First-principles Molecular Dynamics Method Research Articles

Enhancement of interfacial thermal conductance by introducing carbon vacancy at the Cu/diamond interface

Effective heat dissipation of semiconductor devices is crucial for their extended lifespan and operational stability, and the interface of semiconductors provides an effective window for thermal design and management. In this work, we have systematically investigated the effect of the carbon vacancy on the thermal conductivity of diamond and the interface thermal conductance (ITC) of Cu/diamond by using both first-principles calculation and molecular dynamics methods. Although the carbon vacancy leads to a decrease in the thermal conductivity of diamond, a marked increase in ITC from 37.98 MWm−2K−1 to about 177 MWm−2K−1 for diamond (1 1 1) plane and from 78.8 MWm−2K−1 to about 241 MWm−2K−1 for diamond (0 0 1) plane is observed between Cu and diamond with carbon vacancy. The increase of the ITC is mainly due to the anharmonic phonon scattering, revealed by the phonon density of states and phonon participation ratio.

Lorenz number and transport properties of Fe: Implications to the thermal conductivity at Earth's core-mantle boundary

Abstract The electrical resistivity (ρ) and thermal conductivity (κ) of the Earth's core compositions are essential parameters for constraining the core's thermal state, the inner core age, and the evolutionary history of the geodynamo. However, controversies persist between experimental and computational results regarding the electronic transport properties (ρ and κ) of the Earth's core. Iron is the major element in the core, and its transport properties under high pressure and high temperature conditions are crucial for understanding the core's thermal state. We measured the ρ values of solid iron using the four-wire van der Pauw method at 300 K and pressures ranging from 3 to 26 GPa within a multi-anvil press. For comparison, we calculated the ρ and κ values of hexagonal close-packed (hcp) iron at conditions of 300-4100 K and 22-136 GPa using the first-principles molecular dynamics (FPMD) method. Our calculations generally align with prior studies, indicating that the electrical resistivity of solid hcp iron at Earth's core-mantle boundary (CMB) conditions is ~76-83 μΩ∙cm. The resistivity of hcp iron changes small as it melts from solid to liquid at pressures from 98 to 134 GPa. The impact of temperature and pressure on the Lorenz numbers of solid hcp iron are investigated according to our calculation results and previous studies. Under the CMB's pressure conditions, the κ of hcp iron initially decreases with increasing temperature and subsequently increases. The electron-electron scattering plays a dominant role at low temperatures and causes the decrease in κ. At high temperatures, the increase of electronic specific heat significantly increases the Lorentz number and κ. Overall, we estimate the κ of solid hcp iron at CMB's condition to be 114 ± 6 W/m/K, slightly lower than the room temperature value of 129 ± 9 W/m/K at the same pressure. Our model shows that a 0-525 km thickness of a thermally stratified layer may exist beneath the Earth's CMB depending on the core's heat flow and thermal conductivity.

First principles molecular dynamics simulation and thermal decomposition kinetics study of CL-20.

