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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Solute clustering in polycrystals: Unveiling the interplay of grain boundary junction and long-range solute attraction effects

Spectral analysis of local atomic environments has become a powerful tool for studying solute atom segregation and interactions at grain boundaries in nanocrystalline alloys. When applied to individual grain boundaries, the spectral analysis has shown that solute-solute interaction can be either attractive or repulsive, with long-range relative attraction enhancing the likelihood for solute atoms to begin clustering. In this article, we combine this analysis with a new grain-boundary structure descriptor based on grain-boundary atom coordination, to investigate the impact of grain-boundary junctions on solute atom segregation in polycrystals. Specifically, we systematically characterize the tendency of solute clusters to begin forming at various types of ordinary grain boundaries, triple junctions, and high-order junctions in Ag polycrystals containing either Ni or Cu solute atoms. Our findings demonstrate that the formation of solute clusters at grain boundaries is primarily driven by long-range relative solute attraction, rather than short-range solute-solute interactions. Furthermore, this effect is most pronounced near grain-boundary junctions. Our study highlights the multiscale nature of solute segregation at crystalline interfaces and provides new insights into the complex phenomena governing heterogeneous solute segregation in grain-boundary networks.

Grain-boundary junction↗
DOE OSTI2026

A first principles approach for determining solute effect on electrical resistivity of Aluminum solid solution

There are no general approaches for predicting the effect of solutes on electrical resistivity changes in aluminum (Al) solid solutions. Here, we introduce a first principles-based approach for predicting temperature-dependent electrical resistivity of Al solid solutions. A combination of electronic structure methods was applied to calculate electronic scattering effects on chemical disorder and temperature induced atomic vibrations or phonons. Our calculations are validated by contrasting experimental resistivity measurements for two elements in Al solid solution: at 0.3 at. % concentration, Sn (an sp-valence solute) increases the residual resistivity by 0.2 μΩ·m, whereas Zr (a d-valence solute) causes a 2.5 μΩ·m increase. This trend may deviate for solute elements in Al that form semiconductors in pure state, like Si. Our findings provide an understanding of the role of valence electron character of solute atoms in determining electrical resistivity of Al alloys.

Samolyuk, German [ORNL] (ORCID:0000000168778255)↗
DOE OSTI2025

Solid solutions limited by grain-boundary solute clustering in ultrafine-grained alloys

Immiscible Ag-Cu alloys exhibit complex behavior due to varying Cu solid solubilities reported under equilibrium and metastable conditions. In ultrafine-grained alloys, these limits are further complicated by a high fraction of grain boundaries, where solute atoms tend to segregate and, in some cases, form clusters. Here, this study investigates the influence of Cu solute segregation and clustering on solid-solution limits in ultrafine-grained Ag-Cu alloys synthesized by magnetron sputtering with varying Cu content. X-ray diffraction peak shifts reveal a solid-solution concentration plateau for Cu contents from 4.9 to 11.7 at %, in contrast to the peak shifts predicted by density-functional theory for Ag-Cu alloys. Scanning transmission electron microscopy further reveals limited solid solubility and the formation of numerous Cu-rich clusters at grain boundaries. Atomistic simulations demonstrate that such limited solubility does not arise from grain boundary segregation alone, but only when strong solute-solute interactions promote the formation of grain-boundary Cu solute clusters.

Density-functional theory↗
DOE OSTI2025

Faster solutions to the interdiction defense problem using suboptimal solutions

The interdiction defense (ID) problem solves a defender-attacker-defender model where the defender and attacker share the same set of components to harden and target. Here, we build upon the best response intersection (BRI) algorithm by developing the BRI with suboptimal solutions (BRI-SS) algorithm to solve the ID problem. The BRI-SS algorithm utilizes off-the-shelf optimization solvers that return suboptimal solutions at no additional computation cost. We derive novel cuts from suboptimal solutions, reducing the number of iterations required for the algorithm to converge while maintaining optimality guarantees. We also present a heuristic that utilizes all obtained suboptimal solutions to select the next defense to evaluate at each iteration. We perform computational experiments applied to power grid interdiction on standard test cases. Our results demonstrate that the BRI-SS algorithm consistently outperforms the BRI algorithm across all test cases.

