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DOE OSTI2025

Nearby Sites Show Similar Upwind Sources and Differing Semivolatile Concentrations in Coastal Aerosol Particles

The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) characterized aerosol composition using measurements at two sites within 3 km (Scripps Pier and Mt. Soledad) from 15 February 2023 to 14 February 2024. Comparing the two sites shows the strong influence of upwind sources that results in similar monthly compositions at both sites. The seasonal changes in chemical mass concentrations were largely driven by the upwind source regions, with coastal northwesterly back-trajectories occurring 63−65% of the year and bringing submicrometer mass concentrations that were lower than the EPCAPE average for all trajectories at each site. In contrast, refractory black carbon (rBC) and nonrefractory (NR)-organics and nitrate mass concentrations exceeded EPCAPE average concentrations for back-trajectories from urban areas such as Los Angeles-Long Beach. For hourly measurements, NR-organics and non-sea-salt (NSS)-sulfate mass concentrations at Mt. Soledad were correlated strongly (r = 0.73−0.82) to those measured at Scripps Pier, but NR-nitrate was correlated only moderately (r = 0.63). The explanation for the lower correlation of NR-nitrate is both emissions between the sites and semivolatility, with semivolatility accounting for site-to-site changes in daily averages of +0.01 μg m −3 per percentage site-to-site difference in relative humidity and −0.07 μg m −3 per degree Celsius site-to-site difference in temperature. On average, comparing Scripps Pier to Mt. Soledad, NR-nitrate was higher by 29% because of relative humidity and lower by −26% because of temperature. NR-nitrate and rBC mass concentrations at Scripps Pier for nighttime were 13−15% higher than those for daytime because land breezes brought higher inland concentrations. Concentrations of rBC were 52% higher at Mt. Soledad than those measured at Scripps Pier, accompanied by increases in tracers for brake wear because of traffic on the steep roads within 10 m of that site. The implications are that these nearby sites had comparable monthly concentrations of measured components due to their similar backtrajectories, but hourly and daily concentration differences supported quantification of the meteorological effects from relative humidity and temperature on semivolatile NR-nitrate as well as minor differences from land−sea breezes and local emissions.

Aerosols↗

DOE OSTI2025

Origin of Heating-Induced Softening and Enthalpic Reinforcement in Elastomeric Nanocomposites

Molecular simulations demonstrate that the enthalpic softening of elastomeric nanocomposites upon heating can arise naturally from a Poisson’s ratio mismatch between elastomer and nanoparticle networks, providing a more parsimonious explanation for this phenomenon than the widely accepted interpretation based on glassy interparticle bridging. Despite a century of use, the mechanism of nanoparticle-driven mechanical reinforcement of elastomers is unresolved. Here, a major hypothesis attributes it to glassy interparticle bridges, supported by an observed inversion of the variation of the modulus E(T) on heating – from entropic stiffening in elastomers to enthalpic softening in nanocomposites. Here, molecular simulations reveal that elastomer enthalpic softening can instead emerge from a competition over the preferred volumes between elastomer and nanoparticulate networks. A theory for this competition accounting for softening of the bulk modulus on heating predicts the simulated E(T) inversion, suggesting that reinforcement is driven by a volume-competition mechanism unique to cocontinuous systems of soft and rigid networks.

Biopolymers↗

DOE OSTI2025

Excitation Laser Energy Dependence of the Gap-Mode TERS Spectra of WS 2 and MoS 2 on Silver

