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At least 181 records · Page 10

Complex Dependence of Calcite Crack Kinetics on Salinity: The Role of DLVO and Hydration Forces

Abstract Subcritical crack growth (SCG) plays an important role in many geological processes such as delayed earth rupture and rock weathering. The complex dependency of SCG on the in‐crack fluid chemistry, however, is still poorly understood. In this study, we utilize the newly developed surface force‐based fracture theory (SFFT) to elucidate the relative contributions of surface forces and solute transport to the crack growth kinetics of calcite in NaCl solutions. Expanding on Barenblatt's cohesive crack model, SFFT introduces an effective stress intensity at the crack tip that encompasses all the relevant intermolecular forces across the crack in addition to the external far‐field stresses. The nonlinear system of equations portraying the crack opening profile, the solute distribution in a propagating crack, and the crack growth velocity are numerically solved via an implicit scheme. After carefully calibrating the model for calcite‐water systems, the SFFT is used to predict the SCG response of calcite at different NaCl concentrations, based on various hypotheses. These predictions are then compared to existing SCG data from the literature. We demonstrate that the experimentally observed variation of SCG rate with NaCl concentration cannot be explained solely by DLVO forces (electrostatic and Van der Waals interactions). This can be remediated by introducing an exponentially decaying hydration force with a nonlinear, nonmonotonic dependence on NaCl concentration. Furthermore, we demonstrate that accounting for both diffusive and advective transport of ions is important in explaining the absence of a stage‐II SCG response for calcite in electrolyte solutions. Plain Language Summary Subcritical crack growth (SCG) refers to the slow propagation of cracks in materials under a stress below the threshold for catastrophic failure. SCG is a key process in many geological events, for example, delayed earth ruptures and rock weathering. New initiatives such as underground CO 2 and H 2 storage in carbonate reservoirs further call for better understanding of SCG in carbonate minerals subjected to varying fluid chemistry. This study examines the SCG of calcite, a key mineral found in carbonate rocks, intergranular cement in sandstones, and filling material in mineral veins and faults, determining their deformation and strength. A mathematical model is developed to describe how the crack opens and propagates, how solutes (like salts) distribute within the crack, and how the crack surfaces interact with each other. We used the model to predict calcite SCG in water at different salt concentrations and compared it with experimental data. Our results revealed that the hydration force is the dominating factor in determining the complex, non‐linear dependency of SCG on salinity. We also found that both the movement of ions by diffusion and by bulk water flow are crucial for explaining the SCG rates, especially when the cracks grow quickly. Key Points Surface Force‐Based Fracture Theory predicts the complex subcritical crack growth patterns of calcite crystals immersed in NaCl solutions Results highlight the dominant role of hydration forces in altering the fracture behavior of calcite compared to VdW and electric double‐layer forces Advective solute transport explains the absence of stages‐II and ‐III subcritical crack growth responses in solid‐liquid systems

DLVO↗

Learning neural representations for X-ray ptychography reconstruction with unknown probes

X-ray ptychography provides exceptional nanoscale resolution and is widely applied in materials science, biology, and nanotechnology. However, its full potential is constrained by the critical challenge of accurately reconstructing images when the illuminating probe is unknown. Conventional iterative methods and deep learning approaches are often suboptimal, particularly under the low-signal conditions inherent to low-dose and high-speed experiments. These limitations compromise reconstruction fidelity and restrict the broader adoption of the technique. In this work, we introduce the Ptychographic Implicit Neural Representation (PtyINR), a self-supervised framework that simultaneously addresses the object- and probe-recovery problem. By parameterizing both as continuous neural representations, PtyINR performs end-to-end reconstruction directly from raw diffraction patterns without requiring any pre-characterization of the probe. Extensive evaluations demonstrate that PtyINR achieves superior reconstruction quality on both simulated and experimental data, with remarkable robustness under challenging low-signal conditions. Furthermore, PtyINR offers a generalizable, physics-informed framework for addressing probe-dependent inverse problems, making it applicable to a wide range of computational microscopy problems.

