A Holistic Approach for Elucidating Local Structure, Dynamics, and Speciation in Molten Salts with High Structural Disorder

Correlative analysis of Ni(ii) coordination states in molten salts using a combination of X-ray and optical spectroscopies and simulations

Understanding the factors that control the speciation of metal ions in molten salts is crucial for the successful deployment of molten salts in both concentrated solar power and nuclear energy applications. The speciation of the Ni(ii) ion is of interest because it is a common corrosion product, and the distribution of coordination states it occupies is highly sensitive to the molten salt matrix. We employ in situ X-ray absorption spectroscopy (XAS), optical spectroscopy, and ab initio molecular dynamics (AIMD) simulations to investigate and understand the heterogeneities of Ni(ii) coordination in LiCl-KCl, NaCl-MgCl2, and LiCl-ZnCl2 molten salt systems. The main challenge lies in identifying the population distribution of Ni(ii) coordination states as a function of temperature and melt composition. We combined the multivariate curve resolution - alternating least squares (MCR-ALS) analysis of the XAS data and principal component analysis (PCA) of the optical spectra to determine the number of unique coordination states coexisting in the molten state, extract X-ray spectra for each state, and obtain their mixing fractions at different temperatures and for different salt mixtures. AIMD simulations were essential in identifying the coordination states corresponding to the deconvoluted spectra. The differences in the coordination states of Ni(ii) in different salt systems are discussed in terms of the effects of the varying polarizing powers of the cations in the host salt matrix on chloride ion coordination to Ni(ii). Such elucidation of the local structure adopted by metal ions enables a better understanding of the factors controlling the speciation of ions and their effect on molten salt properties.

Chemical Footprints of Thorium and Uranium in Molten LiF-BeF2 Explored by First-Principles Molecular Dynamics Simulations

The chemical forms and transport properties of thorium and uranium ions in molten LiF-BeF2 are systemically studied via first-principles molecular dynamics simulations. The densities, diffusion coefficients, densities of electronic states, and ionic pair and cluster structures of molten LiF-BeF2-ThF4 (FLiBeTh), LiF-BeF2-UF4 (FLiBeU), and LiF-BeF2-ThF4-UF4 (FLiBeThU) are analyzed in detail. Studies have shown that the density and thermal expansion coefficient of molten FLiBeTh are higher than those of FLiBeU in the temperature range of 873-1073 K. Besides, FLiBeTh has higher electron energy, and the active Th electrons contribute to the diversification of its coordination structure and the improvement of diffusion property. Furthermore, the concept of Be-F tetrahedron stress index (SIT) is proposed in molten FLiBe, and the higher SIT of molten FLiBeU is one of the structural factors leading to slow diffusion coefficients of Be and F ions. Overall, the understanding and characterization of fuel salt structure and property are underscored, and the relationships between microstructure and diffusivity performance are preliminarily established.

Computing chemical potentials with machine-learning-accelerated simulations to accurately predict thermodynamic properties of molten salts

The successful design and deployment of next-generation nuclear technologies heavily rely on thermodynamic data for relevant molten salt systems. However, the lack of accurate force fields and efficient methods has limited the quality of thermodynamic predictions from atomistic simulations. Here we propose an efficient free energy framework for computing chemical potentials, which is the central free energy quantity behind many thermodynamic properties. We accelerate our simulations without sacrificing accuracy by using machine learning interatomic potentials trained on density functional theory (DFT) data. Using lithium chloride as our model system, we compute chemical potentials with DFT-accuracy for solid and liquid phases by transmuting ions into noninteracting particles. Notably, in the liquid phase, we demonstrate consistency whether we transmute one ion pair or the entire system into ideal gas particles. By locating the temperature where the chemical potential of solid and liquid phases cross, we predict a melting point of 880 ± 18 K for lithium chloride, which is remarkably close to the experimental value of 883 K. With this successful demonstration, we lay the foundation for high-throughput thermodynamic predictions of many properties that can be derived from the chemical potentials of the minority and majority components in molten salts.

