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At least 667 records · Page 37

Spin Coupling Effect on Geometry-Dependent X-Ray Absorption of Diradicals

Here, we theoretically investigate the influence of diradical electron spin coupling on the time-resolved X-ray absorption spectra of the photochemical ring opening of furanone. We predict geometry-dependent carbon K-edge signals involving transitions from core orbitals to both singly and unoccupied molecular orbitals. The most obvious features of the ring opening come from the carbon atom directly involved in the bond breaking through its transition to both the newly formed singly occupied and the available lowest unoccupied molecular orbitals (SOMO and LUMO, respectively). In addition to this primary feature, the singlet spin coupling of four unpaired electrons that arises in the core-to-LUMO states creates additional geometry dependence in some spectral features with both oscillator strengths and relative excitation energies varying observably as a function of the ring opening. We attribute this behavior to a spin-occupancy-induced selection rule, which occurs when singlet spin coupling is enforced in the diradical state. Notably, one of these geometry-sensitive core-to-LUMO transitions excites core electrons from a backbone carbon not involved in the bond breaking, providing a novel nonlocal X-ray probe of chemical dynamics arising from electron spin coupling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Control over Charge Separation by Imine Structural Isomerization in Covalent Organic Frameworks with Implications on CO 2 Photoreduction

Two-dimensional covalent organic frameworks (COFs) are an emerging class of photocatalytic materials for solar energy conversion. In this work, we report a pair of structurally isomeric COFs with reversed imine bond directions, which leads to drastic differences in their physical properties, photophysical behaviors, and photocatalytic CO 2 reduction performance after incorporating a Re(bpy)(CO) 3 Cl molecular catalyst through bipyridyl units on the COF backbone (Re-COF). Using the combination of ultrafast spectroscopy and theory, we attributed these differences to the polarized nature of the imine bond that imparts a preferential direction to intramolecular charge transfer (ICT) upon photoexcitation, where the bipyridyl unit acts as an electron acceptor in the forward imine case (f-COF) and as an electron donor in the reverse imine case (r-COF). These interactions ultimately lead the Re-f-COF isomer to function as an efficient CO 2 reduction photocatalyst, while the Re-r-COF isomer shows minimal photocatalytic activity. Furthermore, these findings not only reveal the essential role linker chemistry plays in COF photophysical and photocatalytic properties but also offer a unique opportunity to design photosensitizers that can selectively direct charges.

14 SOLAR ENERGY↗

Metal-Tuned Ligand Reactivity Enables CX 2 (X = O, S) Homocoupling with Spectator Cu Centers

Ligand non-innocence is ubiquitous in catalysis with ligands in synthetic complexes contributing as electron reservoirs or co-sites for substrate activation. The latter chemical non-innocence is manifested in H + storage or relay at sites beyond the metal primary coordination sphere. Reaction of a competent CO 2 -to-oxalate reduction catalyst, namely, [K(THF) 3 ](Cu 3 SL), where L 3– is a tris(β-diketiminate) cyclophane, with CS 2 affords tetrathiooxalate at long reaction times or at high CS 2 concentrations, where otherwise an equilibrium is established between the starting species and a complex–CS 2 adduct in which the CS 2 is bound to the C atom on the ligand backbone. X-ray diffraction analysis of this adduct reveals no apparent metal participation, suggesting an entirely ligand-based reaction controlled by the charge state of the cluster. Here, thermodynamic parameters for the formation of the aforementioned Cligand–CS 2 bond were experimentally determined, and trends with cation Lewis acidity were studied, where more acidic cations shift the equilibrium toward the adduct. Relevance of such an adduct in the reduction of CO 2 to oxalate by this complex is supported by DFT studies, similar effects of countercation Lewis acidity on product formation, and the homocoupled heterocumulene product speciation as determined by isotopic labeling studies. Taken together, this system extends chemical non-innocence beyond H + to effect catalytic transformations involving C–C bond formation and represents the rarest example of metal–ligand cooperativity, that is, spectator metal ion(s) and the ligand as the reaction center.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Can the Rate of a Catalytic Turnover Be Altered by Ligands in the Absence of Direct Binding Interactions?

