Combined Ab Initio Molecular Dynamics Research Articles

The basic intermediate-range order structures in the FLiNaK–LaF3–Li2O melt: identification and characterisation

ABSTRACT In this paper, we investigate the structure of FLiNaK–LaF3 melt with small addition of Li2O through the theoretical approach combining ab initio molecular dynamics and simulation of the isolated structural units. The structure of the melt was studied in detail by calculation of radial distribution functions along with coordination numbers and radii. We found that oxyfluoride intermediate-range structure is formed in the melt. Our observations support the suggestions of other authors on formation of intermediate-range structures in fluoride melts containing metal oxides. Given structure shows long lifetime, the consideration of the isolated specie is valuable. We performed a simulation of ‘gas-phase’ [O2La4Fn] structure in order to calculate its Raman spectrum. It was found that the spectrum of the isolated structure agree in semi-quantitative manner with the vibrational density of states of the oxygen ions in the melt.

The relevance of structural variability in the time-domain for computational reflection anisotropy spectroscopy at solid–liquid interfaces

In electrochemistry, reactions and charge-transfer are to a large extent determined by the atomistic structure of the solid–liquid interface. Yet due to the presence of the liquid electrolyte, many surface-science methods cannot be applied here. Hence, the exact microscopic structure that is present under operating conditions often remains unknown. Reflection anisotropy spectroscopy (RAS) is one of the few techniques that allow for an in operando investigation of the structure of solid–liquid interfaces. However, an interpretation of RAS data on the atomistic scale can only be obtained by comparison to computational spectroscopy. While the number of computational RAS studies related to electrochemical systems is currently still limited, those studies so far have not taken into account the dynamic nature of the solid–liquid interface. In this work, we investigate the temporal evolution of the spectroscopic response of the Au(110) missing row reconstruction in contact with water by combining ab initio molecular dynamics with computational spectroscopy. Our results show significant changes in the time evolution of the RA spectra, in particular providing an explanation for the typically observed differences in intensity when comparing theory and experiment. Moreover, these findings point to the importance of structural surface/interface variability while at the same time emphasising the potential of RAS for probing these dynamic interfaces.

Impact of Pt(hkl) Electrode Surface Structure on the Electrical Double Layer Capacitance.

The classical theory of the electrical double layer (EDL) does not consider the effects of the electrode surface structure on the EDL properties. Moreover, the best agreement between the traditional EDL theory and experiments has been achieved so far only for a very limited number of ideal systems, such as liquid metal mercury electrodes, for which it is challenging to operate with specific surface structures. In the case of solid electrodes, the predictive power of classical theory is often not acceptable for electrochemical energy applications, e.g., in supercapacitors, due to the effects of surface structure, electrode composition, and complex electrolyte contributions. In this work, we combine ab initio molecular dynamics (AIMD) simulations and electrochemical experiments to elucidate the relationship between the structure of Pt(hkl) surfaces and the double-layer capacitance as a key property of the EDL. Flat, stepped, and kinked Pt single crystal facets in contact with acidic HClO4 media are selected as our model systems. We demonstrate that introducing specific defects, such as steps, can substantially reduce the EDL capacitances close to the potential of zero charge (PZC). Our AIMD simulations reveal that different Pt facets are characterized by different net orientations of the water dipole moment at the interface. That allows us to rationalize the experimentally measured (inverse) volcano-shaped capacitance as a function of the surface step density.

Interfacial structures and dissociation reactions of protic ionic liquids on Li metal surface: A combined first-principles and ab initio molecular dynamics investigation

Interfacial structures and dissociation reactions of protic ionic liquids (PILs) comprising five protic cations with two common sulfonylimide anions on the Li(001) surface were investigated using first-principles calculations and ab initio molecular dynamics simulations. Both the anions rapidly decompose, yielding LiF, Li2O and Li2S species as well as large fragments, e.g. NSO2CF3 and NSO2. Particularly, the proton attached to the N atom generally segregates from the cations and generates LiOH with the O atom from the anions and the surface Li atom. In addition, detailed comparisons of reaction mechanisms between PIL-based and AIL-based systems were also made.