Elucidating the Transition of 3D Morphological Evolution of Binary Alloys in Molten Salts with Metal Ion Additives

Molten salts serve as effective high-temperature heat transfer fluids and thermal storage media used in a wide range of energy generation and storage facilities, including concentrated solar power plants, molten salt reactors and high-temperature batteries. However, at the salt-metal interfaces, a complex interplay of charge-transfer reactions involving various metal ions, generated either as fission products or through corrosion of structural materials, takes place. Simultaneously, there is a mass transport of ions or atoms within the molten salt and the parent alloys. The precise physical and chemical mechanisms leading to the diverse morphological changes in these materials remain unclear. To address this knowledge gap, this work employed a combination of synchrotron X-ray nanotomography and electron microscopy to study the morphological and chemical evolution of Ni-20Cr in molten KCl-MgCl2, while considering the influence of metal ions (Ni2+, Ce3+, and Eu3+) and variations in salt composition. Our research suggests that the interplay between interfacial diffusivity and reactivity determines the morphological evolution. The summary of the associated mass transport and reaction processes presented in this work is a step forward toward achieving a fundamental comprehension of the interactions between molten salts and alloys. Overall, the findings offer valuable insights for predicting the diverse chemical and structural alterations experienced by alloys in molten salt environments, thus aiding in the development of protective strategies for future applications involving molten salts.

Exploring Cr and molten salt interfacial interactions for molten salt applications

Molten salts play an important role in various energy-related applications such as high-temperature heat transfer fluids and reaction media. However, the extreme molten salt environment causes the degradation of materials, raising safety and sustainability challenges. A fundamental understanding of material-molten salt interfacial evolution is needed. This work studies the transformation of metallic Cr in molten 50/50 mol% KCl-MgCl2via multi-modal in situ synchrotron X-ray nano-tomography, diffraction and spectroscopy combined with density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations. Notably, in addition to the dissolution of Cr in the molten salt to form porous structures, a δ-A15 Cr phase was found to gradually form as a result of the metal-salt interaction. This phase change of Cr is associated with a change in the coordination environment of Cr at the interface. DFT and AIMD simulations provide a basis for understanding the enhanced stability of δ-A15 Cr vs. bcc Cr, by revealing their competitive phase thermodynamics at elevated temperatures and probing the interfacial behavior of the molten salt at relevant facets. This study provides critical insights into the morphological and chemical evolution of metal-molten salt interfaces. The combination of multimodal synchrotron analysis and atomic simulation also offers an opportunity to explore a broader range of systems critical to energy applications.

High-Index NiO Particle Synthesis in Alkali Chloride Salts: Nonclassical Crystallization Pathways and Thermally-Induced Surface Restructuring

The formation mechanism(s) of high-index facets in metal oxides is not widely understood but remains a topic of interest owing to the challenges of stabilizing high-energy surfaces. These metal oxide crystal surfaces are expected to provide unique physicochemical characteristics; therefore, understanding crystallization pathways may enable the rational design of materials with controlled properties. Here the crystallization of NiO via thermal decomposition of a nickel source in excess of alkali chlorides is examined, focusing on KCl, which produces trapezohedral NiO (311) particles that are difficult to achieve through alternative methods. Trapezohedral NiO crystals are confirmed to grow via a molten eutectic where NiO nucleation is followed by nonclassical crystallization through processes resembling colloidal assembly. Aggregates comprised of NiO nanocrystals form mesostructures that ripen with heating time and exhibit fewer grain boundaries as they transition into single-crystalline particles. At temperatures higher than those of NiO crystallization, there is a restructuring of (311) facets into microfacets exposing (111) and (100) surfaces. These findings illustrate the complex crystallization processes taking place during molten salt synthesis. The ability to generate metal oxide particles with high-index facets has the potential to be a more generalized approach to unlock the physicochemical properties of materials for diverse applications.

Heterogeneous Structure, Mechanisms of Counterion Exchange, and the Spacer Salt Effect in Complex Molten Salt Mixtures Including LaCl3

Complex molten chloride salt mixtures of uranium, magnesium, and sodium are top candidates for promising nuclear energy technologies to produce electricity based on molten salt reactors. From a local structural perspective, LaCl3 is similar to UCl3 and hence a good proxy to study these complex salt mixtures. As fission products, lanthanide salts and their mixtures are also very important in their own right. This article describes from an experimental and theory perspective how very different the structural roles of MgCl2 and NaCl are in mixtures with LaCl3. We find that, whereas MgCl2 becomes an integral part of multivalent ionic networks, NaCl separates them. In a recent article (J. Am. Chem. Soc. 2022, 144, 21751-21762) we have called the disruptive behavior of NaCl "the spacer salt effect". Because of the heterogeneous nature of these salt mixtures, there are multiple structural motifs in the melt, each with its particular free energetics. Our work identifies and quantifies these; it also elucidates the mechanisms through which Cl- ions exchange between Mg2+-rich and La3+-rich environments.

