Unveiling the dynamic interface evolution co-induced by cations and vacancies for boosted in situ hydrogen peroxide electrosynthesis.

The shock Hugoniot for full-density and porous ${\mathrm{CeO}}_{2}$ was investigated in the liquid regime using ab initio molecular dynamics (AIMD) simulations with Erpenbeck's approach based on the Rankine-Hugoniot jump conditions. The phase space was sampled by carrying out NVT simulations for isotherms between 6000 and 100 000 K and densities ranging from $\ensuremath{\rho}=2.5$ to $20\phantom{\rule{0.28em}{0ex}}\mathrm{g}/{\mathrm{cm}}^{3}$. The impact of on-site Coulomb interaction corrections $+U$ on the equation of state (EOS) obtained from AIMD simulations was assessed by direct comparison with results from standard density functional theory simulations. Classical molecular dynamics (CMD) simulations were also performed to model atomic-scale shock compression of larger porous ${\mathrm{CeO}}_{2}$ models. Results from AIMD and CMD compression simulations compare favorably with Z-machine shock data to 525 GPa and gas-gun data to 109 GPa for porous ${\mathrm{CeO}}_{2}$ samples. Using results from AIMD simulations, an accurate liquid-regime Mie-Gr\"uneisen EOS was built for ${\mathrm{CeO}}_{2}$. In addition, a revised multiphase SESAME-type EOS was constrained using AIMD results and experimental data generated in this work. This study demonstrates the necessity of acquiring data in the porous regime to increase the reliability of existing analytical EOS models.

Recent advances in synthesis and characterization methods have enabled the controllable fabrication of atomically precise metal clusters (AMCs) of subnanometer size that possess unique physical and chemical properties, yet to be explored. Such AMCs have potential applications in a wide range of fields, from luminescence and sensing to photocatalysis and bioimaging, making them highly desirable for further research. Therefore, there is a need to develop innovative methods to stabilize AMCs upon surface deposition, as their special properties are lost due to sintering into larger nanoparticles. To this end, dispersion-corrected density functional theory (DFT-D3) and ab initio molecular dynamics (AIMD) simulations have been employed. Benchmarking against high-level post-Hartree-Fock approaches revealed that the DFT-D3 scheme describes very well the lowest-energy states of clusters of five and ten atoms, Cu5 and Cu10. AIMD simulations performed at 400 K illustrate how intrinsic defects of graphene sheets, carbon vacancies, are capable of confining individual Cu5 clusters, thus allowing for their stabilization. Furthermore, AIMD simulations provide evidence on the dimerization of Cu5 clusters on defect-free graphene, in agreement with the ab initio predictions of (Cu5)n aggregation in the gas phase. The findings of this study demonstrate the potential of using graphene-based substrates as an effective platform for the stabilization of monodisperse atomically precise Cu5 clusters.

Internal standard-assisted ab initio MD simulation for comparative thermal stability and decomposition mechanisms of energetic materials

Property structure relationships in materials can be studied by a number of computational approaches such as ab initio quantum chemistry calculations, ab initio molecular dynamics (MD) simulations, classical MD and Monte-Carlo simulations, finite element modelling, etc. A choice of the computational method depends on the time and length scales and computational resources available. At the current stage of method and hardware development, ab initio quantum chemistry calculations are best suited for studying energy-structure relationships in relatively small systems consisting of tens of atoms. Ab initio MD simulations allow one to study dynamics of systems on a picosecond time scale for systems consisting of hundreds of atoms. Energy and forces in ab initio MD simulations are obtained from solving the electronic structure problem “on the fly”. Parameterization of the energy a system as a function of the relative atom positions, e. g., development of a classical force field, significantly speeds up calculations of the energies and forces in MD simulations, positioning classical MD simulations as the most suitable tool to obtain properties of the systems containing 10-10 atoms on the time scales from 10 to 10 s. However, the value of the property predictions using classical MD simulations is limited to the accuracy of the force field used, making a consistent derivation of a high quality classical force fields central to accurate prediction of the property-structure relationship from MD simulations.