Second sphere coordination effects ubiquitous in enzymatic catalysis occur through direct interactions, either covalent or non-covalent, with reaction intermediates and transition states. Here, we present herein evidence of indirect second sphere coordination effects in which ligation of water/alkanols far removed from the primary coordination sphere of the active site nevertheless alter energetic landscapes within catalytic redox cycles in the absence of direct physicochemical interactions with surface species mediating catalytic turnovers. Density functional theory, in situ X-ray absorption and infrared spectroscopy, and a wide array of steady-state and transient CO oxidation rate data suggest that the presence of peripheral water renders oxidation half-cycles within two-electron redox cycles over μ m -oxo-bridged trimers in MIL-100(M) more kinetically demanding. Communication between ligated water and the active site appears to occur through the Fe-O-Fe backbone, as inferred from spin density variations on the central μ m -oxygen 'junction'. Evidence is provided for the generality of these second sphere effects in that they influence different types of redox half-cycles or metals, and can be amplified or attenuated through choice of coordinating ligand. Specifically in the case of MIL-100(M) materials, the Cr isostructure can be made to kinetically mimic the Fe variant by disproportionately hindering oxidation half-cycles relative to the reduction half-cycles. Kinetic and spectroscopic inferences presented here significantly expand both the conceptual definition of second sphere effects as well as the palette of synthetic levers available for tuning catalytic redox performance through chemical ligation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure–Function Insights into Thermoresponsive Copolymers as Lanthanide Precipitants

The synthetic toolbox for stimuli-responsive polymers has broadened to include many tunable variables, making these materials applicable in diverse technologies. However, unraveling the key composition–structure–function relationships to facilitate ground-up design remains a challenge due to the inherent dispersity in sequence and conformations for synthetic polymers. We here present a systematic study of these relationships using a model system of copolymers with a thermoresponsive (N-isopropylacrylamide) backbone in addition to metal-chelating (acrylic acid) and hydrophobic structural comonomers and evaluate their efficiency at isolating technologically critical lanthanide ions. The efficiency of lanthanide ion extraction by precipitation was quantitated with a metallochromic dye to reveal trends relating copolymer hydrophobicity to improved separations. Further, we examined the role of different hydrophobic comonomers in dictating the solution-phase conformation of the polymer in the presence and absence of lanthanide ions, and we correlated key features of the hydrophobic comonomer to extraction efficiency. Lastly, we identified how the local proximity of thermoresponsive, chelating, and hydrophobic subunits facilitates metal extraction by manipulating the copolymer sequence with multiblock polymerization. Through mechanistic analysis, we propose a binding-then-assembly process through which metal ions are coprecipitated with macromolecular chelators.

Copolymers↗

Sustained, Selective, and Efficient Photochemical CO 2 Reduction to Formate by Electron-Deficient Ruthenium Polypyridyl Complexes