36 MATERIALS SCIENCE↗

Intercalated chalcogenides Fe 1/4 TaS 2 and Fe 1/3 TaS 2 under extreme pressure—temperature conditions

Intercalation is an important strategy for enhancing functionality in complex chalcogenides. This is because layered materials can be endowed with intriguing properties by filling the van der Waals gap with various ions and molecules, which, in addition to their unique chemistry, break symmetry in new ways. In order to explore the properties of intercalated metal dichalcogenides under extreme pressure-temperature conditions, we combine diamond anvil cell techniques, Raman scattering spectroscopy, magnetic susceptibility, and first-principles calculations to reveal the pressure–temperature phase diagram of Fe 1/3 TaS 2 . This system hosts a compression-driven structural phase transition to a polar state as well as remnant charge density wave signatures deriving from the host lamella of the 2H-parent compound. We also explore the role of different A-site patterns and determine that, by comparison, Fe 1/4 TaS 2 is soft and flexible due to the lower metal density inside the van der Waals gap. These findings open the door to entirely new states of matter with exciting property combinations, including metallicity, polarity, chirality, and altermagnetism – depending upon the conditions – that can support a wide range of spintronics and phononics applications.

Materials science↗

Nitrogen availability and summer drought, but not N:P imbalance, drive carbon use efficiency of a Mediterranean tree-grass ecosystem

All ecosystems contain both sources and sinks for atmospheric carbon (C). A change in their balance of net and gross ecosystem carbon uptake, ecosystem-scale carbon use efficiency (CUE ECO ), is a change in their ability to buffer climate change. However, anthropogenic nitrogen (N) deposition is increasing N availability, potentially shifting terrestrial ecosystem stoichiometry towards phosphorus (P) limitation. Depending on how gross primary production (GPP, plants alone) and ecosystem respiration (R ECO , plants and heterotrophs) are limited by N, P or associated changes in other biogeochemical cycles, CUE ECO may change. Seasonally, CUE ECO also varies as the multiple processes that control GPP and respiration and their limitations shift in time. We worked in a Mediterranean tree-grass ecosystem (locally called ‘dehesa’) characterized by mild, wet winters and summer droughts. We examined CUE ECO from eddy covariance fluxes over 6 years under control, +N and + NP fertilized treatments on three timescales: annual, seasonal (determined by vegetation phenological phases) and 14-day aggregations. Finer aggregation allowed consideration of responses to specific patterns in vegetation activity and meteorological conditions. We predicted that CUE ECO should be increased by wetter conditions, and successively by N and NP fertilization. Milder and wetter years with proportionally longer growing seasons increased CUE ECO , as did N fertilization, regardless of whether P was added. Using a generalized additive model, whole ecosystem phenological status and water deficit indicators, which both varied with treatment, were the main determinants of 14-day differences in CUE ECO . The direction of water effects depended on the timescale considered and occurred alongside treatment-dependent water depletion. Overall, future regional trends of longer dry summers may push these systems towards lower CUE ECO .

59 BASIC BIOLOGICAL SCIENCES↗

Deep learning for time series forecasting: a survey of recent advances

Time series forecasting plays a critical role in numerous real-world applications, such as finance, healthcare, transportation, and scientific computing. In recent years, deep learning has become a powerful tool for modeling complex temporal patterns and improving forecasting accuracy. This survey provides an overview of recent deep learning approaches for time series forecasting, involving various architectures including RNNs, CNNs, GNNs, transformers, large language models, MLP-based models, and diffusion models. We first identify key challenges in the field, such as temporal dependency, efficiency, and cross-variable dependency, which drive the development of forecasting techniques. Then, the general advantages and limitations of each architecture are discussed to contextualize their adaptation in time series forecasting. Furthermore, we highlight promising design trends like multi-scale modeling, decomposition, and frequency-domain techniques, which are shaping the future of the field. This paper serves as a compact reference for researchers and practitioners seeking to understand the current landscape and future trajectory of deep learning in time series forecasting.

