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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Volatilized Ammonia Supports Subterranean Ecosystems with Unusual Nitrogen Isotopic Signatures

The Frasassi cave system hosts a robust subterranean ecosystem based on microbial lithoautotrophy. Curiously, acidic biofilms forming above degassing sulfidic cave streams, and the invertebrates that feed on them, are extremely depleted in nitrogen-15 (δ 15 N values less than −20‰). In this study, we tested the hypothesis that these low δ 15 N values result from the volatilization, trapping, and uptake of ammonia degassed from circumneutral streams. We found that dissolved ammonium in the streams had δ 15 N values near +3‰, whereas NH 3(g) in the cave atmosphere above streams exhibited δ 15 N values as low as −27‰, consistent with fractionation by NH 3 volatilization. Extremely acidic condensation droplets on cave walls efficiently trapped airborne NH 3 , accumulating up to 4 mM NH 4 + with δ 15 N values as low as −29‰, thereby confirming volatilized and trapped ammonia as the primary N source to cave wall biofilms and the extensive subsurface ecosystem they support. Airborne ammonia trapping represents a novel mechanism for biological N acquisition and provides abundant N for growth in an extreme subsurface environment that otherwise receives very limited nutrient input.

Nitrogen↗
DOE OSTI2025

Interfacial Hydrophilicity Controls Mineral Transformation Outcomes for Enstatite and Amorphous MgSiO 3

Subsurface injection of carbon dioxide (CO 2 ) into mafic-ultramafic rocks for permanent storage via mineralization is being studied to reduce emissions. Here, we investigated the carbonation products of enstatite (MgSiO 3 ) to assess its efficiency in sequestering CO 2 for safe and permanent storage as carbonate minerals. This was accomplished by conducting variable temperature carbonation reactions with samples of differing crystallinities and surface chemistries. Reaction progress was monitored utilizing in situ X-ray diffraction, and the presence of carbonate products was confirmed using additional techniques, such as thermogravimetric analysis coupled with mass spectrometry and scanning electron microscopy with energy dispersive spectrometry. Our results show that crystalline enstatite produces small amounts of the anhydrous form of MgCO 3 (magnesite), while amorphous MgSiO 3 , which was used to simulate mafic glass, more readily converts to the hydrated/hydroxylated hydromagnesite [Mg 5 (CO 3 ) 4 (OH) 2 ·4H 2 O]. These results, supplemented with dynamic vapor sorption experiments, suggest that surface properties play a significant role in the pathway and degree of carbonation. These developments concerning the reactivity of CO 2 with reactive mafic phases will help further our understanding of the reactivity of these mafic-ultramafic minerals with implications for permanent carbon storage and other subsurface engineering scenarios involving reactive reservoirs.

basalt↗
DOE OSTI2024

Distinguishing Surface and Bulk Reactivity: Concentration-Dependent Kinetics of Iodide Oxidation by Ozone in Microdroplets

Iodine oxidation reactions play an important role in environmental, biological, and industrial contexts. The multiphase reaction between aqueous iodide and ozone is of particular interest due to its prevalence in the marine atmosphere and unique reactivity at the air–water interface. Here, we explore the concentration dependence of the I – + O 3 reaction in levitated microdroplets under both acidic and basic conditions. To interpret the experimental kinetics, molecular simulations are used to benchmark a kinetic model, which enables insight into the reactivity of the interface, the nanometer-scale subsurface region, and the bulk interior of the droplet. For all experiments, a kinetic description of gas- and liquid-phase diffusion is critical to interpreting the results. We find that the surface dominates the iodide oxidation kinetics under concentrated and acidic conditions, with the reactive uptake coefficient approaching an upper limit of 10 –2 at pH 3. In contrast, reactions in the subsurface dominate under more dilute and alkaline conditions, with inhibition of the surface reaction at pH 12 and an uptake coefficient that is 10× smaller. In conclusion, the origin of a changing surface mechanism with pH is explored and compared to previous ozone-dependent measurements.