Metal-hydrides play a significant role in a variety of reactions, including chemical, electrochemical, and pho-tochemical CO 2 reduction. Molecular metal-hydrides have the distinct advantage of allowing tunability of their hydricities by rational ligand modifications, with more electron-rich metal-hydrides being in general more hydridic. We report here a new approach to generate highly hydridic metal hydrides of the type [Ru(tpy)(LL)(H)] n+ by introducing electron-withdrawing substituents in the backbone of the bidentate LL ligand. This strategy enables the generation of the metal hydride, [Ru(tpy)(LL)(H)] + , at mild negative potentials and further one electron reduction to the more hydridic [Ru(tpy)(LL)(H)] 0 at a potential window that is redox silent for the more electron-rich metal hydride analogue [Ru(tpy)(bpy)(H)] + . In addition, for-mate release takes place from the hydride transfer adducts [Ru---HCOO)(tpy)(LL)] 0 rather than from the corresponding formato complexes, [Ru(tpy)(LL)(OCHO)] 0 , which would require further reduction to [Ru(tpy)(LL)(OCHO)]ˉ as demonstrated by IR-spectroelectrochemistry. The parent [Ru(tpy)(LL)(CH 3 CN)] n+ solvento complexes were then tested as catalysts for the reduction of CO 2 to formate in a 4-component homogenenous photochemical approach driven by a Ru(II) sensitizer. The re-sults showed selective (> 88%) formate production with record turnover number of ~50,000 and record turnover frequency of 4.4 s -1 when compared to other molecular catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elucidating Quintet-State Dynamics in Singlet Fission Oligomers and Polymers with Tetracene Pendants

To unlock the potential of molecular engineering for practical quantum sensing and computing, it is essential to create and control pure magnetic states in molecular systems. Singlet fission (SF) in organic materials offers a promising approach by generating pairs of triplet excited states from photoexcited singlets. Here, in this work, we investigate SF in a polymer with strategically positioned tetracene pendant groups along a polynorbornene backbone and its oligomeric counterparts, facilitating intrapolymer through-space coupling. Using continuous-wave and pulsed time-resolved electron paramagnetic resonance (EPR) spectroscopy, we elucidate the spin dynamics and identify key intermediates, including the quintet state, that emerge during SF. Our findings reveal that exciton translational motion along the pendant groups enhances the dissociation of triplet pairs, with oligomer length playing a critical role in modulating spin state interconversion and exciton transport. Our results provide key insights into the SF mechanism in polymeric materials and highlight the role of oligomer length in modulating spin state interconversion and exciton transport. This work advances our understanding of SF in polymers, paving the way for their application in quantum information science and energy conversion technologies.

Bindra, Jasleen K. [Argonne National Laboratory (A↗

Electrochemically Initiated Depolymerization of Poly(Methyl Methacrylate)

Efficient depolymerization of polymers with all-carbon backbones under mild conditions would be valuable in chemically recycling commodity plastics. Poly(methyl methacrylate) (PMMA) is a commodity thermoplastic that is currently depolymerized under temperatures in excess of 400 °C. Herein, we lower the temperatures needed to achieve depolymerization of PMMA by performing radical generation and depropagation with orthogonal stimuli. This first demonstration of electrochemically initiated PMMA depolymerization relies on reduction of phthalimide esters that, upon subsequent decarboxylation, generate polymer-centered radicals. These radicals then spontaneously unzip the polymer back to its monomeric constituents at temperatures as low as 105 °C. We studied the mechanism and efficiency of this transformation as a function of phthalimide ester placement, incorporation density, and polymer molecular weight. We found that chain-end activation is effective for modest molecular weights but suffers diminished efficiency at higher degrees of polymerization. In contrast, pendent-group activation is more effective for depolymerizing higher molecular weight species. Integrating higher molar amounts of phthalimide ester pendants leads to more effective depolymerization, with >95% depolymerization in copolymers with 5 mol% phthalimide ester incorporation. We leveraged this understanding to create a custom electro-distillation apparatus that allowed us to simultaneously electrochemically depolymerize PMMA and directly distill methyl methacrylate in >22% yield, which could ultimately be repolymerized. These findings establish electrochemistry as a versatile and orthogonal stimulus for vinyl polymer depolymerization and provide a foundation for closed-loop electrochemical recycling of widely used plastics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomic-Scale Imaging Reveals Polar-π Interactions in Two-Dimensional Molecular Superlattices

