Density Functional Theory Molecular Dynamics Research Articles

Melting point of iron at high pressure: An assessment of uncertainties and effect of electronic temperature

An accurate calculation of the melting point of iron at various pressures in the Earth's core is important for understanding the core structure, geodynamo, and the Earth's history. Previous studies have assessed the melt line of iron at these extreme conditions using various experimental measurement techniques as well as both ab initio and classic molecular dynamics simulations. However, experimental measurements have uncertainties up to several hundred Kelvin, and inconsistencies remain among simulation results. In this work, we propose an iterative framework that couples density functional theory (DFT) calculations and molecular dynamics simulations performed using an ensemble of interatomic potentials to assess the effect of electronic temperature on the melting point. We systematically validate the potentials by comparing lattice constants and phonon dispersion curves at 0 K and enthalpy differences between liquid and HCP, FCC, BCC phases of iron close to the melt line at 300 GPa with DFT. Our results show that HCP iron melts at 6144 K (at 300 GPa), BCC phase is thermodynamically unstable, and FCC is metastable at this temperature. The melting points of FCC and BCC phases at 300 GPa are 5858 and 5647 K, respectively.

Computational characterization of novel nanostructured materials: A case study of NiCl[formula omitted

A computational approach combining dispersion-corrected density functional theory (DFT) and classical molecular dynamics is employed to characterize the geometrical and thermomechanical properties of a recently proposed 2D transition metal dihalide NiCl2. The characterization is performed using a classical interatomic force field whose parameters are determined and verified through the comparison with the results of DFT calculations. The developed force field is used to study the mechanical response, thermal stability, melting and solidification of a NiCl2 monolayer on the atomistic level of detail. The 2D NiCl2 sheet is found to be thermally stable at temperatures below its melting point of ∼695 K. At higher temperatures, several subsequent structural transformations of NiCl2 are observed, namely a transition into a porous 2D sheet and a 1D nanowire. The MD simulations of NiCl2 cooling show that the molten NiCl2 system solidifies into an amorphous porous 2D structure at T∼450 K. The resulting structure has lower cohesive energy with respect to the initial 2D sheet. The computational methodology presented through the case study of NiCl2 can also be utilized to study the properties of other novel 2D materials, including recently synthesized NiO2, NiS2, and NiSe2.

Understanding Lignin Dissolution with Urea and the Formation of a Lignin Nano-Aggregate: A Multiscale Approach.

This study employs a combined computational and experimental approach to elucidate the mechanisms governing the interaction between lignin and urea, impacting lignin dissolution and subsequent aggregation behavior. Molecular dynamics (MD) simulations reveal how the urea concentration and temperature influence lignin conformation and interactions. Higher urea concentrations and temperatures promote lignin dispersion by disrupting intramolecular interactions and enhancing solvation. Density functional theory (DFT) calculations quantitatively assess the interaction energy between lignin and urea, supporting the findings from MD simulations. Anti-solvent precipitation demonstrates that increasing the urea concentration hinders the self-assembly of lignin nanoclusters. The findings provide valuable insights for optimizing lignin biorefinery processes by tailoring the urea concentration and temperature for efficient extraction and dispersion. Understanding the influence of urea on lignin behavior opens up avenues for designing novel lignin-based materials with tailored properties. This study highlights the potential for the synergetic application of MD simulations and DFT calculations to unravel complex material interactions at the atomic level.

Significant Increase in the Dipole Moment of Graphene on Functionalization: DFT Calculations and Molecular Dynamics Simulations.