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

Reorganization of Water at Aqueous Aluminum Chloride (AlCl 3 ) Interfaces: Vibrational Sum Frequency Generation and Molecular Dynamics Simulations

AlCl 3 hydration states and complexation are not well understood both in solutions and at the air–aqueous interface despite their potential significance in natural waters and their industrial and energy-related applications. Here, we investigated Al 3+ and Cl – ion behaviors in an AlCl 3 aqueous bulk solution and at the air–aqueous interface using interface-selective vibrational sum frequency generation (SFG), Raman and infrared spectroscopies, molecular dynamics (MD) simulation, as well as molecular-informed reduced modeling. Our reduced modeling reveals relatively long-range effects for Al 3+ as compared to monovalent ions such as Na + indicating that the interfacial depth of trivalent ions can be significantly larger than that of monovalent ions at the air–water interface. MD simulations reveal interfacial stratification and multiple layering of the ions. Compression of the Al 3+ and Cl – distributions with increasing concentrations from 0.5 to 2.5 m is also observed in the subsurface regions. Significant SSP- and PPP-polarized SFG OH spectral intensity increases are observed from 0.5 to 1.5 m and 0.5 to 2.5 m, respectively, indicative of interfacial depth increases and a change in average orientation above 1.5 m. Extensive evaluation of SFG spectra, Fresnel-corrected using several approaches, shows the same trends. The nonmonotonic trend points to a changing structure in surface and subsurface water orientation and hydrogen bonding environment generally consistent with the MD simulation of stratification and water orientation changes. Furthermore, solvent-shared ion pairing is implicated with MD simulation radial distribution analysis and consistent with infrared spectral identification of the hexaaqua aluminum ion in the solution phase. Spectral evidence of a strong Al 3+ hydration shell and the acidic behavior of the Al 3+ ions is obvious in the Raman and infrared spectra of the bulk solution. In conclusion, we show that the MD dipole potential is directly related to the MD second-order susceptibility of the interface, χ SFG–MD (2) , both of which correlate up to ∼35 Å with the spectral observations of increasing and then saturating intensities, suggesting that both ion stratification and interfacial depth determine the water orientations at an air–water interface of 1-3 electrolyte solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Adsorption Properties of Au−Ni Surface Alloys with a Nonstoichiometric Moiré Structure: A Density Functional Theory Study

Due to the large lattice mismatch between gold and nickel, gold–nickel surface alloys can form unique nonstoichiometric overlayer structures characterized by a moiré pattern and subsurface defects. For this work, we performed density functional theory (DFT) calculations to study the adsorption of molecular oxygen, atomic hydrogen, and atomic carbon on a gold–nickel(111) surface alloy with 0.46 monolayer gold randomly distributed in the surface layer. We observed six distinct adsorption structures for molecular oxygen characterized by intramolecular stretching frequencies of <700, 729, 795, 857, 929, and 1004 cm –1 , which describe well the experimentally observed high-resolution electron energy-loss spectra. Surface atomic hydrogen adsorption is associated with adsorbate–surface modes in the ∼1000 cm –1 range, while subsurface hydrogen can have features as low as ∼400 cm –1 . We observed a unique adsorption structure for atomic carbon inside the surface dislocation loop defect, which explains the experimentally observed low carbon-surface mode at ∼340 cm –1 . Our study sheds light on the unique adsorption properties of the gold–nickel surface alloys and helps with rationalizing vibrational frequency experimental studies for this system.

adsorption↗
DOE OSTI2025

Direct Deoxygenation of Phenol over Fe-Based Bimetallic Surfaces Using On-the-Fly Surrogate Models

We present an accelerated nudged elastic band (NEB) study of phenol direct deoxygenation (DDO) on Fe-based bimetallic surfaces using a recently developed Gaussian process regression (GPR) calculator. Our test calculations demonstrate that the GPR calculator achieves up to 3 times speedup compared to conventional density functional theory calculations while maintaining high accuracy, with energy barrier errors below 0.015 eV. Using GPR-NEB, we systematically examine the DDO mechanism on pure Fe(110) and surfaces modified with Co and Ni in both top and subsurface layers. Our results show that subsurface Co and Ni substitutions preserve favorable thermodynamics and kinetics for both C–O bond cleavage and C–H bond formation, comparable to those on the pure Fe(110) surface. In contrast, top-layer substitutions generally increase the C–O bond cleavage barrier, render the step endothermic, and result in significantly higher reverse reaction rates, making DDO unfavorable on these surfaces. This work demonstrates the effectiveness of GRR-accelerated transition state searches for complex surface reactions and provides insights into rational design of bimetallic catalysts for selective deoxygenation.

