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At least 613 records · Page 34

Application of differential resonant high-energy X-ray diffraction to three-dimensional structure studies of nanosized materials: A case study of Pt–Pd nanoalloy catalysts

Atoms in many of the increasingly complex nanosized materials of interest to science and technology do not necessarily occupy the vertices of Bravais lattices. The atomic scale structure of such materials is difficult to determine by traditional X-ray diffraction and so their functional properties remain difficult to optimize by rational design. Here, the three-dimensional structure of Pt x Pd 100– x nanoalloy particles is determined, where x = 0, 14, 36, 47, 64 and 100, by a non-traditional technique involving differential resonant high-energy X-ray diffraction experiments conducted at the K edge of Pt and Pd. The technique is coupled with three-dimensional modeling guided by the experimental total and element-specific atomic pair distribution functions. Furthermore, using DFT (density functional theory) calculation based on the positions of atoms in the obtained three-dimensional structure models, the catalytic performance of Pt–Pd particles is explained. Furthermore, differential resonant high-energy X-ray diffraction is shown to be an excellent tool for three-dimensional structure studies of nanosized materials. The experimental and modeling procedures are described in good detail, to facilitate their wider usage.

36 MATERIALS SCIENCE↗

Long-range dispersion-corrected density functional for noncovalent interactions

Noncovalent interactions are important in determining structures and properties of molecular complexes and biological molecules, and for understanding adsorption processes in chemistry and biological science, and are still challenging to conventional density functional theories. In this work, the recently developed Tao-Mo (TM) meta-GGA (generalized gradient approximation) functional is combined with the D3 scheme of long-range van der Waals (vdW) interaction correction and the parameters of damping function are optimized with the S66[Formula: see text]×[Formula: see text]8 set. The resulting TM-D3 method is applied to the medium-sized molecular set S22 and large size molecular complexes set L7 to calculate intramolecular interaction energies. The TM-D3 method produces the best accuracy for the S22 set with a MAE of 0.2 kcal/mol, improving upon the PBE-D3 (MAE[Formula: see text]=[Formula: see text]0.5 kcal/mol), PBE0-D3 (MAE[Formula: see text]=[Formula: see text]0.5 kcal/mol), TPSS-D3 (MAE[Formula: see text]=[Formula: see text]0.4 kcal/mol), M06L (MAE[Formula: see text]=[Formula: see text]0.8 kcal/mol), and SCAN-D3 (MAE[Formula: see text]=[Formula: see text]0.4 kcal/mol) methods. For the large size set L7, the TM-D3 (MAE[Formula: see text]=[Formula: see text]2.1 kcal/mol) also performs better than the PBE-D3 (MAE[Formula: see text]=[Formula: see text]2.6 kcal/mol), SCAN-D3 (2.5 kcal/mol) and M06L (3.0 kcal/mol), but not accurate than the PBE0-D3 (MAE[Formula: see text]=[Formula: see text]0.8 kcal/mol) and TPSS-D3 (MAE[Formula: see text]=[Formula: see text]1.1 kcal/mol). However, overall, the TM-D3 method performs very well with an error of 2.7% of mean binding of the S22 set and an error of 12.6% of the mean binding of the L7 set for the two typical and important medium and large size molecular complex sets. The success of the dispersion-corrected TM functional benefits from the ability of the plain TM functional to capture the short-range vdW interaction or extend the short-range interaction to the middle range, and the right coupling between the TM and the long-range vdW correction D3 scheme, leading to the improved description of noncovalent interactions.

Physics↗

Identification of the Selective Sites for Electrochemical Reduction of CO to C 2+ Products on Copper Nanoparticles by Combining Reactive Force Fields, Density Functional Theory, and Machine Learning

Recent experiments have shown that CO reduction on oxide derived Cu nanoparticles (NP) are highly selective toward C 2+ products. However, understanding of the active sites on such NPs is limited, because the NPs have ~200 000 atoms with more than 10 000 surface sites, far too many for direct quantum mechanical calculations and experimental identifications. We show here how to overcome the computational limitation by combining multiple levels of theoretical computations with machine learning. This approach allows us to map the machine learned CO adsorption energies on the surface of the copper nanoparticle to construct the active site visualization (ASV). Furthermore, we identify the structural criteria for optimizing selective reduction by predicting the reaction energies of the potential determining step, $ΔE_{OCCOH}$, for the C 2+ product. Based on this structural criterion, we design a new periodic copper structure for CO reduction with a theoretical faradaic efficiency of 97%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding Redox Organic Behavior in Deep Eutectic Solvents: Considerations for Molecular Design