Structural evolutions under surface oxidation of AgPd Alloy: From Orientation, composition and strain effects to catalytic application

The surface oxidation of AgPd alloys can significantly impact their catalytic activity, however, the detailed understanding of such dynamic mechanism and the prediction of catalytic activity is still lacking. Herein, a comprehensive investigation combining ab initio molecular dynamics simulations with experimental observations is performed. The surface oxidation of AgPd alloys is highly dependent on oxygen concentration, where AgOx forms in oxygen-poor environment and PdOx forms in oxygen-rich environment, and shows highly reliance on the orientation, composition and strain state. The oxidation level of Ag, Pd and AgPd alloys follows the trend of (111) < (100) < (110) under 1.0 ML of O coverage. Both Pd single-atom and Ag matrix atoms in PdAg single-atom alloys are susceptible to oxidation under 0.5 ML of O coverage, with the increase of Pd atom number, only AgOx forms. Tensile strain promotes the oxidation of Ag(111) surface by facilitating the inward diffusion of O atoms, while compressive strain promotes the oxidation of Pd(111) and AgPd(111) surfaces by facilitating the outward migration of Ag/Pd atoms. The oxidized AgPd(111) surface with tensile strain under 0.5 ML of O coverage exhibits the optimum electrocatalytic activity toward formate oxidation reaction.

Insights into the Anode‐Initiated and Grain Boundary‐Initiated Mechanisms for Dendrite Formation in All‐Solid‐State Lithium Metal Batteries

AbstractThe formation of lithium dendrites severely hinders the practical application of all‐solid‐state lithium metal batteries (ASSLMBs). The conventional view is that dendrites initiate at the anode and then grow into solid electrolytes (SEs), while a recent popular opinion holds that Li+ ions can directly be reduced at grain boundaries (GBs) within electrolytes, and these internal dendrites then interconnect resulting in the short‐circuit failure. However, whether the internal GBs or the anode interface dominates the dendrite initiation is still under debate. Herein, first‐principles calculations on the representative system, Li6PS5Cl (LPSC), are performed to investigate these two dendrite initiation mechanisms. The results show that the solid electrolyte interphase (SEI) blocks the electron leakage, making the internal Li+ ions less likely to deposit. Combining ab initio molecular dynamics (AIMD) simulations with theoretical models, the critical current density (CCD) for dendrite formation at the anode interface is predicted to be much lower than at the GBs, indicating dendrites are easier to initiate at the anode. This study reveals that the dendrite formation is governed by the anode‐initiated mechanism instead of the GB‐initiated one. These findings suggest that the anode interface should be a primary concern for designing dendrite‐free batteries rather than the GBs.

Intrinsic vs Reaction-Driven Fluxionality in Transition-Metal Oxide Clusters: What Does Probing the Dynamics of M3O6– (M = Mo and W) Reacting with H2O Teach Us?

Fluxionality is an important concept in cluster science, with far reaching implications in the area of catalysis. The interplay between intrinsic structural fluxionality and reaction-driven fluxionality though is underexplored in the literature and is a topic of contemporary interest in physical chemistry. In this work, we present an easy-to-use computational protocol combining ab initio molecular dynamics simulations with static electronic structure computations to ascertain the role of intrinsic structural fluxionality in the course of fluxionality occurring due to a chemical reaction. The reactions of structurally well-defined M3O6- (M = Mo and W) with water─which were originally used in the literature to illustrate the significance of reaction-driven fluxionality in transition-metal oxide (TMO) clusters, were chosen for this study. Besides probing the nature of fluxionality, this work provides the timescale for the key proton-hop step in the fluxionality pathway and further attests to the significance of hydrogen bonding in both stabilizing the key intermediates as well as driving forward the reactions of M3O6- (M = Mo and W) with water. The approach presented in this work becomes valuable given that the use of molecular dynamics alone may not help us in accessing some metastable states whose formation involves an appreciable energy barrier. Similarly, merely obtaining a slice of the potential energy surface via static electronic structure calculations will not be helpful in probing the different types of fluxionality. Hence, there is the need for a combined approach to study fluxionality in structurally well-defined TMO clusters. Our protocol may also serve as a starting point in the analysis of much more complicated fluxional chemistry happening on surfaces wherein the recently developed "ensemble of metastable states" approach to catalysis is deemed to be particularly promising.