Computer science↗
DOE OSTI2024

Hydrothermal solution calorimetry in acidic aqueous solutions and revisiting the standard partial molal thermodynamic properties of Nd 3+ from 25 to 300 °C

The mobility of rare earth elements (REE) can be predicted in aqueous fluids using geochemical modeling but the accuracy of these models strongly depends on the availability of robust thermodynamic properties for the REE aqueous species. The REE 3+ aqua ions are important in the derivation of the formation constants of all the major REE complexes including the chloride, sulfate, and fluoride species which predominate in many hydrothermal-magmatic systems. However, the thermodynamic properties of the REE 3+ aqua ions are still commonly derived from the Helgeson-Kirkham-Flowers (HKF) equation of state parameters tabulated several decades ago. The standard state thermodynamic properties at reference conditions (25 °C and 1bar) and their extrapolations to high temperature need to be verified, if not revised, based on hydrothermal experiments. In this study, the enthalpy of solution was measured for synthetic Nd hydroxide from 25 to 150 ºC to retrieve the standard partial molal thermodynamic properties of Nd 3+ as a function of temperature. The experiments were conducted in aqueous perchloric acid based solutions with starting pH of 2 and varying ionic strength (0.01 to 0.09 mol/kg NaClO 4 ). The standard partial molal enthalpy of formation (Δ f H°) of Nd 3+ derived from the experimental study displays differences of up to 10 kJ/mol compared to the enthalpy values derived from the HKF equation of state in the studied temperature range. These inaccuracies are resolved by adjusting the standard partial molal Gibbs energy of formation (Δ f G°) of Nd 3+ at 25 °C and 1 bar from -672.0 to -679.7 kJ/mol. The heat capacity function (C p °) derived between 25 and 150 ºC can be described by: C p ° = a 0 + a 1 ·T + a 2 ·T -2 , with a 0 = 1256, a 1 = -2.68, a 2 = -55.56·10 6 and T in Kelvin. A set of recommended thermodynamic properties is provided for the Nd 3+ aqua ions and corrections are provided for the chloride and fluoride species to remain internally consistent with the experimentally derived properties. These results allow predicting accurately the solubility of monazite between 25 and 300 ºC. Before these corrections, the properties for the Nd 3+ aqua ions derived from the HKF parameters resulted in up to ~1.5 orders of magnitude lower monazite solubility than determined experimentally. Here, a revision of the REE +3 aqua ions properties is necessary to accurately predict the mobility of REE in hydrothermal acidic solutions.

58 GEOSCIENCES↗
DOE OSTI2025

Magnetism in EuAlSi and the Eu 1−𝑥 ⁢Sr 𝑥 ⁢ AlSi solid solution solid solution

The magnetic properties of EuAlSi, a compound comprising a honeycomb lattice of Al/Si atoms and a triangular lattice of Eu atoms, are presented. By means of single-crystal x-ray diffraction, we find that EuAlSi crystallizes in an AlB 2 -type structure with space group 𝑃⁢6/mmm and unit cell parameters 𝑎 = 4.2229⁢ (10) ⁢Å and 𝑐 = 4.5268 ⁢(12)⁢ Å. Our magnetic measurements indicate that EuAlSi is a soft ferromagnetic material with 𝑇 Curie = 25.8 K. The susceptibility follows the Curie-Weiss law at high temperatures, which allowed us to determine the paramagnetic Curie temperature 𝜃 𝑃 = 36.2 ⁢(1) ⁢K and an effective magnetic moment 𝜇 eff = 8.07 ⁢(1)⁢ µ 𝐵 /Eu. This value is in agreement with the theoretical value of 7.9 µ 𝐵 for Eu 2+ free ion. Moreover, we have prepared the Eu 1−𝑥 ⁢Sr 𝑥 ⁢ AlSi solid solution, where the atoms in the triangular lattice were systematically exchanged, in order to study the evolution of the collective quantum properties from the ferromagnetic EuAlSi toward the superconducting SrAlSi. Across the Eu 1−𝑥 ⁢Sr 𝑥 AlSi solid solution, the unit cell parameters change linearly, following Vegard’s law, and making the system reliable for studying composition dependence of the interplay between the crystal structure and physical properties. As the Sr content increases, i.e., 𝑥 increases, we note a consistent reduction of 𝜇 eff and 𝑇 Curie . Long-range magnetic order in Eu 1−𝑥 ⁢Sr 𝑥 ⁢ AlSi persists up to 𝑥 = 0.95, whereas superconductivity is only observed for samples with 𝑥 > 0.97.

