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Overcoming thermal energy storage density limits by liquid water recharge in zeolite-polymer composites
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Corrosive Influence of Carbon Dioxide on Crack Initiation in Quartz: Comparison With Liquid Water and Vacuum Environments
The stimulation of crack growth in quartz and siliceous materials by injecting carbon dioxide (CO 2 ) represents a key technology in long-term carbon storage and in the development of natural gas wells. While this technology is widely used, the molecular impact of CO 2 interactions on the solid matrix is only incompletely understood. In this work, we employ reactive molecular dynamics simulations to study how the CO 2 fluid environment affects the mechanical properties of pre-cracked single-crystal quartz. The thermodynamic conditions of interest are those relevant to subsurface reservoirs. We report how structural properties of quartz—bond length distribution and crack tip shape—evolve upon introduction of a fluid. These properties are directly related to macroscopic quantities of the global stress-strain curves, thus reaffirming the inherent coupling across multiple scales for fluid-solid interactions in the subsurface. Here, we find that CO 2 reduces the fracture toughness of quartz by 12.1% compared to that of quartz in vacuum, thereby promoting crack growth and enhancing fluid transport in the subsurface.
Molecular origins of bulk viscosity in liquid water
The shear viscous response of water is closely associated with changes in network connectivity on the sub ps timescale. The bulk viscous response is shown here to be associated with local density fluctuations and rotational motion around 1–3 ps.
Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning
Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.
Heat transport in liquid water from first-principles and deep neural network simulations
In this work, we compute the thermal conductivity of water within linear response theory from equilibrium molecular dynamics simulations, by adopting two different approaches. In one, the potential energy surface (PES) is derived on the fly from the electronic ground state of density functional theory (DFT) and the corresponding analytical expression is used for the energy flux. In the other, the PES is represented by a deep neural network (DNN) trained on DFT data, whereby the PES has an explicit local decomposition and the energy flux takes a particularly simple expression. By virtue of a gauge invariance principle, established by Marcolongo, Umari, and Baroni, the two approaches should be equivalent if the PES were reproduced accurately by the DNN model. We test this hypothesis by calculating the thermal conductivity, at the GGA (PBE) level of theory, using the direct formulation and its DNN proxy, finding that both approaches yield the same conductivity, in excess of the experimental value by approximately 60%. Besides being numerically much more efficient than its direct DFT counterpart, the DNN scheme has the advantage of being easily applicable to more sophisticated DFT approximations, such as meta-GGA and hybrid functionals, for which it would be hard to derive analytically the expression of the energy flux. We find in this way that a DNN model, trained on meta-GGA (SCAN) data, reduces the deviation from experiment of the predicted thermal conductivity by about 50%, leaving the question open as to whether the residual error is due to deficiencies of the functional, to a neglect of nuclear quantum effects in the atomic dynamics, or, likely, to a combination of the two.
Ionization by XFEL radiation produces distinct structure in liquid water
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Ice and Supercooled Liquid Water Distributions Over the Southern Ocean Based on In Situ Observations and Climate Model Simulations
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Prominent role of organics in aerosol liquid water content over the south-eastern Atlantic during biomass burning season
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Analysis of contrasting aerosol indirect effects in liquid water clouds over the northern part of Arabian Sea
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Numerical Study of Coupled Water and Vapor Flow, Heat Transfer, and Solute Transport in Variably-Saturated Deformable Soil During Freeze-Thaw Cycles
As climate change intensifies, soil water flow, heat transfer, and solute transport in the active, unfrozen zones within permafrost and seasonally frozen ground exhibit progressively more complex interactions that are difficult to elucidate with measurements alone. For example, frozen conditions impede water flow and solute transport in soil, while heat and mass transfer are significantly affected by high thermal inertia generated from water-ice phase change during the freeze-thaw cycle. To assist in understanding these subsurface processes, the current study presents a coupled two-dimensional model, which examines heat conduction-convection with water-ice phase change, soil water (liquid water and vapor) and groundwater flow, advective-dispersive solute transport with sorption, and soil deformation (frost heave and thaw settlement) in variably saturated soils subjected to freeze-thaw actions. This coupled multiphysics problem is numerically solved using the finite element method. The model's performance is first verified by comparison to a well-documented freezing test on unsaturated soil in a laboratory environment obtained from the literature. Then based on the proposed model, we quantify the impacts of freeze-thaw cycles on the distribution of temperature, water content, displacement history, and solute concentration in three distinct soil types, including sand, silt and clay textures. The influence of fluctuations in the air temperature, groundwater level, hydraulic conductivity, and solute transport parameters was also comparatively studied. The results show that (a) there is a significant bidirectional exchange between groundwater in the saturated zone and soil water in the vadose zone during freeze-thaw periods, and its magnitude increases with the combined influence of higher hydraulic conductivity and higher capillarity; (b) the rapid dewatering ahead of the freezing front causes local volume shrinkage within the non-frozen region when the freezing front propagates downward during the freezing stage and this volume shrinkage reduces the impact of frost heave due to ice formation. This gradually recovers when the thawed water replenishes the water loss zone during the thawing stage; and (c) the profiles of soil moisture, temperature, displacement, and solute concentration during freeze-thaw cycles are sensitive to the changes in amplitude and freeze-thaw period of the sinusoidal varying air temperature near the ground surface, hydraulic conductivity of soil texture, and the initial groundwater levels. Our modeling framework and simulation results highlight the need to account for coupled thermal-hydraulic-mechanical-chemical behaviors to better understand soil water and groundwater dynamics during freeze-thaw cycles and further help explain the observed changes in water cycles and landscape evolution in cold regions.