Compositional transferability of deep potential in molten LiF-BeF2 and LaF3 mixtures: prediction of density, viscosity, and local structure

The accumulation of lanthanide fission products carries the risk of altering the structure and properties of the nuclear fuel carrier salt LiF-BeF2 (Flibe), thereby downgrading the operating efficiency and safety of the molten salt reactor. However, the condition-limited experimental measurements, spatiotemporal-limited first-principles calculations, and accuracy-limited classical dynamic simulations are unable to capture the precise local structure and reliable thermophysical properties of heterogeneous molten salts. Therefore, the deep potential (DP) of LaF3 and Flibe molten mixtures is developed here, and DP molecular dynamics simulations are performed to systemically study the densities, diffusion coefficients, viscosities, radial distribution functions and coordination numbers of multiple molten Flibe + xLaF3, the quantitative relationships between these properties and LaF3 concentration are investigated, and the potential structure-property relationships are analyzed. Eventually, the transferability of DP on molten Flibe + LaF3 with different formulations as well as the predictability of structures and properties are achieved at the nanometer spatial scale and the nanosecond timescale.

Tracing mechanistic pathways and reaction kinetics toward equilibrium in reactive molten salts

In the dynamic environment of multi-component reactive molten salts, speciation unfolds as a complex process, involving multiple competing reaction pathways that are likely to face free energy barriers before reaching the reaction equilibria. Herein, we unravel intricate speciation in the AlCl3-KCl melt compositions with rate theory and ab initio molecular dynamics simulations. We find that the compositions with 100 and 50 mol% AlCl3 exclusively comprise neutral Al2Cl6 dimers and charged AlCl4- monomers, respectively. In intermediate AlCl3-KCl compositions, the chemical speciation proves to be a very complex process, requiring over 0.5 nanosecond to reach an equilibrium distribution of multiple species. It is a consequence of the competitive formation and dissociation of additional species, including charged Al dimers, trimers, and tetramers. Here, the species formation occurs through ion exchange events, which we explain by computing free energy landscapes and employing a Marcus-like rate theory. We show that both interspecies and intraspecies ion exchanges are probable and are dictated by the local structural reorganization reflected in the change of local coulombic fields. The species distributions are validated by comparing computed Raman spectra and neutron structure factors with the available experimental data. We find an excellent simulation-experiment agreement in both cases. Nevertheless, Raman spectroscopy turns out to be particularly advantageous for distinguishing between unique species distributions because of the distinct vibrational signatures of different species. The mechanistic insight into reaction dynamics gained in this study will be essential for the advancement of molten salts as reactive media in high-temperature energy applications.

Probing the local structure of FLiBe melts and solidified salts by in situ high-temperature NMR

The 2LiF-BeF2 (FLiBe) salt melt is considered the primary choice for a coolant and fuel carrier for the generation IV molten salt reactor (MSR). However, the basics of ionic coordination and short-range ordered structures have been rarely reported due to the toxicity and volatility of beryllium fluorides, as well as the lack of suitable high-temperature in situ probe methods. In this work, the local structure of FLiBe melts was investigated in detail using the newly designed HT-NMR method. It was found that the local structure was comprised of a series of tetrahedral coordinated ionic clusters (e.g., BeF42-, Be2F73-, Be3F104-, and polymeric intermediate-range units). Li+ ions were coordinated by BeF42- ions and the polymeric Be-F network through the analysis of the NMR chemical shifts. Using solid-state NMR, the structure of solid FLiBe solidified mixed salts was confirmed to form a 3D network structure, significantly similar to those of silicates. The above results provide new insights into the local structure of FLiBe salts, which verifies the strong covalent interactions of Be-F coordination and the specific structural transformation to the polymeric ions above 25% BeF2 concentration.

Development of Deep Potentials of Molten MgCl2-NaCl and MgCl2-KCl Salts Driven by Machine Learning

Molten MgCl2-based chlorides have emerged as potential thermal storage and heat transfer materials due to high thermal stabilities and lower costs. In this work, deep potential molecular dynamics (DPMD) simulations by a method combination of the first principle, classical molecular dynamics, and machine learning are performed to systemically study the relationships of structures and thermophysical properties of molten MgCl2-NaCl (MN) and MgCl2-KCl (MK) eutectic salts at the temperature range of 800-1000 K. The densities, radial distribution functions, coordination numbers, potential mean forces, specific heat capacities, viscosities, and thermal conductivities of these two chlorides are successfully reproduced under extended temperatures by DPMD with a larger size (5.2 nm) and longer timescale (5 ns). It is concluded that the higher specific heat capacity of molten MK is originated from the strong potential mean force of Mg-Cl bonds, whereas the molten MN performs better in heat transfer due to the larger thermal conductivity and lower viscosity, attributed to the weak interaction between Mg and Cl ions. Innovatively, the plausibility and reliability of microscopic structures and macroscopic properties for molten MN and MK verify the extensibilities of these two deep potentials in temperatures, and these DPMD results also provide detailed technical parameters to the simulations of other formulated MN and MK salts.