Walicka, Dorota I. [University of Geneva (Switzerl↗
DOE OSTI2024

DUNE Phase II: scientific opportunities, detector concepts, technological solutions

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the European Strategy for Particle Physics. While the construction of the DUNE Phase I is well underway, this White Paper focuses on DUNE Phase II planning. DUNE Phase-II consists of a third and fourth far detector (FD) module, an upgraded near detector complex, and an enhanced 2.1 MW beam. The fourth FD module is conceived as a “Module of Opportunity”, aimed at expanding the physics opportunities, in addition to supporting the core DUNE science program, with more advanced technologies. This document highlights the increased science opportunities offered by the DUNE Phase II near and far detectors, including long-baseline neutrino oscillation physics, neutrino astrophysics, and physics beyond the standard model. It describes the DUNE Phase II near and far detector technologies and detector design concepts that are currently under consideration. A summary of key R&D goals and prototyping phases needed to realize the Phase II detector technical designs is also provided. DUNE's Phase II detectors, along with the increased beam power, will complete the full scope of DUNE, enabling a multi-decadal program of groundbreaking science with neutrinos.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Signatures of Thermoreversible Associations in X-ray and Neutron Scattering from Dilute Polyzwitterion Solutions

In aqueous solutions of polyzwitterions (PZs), an interplay between dipole–dipole interactions and hydration of zwitterionic groups can lead to thermoreversible associations, which have been difficult to detect in experiments. Here, in this study, we investigated dilute aqueous solutions of poly(1-(3-sulphonatopropyl)-2-vinylpyridinium) (P2VPPS) using small-angle X-ray and neutron scattering (SAXS and SANS) to probe the structure and neutron spin-echo (NSE) spectroscopy to probe dynamics. The SAXS and SANS data show that the correlation length increases with an increase in the concentration of P2VPPS for three different molecular weights. The addition of 0.1 M NaCl to one of the solutions led to almost no dependence of the correlation length on the concentration. Such a concentration dependence of the correlation length suggests the formation of clusters driven by thermoreversible associations in the solutions. The NSE measurements show that the solutions with a larger correlation length display slower relaxation, reflecting the reduced mobility of larger clusters. These results should be considered as signatures of thermoreversible associations in the solutions of P2VPPS. To establish a quantitative link between local structure (clusters) and dynamics in dilute solutions of P2VPPS, we combined a thermoreversible gelation theory for the structure of PZ solutions (Li, S.-F.; Muthukumar, M. Theory of Thermoreversible Gelation and Anomalous Concentration Fluctuations in Polyzwitterion Solutions. J. Chem. Phys. 2024, 161, 024903) with a model for the dynamics of the clusters (generalized Zimm model), developed in this work. Using such a theoretical framework, we have predicted the distribution of clusters in the solutions probed with SANS and SAXS. With the distributions, the generalized Zimm model has been used to extract the diffusion constant of the clusters and their characteristic size from the NSE data, where the latter agrees with the values estimated from the SAXS/SANS data. These findings confirm the presence of thermoreversible associations and establish a quantitative link between local structure (clusters) and dynamics in dilute solutions of P2VPPS. Furthermore, with growing interest in technological applications, this work can provide useful insights into the structural and dynamical properties of other PZ solutions.

