Ab Initio Molecular Dynamics Simulations Research Articles

Self-passivation of Halide Interstitial Defects by Organic Cations in Hybrid Lead-Halide Perovskites: Ab Initio Quantum Dynamics.

Halide interstitial defects severely hinder the optoelectronic performance of metal halide perovskites, making research on their passivation crucial. We demonstrate, using ab initio nonadiabatic molecular dynamics simulations, that hydrogen vacancies (Hv) at both N and C atoms of the methylammonium (MA) cation in MAPbI3 efficiently passivate iodine interstitials (Ii), providing a self-passivation strategy for dealing with the Hv and Ii defects simultaneously. Hv at the N site (Hv-N) introduces a defect state into the valence band, while the state contributed by Hv at the C site (Hv-C) evolves from a shallow level at 0 K to a deep midgap state at ambient temperature, exhibiting a high environmental activity. Both Hv-N and Hv-C are strong Lewis bases, capable of capturing and passivating Ii defects. Hv-C is a stronger Lewis base, bonds with Ii better, and exhibits a more pronounced passivation effect. The charge carrier lifetimes in the passivated systems are significantly longer than in those containing either Hv or Ii, and even in pristine MAPbI3. Our demonstration of the Hv and Ii defect self-passivation in MAPbI3 suggests that systematic control of the relative concentrations of Hv and Ii can simultaneously eliminate both types of defects, thereby minimizing charge and energy losses. The demonstrated defect self-passivation strategy provides a promising means for defect control in organic-inorganic halide perovskites and related materials and deepens our atomistic understanding of defect chemistry and charge carrier dynamics in solar energy and optoelectronic materials.

An AIMD investigation on the structural properties of Fe-SiO2 melt for converting SiO2 inclusions into the reinforcing particles in Fe matrix

It is essential to understand the structural properties of Fe-SiO2 melt for converting SiO2 inclusions into the reinforcing particles in Fe matrix by liquid metallurgical synthesis. In this work, the structural behaviors of Si and O in Fe27SiO2, Fe24(SiO2)2, Fe21(SiO2)3, and Fe18(SiO2)4 melts at 2800 K and the formation of SiOn clusters in Fe24(SiO2)2 melt (20 at.% SiO2) from 2800 K to 2000 K are investigated by ab-initio molecular dynamics simulations. According to the pseudo-binary mixing enthalpies, partial pair correlation functions, and chemical short-range order, the critical composition range for the formation of SiOn clusters in Fe-SiO2 melt at 2800 K is from 20 at.% SiO2 to 30 at.% SiO2, and the critical temperature range in the quenching process of Fe24(SiO2)2 melt is from 2600 K to 2400 K. By further analyzing the distribution of partial coordination numbers and bond angles, the quenching process of Fe24(SiO2)2 melt from 2800 K to 2000 K can be divided into three stages: the homogenous Fe-SiO2 melt from 2800 K to 2600 K, the dispersive formation of SiOn clusters containing a considerable number of SiO4 tetrahedrons from 2600 K to 2200 K, the gathering of SiOn clusters contributed by the connection of SiO4 tetrahedrons in the pattern of OSi2 from 2200 K to 2000 K.

Interface Stability and Reaction Mechanisms of Li3YCl5Br with High-Voltage Cathodes and Li Metal Anode: Insights from Ab Initio Simulations.

Recent advancements in battery technology emphasize the critical role of solid electrolytes in enhancing the performance and safety of next-generation batteries. In this study, we investigate the interface stability and reaction mechanisms of Li3YCl5Br, a promising halide-based solid electrolyte, in contact with high-voltage Ni-Mn-Co (NMC) cathodes and a Li metal anode using ab initio molecular dynamics simulations. Our findings reveal that Li3YCl5Br reacts with charged NMC cathodes. This reaction involves changes in the oxidation states of Br- anions in Li3YCl5Br and d-element cations in NMC, as well as the diffusion of Li ions from the solid electrolyte to the cathode to maintain charge balance. The reaction is confined to the interface, suggesting bulk stability. Conversely, the Li/Li3YCl5Br interface exhibits significant instability, with a chemical reaction that results in substantial structural changes and the formation of LiCl and LiBr at the solid electrolyte surface and metallic Y at the Li anode surface. These insights provide valuable information for optimizing interfacial design, aiming at improving the performance and reliability of all-solid-state batteries using halide solid electrolytes.