Event Reconstruction for Water-based Liquid Scintillator Detectors
Water Cherenkov and liquid scintillator detectors represent two complementary approaches in neutrino physics. Water Cherenkov detectors provide particle track direction and particle identification (PID) through Cherenkov ring topology, while liquid scintillator detectors offer higher light yield and lower energy thresholds. Water-based liquid scintillator (WbLS) is designed to combine the advantages of both technologies. However, the simultaneous detection of Cherenkov and scintillation light by photosensors introduces significant challenges for event reconstruction. This poster presents event reconstruction studies for WbLS detectors. A likelihood-based reconstruction framework, fiTQun, has been successfully used in Super-Kamiokande to reconstruct water Cherenkov events in cylindrical detectors. We extend and improve this framework to demonstrate event reconstruction in WbLS detectors, enabling the concurrent reconstruction of particle energy, PID, vertex, and direction. The results demonstrate competitive performance in energy resolution, PID separation, and vertex and direction reconstruction, highlighting the strong potential of WbLS for next-generation neutrino experiments.
Measurements of attenuation and scattering properties of water-based liquid scintillator
Water-based liquid scintillator (WbLS) is a hybrid detector medium which has been proposed as a fill material for future large-volume rare event searches, including ν − detectors. This family of scintillating suspensions promises waterlike attenuation and scattering behavior, while offering scintillation light yield for sub-Cherenkov-threshold events. These features may allow for improved vertex and energy resolution, and concomitant improvements in background rejection and particle identification. While subscale measurements of light yield, timing and pulse-shape have been performed in several WbLS formulations, detailed measurements of the attenuation and scattering properties of WbLS remain a critical, unresolved step along the pathway to deployment. In pursuit of a better understanding of these parameters, a “long-arm” attenuation and scattering instrument has been developed at Lawrence Livermore National Laboratory, dubbed LASE (Livermore Attenuation and Scattering Experiment). Optical property measurements have been performed using LASE in DI water, Gd-water, WbLS and Gd-WbLS. Measurements of the optical properties of WbLS (1% LAB-PPO scintillator) provided by Brookhaven National Laboratory demonstrate an attenuation minimum of 4.87 × 10 − 4 ± 1.42 × 10 − 4 cm − 1 at 450 nm, while Gd-loaded WbLS (1% LAB-PPO scintillator, 0.1% Gd) demonstrated a minimum attenuation coefficient of 4.77 × 10 − 4 ± 1.27 × 10 − 4 cm − 1 at the same wavelength. Measurements of scattering in WbLS show a scattering coefficient of 3.39 × 10 − 4 ± 1.98 × 10 − 5 cm − 1 at the 450 nm attenuation minimum, while Gd-WbLS has a scattering coefficient of 2.8 × 10 − 4 ± 1.63 × 10 − 5 cm − 1 at that wavelength. These scattering and attenuation coefficients are significantly larger than measured for DI water at similar wavelengths ( 8.8 × 10 − 5 cm − 1 ± 3.8 × 10 − 5 attenuation at 430 nm, 2.2 × 10 − 5 ± 1.28 × 10 − 6 cm − 1 scattering). Though the WbLS attenuation and scattering coefficients measured are lower than the corresponding values published for ultrapure oils and LAB-PPO liquid scintillator, the material tested attenuates significantly more than water across the blue and green portions of the visible spectrum. This attenuation is markedly stronger at wavelengths under 430 nm. Published by the American Physical Society 2025