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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Oxygen Evolution on Mechanically Strained TiO2/NiTi: Implications of Compositional Heterogeneity at (Photo)Electrocatalytic Interfaces

The adsorption and activation energetics underpinning small molecule conversion on heterogeneous (photo)electrocatalysts are intrinsically tied to catalyst surface properties. Absent compositional characterization techniques with sufficient interface sensitivity, however, (photo)electrochemical performance can be misinterpreted in the context of bulk or near-surface material properties. Here we provide a fundamental investigation of the convoluting role of near-surface compositional heterogeneity in the interpretation of (photo)electrochemical alkaline oxygen evolution reaction (OER) activity, highlighting challenges in correlating composition measured by surface- and near-surface-sensitive probes. TiO2 thin films grown by air-annealing the superelastic alloy Nitinol (TiO2/NiTi) crack under tensile mechanical strain, increasing the number of electrochemically active Ni sites (Ni site density) that are probed via voltammetric features corresponding to Ni3+/Ni2+ redox events. (Photo)electrochemical OER kinetics trend with Ni site density, with overpotentials and Tafel slopes decreasing for Ni site densities < 1013 Ni/cm2geo and asymptotically approaching the performance of the base NiTi substrate for Ni site densities > 1013 Ni/cm2geo. Photoelectrochemical fill factors follow similar Ni site density dependent trends. When probing unstrained TiO2/NiTi, Ni site densities are two orders of magnitude higher when comparing near-surface-sensitive techniques (e.g., X-ray photoelectron spectroscopy (XPS), time of flight secondary ion mass spectrometry (TOF-SIMS), and scanning transmission electron microscopy-energy dispersive X-ray spectroscopy (STEM-EDS)) to surface-sensitive electrochemical measurements. This result highlights the challenge of correlating kinetic performance with intrinsic surface properties of electrochemical interfaces in the presence of near-surface compositional heterogeneity. Further, it reinforces the importance of fundamental investigations of surfaces with well-controlled composition and structure and the need for physically grounded and self-consistent interpretation of multiple near-surface characterization techniques.

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

Estimating coil features from an equilibrium

We present an explicit theoretical framework for constructing artificial modular coils for vacuum stellarator fields based solely on equilibrium properties, achieved through the formulation of a current potential defined on flux surfaces. Contours of constant Boozer toroidal angle can be directly interpreted as proxy coils, and so we demonstrate that key measures of coil complexity—particularly coil non-planarity—are strongly governed by local magnetic-field properties. This approach shows promise as predictor for more realistic coil configurations, providing both a pathway toward deeper understanding of equilibrium–coil relationships and a potential practical proxy for coil design.

