How water models influence the interfacial organization of oxysterol epimers: A comparative simulation study using TIP3P and OPC.

Development of conjugate heat transfer coupling model for supercritical water flowing in 2 × 2 ballooning ATF rod bundles

Assessing the accuracy of bioelectrical impedance analysis for fat-free mass estimation in growing pigs using dual-energy X-ray absorptiometry as a reference method.

How well do U.S. National Water Model short-range forecasts predict flood event timing and magnitude?

Over the past few decades, the field of electrochemistry has witnessed rapid advances in computational methods. This review highlights recent methodological progress in computational electrocatalysis, with a specific focus on the accurate prediction of electrochemical reaction kinetics. Particular emphasis is placed on our group's contributions using single-atom catalysts as model systems to quantitatively simulate the kinetics of energy-relevant small-molecule electrocatalytic reactions. By simultaneously capturing atomic-scale interfacial phenomena in the electric double layer, such as cation effects, explicit solvation structures, proton transfer dynamics, and potential distribution, our approach bridges the gap between idealized models and realistic electrochemical environments and predicts experimental observables, such as current density-potential curves and coverages. The current framework has also revealed previously inaccessible kinetic insights, including hydrogen-bond-mediated intermediate reorganization and its impact on transition states, and potential-driven solvent reorganization that dictates proton transfer kinetics. These advances provide both fundamental kinetic insights into electrocatalytic mechanisms and practical design principles for energy conversion catalysts.

Most biomolecular simulations depend on the quality of empirical force fields, and the use of hybrid restraint potentials has emerged as a promising approach. In this contribution, we extend the application of hybrid potentials to membrane proteins by developing optimized restraints derived from experimentally determined NMR data. NMR chemical shift, chemical shift anisotropy, dipolar coupling, and NOE distance information are combined with appropriately weighted empirical force fields to study two transmembrane systems, namely sarcolipin and phospholamban. To remedy the problems of rare events and broken ergodicity, the energy landscape framework, including basin-hopping global optimization and discrete path sampling, is employed for exploring the underlying energy landscapes. Much of the appeal of the hybrid potential approach is the ability to study membrane proteins in the absence of conventional explicit or implicit solvent and lipid molecules, thereby simplifying the sampling of complex biomolecular conformational spaces. Our results suggest that the hybridization of NMR constraints as penalty energies with empirical force fields improves global optimization and energy landscape analysis by excluding experimentally incompatible structures.

We present a software to calculate phase-resolved resonant vibrational sum-frequency generation (vSFG) susceptibility χ(2)(ω) of water and hydroxyls at planar interfaces, e.g., air/water or solid/liquid or (bio)membrane/liquid interfaces of aqueous solutions. The released code (i) reads several formats of molecular trajectories, both from ab initio (AIMD) and classical MD (CMD), (ii) calculates instantaneous surfaces to allow flexible interfaces, (iii) is written in FORTRAN, parallelized by OpenMP and optimized for memory usage, (iv) allows processing of systems up of tens of thousand atoms and for unlimited simulation time, and (v) includes many tunable processing parameters. The code and its documentation are available via GitHub. Flexible models of water and surface hydroxyl (if evaluated) (CMD or AIMD) must be used. The derivatives of the polarizability tensors and dipole moments with the change of O-H distance must be calculated externally by ab initio methods and provided as input data. We present the impact of various parameters of the MD simulations (simulation length, nonbonded interaction cutoff, size of the system, and thermostat relaxation time) as well as of the processing code (filter relaxation, cutoff of cross-terms) and provide representative results for air/water, charged quartz (101)/aqueous solution, and neutral α-alumina (0001)/aqueous solution interfaces. Further extensions are planned to distinguish signals from specific O-H or C-H bonds of interfacial molecules.

Three-body interactions in water play a crucial role in accurately modeling its structural and thermodynamic properties. These interactions consist of a polarization term that decays as an inverse power of the intermolecular separations Rab and a term that is usually assumed to describe exchange interactions and decay exponentially. Due to the complexity of fitting the latter term at large Rab, it is often damped or truncated beyond a certain distance, also because the computational cost of including three-body effects in molecular simulations scales as N3 with the number of molecules, compared to the N2 scaling of two-body interactions. Here, investigations of the impact of long-range three-body exchange interactions on the results of such simulations have been performed by systematically extending the average Rab of trimers included. It is demonstrated that these long-range effects are important for accurately describing the density of liquid water, ρ(T), as a function of temperature, but are essentially negligible for several other properties of water. The effects of three-body damping onset on ρ(T) are larger than they would have been with an exponential decay; however, it is shown here that the decay is dominated by exponential components only at fairly small Rab, while for large Rab, the nonpolarization three-body effects decay as 1/Rabn. These findings are rationalized by calculations with the symmetry-adapted perturbation theory. Another reason for the importance of three-body effects is their N3 scaling. Clearly, long-range three-body exchange interactions should be included in high-accuracy water models. It is shown that the reason these interactions have such large effects on ρ(T) is their extreme anisotropy affecting the structure of liquid water. Our work also sheds light on discrepancies between the theory and experiment for ρ(T).