In this work we present a systematic study of the dependence of the gap mode tip-enhanced Raman scattering (TERS) response of the mono- and bi-layer WS 2 and MoS 2 on silver as a function of the excitation laser energy in a broad spectral range from 473nm to 830 nm. For this purpose, we collected consecutive TERS maps of the same area in the sample containing mono-and bi-layer regions with the same TERS probe with 6 different excitation lasers. To decrease the number of collected TERS maps, we used for the first time to the best of our knowledge, concurrent excitation and collection with two lasers simultaneously. We found that the E 2g /A 1g peak intensity ratio for the bilayer WS 2 @Ag and the ratio of the A’/A 1g peak intensity of the out-of-plane mode for the mono- and the bilayer, change in a significantly non-monotonous way as the excitation laser energy is swept from 1.58 eV to 2.62 eV. The former ratio increases at energies corresponding to A and B excitons (~2.0 eV and 2.4 eV correspondingly) in bilayer WS 2 . The absolute intensity of the A’ peak in the monolayer, and correspondingly the A’/A 1g ratio, is surprisingly high at lower excitation energies, but dips dramatically at the energy corresponding to the A exciton, being restored partially in between A and B excitons, but still showing the descending trend as the excitation laser energy increases. A somewhat similar picture was observed in mono- and bi-layers of MoS 2 @Ag, though the existing set of excitation lasers did not match the excitonic profile of this material as nicely as for the case of WS 2 . We attribute the observed behavior to the presence of intermediate (Fano resonance) or strong (Rabi splitting) coupling between the excitons in transition metal dichalcogenides (TMDs) and the plasmons in the tip-substrate nanocavity. This is akin to the so-called Fano (Rabi) transparency experimentally observed in far field scattering from transition metal dichalcogenides between two plasmonic metals. The possibility of the formation of intermediate/strong coupling between the excitonic resonances in TMDs and the nanocavity re-evaluates the role of various resonances in the gap-mode TERS and should become an important factor to be considered by TERS practitioners during planning the experiments. Lastly, based on observed phenomena and its explanation, we propose the “ideal” substrate for efficient TERS and tip enhanced photoluminescence (TEPL) measurements.

Raman spectroscopy↗

DOE OSTI2024

High-Throughput Screening and Accurate Prediction of Ionic Liquid Viscosities Using Interpretable Machine Learning

Ionic liquids (ILs) are a novel group of green solvents with great promise for various industrial applications, including carbon capture and lignocellulosic biomass deconstruction. However, the use of ILs at the industrial scale remains challenging due to their high viscosities at ambient temperatures. To develop ILs with lower viscosities, a systematic study of their quantitative structure–property relationship (QSPR) is desirable. Here, we developed four machine learning (ML) models to predict viscosity at various temperature and pressure ranges, trained over a wide range of ILs consisting of various cationic and anionic families. ML methods including two-factor polynomial regression (two-factor PR), support vector regression (SVR), feed-forward neural networks (FFNN), and categorical boosting (CATBoost) were developed based on features that have proven useful in previous ML studies: COSMO-RS (conductor-like screening model for real solvents)-derived surface screening charge densities (sigma profiles). FFNN and CATBoost were the most accurate in predicting IL viscosities with lower average absolute relative deviation and higher R2 values on the test set. Tanimoto similarity scores were calculated to characterize the chemical space and structural similarity of the investigated ions. Furthermore, SHapley Additive exPlanation (SHAP) analysis was employed to interpret the ML results. Temperature, the polar area of ILs, and the nonpolar regions of ions are key features that influence the viscosity predictions. Importantly, the IL viscosity prediction here is the most accurate reported to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Characterizing Variability in Lignocellulosic Biomass: A Review

Feedstock variability is a significant barrier to the scale-up and commercialization of lignocellulosic biofuel technologies. Variability in feedstock characteristics and behavior creates numerous challenges to the biorefining industry by affecting continuous operation and biofuels yields. Recently, feedstock variability is understood and explained largely on the basis of chemical composition. Physical and mechanical properties and behavior of lignocellulosic feedstock in various unit operations, studied through advanced analytical methods, can further explain variability. Such studies will enable us in developing processes and designing equipment to improve operation and conversion performance. In this perspective, we review several advanced analytical methods that measure density, moisture content, thermal properties, flowability, grindability, rheology properties, and micromorphological characteristics. We also discuss the correlations and interactions among these properties that reflect the complexity of lignocellulosic biomass as a feedstock and the associated quality metrics and logistics of supplying consistent quality feedstock to a biorefinery. We further examine methods that have not traditionally been used to characterize lignocellulosic feedstocks but have the potential to bridge the gap in our explanation of feedstock variability.