97 MATHEMATICS AND COMPUTING↗

Directional Variations in Tidal Flow Multifractality and Intermittency

We explored distinct directional variations of multifractal and intermittent characteristics of ebb and flood flow velocities at nodule point, WA, tidal energy site, and complementary inspection on the East River, NY using scaling exponents of the structure function, distribution flatness, detrending moving average (DMA) analysis, multifractal detrended fluctuation analysis (MF-DFA), and high-order spectral moments. Our findings reveal that tidal flow presents higher long-range dependence (LRD) and intermittent levels for the ebb flow sections, whereas the flood flow sections exhibit a higher degree of multifractality and greater sensitivity to larger magnitude of turbulent fluctuations. We demonstrate that long-range dependence predominantly contributes to multifractal behavior in both ebb and flood flows, as evidenced by the significantly reduced multifractal spectrum width for temporally randomly permuted time series. Moreover, spectral kurtosis analysis uncovers a higher intermittent level across all frequency scales for ebb flow sections and reveals a distinct pattern of tidal flow intermittency differing from the monotonically increasing intermittent level observed in wall-bounded and grid turbulence. Finally, we demonstrate that DMA, MF-DFA, and high-order spectral moments provide more comprehensive insights than structure function scaling exponents and PDF flatness methods.

Cheng, Shyuan [Univ. of Illinois at Urbana-Champai↗

Potential long-term, global effects of enhancing the domestic terrestrial carbon sink in the United States through no-till and cover cropping

Abstract Background Achieving a net zero greenhouse gas United States (US) economy is likely to require both deep sectoral mitigation and additional carbon dioxide removals to offset hard-to-abate emissions. Enhancing the terrestrial carbon sink, through practices such as the adoption of no-till and cover cropping agricultural management, could provide a portion of these required offsets. Changing domestic agricultural practices to optimize carbon content, however, might reduce or shift US agricultural commodity outputs and exports, with potential implications on respective global markets and land use patterns. Here, we use an integrated energy-economy-land-climate model to comprehensively assess the global land, trade, and emissions impacts of an adoption of domestic no-till farming and cover cropping practices based on carbon pricing. Results We find that the adoption of these practices varies depending on which aspects of terrestrial carbon are valued. Valuation of all terrestrial carbon resulted in afforestation at the expense of domestic agricultural production. In contrast, a policy valuing soil carbon in agricultural systems specifically indicates strong adoption of no-till and cover cropping for key crops. Conclusions We conclude that under targeted terrestrial carbon incentives, adoption of no-till and cover cropping practices in the US could increase the terrestrial carbon sink with limited effects on crop availability for food and fodder markets. Future work should consider integrated assessment modeling of non-CO 2 greenhouse gas impacts, above ground carbon storage changes, and capital and operating cost considerations.

54 ENVIRONMENTAL SCIENCES↗

Microscopic theory of angular momentum distributions across the full range of fission fragments

Modern nuclear theory provides qualitative insights into the fundamental mechanisms of nuclear fission and is increasingly capable of making reliable quantitative predictions. Most quantities of interest pertain to the primary fission fragments, whose subsequent decay is typically modeled using statistical reaction models. Consequently, a key objective of fission theory is to inform these models by predicting the initial conditions of the primary fragments. Here, in this work, we employ a framework that combines joint angular momentum and particle number projection with time-dependent configuration mixing to calculate the angular momentum distributions of primary fragments. Focusing on the benchmark cases of neutron-induced fission of 235 U and 239 Pu , we predict—for the first time—microscopic angular momentum distributions for all fragments observed in experiments. Our results reveal a pronounced sawtooth pattern in the average angular momentum as a function of fragment mass, consistent with recent measurements. Additionally, we observe substantial variations in angular momentum distributions along isobaric chains, indicating that commonly used empirical formulas lack sufficient accuracy. We also quantify a strong correlation between the angular momentum and the deformation of the fragments at scission, and a weak correlation in the magnitude of the angular momentum between fragment partners. The generated data will enable estimation of the impact of microscopic distributions on fission spectra, paving the way toward fission modeling based on microscopic inputs.