Electrolytes based on deep eutectic solvents (DESs) coupled with redox active organic molecules have shown potential as a versatile and energy dense electrochemical energy storage system. However, progress in these systems has been held back by a lack of understanding of the irregular behavior displayed when redox active organic molecules are transitioned from other solvent systems. In this work, the hydrogen bonding characteristics of a series of redox organic molecules were investigated through infrared spectroscopy and molecular modeling. New understanding of these interactions was then used to explain their electrochemical behavior in a DES electrolyte. A model was used to predict the behavior of new derivatives towards the design of an optimized redox organic-DES system. Hydrogen bonding between the redox molecules and the solvent was found to significantly shift the potential of a redox reaction more positive when a hydrogen bond forms at the redox active site. It was predicted that functionalizing a molecule with electron withdrawing groups to lower the electron density of the redox active functional group lowers the strength of the hydrogen bond and thus alleviates the undesirable potential shift. This hypothesis was demonstrated by the addition of nitro groups to fluorenones.

25 ENERGY STORAGE↗

Reaction Mechanism of Vapor-Phase Formic Acid Decomposition over Platinum Catalysts: DFT, Reaction Kinetics Experiments, and Microkinetic Modeling

A combination of periodic density functional theory (DFT, PW91-GGA) calculations, reaction kinetics experiments, and mean-field microkinetic modeling is used to derive insights on the reaction mechanism and determine the nature of the active site under reaction conditions for the vapor-phase decomposition of formic acid (FA, HCOOH) over Pt/C catalysts. Microkinetic models formulated using DFT energetics derived on the clean Pt(100) and Pt(111) required large parameter adjustments to reproduce the experimentally measured apparent activation energies and reaction orders. Further, these models predicted high surface coverage of adsorbed carbon monoxide (CO*), inconsistent with the environment of the active site in the DFT calculations on the clean surfaces. Consequently, we reperformed DFT calculations for the entire reaction network on partially CO*-covered (4/9 monolayer, ML) Pt(111) and Pt(100). The resultant microkinetic models, with thermochemistry and kinetics explicitly dependent on CO* coverage, were able to reproduce the experimentally determined activation energies and reaction orders, in addition to being self-consistent in CO* coverage. Our results suggest that Pt(100) is likely poisoned by CO* under typical reaction conditions and does not contribute significantly to the experimentally observed reactivity. Instead, we find that Pt(111) better represents the active site for FA decomposition reaction on Pt/C catalysts. The optimized model on 4/9 ML CO*-covered Pt(111) suggests that the reaction occurs via the carboxyl (COOH*) intermediate and that the spectator CO*-assisted pathways play a significant role under reaction conditions. Lastly, this study underscores the importance of spectator species on the energetics and the mechanism of a catalytic reaction and their key role in developing a model that better addresses the nature of the active site under realistic catalytic reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Facet-Dependent Photodegradation of Methylene Blue by Hematite Nanoplates in Visible Light

The expression of specific crystal facets in different nanostructures is known to play a vital role in determining the sensitivity toward photodegradation of organics, which can generally be ascribed to differences in surface structure and energy. Herein, we report the synthesis of hematite nanoplates with controlled relative exposure of basal (001) and edge (012) facets, enabling us to establish direct correlation between surface structure and the photocatalytic degradation efficiency of methylene blue (MB) in the presence of hydrogen peroxide. MB adsorption experiments showed that the capacity on (001) is about three times larger than on (012), and this is supported by density functional theory calculations suggesting adsorption energies about 1.5 times higher. However, this alone cannot explain the observed MB photodegradation rate, which is around 14.5 times faster on (001) than (012). The enhancement we attribute to a higher availability of photoelectron accepting surface Fe3+ sites on the (001) facet. This facilitates more efficient iron valence cycling and the heterogeneous photo-Fenton reaction yielding MB-oxidizing hydroxyl radicals at the surface. Our findings help establish a rational basis for design and optimization of hematite nanostructures as photocatalysts for environmental remediation.