2,4,6,8,10, 12-hexanitro-2,4,6,8,10, 12-hexazepane (CL-20) is a new energetic material with high performance and low sensitivity. In-depth study of the thermal decomposition mechanism of CL-20 is a necessary condition to improve its performance, ensure its safety, and optimize its application. On the basis of a large number of empirical force fields used in molecular dynamics simulation in the past, the machine learning augmented first-principles molecular dynamics method was used for the first time to simulate the thermal decomposition reaction of CL-20 at 2200 K, 2500 K, 2800 K, and 3000 K isothermal temperature. The main stable resulting compounds are N2, CO2, CO, H2O, andH2, where CO2 and H2O continue to decompose at higher temperatures. The initial decomposition pathways are denitration by N-N fracture, ring-opening by C-N bond fracture, and redox reaction involving NO2 and CL-20. After ring opening, two main compounds, fused tricyclic pyrazine and azadicyclic, were formed, which were decomposed continuously to form monocyclic pyrazine and pyrazole ring structures. The most common fragments formed during decomposition are those containing two, three, four, and six carbons. The formation rule and quantity of main small molecule intermediates and resulting stable products under different simulated temperatures were analyzed. Based on ab initio Bayesian active learning algorithm, efficient and accurate prediction of CL-20 is made using the dynamic machine learning function of Vienna Ab-Initio Simulation Package (VASP), which constructs the energy potential surface by learning a large number of data based on AIMD calculations. The result is a machine learning force field (MLFF). Then the molecular dynamics of CL-20 was simulated using the trained MLFF model. PAW pseudopotentials and generalized gradient approximation (GGA), namely, Perdew-Burke-Ernzerhof (PBE) functional, are used in the calculation. The plane wave truncation energy (ENCUT) is set to 550 eV, and using the Gaussian broadening, the thermal broadening size of the single-electron orbital is 0.05 eV. A van der Waals revision of the system with Grimme Version 3. The energy convergence accuracy (EDIFF) of electron self-consistent iteration is set to 1E-5 eV and 1E-6 eV, respectively. The two-step structure optimization is carried out using 1'1'1 k point grid and conjugate gradient method. The ENCUT was changed to 500 eV and EDIFF to 1E-5 eV, and NVT integration (ISIF = 2) of Langevin thermostat was used for machine learning force field training and AIMD simulation of the system.

Combining stochastic density functional theory with deep potential molecular dynamics to study warm dense matter

In traditional finite-temperature Kohn–Sham density functional theory (KSDFT), the partial occupation of a large number of high-energy KS eigenstates restricts the use of first-principles molecular dynamics methods at extremely high temperatures. However, stochastic density functional theory (SDFT) can overcome this limitation. Recently, SDFT and the related mixed stochastic–deterministic density functional theory, based on a plane-wave basis set, have been implemented in the first-principles electronic structure software ABACUS [Q. Liu and M. Chen, Phys. Rev. B 106, 125132 (2022)]. In this study, we combine SDFT with the Born–Oppenheimer molecular dynamics method to investigate systems with temperatures ranging from a few tens of eV to 1000 eV. Importantly, we train machine-learning-based interatomic models using the SDFT data and employ these deep potential models to simulate large-scale systems with long trajectories. Subsequently, we compute and analyze the structural properties, dynamic properties, and transport coefficients of warm dense matter.

Operando Modeling of Zeolite-Catalyzed Reactions Using First-Principles Molecular Dynamics Simulations.