How machine learning can accelerate electrocatalysis discovery and optimization

Advances in machine learning (ML) provide the means to bypass bottlenecks in the discovery of new electrocatalysts using traditional approaches. In this review, we highlight the currently achieved work in ML-accelerated discovery and optimization of electrocatalysts via a tight collaboration between computational models and experiments. First, the applicability of available methods for constructing machine-learned potentials (MLPs), which provide accurate energies and forces for atomistic simulations, are discussed. Meanwhile, the current challenges for MLPs in the context of electrocatalysis are highlighted. Then, we review the recent progress in predicting catalytic activities using surrogate models, including microkinetic simulations and more global proxies thereof. Several typical applications of using ML to rationalize thermodynamic proxies and predict the adsorption and activation energies are also discussed. Next, recent developments of ML-assisted experiments for catalyst characterization, synthesis optimization and reaction condition optimization are illustrated. In particular, the applications in ML-enhanced spectra analysis and the use of ML to interpret experimental kinetic data are highlighted. Additionally, we also show how robotics are applied to high-throughput synthesis, characterization and testing of electrocatalysts to accelerate the materials exploration process and how this equipment can be assembled into self-driven laboratories.

Transferable Deep Learning Potential Reveals Intermediate-Range Ordering Effects in LiF-NaF-ZrF4 Molten Salt

LiF-NaF-ZrF₄ multicomponent molten salts are promising candidate coolants for advanced clean energy systems owing to their desirable thermophysical and transport properties. However, the complex structures enabling these properties, and their dependence on composition, is scarcely quantified due to limitations in simulating and interpreting experimental spectra of highly disordered, intermediate-ranged structures. Specifically, size-limited ab initio simulations and accuracy-limited classical models used in the past are unable to capture a wide range of fluctuating motifs found in the extended heterogeneous structures of liquid salt. This greatly inhibits our ability to design tailored compositions and materials. Here, accurate, efficient, and transferable machine learning potentials are used to predict structures far beyond the first coordination shell in LiF-NaF-ZrF₄. Neural networks trained at only eutectic compositions with 29% and 37% ZrF₄ are shown to accurately simulate a wide range of compositions (11-40% ZrF₄) with dramatically different coordination chemistries, while showing a remarkable agreement with theoretical and experimental Raman spectra. The theoretical Raman calculations further uncovered the previously unseen shift and flattening of bending band at ∼250 cm^-1 which validated the simulated extended-range structures as observed in compositions with higher than 29% ZrF₄ content. In such cases, machine learning-based simulations capable of accessing larger time and length scales (beyond 17 Å) were critical for accurately predicting both structure and ionic diffusivities.

First-principles molecular dynamics simulations of UCln-MgCl2 (n = 3, 4) molten salts

Molten chlorides are a preferred choice for fast-spectrum molten salt reactors. Molten MgCl₂ forms eutectic mixtures with NaCl and is considered as a promising dilutant to dissolve fuel salts such as UCl₃ and UCl₄. However, the structure and chemical properties of UCl_n (n = 3, 4) in molten MgCl₂ are not well understood. Here we use first-principles molecular dynamics to investigate the molten salt system UCl_n-MgCl₂ (n = 3, 4) at various concentrations of U³⁺ and U⁴⁺. It is found that the coordination environment of Cl^- around U³⁺, especially in the first coordination shell, varies only slightly with the uranium concentration and that both the 7-fold coordinate (UCl₇^4-) and 6-fold coordinate (UCl₆^3-) structures dominate at ∼40%, leading to an average coordination number of 6.6-6.7. A network or polymeric structure of U³⁺ cations sharing Cl^- ions is extensively formed when the mole fraction of UCl₃ is greater than 0.2. In contrast, the average coordination number of Cl^- around U⁴⁺ is about 6.4 for a mole fraction of UCl₄, x(UCl₄), of 0.1 but decreases to 6.0 for x(UCl₄) = 0.2 and then stays at about 6.0-6.2 with the uranium concentration. The 6-fold coordinate structure (UCl₆^2-) is the most populous in UCl₄-MgCl₂, at about 60%. U-Cl network formation becomes dominant (>50%) only when x(UCl₄) > 0.5. Unlike Na⁺, Mg²⁺ forms a network structure with Cl^- ions and when x(UCl₃) or x(UCl₄) < 0.5, over 90% of Mg²⁺ ions are part of a network structure, implying the complex influences from Mg²⁺ on the coordination of Cl around U. The present work reveals the impact of MgCl₂ as a solvent for UCl_n (n = 3, 4) on the U-Cl coordination and structure, and motivates further studies of their transport properties and the tertiary systems containing MgCl₂-UCl_n.