field theory↗
DOE OSTI2025

Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble

In this work we explore the capability of physics-informed neural networks (PINNs) to discover multiple solutions. Many real-world phenomena governed by nonlinear differential equations (DEs), such as fluid flow, exhibit multiple solutions under the same conditions, yet capturing this solution multiplicity remains a significant challenge. A key difficulty lies in providing appropriate initial conditions or guesses, as widely used time-marching schemes and Newton’s method are highly sensitive to these choices when solving complex computational problems. While machine learning models, particularly PINNs, have shown promise in solving DEs, their ability to capture multiple solutions remains underexplored. In this work, we propose a simple and practical approach using PINNs to learn and discover multiple solutions. We first demonstrate that PINNs, when combined with random initialization and deep ensemble method—originally developed for uncertainty quantification—can effectively uncover multiple solutions to nonlinear ordinary and partial DEs. Although training large ensembles of PINNs may appear computationally demanding, this can be done efficiently using vectorization techniques supported by modern deep learning frameworks, allowing many networks to be trained simultaneously. Our approach highlights the critical role of initialization in shaping solution diversity, addressing an often-overlooked aspect of machine learning for scientific computing. Furthermore, we propose utilizing PINN-generated solutions as initial conditions or initial guesses for conventional numerical solvers to enhance accuracy and efficiency in capturing multiple solutions. Extensive numerical experiments, including the Allen–Cahn equation and cavity flow, where our approach successfully identifies both stable and unstable solutions, validate the effectiveness of our method. These findings establish a general and efficient framework for addressing solution multiplicity in nonlinear DEs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Uncertainty estimation of bifurcated solutions in the Rayleigh–Bénard problem for advanced nuclear reactors applications

Multiphysics models of nuclear reactors frequently comprise nonlinear systems of equations. The nonlinear nature of these models could lead to solution bifurcations, where a small change in a certain parameter, e.g., the thermophysical properties of the coolant, can lead to a sudden change in the system’s behavior. At the point in parameter space where this happens, called a critical point, the Jacobian matrix of the model’s nonlinear operator becomes singular potentially permitting multiple solutions to coexist. In this paper, we perform uncertainty estimation (UE) in a parameter range that includes bifurcated solutions within the context of Rayleigh–Bénard problem. We perform this analysis assuming uncertain temperature difference, and tilt angle for the iterative solution algorithm with a unit Prandtl number (Pr = 1). Also, we perform this analysis under uncertain thermophysical properties for both FLiBe molten salt and liquid sodium as working fluid. We deploy two approaches to compute statistical moments for the resulting distributions of selected flow-field variables. The first approach is the blind computation of the mean and the standard deviation without any consideration of solution bifurcation, while the second approach utilizes k-means clustering to cluster each branch’s solutions together and compute separate statistical moments for each branch. The statistical distributions are obtained by perturbing the selected parameters about nominal values that correspond to a solution on one of the valid branches, and that solution is used as initial guess for the iterative solution algorithm. We found that perturbation of any parameter when its nominal value is close to its critical point always leads to branch jumping, i.e., the iterations converge to a solution on a branch different from the branch of the initial guess. This produces a statistical ensemble comprised of fundamentally different solutions leading to wrong mean values and uncertainty estimates, whereas clustering provides an efficient way to deal with this type of computation. This work is important for developing Gen IV nuclear systems because many of these systems rely on natural convection for cooling especially in accident conditions.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Computationally efficient and error aware surrogate construction for numerical solutions of subsurface flow through porous media

Limiting the injection rate to restrict the pressure below a threshold at a critical location can be an important goal of simulations that model the subsurface pressure between injection and extraction wells. The pressure is approximated by the solution of Darcy’s partial differential equation for a given permeability field. The subsurface permeability is modeled as a random field since it is known only up to statistical properties. This induces uncertainty in the computed pressure. Solving the partial differential equation for an ensemble of random permeability simulations enables estimating a probability distribution for the pressure at the critical location. These simulations are computationally expensive, and practitioners often need rapid online guidance for real-time pressure management. An ensemble of numerical partial differential equation solutions is used to construct a Gaussian process regression model that can quickly predict the pressure at the critical location as a function of the extraction rate and permeability realization. The Gaussian process surrogate analyzes the ensemble of numerical pressure solutions at the critical location as noisy observations of the true pressure solution, enabling robust inference using the conditional Gaussian process distribution. Our first novel contribution is to identify a sampling methodology for the random environment and matching kernel technology for which fitting the Gaussian process regression model scales as O ( n log n ) instead of the typical O ( n 3 ) rate in the number of samples n used to fit the surrogate. The surrogate model allows almost instantaneous predictions for the pressure at the critical location as a function of the extraction rate and permeability realization. Our second contribution is a novel algorithm to calibrate the uncertainty in the surrogate model to the discrepancy between the true pressure solution of Darcy’s equation and the numerical solution. Finally, although our method is derived for building a surrogate for the solution of Darcy’s equation with a random permeability field, the framework broadly applies to solutions of other partial differential equations with random coefficients.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Isolating solvent–solute hydrogen bonding interactions via 2D IR solvation shell spectroscopy

