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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Effect of CO 2 on the water slip flow at silica surfaces for nanometer slit pores of talc

In our previous study, Molecular Dynamics (MD) simulated water flow with no dissolved gas in nanometer slit pores of the hydrophobic talc surfaces revealed a slip length of about 0.5 nm, which is close to the size of “water exclusion zone” but much less than experimental slip length. Atomic Force Microscopy (AFM) imaging confirmed the presence of pancake shape nanobubbles at the hydrophobic talc (001) surface (size from tens to hundreds of nanometers). The effect of CO 2 on water slip flow in talc nanopores is reported to reveal the importance of dissolved gas for confined fluid flow. MD simulated 7 nm CO 2 nanobubbles were found to attach and spread at the talc (001) surface, consistent with the AFM observation. Simulated CO 2 saturated water flow in the slit pores of talc (001) surfaces predicted the generation of CO 2 nanobubbles at the end of the slit pore, due to the stabilization of a CO 2 film at the talc (001) surfaces and a water barrier at the edge surfaces of talc. A “critical thickness” of about 1.5 nm was found for CO 2 nanobubbles to be stabilized at the end of the talc (001) surface. With 1.5 nm CO 2 nanobubbles at the talc (001) surface of a 6 nm slit pore, a water slip length of 1.8 nm was determined. Furthermore, the nanometer slit pore simulations with dissolved CO 2 in water revealed an increased slip length. It is expected that an increased slip length value would be found with an increased CO 2 film thickness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Understanding the phase transformation mechanisms that affect the dynamic response of Fe-based microstructures at the atomic scales

Large-scale molecular dynamics (MD) simulations were carried out to investigate the shock-induced evolution of microstructure in Fe-based systems comprising single-crystal and layered Cu/Fe alloys with a distribution of interfaces. The shock compression of pure single-crystal Fe oriented along [110] above a threshold pressure results in a BCC (α)→HCP (ε) phase transformation behavior that generates a distribution of ε phase variants in the phase transformed region of the microstructure behind the shock front. The propagation of the release wave through a phase transformed ε phase causes a reverse ε→α phase transformation and renders a distribution of twins for the [110] oriented Fe that serve as void nucleation sites during spall failure. The simulations reveal that the α→ε→α transformation-induced twinning for shock loading along the [110] direction is due to a dominant ε phase variant formed during compression that rotates on the arrival of the release wave followed by a reverse phase transformation to twins in the α phase. The modifications in the evolution of the ε phase variants and twins in Fe behavior are also studied for Cu–Fe layered microstructures due to the shock wave interactions with the Cu/Fe interfaces using a newly constructed Cu–Fe alloy potential. Here, the MD simulations suggest that interfaces affect the observed variants during shock compression and, hence, distributions of twins during shock release that affects the void nucleation stresses in the Fe phase of Cu/Fe microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Molecular Level Understanding of Polyethylene Terephthalate (PET) Depolymerization in Base/Alcohol Hybrid Systems

Polyethylene terephthalate (PET) depolymerization in base/alcohol hybrid systems represents a promising low-energy approach for chemically recycling PET waste into valuable monomers. This study investigates the mechanistic pathways of PET depolymerization in NaOH/alcohol solutions, emphasizing the competing roles of hydroxide and alkoxide species. Utilizing a combination of experimental techniques, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations, we explore how factors such as base concentration, alcohol chain length, and pKa values of alcohols influence PET depolymerization efficiency and pathways. Our findings indicate that alkoxide ions (RO⁻) exhibit notably higher reactivity than hydroxide ions (HO⁻), favoring an alcoholysis pathway in the base/alcohol hybrid system. Experimental results across a series of C1 to C5 alcohols show that longer-chain alcohols, particularly 1-butanol, achieve higher PET conversion, although this does not align solely with simple nucleophilicity trends of alkoxides. While DFT calculations reveal comparable activation energies for various alkoxides in PET depolymerization, MD simulations underscore the significant role of alcohol chain length, with longer-chain alcohols forming more stable or frequent interactions with PET. Additionally, the alkoxide concentration, influenced by the alcohol’s pK a , directly impacts PET conversion. These suggest that PET depolymerization is governed by a balance between alkoxide concentration and alkoxide-PET interactions, rather than activation energies or nucleophilicity alone. From a practical perspective, incorporating long-chain alcohols as cosolvents may enhance process efficiency but increases raw material costs by approximately 30%. However, long-chain alcohols present a safer and more sustainable alternative to hazardous cosolvents such as dichloromethane. This work offers a molecular-level understanding of PET depolymerization in base/alcohol systems and provides insights into optimizing these systems for more efficient and sustainable PET recycling processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Atomic Edge-Guided Polyethylene Crystallization on Monolayer Two-Dimensional Materials