Zong, Meirong↗

Tip Functionalization of Finite Single-Walled Carbon Nanotubes and Its Impact on the Ground and Excited State Electronic Structure

We explore the effect of capping of finite (10,5) carbon nanotube (SWCNT) with various functional groups, including methylene, ether, ester, and carboxylic derivatives, having different electron withdrawing/donating properties. Using density functional theory (DFT) and time-dependent DFT (TDDFT), we found that the sp2-hybridization of the bonding atom of the capping groups and the number of such groups plays the predominant role in eliminating optically inactive edge-localized midgap states, while withdrawing/donating properties of the functional groups are less significant. Our calculations show that two sp 2 -groups, like methylene derivatives, combined with hydrogens are an optimal capping scheme for (10,5) SWCNT to provide the well-opened energy gap, since sp 2 -groups can be placed relatively far from each other to minimize the dipole moment at the edges, while preserving conjugation of the edge according to the tube chirality. Absorption spectra demonstrate negligible effects of electron donating/withdrawing groups on the lowest optical E11 band. In contrast, the change in the bond order of the capping groups significantly changes optical spectra, resulting in red-shifted and less intensive E 11 band when sp 3 -capping substitutes two sp 2 -groups. Our findings can be helpful in choosing the functional groups for tuning the optoelectronic properties of SWCNTs. In addition, a complete understanding of the role of tube’s capping allows for using smaller computational models making computations of a wide range of phenomena in SWNTs practical.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

237 Np Mössbauer Isomer Shifts: A Lesson About the Balance of Static and Dynamic Electron Correlation in Heavy Element Complexes

A large set of neptunium compounds with different oxidation states (III to VII) was assembled to study the Mössbauer isomer shift by wave function calculations and better understand covalency in f-elements complexes. The contact density approach was used to calculate the isomer shift using complete active space self-consistent field (CASSCF) multiconfiguration wave functions, as well as matrix product states [from Density Matrix Renormalization Group (DMRG) algorithms] for large active spaces. Dynamic correlation effects for the isomer shifts were treated via CASPT2 energy derivatives with respect to the nuclear radius. The CASSCF calculations appear to produce different orbital overlocalization errors for low and high Np oxidation states. For compounds with low Np oxidation numbers, the errors can be attributed to the overlocalization of the 5f orbitals. For the compounds with high Np oxidation numbers, the main errors arise from an overlocalization of ligand orbitals and concomitant to weak donation bonding. Attempts to mitigate the overlocalization errors with large active spaces using DMRG were only partially successful, showing that explicit treatment of dynamic correlation is necessary for accurate predictions of Mössbauer isomer shifts. The CASPT2 calculations perform very satisfactorily. For a subset of Np compounds, both static and dynamic correlation effects were substantial. Furthermore, a rational active space selection based on orbital entanglement diagrams proved beneficial for determining the optimal reference wave function.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pseudocapacitance and excellent cyclability of 2,5-dimethoxy-1,4-benzoquinone on graphene

Electrochemically active organic materials are emerging as low cost, naturally abundant and sustainable alternatives to their metal-based counterparts. However, their usage in energy storage systems is mainly hindered by their poor conductivity, which results in capacitance fade upon cycling. In this paper, we present a redox-active xerogel composed of 2,5-dimethoxy-1,4-benzoquinone (DMQ) decorated on reduced graphene oxide (rGO) sheets via a hydrothermal method as a high capacitance and long cycle life pseudocapacitive electrode. DMQ not only provided stable redox-active centers but also served as a spacer to avoid rGO sheets aggregation and led to a three-dimensional (3D) hierarchical electrode architecture. When a binder-free 50 μm thick rolled film was tested as a pseudocapacitive electrode, it exhibited an excellent capacitance of 650 F g -1 at 5 mV s -1 (780 F cm -3 ) in 1 M sulfuric acid, outperforming a large number of reported organic and inorganic electrodes. Most importantly, optimized electrodes showed an excellent capacitance retention of 99% after 25 000 cycles at 50 mV s -1 . Density functional theory (DFT) calculations are further used to understand the charge storage mechanism, the preferred orientation of the adsorbed molecules, charge density distribution and density of states. In conclusion, our combined experimental and theoretical findings demonstrate that the careful selection of the conductive substrate, electrode architecture and organic molecules plays a crucial role in achieving high capacitance and long cycling performance.

