We quantified the impact of support interactions on the binding and interaction energies of CO and O adsorbed on Pt-13 nanoclusters supported on amorphous silica surfaces through the use of density functional theory calculations. We used an accurate model for amorphous silica having two different surface silanol concentrations, corresponding to low (200 degrees C) and high (715 degrees C) surface pretreatment temperatures. We compared CO and O adsorbed on supported and freestanding Pt-13 clusters. We found that Pt-13 is highly susceptible to both support- and adsorbate-induced reconstruction, depending on the relaxed structure of the Pt-13 cluster on the surface. Structure relaxation effects dominate over electronic effects of the support. We considered an ensemble of 50 different systems by varying the placement of the Pt-13 cluster on the surfaces and by exploring a range of different binding sites for CO and O on the Pt-13 cluster. In select cases, binding energy differences between supported and freestanding Pt-13 are as large as 2 eV. However, the mean absolute error between supported and freestanding clusters over all systems we studied is only a few tenths of an eV. Coverage effects on coadsorption of CO and O are significantly different on supported clusters compared with the Pt(111) surface. Our results can be used for predicting when support interactions may be important for any reaction catalyzed by small metal nanoclusters.

Amorphous silica is a commonly used catalyst support, yet there are relatively few experimental or computational studies on catalyst support interactions for this material. This is largely due to the inherent difficulty in modeling and experimentally characterizing amorphous silica. We used a recently developed surface model for amorphous silica surfaces to study the support effects on single-atom molybdenum catalysts. We found that the local structure of the silica support in the vicinity of the Mo site has a profound effect on the energetics and kinetics of metallacycle rotation, which is related to ethene metathesis. We have compared site energies, reaction energies, and reaction barriers computed from simple cluster models with results from surface models. The cluster models show a clear relationship between Si-Si distances and the site energies and reaction energies. In contrast, the surface model shows no correlation between Si-Si distances and energetics. The reaction barriers clearly increase with increasing Si-Si distances in the cluster model, whereas there is only a qualitative trend in the surface model. Analysis of the surface results indicates that the reaction energetics are affected by neighboring hydroxyl groups and Si atoms in the surface that are not accounted for in the cluster models. We therefore conclude that the simple trends relating support atom geometries to reaction energetics observed in the cluster models are artifacts of the model.

Metal-support interactions significantly affect the stability and activity of supported catalytic nanoparticles (NPs), yet there is no simple and reliable method for estimating NP-support interactions, especially for amorphous supports. We present an approach for rapid prediction of catalyst-support interactions between Pt NPs and amorphous silica supports for NPs of various sizes and shapes. We use density functional theory calculations of 13atom Pt clusters on model amorphous silica supports to determine linear correlations relating catalyst properties to NP-support interactions. We show that these correlations can be combined with fast discrete element method simulations to predict adhesion energy and NP net charge for NPs of larger sizes and different shapes. Furthermore, we demonstrate that this approach can be successfully transferred to Pd, Au, Ni, and Fe NPs. This approach can be used to quickly screen stability and net charge transfer and leads to a better fundamental understanding of catalyst-support interactions.

An accurate description of metal nanoparticle (NP)support interactions is required for designing and optimizing NP catalytic systems because NPsupport interactions may significantly impact NP stability and properties, such as catalytic activity. The ability to calculate NP interactions with amorphous supports, which are commonly used in industrial practice, is hampered because of a general lack of accurate atomically detailed model structures of amorphous surfaces. We have systematically studied relaxation processes of Pt13 NPs on amorphous silica using recently developed realistic model amorphous silica surfaces. We have modeled the NP relaxation process in multiple steps: hard-sphere interactions were first used to generate initial placement of NPs on amorphous surfaces, then Ptsilica bonds were allowed to form, and finally both the NP and substrate were relaxed with density functional theory calculations. We find that the amorphous silica surface significantly impacts the morphology and electronic structure of the Pt clusters. Both NP energetics and charge transfer from NP to the support depend linearly on the number of Ptsilica bonds. Moreover, we find that the number of Ptsilica bonds is determined by the silica silanol number, which is a function of the silica pretreatment temperature. We predict that catalyst stability and electronic charge can be tuned via the pretreatment temperature of the support materials. The extent of support effects suggests that experiments aiming to measure the intrinsic catalytic properties of very small NPs on amorphous supports will fail because the measurable catalytic properties will depend critically on metalsupport interactions. The magnitude of support effects highlights the need for explicitly including amorphous supports in atomistic studies.