In this report we combine an advanced synthesis of two-dimensional (2D) materials (MoSe 2 ) having well-defined atomic edge configurations with ab initio and atomistic molecular dynamics (MD) simulations to study how atomic edges interact with polyethylene (HDPE) chains in a dilute solution assembly process. Our results reveal that Mo-terminated zigzag (Mo-ZZ) edges act as preferred nucleation sites and strongly interact with HDPE chains. The HDPE chains align in parallel with the Mo-ZZ edges and form arrays of lamellae that are perpendicular to the edges. Interestingly, atomic edge configurations are observed to dramatically change such interactions. The crystallization discrepancy at different edges was demonstrated on the same piece of MoSe 2 with different types of edges. The ab initio and MD simulations between n-alkane (n = 5 and 25), a segment of HDPE, and MoSe 2 suggest that the atomic structures of MoSe 2 can affect their interactions with n-alkane chains. Following the Mo-ZZ edge preferred nucleation principle, controlled long-range alignment of HDPE lamellae can be realized by creating multilayer MoSe 2 with parallel atomic steps. This research opens a pathway toward an atomic level understanding of polymer–2D nanomaterial interactions. It also bridges the gap between atomic-level and long-range mesoscopic structures and introduces a novel strategy for long-range structural control.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Application-specific machine-learned interatomic potentials: exploring the trade-off between DFT convergence, MLIP expressivity, and computational cost

Machine-learned interatomic potentials (MLIPs) are revolutionizing computational materials science and chemistry by offering an efficient alternative to ab initio molecular dynamics (MD) simulations. However, fitting high-quality MLIPs remains a challenging, time-consuming, and computationally intensive task where numerous trade-offs have to be considered, e.g., How much and what kind of atomic configurations should be included in the training set? Which level of ab initio convergence should be used to generate the training set? Which loss function should be used for fitting the MLIP? Which machine learning architecture should be used to train the MLIP? The answers to these questions significantly impact both the computational cost of MLIP training and the accuracy and computational cost of subsequent MLIP MD simulations. In this study, we use a configurationally diverse beryllium dataset and quadratic spectral neighbor analysis potential. We demonstrate that joint optimization of energy versus force weights, training set selection strategies, and convergence settings of the ab initio reference simulations, as well as model complexity can lead to a significant reduction in the overall computational cost associated with training and evaluating MLIPs. This opens the door to computationally efficient generation of high-quality MLIPs for a range of applications which demand different accuracy versus training and evaluation cost trade-offs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Development of a deep potential model for F and CF 2 etching of Si and SiO 2

An understanding of plasma-surface interactions at increasingly smaller scales is invaluable for the development of novel technologies and processing techniques. Molecular dynamics (MD) simulations can provide insights into atomic-scale interactions, though they are restricted by the availability of interatomic potentials. Machine learning methods, such as Deep Potential Molecular Dynamics (DeepMD), provide a systematic framework for the development of accurate and flexible ab initio-based models. In this work, we develop DeepMD models for the ion-enhanced etching of Si and SiO 2 by F and CF 2 radicals. We employ an active learning process to expand the data set on which the model is trained and demonstrate its effect on the model accuracy. The DeepMD results are compared to data from classical MD simulations and experiments. Physical sputtering yields of SiO 2 by Ar + ions show good agreement with previous simulation results using conventional interatomic potentials, though the predicted depth profiles are different. Etching yields are calculated as a function of ion energy and neutral to ion flux ratio for the Ar + ion-enhanced etching of SiO 2 and Si by F atoms, as well as for etching of SiO 2 by CF 2 radicals, showing reasonable agreement with experimental data. Finally, an ion-enhanced surface kinetic model is fitted to the DeepMD etch yields, and the fitted parameters are compared to quantities computed directly from DeepMD simulations. This study illustrates how molecular dynamics simulations using machine learning potentials can provide an accurate model of etching processes relevant to device manufacturing.