09 BIOMASS FUELS↗

DOE OSTI2020

Crystallizing Atomic Xenon in a Flexible MOF to Probe and Understand Its Temperature-Dependent Breathing Behavior and Unusual Gas Adsorption Phenomenon

Flexible metal–organic frameworks (MOFs) hold great promise as smart materials for specific applications such as gas separation. These materials undergo interesting structural changes in response to guest molecules, which is often associated with unique adsorption behavior not possible for rigid MOFs. Understanding the dynamic behavior of flexible MOFs is crucial yet challenging as it involves weak host–guest interactions and subtle structural transformation not only at the atomic/molecular level but also in a nonsteady state. Here we report an in-depth study on the adsorbate- and temperature-dependent adsorption in a flexible MOF by crystallizing atomic gases into its pores. Mn(ina)2 shows an interesting temperature-dependent response toward noble gases. Its nonmonotonic, temperature-dependent adsorption profile results in an uptake maximum at a temperature threshold, a phenomenon that is unusual. Full characterization of Xe-loaded MOF structures is performed by in situ single-crystal and synchrotron X-ray diffraction, IR spectroscopy, and molecular modeling. The X-ray diffraction analysis offers a detailed explanation into the dynamic structural transformation and provides a convincing rationalization of the unique adsorption behavior at the molecular scale. The guest and temperature dependence of the structural breathing gives rise to an intriguing reverse of Xe/Kr adsorption selectivity as a function of temperature. The presented work may provide further understanding of the adsorption behavior of noble gases in flexible MOF structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Ring-Opening Dynamics of the Cyclopropyl Radical and Cation: the Transition State Nature of the Cyclopropyl Cation

Here, we provide compelling experimental and theoretical evidence for the transition state nature of the cyclopropyl cation. Synchrotron photoionization spectroscopy employing coincidence techniques together with a novel simulation based on high-accuracy ab initio calculations reveal that the cation is unstable via its allowed disrotatory ring-opening path. The ring strains of the cation and the radical are similar, but both ring opening paths for the radical are forbidden when the full electronic symmetries are considered. These findings are discussed in light of the early predictions by Longuet-Higgins alongside Woodward and Hoffman; we also propose a simple phase space explanation for the appearance of the cyclopropyl photoionization spectrum. The results of this work allow the refinement of the cyclopropane C–H bond dissociation energy, in addition to the cyclopropyl radical and cation cyclization energies, via the Active Thermochemical Tables approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Tuning the Type 1 Reduction Potential of Multicopper Oxidases: Uncoupling the Effects of Electrostatics and H-Bonding to Histidine Ligands

In multicopper oxidases (MCOs), the type 1 (T1) Cu accepts electrons from the substrate and transfers these to the trinuclear Cu cluster (TNC) where O 2 is reduced to H 2 O. The T1 potential in MCOs varies from 340 to 780 mV, a range not explained by the existing literature. Here, this study focused on the ~350 mV difference in potential of the T1 center in Fet3p and Trametes versicolor laccase (TvL) that have the same 2His1Cys ligand set. A range of spectroscopies performed on the oxidized and reduced T1 sites in these MCOs shows that they have equivalent geometric and electronic structures. However, the two His ligands of the T1 Cu in Fet3p are H-bonded to carboxylate residues, while in TvL they are H-bonded to noncharged groups. Electron spin echo envelope modulation spectroscopy shows that there are significant differences in the second-sphere H-bonding interactions in the two T1 centers. Redox titrations on type 2-depleted derivatives of Fet3p and its D409A and E185A variants reveal that the two carboxylates (D409 and E185) lower the T1 potential by 110 and 255–285 mV, respectively. Density functional theory calculations uncouple the effects of the charge of the carboxylates and their difference in H-bonding interactions with the His ligands on the T1 potential, indicating 90–150 mV for anionic charge and ~100 mV for a strong H-bond. Finally, this study provides an explanation for the generally low potentials of metallooxidases relative to the wide range of potentials of the organic oxidases in terms of different oxidized states of their TNCs involved in catalytic turnover.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Supersaturation, Nucleation, and Phase Separation of Mesoscopic Systems