Physics - Nuclear physics and radiation physics↗

Electron transport across the cell envelope via multiheme c -type cytochromes in Geobacter sulfurreducens

Extracellular electron transfer (EET) enables certain microorganisms to respire using soluble and insoluble extracellular electron acceptors by transporting electrons across the cell envelope. Among these, G. sulfurreducens serves as a model organism for understanding direct EET pathways, where multiheme c-type cytochromes mediate electron transport from intracellular redox carriers to extracellular acceptors such as Fe(III) oxides and electrodes. This review focuses on heme-dependent electron transfer in Geobacter sulfurreducens, detailing the roles of inner membrane cytochromes, periplasmic carriers, outer membrane conduits, and recently characterized extracellular nanowires formed by polymerized multiheme c-type cytochromes, including OmcS, OmcE, and OmcZ. We examine the state of understanding of their physiological function, their structural features, expression patterns, and essentiality under various respiratory conditions. These insights advance our understanding of microbial anaerobic respiration and have implications for biogeochemical cycling, bioenergy generation, and bioremediation. The molecular architecture, assembly mechanisms, and secretion pathways of multiheme c-type cytochrome nanowires remain active areas of investigation, offering promising directions for future research and biotechnological innovation in engineered microbial systems.

Chemistry↗

CareWELL: Multimodal Region Representation Learning with Spatial Contexts for Urban Health

Rapid urbanization affects living environments by intensifying exposure to air pollution, heat, noise, and urban dynamics, which together contribute to uneven health outcomes across neighborhoods. For instance, cardiovascular, respiratory, and mental health conditions are each influenced by distinct exposures such as air pollution, extreme temperatures, or limited access to green space. These heterogeneous patterns require understanding the characteristics of geographic regions in order to explain why urban health risks vary across urban areas. Recent work in self-supervised region representation learning provides a promising way to model such characteristics from multimodal geospatial data. However, existing methods face two major limitations: (i) they often depend on non-public datasets, limiting reproducibility and applicability, and (ii) their generic pretraining objectives overlook health-relevant determinants, including temporal variability in environmental exposures and inequalities in social conditions. To address these gaps, we propose Context-Aware Region rEpresentation with Weather, Environment, and Location Learning (CareWELL). CareWELL leverages large language models to encode seasonal variability in weather, employs contrastive learning to align geo-coordinate and weather representations, and introduces a context-aware objective that integrates socio-demographic factors while preserving spatial correlations. We evaluate CareWELL by predicting six urban health outcomes in Manhattan, New York City, and demonstrate that CareWELL consistently outperforms state-of-the-art baselines as well as a traditional spatial computing method. These results suggest the importance of context-aware pretraining objectives for learning health-relevant region representations.

Namgung, Min [ORNL]↗

Spatially Patterned Architectures to Modulate CO 2 Reduction Cascade Catalysis Kinetics

Electrochemical CO 2 reduction using renewable sources of electrical energy holds promise for converting CO 2 into fuels and chemicals. The complex interactions among chemical/electrochemical reactions and mass transport make it difficult to analyze the effect of an individual process on electrode performance based only on experimental methods. Here, we developed a generalized steady-state simulation to describe an electrode surface in which sequential cascade catalysts are patterned in a periodic trench design. If appropriately constructed, this trench geometry is hypothesized to be able to yield a higher net current density for a CO 2 reduction (CO 2 R) cascade reaction. We have used realistic experimental reaction kinetics to investigate the role of trench geometry in mass transport, local microenvironments, and selectivity for a model CO 2 R cascade reaction. The model considers local concentration gradients of bicarbonate species at quasi-equilibrium and catalytic surface reactions based on concentration-dependent Butler–Volmer kinetics. Our results suggest that varying the spatial distribution of active sites plays a significant role in facilitating effective mass transport between active sites, modulating selectivity for the cascade reaction, and enhancing the yield of desirable cascade products. Moreover, we observe that this trench geometry significantly alters the cascade reaction rate by affecting the local pH, which can cause inadvertent depletion of available aqueous CO 2 to limit the CO 2 R cascade kinetics and modest suppression of the hydrogen evolution reaction (HER). The results highlight the trade-offs between mass transport, pH, and reaction kinetics that become apparent only when considering the coupled physics of all processes at the electrode surface. Here, this model can thus serve as a primary tool to build more selective and efficient patterned architectures for the CO 2 R cascade catalysis.