Dynamic catalysis of sub-nanometer metal clusters in oxygen dissociation

When the catalyst size decreases down to the nanometer or even sub-nanometer scale, their geometric and electronic structures are very different from the bulk materials. Especially, their structural dynamics can greatly affect catalytic performances. Herein, we report a theoretical study on oxygen dissociation on Ag19 cluster, a critical step of ethylene epoxidation, to investigate the effect of structural dynamics on the catalytic activity. Combining ab initio molecular dynamics (AIMD) and free energy calculation, we obtain the free energy profiles under different temperatures and find sudden drops in the reaction free energy and barrier at certain temperature ranges. The reaction entropy change shows a positive peak because of the different melting temperatures between initial and final states. Additionally, we further investigate the oxygen diffusion process on the Ag cluster and compare it with the Au and Cu clusters. We find that weak adsorption of oxygen on the silver cluster leads to its facile diffusion and thus reduces the melting temperature of the cluster, therefore facilitating partial oxidation under mild conditions.

Dynamic cooperativity of chromophores in promoting singlet fission in perylenediimide crystals

Cooperativity of proximate monomers in promoting SF under the influence of structure dynamics in perylenediimide crystals is explored using combined ab initio molecular dynamics simulations and time-dependent density functional theory calculations.

An investigation into the adsorption mechanism of n-butanol by ZIF-8: a combined experimental and ab initio molecular dynamics approach.

The zeolitic imidazolate framework, ZIF-8, has been shown by experimental methods to have a maximum saturation adsorption capacity of 0.36 g g-1 for n-butanol from aqueous solution, equivalent to a loading of 14 butanol molecules per unit cell or 7 molecules per sodalite β-cage. Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) shows the presence of hydrogen bonding between adsorbed butanol molecules within the cage; the presence of three different O-H stretching modes indicates the formation of butanol clusters of varying size. Ab initio molecular dynamics simulations show the formation of intermolecular hydrogen bonding between the butanol molecules, with an average hydrogen-bond coordination number of 0.9 after 15 ps simulation time. The simulations also uniquely demonstrate the presence of weaker interactions between the alcohol O-H group and the π-orbital of the imidazole ring on the internal surface of the cage during early stages of adsorption. The calculated adsorption energy per butanol molecule is -33.7 kJ mol-1, confirming that the butanol is only weakly bound, driven primarily by the hydrogen bonding. Solid-state MAS NMR spectra suggest that the adsorbed butanol molecules possess a reasonable degree of mobility in their adsorbed state, rather than being rigidly held in specific sites. 2D 13C-1H heteronuclear correlation (HETCOR) experiments show interactions between the butanol aliphatic chain and the ZIF-8 framework experimentally, suggesting that O-H interactions with the π-orbital are only short lived. The insight gained from these results will allow the design of more efficient ways of recovering and isolating n-butanol, an important biofuel, from low-concentration solutions.

Multiscale simulation of surface-assisted synthesis of 7-armchair graphene nanoribbons

The on-surface synthesis method is a remarkably promising technology in producing nanometer-wide graphene nanoribbons (GNRs) whose edge structures are well preserved. Controlling the quality of GNRs in terms of length is important for various GNR-based applications. We studied the surface-assisted synthesis of 7-armchair graphene nanoribbons (7-AGNRs) using a multiscale simulation method combining ab initio molecular dynamics simulations (AIMD) and kinetic Monte Carlo (KMC) simulations. The effect of monomer coverage and substrate type on the polymerization process are investigated. The length of the synthesized polyanthracene/GNRs on both Au(111) and Ag(111) substrates is shown to be significantly influenced by the deposited monomer amount. Ag(111) is better than Au(111) in facilitating the formation of longer polyanthracene/GNRs. An empirical mathematical model for predicting the percentage of long GNRs in the growth process is developed based on reaction parameters such as monomer coverage, the bonding and diffusion activation energies of DBBA radicals on the substrate, and temperature. This work provides a robust means for predicting and controlling the synthesis of 7-AGNRs on various substrates and presents a general multiscale framework for the synthesis of various GNRs.