Thermal decomposition behavior of Hf6Ta2O17 powders: Experiment and ab initio molecular dynamics simulation

To investigate the thermal stability of Hf6Ta2O17, experiment and ab initio molecular dynamics simulation (from 1473 K to 1573 K) were employed. The results show that HfO2 and Ta2O5 were formed owning to the decomposition of Hf6Ta2O17 at high temperatures. The content of HfO2 was much higher than that of Ta2O5 because the number and bonding strength of the topmost Hf-O bonds were more than those of the topmost Ta-O bonds with the temperature increase. Finally, more Ta2O5 was introduced to effectively suppress the decomposition of Hf6Ta2O17. Our work provides useful information for understanding the decompositions of complex oxides. This work also provides a new option for the preparation and development of the ternary oxides by APS.

Piezoelectric GaGeX2 (X = N, P, and As) semiconductors with Raman activity and high carrier mobility for multifunctional applications: a first-principles simulation.

In the present work, we propose GaGeX2 (X = N, P, As) monolayers and explore their structural, vibrational, piezoelectric, electronic, and transport characteristics for multifunctional applications based on first-principles simulations. Our analyses of cohesive energy, phonon dispersion spectra, and ab initio molecular dynamics simulations indicate that the three proposed structures have good energetic, dynamic, and thermodynamic stabilities. The GaGeX2 are found as piezoelectric materials with high piezoelectric coefficient d 11 of -1.23 pm V-1 for the GaGeAs2 monolayer. Furthermore, the results from electronic band structures show that the GaGeX2 have semiconductor behaviours with moderate bandgap energies. At the Heyd-Scuseria-Ernzerhof level, the GaGeP2 and GaGeAs2 exhibit optimal bandgaps for photovoltaic applications of 1.75 and 1.15 eV, respectively. Moreover, to examine the transport features of the GaGeX2 monolayers, we calculate their carrier mobility. All three investigated GaGeX2 systems have anisotropic carrier mobility in the two in-plane directions for both electrons and holes. Among them, the GaGeAs2 monolayer shows the highest electron mobilities of 2270.17 and 1788.59 cm2 V-1 s-1 in the x and y directions, respectively. With high electron mobility, large piezoelectric coefficient, and moderate bandgap energy, the GaGeAs2 material holds potential applicability for electronic, optoelectronic, piezoelectric, and photovoltaic applications. Thus, our findings not only predict stable GaGeX2 structures but also provide promising materials to apply for multifunctional devices.

Metal Complexation for the Rational Design of Gemcitabine Formulations in Cancer Therapy.

Nanoformulation of chemotherapies represents a promising strategy to enhance outcomes in cancer therapy. Gemcitabine is a chemotherapeutic agent approved by the Food and Drug Administration for the treatment of various solid tumors. Nevertheless, its therapeutic effectiveness is constrained by its poor metabolic stability and pharmacokinetic profile. Nanoformulations of gemcitabine in lipid and polymer nanocarriers usually lead to poor loading capability and an inability to effectively control its release profile due to the physicochemical characteristics of the drug and matrices. Here, we propose metal-gemcitabine complexation with biorelevant metal cations as a strategy to alter the properties of gemcitabine in a noncovalent manner, paving the way for the development of novel nanoformulations. A speciation study on gemcitabine and Mn2+, Zn2+, and Ca2+ was performed with the aim of investigating the extent of the interaction between the drug and the proposed metal cations, and selecting the best conditions of temperature, pH, and drug-to-metal molar ratio that optimize such interactions. Also, a series of density functional theory calculations and spin-polarized ab initio molecular dynamics simulations were carried out to achieve insights on the atomistic modalities of these interactions. Mn2+-gemcitabine species demonstrated the ability to maintain gemcitabine's biological activity in vitro. The scientific relevance of this study lies in its potential to propose metal-gemcitabine as a valuable strategy for developing nanoformulations with optimized quality target product profiles. The work is also clinically relevant because it will lead to improved treatment outcomes, including enhanced efficacy and pharmacokinetics, decreased toxicity, and new clinical possibilities for this potent therapeutic molecule.

From unbound to bound states: Ab initio molecular dynamics of ammonia clusters with an excess electron.

