Water Model Research Articles

Efficient screening and catalytic mechanism of TM@β-Te for nitrogen reduction reaction

At present, nitrogen reduction reaction (NRR) has become one critical method for NH3 production through the single-atom catalyst (SAC). A variety of TM@β-Te SACs, constructed by 28 transition metal (TM) atoms anchoring on monovacant β-Te substrate, are systematically investigated by using DFT calculations. An efficient “six-step” screening scheme is proposed to screen out potential NRR catalysts, during which the implicit and explicit solvent models are involved to evaluate competitive reactions of H2O and H+. The final selected (Ta, W)@β-Te catalysts have limiting potentials (UL) of −0.32 V and −0.37 V, respectively. Three intrinsic descriptors of φ (the ratio of number of valence electrons and electronegativity of TM atom), ΔG∗N(adsorption energy of a single N atom on the substrate) and ICOHP (Crystal orbital Hamiltonian integrals for TM-N bonds) are proposed and their correlations with UL are investigated to expound the catalytic activity and mechanism. The relationships of dN≡N ∼ φ, ΔG∗N2∼ φ, ΔG∗N∼ φ and ICOHP ∼ φ resemble “volcanoes”, where (Ta, W)@β-Te are located near the vertex as potential catalysts, which can be verified by scaling relationship of ICOHP and ΔG∗N. Moreover, the UL ∼ φ, UL ∼ ΔG∗Nand UL ∼ ICOHP can be used to determine the potential catalysts from rough catalyst screening to accurate determination of potential determining step (PDS) in catalytic reaction. The constant potential model is adopted to investigate the influences of electrode potentials on adsorption strength of NRR intermediates. This work is informative for the research of NRR process and catalyst design of monoalkenes, which offers an efficient and dependable approach for screening excellent NRR catalysts and revealing the origin of catalytic activity.

Comparison of COSMO Water Models in Quantum Quasi-Docking

Comparison of COSMO Water Models in Quantum Quasi-Docking

Comparison of COSMO Water Models in Quantum Quasi-Docking

Comparison of COSMO Water Models in Quantum Quasi-Docking

Deep Learning With Physics-Embedded Neural Network for Full Waveform Ultrasonic Brain Imaging.

The convenience, safety, and affordability of ultrasound imaging make it a vital non-invasive diagnostic technique for examining soft tissues. However, significant differences in acoustic impedance between the skull and soft tissues hinder the successful application of traditional ultrasound for brain imaging. In this study, we propose a physics-embedded neural network with deep learning based full waveform inversion (PEN-FWI), which can achieve reliable quantitative imaging of brain tissues. The network consists of two fundamental components: forward convolutional neural network (FCNN) and inversion sub-neural network (ISNN). The FCNN explores the nonlinear mapping relationship between the brain model and the wavefield, replacing the tedious wavefield calculation process based on the finite difference method. The ISNN implements the mapping from the wavefield to the model. PEN-FWI includes three iterative steps, each embedding the F CNN into the ISNN, ultimately achieving tomography from wavefield to brain models. Simulation and laboratory tests indicate that PEN-FWI can produce high-quality imaging of the skull and soft tissues, even starting from a homogeneous water model. PEN-FWI can achieve excellent imaging of clot models with constant uniform distribution of velocity, randomly Gaussian distribution of velocity, and irregularly shaped randomly distributed velocity. Robust differentiation can also be achieved for brain slices of various tissues and skulls, resulting in high-quality imaging. The imaging time for a horizontal cross-sectional imag e of the brain is only 1.13 seconds. This algorithm can effectively promote ultrasound-based brain tomography and provide feasible solutions in other fields.

Theoretical Investigations of Hydrolysis Mechanisms of N(SiMe3)3.