Unveiling the electronic structures and optical properties of alkaline‐earth oxides–modified silicate glasses

AbstractThe electronic structure, interatomic bonding, and optical properties of mixed alkaline‐earth metal oxides MO (M = Mg, Ca) on amorphous silica glasses were calculated by combined ab initio molecular dynamics and the orthogonalized linear combination of atomic orbitals approaches. With the addition of alkaline‐earth metal oxides, the original structural network model is destroyed, nonbridging oxygen is generated, and the covalent bonding is reduced, which reduces the total bond order density for silicate glass. The complex dielectric function plot shows that there are three distinct peaks in the imaginary part of the original silica glasses, and the last two peaks level off with the modification of alkaline earth oxides.

Graphene, phosphorene and silicene coatings on the (0001) surfaces of hcp metals: Structural stability and hydrophobicity

Single atomic layer or monolayer (ML) 2D materials have unique features that can be relevant for protection and functionalization of high-performance surfaces. Here we report a combined density functional theory and ab initio molecular dynamics study on the stability of graphene (Gr), phosphorene (Pp) and silicene (Sl) coatings at the most stable (0001) surface of the metals that have hcp structure at room temperature: Hf, Mg, Os, Re, Ru, Sc, Ti, Zn and Zr. We found that the three 2D materials are stable at the surfaces of many of these metals: Gr is stable at Os, Re, Ti, Zn and Zr; Pp is stable in the blue form at Hf, Mg, Ti and Zr; Sl is stable in the 2D zigzag structure at Hf, Mg and Ti and in the planar form at the Zr surface. For the remaining metals Gr, Pp and Sl do not form van der Waals bonded MLs. In those cases we found structures such as 2D arrangements of mixed hexagons and pentagons, trigonal pyramidal structures and 2 half-monolayers. Many of these structures are very stable coatings covalently bound to the surfaces with considerable adsorption energies that can reach − 2 eV per atom of the coating. Gr imparts hydrophobicity to the surfaces of all materials here studied and increases the distance between these and the first H2O layer by as much as 75 % for Gr coated Ti. These H2O layers have increased rigidity despite being located further apart from the surfaces. These effects could be explored for the protection or functionalization of high-performance systems such as metallic electrodes for example.

Actinides in complex reactive media: A combined ab initio molecular dynamics and machine learning analytics study of transuranic ions in molten salts

The predominant ionic chemistry and the similarity in ionic radius of actinides make it very difficult to structurally distinguish them in liquids. To tackle this problem, we investigate actinides in molten salts using ab initio molecular dynamics and machine learning analytics. Ab initio simulations show that the f-states clearly affects the electronic properties while their impact on structural properties is not obvious. For the series of trivalent actinides U3+, Pu3+, Cm3+, Cf3+, and Fm3+ in molten NaCl and FLiBe, actinide-ligand bonds have a higher degree of covalency in NaCl (than in FLiBe), and a higher degree of ionicity in FLiBe. Furthermore, a machine learned classification model can distinguish atomic environments of chemically similar actinides with more than 80% confidence, as long as atoms beyond the first solvation shells are considered. Our work shows that only two types of descriptors are necessary to account for all the fluctuations in heavy metal/molten salt mixtures: The first descriptor represents the electronic state of the heavy metal, while the second encompasses the local coordination environment.