Supersaturation, nucleation, and phase separation are ubiquitous phenomena of great interest in both science and industry. However, a unified, quantitative understanding of these phenomena has yet to be achieved for mesoscopic systems. Here, we present a set of general equations that determine the monomer saturation degree, the size distribution, and the free energy of mesoscopic systems, as well as their phase-transition conditions. These equations reveal that, under supersaturation, the largest cluster size (LCS) is an important state variable; the supersaturation degree decreases with the LCS, approaching unity in the macroscopic limit. We identify the critical supersaturation, at which the nuclei undergo the phase transition to form large crystals. Below this critical supersaturation, the nucleus size distribution is either a unimodal function or a monotonically decreasing function of size, depending on the system and temperature. We also predict the most probable nucleus size and the direction of spontaneous changes of the LCS. Our theory provides a unified, quantitative explanation of the nucleus-size-distribution across six different systems, including nanoparticles and biological condensates. This work serves as a general theoretical framework useful for understanding and designing nucleation and phase transitions of mesoscopic systems.

Kang, Jingyu↗

DOE OSTI2025

Metal–Metal Bonding Influences Hydride Reactivity in [Sn–Rh] 3+ and [Sn–Ni] 2+ Bimetallics

Heavier group 14 metal hydrides serve as key intermediates in catalytic transformations, such as hydroboration. Regenerating such intermediates via a clean hydride source like dihydrogen could provide catalytic processes with a more economical alternative to, e.g., silanes and hydridoborane reagents. Herein, we report our efforts toward this goal using a [Sn–Rh] 3+ bimetallic system with the formal Rh I center acting as a potential dihydrogen activator. Targeting the introduction of a hydride ligand to the bimetallic core, our reactivity studies have revealed a preference for the hydride ligand to be bound to the Rh center, instead of the Sn center. Finally, examination of the electronic structures of these complexes via theoretical and experimental methods has revealed the electron acceptor nature of the Rh center within the bimetallic core and offers an explanation for the localization of the hydride between metal centers.

anions↗

DOE OSTI2025

Active Site Dynamics in Molybdenum-Based Silica-Supported Olefin Metathesis Catalysts: Site Renewal and Decay Beyond the Chauvin Cycle

Heterogeneous olefin metathesis catalysts exhibit low active site densities and unpredictable kinetics due to dynamic active site formation and decay processes. Here, in this study, we establish a quantitative framework that captures active site generation, renewal, and decay in olefin metathesis over silica-supported molybdenum oxide catalysts, enabling a mechanistic explanation of catalytic behavior and strategies to achieve high, stable activity. Steady-state active site titrations reveal that 2,3-dimethyl-butene isomers (4MEs) cofeeding increases active site density by up to 4.3-fold, directly correlating with enhanced metathesis rates. Spectroscopic studies demonstrate that 4MEs facilitate Mo(VI) reduction to Mo(IV) and interact strongly with surface Si–OH groups, generating labile protons that promote active site formation via a 1,2-proton shift mechanism. Kinetic modeling indicates that ethylene acts as a decay promoter, shifting kinetic control away from the Chauvin cycle and suppressing metathesis activity. Comparative studies on catalysts with varying Mo loading reveal that promotion is most effective for dispersed molybdate species, with a decline at higher Mo loadings. These findings provide a unified mechanistic framework for heterogeneous olefin metathesis, offering new strategies to enhance active site accessibility, mitigate deactivation, and optimize catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Size-Dependent Optical Band Gaps in Metal–Organic Framework Nanoparticles

Decades of research into size-dependent semiconductor optical gaps have focused on quantum confinement as the dominant mechanism. Emerging reports indicate that lattice strain─intentional or incidental─can impart optical shifts similar or greater in magnitude. Here, we report evidence of optical absorption and photoluminescence spectra of M(1,2,3-triazolate)2 (M = Mg, Cr, Mn, Fe, Co, Cu, Zn, or Cd) nanoparticles that blueshift from bulk values with decreasing particle sizes in a manner that defies explanation by conventional quantum confinement. Here, the phenomenon persists for particle sizes as large as 200 nm, whereas quantum confinement generally ceases beyond 20–30 nm diameters and follows a weaker dependence on the particle radius. Computational simulations and crystallographic analysis suggest that this behavior arises from size-dependent changes to metal–linker bonding that manifest in strain values comparable to literature reports of strain-induced optical shifts in other classes of materials. This behavior appears beyond this family of materials in other notable examples of metal–organic frameworks (MOFs), including the well-studied Cu3(trimesate)2 (CuBTC), where smaller sizes correlate with blueshifted optical gaps. Taken together, these results represent one of the few examples of size-dependent strain in crystalline materials and reinforce the emerging view that MOFs become softer materials when isolated as nanoparticles.