Kounis-Melas, Andreas [Princeton Univ., NJ (United↗
DOE OSTI2025

Efficient machine learning interatomic potentials robust for liquid and multiple solid polymorphs of NaF and KF

Achieving atomic-level understanding of crystallization of molten salts is of importance to a wide range of technological applications. Recent work [Fan et al., Proc. Natl. Acad. Sci. USA 122, e2425702122 (2025)] revealed that crystal nucleation in molten LiF salt is a multistage process according to the molecular-dynamics (MD) simulations based on an atomic cluster expansion (ACE) machine-learning interatomic potential (MLIP). In order to understand the influence of increasing cation size on nucleation pathways and nucleation rates of molten fluoride salts, here we develop two new ACE MLIPs for NaF and KF. The two ACE MLIPs feature DFT-SCAN-level accuracy for liquid and multiple solid polymorphs over a wide temperature (0–2000 K) and pressure (0–100 GPa) range, and also reproduce well a number of experimental data for solid and liquid equilibrium properties. The efficiency of the two ACE MLIPs enable million-atom-scale or microsecond-scale MD simulations. The two general-purpose ACE MLIPs are expected to be useful for atomistic simulations for different purposes, in addition to studying crystallization of molten NaF and KF salts.

Crystal melting↗
DOE OSTI2022

Computational Insights into Malononitrile-Based Carbanions for CO 2 Capture

Although anionic N and O sites have been widely used in chemisorption of CO 2 , carbanions are much less explored for CO 2 capture. Here, in this study, we employ ab initio calculations and quantum mechanical/molecular mechanical (QM/MM) molecular dynamics (MD) simulations to examine the interaction between CO 2 and the malononitrile carbanion, [CH(CN) 2 ] – . We have explored the potential energy surface of CO 2 binding by scanning the C–C distance between CO 2 and the central C site of the carbanion. We find that CO 2 prefers to bind to the nitrile group physically rather than to form a C–C bond via the carboxylation reaction at the sp 2 C site. Moreover, the two –CN groups can attract two CO 2 molecules at equal strength. The presence of an alkali metal ion enhances both physical and chemical interactions of CO 2 with the malononitrile carbanion. QM/MM MD simulations further confirm the preference of physical interaction in the condensed ionic liquid phase with a phosphonium cation. Our findings suggest that ionic liquids based on the malononitrile carbanion may have a high CO 2 solubility for carbon capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The impact of physiologically relevant temperatures on physical properties of thylakoid membranes: a molecular dynamics study

Thylakoid membranes are energy-converting membranes with a unique lipid composition. Though the membranes are primarily composed of proteins, their photosynthetic function is strongly influenced by the lipid constituents. Here we characterize, with molecular dynamics (MD) simulations, lipid bilayers with compositions representative of plant thylakoid membranes. We determine, in a wide range of temperatures, the physical parameters of the model membranes which are relevant for the photosynthetic function. We found a marked impact of temperature on membrane permeability due to a combination of increased compressibility and curvature of the membrane at elevated temperatures. With increasing temperatures, we observed increasingly smeared transmembrane density profiles of the membrane forming lipid headgroups predicting increased membrane flexibility. The diffusion coefficient of the lipids increased with temperature without apparent specificity for lipid species. Instead of a comprehensive experimental dataset in the relevant temperature range, we quantitatively compared and validated our MD results with MD simulations on a dipalmitoylphosphatidylcholine model system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Theory of Cation Solvation in the Helmholtz Layer of Li-Ion Battery Electrolytes