Tris(trimethylsilyl)amine (N(SiMe3)3) is one of the most important intermediate products in the indirect synthesis of ammonia (NH3) from nitrogen (N2), which could be hydrolyzed to NH3 under mild conditions. Herein, the hydrolysis mechanism of N(SiMe3)3 has been systematically investigated using density functional theory (DFT) with explicit combined implicit water models. Under neutral conditions, the active barrier of the hydrolysis of N(SiMe3)3 is 17.6 kcal mol-1 in water solvent. The attacking of proton to N center and OH group to Si from water is decoupled for the stabilization of OH group by solvent water molecules, which lower the hydrolysis energy barriers. Furthermore, under acid conditions, N(SiMe3)3 is easily coordinated with proton to form [NH(SiMe3)3]+, and the energy barrier of the hydrolysis reaction could be reduced to 11.5 kcal mol-1 of the first stage, making it being promoted according to the chemical equilibrium. Thus, the results provide an explanation for the possible mechanism of the quantitative conversion of N(SiMe3)3 to NH3 under mild conditions. The decoupled hydrolysis mechanism may play important role in other hydrolysis processes.

Exploring Advanced Analysis Technique for Shallow Water Flow Models with Diverse Applications

The present article focuses on the analytical approach using fractional orders and its applicationin the dynamics of physical processes. Fractional order models align better with experimental data compared tonon-fractional ones. This study primarily focuses on employing the new approximate analytical method to solveshallow water models with fractional orders. Numerical examples within the Caputo fractional derivative showcasethe method’s application. Results for both integer and fractional orders are graphically depicted, demonstrating thefractional solutions’ closeness to actual data. Analysis of 3D and 2D fractional order graphs reveals convergencetoward integer order graphs as fractional derivatives approach non-fractional ones. This method shows promise fordirect application in solving targeted problems and can be easily adapted for other fractional nature problems.

Exploring Advanced Analysis Technique for Shallow Water Flow Models with Diverse Applications

The present article focuses on the analytical approach using fractional orders and its applicationin the dynamics of physical processes. Fractional order models align better with experimental data compared tonon-fractional ones. This study primarily focuses on employing the new approximate analytical method to solveshallow water models with fractional orders. Numerical examples within the Caputo fractional derivative showcasethe method’s application. Results for both integer and fractional orders are graphically depicted, demonstrating thefractional solutions’ closeness to actual data. Analysis of 3D and 2D fractional order graphs reveals convergencetoward integer order graphs as fractional derivatives approach non-fractional ones. This method shows promise fordirect application in solving targeted problems and can be easily adapted for other fractional nature problems.

Modeling Chromatography Binding through Molecular Dynamics Simulations with Resin Fragments.

Accurate atomistic modeling of the interactions of a chromatography resin with a solute can inform the selection of purification conditions for a product, an important problem in the biotech and pharmaceutical industries. We present a molecular dynamics simulation-based approach for the qualitative prediction of interaction sites (specificity) and retention times (affinity) of a protein for a given chromatography resin. We mimicked the resin with an unrestrained ligand composed of the resin headgroup coupled with successively larger fragments of the agarose backbone. The interactions of the ligand with the protein are simulated in an explicit solvent using the Replica Exchange Molecular Dynamics enhanced sampling approach in conjunction with Hydrogen Mass Repartitioning (REMD-HMR). We computed the ligand interaction surface from the simulation trajectories and correlated the features of the interaction surface with experimentally determined retention times. The simulation and analysis protocol were first applied to a series of ubiquitin mutants for which retention times on Capto MMC resin are available. The ubiquitin simulations helped identify the optimal ligand that was used in subsequent simulations on six proteins for which Capto MMC elution times are available. For each of the six proteins, we computed the interaction surface and characterized it in terms of a range of simulation-averaged residue-level physicochemical descriptors. Modeling of the salt concentrations required for elution with respect to the descriptors resulted in a linear fit in terms of aromaphilicity and Kyte-Doolittle hydrophobicity that was robust to outliers, showed high correlation, and correctly ranked the protein elution order. The physics-based model building approach described here does not require a large experimental data set and can be readily applied to different resins and diverse biomolecules.