Electrical conductivity↗

DOE OSTI2026

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↗

DOE OSTI2026

Photoluminescent Cu(I) HETPHENs Featuring Bulky Alkyl-Substituted Phenanthrolines

Successful excited-state-enhancing substituent effect strategies applied in homoleptic Cu(I) metal-to-ligand charge transfer (MLCT) chromophores have been adapted to the heteroleptic phenanthroline (HETPHEN) platform, leveraging 2,9-mesityl-1,10-phenanthroline (mesPhen) in conjunction with a series of seven distinct 2,9- and 2,3,4,7,8,9-substituted phenanthrolines. The newly conceived CuHETPHEN complexes feature MLCT lifetimes ranging from 62 to 443 ns, all of which exhibit unprecedented room-temperature photoluminescence and demonstrate quantitative adherence to the energy gap law. TD-DFT calculations successfully modeled the systematic variation in electronic transition intensities, accounting for the experimentally observed UV–vis absorption bands across the entire series of molecules while providing detailed structural explanations for the variations in spectral profiles. These heteroleptic Cu(I) diimine chromophores exhibit thermally activated delayed fluorescence (TADF), with delayed fluorescence occurring between closely spaced 1 MLCT and 3 MLCT excited manifolds, having energetic separations of ΔE = 713–1009 cm –1 , as demonstrated here for the first time. Nanosecond and ultrafast transient absorption spectroscopy verified the MLCT nature of these excited states and extracted the time constants for the initial pseudo-Jahn–Teller distortion and intersystem crossing throughout the entire series of molecules. Lastly, the triplet photosensitization properties of these Cu(I) HETPHENs are demonstrated in a number of model photochemical transformations.

Chromophores↗

DOE OSTI2026

Understanding Electrochemical Alcohol Hydrogenolysis Enabled by Carbonyl Reduction in Lignocellulosic Biomass-Derived Aromatic Oxygenates

Molecules derived from lignocellulosic biomass are oxygenates with multiple oxygen-containing functional groups, such as hydroxyl and carbonyl groups. Therefore, the ability to selectively reduce a specific oxygenate group is essential for the reductive upgrading of such molecules. Previous studies on electrochemical biomass conversion have shown that alcohol hydrogenolysis, which involves cleavage of the σ(C–O alcohol ) bond, is extremely challenging for furfural and 5-hydroxymethylfurfural (HMF) derivatives, including furfuryl alcohol, 5-methylfurfuryl alcohol (MFA), and 2,5-bis(hydroxymethyl)furan (BHMF). In contrast, HMF itself undergoes alcohol hydrogenolysis relatively easily in acidic aqueous media. Considering that the only structural difference between HMF and BHMF or MFA is the presence of a carbonyl group, this observation raises the question of whether the carbonyl group in HMF facilitates alcohol hydrogenolysis. In this study, we designed systematic experiments to provide a coherent explanation of when and how a carbonyl group enables hydrogenolysis of a copresent alcohol group. Specifically, we show that alcohol hydrogenolysis in HMF proceeds via reduction of the carbonyl group to a ketyl radical, followed by a spin-center shift (SCS) through extended π conjugation. We also elucidate the effect of pH on the selectivity between carbonyl hydrogenation and alcohol hydrogenolysis, both of which share the ketyl radical intermediate. This mechanistic understanding enhances our ability to predict and control alcohol hydrogenolysis in the reductive upgrading of biomass-derived oxygenates.