Controlling coassembly of synthetic oligomers into binary superlattices at the atomic level is challenging. Here, we report a strategy for programming polar-π interactions in oligomeric peptoids, a class of sequence-defined peptidomimetics, facilitating the formation of homogeneous two-dimensional (2D) superlattices. N-2-phenylethyl and N-(2-perfluorophenyl)ethyl side chains, similar in size, but with contrasting electrostatic characteristics, were introduced at defined sequence positions to generate favorable dipolar aromatic interactions. The resulting nanosheets exhibit different crystal motifs depending on the side chain interactions: systems containing only one type of aromatic side chain form a parallel V-shaped motif driven by π-π interactions, whereas a combination of both types of aromatic side chains, either within one backbone or through the coassembly of two distinct peptoids, adopt an antiparallel V-shaped superlattice with higher thermal stability, driven by polar-π interactions. Cryogenic transmission electron microscopy directly resolved the packing arrangement of perfluorophenyl and phenyl rings in individual nanosheet superlattices, confirming that intermolecular polar-π interaction dominates the superlattice motifs and increases lattice stability. Molecular dynamics simulations and density functional theory calculations further substantiate the energetic favorability of polar-π interactions over π-π interactions, rationalizing the formation of homogeneous superlattices with enhanced thermal stability. Our discoveries establish a design principle for binary coassembly using sequence-defined oligomers, which enables control over unit cell geometry, lattice stability, and molecular registration through aromatic side chain polarization and sequence control. This ability to program atomic-scale binary superlattices opens new avenues for designing functional 2D soft materials.

Lee, Yen Jea [Lawrence Berkeley National Laborator↗

Pseudo–Jahn–Teller Distortion in a One-Dimensional π-Conjugated Polymer

Structural distortions in low-dimensional π-conjugated systems profoundly influence their electronic properties, but the control of such behavior in laterally extended systems remains challenging. Here, in this study, we demonstrate that a one-dimensional conjugated polymer─ poly -(difluorenoheptalene-ethynylene) (PDFHE)─undergoes a pronounced out-of-plane backbone distortion, equivalent to a spontaneous symmetry breaking (SSB) of its mirror symmetry. We synthesized PDFHE on noble metal surfaces and characterized its structure and electronic states using low-temperature scanning tunneling microscopy (STM). Rather than adopting a planar, high-symmetry conformation, PDFHE relaxes into nonplanar isomers stabilized by a pseudo–Jahn–Teller (PJT) distortion having mirror-odd out-of-plane character. The distortion lowers the total energy and increases the band gap, providing a concise rationale for the observed symmetry breaking. Density functional theory calculations corroborate these findings, providing a microscopic explanation for the SSB. Our results show that even in mechanically robust extended π-systems, subtle electron–lattice coupling can spontaneously drive significant structural rearrangements, even in mechanically robust extended π-systems.

conformation↗

Interfacial Inversion of Stealth Surfactants

Amphiphilic macromolecular surfactants segregate to liquid–liquid interfaces, thereby reducing the interfacial tension and free energy. Here, we investigated “stealth surfactants” in the form of core–shell bottlebrush polymers comprised of pH-responsive diblock copolymer side chains forming a hydrophilic core and a hydrophobic shell, enabling solubility in oil. At liquid–liquid interfaces, these polymers undergo a structural “inversion”, with hydrophilic blocks segregating into the aqueous phase and hydrophobic blocks residing in the oil phase. The reconfiguration kinetics and surfactant properties are influenced by multiple factors, including the molecular weights of the backbone and side chain components, the hydrophilic-to-hydrophobic balance of the side chains, and the pH of the aqueous phase. An observed nonmonotonic dependence of interfacial tension with time is attributed to a progressive structural inversion, where the projected area of the macromolecule onto the interface decreases. To validate this inversion hypothesis, interfacial properties were characterized by sum-frequency generation vibrational spectroscopy, which revealed configurational changes of the core–shell bottlebrush polymers at the fluid interface and revealed a pH-dependent interfacial coverage. Coarse-grained molecular dynamics simulations supported these experimental findings, showing that the pH-responsive core and hydrophobic shell assume a time-averaged configuration with orientations parallel and perpendicular to the plane of the interface, respectively. These findings open routes to design multistimuli-responsive polymeric surfactants and compatibilizers, expanding their potential applications in advanced interfacial systems.