Prebiotic chemical reactivity in solution with quantum accuracy and microsecond sampling using neural network potentials

While RNA appears as a good candidate for the first autocatalytic systems preceding the emergence of modern life, the synthesis of RNA oligonucleotides without enzymes remains challenging. Because the uncatalyzed reaction is extremely slow, experimental studies bring limited and indirect information on the reaction mechanism, the nature of which remains debated. Here, we develop neural network potentials (NNPs) to study the phosphoester bond formation in water. While NNPs are becoming routinely applied to nonreactive systems or simple reactions, we demonstrate how they can systematically be trained to explore the reaction phase space for complex reactions involving several proton transfers and exchanges of heavy atoms. We then propagate at moderate computational cost hundreds of nanoseconds of a variety of enhanced sampling simulations with quantum accuracy in explicit solvent conditions. The thermodynamically preferred reaction pathway is a concerted, dissociative mechanism, with the transient formation of a metaphosphate transition state and direct participation of water solvent molecules that facilitate the exchange of protons through the nonbridging phosphate oxygens. Associative-dissociative pathways, characterized by a much tighter pentacoordinated phosphate, are higher in free energy. Our simulations also suggest that diprotonated phosphate, whose reactivity is never directly assessed in the experiments, is significantly less reactive than the monoprotonated species, suggesting that it is probably never the reactive species in normal pH conditions. These observations rationalize unexplained experimental results and the temperature dependence of the reaction rate, and they pave the way for the design of more efficient abiotic catalysts and activating groups.

Towards autonomous inland shipping: a manoeuvring model in confined waterways

ABSTRACT Autonomous inland water vessels are essential for promoting intelligent and sustainable waterborne transport. An accurate ship manoeuvring model ensures reliable control strategies and enhances navigation safety. Although ship manoeuvrability models have existed for decades, few studies address shallow and restricted waters. This study introduces a manoeuvring model for inland water vessels, accounting for confinement effects on ship motion. The Manoeuvring Modelling Group (MMG) model in open water serves as the baseline, incorporating empirical methods for shallow water and bank effects. This approach aims to provide a fast and accurate prediction of vessel motion response. The model was validated with free-running experimental data of a pusher-barge model from turning tests at three water depths. Additional case studies highlight shallow water impact compared to infinite water performance under bank effects. Finally, course-keeping case studies are presented, integrating a Proportional-Derivative controller with combined river current and bank-induced forces..

Development of an Elementary Reaction-Based Kinetic Model to Predict the Aqueous-Phase Fate of Organic Compounds Induced by Reactive Free Radicals.

ConspectusAqueous-phase free radicals such as reactive oxygen, halogen, and nitrogen species play important roles in the fate of organic compounds in the aqueous-phase advanced water treatment processes and natural aquatic environments under sunlight irradiation. Predicting the fate of organic compounds in aqueous-phase advanced water treatment processes and natural aquatic environments necessitates understanding the kinetics and reaction mechanisms of initial reactions of free radicals with structurally diverse organic compounds and other reactions. Researchers developed conventional predictive models based on experimentally measured transformation products and determined reaction rate constants by fitting with the time-dependent concentration profiles of species due to difficulties in their measurements of unstable intermediates. However, the empirical treatment of lumped reaction mechanisms had a model prediction limitation with respect to the specific parent compound's fate. We use ab initio and density functional theory quantum chemical computations, numerical solutions of ordinary differential equations, and validation of the outcomes of the model with experiments. Sensitivity analysis of reaction rate constants and concentration profiles enables us to identify an important elementary reaction in formating the transformation product. Such predictive elementary reaction-based kinetics models can be used to screen organic compounds in water and predict their potentially toxic transformation products for a specific experimental investigation.Over the past decade, we determined linear free energy relationships (LFERs) that bridge the kinetic and thermochemical properties of reactive oxygen species such as hydroxyl radicals (HO•), peroxyl radicals (ROO•), and singlet oxygen (1O2); reactive halogen species such as chlorine radicals (Cl•) and bromine radicals (Br•); reactive nitrogen species (NO2•); and carbonate radicals (CO3•-). We used literature-reported experimental rate constants as kinetic information. We considered the theoretically calculated aqueous-phase free energy of activation or reaction to be a kinetic or a thermochemical property, and obtained via validated ab initio or density functional theory-based quantum chemical computations using explicit and implicit solvation models. We determined rate-determining reaction mechanisms involved in reactions by observing robust LFERs. The general accuracy of LFERs to predict aqueous-phase rate constants was within a difference of a factor of 2-5 from experimental values.We developed elementary reaction-based kinetic models and predicted the fate of acetone induced by HO• in an advanced water treatment process and methionine by photochemically produced reactive intermediates in sunlit fresh waters. We provided mechanistic insight into peroxyl radical reaction mechanisms and critical roles in the degradation of acetone and the formation of transformation products. We highlighted different roles of triplet excited states of two surrogate CDOMs, 1O2, and HO•, in methionine degradation. Predicted transformation products were compared to those obtained via benchtop experiments to validate our elementary reaction-based kinetic models. Predicting the reactivities of reactive halogen and nitrogen species implicates our understanding of the formation of potentially toxic halogen- and nitrogen-containing transformation products during water treatment processes and in natural aquatic environments.