Within this Perspective, we critically reflect on the role of first-principles molecular dynamics (MD) simulations in unraveling the catalytic function within zeolites under operating conditions. First-principles MD simulations refer to methods where the dynamics of the nuclei is followed in time by integrating the Newtonian equations of motion on a potential energy surface that is determined by solving the quantum-mechanical many-body problem for the electrons. Catalytic solids used in industrial applications show an intriguing high degree of complexity, with phenomena taking place at a broad range of length and time scales. Additionally, the state and function of a catalyst critically depend on the operating conditions, such as temperature, moisture, presence of water, etc. Herein we show by means of a series of exemplary cases how first-principles MD simulations are instrumental to unravel the catalyst complexity at the molecular scale. Examples show how the nature of reactive species at higher catalytic temperatures may drastically change compared to species at lower temperatures and how the nature of active sites may dynamically change upon exposure to water. To simulate rare events, first-principles MD simulations need to be used in combination with enhanced sampling techniques to efficiently sample low-probability regions of phase space. Using these techniques, it is shown how competitive pathways at operating conditions can be discovered and how broad transition state regions can be explored. Interestingly, such simulations can also be used to study hindered diffusion under operating conditions. The cases shown clearly illustrate how first-principles MD simulations reveal insights into the catalytic function at operating conditions, which could not be discovered using static or local approaches where only a few points are considered on the potential energy surface (PES). Despite these advantages, some major hurdles still exist to fully integrate first-principles MD methods in a standard computational catalytic workflow or to use the output of MD simulations as input for multiple length/time scale methods that aim to bridge to the reactor scale. First of all, methods are needed that allow us to evaluate the interatomic forces with quantum-mechanical accuracy, albeit at a much lower computational cost compared to currently used density functional theory (DFT) methods. The use of DFT limits the currently attainable length/time scales to hundreds of picoseconds and a few nanometers, which are much smaller than realistic catalyst particle dimensions and time scales encountered in the catalysis process. One solution could be to construct machine learning potentials (MLPs), where a numerical potential is derived from underlying quantum-mechanical data, which could be used in subsequent MD simulations. As such, much longer length and time scales could be reached; however, quite some research is still necessary to construct MLPs for the complex systems encountered in industrially used catalysts. Second, most currently used enhanced sampling techniques in catalysis make use of collective variables (CVs), which are mostly determined based on chemical intuition. To explore complex reactive networks with MD simulations, methods are needed that allow the automatic discovery of CVs or methods that do not rely on a priori definition of CVs. Recently, various data-driven methods have been proposed, which could be explored for complex catalytic systems. Lastly, first-principles MD methods are currently mostly used to investigate local reactive events. We hope that with the rise of data-driven methods and more efficient methods to describe the PES, first-principles MD methods will in the future also be able to describe longer length/time scale processes in catalysis. This might lead to a consistent dynamic description of all steps-diffusion, adsorption, and reaction-as they take place at the catalyst particle level.

Detailed and reduced chemical kinetic model of CH4/air mixtures combustion based on high-precision first-principles molecular dynamics simulation

CH4/air combustion reaction kinetics has attracted many research interests because of its wide application in engineering. In this work, the CH4 oxidation in O2 at high temperatures is simulated based on the first-principles molecular dynamics method first time. Two new intermediates, HCOOH and O3, and their effect on the CH4 oxidation are revealed. Specifically, adding HCOOH-related reactions into current model GRI 3.0, NUIG 1.1 and USC II may significantly improve their predictions on the premixed laminar flame speed of CH4/air mixtures. Elementary reaction analysis also discovered that radicals, such as OH, HO2, and others play key roles in CH4 oxidation. These radicals act as highly active oxidants and promote final product formation. Combining elementary reaction with simplifying technique, a novel First-Principle (FP) and 30-step Reduced-FP (R-FP) chemical kinetic model are constructed. By using our two models, the ignition delay time, species concentration in flow reactor and premixed laminar flame speed of premixed reactive mixture (CH4/O2/Ar, CH4/O2/H2O/N2 and CH4/air) combustion are successfully predicted and verified by comparing with experimental results. In general, the FP and R-FP models will be advantageous for application of engineering in the future.

Molecular Dynamics Simulations of the Thermal Decomposition of RDX/HTPB Explosives.

The addition of binders to energetic materials is known to complicate the thermal decomposition process of such materials. To assess this effect, the present work studied the thermal decomposition of cyclotrimethylene trinitramine (RDX)/hydroxy-terminated polybutadiene (HTPB) mixtures and of pure RDX over the temperature range of 2000-3500 K by combining the classical reaction and first-principles molecular dynamics methods. The incorporation of HTPB as a binder was found to significantly reduce the decomposition rate of RDX. At 3500 K, the decay rate constant of RDX in the RDX/HTPB system is 2.0141 × 1012 s-1, while it is 2.7723 × 1012 s-1 in the pure RDX system. However, the binder HTPB had little effect on the initial decomposition mechanism, which involved the rupture of N-NO2 bonds to produce NO2. The HTPB was predicted to undergo dehydrogenation and chain breaking. The free H resulting from these processes was predicted to react with low-molecular-weight intermediates generated by the RDX, resulting in greater equilibrium quantities of the final products H2O and H2 being obtained from the mixed system compared with pure RDX. HTPB-chain fragments were also found to combine with the primary RDX decomposition product NO2 to inhibit the formation of N2 and CO2.