CO2 reduction↗

An uncertain future change in aridity over the tropics

Abstract An ensemble of climate models from phase six of the Coupled Model Intercomparison Project shows that temperature and potential evapotranspiration (PET) are projected to increase globally towards the end of the 21st century. However, climate models show a spatially heterogeneous change in precipitation over the tropics. Consequently, future changes in aridity (a measure of water availability) are complex and location-dependent. We assess future changes in aridity using three climate models and several single-forcing experiments. Near-term (2021–2040) changes in aridity are small, and we focus instead on its long-term (2081–2100) changes. We show that the increase in greenhouse gases (GHG) primarily explains the spatial pattern, magnitude and ensemble spread of the long-term future changes in aridity. On this timescale, the effects of changes in emissions of anthropogenic aerosols are moderate compared to the effects of increases in atmospheric GHG concentrations. Model diversity in the responses to GHG concentration is large over northern Africa and North and South America. We suggest the large uncertainty is due to differences between models in simulating the effects of an increase in GHG concentrations on surface air temperature over the North Atlantic Ocean, on the interhemispheric temperature gradient, and on PET over North and South America.

Environmental Sciences & Ecology↗

Search for a critical point of strongly-interacting matter in central \(^{40}\)Ar + \(^{45}\)Sc collisions at 13 A–75 A GeV/c beam momentum

The critical point of strongly interacting matter is searched for at the CERN SPS by the NA61/SHINE experiment in central \(^{40}\)Ar + \(^{45}\)Sc collisions at 13 A, 19 A, 30 A, 40 A, and 75 A GeV/c. The dependence of the second-order scaled factorial moments of proton multiplicity distributions on the number of subdivisions in transverse momentum space is measured. The intermittency analysis uses statistically independent data sets for every subdivision in transverse and cumulative-transverse momentum variables. The results obtained do not indicate the searched intermittent pattern. An upper limit on the fraction of correlated protons and the intermittency index is obtained based on a comparison with the Power-law Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Comparative analysis of SARS-CoV-2 neutralization titers reveals consistency between human and animal model serum and across assays

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires ongoing monitoring to judge the ability of newly arising variants to escape the immune response. A surveillance system necessitates an understanding of differences in neutralization titers measured in different assays and using human and animal serum samples. We compared 18 datasets generated using human, hamster, and mouse serum and six different neutralization assays. Datasets using animal model serum samples showed higher titer magnitudes than datasets using human serum samples in this comparison. Fold change in neutralization of variants compared to ancestral SARS-CoV-2, immunodominance patterns, and antigenic maps were similar among serum samples and assays. Most assays yielded consistent results, except for differences in fold change in cytopathic effect assays. Hamster serum samples were a consistent surrogate for human first-infection serum samples. These results inform the transition of surveillance of SARS-CoV-2 antigenic variation from dependence on human first-infection serum samples to the utilization of serum samples from animal models.

Cell Biology↗

In-Plane Liftout and Push-to-Pull for In Situ Mechanical Testing of Irradiated Inconel X-750

A streamlined sample preparation method for nanomechanical testing is needed to improve the quality of specimens, reduce the cost, and increase the versatility of specimen fabrication. This work outlines an in-plane liftout focused ion beam (FIB) fabrication procedure to prepare electron-transparent specimens for in situ transmission electron microscopy (TEM) nanomechanical testing. Ion etching and electron backscatter diffraction (EBSD) techniques were used to lift out a [110] oriented grain from a neutron-irradiated bulk X-750 alloy. Careful control of voltages and currents ensured precision. Top surface thinning sweeps prevented resurfacing and redeposition while dog-bone geometries were shaped with a 1:4 gauge width-to-milling pattern diameter ratio. Nanotensile testing in the TEM with a picoindenter allowed for the estimation of an ultimate tensile strength of 2.41 GPa, and inspection revealed a high density of bubbles in the X-750 matrix. The proposed fabrication procedure is significant for preparing samples from radioactive materials, studying complex structures that are orientation-dependent, and analyzing desired planar areas.