The limited solubility of graphene in water can be attributed to the existence of π-π bonds connecting its layers. Functionalized graphene or graphene oxide (GO) is frequently produced in order to overcome the shortcomings of graphene. Using density functional theory (DFT) calculation, functionalized graphene with various combinations of hydroxyl, epoxy, and carboxylic functional groups were investigated computationally. The study focused on the effects of functional group combinations on the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energies, giving information about the chemical reactivity and stability of the molecules under investigation. Global chemical reactivity descriptors, including chemical hardness, softness, electronegativity, chemical potential, and electrophilicity index, were calculated to further elucidate the overall stability and reactivity of the molecules. The results demonstrated that the introduction of oxygen-containing functional groups on graphene significantly influenced its electronic properties, leading to variations in the chemical reactivity and stability. Molecular electrostatic potential (MEP) maps highlighted the susceptibility of specific regions to electrophilic and nucleophilic attacks. The flexibility and stability of functionalized graphene through root mean square fluctuation (RMSF) and root mean square deviation (RMSD) analyses indicate the stability of functionalized graphene in water. This comprehensive computational investigation provides valuable insights into the design and understanding of functionalized graphene for potential applications in drug delivery.

Water-Hydrocarbon Interactions in Anionic Pyrene Monohydrate.

Interactions between water and polycyclic aromatic hydrocarbons are essential in many aspects of chemistry, from interstellar and atmospheric processes to interfacial hydrophobicity and wetting phenomena. Despite their growing importance, the intermolecular potentials of the water-hydrocarbon interactions are underdeveloped compared to the water-water potentials, and there are similarly few experimental probes that are sensitive to the details of the water-hydrocarbon potential. We present a combined experimental and computational study of anionic pyrene monohydrate, one of the simplest water/hydrocarbon clusters. The action spectrum in the OH region of the mass-selected cluster ion provides a rigorous benchmark for intermolecular potentials and computational methodologies. We identify missing intermolecular interactions and shortcomings in conventional dynamics calculations by comparing experimental data to density functional theory and classical molecular dynamics calculations. Kinetic trapping is prevalent, even for one water molecule and one pyrene molecule, leading to slow equilibration in conventional molecular dynamics calculations, even on nanosecond time scales and at low temperatures (50 K). At constant energy, temperature fluctuations for the pair of molecules are substantial. Immersing the system in a bath of soft spheres and employing parallel tempering alleviates kinetic trapping and dampens temperature fluctuations, bringing the system closer to the thermodynamic limit. With such augmented sampling, a simple, flexible water model reproduces the line width and the asymmetric broadening of the symmetric OH stretching mode, which we assign to spectral diffusion. In the OH stretching region, dynamics calculations predict a more intense antisymmetric peak than experiments observe but do not predict the bimodal split symmetric peak that the experiments show. Our work suggests that electronic polarization, missing in the empirical force field, is responsible for the first discrepancy and that quantum nuclear effects, captured neither in density functional theory nor in classical dynamics, may be responsible for the second.

Magnetism and finite-temperature effects in UZr2: A density functional theory analysis

The structure and the thermophysical properties of δ-UZr2 are investigated using 0 K density functional theory and ab initio molecular dynamics (AIMD). Modeling the true paramagnetic state of this intermetallic compound has been challenging using first-principles calculations. For the first time, we find that the generalized gradient approximation method without applying an on-site Coulomb interaction term (Hubbard U) can result in a ground state that is antiferromagnetic (AFM). We believe that this weak AFM ground state is the closest to the real paramagnetic state. We found that structure optimization at finite temperatures using AIMD is necessary to achieve this ground state instead of the non-magnetic and ferromagnetic states previously reported in the literature. Our findings indicate that applying the Hubbard U on uranium f-orbitals in this metallic system is unnecessary and not recommended, as it leads to a large overestimation of the volume and introduces an unphysical strong spin polarization. Our approach results in atomic volume, thermal expansion, and heat capacities that have strong agreement with experiments.