25 ENERGY STORAGE↗

Predicting the morphologies of γ' precipitates in cobalt-based superalloys

Cobalt-based alloys with γ/γ' microstructures have the potential to become the next generation of superalloys, but alloy compositions and processing steps must be optimized to improve coarsening, creep, and rafting behavior. While these behaviors are different than in nickel-based superalloys, alloy development can be accelerated by understanding the thermodynamic factors influencing microstructure evolution. In this work, we develop a phase field model informed by first-principles density functional theory and experimental data to predict the equilibrium shapes of Co-Al-W γ' precipitates. Three-dimensional simulations of single and multiple precipitates are performed to understand the effect of elastic and interfacial energy on coarsened and rafted microstructures; the elastic energy is dependent on the elastic stiffnesses, misfit strain, precipitate size, applied stress, and precipitate spatial distribution. We observe characteristic microstructures dependent on the type of applied stress that have the same γ' morphology and orientation seen in experiments, indicating that the elastic stresses arising from coherent γ/γ' interfaces are important for morphological evolution during creep. Here, the results also indicate that the narrow γ channels between γ' precipitates are energetically favored, and provide an explanation for the experimentally observed directional coarsening that occurs without any applied stress.

36 MATERIALS SCIENCE↗

Density Functionals for Hydrogen Storage: Defining the H2Bind275 Test Set with Ab Initio Benchmarks and Assessment of 55 Functionals

Efficient and high-capacity storage materials are indispensable for a hydrogen-based economy. In silico tools can accelerate the process of discovery of new adsorbent materials with optimal hydrogen adsorption enthalpies. Density functional theory is well-poised to become a very useful tool for enabling high-throughput screening of potential materials. In this work, we have identified density functional approximations that provide good performance for hydrogen binding applications following a two-pronged approach. First, we have compiled a data set (H2Bind275) that comprehensively represents the hydrogen binding problem capturing the chemical and mechanistic diversity in the binding sites encountered in hydrogen storage materials. We have also computed reference interaction energies for this data set using coupled-cluster theory. Second, we have assessed the performance of 55 density functional approximations for predicting H 2 interaction energies and have identified two hybrid density functionals (ωB97X-V and ωB97M-V), two double hybrid density functionals (DSD-PBEPBE-D3(BJ) and PBE0-DH), and one semilocal density functional (B97M-V) as the best performing ones. We have recommended the addition of empirical dispersion corrections to systematically underbinding density functionals such as revPBE, BLYP, and B3LYP for improvements in performance at negligible additional cost. We have also recommended the usage of the def2-TZVPP basis set as it represents a good compromise between accuracy and cost, limiting the finite basis set errors to less than 1 kJ/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of graphene thickness and grain boundaries on MoS 2 wrinkle nanostructures

Controlling wrinkle nanostructures of two-dimensional materials is critical for optimizing the material properties and device performance. Herein, we demonstrated the in situ synthesis of large-area MoS 2 wrinkles on graphene by chemical-vapor-deposition-assisted sulfurization, and investigated the influence of graphene thickness and grain structures on the feature dimensions of MoS 2 wrinkle nanostructures. The height, width, and overall surface roughness of the MoS 2 wrinkles diminish as the number of graphene layers increases, which was further verified by determining the binding energy of graphene layers by density functional theory calculations. Furthermore, the feature dimensions of MoS 2 wrinkle nanostructures were also influenced by graphene domain boundaries because of the difference in graphene nucleation density. This may be attributed to the influence of the mechanical properties of graphene substrates on the overall feature dimensions of MoS 2 wrinkles, which are directly correlated with the interfacial adhesion energy. We believe that our findings may contribute toward the controllable synthesis of MoS 2 wrinkle nanostructures and other two-dimensional materials used for high-performance devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accelerating defect predictions in semiconductors using graph neural networks