36 MATERIALS SCIENCE↗

Longitudinal Patterns in Nitrate Revealed Through Drone‐Based Measurements in an Agriculturally Influenced Midwestern U.S. River

Nitrate concentrations in streams and rivers in the Midwestern United States are often elevated, reflecting the predominance of agriculture in the surrounding landscape. Recent advances in technology, including surface water drones and more precise sensors, provide opportunities to investigate nitrate dynamics with high spatial and temporal resolution. We deployed an aquatic drone, the AquaBOT, in a sixth-order, agriculturally influenced river to examine longitudinal patterns in water quality. Our goal was to measure the spatial and temporal heterogeneity in nitrate and nitrate removal processes and determine the influence of tributary inputs on main stem chemistry. We navigated the drone along a 12-km reach of the Des Moines River (Iowa, USA) nine times between June 2021 and August 2022. Across the deployments, mean nitrate concentration was positively related to discharge and was nearly two orders of magnitude higher in spring than summer. We observed contrasting patterns in main stem nitrate, which decreased downstream during some runs (e.g., 3.1–2.7 mg N L −1 in June 2021), demonstrating net nitrate uptake along the reach, and remained constant on other dates. Similarly, tributaries to the Des Moines had a varied influence on riverine nitrate. Tributaries either increased or decreased main stem nitrate concentrations depending on the tributary and the date. Nitrate removal rates were spatially and temporally variable but showed some consistency at the subreach (2 km) scale, with two subreaches often showing elevated rates of nitrate removal across dates. In conclusion, our study reveals nuanced heterogeneity in nitrate dynamics of the Des Moines River despite the homogeneity of agricultural land cover in the watershed.

54 ENVIRONMENTAL SCIENCES↗

cis-p -Coumarates acylate the lignin sidechain in grasses and other plants

In this study, we present evidence that the lignins of grasses and other plants undergo partial acylation by cis-p-coumarate. Unlike the more widely observed trans-p-coumarates, cis-p -coumarates represent a novel acylation pattern on the lignin sidechains. The finding was substantiated by detailed NMR analyses (HSQC, HSQC-TOCSY, HMBC) and alkaline hydrolysis of the lignin isolated from abacá, a plant that exhibits substantial amounts of cis-p -coumarate. The presence of cis-p -coumarates broadens the range of groups known to acylate lignin sidechains and suggests that subtle variations in the acylation pattern can modulate the final structure and properties of the lignin. A broad survey of lignins from diverse plant species revealed that all lignins incorporating trans-p-coumarates also incorporated cis-p-coumarates, albeit in varying proportions. The cis-p-coumarate content ranged from 2 % to 12 % of the total p-coumarate units, depending on the plant species. As cis-p -coumarate is formed through the isomerization of trans-p-coumarate triggered by UV light, this transformation may occur at various stages, including at the free p-coumaric acid level, at the monolignol p-coumarate level, or directly within the lignin polymer. The potential pathways through which cis-p -coumaric acid becomes incorporated into the lignin are discussed.

NMR↗

Understanding the stability of a plastic‐degrading Rieske iron oxidoreductase system

Abstract Rieske oxygenases (ROs) are a diverse metalloenzyme class with growing potential in bioconversion and synthetic applications. We postulated that ROs are nonetheless underutilized because they are unstable. Terephthalate dioxygenase (TPA DO PDB ID 7Q05 ) is a structurally characterized heterohexameric α 3 β 3 RO that, with its cognate reductase (TPA RED ), catalyzes the first intracellular step of bacterial polyethylene terephthalate plastic bioconversion. Here, we showed that the heterologously expressed TPA DO /TPA RED system exhibits only ~300 total turnovers at its optimal pH and temperature. We investigated the thermal stability of the system and the unfolding pathway of TPA DO through a combination of biochemical and biophysical approaches. The system's activity is thermally limited by a melting temperature ( T m ) of 39.9°C for the monomeric TPA RED , while the independent T m of TPA DO is 50.8°C. Differential scanning calorimetry revealed a two‐step thermal decomposition pathway for TPA DO with T m values of 47.6 and 58.0°C (Δ H = 210 and 509 kcal mol −1 , respectively) for each step. Temperature‐dependent small‐angle x‐ray scattering and dynamic light scattering both detected heat‐induced dissociation of TPA DO subunits at 53.8°C, followed by higher‐temperature loss of tertiary structure that coincided with protein aggregation. The computed enthalpies of dissociation for the monomer interfaces were most congruent with a decomposition pathway initiated by β‐β interface dissociation, a pattern predicted to be widespread in ROs. As a strategy for enhancing TPA DO stability, we propose prioritizing the re‐engineering of the β subunit interfaces, with subsequent targeted improvements of the subunits.

59 BASIC BIOLOGICAL SCIENCES↗