Corrosion inhibition performance of new Schiff base cyclohexanamine derivatives on C-steel in 1 M HCl solution: Electrochemical, chemical, surface and computational explorations

Iron has many advantages, which makes it a material of great importance on the industrial level, but it is quickly affected by surrounding environmental factors that cause its corrosion. In this context, two new Schiff base cyclohexanamine derivatives (CSBs) were synthesized, characterized, and screened as corrosion inhibitors of C-steel in a 1 M hydrochloric acid solution. Specifically, they are (Z)-N-cyclohexyl-1-phenylethan-1-imine (CSB-1) and (E)-N′-cyclohexyl-N-hydroxybenzimidamide (CSB-2). 1H NMR was used to determine the structures of the new CSB molecules. The inhibition efficacies (%IE) were evaluated by combining theoretical, physical, chemical, electrochemical, and spectroscopic methods. The results confirmed that CSBs were mixed-type inhibitors and that the IE depended linearly on their concentration. The adsorption of these molecules on the metal surface is key to this role. Kinetic and thermodynamic studies indicated that they are physically adsorbed and subject the Langmuir adsorption isotherm. Using 0.001 M of inhibitor, the maximum %IEs achieved were 91.1 % for CSB-1 and 94.4 % for CSB-2, respectively, which confirms tatehat they are promising inhibitors. Surface analysis via atomic force microscopy (AFM) confirmed that the C-steel was covered in a protective layer. Several thermodynamic and kinetic parameters were calculated. DFT and Mullikan charge calculations and molecular dynamics (MD) simulations were applied to predict the effectiveness and interactions of new CSBs on the steel surface as well. Theoretical expectations correspond to the practical.

Deciphering the Molecular Mechanisms of Reactive Metabolite Formation in the Mechanism-Based Inactivation of Cytochrome p450 1B1 by 8-Methoxypsoralen and Assessing the Driving Effect of phe268.

This study provides a comprehensive computational exploration of the inhibitory activity and metabolic pathways of 8-methoxypsoralen (8-MP), a furocoumarin derivative used for treating various skin disorders, on cytochrome P450 (P450). Employing quantum chemical DFT calculations, molecular docking, and molecular dynamics (MD) simulations analyses, the biotransformation mechanisms and the active site binding profile of 8-MP in CYP1B1 were investigated. Three plausible inactivation mechanisms were minutely scrutinized. Further analysis explored the formation of reactive metabolites in subsequent P450 metabolic processes, including covalent adduct formation through nucleophilic addition to the epoxide, 8-MP epoxide hydrolysis, and non-CYP-catalyzed epoxide ring opening. Special attention was paid to the catalytic effect of residue Phe268 on the mechanism-based inactivation (MBI) of P450 by 8-MP. Energetic profiles and facilitating conditions revealed a slight preference for the C4'=C5' epoxidation pathway, while recognizing a potential kinetic competition with the 8-OMe demethylation pathway due to comparable energy demands. The formation of covalent adducts via nucleophilic addition, particularly by phenylalanine, and the generation of potentially harmful reactive metabolites through autocatalyzed ring cleavage are likely to contribute significantly to P450 metabolism of 8-MP. Our findings highlight the key role of Phe268 in retaining 8-MP within the active site of CYP1B1, thereby facilitating initial oxygen addition transition states. This research offers crucial molecular-level insights that may guide the early stages of drug discovery and risk assessment related to the use of 8-MP.

Impact of Atomic Defects on Ceria Surfaces on Chemical Mechanical Polishing of Silica Glass Surfaces.

This study investigates the impact of atomic defects, such as oxygen vacancies and Ce3+ ions, on cerium oxide (ceria) surfaces during chemical mechanical polishing (CMP) for silica glass finishing. Using density functional theory (DFT) and reactive molecular dynamics simulations, the interaction of orthosilicic molecules and silica glass with dry and wet ceria surfaces is explored. Defects alter the surface reactivity, leading to the dissociation of orthosilicic acid on oxygen vacancies, forming a strong Si-O-Ce bond. Hydroxylated surfaces exhibit easier oxygen vacancy formation and thermodynamically favored substitution of hydroxyl groups with orthosilicic acid. A new ReaxFF library for silica/ceria interfaces with defects is validated using DFT outcomes. Reactive MD simulations demonstrate that ceria surfaces with 30% Ce3+ ions on (111) planes exhibit higher polishing efficiency, attributed to increased Si-O-Ce bond formation. The simultaneous presence of oxygen vacancies and various acidic and basic sites on ceria surfaces enhances the polishing efficiency, involving acid-base reactions with silica. Defective surfaces show superior efficiency by removing silicate chains, contrasting with nondefective surfaces removing isolated orthosilicate units. This study provides insights into optimizing CMP processes for high-precision glass industry surface finishing.