Electronic and elastic properties of BN, AlN and GaN

We have carried out first-principles total energy calculations to investigate electronic and elastic properties of both zinc-blende and wurtzite BN, AlN, and GaN. We have calculated lattice parameters, elastic constants, deformation potential constants, phonon frequencies at r point, Born effective charges, and piezoelectric constants. Lattice parameters are fully relaxed by using the first-principles molecular dynamics method with variable cell shape. The internal strain in a strained crystal is also relaxed by the first-principles molecular dynamics method. The internal strain influences the elastic constants, the deformation potential constants, and the piezoelectric constants effectively. We have calculated the wurtzite deformation potential constants D1 – D5 considering the internal strain correction. The piezoelectric constants of wurtzite and also zinc-blende crystals have been calculated using the Berry phase approach and we have found from first principles that those of BN have an inverse sign in contrast to AlN and GaN. Discussions will be given in comparison with results obtained herein with the previous ones. © 1998 American Institute of Physics. [S0021-8979(98)07921-3]

Finite-temperature phonon dispersion and vibrational dynamics of BaTiO3 from first-principles molecular dynamics

A systematic investigation of the finite-temperature phonon dispersion, including its smearing and temperature effects, is carried out using autocorrelation function method together with first-principles molecular dynamics method along the [001] direction of $\mathrm{Ba}\mathrm{Ti}{\mathrm{O}}_{3}$, as an illustrating example of entropy-stabilized structures. A unique anharmonicity in the cubic phase mainly derived from the interactions between titanium and oxygen atoms is revealed, which provides extremely strong damping and smearing to longitudinal optical phonons but no discernible effect on the shift of phonon energies. The anharmonicity gives rise to a nearly constant density distribution in a cubic region around the equilibrium position of the relative motion of titanium atoms with respect to oxygen atoms. These results may help to gain a further insight into complex interactions in entropy-stabilized structures and provide an essential benchmark reference to the development of the promising machine-learning based molecular dynamics methods for the investigation of phonon properties.

Thermal Decomposition Mechanism and Energy Release Law of Novel Cyclo-N5--Based Nitrogen-Rich Energetic Salt.

Detonation energy of novel cyclo-N5--based nitrogen-rich energetic salts is expected to exceed 3 times the equivalent of TNT. PHAC([(N5)6(H3O)3(NH4)4Cl]) was selected as the prototype to investigate the thermal decomposition reaction of PHAC in the solid phase for the first time by the first-principles molecular dynamics method. At about 38 ps, the final state of the reaction was reached. It was found that there were mainly five final products, among which the proportion of N2 molecules was the maximum and accounted for 60% (mole fraction) of all final products. The reaction pathways of PHAC were analyzed, and more than 30 elementary reactions were found. The initial reaction of the PHAC thermal decomposition was the ring-opening of cyclo-N5- ion and proton transfer. The energy release of PHAC thermal decomposition is divided into two stages. The first stage is a slow release of energy before the formation of the HN3 molecule. The second stage is the rapid release of energy after the formation of HN3 molecules. The HN3 molecule is an essential junction, and the unimolecular dissociation of HN3 is the rate-determining step. Such an understanding of reaction mechanism and energy release law greatly promotes the application and synthesis of novel cyclo-N5--based nitrogen-rich energetic salts.