The solvation environments of Li + in conventional nonaqueous battery electrolytes, such as LiPF 6 in mixtures of ethylene carbaronate (EC) and ethyl methyl carbonate (EMC), are often used to rationalize transport properties and solid electrolyte interphase (SEI) formation. Solvation environments in the compact electrical double layer (EDL) next to the electrode, also known as the Helmholtz layer, determine (partially) what species can react to form the SEI, with bulk solvation environments often being used as a proxy. Here, we develop and test a theory of cation solvation in the Helmholtz layer of nonaqueous Li-ion battery electrolytes. First, we validate the theory against bulk and diffuse EDL atomistic molecular dynamics (MD) simulations of LiPF 6 EC/EMC mixtures as a function of surface charge, where we find the theory can qualitatively capture the solvation environments. Next, we turn to the Helmholtz layer, where we find the main effect of the solvation structures next to the electrode is an apparent reduction in the number of binding sites between Li + and the solvents, again where we find reasonable agreement with our developed theory. Finally, by solving a simplified version of the theory, we find that the probability of Li + binding to each solvent remains equal to the bulk probability, suggesting that the bulk solvation environments are a reasonable place to start when understanding battery electrolytes. Our developed formalism can be parametrized from bulk MD simulations and used to predict the solvation environments in the Helmholtz layer through reducing the number of available coordination sites, which can be used to determine what could react and form the SEI.

Helmholtz↗
DOE OSTI2023

Disentangling the evolution of electrons and holes in photoexcited ZnO nanoparticles

The evolution of charge carriers in photoexcited room temperature ZnO nanoparticles in solution is investigated using ultrafast ultraviolet photoluminescence spectroscopy, ultrafast Zn K-edge absorption spectroscopy, and ab initio molecular dynamics (MD) simulations. The photoluminescence is excited at 4.66 eV, well above the band edge, and shows that electron cooling in the conduction band and exciton formation occur in <500 fs, in excellent agreement with theoretical predictions. The x-ray absorption measurements, obtained upon excitation close to the band edge at 3.49 eV, are sensitive to the migration and trapping of holes. They reveal that the 2 ps transient largely reproduces the previously reported transient obtained at 100 ps time delay in synchrotron studies. In addition, the x-ray absorption signal is found to rise in ∼1.4 ps, which we attribute to the diffusion of holes through the lattice prior to their trapping at singly charged oxygen vacancies. Indeed, the MD simulations show that impulsive trapping of holes induces an ultrafast expansion of the cage of Zn atoms in <200 fs, followed by an oscillatory response at a frequency of ∼100 cm−1, which corresponds to a phonon mode of the system involving the Zn sub-lattice.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Mapping the structural–mechanical landscape of amorphous carbon with ReaxFF molecular dynamics

We use ReaxFF molecular dynamics (MD) to investigate the relationship between structural and mechanical properties in bulk and nanostructured amorphous carbon (a-C). The liquid-quench MD method is used to generate isotropic bulk samples with mass densities ranging from 0.96 to 3.29 g/cm3. Structural analysis identifies two types of structures with distinct short- and medium-range order: lower-density sp2-dominated a-C, which is characterized by a bimodal ring-size distribution, and higher-density sp3-dominated tetrahedral amorphous carbon (ta-C), exhibiting a unimodal ring-size distribution. Stress–strain MD simulations and analysis reveal how an atomistic structure impacts elastic properties and post-yield atomic rearrangements. All stretched structures demonstrate elastic isotropy and plasticity driven by a ring-size expansion mechanism reflected in changes in ring statistics. The plastic region is substantially larger in ta-C than in a-C due to the post-yield shift from sp3 to sp2 C dominant bonding. In both a-C and ta-C, ultimate failure occurs when a reactive crack, traversed by long sp chains, forms and propagates predominantly perpendicular to the direction of the applied strain. Oxygen infiltration into the fractured region significantly reduces stress resistance, primarily through the early rupture of long sp chains. MD simulations and analysis are extended to a-C slabs, a-C nanotubes, and partially a-C nanotubes. The latter nanostructure highlights the differences between the elastically isotropic a-C walls, which develop circumferential cracking, and the crystalline walls, which tear along crystallographic directions. These results provide a strong foundation for further computational characterization of a-C materials.