Aromatic compounds↗
DOE OSTI2025

Dynamic Surface Restructuring in Cu(Au) Alloys Driven by Oxygen-Mediated Au Mobility

Alloying plays a crucial role in tuning the surface properties of metals, but the atomic-level mechanisms by which alloying elements influence surface structure dynamics under reactive conditions remain elusive. Using Cu(Au) in oxidizing environments as a model system, we reveal a dynamic oxygen-induced transformation of the topmost atomic layer into a periodically hill-and-valley morphology with reversible switching between undulated and flattened surface states. These interconversions are driven by the retreat of surface Au to the subsurface during oxygen adsorption and its resegregation to the surface upon oxygen desorption. This cyclical mobility establishes a feedback loop, allowing the surface to dynamically reconfigure in response to changes in the oxygen pressure. The results offer a broadly applicable framework for understanding atomic-scale surface restructuring in alloy systems, where differences in the chemical reactivity of alloying elements drive dynamic redistribution between surface and subsurface regions. As a result, this dynamic coupling has practical implications for designing corrosion-resistant coatings and metastable nanostructures with tunable catalytic properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Adsorption of REEs to Kaolinite via Ion Exchange and Surface Complexation as a Function of Water Chemistry

Rare earth elements (REEs) are critical components of modern technology behind renewable energy, transportation, and electronics but have a limited current supply. A substantial portion of global REE production relies on ion adsorption deposits. A high abundance of kaolinite in REE enrichment zones within these deposits suggests that kaolinite controls the subsurface migration of REEs. This study aimed to improve the current understanding of REE binding to kaolinite under varying water chemistry conditions. We conducted batch experiments with kaolinite (KGa-2) and three REEs (Nd, Dy, and Yb) at varying pH, electrolyte concentration, dissolved inorganic carbon (DIC), low molecular weight organic acids (citric and oxalic acids), and total REE concentration conditions. Increasing electrolyte concentration inhibits REE adsorption at pH < 7, suggesting that ion exchange contributes to adsorption at these pH values. DIC affects adsorption above pH 7–8 by forming strong aqueous complexes with heavy REEs. Citric acid decreases REE adsorption via aqueous complexation of REEs at pH > 5 but does not affect adsorption at pH < 5. The surface complexation model captures the main adsorption trends with two mechanisms: ion exchange on basal planes at pH < ∼6 and inner-sphere surface complexation to edge sites at pH > ∼6. Equilibrium constants for surface complexation increase in the order of Yb > Dy > Nd, indicating a higher strength of adsorption for heavy REEs. This study demonstrates how water chemistry conditions control the adsorption mechanisms that may determine the mobility of REEs in subsurface environments rich in kaolinite.

58 GEOSCIENCES↗
DOE OSTI2025

Spatial Distribution and Clustering of Glycosaminoglycans in Electrospun Gelatin-Based Scaffolds

The extracellular matrix (ECM) is comprised of components like collagen, elastin, and glycosaminoglycans (GAGs). Electrospun fibrous scaffolds are designed to replicate the form and composition of the native ECM, often requiring blending of various ECM component mimics to enhance cellular responses. However, the spatial distribution of blended components within these fibers remains unclear. This study investigates the spatial distribution of chondroitin sulfate-C (CSC) in electrospun gelatin-based scaffolds. scanning electron microscopy (SEM), attenuated reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), and Time-of-flight Secondary Ion Mass Spectrometry (ToF-SIMS) were applied for surface and subsurface chemical characterization of the fibrous scaffolds. SEM confirmed a fibrous morphology, while ATR-FTIR and XPS analyses indicated the presence of CSC through the identification of sulfate groups. ToF-SIMS imaging, alongside K-means clustering and Ripley’s K function, revealed a nonuniform CSC distribution with higher concentrations at the top layer of the scaffold. This study demonstrates that CSC presentation at the fiber surface varies with depth and differs from bulk incorporation while reveals nanoscale clustering and spatial heterogeneity at both the surface and subsurface of electrospun gelatin fibers. These findings define an underexplored design consideration with potential to influence cell–scaffold interactions.