Atomistic Scale Analysis of Motion and Dynamics of Li-Ion in Li-Zn-Zr-S Compound Electrolyte

Solid-state electrolytes are considered as key materials for overcoming the limitations of the liquid-electrolyte-based Li-ion batteries in terms of energy capacity, cyclability, and safety. Among the many possible solid-state electrolyte materials, inorganic sulfides are of intensive research interest mainly because the larger and more polarizable sulfur anions substantially enhance the mobility of cationic Li species. In particular, Li-P-S electrolytes, such as Li10GeP2S12and Li7P3S11, have been reported to have room-temperature Li-ion conductivity of greater than 10-2 S/cm, which is comparable to that of conventional liquid electrolytes. Despite the facile Li-ion transport, the Li-P-S electrolytes tend to undergo irreversible structural degradation within typical operating conditions of the battery. This lack of electrochemical stability leads to the formation of high impedance intermediate transition layers at the electrode/electrolyte interfaces, hindering the practical application of the Li-P-S electrolytes. Partial replacement of the element P with other elements within a Li-P-S structural family can improve the lithium-ion conductivity, but notable improvement in their electrochemical stability has yet to be achieved. Li-M-S (M = transition metals, such as Cr, Zr, Nb, Mo, and Sn) families can be possible candidates for electrochemically stabile solid-state electrolytes, while having excellent Li-ion transport properties of the inorganic sulfides. Like the Li-P-S structure, numerous Li-M-S structural derivatives have already been synthesized by varying the element M or by replacing a portion of the element M with another element, and the Li-ion conductivity and electrochemical stability are expected to be heavily dependent on the element composition and crystalline structure.In this study, we investigate the motion and dynamics of Li-ions in Li-Zr-S and Li-Zn-Zr-S compound electrolyte by performing a series of first-principles calculations. To this end, we generate multiple Li-Zn-Zr-S compound model structures with varying Zr-to-Zn ratios. Then, we evaluate Li-ion conductivities by using velocity auto correlation scheme combined ab initio molecular dynamics (AIMD) simulations. More specifically, we calculate the diffusivity and ionic conductivity of the stoichiometric structure and at a range of defect concentrations on Li2+2xZnxZr1-xS3, from x = 0 to x = 0.5. Our calculation results reveal how the introduction of Zn into the Li-Zr-S compound affects the Li-ion mobilities. The theoretical insight obtained in this study well corroborates with recently reported experimental results for varying ionic conductivities in Li-Zn-Zr-S electrolytes depending on the Zr-to-Zn ratio. This fundamental understanding can be an important theoretical basis for developing practically applicable Li-M-S electrolytes. Figure 1

Bidimensional Engineered Amorphous a-SnO2 Interfaces: Synthesis and Gas Sensing Response to H2S and Humidity.

Two-dimensional (2D) transition metal dichalcogenides (TMDs) and metal chalcogenides (MCs), despite their excellent gas sensing properties, are subjected to spontaneous oxidation in ambient air, negatively affecting the sensor’s signal reproducibility in the long run. Taking advantage of spontaneous oxidation, we synthesized fully amorphous a-SnO2 2D flakes (≈30 nm thick) by annealing in air 2D SnSe2 for two weeks at temperatures below the crystallization temperature of SnO2 (T < 280 °C). These engineered a-SnO2 interfaces, preserving all the precursor’s 2D surface-to-volume features, are stable in dry/wet air up to 250 °C, with excellent baseline and sensor’s signal reproducibility to H2S (400 ppb to 1.5 ppm) and humidity (10–80% relative humidity (RH)) at 100 °C for one year. Specifically, by combined density functional theory and ab initio molecular dynamics, we demonstrated that H2S and H2O compete by dissociative chemisorption over the same a-SnO2 adsorption sites, disclosing the humidity cross-response to H2S sensing. Tests confirmed that humidity decreases the baseline resistance, hampers the H2S sensor’s signal (i.e., relative response (RR) = Ra/Rg), and increases the limit of detection (LOD). At 1 ppm, the H2S sensor’s signal decreases from an RR of 2.4 ± 0.1 at 0% RH to 1.9 ± 0.1 at 80% RH, while the LOD increases from 210 to 380 ppb. Utilizing a suitable thermal treatment, here, we report an amorphization procedure that can be easily extended to a large variety of TMDs and MCs, opening extraordinary applications for 2D layered amorphous metal oxide gas sensors.