First-principles computations reliably predict the energetics of point defects in semiconductors but are constrained by the expense of using large supercells and advanced levels of theory. Machine learning models trained on computational data, especially ones that sufficiently encode defect coordination environments, can be used to accelerate defect predictions. Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of group IV, III–V, and II–VI zinc blende semiconductors, powered by crystal Graph-based Neural Networks (GNNs) trained on high-throughput density functional theory (DFT) data. Using an innovative approach of sampling partially optimized defect configurations from DFT calculations, we generate one of the largest computational defect datasets to date, containing many types of vacancies, self-interstitials, anti-site substitutions, impurity interstitials and substitutions, as well as some defect complexes. We applied three types of established GNN techniques, namely crystal graph convolutional neural network, materials graph network, and Atomistic Line Graph Neural Network (ALIGNN), to rigorously train models for predicting defect formation energy (DFE) in multiple charge states and chemical potential conditions. We find that ALIGNN yields the best DFE predictions with root mean square errors around 0.3 eV, which represents a prediction accuracy of 98% given the range of values within the dataset, improving significantly on the state-of-the-art. We further show that GNN-based defective structure optimization can take us close to DFT-optimized geometries at a fraction of the cost of full DFT. The current models are based on the semi-local generalized gradient approximation-Perdew–Burke–Ernzerhof (PBE) functional but are highly promising because of the correlation of computed energetics and defect levels with higher levels of theory and experimental data, the accuracy and necessity of discovering novel metastable and low energy defect structures at the PBE level of theory before advanced methods could be applied, and the ability to train multi-fidelity models in the future with new data from non-local functionals. The DFT-GNN models enable prediction and screening across thousands of hypothetical defects based on both unoptimized and partially optimized defective structures, helping identify electronically active defects in technologically important semiconductors.

Rahman, Md Habibur (ORCID:000000027705984X)↗

Ab initio investigation on hydrogen adsorption capability in Zn and Cu-based metal organic frameworks

One of the biggest challenge in material technology for hydrogen storage application is to increase hydrogen uptake in room temperature and pressure. As a class of highly porous material, Metal-Organic Frameworks (MOF) holds great potential with its tunable structure. However, little is known about the effect of metal cluster to its hydrogen storage capability. Investigation on this matter has been carried out carefully on small cluster of Zn and Cu-based MOF using first principles method. The calculation of two distinct building units of MOFs, namely octahedral and paddle-wheel models, have been done with B3LYP density functional method using 6-31G(d,p) and LANL2DZ basis sets. From geometry optimization of Zn-based MOF linked by benzene-dicarboxylate (MOF-5), it is found that hydrogen tends to keep distance from metal cluster group and stays above benzene ring. In the other hand, hydrogen molecule prefers to stay atop of the exposed Cu atom in Cu-based MOF system linked by the same linker group (Cu-bdc). Calculated hydrogen binding enthalpies for Zn and Cu octahedral cages at ZnO{sub 3} sites are 1.64kJ/mol and 2.73kJ/mol respectively, while hydrogen binding enthalpies for Zn and Cu paddle-wheel cages calculated on top of metal atoms are found to be at 6.05kJ/mol and 6.10kJ/mol respectively. Major difference between Zn-MOF-5 and Cu-bdc hydrogen uptake performance might be caused by unsaturated metal sites present in Cu-bdc system and the influence of their geometric structures, although a small difference on binding energy in the type of transition metal used is also observed. The comparison between Zn and Cu-based MOF may contribute to a comprehensive understanding of metal clusters and the importance of selecting best transition metal for design and synthesis of metal-organic frameworks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Size and structure effects of Pt{sub N} (N = 12 − 13) clusters for the oxygen reduction reaction: First-principles calculations

Size and structure effects on the oxygen reduction reaction on Pt{sub N} clusters with N = 12–13 atoms have been investigated using periodic density functional theory calculations with the generalized gradient approximation. To describe the catalytic activity, we calculated the O and OH adsorption energies on the cluster surface. The oxygen binding on the 3-fold hollow sites on stable Pt{sub 12−13} cluster models resulted more favorable for the reaction with O, compared with the Pt{sub 13}(I{sub h}) and Pt{sub 55}(I{sub h}) icosahedral particles, in which O binds strongly. However, the rate-limiting step resulted in the removal of the OH species due to strong adsorptions on the vertex sites, reducing the utility of the catalyst surface. On the other hand, the active sites of Pt{sub 12−13} clusters have been localized on the edge sites. In particular, the OH adsorption on a bilayer Pt{sub 12} cluster is the closest to the optimal target; with 0.0-0.2 eV weaker than the Pt(111) surface. However, more progress is necessary to activate the vertex sites of the clusters. The d-band center of Pt{sub N} clusters shows that the structural dependence plays a decisive factor in the cluster reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystal orbital study on the double walls made of nanotubes encapsulated inside zigzag carbon nanotubes