Animal derived food↗
DOE OSTI2026

Integration of the Biot–Gassmann Fluid Substitution Method and Machine Learning-Based Velocity–Stress Relationship for Estimating In Situ Stresses

Recent advancements have shown that in situ stresses can be reliably estimated through an integrated machine/deep learning (ML/DL)-based framework, which relies on models trained and validated using true triaxial ultrasonic velocity (TUV) experimental data that involve measurements of ultrasonic velocity in saturated rocks under varying stress configurations. However, when the goal is to interpret lower frequency measurements, it may be more appropriate to run experiments on dry rocks and then obtain Biot–Gassmann-derived equivalent saturated velocities (low-frequency approximation) and employ these quantities for training ML/DL models to predict in situ stress. Whether the dispersion effect of frequency on the velocity–stress relationship substantially impacts in situ stress prediction is an important and unresolved question. This work presents an enhancement of ML/DL-based workflow by training and implementing ML/DL models using equivalent saturated acoustic velocities (low-frequency) obtained by applying Biot–Gassmann fluid substitution on the ultrasonic velocities of dry cores. The models were trained on TUV data sets derived from three subsurface cores extracted from the geothermal well 16B(78)-32 at the Utah FORGE site. Each core was subjected to 75 unique stress configurations for velocity measurement in the dry state. The ML/DL trained on the TUV data set with equivalent saturated velocities demonstrated promising performance to predict in situ stress in subsurface geological rocks using velocity–stress relationships with R 2 of 0.86, 0.971, and 0.975 and root mean squared error (RMSE) of 2.59, 1.92, and 1.80 for validation/testing phases of vertical, minimum horizontal, and maximum horizontal stress models, respectively. Additionally, interpretation and explanation by Shapley additive explanations (SHAP) analysis further improved scientific validation and model reliability for estimating in situ stresses.

colloids↗
DOE OSTI2024

Spatio–Temporal Machine Learning for Regional to Continental Scale Terrestrial Hydrology

Integrated hydrologic models can simulate coupled surface and subsurface processes but are computationally expensive to run at high resolutions over large domains. Here we develop a novel deep learning model to emulate subsurface flows simulated by the integrated ParFlow–CLM model across the contiguous US. We compare convolutional neural networks like ResNet and UNet run autoregressively against our novel architecture called the Forced SpatioTemporal RNN (FSTR). The FSTR model incorporates separate encoding of initial conditions, static parameters, and meteorological forcings, which are fused in a recurrent loop to produce spatiotemporal predictions of groundwater. We evaluate the model architectures on their ability to reproduce 4D pressure heads, water table depths, and surface soil moisture over the contiguous US at 1 km resolution and daily time steps over the course of a full water year. The FSTR model shows superior performance to the baseline models, producing stable simulations that capture both seasonal and event–scale dynamics across a wide array of hydroclimatic regimes. The emulators provide over 1,000× speedup compared to the original physical model, which will enable new capabilities like uncertainty quantification and data assimilation for integrated hydrologic modeling that were not previously possible. Our results demonstrate the promise of using specialized deep learning architectures like FSTR for emulating complex process–based models without sacrificing fidelity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Hydrology Outweighs Temperature in Driving Production and Export of Dissolved Carbon in a Snowy Mountain Catchment