The solvation shell around a solute is a fundamental feature of liquid-phase solutions, determining the behavior and properties of both the solute and the overall solution. Direct experimental measurements of the solvation shell properties are challenging due to the strong signals generated from the bulk solvent, which overwhelm the small contribution of the solvation shell. Here, we use ultrafast two dimensional infrared (2D IR) spectroscopy and intermolecular cross-peaks to isolate the IR absorption spectrum of methanol molecules in the solvation shell surrounding the solute N-methylacetamide. We demonstrate that the intermolecular coupling between the solvent and solute vibrations is indirectly mediated by a low-frequency hydrogen-bonding mode, suggesting an important mechanism for anharmonic coupling induced by hydrogen bonds. From the relative frequency shifts and cross-peak anisotropy, we find that methanol molecules surrounding N-methylacetamide form stronger and distinctly oriented hydrogen bonds than those in the bulk solvent. Here, we also compare these results with the solvent spectra of the solute N,N-dimethylacetamide to investigate how solute structural changes alter the solvation shell and the contribution of N–H hydrogen bond donation. Our results are supported by molecular dynamics simulations, which provide detailed insights into the hydrogen-bonding distributions. Through these results, we demonstrate 2D solvation shell spectroscopy to be a valuable method for investigating solvation structures and dynamics without interference from the bulk solvent.

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

Hierarchical Network Partitioning for Solution of Potential-Driven, Steady-State Nonlinear Network Flow Equations

The solution of potential-driven steady-state flow in large networks is a task which manifests in various engineering applications, such as transport of natural gas or water through pipeline networks. The resultant system of nonlinear equations depends on the network topology, and in general, there is no numerical algorithm that offers guaranteed convergence to the solution (assuming a solution exists). Some methods offer guarantees in cases where the network topology satisfies certain assumptions, but these methods fail for larger networks. On the other hand, the Newton-Raphson algorithm offers a convergence guarantee if the starting point lies close to the (unknown) solution. It would be advantageous to compute the solution of the large nonlinear system through the solution of smaller nonlinear sub-systems wherein the solution algorithms (Newton-Raphson or otherwise) are more likely to succeed. Here, this letter proposes and describes such a procedure, a hierarchical network partitioning algorithm that enables the solution of large nonlinear systems corresponding to potential-driven steady-state network flow equations.

42 ENGINEERING↗
DOE OSTI2025

Experimental observation of nonlinear relation between pressure and water flux is consistent with the solution-diffusion model

In several recent studies, it has been proposed that the fundamental understanding of penetrant transport in dense polymer membranes occurring via the solution-diffusion model, which has been the generally accepted theoretical framework for describing penetrant transport in such materials for the past several decades, is flawed. An alternate mechanistic framework based on the idea of two-phase flow in a porous medium (i.e., pore-flow) has been broadly advanced instead, with proponents of this approach claiming that the pore-flow theoretical framework provides the necessary mechanistic insight to design novel polymeric membrane materials for emerging applications. In this study, we show experimental results for hydraulic permeation of water that are entirely consistent with the solution-diffusion theory, without modification, for three dense polymeric membranes: crosslinked poly(ethylene glycol diacrylate) (XLPEGDA), Nafion 117 ionomer in the sodium counterion form (Nafion 117-Na), and cellulose acetate (CA). By measuring water flux at transmembrane pressures up to 240 bar, we observe a nonlinear relationship between the transmembrane pressure (TMP) and water flux, J w , for XLPEGDA and Nafion 117-Na, while this relationship is linear for CA. We demonstrate that the behavior of these three materials is described via the solution-diffusion model. According to the solution-diffusion model, flux is, to a good approximation, proportional to the transmembrane concentration difference induced by the pressure difference across the membrane, rather than to TMP itself. Water sorption isotherms are reported for all three materials. They further justify the nonlinear relationship between TMP and J w observed in XLPEGDA and Nafion 117-Na, emphasizing that the nonlinearity in the flux/TMP relationship stems from nonlinearities in the sorption isotherm with pressure. Additionally, the relationship between water flux and TMP can be predicted, a priori, with no adjustable parameters when a predictive model for the diffusion coefficient of water is employed in conjunction with the experimental water sorption isotherms in the solution-diffusion model. Furthermore, our results demonstrate the validity of the solution-diffusion model to describe transport of penetrants in dense polymer membranes, while highlighting the sensitivity of the solution-diffusion model to the many physical and mathematical simplifications commonly applied to the theory in literature.