Rodríguez, Eduardo [Max Planck Institute for Plasm↗
DOE OSTI2025

STILGAR End-of-Project Report

The Subsurface Tunnel Imaging LeveraGed by Analysis of Rayleigh wave ellipticity (STILGAR) project demonstrated an integrated geophysical approach for detecting, locating, and characterizing underground structural changes using dense seismic arrays and advanced inversion techniques. Field campaigns were conducted at two operational mines—the Redmond salt mine (Utah) and Graymont Pleasant Gap limestone mine (Pennsylvania)—providing real-world testbeds for monitoring anthropogenic subsurface activity. At the Redmond salt mine, seismic interferometry combined with back-projection inversion successfully identified continuous, low-amplitude signals from mining operations. The approach differentiated stationary from migrating anthropogenic sources, captured daily operational cycles, and validated the potential of passive seismic monitoring for remote detection of underground activity. At the Graymont Pleasant Gap mine, two dense seismic deployments in the spring and fall of 2023 generated over 4 TB of high-resolution data. Key outcomes included the relocation of 199 underground and 8 surface explosions with accuracies within tens of meters and the development of a 3D P-wave velocity model using the triple-difference tomography algorithm (tomoTD) that resolved major structural features such as the mine entrance, low-velocity tunnels, and roof-collapse areas. Ambient noise cross-correlation and back-projection analyses revealed persistent sources linked to ongoing mining activity, whereas horizontal-to-vertical spectral ratio (HVSR) and ellipticity studies confirmed stable site responses across seasons and identified soil thickness trends consistent with regional erosional and depositional processes. Checkerboard and sensitivity tests further validated the robustness of the tomographic results. Overall, the findings emphasize that although significant progress has been made in subsurface imaging, further work is needed to enhance the detection and localization of underground structures. Accurate imaging requires higher frequencies, yet anthropogenic sources tend to dominate the seismic record at those frequencies, and high-frequency surface waves are affected by higher modes that complicate interpretation. The improved detection and localization of human-induced signals enabled detailed temporal and spatial mapping of daily mine operations, demonstrating the feasibility of continuous anthropogenic source monitoring. Sensitivity to signals from nontraditional sources, such as fan operations, highlights the broader applicability of this approach to other industrial environments in which continuous and impulsive signals are present. The field campaigns produced a substantial volume of high-quality seismic data, supporting the development and testing of new methods for seismic source characterization and subsurface imaging. Future deployments should include sensors capable of recording lower frequencies to probe deeper structures, increase bandwidth to enhance resolution and sensitivity to both shallow and deep targets, and collect additional large-scale datasets to refine imaging and source characterization techniques. Moreover, conducting 3D modeling studies of seismic wavefields at higher frequencies will provide a better understanding of wave scattering and cavity–wavefield interactions in complex underground environments. In conclusion, the STILGAR project demonstrated that integrated seismic monitoring can effectively characterize underground operations, capturing both natural and anthropogenic signals. The approaches developed provide a foundation for improved detection, localization, and imaging of subsurface structures and are directly transferable to broader industrial monitoring applications.

58 GEOSCIENCES↗
DOE OSTI2024

Recent Progress on Surface Water Quality Models Utilizing Machine Learning Techniques

Surface waterbodies are heavily exposed to pollutants caused by natural disasters and human activities. Empowering sensor technologies in water quality monitoring, sufficient measurements have become available to develop machine learning (ML) models. Numerous ML models have quickly been adopted to predict water quality indicators in various surface waterbodies. This paper reviews 78 recent articles from 2022 to October 2024, categorizing water quality models utilizing ML into three groups: Point-to-Point (P2P), which estimates the current target value based on other measurements at the same time point; Sequence-to-Point (S2P), which utilizes previous time series data to predict the target value at one time point ahead; and Sequence-to-Sequence (S2S), which uses previous time series data to forecast sequential target values in the future. The ML models used in each group are classified and compared according to water quality indicators, data availability, and model performance. Widely used strategies for improving performance, including feature engineering, hyperparameter tuning, and transfer learning, are recognized and described to enhance model effectiveness. The interpretability limitations of ML applications are discussed. This review provides a perspective on emerging ML for surface water quality models.

machine learning (ML)↗
DOE OSTI2025

Numerical case study of the aerosol–cloud interactions in warm boundary layer clouds over the eastern North Atlantic with an interactive chemistry module

The presence of warm boundary layer stratiform clouds over the eastern North Atlantic (ENA) region is commonly influenced by the Azores High, especially during the summer season. To investigate comprehensive aerosol–cloud interactions, this study employs the Weather Research and Forecasting model coupled with a chemistry component (WRF-Chem), incorporating aerosol chemical components that are relevant to the formation of cloud condensation nuclei (CCN) and accounting for aerosol spatiotemporal variation. This study focuses on aerosol indirect effects, particularly the long-range transport of aerosols, in the ENA region under three different weather regimes: a ridge with a surface high-pressure system, a post-trough with a surface high-pressure system, and a weak trough. The WRF-Chem simulations conducted at a near-large-eddy scale offer valuable insights into the model's performance, especially in terms of its ability to use high spatial resolution to capture mesoscale cloud features across various weather regimes. Our result shows that introducing 5 times more aerosols to either non-precipitating or precipitating clouds significantly increases ambient CCN numbers, resulting in, to varying degrees, higher liquid water path (LWP) values. The substantial aerosol–cloud interaction especially occurs in the precipitating clouds and demonstrates the susceptibility of the LWP to changes in CCN under different regimes. Conversely, thin, non-rain clouds at the edges of a cloud system are prone to evaporation, exhibiting an aerosol drying effect. The aerosols released during this process transition back to the accumulation mode, facilitating future activation. This dynamic behavior is not adequately represented in prescribed-aerosol simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Micropolar Elastoplasticity Using a Fast Fourier Transform‐Based Solver