Abstract Terrestrial production and export of dissolved organic and inorganic carbon (DOC and DIC) to streams depends on water flow and biogeochemical processes in and beneath soils. Yet, understanding of these processes in a rapidly changing climate is limited. Using the watershed‐scale reactive‐transport model BioRT‐HBV and stream data from a snow‐dominated catchment in the Rockies, we show deeper groundwater flow averaged about 20% of annual discharge, rising to ∼35% in drier years. DOC and DIC production and export peaked during snowmelt and wet years, driven more by hydrology than temperature. DOC was primarily produced in shallow soils (1.94 ± 1.45 gC/m 2 /year), stored via sorption, and flushed out during snowmelt. Some DOC was recharged to and further consumed in the deeper subsurface via respiration (−0.27 ± 0.02 gC/m 2 /year), therefore reducing concentrations in deeper groundwater and stream DOC concentrations at low discharge. Consequently, DOC was primarily exported from the shallow zone (1.62 ± 0.96 gC/m 2 /year, compared to 0.12 ± 0.02 gC/m 2 /year from the deeper zone). DIC was produced in both zones but at higher rates in shallow soils (1.34 ± 1.00 gC/m 2 /year) than in the deep subsurface (0.36 ± 0.02 gC/m 2 /year). Deep respiration elevated DIC concentrations in the deep zone and stream DIC concentrations at low discharge. In other words, deep respiration is responsible for the commonly‐observed increasing DOC concentrations (flushing) and decreasing DIC concentrations (dilution) with increasing discharge. DIC export from the shallow zone was ~66% of annual export but can drop to ∼53% in drier years. Numerical experiments suggest lower carbon production and export in a warmer, drier future, and a higher proportion from deeper flow and respiration processes. These results underscore the often‐overlooked but growing importance of deeper processes in a warming climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Selecting Appropriate Model Complexity: An Example of Tracer Inversion for Thermal Prediction in Enhanced Geothermal Systems

Abstract A major challenge in the inversion of subsurface parameters is the ill‐posedness issue caused by the inherent subsurface complexities and the generally spatially sparse data. Appropriate simplifications of inversion models are thus necessary to make the inversion process tractable and meanwhile preserve the predictive ability of the inversion results. In this study, we investigate the effect of model complexity on fracture aperture inversion and thermal performance prediction in a field‐scale EGS model. Principal component analysis was used to map the aperture field to a low‐dimensional latent space. The complexity of the inversion model was quantitatively represented by the percentage of total variance in the original aperture fields preserved by the latent space. Tracer, pressure and flow rate data were used to invert for fracture aperture through an ensemble‐based inversion method, and the inferred aperture field was used to predict thermal performance. With an over‐simplified aperture model, ensemble collapse occurred. The inverted aperture models failed to resolve necessary flow and transport features, leading to a biased thermal performance prediction. A complex aperture model involved excessive features and was prone to overinterpreting the inversion data. Both the tracer/pressure/flow rate data reproduction and thermal prediction showed significant uncertainties, making it difficult to properly estimate long‐term thermal performance. Fortunately, our results indicate that there exists an appropriate model complexity which can simultaneously match inversion data and predict thermal performance with an acceptable uncertainty. The quality of the fit of tracer data appears to be a useful indicator of such an appropriate model complexity.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

High Frequency Monitoring and Nitrate Sourcing Reveals Baseflow and Stormflow Controls on Total Dissolved Nitrogen and Carbon Export Along a Rural‐Urban Gradient

Abstract Efforts to reduce nitrogen and carbon loading from developed watersheds typically target specific flows or sources, but across gradients in development intensity there is no consensus on the contribution of different flows to total loading or sources of nitrogen export. This information is vital to optimize management strategies leveraging source reductions, stormwater controls, and restorations. We investigate how solute loading and sources vary across flows and land‐use using high frequency monitoring and stable nitrate isotope analysis from five catchments with different sanitary infrastructure, along a gradient in development intensity. High frequency monitoring allowed estimation of annual loading and attribution to storm versus baseflows. Nitrate loads were 16 kg/km 2 /yr. from the forested catchment and ranged from 68 to 119 kg/km 2 /yr., across developed catchments, highest for the septic served site. Across developed catchments, baseflow contributions ranged from 40% of N loading to 75% from the septic served catchment, and the contribution from high stormflows increased with development intensity. Stormflows mobilized and mixed many surface and subsurface nitrate sources while baseflow nitrate was dominated by fewer sources which varied by catchment (soil, wastewater, or fertilizer). To help inform future sampling designs, we demonstrate that grab sampling and targeted storm sampling would likely fail to accurately predict annual loadings within the study period. The dominant baseflow loads and subsurface stormflows are not treated by surface water management practices primarily targeted to surface stormflows. Using a balance of green and gray infrastructure and stream/riparian restoration may target specific flow paths and improve management.