materials↗
DOE OSTI2025

A Semi-Empirical Density Law for Ternary, Homogeneous PuCl 3 /HCl/H 2 O Solutions

Nuclear material operations pose unique hazards that are not encountered in other chemical, energy, or manufacturing industries. One of these hazards is the potential for a nuclear criticality accident when handling fissile isotopes such as 235 U and 239 Pu. These hazards are particularly high when fissile material is dissolved in solution as the neutron behaviors of the system can change rapidly with the physical and chemical changes accessible in solution. Current estimates of solution density used for criticality safety are outdated and hinder fissile material handling. Developing new estimates for these safety calculations requires experimental characterization and the derivation of empirical density models. We have derived a density law describing PuCl 3 /HCl/H 2 O solutions from experimental data characterizing solution density. Density data was treated using a Pitzer-derived eight-parameter equation, defining density as a function of analyte concentrations, temperature, and interactions between these variables. The model is predictive across the concentration and temperature ranges from which it was derived. The potential effects of varying oxidation states of plutonium, which are easily accessible in aqueous media, on the bulk solution density of the ternary system were also investigated. The resulting Pitzer-derived density law was applied to a nuclear criticality safety model, and the impact of the experimental characterization of solution density relative to previous estimates was demonstrated to be significant and suggest that the current approach to estimating density in nuclear criticality safety calculations may lead to overly conservative controls.

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

Determination of Intermolecular Distances in Dilute Solutions of Macroions and Their Direct Correlations with Self-Assembly and Macrophase Transitions

Here, this work demonstrates new attempts to determine the intermolecular distances between charged macroionic solutes in their dilute solutions, which regulate the solute’s microphase (self-assembly) and macrophase transitions. Small-angle X-ray scattering (SAXS) and analytical ultracentrifuge (AUC) techniques were applied to determine the intermolecular distances for the 2.42 nm-sized, spherical uranyl peroxide molecular cluster {U 60 } in their self-assembled states in dilute aqueous solution and concentrated phases, respectively. The counterion-mediated attraction among {U 60 } leads to characteristic, inter-{U 60 } distances in solutions, which increase gradually with decreasing the strength of introduced counterions (e.g., lower valency). The gradual increment of inter-{U 60 } distance demonstrates a nice correlation with the macroscopic phase transitions of {U 60 }, from single crystals to concentrated fluids containing rigid 2-D sheets, then to dilute solutions containing a small amount of standalone, floating 2-D sheets of {U 60 }, and finally to dilute solutions containing a limited amount of self-assembled single-layered, spherical blackberry structures of different sizes from the bending of more flexible 2-D sheets.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Elucidating molecular scale interactions underlying the freezing behavior of salt solutions in silica nanopores

Elucidating the influence of nanoscale confinement on the freezing behavior of salt solutions is of fundamental interest to environmental security and materials science and engineering. Specific structural information such as the coordination environment of ions in confined aqueous medium, effects on the extended hexagonal network of water molecules and their mutual non-bonding interactions in confinement are sparse in the literature along with the change in the dynamical characteristics of water in the presence of ions. To address these knowledge gaps, the current study is focused on investigating the influence of reduced dimensionality arising from nanoscale confinement on the structural evolution of salt solutions on freezing and the associated fluid–surface interactions. In this regard, operando wide-angle X-ray scattering (WAXS) measurements and classical molecular dynamics (MD) simulations are conducted with water and 0.5 M CaCl 2 , MgCl 2 and KCl solutions confined in 4 nm sized SBA-15 silica pores upon cooling from 300 K to 200 K. The freezing point of the salt solutions is depressed to 235 K which is about 10 K lower than that of confined water. The translational dynamics of confined salt solutions indicates shifts in the fragile-to-strong dynamical crossover to a lower temperature compared to pure water. The strong electrostatic attraction between the cations and the surrounding water molecules contributes to the freezing point depression in confined salt solutions. These insights unlock the molecular-scale basis and mechanisms underlying the freezing behavior of confined salt solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