Not One, Not Two, But at Least Three: Activity Origin of Copper Single-Atom Catalysts toward CO2/CO Electroreduction to C2+ Products.

Copper (Cu) single-atom catalysts (SACs) exhibit great potential for generating multicarbon (C2+) products, but the intrinsic activity of single-atom Cu (Cu1) under realistic conditions remains controversial. Herein, we perform extensive calculations with explicit solvation to investigate the underlying mechanism of Cu SACs, disclosing the absence of C2+ activity in Cu1 sites regardless of the different substrates. The original Cu1 sites (first taking Cu1 stably anchored on carbon nitride as an example) cannot facilitate *CO hydrogenation and CO-CO coupling due to the lack of active sites nearby, and they are unstable under operation, causing leaching and aggregation to form small Cu clusters. The derived Cu clusters composed of at least three Cu atoms can efficiently promote CO-CO coupling, as revealed by kinetic analyses. We extend the modeling to other typical Cu SACs and reveal that all of the Cu1 sites are inactive, while the C2+ performance of the derived Cu-cluster catalysts is substrate-dependent. This study offers mechanistic insights into Cu SACs and provides practical guidance for their rational optimization.

Widom Line in Supercritical Water in Terms of Changes in Local Structure: Theoretical Perspective.

Performing molecular dynamics simulations with the TIP4P/2005 water model along 9 isobars (from 175 to 375 bar) in the temperature range between 300 and 1100 K, we have found that the loci of the extrema in the rate of change of specific structural properties can be used to define purely structure-based Widom lines. We have examined several parameters that describe the local structure of water, such as the tetrahedral arrangement, nearest neighbor distance, local density around the molecules, and the size of the largest dense domain. The last two parameters were determined using the Voronoi polyhedral and density-based spatial clustering of applications with noise methods, respectively. By analyzing the moments of the associated distributions, we show that along a given isobar, the temperature at which we observe a maximum in the fluctuation, the rate of change of the average values, or in the skewness values unambiguously determines the Widom line that is in agreement with the experimentally detected, thermodynamic response function-based ones.

Development and Application of the Snow, Soil Water and Water Balance Model, an Online Model for Daily Estimation of Snowpack Processes, Soil Water Content and Soil Water Balance

SNOSWAB (Snow, Soil Water and Water Balance) is a unique online deterministic model built using tipping-bucket approaches that allows for the daily estimation of (i) snowpack processes; (ii) soil water content; and (iii) soil water budget. SNOSWAB is most suitable for modeling field-scale processes for vertically and horizontally homogeneous soils, and its applicability is not limited to specific climate zones or geographical areas. The model is freely available, and its streamlined online interface integrates powerful calibration, visualization and data export routines. In this study, SNOSWAB development and a conceptual model, as well as an example of its application using data collected during a 12-year (2008–2019) field study conducted at the Agriculture and Agri-Food Canada Harrington Experimental Farm (HEF) on Prince Edward Island (PEI), Canada, are presented. Input data consisting of daily air temperature, total precipitation, rainfall and evapotranspiration were used in conjunction with soil properties and daily soil water content, snowpack thickness, surface runoff and groundwater recharge to calibrate (2010–2014) and validate (2015–2019) the model. For both the calibration and validation simulations, the statistical indicators used for evaluating model performance indicated, in most cases, high model fitness (i.e., R2 > 0.5, NRMSE < 50% and −25% < PBIAS < 25%) for the various time intervals and parameters analyzed. SNOSWAB fills an existing gap in the online environment and, due to its ease of use, robustness and flexibility, shows promise to be adopted as an alternative for more complex, standalone models that might require extensive resources and expertise.