ABSTRACT This work presents a micromechanical spectral formulation for obtaining the full‐field and homogenized response of elastoplastic micropolar composites. A closed‐form radial‐return mapping is derived from thermodynamics‐based micropolar elastoplastic constitutive equations to determine the increment of plastic strain necessary to return the generalized stress state to the yield surface, and the algorithm implementation is verified using the method of numerically manufactured solutions. Then, size‐dependent material response and micro‐plasticity are shown as features that may be efficiently simulated in this micropolar elastoplastic framework. The computational efficiency of the formulation enables the generation of large datasets in reasonable computing times.

42 ENGINEERING↗
DOE OSTI2026

Real-Space Constrained Density Functional Theory Investigation of Site-Specific, Interfacial Charge Recombination Dynamics Across the Au Nanoparticle/TiO 2 Heterojunction

Au nanoparticle (NP)/TiO 2 heterojunction is a representative system to study interfacial charge transfer in photocatalysis and photovoltaics, where suppressing recombination from TiO 2 to Au can enhance hot carrier extraction. We apply real-space constrained density functional theory (CDFT) with Marcus theory to quantify charge recombination time scales across Au/TiO 2 . This approach enables direct control and visualization of charge-separated states, aligning with site-specific probes like time-resolved X-ray photoelectron spectroscopy (trXPS). We find that the charge-separated state features a bipolaron, with recombination dominated by TiO 2 LUMO to Au HOMO transitions, primarily at interfacial Au sites. Marcus rate predictions are benchmarked with surface hopping methods, quantifying differences in time scales and computational efficiency. Lastly, we examine how the Au cluster size affects the free energy change (ΔG) and reorganization energy (λ), explaining trends in closed-shell systems and highlighting challenges for open-shell extrapolations. Overall, CDFT + Marcus theory provides efficient, mechanistically transparent interfacial charge transfer modeling, and we clearly defined its applicability and limitation.

Glenna, Drew M. [Univ. of Idaho, Idaho Falls, ID (↗
DOE OSTI2024

Vertically Resolved Analysis of the Madden-Julian Oscillation Highlights the Role of Convective Transport of Moist Static Energy

We simulate the Madden-Julian oscillation (MJO) over an aquaplanet with uniform surface temperature using the multiscale modeling framework (MMF) configuration of the Energy Exascale Earth System Model (E3SM-MMF). The model produces MJO-like features that have a similar spatial structure and propagation behavior to the observed MJO. To explore the processes involved in the propagation and maintenance of these MJO-like features, we perform a vertically resolved moist static energy (MSE) analysis for the MJO (Yao et al., 2022, https://doi.org/10.1175/jas-d-20-0254.1). Unlike the column-integrated MSE analysis, our method emphasizes the local production of MSE variance and quantifies how individual physical processes amplify and propagate the MJO's characteristic vertical structure. We find that radiation, convection, and boundary layer (BL) processes all contribute to maintaining the MJO, balanced by the large-scale MSE transport. Furthermore, large-scale dynamics, convection, and BL processes all contribute to the propagation of the MJO, while radiation slows the propagation. Additionally, we perform mechanism-denial experiments to examine the role of radiation and associated feedbacks in simulating the MJO. We find that the MJO can still self-emerge and maintain its characteristic structures without radiative feedbacks. This study highlights the role of convective MSE transport in the MJO dynamics, which was overlooked in the column-integrated MSE analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Stabilizing LiCoO 2 at 4.6 V by regulating anti-oxidative solvents