Machine learning approach for longitudinal spin fluctuation effects in bcc Fe atTcand under Earth-core conditions

We propose a machine learning approach to predict the shapes of the longitudinal spin fluctuation (LSF) energy landscapes for each local magnetic moment. This approach allows the inclusion of the effects of LSFs in, e.g., the simulation of a magnetic material with ab initio molecular dynamics in an effective way. This type of simulation requires knowledge of the reciprocal interaction between atoms and moments, which, in principle, would entail calculating the energy landscape of each atom at every instant in time. The machine learning approach is based on the kernel ridge regression method and developed using bcc Fe at the Curie temperature and ambient pressure as a test case. We apply the trained machine learning models in a combined atomistic spin dynamics and ab initio molecular dynamics (ASD-AIMD) simulation, where they are used to determine the sizes of the magnetic moments of every atom at each time step. In addition to running an ASD-AIMD simulation with the LSF machine learning approach for bcc Fe at the Curie temperature, we also simulate Fe at temperature and pressure comparable to the conditions at the Earth's inner solid core. The latter simulation serves as a critical test of the generality of the method and demonstrates the importance of the magnetic effects in Fe in the Earth's core despite its extreme temperature and pressure.

The Phonon Quasiparticle Approach for Anharmonic Properties of Solids

Knowledge of lattice anharmonicity is essential to elucidate distinctive thermal properties in crystalline solids. Yet, accurate ab initio investigations of lattice anharmonicity encounter difficulties owing to the cumbersome computations. Here we introduce the phonon quasiparticle approach and review its application to various materials. This method efficiently and reliably addresses lattice anharmonicity by combining ab initio molecular dynamics and lattice dynamics calculations. Thus, in principle, it accounts for full anharmonic effects and overcomes finite-size effects typical of ab initio molecular dynamics. The validity and effectiveness of the current approach are demonstrated in the computation of thermodynamic and heat transport properties of weakly and strongly anharmonic systems.

On the anomalous diffusion of proton in Y-doped BaZrO3 perovskite oxide

Proton transport in perovskite oxides (ABO3) is a complex dynamical process involving hydroxide ion rotation and proton transfer. Combining ab initio molecular dynamics (AIMD) and machine-learning molecular dynamics (MLMD) simulations of proton dynamics in Y-doped BaZrO3 perovskite oxide, we systematically illustrate the anomalous characteristics of proton motion. At short times, proton performs superdiffusion through the OH wag and proton transfer. At intermediate times, the larger rotation angle results in the larger plateau value. At longer times, proton diffusion first becomes subdiffusive due to the hydroxide ion rotations then gradually turns to normal diffusion. A theoretical model is also offered to quantitatively describe this abnormal proton diffusion. In all, this work provides a more complete understanding of proton dynamics in perovskite oxides.

Deep neural network based quantum simulations and quasichemical theory for accurate modeling of molten salt thermodynamics.

With dual goals of efficient and accurate modeling of solvation thermodynamics in molten salt liquids, we employ ab initio molecular dynamics (AIMD) simulations, deep neural network interatomic potentials (NNIP), and quasichemical theory (QCT) to calculate the excess chemical potentials for the solute ions Na+ and Cl− in the molten NaCl liquid. NNIP-based molecular dynamics simulations accelerate the calculations by 3 orders of magnitude and reduce the uncertainty to 1 kcal mol−1. Using the Density Functional Theory (DFT) level of theory, the predicted excess chemical potential for the solute ion pair is −178.5 ± 1.1 kcal mol−1. A quantum correction of 13.7 ± 1.9 kcal mol−1 is estimated via higher-level quantum chemistry calculations, leading to a final predicted ion pair excess chemical potential of −164.8 ± 2.2 kcal mol−1. The result is in good agreement with a value of −163.5 kcal mol−1 obtained from thermo-chemical tables. This study validates the application of QCT and NNIP simulations to the molten salt liquids, allowing for significant insights into the solvation thermodynamics crucial for numerous molten salt applications.