Ion adsorption or exclusion from surfaces plays a major role in many systems and processes. Unfortunately, thermodynamic information characterizing the relative surface adsorption of individual ions is not currently available from approaches based on the Gibbs adsorption isotherm for mixed electrolytes without approximation. Here, we address this issue for electrolyte solutions containing any number of components at any concentration in a single phase in the presence of any type of fixed charged or uncharged surface in the absence of chemisorption or other chemical reactions. This is achieved by reference to local and global electroneutrality requirements between integrals over the surface-ion distributions. The results indicate that the surface-ion distribution integrals can be decomposed into two independent contributions: one that leads to surface charge neutralization, and the other that explains the surface thermodynamics. The resulting surface-ion integral relationships obtained here indicate exactly how the presence of additional electrolytes affects the surface distribution of any target ion of interest. The validity of the resulting relationships is confirmed using classical all atom explicit solvent molecular dynamics simulations. Using these relationships, one can then obtain individual relative surface-ion adsorptions from experimental data. We illustrate how to use the approach to extract more detailed information from experimental data than was previously available for two experimental mixed electrolyte systems involving vacuum electrolyte solution interfaces. The approach is exact and does not require a particular model for the surface region or the use of single ion chemical potentials.

Parallelization of Monte Carlo (MC) is required to observe the same growth as molecular dynamics because computer processor clock speeds have plateaued while the number of cores has increased. Although prefetch parallelization can speed up an Monte Carlo molecular simulation by a factor of 3 using four parallel threads for simultaneous single-particle displacements in the canonical ensemble, other ensembles require multiple trial types that impact efficiency when threads wait for the other threads with more time-consuming trials, such as volume changes or particle insertions and deletions in the isothermal-isobaric, grand canonical, and Gibbs ensemble. Load balancing increases efficiency by attempting the same trial in each thread of a parallel batch but violates detailed balance if done incorrectly. By computing standard deviations as a function of processor time, efficiency is systematically investigated over a variety of ensembles, load balancing algorithms, and trial attempt and acceptance probabilities for dense liquids of Lennard-Jones and an extended simple point charge model of water, to reveal numerous efficiency gains, including in serial simulations. Parallel efficiency in these ensembles approached the theoretical maximum by reducing overhead costs with improved algorithms and data structures released in the open-source Monte Carlo software called FEASST.

Mercury dihalides (HgX2, X = Cl, Br, I) undergo photoreduction much more rapidly in aqueous environments than in the gas phase. Using ab initio molecular dynamics simulations and high-level electronic structure calculations, we investigate how solvation shapes the molecular structure, electronic distribution, and excited-state character of HgX2 complexes. We find that strong Hg-solvent interactions induce pronounced deviations from linear geometries and lead to partial negative charge accumulation on HgX2 in polar solution. Moreover, we identify that the second absorption band in the deep-UV region exhibits a strong solvent-to-solute charge-transfer (CT) character. Combining the accumulation of partial negative charge in the ground state with the enhanced solvent-to-solute CT character promotes efficient electron localization on the Hg center after photoexcitation, thereby accelerating photoreduction in solution. By providing atomistic insight into solvation-driven excited-state reactivity, this work establishes the molecular basis for the accelerated photochemistry of HgX2 in aqueous media and underscores the essential role of explicit solvation in modeling the solution-phase photochemistry of mercury species relevant to the global mercury cycle.