For LiCoO 2 (LCO) operating at high voltages (>4.5 V vs. Li/Li + ), the intensive side reactions between LCO and traditional ethylene carbonate (EC)-based electrolytes with LiPF 6 salts can produce plenty of corrosive species (such as HF and HPO 2 F 2 ), causing severe surface degradation. Herein, anti-oxidative fluoroethylene carbonate (FEC) and difluoroethylene carbonate (DFEC) were selected as co-solvents to reduce the generation of corrosive species. Besides, PF 6 − anions enrich the Helmholtz plane of the LCO/electrolyte interface and promote the formation of a robust cathode/electrolyte interphase (CEI) featuring LiF/Li x PO y F z /Li 3 PO 4 inorganics and P-containing organics under the synergy of fluorinated solvents, which significantly inhibits the catalysis of highly oxidative Co 4+ /O n− (0 < n < 2). Benefiting from the reduced corrosive species and reinforced CEI, the layered structure of the LCO surface is well preserved during long-term cycling, with a highly reversible O3/H1-3 phase transition. Consequently, a LCO||graphite pouch cell exhibits a remarkable capacity retention of 85.7% after 500 cycles in 3.0–4.55 V. Furthermore, this work provides a new insight into developing advanced functional electrolytes for high-voltage lithium-ion batteries.

Co/O loss↗
DOE OSTI2025

The Photochemistry of Amino Acids Produced on the Polar Cryovolcanic Regions of Titan

The cryovolcanic regions of Titan offer transient opportunities for prebiotic molecules to exist in water–ammonia solutions on the surface of the Saturnian moon. The upcoming NASA’s Dragonfly mission will search for high nitrogen concentrations and amino acids on Titan’s equatorial terrains. Cryovolcanic features, however, are most common on the polar regions. To mitigate the distance, bubble bursting may encapsulate the prebiotic molecules into aerosols, which Titan’s Hadley circulation would subsequently transport to the equator. Here we investigate whether alanine and glycine survive this meridional journey. Despite the unconstrained meridional wind velocities, our results suggest that the amino acids can survive the transport through the mesosphere. Dragonfly may find cryo-volcanogenic amino acids on Titan’s equator. Further, the interaction between the two amino acids increased 10-fold the photodegradation rate of glycine. We justify it based on changes in the environment polarity.

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

Predicting Flow in Fracture Networks With Quantum Algorithms

Uncertainty quantification plays a crucial role in the modeling of subsurface flow. For instance, uncertainties in the properties of geologic fracture networks significantly impact flow, requiring numerous simulations to accurately estimate quantities of interest. However, each simulation is computationally expensive because it requires solving a large linear system to capture features that involve both small and large fractures. An example is in percolation, where the interaction of many small fractures (which cumulatively can have a large surface area) with the rock matrix must be modeled precisely. Quantum computing is an emerging tool with the potential to address this issue. Quantum algorithms offer a significant speedup in solving linear systems, achieving efficiencies that are challenging to match with classical approaches. These classical approaches include direct solvers, such as LU decomposition, and iterative methods, notably preconditioned conjugate gradient, commonly used in subsurface modeling to solve large sparse systems. However, applying quantum algorithms to geologic fracture flow requires careful attention to algorithmic and problem-specific constraints to fully realize this quantum advantage. In this work we describe a quantum algorithm for generalized Monte Carlo applications with a quadratic speedup over the classical approaches which can be combined with the quantum speedup, currently under investigation, for solving quantum linear systems for subsurface flow. We show that for quantum algorithms the computational cost of estimating a quantity of interest for a statistical ensemble of networks is roughly the same as that of a single realization, essentially implying that one can get uncertainty quantification for free.

58 GEOSCIENCES↗
DOE OSTI2024

Realization of a gas puff imaging system on the Wendelstein 7-X stellarator

A system for studying the spatiotemporal dynamics of fluctuations in the boundary of the W7-X plasma using the “Gas-Puff Imaging” (GPI) technique has been designed, constructed, installed, and operated. This GPI system addresses a number of challenges specific to long-pulse superconducting devices, such as W7-X, including the long distance between the plasma and the vacuum vessel wall, the long distance between the plasma and diagnostic ports, the range of last closed flux surface (LCFS) locations for different magnetic configurations in W7-X, and management of heat loads on the system’s plasma-facing components. The system features a pair of “converging–diverging” nozzles for partially collimating the gas puffed locally ≈135 mm radially outboard of the plasma boundary, a pop-up turning mirror for viewing the gas puff emission from the side (which also acts as a shutter for the re-entrant vacuum window), and a high-throughput optical system that collects visible emission resulting from the interaction between the puffed gas and the plasma and directs it along a water-cooled re-entrant tube directly onto the 8 × 16 pixel detector array of the fast camera. The DEGAS 2 neutral code was used to simulate the Hα (656 nm) and HeI (587 nm) line emission expected from well-characterized gas-puffs of H2 and He and excited within typical edge plasma profiles in W7-X, thereby predicting line brightnesses used to reduce the risks associated with system sensitivity and placement of the field of view. Operation of GPI on W7-X shows excellent signal-to-noise ratios (>100 at 2 Mframes/s) over the field of view for minimally perturbing gas puffs. The GPI system provides detailed measurements of the two-dimensional (radial and poloidal) dynamics of plasma fluctuations in the W7-X edge and scrape-off layer and in and around the magnetic islands outside the LCFS that make up the island divertor configuration employed on W7-X.