Equations of state of poly- α -methylstyrene and polystyrene: First-principles calculations versus precision measurements

We show with a recently devised extended first-principles molecular dynamics method that calculated Hugoniots of poly-$\ensuremath{\alpha}$-methylstyrene agree well with precision experimental results of Kritcher et al. [Nature (London) 584, 51 (2020)] and D\oppner et al. [Phys. Rev. Lett. 121, 025001 (2018)]. The deviation is smaller than 0.8%. This agreement does not sensitively rely on the approximations in the employed first-principles methods as long as underlying physics are well described, as illustrated in the calculation of equation of state for polystyrene covering the warm dense regime. These results may stimulate a broad range of quantitative investigations on warm dense matter that were not thought possible before, and may thus afford a new prospect to the field of inertial confinement fusion and high-energy-density physics.

Electronic charge density as a fast approach for predicting Li-ion migration pathways in superionic conductors with first-principles level precision

Finding Li-ion migration pathways in solid state electrolytes is an important prerequisite for disruptive development of all-solid-state battery materials. Previous studies either used empirical method such as bond valence (BV) or relied on on-the-fly first-principles molecular dynamics (FPMD) simulations, which are very time and resource consuming. In this paper, we propose an approach of using spatially dependent electronic charge density to predict Li-ion migration pathways in superionic conductors with first-principles level precision. Since the electronic charge density can be simultaneously calculated along with the structure optimization, this method saves tremendous computing time in finding the migration pathways, as is the case for the currently widely used FPMD method. Its accuracy and feasibility are validated by reproducing 3D diffusion channel of six representative Li-ion structures [LiFePO4, Li2S, Li5PS4Cl2, Li10GeP2S12, Li4GeS4, and Li3Y(PS4)2]. Our approach is expected to accelerate high-throughput screening of superionic conductors, such as using the most likely migration paths replaces global search of migration paths for first-principles method. The direct relationship between ion transport pathways and electronic charge densities constructed here could serve as an efficient descriptor for training machine learning models. Due to the inherent relationship between bottom-level electronic charge density and macroscopic properties, we expect that this method can be also extended to designing materials with other target physical or chemical properties such as thermoelectrics, photovoltaics, and fuel cells.

First-principles calculations of equilibrium bromine isotope fractionations

Significant bromine (Br) isotope composition variations are found in natural salts and brines, which are often even larger than those of co-existing chlorine isotope compositions. The cause of such large Br isotope variations remains elusive. In this study, equilibrium Br isotope fractionations among Br-bearing gaseous molecules, aqueous species and crystalline minerals are provided via the density functional theory (DFT) based first-principles calculations. These fractionation factors form the base for future Br isotope geochemistry studies. Specifically, the first-principles molecular dynamics (FPMD) method is used to evaluate the tricky solvation effects, i.e., dozens of snapshots of FPMD trajectories are selected and re-optimized to their lowest energy atomic coordinates, then the reduced partition function ratios (i.e., β factors) of aqueous Br-bearing species are obtained by computing the average values of those snapshots. In this way, the configurational effects of aqueous Br-bearing species are included. For crystalline compounds, the static first-principles periodic DFT methods are used. We find that the β factors generally increase as the oxidation states of Br increase, indicating that heavy Br isotopes tend to be enriched in substances with higher Br oxidation states. The aqueous Br-bearing species in brines have detectable but small Br isotope fractionations with each other. However, the fractionations between gaseous molecules and NaBr(aq) are significantly larger, e.g., Δ81BrCH3Br(gas)-NaBr(aq) is 0.95 ± 0.041‰ at 20 °C. As for minerals, the fractionation between Br-halite(p) (pure NaBr crystal) and NaBr(aq) is close to zero, but for Br-halite(1/124) (Na125Cl124Br1) and NaBr(aq), the fractionation is 0.206 ± 0.041‰. Similar results are found for the fractionations between Br-sylvite, Br-bischofite and Br-bearing solutions, indicating that Br isotope compositions are closely related to Br/Cl ratios in minerals.By using the calculated isotope fractionation factors, we have modeled the Br isotope composition variations during salt precipitation processes. At 20 °C, the total variations of Br isotopes of salts and brines are found to be −0.45‰ to +0.21‰ and −0.39‰ to 0‰, respectively. They are much smaller than the observed Br isotope variations in natural samples. There must be other ways to fractionate Br isotopes to the extent that observed in nature. Based on the predicted equilibrium Br isotope fractionations among substances with different Br oxidation states, the large Br isotope variations in nature can be explained by the change of Br oxidation state. The sudden change of Br isotope compositions hence can be used as a new indicator for the change of redox conditions.