Hybrid AI Modelling for Imputation and Modelling of Remotely Sensed Surface Water in Climate-Sensitive Wetland

Against the backdrop of the continuous growth of global energy demand, heavy oil, as an important unconventional resource, and its efficient exploitation are of great significance for ensuring national energy security. Electric field-enhanced oil recovery technology has broad prospects for development in the green exploitation of heavy oil. However, at present, few studies have comprehensively considered these mechanisms and established a microscopic numerical simulation model for electric field-assisted hot water flooding for oil recovery from heavy oil reservoirs. This paper considered the mechanism of direct current electric field in reducing crude oil viscosity, interfacial tension, wetting angle, and electroosmotic flow. A fully coupled mathematical model of flow field–temperature field–direct current electric field was established. The model was solved by the finite element method and verified through previous experiments. Using this model, the effects of the potential difference at both ends of the porous medium, the direction of the electric field, the wetting angle, and the interfacial tension on the degree of heavy oil recovery were studied. Finally, the hot water flooding and the direct current (DC) electric field-assisted hot water flooding technology for enhanced oil recovery were compared. The research results show that as the potential difference between the two ends of the porous medium increases, it will inhibit the premature breakthrough of water and prolong the water breakthrough time. As a result, the water will be displaced along the smaller pore throat, thereby playing a role in expanding the volume of water displacement waves. The degree of recovery is the greatest when the direction of the electric field is consistent with the displacement direction. The smaller the wetting angle and interfacial tension, the greater the degree of heavy oil recovery. Compared with hot water flooding, the direct current electric field-assisted hot water flooding can significantly increase the recovery degree of heavy oil.

ABSTRACT In Mediterranean vineyards, soils are often managed with tillage or herbicides to limit weed growth and competition for resources. However, with rising concerns about water scarcity and climate change, cover crops are being reconsidered as sustainable alternatives to conserve soil moisture and support adaptation through better soil structure and biodiversity. Although they are often reported to decrease yields, this is not always the case, and the magnitude and timing of their competition for resources with vines are still not well understood. To address this gap, we examined vine and cover crop water uptake depth during veraison in August in a vineyard from Rioja Alavesa, Spain. We compared tillage (control treatment) with spontaneous cover crop. Using the isotopic composition of plant and soil water (δ 18 O and δ 2 H) and Bayesian mixing models, we found that the cover crop relied on water from the upper soil (100% from 0 to 30 cm), while vines under cover crop accessed water from shallow (~48% from 0 to 30 cm) and deeper soil layers (~52% from 30 to 100 cm). Despite cover crops and vines competing for water in the upper soil, the vine's ability to access water from both shallow and deeper soil horizons helped maintain its water status during veraison. Vines under tillage relied predominantly on water in the deeper soil (~73% from 30 to 100 cm). These results indicate that soil management strongly influences vine water uptake patterns. In our vineyard, the spontaneous summer cover crop did not compromise vine water availability during veraison.

Unveiling the methane hydrate-water interfacial free energy through direct molecular simulation at coexistence conditions.

Soil moisture and saturation are crucial hydrological variables for understanding the soil’s condition and modeling improvement. The National Water Model (NWM), a large-scale model, simulates the hydrologic cycle across the Contiguous United States, Hawaii, and Puerto Rico. The study’s objective was to evaluate the NWM’s performance in estimating and forecasting soil moisture in Puerto Rico from the year 2021 to 2023. The datasets used included in situ stations, model outputs, and remotely sensed data from the Soil Moisture Active Passive (SMAP) mission. Then, we used Volumetric bias (Vbias), Mean Absolute Error (MAE), and Kling–Gupta Efficiency (KGE) to measure performance. The analysis assimilation results showed that three stations in each dataset had an inversely predominant error equal to 25% or less. This low error was reflected in the obtained Vbias and MAE results. Meanwhile, the KGE analysis indicated that the NWM achieves low to moderate soil moisture performance, with better agreement against SMAP than in situ observations. However, the forecasted datasets did not produce satisfactory results. Short-range forecasts exhibited negative KGE values, highlighting the importance of data assimilation, the persistent influence of bias, and scale mismatch. Although the NWM’s primary focus is streamflow forecast, these findings highlight the potential application of the model beyond its primary focus.

Activated carbon biosorption is a feasible alternative for both the removal of emerging contaminants from water and for the utilization of agro-industrial waste. 17-α-ethinylestradiol (EE2) is a hormone considered an emerging contaminant in water bodies, which causes physiological alterations in aquatic animals and ecological problems in aquatic ecosystems. In Mexico, 2.3 million cubic meters of agroforestry waste are generated in the sawmill industry. The primary waste from this industry is sawdust, which is either used as fuel or left in fields, thereby causing pollution. The aim of the current study was to determine the potential of activated carbons made from pine sawdust using inexpensive methods (different H3PO4 treatments) for the removal of EE2 in a water model. The biosorbents were characterized by their yield and surface changes using infrared spectroscopy, scanning electron microscopy, energy-dispersive spectroscopy, X-ray diffraction, and specific surface area analysis with the Brunauer-Emmett-Teller (BET) method. To determine the EE2 removal capacity, five concentrations of activated carbon (68, 400, 1200, 2000, and 2331 mg/L) at different pH conditions (1.7, 3, 6, 9 and 10.2), and an EE2 solution (400 mg/L water-ethanol, 7:3 v/v) were used. EE2 quantification was carried out by high-performance liquid chromatography with a photodiode array detector (HPLC-PDA). Three activated carbons were prepared, highlighting specific surface area (from 543 to 571.7 m2/g). Although there were no significant differences, the highest EE2 removal (26.92%) was obtained with activated carbon 2 (AC2) for a treatment of 2331 mg/L and pH 6. The results revealed that pine sawdust is an adequate material for producing efficiently activated carbon for removing EE2 from water through inexpensive methods.