Dernov, A. (ORCID:0009000004220973)↗
DOE OSTI2021

Atomistic observation on diffusion-mediated friction between single-asperity contacts

Super-lubricity, a sliding regime in which friction almost vanishes, has been well-documented with the advent of atomic force microscopy (AFM) and molecular dynamics (MD) simulation due to its enormous implications for manufacturing micro-/nano-electromechanical systems (MEMS/NEMS). Nevertheless, the atomistic mechanisms for super-lubricious behaviors are still elusive, primarily due to a lack of direct observation of interface at atomic resolution during frictional process. Here by using in situ high-resolution transmission electron microscopy (HRTEM) coupled with AFM, we report diffusion-mediated formation of a loosely-packed interfacial layer between two metallic asperities at infinitesimal normal forces, which is responsible for the sliding regime, super-lubricity exhibiting ultra-low friction forces and continuous sliding. By contrast, the loosely-packed interfacial layer vanishes along with the super-lubricity, leading to typical stick-slip friction. Additionally, in situ TEM observation and MD simulations reveals the crucial role that atom diffusion plays in atomic friction, and provides new insights into the fundamental mechanisms of super-lubricity.

42 ENGINEERING↗
DOE OSTI2025

Charge state-dependent ion condensation near conjugated polymer backbones

Despite the technological appeal of polymeric organic mixed ionic/electronic conductors (OMIECs) for diverse applications, a deep understanding of the fundamentals of mixed charge transport in these materials, especially regarding the complex interplay between polymer, ion and solvent structure in determining transport, is lacking. Herein, extensive molecular dynamics (MD) simulations of a model OMIEC representing various electrochemically gated states are reported that reveal charge state-dependent counterion condensation. X-ray diffraction simulations based on the MD data predict a measurable change in the scattering intensity at the counterion absorption edge, indicative of counterion repositioning with charging. We leverage an operando resonant X-ray scattering technique to experimentally corroborate the simulated scattering and report excellent agreement between predicted and experimental data, confirming that counterions preferentially reside in the lamellar mid-plane of crystallites at low doping, and near the polymer backbone at higher doping. Driving forces for ion type-dependent spatial repositioning and implications thereof are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Structure and Shape of Surface-Mediated Assembly of Surfactants

Achieving controls on the self-assembly of cationic and block copolymer micelles has significant implications for advancing novel material systems for energy, environmental, and biological applications and for tuning fluid flow behavior in subsurface geologic environments. While it is known that the aggregation of micelles is influenced by the composition of the surrounding fluid, the influence of a solid interface has been less explored. In this study, we probe the organization of cetyltrimethylammonium bromide (CTAB) micelles in the absence and presence of the Pluronic P123 block copolymer and quartz substrate using transmission and grazing-incidence small-angle X-ray scattering measurements and classical molecular dynamics (MD) simulations. In the absence of the quartz interface, CTAB with and without P123 molecules assemble as ellipsoid core–shell micelles. Densification of the core on adding P123 is noted from the decrease in the core radius from 15.9 to 14.6 Å. Here, the presence of a quartz substrate causes the micelles to elongate, which is noted by the emergence of a power-law slope in the low q region (<0.02 Å –1 ). Moreover, in the presence of both P123 and the quartz substrate, the micelle shape changes from ellipsoid core–shell to cylindrical core–shell, and a significantly higher number of aggregates are formed. The higher number of aggregates, and faster aggregation kinetics are linked to the organization of the solvent structures as noted from the MD simulations. These findings demonstrate the effects of adding a block copolymer and including a quartz substrate on the self-assembly of cationic (CTAB) micelles, which can be used to inform the design of functional material systems that harness surfactant chemistries.

42 ENGINEERING↗
DOE OSTI2022

NMR and Theoretical Study of In-Pore Diffusivity of Ionic Liquid–Solvent Mixtures

We report despite having a lower energy density than common batteries, electric double-layer capacitors (EDLCs) offer several advantages for high-power applications, including high power density, quick charge and discharge time, and long cycle life. Room-temperature ionic liquids (RTILs) have been intensely studied as promising electrolytes for applications in ELDCs because of their wide potential window, low volatility, as well as thermal and chemical stability. The main deficiency of neat RTILs in such applications is the sluggish diffusivity, which restricts the EDLCs’ power density. To alleviate the slow diffusivity, RTILs can be used in a mixture with organic solvents. In this study, we applied two-dimensional exchange nuclear magnetic resonance spectroscopy (2D EXSY NMR) and molecular dynamics (MD) simulations to investigate the diffusivity of anions of an RTIL, namely, 1-butyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl)imide (BMIM + –TFSI – ), dissolved in five different organic solvents, in the micropores of activated carbon. We determined that the relative concentrations of ions in solutions in the micropores were higher than those in the bulk solutions and were also solvent-dependent. The ion diffusivities in the pores were found to be almost 2 orders of magnitude slower than in the bulk solutions, with methanol showing the largest relative disparity. These results suggested that the interactions of solvents with the activated carbon are critical not only to the power density of EDLCs but also to the energy density. The comparisons of ion diffusivities between the experiments and the MD simulations suggest the need to consider also the surface functionalities of activated carbon for the simulation of ion diffusion in the micropores of activated carbon.