Stealth surfactants↗

Concerted Electron-Ion Transport by Polyacrylonitrile Elucidated with Reactive Deep Learning Potentials

Charge transport in polymers, such as polyacrylonitrile (PAN), is crucial for electronics and energy storage. For instance, PAN can transport cations e.g., Li + , by facilitating dynamic cation-nitrile coordination in batteries. However, little is known regarding the underlying role of complex reactive polymer configurations. Herein, we develop a deep-learning potential, trained on ab initio energies and forces of nonequilibrium reactive PAN configurations, to unravel the kinetics of PAN cyclization initiated by a nucleophile (OH – dissociated from LiOH) attacking the terminal nitrile carbon. We find, based on the reaction free-energetics, rates, and charge analysis, that the nucleophile attack producing the first ring is the rate-limiting step, which subsequently triggers Li + -coupled electron transfer along the PAN backbone, causing ∼10 4 times faster sequential ring-formation of the remaining nitriles. PAN’s extended configurations, where dipolar and H-bonding interactions are minimal, enable such rapid kinetics. By validating our computational findings with IR and NMR experiments, we establish a pathway for designing reactive polymers with enhanced charge transport for energy applications.

Chahal-Crockett, Rajni [Oak Ridge National Laborat↗

Unraveling the Luminescence Quenching Mechanism in Strong and Weak Quantum-Confined CsPbBr 3 Triggered by Triarylamine-Based Hole Transport Layers

Luminescence quenching by hole transport layers (HTLs) is one of the major issues in developing efficient perovskite light-emitting diodes (PeLEDs), particularly prominent in blue-emitting devices. While a variety of material systems have been used as interfacial layers, the origin of such quenching and the type of interactions between perovskites and HTLs are still ambiguous. Here, we present a systematic investigation of the luminescence quenching of CsPbBr 3 by a commonly employed hole transport polymer, Poly(9,9-dioctylfluorene-alt-N-(4-sec-butylphenyl)-diphenylamine) (TFB) in LEDs. Strong and weakly quantum-confined CsPbBr 3 (nanoplatelets (NPLs)/nanocrystals (NCs)) are rationally selected to study the quenching mechanism by considering the differences in their morphology, energy level alignments, and quantum confinement. The steady-state and time-resolved Stern-Volmer plots unravel the dominance of dynamic and static quenching at lower and higher concentrations of TFB, respectively, with maximum quenching efficiency of 98%. The quenching rate in NCs is faster than in NPLs owing to their longer PL lifetimes and weak quantum confinement. The ultrafast transient absorption results support these dynamics and rule out the involvement of Forster or Dexter energy transfer. Finally, the 1D 1 H and 2D NOESY NMR study confirms the exchange of native ligands at the NCs surface with TFB, leading to dark CsPbBr 3 -TFB ensemble formation accountable for luminescence quenching. This highlights the critical role of the triarylamine functional group on TFB (also the backbone of many HTLs) in the quenching process. These results shed light on the underlying reasons for the luminescence quenching in PeLEDs and will help to choose the interfacial layers rationally for developing efficient LEDs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design and Evaluation of Pyridinyl Sulfonyl Piperazine LpxH Inhibitors with Potent Antibiotic Activity Against Enterobacterales