Ab initio molecular dynamics simulations of negatively charged clusters of 2-48 ammonia molecules were performed to elucidate the electronic stability of the excess electron as a function of cluster size. We show that while the electronic stability of finite temperature clusters increases with cluster size, as few as 5-7 ammonia molecules can bind an excess electron, reaching a vertical binding energy slightly less than half of the bulk value for the largest system studied. These results, which are in agreement with previous studies wherever available, allowed us to analyze the excess electron binding patterns in terms of its radius of gyration and shape anisotropy and provide a qualitative interpretation based on a particle-in-a-spherical-well model.

Propensity of hydroxide and hydronium ions for the air-water and graphene-water interfaces from abinitio and force field simulations.

Understanding acids and bases at interfaces is relevant for a range of applications from environmental chemistry to energy storage. We present combined abinitio and force-field molecular dynamics simulations of hydrochloric acid and sodium hydroxide highly concentrated electrolytes at the interface with air and graphene. In agreement with surface tension measurements at the air-water interface, we find that HCl presents an ionic surface excess, while NaOH displays an ionic surface depletion, for both interfaces. We further show that graphene becomes less hydrophilic as the water ions concentration increases, with a transition to being hydrophobic for highly basic solutions. For HCl, we observe that hydronium adsorbs to both interfaces and orients strongly toward the water phase, due to the hydrogen bonding behavior of hydronium ions, which donate three hydrogen bonds to bulk water molecules when adsorbed at the interface. For NaOH, we observe density peaks of strongly oriented hydroxide ions at the interface with air and graphene. To extrapolate our results from concentrated electrolytes to dilute solutions, we perform single ion-pair abinitio simulations, as well as develop force-field parameters for ions and graphene that reproduce the density profiles at high concentrations. We find the behavior of hydronium ions to be rather independent of concentration. For NaOH electrolytes, the force-field simulations of dilute NaOH solutions suggest no hydroxide adsorption but some adsorption at high concentrations. For both interfaces, we predict that the surface potential is positive for HCl and close to neutral for NaOH.

UV-Induced Reaction Pathways in Bromoform Probed with Ultrafast Electron Diffraction.

For many chemical reactions, it remains notoriously difficult to predict and experimentally determine the rates and branching ratios between different reaction channels. This is particularly the case for reactions involving short-lived intermediates, whose observation requires ultrafast methods. The UV photochemistry of bromoform (CHBr3) is among the most intensely studied photoreactions. Yet, a detailed understanding of the chemical pathways leading to the production of atomic Br and molecular Br2 fragments has proven challenging. In particular, the role of isomerization and/or roaming and their competition with direct C-Br bond scission has been a matter of continued debate. Here, gas-phase ultrafast megaelectronvolt electron diffraction (MeV-UED) is used to directly study structural dynamics in bromoform after single 267 nm photon excitation with femtosecond temporal resolution. The results show unambiguously that isomerization contributes significantly to the early stages of the UV photochemistry of bromoform. In addition to direct C-Br bond breaking within <200 fs, formation of iso-CHBr3 (Br-CH-Br-Br) is observed on the same time scale and with an isomer lifetime of >1.1 ps. The branching ratio between direct dissociation and isomerization is determined to be 0.4 ± 0.2:0.6 ± 0.2, i.e., approximately 60% of molecules undergo isomerization within the first few hundred femtoseconds after UV excitation. The structure and time of formation of iso-CHBr3 compare favorably with the results of an ab initio molecular dynamics simulation. The lifetime and interatomic distances of the isomer are consistent with the involvement of a roaming reaction mechanism.

Phase transition in the shape memory alloy NiTi described by the SCAN meta-GGA functional.