Warm dense matter simulation via electron temperature dependent deep potential molecular dynamics

Simulating warm dense matter that undergoes a wide range of temperatures and densities is challenging. Predictive theoretical models, such as quantum-mechanics-based first-principles molecular dynamics (FPMD), require a huge amount of computational resources. Herein, we propose a deep learning based scheme called electron temperature dependent deep potential molecular dynamics (TDDPMD), which can be readily applied to study larger systems with longer trajectories, yielding more accurate properties. We take warm dense beryllium (Be) as an example with the training data from FPMD simulations spanning a wide range of temperatures (0.4–2500 eV) and densities (3.50–8.25 g/cm3). The TDDPMD method well reproduces the principal Hugoniot curve and radial distribution functions from the FPMD method. Furthermore, it depicts the reflection point of the Hugoniot curve more smoothly and provides more converged diffusion coefficients. We also show the new model can yield static structure factors and dynamic structure factors of warm dense Be.

Selective linear etching of monolayer black phosphorus using electron beams**Project supported by the National Natural Science Foundation of China (Grant Nos. 11622437, 61674171, 11804247, and 11974422), the Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDB30000000), Key Research Program of Frontier Sciences, Chinese Academy of Sciences (B.L, W.Z.), the Fundamental Research Funds for the Central Universities, China,

Point and line defects are of vital importance to the physical and chemical properties of certain two-dimensional (2D) materials. Although electron beams have been demonstrated to be capable of creating single- and multi-atom defects in 2D materials, the products are often random and difficult to predict without theoretical inputs. In this study, the thermal motion of atoms and electron incident angle were additionally considered to study the vacancy evolution in a black phosphorus (BP) monolayer by using an improved first-principles molecular dynamics method. The P atoms in monolayer BP tend to be struck away one by one under an electron beam within the displacement threshold energy range of 8.55–8.79 eV, which ultimately induces the formation of a zigzag-like chain vacancy. The chain vacancy is a thermodynamically metastable state and is difficult to obtain by conventional synthesis methods because the vacancy formation energy of 0.79 eV/edge atom is higher than the typical energy in monolayer BP. Covalent-like quasi-bonds and a charge density wave are formed along the chain vacancy, exhibiting rich electronic properties. This work proposes a theoretical protocol for simulating a complete elastic collision process of electron beams with 2D layers and will facilitate the establishment of detailed theoretical guidelines for experiments on 2D material etching using focused high-energy electron beams.

First principles study on the stability and thermodynamic properties of N[sbnd]Au co-doped graphene

Based on first-principles density functional perturbation theory and first-principles molecular dynamics (MD) method, the effects of N and Au dopants as well as doping concentration on the structure stability, thermal stability and thermodynamic properties of graphene were systemically studied. It is found that the formation energy, phonon dispersion curve and MD simulation analysis indicate that N-doped graphene is more stable than Au and NAu co-doped graphene at the ground state or room temperature (300 K). The graphene doped with N, Au and NAu pair at different doping concentration can significantly affect its thermodynamic properties. Regardless of low or high concentrations, the specific heat and entropy of the doped graphene system increase as temperature increases, whereas free energy decreases. The results provide a theoretical basis for regulating the thermal conductivity of graphene and for relevant developing device applications.