Alleviating zinc dendrite growth by versatile sodium carboxymethyl cellulose electrolyte additive to boost long-life aqueous Zn ion capacitors

Zn ion capacitors (ZICs) have become a strong candidate for energy storage equipment because the advantages of environment friendly, high safety, low cost. However, the Zn anode suffers from severe dendrite growth and irreversible side reactions, resulting in a short cycle life of ZICs. In this work, a green and low-cost sodium carboxymethyl cellulose (CMC-Na) is used as an additive in ZnSO4 electrolyte. The density functional theory calculations and molecular dynamics simulations demonstrate that CMC-Na can effectively optimize the electrolyte environment and regulate the electrode-electrolyte interface. Among them, Na+ has a lower redox site compared to Zn2+, Na+ can be reduced preferentially to Zn2+, the formation of the electrostatic protection layer can inhibit the formation of differential electric field and promote the uniform distribution of the electric field, which is conducive to the homogenization of the nucleation sites of the Zn deposition layer. The organic molecules contain abundant hydrophilic groups (OH, COO−), which can effectively optimize the structure of Zn2+ solvation sheath by destroying the hydrogen bonding network in the environment of ZnSO4 electrolyte, thus reducing the rate of side reactions and the random growth of dendrites will be suppressed. And the Zn//Zn cells with ZnSO4+CMC-Na(0.13) electrolyte enable to perform a stable cycle over 1600 h (at 4 mA cm−2 with a capacity of 1 mAh cm−2), which is vastly superior that of without additive (only 70 h). The results confirm that the import of CMC-Na additive into the ZnSO4 electrolyte can effectively prevent side reaction and achieve uniform deposition of Zn dendrites. The low-cost electrolyte additive provides an innovative strategy or the protection of Zn metal electrode in aqueous electrochemical energy storage devices.

Unveiling the oxidation mechanism of CrTaTiMo refractory medium-entropy alloys: A synergy of density functional theory and ab initio molecular dynamics

The demand for advanced materials capable of withstanding extreme high-temperature conditions has led to the development of novel High-Entropy Alloys (HEAs). Recent works indicate that forming a CrTaO4 protection layer gives HEAs excellent long-term oxidation resistance. In this study, the high-temperature oxidation resistance properties of CrTaTiMo Refractory Medium-Entropy Alloys (RMEAs) were assessed by Density Functional Theory (DFT) and ab initio Molecular Dynamics (AIMD). Through the oxygen adsorption and diffusion calculations, we demonstrated the preferential oxygen adsorption sequence on the surface of the RMEA as Ti, Ta, Cr, and Mo. Furthermore, our analysis identified the sites featuring Ta as subsurface atoms were the weakest locations for oxygen atom diffusion. The dynamic oxidation mechanism of oxygen molecules on CrTaTiMo RMEA was investigated by AIMD simulations. The results confirmed that the adsorption and dissociation of O2 molecules on the alloy surface. Additionally, the diffusion of the O atom took place at temperatures greater than 873 K and confirmed the O-attracting feature of Ta atoms. Moreover, electronic structure calculations confirmed the bonding of oxygen atoms with those four metal elements. This study could serve as a valuable reference for the strategic development of the CrTaTiMo-based RMEAs or RHEAs for high-temperature, long-term oxidation resistance applications.