electric double layer capacitors↗
DOE OSTI2023

Electric Field Effects on Water and Ion Structure and Diffusion at the Orthoclase (001)–Water Interface

Understanding the electrochemical properties of mineral–water interfaces tends to rely upon electrical double layer (EDL) models, but these models are based on the assumption that electrostatic equilibrium is constantly maintained. In reality, interfacial reactions, ion diffusion, and their electrochemical signatures are based in nonequilibrium conditions of locally or globally imbalanced electrical fields where current EDL models have limited purview. In this work, we performed molecular dynamics (MD) simulations of the orthoclase (001) surface in contact with a 1 M NaCl aqueous solution under various electric fields, to explore the interplay between EDL structure and dynamics when perturbed by electric fields of different direction and strength, by confinement, and by different distributions of structural surface charge. The simulations showed that confinement between two opposing (001) surfaces led to the development of an induced field when the applied field was perpendicular to the surfaces and, as a result, to ionic diffusion coefficients that were independent of electric field strength. In contrast, when the applied field was parallel to the surfaces, confinement resulted in ionic diffusion coefficients that were more strongly dependent on the magnitude of the electric field than in bulk water. Differences in the density and distribution of aluminol groups on the two surfaces had a significant impact on how the interfacial structure and dynamics varied in the presence of an electric field. Notably, these differences resulted in an electro-osmotic flow with opposite directions at the two surfaces under parallel applied electric field. Overall, the MD simulations highlighted the importance of considering atomic-level structure and heterogeneities when developing models of the electrochemical properties of mineral–water interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Role of Capping Agents in the Synthesis of Salicylate-Capped Zinc Oxide Nanoparticles

Capping agents are often used for controlling the size, aggregation, and properties of nanoparticles. To guide the design of improved nanomaterials for targeted performance, one can use mechanistic insights into the interactions between capping agents and nanoparticles. Here, we employ density functional theory (DFT), reactive force-field molecular dynamics (ReaxFF MD) simulations, and optical spectroscopy to study the interactions between salicylate, as a model capping agent, and zinc oxide (ZnO) nanoparticles. In this work, we find that salicylate strongly interacts with the nanoparticle via the formation of O–Zn bonds in a distorted six-membered coordination ring structure. We describe the mechanisms of capping of ZnO nanoparticles by salicylate via three different binding modes. Simulations indicate that salicylate undergoes dissociative adsorption at the highly active surface Zn sites via a hydrogen-transfer process, thereby forming a tridentate configuration. The water-mediated interaction also facilitates the dissociative adsorption, leading to two salicylate O atoms coordinating with a surface Zn atom, while the other salicylate O atom bonds with another surface Zn atom. For molecular adsorption, binding free energies indicate that salicylate binds more strongly to ZnO, often in a bidentate configuration, than water does. The formation of the salicylate–ZnO complex is substantiated by UV–visible and Fourier transform infrared spectra. We find that the C=O stretching mode of salicylate becomes softened when it interacts with the nanoparticle, suggesting chemisorption of salicylate on ZnO. Although DFT predicts strong interaction between salicylate and ZnO, ReaxFF MD simulation indicates the moderate interaction between these two components in aqueous solution. Water molecules in close contact with the nanoparticle surface undergo dissociation, thus resulting in a surface hydroxyl, a reactive oxygen species that may influence the nanoparticle’s catalytic properties. Overall, the atomic-level information provided here can guide the selection process of salicylate as an appropriate agent for ZnO nanoparticle synthesis when strong interactions of particles with capping agents are required.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