Electrode wettability and capacitance of electrical double layer capacitor: a classical density functional theory study

We suggest a coarse-grained water model for use in classical density functional theory (cDFT) to describe aqueous inorganic salt solutions that act as working electrolytes in electrical double-layer capacitors (EDLCs) with electrodes comprising two face-to-face doped carbon monolayers. Focus of the cDFT calculations lies on the influence of solvent electrode wettability (SEW) on capacitance and energy storage behaviors, while also considering its interaction with factors like electrolyte bulk concentration, pore size, electrode voltage, and temperature. New phenomena are disclosed theoretically. Remarkably, this study challenges the traditional notion that energy storage is consistently boosted by enhancing the electrode’s ionophobicity. Contrarily, the SEW effect reduces energy storage below the standard aqueous electrochemical window voltage (around 1.2 V) and only enhances the energy storage as the voltage surpasses a certain threshold up to the optimal window voltage (2 V–2.5 V). Furthermore, a non-monotonic SEW effect on energy storage is demonstrated under appropriate conditions, shedding new light on the complex relationship between ionophobicity and energy storage. Moreover, the present coarse-grained water model enables the prediction of the experimentally observed inverse relationship between temperature and capacitance. In contrast, the widely used electrolyte primitive model predicts the existence of a maximum value. The decisive factor for the impact of SEW on capacitance and energy storage is identified as congestion within the electrode pore, while other factors contribute by affecting this congestion. The present research offers valuable insights, highlighting the significance of SEW in the innovative and strategic design of aqueous inorganic EDLC devices.

Monte Carlo simulation study of the structure of calcium and potassium chlorides ternary solutions

ABSTRACT Monte Carlo simulations were conducted on pure water and aqueous calciumand potassium chloride ternary solutions at different salts concentrations. To assess the local order within the solutions, the Monte Carlo simulations utilised the Madrid-2019 force field, usingtheTIP4P/2005 water model and scaled charges. The results demonstrate that as the salt concentrations increase, there is a notable decrease in the contribution of the structured tetrahedral arrangement of water molecules, favouring an unstructured configuration instead. The use of the nearest neighbour approach, provided unambiguous information regarding the radial and orientation characteristics of the unstructured configuration of water. Structures of the solvation shells around ions are also studied. The Monte Carlo simulations indicate that as the salt concentration increases, the hydration number around the cation decreases. This effect is likely due to the occasional substitution of some water molecules in the first hydration shell by chlorine ions.

Magnesium ions mitigate metastable states in the regulatory landscape of mRNA elements.

Residing in the 5' untranslated region of the mRNA, the 2'-deoxyguanosine (2'-dG) riboswitch mRNA element adopts an alternative structure upon binding of the 2'-dG molecule, which terminates transcription. RNA conformations are generally strongly affected by positively charged metal ions (especially Mg2+). We have quantitatively explored the combined effect of ligand (2'-dG) and Mg2+ binding on the energy landscape of the aptamer domain of the 2'-dG riboswitch with both explicit solvent all-atom molecular dynamics simulations (99 μsec aggregate sampling for the study) and selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) experiments. We show that both ligand and Mg2+ are required for the stabilization of the aptamer domain; however, the two factors act with different modalities. The addition of Mg2+ remodels the energy landscape and reduces its frustration by the formation of additional contacts. In contrast, the binding of 2'-dG eliminates the metastable states by nucleating a compact core for the aptamer domain. Mg2+ ions and ligand binding are required to stabilize the least stable helix, P1 (which needs to unfold to activate the transcription platform), and the riboswitch core formed by the backbone of the P2 and P3 helices. Mg2+ and ligand also facilitate a more compact structure in the three-way junction region.