Effect of tabebuia heterophylla plant leaves extract on corrosion protection of low carbon steel in 1M HCl medium: Electrochemical, quantum chemical and surface characterization studies.

In the current study the chemical constituents of Tabebuia heterophylla plant leaves extract (THLE) evaluated as corrosion inhibitor for low carbon steel (LCS) in 1 M HCl. The major component present in plant extract was Hexadecanoic acid 2-hydroxy-1-(hydroxymethyl) ethyl ester confirmed by Gas Chromatography with Mass spectroscopic (GC-MS) analysis. Electrochemical impedance spectroscopy (EIS), potentiodynamic polarisation (PDP) and weight loss measurements were used to evaluate the THLE ability to protect low-carbon steel surface against corrosion in 1M HCl medium. The maximum inhibition efficiency reported as 95.45%, 93.99% and 94.79% by weight loss measurements, EIS and PDP methods respectively. In the prolongation of the work, the entropy of adsorption (Δ Sa*), enthalpy of adsorption (Δ Ha*), Gibbs free energy of adsorption (Δ Ga*), and activation energy (Ea) of the reaction were calculated. In absence of inhibitor, the Ea value was found to be minimum 49.38 kJ/mol whereas for optimum concentration of THLE it was found to be 77.2 kJ/mol implies more energy is required to undergo corrosion. The surface morphological observation from Scanning Electron Microscope (SEM), Atomic Force Microscopic (AFM) and Contact angle explored the effective adsorption of THLE. AFM values revealed that average surface roughness (Ra) value of LCS is high (188.08), where as in the presence of THLE, Ra values significantly reduced to minimum value of 37.226. Further chemical interactions between THLE and the low-carbon steel surface as well as inhibitory mechanism were further elucidated by theoretical simulations such as Density Functional Theory (DFT) calculations and Molecular dynamics (MD) simulations.

Integrating theory with the nanoreactor concept to synthesize hollow carbon sphere‐encapsulated PtNi alloys for enhanced H2 generation

AbstractThe rational design of efficient bimetallic nanoparticle (NP) catalysts is challenging due to the lack of theoretical understanding of active components and insights into the mechanisms of a specific reaction. Here, we report the rational design of nanoreactors comprising hollow carbon sphere‐confined PtNi bimetallic NPs (PtNi@HCS) as highly efficient catalysts for hydrogen generation via ammonia borane hydrolysis in water. Using both density functional theory calculations and molecular dynamics simulations, the effects of an active PtNi combination and the critical synergistic role of a hollow carbon shell on the molecule diffusion adsorption behaviors are explored. Kinetic isotope effects and theoretical calculations allow the clarification of the mechanism, with oxidative addition of an O–H bond of water to the catalyst surface being the rate‐determining step. The remarkable catalytic activity of the PtNi@HCS nanoreactor was also utilized for successful tandem catalytic hydrogenation reactions, using in situ‐generated H2 from ammonia borane with high efficiency. The concerted design, theoretical calculations, and experimental work presented here shed light on the rational elaboration of efficient nanocatalysts and contribute to the establishment of a circular carbon economy using green hydrogen.

Running Wild through Dirhodium Tetracarboxylate-Catalyzed Combined CH(C)-Functionalization/Cope Rearrangement Landscapes: Does Post-Transition-State Dynamic Mismatching Influence Product Distributions?

A special type of C-H functionalization can be achieved through C-H insertion combined with Cope rearrangement (CHCR) in the presence of dirhodium catalysts. This type of reaction was studied using density functional theory and ab initio molecular dynamics simulations, the results of which pointed to the dynamic origins of low yields observed in some experiments. These studies not only reveal intimate details of the complex reaction network underpinning CHCR reactions but also further cement the generality of the importance of nonstatistical dynamic effects in controlling Rh2L4-promoted reactions.