The interaction between catalytic nanopartides (NPs) and their supports, which are often amorphous oxides, has not been well characterized at the atomic level, although it is known that, in some cases, NP support interactions dominate the catalytic activity of the system. Furthermore, there is a lack of understanding of how support preparation affects both the stability of the NP (resistance to sintering) and the catalytic activity. We present first-principles density functional theory (DFT) calculations on amorphous silica supported Pt NPs of various sizes. Our calculations predict that support preparation methods that lead to higher hydroxyl density when NPs are deposited on the support will lead to higher resistance to sintering. We find that the total charge on supported NPs, which can affect catalyst activity, depends linearly on the number of Pt silica bonds formed during NP deposition. The number of bonds between an NP of a known geometry and the silica support with a known hydroxyl density can be estimated from very fast discrete element method simulations, enabling the prediction of both the net charge and the adhesion energy of the particle from a linear fit correlation derived from DFT calculations of a series of differently sized Pt clusters. This work quantifies interactions between Pt NPs and amorphous silica supports and demonstrates a new method for rapid estimation of NP support interactions on amorphous supports.

Accurate atomically detailed models of amorphous materials have been elusive to-date due to limitations in both experimental data and computational methods. We present an approach for constructing atomistic models of amorphous silica surfaces encountered in many industrial applications (such as catalytic support materials). We have used a combination of classical molecular modeling and density functional theory calculations to develop models having predictive capabilities. Our approach provides accurate surface models for a range of temperatures as measured by the thermodynamics of surface dehydroxylation. We find that a surprisingly small model of an amorphous silica surface can accurately represent the physics and chemistry of real surfaces as demonstrated by direct experimental validation using macroscopic measurements of the silanol number and type as a function of temperature. Beyond accurately predicting the experimentally observed trends in silanol numbers and types, the model also allows new insights into the dehydroxylation of amorphous silica surfaces. Our formalism is transferrable and provides an approach to generating accurate models of other amorphous materials.

ADVERTISEMENT RETURN TO ISSUEPREVCommunication to the...Communication to the EditorNEXTSynthesis of Proton Conductive Polymers with High Electrochemical SelectivityKui Xu, Kun Li, Christopher S. Ewing, Michael A. Hickner, and Qing Wang*View Author Information Department of Materials Science and Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802*To whom correspondence should be addressed. E-mail: [email protected]Cite this: Macromolecules 2010, 43, 4, 1692–1694Publication Date (Web):January 25, 2010Publication History Received9 December 2009Revised15 January 2010Published online25 January 2010Published inissue 23 February 2010https://pubs.acs.org/doi/10.1021/ma902716xhttps://doi.org/10.1021/ma902716xrapid-communicationACS PublicationsCopyright © 2010 American Chemical SocietyRequest reuse permissionsArticle Views1198Altmetric-Citations10LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Alcohols,Fluoropolymers,Membranes,Permeability,Polymers Get e-Alerts

Dynamic gravimetric water sorption and desorption was measured while incrementing the relative humidity of the sample environment for a variety of ion-containing polymers. The sorption and desorption experiments as a function of time were performed from 20 to 95% relative humidity and temperatures from 30 to 70 degrees C. The water uptake characteristics of the membranes were observed to depend on the flexibility of the polymer backbone, the ion exchange capacity of the membrane, and in the case of triblock copolymers, the molecular weight of the sulphonated block. Additionally, the water uptake tended to occur more slowly at high relative humidity where the enthalpy of solvation is low relative humidity, the water sorption occurred quickly due to the high enthalpy of solvation at low lambda, but the polymer matrix constrained the magnitude of the total water swelling. A unique physical crosslinking effect was observed for triblock copolymers where less swelling of the network occurred at high temperatures than at low temperatures. This deswellingg phenomenon with increased temperature was not observed for Nafion, which behaved like a classic elastic solid and swelled to a greater extent with increased temperature.

Gravimetric analysis was performed during a step change in relative humidity for a series of sulfonated polymers to determine their dynamic water uptake characteristics. The mass change was recorded as a function of time for both stiff-backboned and flexible-backboned polymers when the humidity was instantaneously increased from 40 to 50 %. The observed water uptake profiles were distinctly different based on the inferred stiffness of the sulfonated polymer backbone. A sulfonated poly(sulfone)-based membrane had a slower mass uptake than more flexible Nafion with time constants of 307 s and 150 s for the sulfonated poly(sulfone) and NRE212, respectively. The dynamic water absorption properties were measured for a series of sulfonated poly(styrene)-b-poly(vinylidene fluoride)-b-sulfonated poly(styrene) membranes. The backbone flexibility of these polymers was intermediate to that of the poly(sulfone) and Nafion membranes and could be tuned based on the molecular weight of the poly(styrene) blocks and sulfonation level.