Instruments & Instrumentation↗
DOE OSTI2026

Screen-Printed SHJ Solar Cells with Complex Silver Inks

Metallization using complex metal inks has gained significant research interest due to its cost-effectiveness and ability to achieve performance comparable to traditional nanoparticle pastes. This study introduces the use of complex silver (Ag) inks applied via industrial screen-printing for silicon heterojunction (SHJ) solar cell metallization. The printed Ag lines exhibit a contact resistivity on SHJ tin-doped indium oxide (ITO) surfaces as low as approximately 0.2-12 mO cm2. Photoluminescence imaging reveals minimal surface passivation degradation (iVoc < 3.5 mV), while scanning electron microscopy (SEM) shows a denser structure compared to Ag layer from nanoparticle pastes. The printed Ag grid features thin (approximately 1 micrometer), continuous fingers approximately 100-120 micrometer wide, significantly thinner than conventional approximately 20-30 micrometer fingers produced with nanoparticle-based pastes. Double printing achieves SHJ device efficiencies exceeding 20%, the highest reported for industrial solar cell precursors using this technology. These findings highlight the potential of complex Ag inks as a sustainable alternative to particle-based pastes, reducing Ag consumption and processing temperatures without compromising efficiency.

14 SOLAR ENERGY↗
DOE OSTI2025

Stemflow Hydrodynamics

Stemflow hydrodynamics is the study of water movement along the exterior surface area of plants. Its primary goal is to describe water velocity and water depth along the stem surface area. Its significance in enriching the rhizosphere with water and nutrients is not in dispute. Yet, the hydrodynamics of stemflow have been entirely overlooked. This review seeks to fill this knowledge gap by drawing from thin film theories to seek outcomes at the tree scale. The depth‐averaged conservation equations of water and solute mass are derived at a point. These equations are then supplemented with the conservation of momentum that is required to describe water velocities or relations between water velocities and water depth. Relevant forces pertinent to momentum conservation are covered and include body forces (gravitational effects), surface forces (wall friction), line forces (surface tension), and inertial effects. The inclusion of surface tension opens new vistas into the richness and complexity of stemflow hydrodynamics. Flow instabilities such as fingering, pinching of water columns into droplets, accumulation of water within fissures due to surface tension and their sudden release are prime examples that link observed spatial patterns of stemflow fronts and morphological characteristics of the bark. Aggregating these effects at the tree‐ and storm‐ scales are featured using published experiments. The review discusses outstanding challenges pertaining to stemflow hydrodynamics, the use of dynamic similarity and 3D printing to enable the interplay between field studies and controlled laboratory experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

West African Monsoon System’s Responses to Global Ocean–Regional Atmosphere Coupling