alcohols↗

DOE OSTI2025

A Universal Model of Cation Effects in Electrocatalysis

Electrolyte cations are conventionally viewed as inert spectators in electrocatalysis. However, a wealth of observations show that catalytic rates are often highly sensitive to cation identity. Despite their prevalence, these cation effects have resisted a unified mechanistic explanation, with different physical phenomena implicated across reaction chemistries, catalyst compositions, and choice of solvent. In this perspective, we describe a general framework for understanding cation effects in electrocatalysis based on electrostatics. We argue that cations influence reaction rates by modifying the strength of the electric field present at the catalyst surface, which alters the energetics of adsorbed intermediates and transition states according to their dipole moments and polarizabilities. The magnitude of this field depends on how cations arrange at the electrode surface, controlled by their size, shape, solvation, and packing efficiency. Cations that can arrange more densely result in a steeper potential drop at the electrode surface and consequently a stronger electric field. Our model further identifies two criteria for observing cation effects: (1) the operating potential must be negative of the electrode’s potential of zero total charge, ensuring that cations accumulate at the interface, and (2) the energetics of the kinetically relevant elementary step must be field sensitive. This framework reconciles previously inconsistent trends, including why cation effects appear only for some catalysts, why reaction selectivity is sensitive to cation identity, and why activity can increase with cation size on certain metals but decrease on others. Supported by kinetic measurements, spectroscopy, and atomistic simulations, the model provides both conceptual value for building intuition about catalysis at charged interfaces and predictive value for anticipating trends for new reactions, catalysts, and electrolytes. We conclude by highlighting the importance of electric fields across electrochemical, thermochemical, and biological catalysis and propose that considering the electrostatic environment around active sites offers new opportunities for improving activity and selectivity.

cation effects↗

DOE OSTI2020

Decreased Soil Organic Matter in a Long-Term Soil Warming Experiment Lowers Soil Water Holding Capacity and Affects Soil Thermal and Hydrological Buffering

Long-term soil warming can decrease soil organic matter (SOM), resulting in self-reinforcing feedback to the global climate system. We investigated additional consequences of SOM reduction for soil water holding capacity (WHC) and soil thermal and hydrological buffering. At a long-term soil warming experiment in a temperate forest in the northeastern United States, we suspended the warming treatment for 104 days during the summer of 2017. The formerly heated plot remained warmer (+0.39 °C) and drier (-0.024 cm 3 H 2 O cm -3 soil) than the control plot throughout the suspension. We measured decreased SOM content (-0.184 g SOM g -1 for O horizon soil, -0.010 g SOM g -1 for A horizon soil) and WHC (-0.82 g H 2 O g -1 for O horizon soil, -0.18 g H2O g -1 for A horizon soil) in the formerly heated plot relative to the control plot. Reduced SOM content accounted for 62% of the WHC reduction in the O horizon and 22% in the A horizon. We investigated differences in SOM composition as a possible explanation for the remaining reductions with Fourier transform infrared (FTIR) spectra. We found FTIR spectra that correlated more strongly with WHC than SOM, but those particular spectra did not differ between the heated and control plots, suggesting that SOM composition affects WHC but does not explain treatment differences in this study. We conclude that SOM reductions due to soil warming can reduce WHC and hydrological and thermal buffering, further warming soil and decreasing SOM. This feedback may operate in parallel, and perhaps synergistically, with carbon cycle feedbacks to climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A Benchmark to Test Generalization Capabilities of Deep Learning Methods to Classify Severe Convective Storms in a Changing Climate

Abstract This is a test case study assessing the ability of deep learning methods to generalize to a future climate (end of 21st century) when trained to classify thunderstorms in model output representative of the present‐day climate. A convolutional neural network (CNN) was trained to classify strongly rotating thunderstorms from a current climate created using the Weather Research and Forecasting model at high‐resolution, then evaluated against thunderstorms from a future climate and found to perform with skill and comparatively in both climates. Despite training with labels derived from a threshold value of a severe thunderstorm diagnostic (updraft helicity), which was not used as an input attribute, the CNN learned physical characteristics of organized convection and environments that are not captured by the diagnostic heuristic. Physical features were not prescribed but rather learned from the data, such as the importance of dry air at mid‐levels for intense thunderstorm development when low‐level moisture is present (i.e., convective available potential energy). Explanation techniques also revealed that thunderstorms classified as strongly rotating are associated with learned rotation signatures. Results show that the creation of synthetic data with ground truth is a viable alternative to human‐labeled data and that a CNN is able to generalize a target using learned features that would be difficult to encode due to spatial complexity. Most importantly, results from this study show that deep learning is capable of generalizing to future climate extremes and can exhibit out‐of‐sample robustness with hyperparameter tuning in certain applications.

54 ENVIRONMENTAL SCIENCES↗