Toward stabilization of formamidinium lead iodide perovskites by defect control and composition engineering

Phase instability poses a serious challenge to the commercialization of formamidinium lead iodide (FAPbI3)-based solar cells and optoelectronic devices. Here, we combine density functional theory and machine learning molecular dynamics simulations, to investigate the mechanism driving the undesired α-δ phase transition of FAPbI3. Prevalent iodine vacancies and interstitials can significantly expedite the structural transition kinetics by inducing robust covalency during transition states. Extrinsically, the detrimental roles of atmospheric moisture and oxygen in degrading the FAPbI3 perovskite phase are also rationalized. Significantly, we discover the compositional design principles by categorizing that A-site engineering primarily governs thermodynamics, whereas B-site doping can effectively manipulate the kinetics of the phase transition in FAPbI3, highlighting lanthanide ions as promising B-site substitutes. A-B mixed doping emerges as an efficient strategy to synergistically stabilize α-FAPbI3, as experimentally demonstrated by substantially higher initial optoelectronic characteristics and significantly enhanced phase stability in Cs-Eu doped FAPbI3 as compared to its Cs-doped counterpart. This study provides scientific guidance for the design and optimization of long-term stable FAPbI3-based solar cells and other optoelectronic devices through defect control and synergetic composition engineering.

Binding of Carbon Monoxide to Hemoglobin in an Oxygen Environment: Force Field Development for Molecular Dynamics.

Carbon monoxide (CO) is a byproduct of the incomplete combustion of carbon-based fuels, such as wood, coal, gasoline, or natural gas. As incomplete combustion in a fire accident or in an engine, massively produced CO leads to a serious life threat because CO competes with oxygen (O2) binding to hemoglobin and makes people suffer from hypoxia. Although there is hyperbaric O2 therapy for patients with CO poisoning, the nanoscale mechanism of CO dissociation in the O2-rich environment is not completely understood. In this study, we construct the classical force field parameters compatible with the CHARMM for simulating the coordination interactions between hemoglobin, CO, and O2, and use the force field to reveal the impact of O2 on the binding strength between hemoglobin and CO. Density functional theory and Car-Parrinello molecular dynamics simulations are used to obtain the bond energy and equilibrium geometry, and we used machine learning enabled via a feedforward neural network model to obtain the classical force field parameters. We used steered molecular dynamics simulations with a force field to characterize the mechanical strength of the hemoglobin-CO bond before rupture under different simulated O2-rich environments. The results show that as O2 approaches the Fe2+ of heme at a distance smaller than ∼2.8 Å, the coordination bond between CO and Fe2+ is reduced to 50% bond strength in terms of the peak force observed in the rupture process. This weakening effect is also shown by the free energy landscape measured by our metadynamics simulation. Our work suggests that the O2-rich environment around the hemoglobin-CO bond effectively weakens the bonding, so that designing of O2 delivery vector to the site is helpful for alleviating CO binding, which may shed light on de novo drug design for CO poisoning.

Solvation enhanced long-range proton transfer in aqueous phase for glycolaldehyde hydrogenation over Ru/C catalyst.

The catalytic hydrogenation of biomass-derived chemicals is essential in chemical industry due to the growing demand for sustainable and renewable energy sources. In this study, we present a comprehensive theoretical investigation regarding the hydrogenation of glycolaldehyde to ethylene glycol over a Ru/C catalyst by employing density functional theory and abinitio molecular dynamics simulations. With inclusion of explicit solvation, we have demonstrated that the glycolaldehyde hydrogenation is significantly improved due to the fast proton transfer through the hydrogen bond network. The enhanced activity could be attributed to the participation of the solvent water as the hydrogen source and the highly positively charged state of a Ru cluster in an aqueous phase, which are critical for the activation of aldehyde groups and proton-assisted hydrogenation. Overall, our findings provide valuable insights into glycolaldehyde hydrogenation over Ru/C catalysts in the aqueous phase, highlighting the importance of solvation effects in the biomass conversion.