Distribution of the mechanical properties of Ti–Cu combinatorial thin film evaluated using nanoindentation experiments and molecular dynamics with a neural network potential

In the paper, the ORR/OER on graphene-supported nitrogen coordinated Ru-atom (Ru-N-C) is simulated. We discuss nitrogen coordination influences electronic properties, adsorption energies, and catalytic activity in a single-atom Ru active site. The over potentials on Ru-N-C are 1.12 eV/1.00 eV for ORR/OER. We calculate Gibbs-free energy (ΔG) for every reaction step in ORR/OER process. In order to gain a deeper understanding of the catalytic process on the surface of single atom catalysts, the ab initio molecular dynamics (AIMD) simulations show that Ru-N-C has a structural stability at 300 K and that ORR/OER on Ru-N-C can occur along a typical four-electron process of reaction. AIMD simulations of catalytic processes provide detailed information about atom interactions. In this paper, we use density functional theory (DFT) with PBE functional to study the electronic properties and adsorption properties of graphene-supported nitrogen coordinated Ru-atom (Ru-N-C) Gibbs-free energy and Gibbs-free energy for very reaction step. The structural optimization and all the calculations are carried out by Dmol3 package, adopting the PNT basis set and DFT semicore pseudopotential. Ab initio molecular dynamics simulations (AIMD) were run for 10 ps. The canonical (NVT) ensemble, massive GGM thermostat, and a temperature of 300 K are taken into account. The functional of B3LYP and the DNP basis set are chosen for AIMD.

Ab initio and classical molecular dynamics studies of electrode reactions

We examine the effect of equilibration methodology and sampling on ab initio molecular dynamics (AIMD) simulations of systems of common solvents and salts found in lithium-oxygen batteries. We compare two equilibration methods: (1) using an AIMD temperature ramp and (2) using a classical MD simulation followed by a short AIMD simulation both at the target simulation temperature of 300 K. We also compare two different classical all-atom force fields: PCFF+ and OPLS. By comparing the simulated association/dissociation behavior of lithium salts in different solvents with the experimental behavior, we find that equilibration with the classical force field that produces more physically accurate behavior in the classical MD simulations, namely, OPLS, also results in more physically accurate behavior in the AIMD runs compared to equilibration with PCFF+ or with the AIMD temperature ramp. Equilibration with OPLS outperforms even the pure AIMD equilibration because the classical MD equilibration is much longer than the AIMD equilibration (nanosecond vs picosecond timescales). These longer classical simulations allow the systems to find a more physically accurate initial configuration, and in the short simulation times available for the AIMD production runs, the initial configuration has a large impact on the system behavior. We also demonstrate the importance of averaging coordination number over multiple starting configurations and Li+ ions, as the majority of Li+ ions do not undergo a single association or dissociation event even in an ∼40 ps long simulation and thus do not sample a statistically significant portion of the phase space. These results show the importance of both equilibration method and sufficient independent sampling for extracting experimentally relevant quantities from AIMD simulations.

Ab initio molecular dynamics (AIMD) simulation is widely employed in studying diffusion mechanisms and in quantifying diffusional properties of materials. However, AIMD simulations are often limited to a few hundred atoms and a short, sub-nanosecond physical timescale, which leads to models that include only a limited number of diffusion events. As a result, the diffusional properties obtained from AIMD simulations are often plagued by poor statistics. In this paper, we re-examine the process to estimate diffusivity and ionic conductivity from the AIMD simulations and establish the procedure to minimize the fitting errors. In addition, we propose methods for quantifying the statistical variance of the diffusivity and ionic conductivity from the number of diffusion events observed during the AIMD simulation. Since an adequate number of diffusion events must be sampled, AIMD simulations should be sufficiently long and can only be performed on materials with reasonably fast diffusion. We chart the ranges of materials and physical conditions that can be accessible by AIMD simulations in studying diffusional properties. Our work provides the foundation for quantifying the statistical confidence levels of diffusion results from AIMD simulations and for correctly employing this powerful technique.

Solution chemistry of actinide ions is critical to understanding the solvation behaviors and hydrolysis process. Using tetravalent thorium ion Th4+ as a representative example, we investigate the local structures and dynamic behaviors of hydrated Th4+ ions by ab initio molecular dynamics (AIMD) simulations using the recently developed norm-conserving pseudopotentials and basis sets optimized for actinides (J.-B. Lu et al., J. Chem. Theory Comput. 2021, 17, 3360-3371). AIMD simulations reveal two distinct solvation shells, with the first shell comprising 9 water molecules at approximately rTh-O = 2.50 Å and exhibiting a tricapped trigonal prism geometry. These conclusions are confirmed through metadynamics simulations and further structural analysis. AIMD simulations also show the slight effect of temperature and counterions on the structure of the solution. The structured solvation shells of the highly charged Th4+ ion with the specific geometry, distinct from the structure of liquid water, lead to corresponding structural changes in the hydrogen bond network in water. Additionally, beyond the solvent-shared ion pair (SIP) state observed in the unbiased AIMD simulations, the metadynamics simulations reconstruct a two-dimensional free energy surface that clearly indicates the potential stability of the contact ion pair (CIP) state in the system with Cl- as a counterion. The findings in this work provide insights into the solution chemistry of actinides and serve as a reference for studying other actinide solution systems.