Insights into Ionic Liquids: From Z-Bonds to Quasi-Liquids

Ionic liquids (ILs) hold great promise in the fields of green chemistry, environmental science, and sustainable technology due to their unique properties, such as a tailorable structure, the various types available, and their environmentally friendly features. On the basis of multiscale simulations and experimental characterizations, two unique features of ILs are as follows: (1) strong coupling interactions between the electrostatic forces and hydrogen bonds, namely in the Z-bond, and (2) the unique semiordered structure and properties of ultrathin films, specifically regarding the quasi-liquid. In accordance with the aforementioned theoretical findings, many cutting-edge applications have been proposed: for example, CO₂ capture and conversion, biomass conversion and utilization, and energy storage materials. Although substantial progress has been made recently in the field of ILs, considerable challenges remain in understanding the nature of and devising applications for ILs, especially in terms of e.g. in situ/real-time observation and highly precise multiscale simulations of the Z-bond and quasi-liquid. In this Perspective, we review recent developments and challenges for the IL research community and provide insights into the nature and function of ILs, which will facilitate future applications.

Dilute Alloys Based on Au, Ag, or Cu for Efficient Catalysis: From Synthesis to Active Sites

The development of new catalyst materials for energy-efficient chemical synthesis is critical as over 80% of industrial processes rely on catalysts, with many of the most energy-intensive processes specifically using heterogeneous catalysis. Catalytic performance is a complex interplay of phenomena involving temperature, pressure, gas composition, surface composition, and structure over multiple length and time scales. In response to this complexity, the integrated approach to heterogeneous dilute alloy catalysis reviewed here brings together materials synthesis, mechanistic surface chemistry, reaction kinetics, in situ and operando characterization, and theoretical calculations in a coordinated effort to develop design principles to predict and improve catalytic selectivity. Dilute alloy catalysts─in which isolated atoms or small ensembles of the minority metal on the host metal lead to enhanced reactivity while retaining selectivity─are particularly promising as selective catalysts. Several dilute alloy materials using Au, Ag, and Cu as the majority host element, including more recently introduced support-free nanoporous metals and oxide-supported nanoparticle "raspberry colloid templated (RCT)" materials, are reviewed for selective oxidation and hydrogenation reactions. Progress in understanding how such dilute alloy catalysts can be used to enhance selectivity of key synthetic reactions is reviewed, including quantitative scaling from model studies to catalytic conditions. The dynamic evolution of catalyst structure and composition studied in surface science and catalytic conditions and their relationship to catalytic function are also discussed, followed by advanced characterization and theoretical modeling that have been developed to determine the distribution of minority metal atoms at or near the surface. The integrated approach demonstrates the success of bridging the divide between fundamental knowledge and design of catalytic processes in complex catalytic systems, which can accelerate the development of new and efficient catalytic processes.

Solving the structure of "single-atom" catalysts using machine learning - assisted XANES analysis

"Single-atom" catalysts (SACs) have demonstrated excellent activity and selectivity in challenging chemical transformations such as photocatalytic CO₂ reduction. For heterogeneous photocatalytic SAC systems, it is essential to obtain sufficient information of their structure at the atomic level in order to understand reaction mechanisms. In this work, a SAC was prepared by grafting a molecular cobalt catalyst on a light-absorbing carbon nitride surface. Due to the sensitivity of the X-ray absorption near edge structure (XANES) spectra to subtle variances in the Co SAC structure in reaction conditions, different machine learning (ML) methods, including principal component analysis, K-means clustering, and neural network (NN), were utilized for in situ Co XANES data analysis. As a result, we obtained quantitative structural information of the SAC nearest atomic environment, thereby extending the NN-XANES approach previously demonstrated for nanoparticles and size-selective clusters.

Chemistry Dissolved in Ionic Liquids. A Theoretical Perspective

The theoretical treatment of ionic liquids must focus now on more realistic models while at the same time keeping an accurate methodology when following recent ionic liquids research trends or allowing predictability to come to the foreground. In this Perspective, we summarize in three cases of advanced ionic liquid research what methodological progress has been made and point out difficulties that need to be overcome. As particular examples to discuss we choose reactions, chirality, and radicals in ionic liquids. All these topics have in common that an explicit or accurate treatment of the electronic structure and/or intermolecular interactions is required (accurate methodology), while at the same time system size and complexity as well as simulation time (realistic model) play an important role and must be covered as well.