Unveiling the enhancement mechanism of Fe ion for muscovite flotation: Adjustment of surface potential and agent dispersion

Metal ions have been used to improve the flotation recovery of muscovite, while the enhancement mechanism is still unclear. In this paper, density functional theory (DFT) calculations and molecular dynamics (MD) simulations were employed to investigate the adsorption structure of sodium oleate (NaOL) on muscovite surface, and the diffusivity and foaming of NaOL in the pulp system, in presence of Fe3+ at different pH range. DFT calculation results suggested that the adsorption of iron ions, include FeOH2+ and Fe(OH)2+, could change the surface charge from negative to positive, thus enhancing binding performance for OL−. Moreover, MD simulations indicated that the distribution of iron ions in aqueous solution can significantly affect the dispersion of sodium oleate molecules. Specifically, FeOH2+ may lead to the complexation of oleate ions and result in the agglomeration, which is not conducive to its dispersion in solution. However, Fe(OH)2+ can significantly inhibit the aggregation of OL− molecules, and accelerate the dispersion of OL− in flotation pulp. This work reveals atomic-level mechanism of Fe ion on the dispersion and adsorption of sodium oleate in pulp, which is helpful to the understanding of minerals flotation behavior in presence of metal ions.

Size tuning of Pt nanoparticles on ZrO2: Optimizing catalytic performance for hydrogen evolution and water-splitting reactions - A DFT study

In heterogeneous catalysis, determining the optimal metal particle size is challenging due to the intricate relationship between particle size, electronic structure, and activity. Here, we investigate the size-dependent activity of Pt nanoparticle (PtNP)-based ZrO2 catalyst for hydrogen evolution reaction (HER) and water-splitting reaction (WSR) using density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations. By analyzing different Pt nanoparticle sizes (Pt4, Pt7, Pt11, P15, Pt19, and Pt25) supported on ZrO2, we determined their optimized geometries, and electronic structures, and calculated the hydrogen adsorption energies (ΔGH) for HER and activation energies barrier (Δ‡G) for WSR. The calculated results demonstrate that Pt11 is the optimal size for HER, exhibiting the lowest ΔGH (−0.066 eV), while Pt15 shows the lowest Δ‡G (0.24 eV) for WSR. The density of states (DOS) shows that the occupied Pt states fill the gap of ZrO2 (3.72 eV), significantly reducing the band gap (Eg) of the PtNP/ZrO2 composites. The most favorable configuration of the PtNP on ZrO2 for HER and WSR is determined to be a three-Pt-layer structure with rooflike edges which corresponds to a nanoparticle size of ∼0.70–1.55 nm for experiments. These findings can be regarded as an effort toward the design and optimization of metal-based oxide catalysts for renewable energy applications.

Machine Learning for Polaritonic Chemistry: Accessing Chemical Kinetics.

Altering chemical reactivity and material structure in confined optical environments is on the rise, and yet, a conclusive understanding of the microscopic mechanisms remains elusive. This originates mostly from the fact that accurately predicting vibrational and reactive dynamics for soluted ensembles of realistic molecules is no small endeavor, and adding (collective) strong light-matter interaction does not simplify matters. Here, we establish a framework based on a combination of machine learning (ML) models, trained using density-functional theory calculations and molecular dynamics to accelerate such simulations. We then apply this approach to evaluate strong coupling, changes in reaction rate constant, and their influence on enthalpy and entropy for the deprotection reaction of 1-phenyl-2-trimethylsilylacetylene, which has been studied previously both experimentally and using ab initio simulations. While we find qualitative agreement with critical experimental observations, especially with regard to the changes in kinetics, we also find differences in comparison with previous theoretical predictions. The features for which the ML-accelerated and ab initio simulations agree show the experimentally estimated kinetic behavior. Conflicting features indicate that a contribution of dynamic electronic polarization to the reaction process is more relevant than currently believed. Our work demonstrates the practical use of ML for polaritonic chemistry, discusses limitations of common approximations, and paves the way for a more holistic description of polaritonic chemistry.