First-Principles Methods in the Investigation of the Chemical and Transport Properties of Materials under Extreme Conditions

Abstract Earth is a dynamic system. The thermodynamics conditions of Earth vary drastically depending on the depth, ranging from ambient temperature and pressure at the surface to 360 GPa and 6600 K at the core. Consequently, the physical and chemical properties of Earth’s constituents (e.g., silicate and carbonate minerals) are strongly affected by their immediate environment. In the past 30 years, there has been a tremendous amount of progress in both experimental techniques and theoretical modeling methods for material characterization under extreme conditions. These advancements have elevated our understanding of the properties of minerals, which is essential in order to achieve full comprehension of the formation of this planet and the origin of life on it. This article reviews recent computational techniques for predicting the behavior of materials under extreme conditions. This survey is limited to the application of the first-principles molecular dynamics (FPMD) method to the investigation of chemical and thermodynamic transport processes relevant to Earth Science.

Thermodynamics, structure, and transport properties of the MgO–Al2O3 liquid system

Seven liquids along the MgO–Al2O3 join were simulated at zero pressure in temperature (T) range 2000–6000 K using the first-principles molecular dynamics method. The simulation results show continuous changes in various physical properties with composition (molar fraction of alumina, X). They suggest that the binary mixing tends to be nearly ideal with no immiscibility along the entire join. The calculated mean coordination numbers of MgO and AlO polyhedra gradually increase with increasing X, for example, their respective values are 4.6 and 4.3 at/near the MgO end, 5.2 and 4.6 for MgAl2O4 spinel composition, and 5.5 and 4.8 at/near the alumina end. The mean O–O coordination number remains almost unchanged along the join at ≥ 12 implying a closely packed arrangement. In contrast, all other coordination types including O–Mg and O–Al change dramatically along the join. The calculated self-diffusion and viscosity coefficients vary much less with composition (by a factor of 4 or less along the entire join) than with temperature (by two orders of magnitudes over the T range considered). Their T–X variations can be well described by the respective Arrhenius equations with composition-dependent activation energies and pre-exponential parameters. While the alumina and silica components are considered to play a similar role with regard to the structural polymerization of amorphous aluminosilicates, our results show that they influence the melt transport properties very differently. Therefore, the general notion that these two oxide components play an equivalent role in multicomponent magmatic melts is not unambiguous.

Ab initio simulations of liquid electrolytes for energy conversion and storage

AbstractUnderstanding physicochemical properties of liquid electrolytes is essential for predicting and optimizing device performance for a wide variety of emerging energy technologies, including photoelectrochemical water splitting, supercapacitors, and batteries. In this work, we review recent progress and open challenges in predicting structural, dynamical, and electronic properties of the liquids using first‐principles approaches. We briefly summarize the basic concepts of first‐principles molecular dynamics (FPMD), and we discuss how FPMD methods have enriched our understanding of a number of liquids, including aqueous solutions, organic electrolytes and ionic liquids. We also discuss technical challenges in extending FPMD simulations to the study of liquid electrolytes in more complex environments, including the interface between electrolytes and electrodes, which is a key component in many energy storage and conversion systems.

Contrasting Roles of Water at Sliding Interfaces between Silicon-Based Materials: First-Principles Molecular Dynamics Sliding Simulations

It is known that the wear of silicon-based materials is due to the tribochemical reaction with water at the sliding interface, but the detailed mechanisms remain under debate. In this study, we used a first-principles molecular dynamics method to investigate the tribochemical wear mechanism. When a small amount of water was present at the sliding interface, the formation of interfacial bridge bonds connecting the two surfaces was observed. These bonds transmitted shear force to the surfaces that induced strain therein. The strained surface Si–O bonds subsequently reacted with water (Si–O–Si + H2O → Si–OH + Si–OH), that is, the hydrolysis reaction occurred. Because the hydrolysis reaction resulted in dissociation of the surface Si–O bonds, water promoted tribochemical wear. However, when a large amount of water was present, it separated the two surfaces. The water thereby suppressed the formation of interfacial bridge bonds and in turn the hydrolysis of Si–O bonds and thus tribochemical wear. Our results i...