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.

An accurate description of metal nanoparticle (NP)−support interactions is required for designing and optimizing NP catalytic systems because NP−support 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 Pt 13 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 Pt−silica 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 Pt−silica bonds. Moreover, we find that the number of Pt−silica 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 metal−support interactions. The magnitude of support effects highlights the need for explicitly including amorphous supports in atomistic studies.

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 °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 due to already well‐hydrated ions in the membrane. At low relative humidity, the water sorption occurred quickly due to the high enthalpy of solvation at low λ, 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 deswelling 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.

The interaction between catalytic nanoparticles (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. ■ INTRODUCTIONRecent developments in both computational methods 1−11 and experimental characterization techniques 12−14 have facilitated detailed characterization of catalytic materials at the atomic level. Insights relating structural and electronic properties to catalytic reactivity, selectivity, and stability have provided some general rules for tailoring catalyst properties via what is now ubiquitously termed "rational design." 7−11,14,15 Many computational results have been shown to agree quite well with experimental observations, in particular, correlations involving simple properties (e.g., coordination number and adsorbate binding energies) and simple systems (e.g., extended metal surfaces and diatomic reactants). Catalytic materials research, however, has recently shifted toward ever-smaller nanoparticles (NPs) and increasingly complex support materials. Whereas approaches to understanding simple catalytic materials have been well-established and researched in recent years, 7−11,14−16 atomistic studies of supported NP systems have been limited to idealized, perfectly crystalline supports. 17−21 Numerous studies have exploited geometry-constrained calculations to isolate the effects of coordination number and NP size. 7,8,11 This approach often provides clear trends and powerful insight regarding catalyst design. However, distortion of the support structure has been shown to significantly alter the structure and electronic properties of supported NPs. 17,22 Amorphous supports exhibit a diverse range of local surface structures, which result in a distribution of catalyst−support...