This study explores the added value (AV) of a regional Earth system model (ESM) compared to an atmosphere-only regional climate model (RCM) in simulating West African monsoon (WAM) rainfall. The primary goals are to foster discussions on the suitability of coupled RCMs for WAM projections and deepen our understanding of ocean–atmosphere coupling’s influence on the WAM system. The study employs results from dynamical downscaling of the ERA-Interim reanalysis and Max Plank Institute ESM, low resolution (MPI-ESM-LR), by two RCMs, atmosphere only (REMO) and REMO coupled with Max Planck Institute Ocean Model (MPIOM) (ROM), at ~25-km horizontal resolution. Results show that in regions distant from coupling domain boundaries such as West Africa (WA), constraint conditions from ERA-Interim are more beneficial than coupling effects. REMO, reliant on oceanic sea surface temperatures (SSTs) from observations and influenced by ERA-Interim, is biased under coupling conditions, although coupling offers potential advantages in representing heat and mass fluxes. Contrastingly, as intended, coupling improves SSTs and monsoon fluxes’ relationships under ESM-forced conditions. In this latter case, the coupling features a dipole-like spatial structure of AV, improving precipitation over the Guinea Coast but degrading precipitation over half of the Sahel. Our extensive examination of physical processes and mechanisms underpinning the WAM system supports the plausibility of AV. Additionally, we found that the monsoonal dynamics over the ocean respond to convective activity, with the Sahara–Sahel surface temperature gradient serving as the maintenance mechanism. While further efforts are needed to enhance the coupled RCM, we advocate for its use in the context of WAM rainfall forecasts and projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Characterization of Field-Exposed Photovoltaic Modules Featuring Signs of Contact Degradation

Here, this work investigates several photovoltaic (PV) modules that have shown signs of metal contact corrosion due to field exposure in a hot and humid climate. This includes two multicrystalline silicon aluminum back surface field systems with 10 and 14 years of exposure and one monocrystalline silicon passivated emitter and rear cell system with four years of exposure. A comprehensive, multiscale characterization process is used to evaluate these PV modules in great detail. Current–voltage (I−V), Suns-V OC measurements, electroluminescence imaging, infrared imaging, and ultraviolet fluorescence imaging were performed, and locations of interest were cored and analyzed using cross-sectional scanning electron microscopy (SEM). A rigorous, quantitative analysis procedure for the cross-sectional SEM images is proposed and implemented. Careful characterization does reveal that some of these PV modules do indeed exhibit the same classic signs of acetic-acid-based corrosion of the glass frit that is present at the silver/silicon interface, which have been observed previously in PV modules exposed to damp heat in an environmental chamber.

14 SOLAR ENERGY↗
DOE OSTI2026

Synergistic Solvent-Surface Interactions Enable Alkyne Semihydrogenation at Palladium

Enabling higher yield and better selectivity for fine-chemical synthesis through heterogeneous catalysis is intricately linked to the interplay of active sites, reaction conditions, and mass transfer influence provided by the catalyst. Alkyne semihydrogenation is ubiquitous in the production of bulk chemicals in the pharmaceutical, polymer, or fine-chemical industries, but product selectivity remains a major challenge. Here, in this study, we demonstrate that the design of catalysts encompassing nickel (Ni) foams as contiguous monolith supports, decorated with ultralow loading of Pd/PdO x nanoparticles on a carbonized polydopamine interface and tuned with a thin layer of Al 2 O 3 , in conjunction with an optimized reaction environment leads to highly selective alkyne semihydrogenation. The reactions demonstrate good functional group tolerance and applicability to flow reactor systems. Combined computational and experimental studies are presented to describe the synergistic effect between the solvent-surface interaction and the degree of Pd surface reduction that are necessary to promote this selectivity. The system highlights the opportunity for catalyst-solvent codesign as a benign alternative to more complex reactants featuring extrinsic poisons or less-favored dopants.

atomic layer deposition↗
DOE OSTI2024

Seismic Features Predict Ground Motions During Repeating Caldera Collapse Sequence

Abstract Applying machine learning to continuous acoustic emissions, signals previously deemed noise, from laboratory faults and slowly slipping subduction‐zone faults, demonstrates hidden signatures are emitted that describe physical details, including fault displacement and friction. However, no evidence currently exists to demonstrate that similar hidden signals occur during seismogenic stick‐slip on earthquake faults—the damaging earthquakes of most societal interest. We show that continuous seismic emissions emitted during the 2018 multi‐month caldera collapse sequence at the Kı̄lauea volcano in Hawai'i contain hidden signatures characterizing the earthquake cycle. Multi‐spectral data features extracted from 30 s intervals of the continuous seismic emission are used to train a gradient boosted tree regression model to predict the GNSS‐derived contemporaneous surface displacement and time‐to‐failure of the upcoming collapse event. This striking result suggests that at least some faults emit such signals and provide a potential path to characterizing the instantaneous and future behavior of earthquake faults.

58 GEOSCIENCES↗