Climbing the ladder of density functional approximations has long been proposed to systematically improve the accuracy of first-principles calculations employing the density functional theory (DFT); however, up until now, the Perdew-Burke-Ernzerhof (PBE) functional at the second rung of the ladder, has dominated. Here, we present a study of the martensitic phase transition in NiTi based on abinitio molecular dynamics simulations and thermodynamic integration using the third-rung approximation of the strongly constrained and appropriately normalized (SCAN) meta-generalized gradient approximation (GGA). Although the predicted equilibrium lattice constants and formation enthalpy agree well with experimental data, the martensitic transition temperature (MTT) is overestimated by 94% (or 324K too high), compared with only 22% (77K) overestimation by PBE. The latent heat (q) is severely overestimated by SCAN as well. This deteriorated performance originates from the enlarged energy difference (ΔE) between the austenite and martensite phases, compared with the PBE result. Furthermore, a large variation (over 50meV/atom) in ΔE using different meta-GGAs indicates large variations in computed MTTs (∼400-500 K) and q, i.e., the predicted thermodynamic properties depend sensitively on the choice of meta-GGA. This would pose a serious problem when upgrading DFT calculations to the third rung. One possible solution is to add NiTi as a normsystem so that the revised SCAN meta-GGA could reproduce the PBE results of the relevant energy difference.

Simulation of lithium hydroxide decomposition using deep potential molecular dynamics.

Chemical reactions and vapor-liquid equilibria for molten lithium hydroxide (LiOH) were studied using molecular dynamics simulations and a deep potential (DP) model. The neural network for the model was trained on quantum density functional theory data for a range of conditions. The DP model allows simulations over timescales of hundreds of ns, which provide equilibrium compositions for the systems of interest. Single-phase NPT simulations of the liquid show the decomposition of LiOH into lithium oxide (Li2O) and dissolved water (H2O). These DP results were validated by direct abinitio molecular dynamics simulations that confirmed the accuracy of the model with respect to reaction kinetics and equilibrium properties of the melt. The reactive vapor-liquid behavior of this system was subsequently studied using direct coexistence interfacial DP simulations. Partial pressures of H2O in the vapor are found to be in close agreement with available experimental measurements. By fitting temperature-dependent expressions for the reaction equilibrium and Henry's law constants, the equilibrium composition for any given initial composition and temperature can be quantitatively modeled. For high initial concentrations of Li2O or H2O, mixtures of LiOH + Li2O/H2O are found to undergo phase separation. The present study illustrates how DP-based molecular dynamics simulations can be used for quantitative modeling of multiphase reactive behavior with the accuracy of the underlying abinitio quantum chemical methods.

Insight into the Reversible Hydrogen Storage of Titanium-Decorated Boron-Doped C20 Fullerene: A Theoretical Prediction

Hydrogen storage has been a bottleneck factor for the application of hydrogen energy. Hydrogen storage capacity for titanium-decorated boron-doped C20 fullerenes has been investigated using the density functional theory. Different boron-doped C20 fullerene absorbents are examined to avoid titanium atom clustering. According to our research, with three carbon atoms in the pentagonal ring replaced by boron atoms, the binding interaction between the Ti atom and C20 fullerene is stronger than the cohesive energy of titanium. The calculated results revealed that one Ti atom can reversibly adsorb four H2 molecules with an average adsorption energy of −1.52 eV and an average desorption temperature of 522.5 K. The stability of the best absorbent structure with a gravimetric density of 4.68 wt% has been confirmed by ab initio molecular dynamics simulations. These findings suggest that titanium-decorated boron-doped C20 fullerenes could be considered as a potential candidate for hydrogen storage devices.

Enhancing hydrogen storage efficiency: Computational insights into scandium-decorated 2D polyaramid

This study explores hydrogen storage in 2D polyaramid (2DPA) and its enhancement via scandium decoration for onboard storage in fuel cell vehicles. Sc decoration in 2DPA is accompanied by a net 1.6 e charge transfer from Sc to 2DPA. Hydrogen binding in 2DPA + Sc proceeds with a net charge transfer of 0.32 e from Sc towards H2. 2DPA + Sc demonstrates a maximum hydrogen loading capacity of 8.589 wt% with an average adsorption energy of −0.376 eV/H2. These findings meet the stipulated criteria by the US Department of Energy for solid-state hydrogen storage in light-duty vehicles. Feasibility studies were conducted considering practical limitations in transition metal-modified carbon nanomaterials, including Sc-Sc clustering tendencies, stability, and hydrogen desorption behavior via ab initio molecular dynamics simulations, phonon dispersion, and diffusion studies. The highest barrier height for hydrogen desorption from 2DPA + Sc is 0.48 eV, and desorption is predicted to occur at 412 K (5 bar) indicating possibility of room temperature and reversible hydrogen storage. Our findings indicate that 2DPA + Sc is a promising hydrogen storage substrate material and should be explored in experimental trials.