Complexation of Cu + in Hydrothermal NaCl Brines: Ab initio molecular dynamics and energetics

The infrared spectrum of the protic ionic liquid 1-methylimidazolium nitrate: An ab initio molecular dynamics simulation study

Glycosaminoglycans (GAGs) are negatively charged polysaccharides found on cell surfaces, where they regulate transport pathways of foreign molecules toward the cell. The structural and functional diversity of GAGs is largely attributed to varied sulfation patterns along the polymer chains, which makes understanding their molecular recognition mechanisms crucial. Molecular dynamics (MD) simulations, thanks to their unmatched microscopic resolution, have the potential to be a reference tool for exploring the patterns responsible for biologically relevant interactions. However, the capability of molecular dynamics force fields used in biosimulations to accurately capture sulfation-specific interactions is not well established, partly due to the intrinsic properties of GAGs that pose challenges for most experimental techniques. In this work, we evaluate the performance of molecular dynamics force fields for sulfated GAGs by studying ion pairing of Ca2+ to sulfated moieties─N-methylsulfamate and methylsulfate─that resemble N- and O-sulfation found in GAGs, respectively. We tested available nonpolarizable (CHARMM36 and GLYCAM06) and explicitly polarizable (Drude and AMOEBA) force fields, and derived new implicitly polarizable models through charge scaling (prosECCo75 and GLYCAM-ECC75) that are consistent with our developed "charge-scaling" framework. The calcium-sulfamate/sulfate interaction free energy profiles obtained with the tested force fields were compared against reference ab initio molecular dynamics (AIMD) simulations, which serve as a robust alternative to experiments. AIMD simulations indicate that the preferential Ca2+ binding mode to sulfated GAG groups is solvent-shared pairing. Only our scaled-charge models agree satisfactorily with the AIMD data, while all other force fields exhibit poorer agreement, sometimes even qualitatively. Surprisingly, even explicitly polarizable force fields display a notable disagreement with the AIMD data, likely attributed to difficulties in their optimization and possible inherent limitations in depicting high-charge-density ion interactions accurately. Finally, the underperforming force fields lead to unrealistic aggregation of sulfated saccharides, which qualitatively disagrees with our understanding of the soft glycocalyx environment. Our results highlight the importance of accurately treating electronic polarization in MD simulations of sulfated GAGs and caution against over-reliance on currently available models without thorough validation and optimization.

We present the absolute enthalpy, entropy, heat capacity, and free energy of liquid water at ambient conditions calculated by the two-phase thermodynamic method applied to ab initio, reactive and classical molecular dynamics simulations. We find that the absolute entropy and heat capacity of liquid water from ab initio molecular dynamics (AIMD) is underestimated, but falls within the range of the flexible empirical as well as the reactive force fields. The origin of the low absolute entropy of liquid water from AIMD simulations is due to an underestimation of the translational entropy by 20% and the rotational entropy by 40% compared to the TIP3P classical water model, consistent with previous studies that reports low diffusivity and increased ordering of liquid water from AIMD simulations. Classical MD simulations with rigid water models tend to be in better agreement with experiment (in particular TIP3P yielding the best agreement), although the TIP4P-ice water model, the only empirical force field that reproduces the experimental melting temperature, has the lowest entropy, perhaps expectedly. This reiterates the limitations of existing empirical water models in simultaneously capturing the thermodynamics of solid and liquid phases. We find that the quantum corrections to heat capacity of water can be as large as 60%. Although certain water models are computed to yield good absolute free energies of water compared to experiments, they are often due to the fortuitous enthalpy-entropy cancellation, but not necessarily due to the correct descriptions of enthalpy and entropy separately.

We report calculations on the surface tension of the water-air interface using ab initio molecular dynamics (AIMD) simulations. We investigate the influence of the cell size on surface tension of water from force field molecular dynamics simulations. We find that the calculated surface tension increases with increasing simulation cell size, thereby illustrating that a correction for finite size effects is essential for small systems that are customary in AIMD simulations. Moreover, AIMD simulations reveal that the use of a double-ζ basis set overestimates the experimentally measured surface tension due to the Pulay stress while more accurate triple and quadruple-ζ basis sets give converged results. We further demonstrate that van der Waals corrections critically affect the surface tension. AIMD simulations without the van der Waals correction substantially underestimate the surface tension while the van der Waals correction with the Grimme's D2 technique results in a value for the surface tension that is too high. The Grimme's D3 van der Waals correction provides a surface tension close to the experimental value. Whereas the specific choices for the van der Waals correction and basis sets critically affect the calculated surface tension, the surface tension is remarkably insensitive to the details of the exchange and correlation functionals, which highlights the impact of long-range interactions on the surface tension. Our simulated values provide important benchmarks, both for improving van der Waals corrections and AIMD simulations of aqueous interfaces.