across five evergreen needleleaf FLUXNET sites, perturbing 26 vegetation-related model parameters. Gaussian process emulators were employed to expedite GSA and model calibration. Four critical parameters that strongly influence selected land-atmosphere fluxes were identified by GSA. Bayesian approaches were used to infer parameter probability distributions leveraging synthetic data and FLUXNET observations. The results reveal that posterior parameter distributions vary significantly across different sites and observables within the same plant functional type. Probabilistic predictions indicate that parameters calibrated at one site can enhance predictive accuracy at other sites, although site heterogeneity may sometimes outweigh parametric uncertainty. Additionally, the probabilistic predictions demonstrate that calibration for one variable can also improve predictability for other variables, thereby maximizing predictive capabilities with limited observations. This framework provides a powerful approach for reducing parametric uncertainty in Earth system models and deepening our understanding of carbon dynamics and energy cycles. Its adaptability makes it a valuable tool for broader applications in Earth system modeling.

54 ENVIRONMENTAL SCIENCES↗