Data-Efficient Active Learning for Thermodynamic Integration: Acidity Constants of BiVO4 in Water.

The protonation state of molecules and surfaces is pivotal in various disciplines, including (electro-)catalysis, geochemistry, biochemistry, and pharmaceutics. Accurately and efficiently determining acidity constants is critical yet challenging, particularly when explicitly considering the electronic structure, thermal fluctuations, anharmonic vibrations, and solvation effects. In this research, we employ thermodynamic integration accelerated by com- mittee Neural Network potentials, training a single machine learning model that accurately describes the relevant protonated, deprotonated, and intermediate states. We investigate two deprotonation reactions at the BiVO4 (010)-water interface, a promising candidate for efficient photocatalytic water splitting. Our results illustrate the convergence of the required ensemble averages over simulation time and of the final acidity constant as a function of the Kirkwood coupling parameter. We demonstrate that simulation times on the order of nanoseconds are required for statistical convergence. This time scale is currently unachievable with explicit ab-initio molecular dynamics simulations at the hybrid DFT level of theory. In contrast, our machine learning workflow only requires a few hundred DFT single point calculations for training and testing. Exploiting the extended time scales accessible, we furthermore asses the effect of commonly applied bias potentials. Thus, our study significantly advances calculating free energy differences with ab-initio accuracy.

Structural evolution of liquid silicates under conditions in Super-Earth interiors

Molten silicates at depth are crucial for planetary evolution, yet their local structure and physical properties under extreme conditions remain elusive due to experimental challenges. In this study, we utilize in situ X-ray diffraction (XRD) at the Matter in Extreme Conditions (MEC) end-station of the Linear Coherent Linac Source (LCLS) at SLAC National Accelerator Laboratory to investigate liquid silicates. Using an ultrabright X-ray source and a high-power optical laser, we probed the local atomic arrangement of shock-compressed liquid (Mg,Fe)SiO3 with varying Fe content, at pressures from 81(9) to 385(40) GPa. We compared these findings to ab initio molecular dynamics simulations under similar conditions. Results indicate continuous densification of the O-O and Mg-Si networks beyond Earth’s interior pressure range, potentially altering melt properties at extreme conditions. This could have significant implications for early planetary evolution, leading to notable differences in differentiation processes between smaller rocky planets, such as Earth and Venus, and super-Earths, which are exoplanets with masses nearly three times that of Earth.

Direct Hydrogen Production Promoted by Laser-Induced Water Plasma.

Hydrogen, as a clean energy carrier, plays an important role in addressing the current energy and environmental crisis. However, conventional hydrogen production technologies require extreme reaction conditions, such as high temperature, high pressure, and catalysts. Herein, we study the microscopic mechanism of laser-induced water plasma and subsequent H2 production with real-time time-dependent density functional theory simulations and ab initio molecular dynamics simulations. The results demonstrate that intense laser excites liquid water to generate nonequilibrium plasma in a warm-dense state, which constitutes a superior reaction environment. Subsequent annealing leads to the recombination of energetic reactive particles to generate H2, O2, and H2O2 molecules. Annealing rate and laser wavelength are shown to modulate the product ratio, and the energy conversion efficiency can reach ∼9.2% with an annealing rate of 1.0 K/fs. This work reveals the nonequilibrium atomistic mechanisms of hydrogen production from laser-induced water plasma and shows far-reaching implications for the design of optically controllable hydrogen technology.

Tunable optical properties of BAs/ZnO vdW heterostructure

Stacked heterostructures is an effective strategy for physical property modulation and application of novel two-dimensional materials. In this study, a heterostructure consisting of two-dimensional III-V group hexagonal BAs and monolayer of ZnO is presented. The minimum value of binding and cohesive energies screened the BB’ configuration. Phonon spectra and ab initio molecular dynamics (AIMD) simulations further demonstrated the kinetic and thermodynamic stability of the selected model. Most notably, the formation of the heterostructure greatly improves the optical absorption performance of the monolayer, especially in the infrared (IR) regions. At a compressive strain of −6%, the band alignment shifts from type I to type II, while the bandgap becomes dramatically smaller. Refraction and reflection coefficients in the IR region under compressive strain (−2% and −4%) modulation were enhanced significantly. Our results provide theoretical guidance for the design of high-performance photovoltaic devices and solar cells based on BAs/ZnO heterostructures.