The structure stabilities and electronic properties are investigated by using ab initio self-consistent-field crystal orbital method based on density functional theory for the one-dimensional (1D) double-wall nanotubes made of n-gon SiO{sub 2} nanotubes encapsulated inside zigzag carbon nanotubes. It is found that formation of the combined systems is energetically favorable when the distance between the two constituents is around the Van der Waals scope. The obtained band structures show that all the combined systems are semiconductors with nonzero energy gaps. The frontier energy bands (the highest occupied band and the lowest unoccupied band) of double-wall nanotubes are mainly derived from the corresponding carbon nanotubes. The mobilities of charge carriers are calculated to be within the range of 10{sup 2}–10{sup 4} cm{sup 2} V{sup −1} s{sup −1} for the hybrid double-wall nanotubes. Young’s moduli are also calculated for the combined systems. For the comparison, geometrical and electronic properties of n-gon SiO{sub 2} nanotubes are also calculated and discussed. - Graphical abstract: Structures and band structures of the optimum 1D Double walls nanotubes. The optimized structures are 3-gon SiO2@(15,0), 5-gon SiO2@(17,0), 6-gon SiO2@(18,0) and 7-gon SiO2@(19,0). - Highlights: • The structure and electronic properties of the 1D n-gon SiO{sub 2}@(m,0)s are studied using SCF-CO method. • The encapsulation of 1D n-gon SiO{sub 2} tubes inside zigzag carbon nanotubes can be energetically favorable. • The 1D n-gon SiO{sub 2}@(m,0)s are all semiconductors. • The mobility of charge carriers and Young’s moduli are calculated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Towards defect engineering in hexagonal MoS 2 nanosheets for tuning hydrogen evolution and nitrogen reduction reactions

Combined computational and experimental approaches were used to evaluate defective 2H-MoS 2 nanosheets for their activity and selectivity for hydrogen evolution reaction (HER) and nitrogen reduction reaction (NRR). Density functional theory calculations were used to understand the relationship between HER and NRR activity on the ideal basal MoS 2 plane, seven grain-boundaries, ten single-/few-atom vacancies and anti-sites, and zigzag and armchair edge sites. The results confirm that 2H-MoS 2 should contain several defects with high activity for HER: armchair and zigzag edges, VS vacancy, MoS 2 anti-site, and S-S and Mo-Mo grain boundaries. Considering Gibbs free energy change for all the steps in the NRR mechanism and kinetic barriers for a key NRR step, we have found that activation of perspective NRR selective sites in 2H-MoS 2 , namely V MoS6 and clusters of S-vacancies, would require large overpotential, conditions at which HER dominates. The DFT conclusions are supported by the electrochemical studies of NRR activity and selectivity under aqueous conditions, which show an increase in NRR activity but a decrease in Faradaic efficiency as applied cell potential becomes more negative. The results of this work therefore highlight the challenges in activating natural 2H-MoS 2 for NRR, which would require additional material engineering or reaction condition optimization as a way to suppress HER, decrease the NRR overpotential or preferentially both.

2H-MoS2↗

Actinide Molten Salts: A Machine-Learning Potential Molecular Dynamics Study

We know that actinide molten salts represent a class of important materials in nuclear energy. Understanding them at a molecular level is critical to proper and optimal design of relevant technological applications. Yet, owing to the complexity of electronic structure due to the 5f orbitals, computational studies of heavy elements in condensed phases using ab initio potentials to study the structure and dynamics of these elements embedded in molten salts are difficult. This lack of efficient computational protocols makes it difficult to obtain information on properties that require extensive statistical sampling like transport. To tackle this problem, we adopted a machine-learning approach to study ThCl 4 -NaCl and UCl 3 -NaCl binary systems. The machine-learning potential, with the density functional theory accuracy, allows us to obtain long molecular dynamics trajectories (ns) for large systems (10 3 atoms) at a considerably low computing cost, thereby efficiently gaining information about their bonding structures, thermodynamics, and dynamics at a range of temperature. We observed a considerable change in the coordination environments of actinide elements and their characteristic coordination-sphere lifetime. Our study also suggests that actinides in molten salts may not follow well known entropy-scaling laws.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