Enterobacterales, a large order of Gram-negative bacteria, including Escherichia coli and Klebsiella pneumoniae, are major causes of urinary tract and gastrointestinal infections, pneumonia, and other diseases in healthcare settings and communities. ESBL-producing Enterobacterales and carbapenem-resistant Enterobacterales can break down commonly used antibiotics, with some strains being resistant to all available antibiotics. This public health threat necessitates the development of novel antibiotics, ideally targeting new pathways in these bacteria. Gram-negative bacteria possess an outer membrane enriched with lipid A, a saccharolipid that serves as the membrane anchor of lipopolysaccharides and the active component of the bacterial endotoxin, causing septic shock. The biosynthesis of lipid A is crucial for the viability of Gram-negative bacteria, and as an essential enzyme in this process, LpxH has emerged as a promising target for developing novel antibiotics against multidrugresistant Gram-negative pathogens. Here, we report the development of pyridinyl sulfonyl piperazine LpxH inhibitors. Among them, ortho-substituted pyridinyl compounds significantly boost LpxH inhibition and antibiotic activity over the original phenyl series. Structural and QM/MM analyses reveal that these improved activities are primarily due to the enhanced interaction between F141 of the LpxH insertion lid and the pyridinyl group. Incorporation of the N-methyl-N-phenyl-methanesulfonamide moiety into the pyridinyl sulfonyl piperazine backbone results in JHLPH- 106 and JH-LPH-107, both of which exhibit potent antibiotic activity against wild-type Enterobacterales such as K. pneumoniae and E. coli. JH-LPH-107 exhibits a low rate of spontaneous resistance and a high safety window in vitro, rendering it an excellent lead for further clinical development.

60 APPLIED LIFE SCIENCES↗

A Robust Methodology to Elucidate Kinetics of Room Temperature Electrochemical Propane Adsorption on Platinum

Electrocatalytic activation of alkanes can further decarbonize chemical manufacturing by leveraging affordable renewable electricity and readily available shale gas reserves in the United States. Earlier works have identified the unique role of Pt in adsorbing and activating alkanes, like propane, at room temperature in acidic, aqueous electrolytes, revealing spontaneous formation of deeply dehydrogenated propane-derived surface species with an intact C 3 - backbone. Although an adsorption mechanism was hypothesized, it has not been explicitly investigated to date, preventing the quantification of kinetic rate parameters. A robust methodology to investigate and benchmark propane adsorption kinetics on Pt is critical for the rational design of electrocatalysts that exhibit higher selectivity toward desired partially oxidized products. Herein, we analyze an oxidative current transience that appears during the adsorption of propane on Pt in aqueous electrochemical conditions and develop a methodology that elucidates the adsorption mechanism and enables quantification of rate parameters such as order dependences and apparent activation barriers. This method yields an expected first-order dependence with respect to propane concentration at low coverage and reveals a second-order dependence with respect to the concentration of surface active sites. Additionally, the apparent activation barrier for propane adsorption was calculated using an Arrhenius analysis of the current transience under temperature control. The experimentally measured activation barrier of 35 kJ mol –1 is in excellent agreement with the theoretical barrier calculated by density functional theory (DFT). The kinetic analysis was extended, via the use of transition state theory, to extract entropy and enthalpy of activation, yielding consistent results with the proposed two-step adsorption mechanism and DFT calculations. These results demonstrate reliable quantification of kinetic parameters for electrocatalytic activation of C–H bonds in alkanes that can be employed for rational catalyst development for a versatile range of electrocatalytic conditions.

alkane activation↗

An End-To-End Earthquake Detection Method for Joint Phase Picking and Association Using Deep Learning

Earthquake monitoring by seismic networks typically involves a workflow consisting of phase detection/picking, association, and location tasks. In recent years, the accuracy of these individual stages has been improved through the use of machine learning techniques. Here, in this study, we introduce a new end-to-end approach that improves overall earthquake detection accuracy by jointly optimizing each stage of the detection pipeline. We propose a neural network architecture for the task of multi-station processing of seismic waveforms recorded over a seismic network. This end-to-end architecture consists of three sub-networks: a backbone network that extracts features from raw waveforms, a phase picking sub-network that picks P- and S-wave arrivals based on these features, and an event detection sub-network that aggregates the features from multiple stations to associate and detect earthquakes across a seismic network. We use these sub-networks together with a shift-and-stack module based on back-projection that introduces kinematic constraints on arrival times, allowing the neural network model to generalize to different velocity models and to variable station geometry in seismic networks. We evaluate our proposed method on the STanford EArthquake Dataset (STEAD) and on the 2019 Ridgecrest, CA earthquake sequence. The results demonstrate that our end-to-end approach can effectively pick P- and S-wave arrivals and achieve earthquake detection accuracy rivaling that of other state-of-the-art approaches. Because our approach preserves information across tasks in the detection pipeline, it has the potential to outperform approaches that do not.