Conformations of aqueous macromolecules depend on a delicate balance of hydrophobic, electrostatic, and hydrogen-bonding interactions, all of which are influenced by environmental factors such as pressure and pH. Understanding how these factors modulate structural stability is critical for both biological and material science applications. Here, we use constant-pH molecular dynamics simulations to investigate the pressure response of a short, pH-sensitive polymer in explicit solvent. Our results reveal that increasing pressure unfolds both neutral and charged polymers, but the degree of unfolding is markedly reduced when the polymer carries a charge, demonstrating the coupling of pressure and charge regulation. At pH = pKa, we observe a pressure-dependent transition from neutral-like behavior at low pressure to charged-like behavior at high pressure, a signature of pressure-induced pKa shifts. Additionally, pressure-induced unfolding is enhanced at this pH. Extending our study to a model polyampholyte with one acidic and one basic monomer, we find clear evidence of non-additive acid-base coupling that stabilizes collapsed states at low pressure, as well as pressure-induced salt-bridge denaturation at high pressure. This behavior reveals a competition between electrostatic stabilization and pressure-driven hydration effects. These findings shed some light on the pressure-modulated macromolecular behavior of charged and neutral polymers and provide insights relevant to both synthetic polymers and pressure-adapted biological systems.

Coastal erosion is increasingly influenced by anthropogenic alterations to the sediment cycle and morphological transformations. Traditional shallow water models often neglect the mechanical behavior of the seabed and its rheological response to hydrodynamic forcing, limiting their accuracy in forecasting erosion patterns. To address these limitations, this study extends the classical one-dimensional Saint-Venant (shallow water) model by incorporating effects of viscosity, frictional effects, sediment transport and viscoelasticity. The seabed is treated as a Kelvin–Voigt material, characterized by an elastic modulus and a viscous damping coefficient, to account for both immediate and time-dependent mechanical responses. Using the COMSOL Multiphysics platform, the evolution of the water column and seabed was simulated in six idealized case studies under various conditions, including changes in seabed topography and different frictional and dispersive regimes. The results demonstrate the influence of seabed topography, friction Sf, diffusion/dispersion regularization term E, and viscoelastic properties on wave seabed interactions and morphodynamic bed evolution (Exner-type). The inclusion of viscoelastic damping contributes to the stabilization of morphological evolution, mitigating abrupt changes in bathymetry and enhancing the physical realism of the simulations. The whole research aims to improve the prediction capabilities of erosion processes and advance the current modeling tools.

Chondroitin sulfate A (CSA) is a negatively charged linear glycosaminoglycan that plays a vital role in many biological processes. Research on CSA has been challenging due to its size, chemical heterogeneity, and multitude of binding partners. To address these issues, we developed a model of CSA for coarse-grained molecular dynamics simulations based on the Martini 3 force field. We demonstrate that this model is capable of reproducing atomistic properties of the repeating CSA disaccharide unit, including its molecular volume, bonded interactions, and structural polymer properties of CSA chains of different lengths. In particular, for biologically relevant long chains and despite using an explicit solvent, the computational cost is significantly reduced, relative to the cost equivalent atomistic simulations would require. The compatibility of the model with the Martini Go̅ protein model was tested by retrieving the force-response relationship of the CSA-malaria adhesin VAR2CSA complex. Importantly, we explored the influence of electrostatics on CSA aggregation. We show that the default Martini 3 parameters lead to overaggregation. We provide at least three different strategies to alleviate this issue, making use of a bigger bead for sodium cations, reflecting their hydration shell, partial ionic charges as a mean-field resource to take into account electronic polarizability, and, optionally, particle mesh Ewald summation as a more robust treatment of long-range electrostatics. Our model enables predictive modeling of CSA and potentially other chondroitin sulfates with the Martini 3 force field. In addition, this model provides insights for the further development of coarse-grained models of highly charged systems.