Delesantro, Joseph M.↗
DOE OSTI2024

Quartz Dissolution Effects on Flow Channelization and Transport Behavior in Three‐Dimensional Fracture Networks

We perform a set of reactive transport simulations in three-dimensional fracture networks to characterize the impact of geochemical reactions on flow channelization. Flow channelization, a frequently observed phenomenon in porous and fractured subsurface rock formations, results from the spatially variable hydraulic resistance offered by a geological structure. In addition to geo-structural features such as network connectivity, geometry, and hydraulic resistance, geochemical reactions, for example, dissolution and precipitation, can dynamically inhibit or enhance flow channelization. These geochemical processes can change the fracture permeability leading to increased flow channelization, which are localized connected regions of high volumetric flow rates that are seemingly ubiquitous in the subsurface. In our simulations, fractures partially filled with quartz are gradually dissolved until quasi-steady state conditions are obtained. We compare the flow field's initial unreacted and final dissolved states in terms of flow and transport observations. We observe that the dissolved fracture networks provide less resistance to flow and exhibit increased flow channelization when compared to their unreacted counterparts. However, there is substantial variability in the magnitude of these changes which implies that the channelization strongly depends on the network structure. In turn, we identify the interplay between the particular network structure and the impact of geochemical dissolution on flow channelization. The presented results indicate that geological systems that have been weathering or reactive for longer times in older landscapes are likely to have increased flow channelization compared to their equivalent but younger counterparts, which implies a time dependence on flow channelization in fractured media.

Hyman, Jeffrey D.↗
DOE OSTI2024

4D Electrical Resistivity Imaging of Stress Perturbations Induced During High–Pressure Shear Stimulation Tests

Fluid flow through fractured media is typically governed by the distribution of fracture apertures, which are in turn governed by stress. Consequently, understanding subsurface stress is critical for understanding and predicting subsurface fluid flow. Although laboratory–scale studies have established a sensitive relationship between effective stress and bulk electrical conductivity in crystalline rock, that relationship has not been extensively leveraged to monitor stress evolution at the field scale using electrical or electromagnetic geophysical monitoring approaches. In this paper we demonstrate the use time–lapse 3–dimensional (4D) electrical resistivity tomography to image perturbations in the stress field generated by pressurized borehole packers deployed during shear–stimulation attempts in a 1.25 km deep metamorphic crystalline rock formation.

58 GEOSCIENCES↗
DOE OSTI2024

Electrical Resistivity Changes During Heating Experiments Unravel Heterogeneous Thermal‐Hydrological‐Mechanical Processes in Salt Formations

Abstract Rock salt is considered a suitable medium for the permanent disposal of heat‐generating radioactive waste due to its isolation properties. However, excavation damage and heating induce complex and heterogeneous thermal‐hydrological‐mechanical (THM) processes across different zones. Quantifying this heterogeneity is crucial for accurate long‐term performance assessment models, but traditional methods lack the necessary resolution. This study employs 4D electrical resistivity tomography (ERT) monitoring during controlled heating experiments in a salt formation to unravel the spatiotemporal dynamics of THM processes. Advanced time‐lapse inversion and clustering analysis quantify subsurface properties and map the heterogeneity of THM dynamics. The ERT results can estimate subsurface properties and delineate the damaged and intact zones, enabling appropriate parameterization and representation of processes for long‐term modeling. This approach may be used in further improving the predictive models and ensuring the safe long‐term disposal of radioactive waste in rock salt.

58 GEOSCIENCES↗
DOE OSTI2024

Complex Fluid‐Driven Fractures Caused by Crack‐Parallel Stress

Abstract Managing fluid‐driven fracture networks is crucial for subsurface resource utilization, yet the current understanding of the key controlling factors remains insufficient. While geologic discontinuities have been shown to significantly influence fracture network complexity, this study identifies another major contributor. We conducted a new set of experiments using a transparent true triaxial cell, which enabled video recording of the temporal evolution of fluid‐driven fracture paths. Using pseudo‐2D samples without macroscale structural discontinuities, we observed multiple occurrences of hydraulic fracture curving and branching under anisotropic boundary stresses. We proposed a theoretical model demonstrating that the stress parallel to the crack line in the solid matrix near the crack tip (i.e., the T ‐stress) accounts for the observed fracture curving behavior. This finding suggests that T ‐stress is an additional mechanism contributing to the complexity of fluid‐driven fracture networks in the subsurface, besides the geologic discontinuities.

58 GEOSCIENCES↗