Construction of Al–Si interatomic potential based on Bayesian active learning

Nanoscale simulations for optimizing the performance and processing of Al–Si alloys are currently facing two major obstacles: the scarcity of high-quality semi-empirical potentials tailored to complex alloy systems, and the prohibitively high computational cost associated with ab initio molecular dynamics simulations. In order to enhance simulation efficiency and accuracy of the Al–Si alloys’ microstructural evolution, this study employs a dynamic active learning technique, FLARE, to develop a non-parametric machine learning potential that combines the high accuracy of density functional theory (DFT) with the efficiency of classical molecular dynamics (MD). Without relying on extensive initial ab initio molecular dynamics data or existing databases, collection of the necessary data is progressively made during the active learning process, thereby constructing a potential capable of accurately simulating the structure and dynamics of high-temperature Al–Si alloys. By comparing with experimental measurements and ab initio molecular dynamics calculations, the high accuracy and computational efficiency of this potential is demonstrated in predicting energy, force, structure, and dynamic properties. The results provide novel theoretical insights for optimizing Al–Si alloy processing and underscore the usefulness of active learning methods in constructing high-accuracy potentials.

Ligand engineering regulates the electronic structure of Ni-N-C sites to promote electrocatalytic acetylene semi-hydrogenation

Compared with traditional thermal catalytic hydrogenation technology, electrocatalytic acetylene semi-hydrogenation (EASH) is a green and environmentally friendly method. EASH utilizes renewable electricity under normal temperature and pressure conditions, and uses water as a hydrogen source to electrocatalytically semi-hydrogenate acetylene to ethylene. Ni-based single-atom catalysts (SACs) have shown good application prospects in EASH, but there is still much room for optimization. The axial coordination regulation of the active center is a potential means to improve its activity. In this work, the activity and selectivity of NiN4 SACs with 14 axial ligands (X) for EASH were systematically studied via density functional theory (DFT). First, the binding energy and ab initio molecular dynamics simulation results show that all the NiN4-X can exist stably. Second, the Gibbs free energy diagram shows that the activation and adsorption of C2H2 is the rate-determining step of the reaction. The introduction of the –ONO ligand enhances the activation and adsorption of C2H2 by NiN4, which is beneficial to the occurrence of EASH and inhibits the side reactions of hydrogen evolution. The two parameters ΔG∗CHCH and ΔG∗CH2CH3 can be used as characteristic descriptors to predict the activity and selectivity of EASH. Finally, the catalytic activity mechanism was explained from the perspective of electrons and orbitals, and it was found that the dz2 orbital played a leading role in the axial ligand regulation of C2H2 catalytic activity. This work provides a new method for the development of efficient EASH catalysts.

Dual optimization strategy assisted m-phenylenediamine-based hypercrosslinked polymer loaded ultrafine bimetallic nanoparticles for efficient formic acid dehydrogenation

Heterogeneous catalysts based on Pd play a vital role in enabling efficient formic acid decomposition (FAD). Nevertheless, the performance of Pd-based catalysts is constrained by inherent challenges, such as Pd particles’ tendency to aggregate and possess localized electronic structures. Therefore, there is an urgent need to develop an effective strategy to simultaneously overcome these challenges. In response to this, we synthesized knitting hypercrosslinked polymers (HCPs) using m-phenylenediamine (MPD) as the aromatic monomer. A dual-optimization approach was proposed, aiming to mitigate the adverse effects of excessive coordination and maximize the involvement of residual Fe3+ in the bimetallic synergistic effect. Experimental findings, DFT calculations, and ab initio molecular dynamics simulations (AIMDs) collectively suggest that reducing the coordination effect leads to enhanced nitrogen exposure in the HCPs, consequently reducing the size of Pd species. Furthermore, the incorporation of residual Fe3+ into Pd forms Pd-Fe bimetallic species, which then adjusts the catalytic reaction barrier and enhances catalytic activity. Notably, the optimized Pd@MHCP-2 catalyst exhibited exceptional performance in the FAD reaction at 323 K, achieving a remarkable turnover frequency (TOF) value of 1486 h−1. This research introduces a novel perspective for the design and development of next-generation Pd-based catalysts.