Widespread seawater intrusions beneath the grounded ice of Thwaites Glacier, West Antarctica

Warm water from the Southern Ocean has a dominant impact on the evolution of Antarctic glaciers and in turn on their contribution to sea level rise. Using a continuous time series of daily-repeat satellite synthetic-aperture radar interferometry data from the ICEYE constellation collected in March-June 2023, we document an ice grounding zone, or region of tidally controlled migration of the transition boundary between grounded ice and ice afloat in the ocean, at the main trunk of Thwaites Glacier, West Antarctica, a strong contributor to sea level rise with an ice volume equivalent to a 0.6-m global sea level rise. The ice grounding zone is 6 km wide in the central part of Thwaites with shallow bed slopes, and 2 km wide along its flanks with steep basal slopes. We additionally detect irregular seawater intrusions, 5 to 10 cm in thickness, extending another 6 km upstream, at high tide, in a bed depression located beyond a bedrock ridge that impedes the glacier retreat. Seawater intrusions align well with regions predicted by the GlaDS subglacial water model to host a high-pressure distributed subglacial hydrology system in between lower-pressure subglacial channels. Pressurized seawater intrusions will induce vigorous melt of grounded ice over kilometers, making the glacier more vulnerable to ocean warming, and increasing the projections of ice mass loss. Kilometer-wide, widespread seawater intrusion beneath grounded ice may be the missing link between the rapid, past, and present changes in ice sheet mass and the slower changes replicated by ice sheet models.

Isotope effects in supercooled H2O and D2O and a corresponding-states-like rescaling of the temperature and pressure.

Water shows anomalous properties that are enhanced upon supercooling. The unusual behavior is observed in both H2O and D2O, however, with different temperature dependences for the two isotopes. It is often noted that comparing the properties of the isotopes at two different temperatures (i.e., a temperature shift) approximately accounts for many of the observations-with a temperature shift of 7.2K in the temperature of maximum density being the most well-known example. However, the physical justification for such a shift is unclear. Motivated by recent work demonstrating a "corresponding-states-like" rescaling for water properties in three classical water models that all exhibit a liquid-liquid transition and critical point [Uralcan et al., J. Chem. Phys. 150, 064503 (2019)], the applicability of this approach for reconciling the differences in the temperature- and pressure-dependent thermodynamic properties of H2O and D2O is investigated here. Utilizing previously published data and equations-of-state for H2O and D2O, we show that the available data and models for these isotopes are consistent with such a low temperature correspondence. These observations provide support for the hypothesis that a liquid-liquid critical point, which is predicted to occur at low temperatures and high pressures, is the origin of many of water's anomalies.

Effect of Salt Solution Tracer Dosage on the Transport and Mixing of Tracer in a Water Model of Asymmetrical Gas-Stirred Ladle with a Moderate Gas Flowrate

In previous research simulating steelmaking ladles using cold water models, the dosage/volume of the salt tracer solution is one of the factors that has been overlooked by researchers to a certain extent. Previous studies have demonstrated that salt tracers may influence the flow and measured mixing time of fluids in water models. Based on a water model scaled down from an industrial 130-ton ladle by a ratio of 1:3, this study investigates the impact of salt tracer dosage on the transport and mixing of tracers in the water model of gas-stirred ladle with a moderate gas flow rate. A preliminary uncertainty analysis of the experimental mixing time is performed, and the standard deviations were found to be less than 15%. It was observed in the experiments that the transport paths of tracers in the ladle can be classified into two trends. A common trend is that the injected salt solution tracer is asymmetrically transported towards the left sidewall of the ladle by the main circulation. In another trend, the injected salt solution tracer is transported both by the main circulation to the left side wall and by downward flow towards the gas column. The downward flow may be accelerated and become a major flow pattern when the tracer volume increases. For the dimensionless concentration curve, the sinusoidal type, which represents a rapid mixing, is observed at the top surface monitoring points, while the parabolic type is observed at the bottom monitoring points. An exception is the monitoring point at the right-side bottom (close to the asymmetric gas nozzle area), where both sinusoidal-type and parabolic-type curves are observed. Regarding the effect of tracer volume on the curve and mixing time, the curves at the top surface monitoring points are less influenced but curves at the bottom monitoring points are noticeably influenced by the tracer volume. A trend of decreasing and then increasing as the tracer volume increases was found at the top surface monitoring points, while the mixing times at the bottom monitoring points decrease with the increase in the tracer volume.