58 GEOSCIENCES↗

Differentiable, Learnable, Regionalized Process-Based Models With Multiphysical Outputs can Approach State-Of-The-Art Hydrologic Prediction Accuracy

Predictions of hydrologic variables across the entire water cycle have significant value for water resources management as well as downstream applications such as ecosystem and water quality modeling. Recently, purely data-driven deep learning models like long short-term memory (LSTM) showed seemingly insurmountable performance in modeling rainfall runoff and other geoscientific variables, yet they cannot predict untrained physical variables and remain challenging to interpret. Here, we show that differentiable, learnable, process-based models (called δ models here) can approach the performance level of LSTM for the intensively observed variable (streamflow) with regionalized parameterization. We use a simple hydrologic model HBV as the backbone and use embedded neural networks, which can only be trained in a differentiable programming framework, to parameterize, enhance, or replace the process-based model's modules. Without using an ensemble or post-processor, δ models can obtain a median Nash-Sutcliffe efficiency of 0.732 for 671 basins across the USA for the Daymet forcing data set, compared to 0.748 from a state-of-the-art LSTM model with the same setup. For another forcing data set, the difference is even smaller: 0.715 versus 0.722. Meanwhile, the resulting learnable process-based models can output a full set of untrained variables, for example, soil and groundwater storage, snowpack, evapotranspiration, and baseflow, and can later be constrained by their observations. Both simulated evapotranspiration and fraction of discharge from baseflow agreed decently with alternative estimates. The general framework can work with models with various process complexity and opens up the path for learning physics from big data.

54 ENVIRONMENTAL SCIENCES↗

High‐Resolution National‐Scale Water Modeling Is Enhanced by Multiscale Differentiable Physics‐Informed Machine Learning

Abstract The National Water Model (NWM) is a key tool for flood forecasting, planning, and water management. Key challenges facing the NWM include calibration and parameter regionalization when confronted with big data. We present two novel versions of high‐resolution (∼37 km 2 ) differentiable models (a type of hybrid model): one with implicit, unit‐hydrograph‐style routing and another with explicit Muskingum‐Cunge routing in the river network. The former predicts streamflow at basin outlets whereas the latter presents a discretized product that seamlessly covers rivers in the conterminous United States (CONUS). Both versions use neural networks to provide a multiscale parameterization and process‐based equations to provide a structural backbone, which were trained simultaneously (“end‐to‐end”) on 2,807 basins across the CONUS and evaluated on 4,997 basins. Both versions show great potential to elevate future NWM performance for extensively calibrated as well as ungauged sites: the median daily Nash‐Sutcliffe efficiency of all 4,997 basins is improved to around 0.68 from 0.48 of NWM3.0. As they resolve spatial heterogeneity, both versions greatly improved simulations in the western CONUS and also in the Prairie Pothole Region, a long‐standing modeling challenge. The Muskingum‐Cunge version further improved performance for basins >10,000 km 2 . Overall, our results show how neural‐network‐based parameterizations can improve NWM performance for providing operational flood predictions while maintaining interpretability and multivariate outputs. The modeling system supports the Basic Model Interface (BMI), which allows seamless integration with the next‐generation NWM. We also provide a CONUS‐scale hydrologic data set for further evaluation and use.

Song, Yalan [Civil and Environmental Engineering T↗