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Supported metal nanoparticles are used as heterogeneous catalysts but often deactivated due to sintering at high temperatures. Confining metal species into a porous matrix reduces sintering, yet supports rarely provide additional stabilization. Here, we used the silanol‐rich layered zeolite IPC‐1P to stabilize ultra‐small Rh nanoparticles. By adjusting the IPC‐1P interlayer space through swelling, we prepared various architectures, including microporous and disordered mesoporous. In situ scanning transmission electron microscopy confirmed that Rh nanoparticles are resistant to sintering at high temperature (750 °C, 6 hrs). Rh clusters strongly bind to surface silanol quadruplets at IPC‐1P layers by hydrogen transfer to clusters, while high silanol density hinders their migration based on density functional theory calculations. Ultimately, combining swelling with long‐chain surfactant and utilizing metal‐silanol interactions resulted in a novel, catalytically active material—Rh@IPC_C22. [ABSTRACT FROM AUTHOR]

One of the main limitations in supporting experimental characterization of Al siting/pairing via modelling is the high computational cost of ab initio calculations. For this reason, most works rely on static or very short dynamical simulations, considering limited Al pairing/siting combinations. As a result, comparison with experiment suffers from a large degree of uncertainty. To alleviate this limitation we have developed neural network potentials (NNPs) which can dynamically sample across broad configurational and chemical spaces of sodium-form aluminosilicate zeolites, preserving the level of accuracy of the ab initio (dispersion-corrected metaGGA) training set. By exploring a wide range of Al/Na arrangements and a combination of experimentally relevant Si/Al ratios, we found that the 23 Na NMR spectra of dehydrated high-silica CHA zeolite offer an opportunity to assess the distribution and pairing of Al atoms. We observed that the 23 Na chemical shift is sensitive not only to the location of sodium in 6- and 8MRs, but also to the Al-Si n -Al sequence length. Furthermore, neglect of thermal and dynamical contributions was found to lead to errors of several ppm, and has a profound influence on the shape of the spectra and the dipolar coupling constants, thus necessitating the long-term dynamical simulations made feasible by NNPs. Finally, we obtained a predictive regression model for the 23 Na chemical shift in CHA (Si/Al = 35, 17, 11) that circumvents the need for expensive NMR density functional calculations and can be easily extended to other zeolite frameworks. By combining NNPs and regression methods, we can expedite the simulations of NMR properties and capture the effect of dynamics on the spectra, which is often overlooked in computational studies despite its clear manifestation in experimental setups.

Solid state (ss-) 27 Al NMR is one of the most valuable tools for the experimental characterization of zeolites, owing to its high sensitivity and the detailed structural information which can be extracted from the spectra. Unfortunately, the interpretation of ss-NMR is complex and the determination of aluminum distributions remains generally unfeasible. As a result, computational modelling of 27 Al ss-NMR spectra has grown increasingly popular as a means to support experimental characterization. However, a number of simplifying assumptions are commonly made in NMR modelling, several of which are not fully justified. In this work, we systematically evaluate the effects of various common models on the prediction of 27 Al NMR chemical shifts in zeolites CHA and MOR. We demonstrate the necessity of operando modelling; in particular, taking into account the effects of water loading, temperature and the character of the charge-compensating cation. We observe that conclusions drawn from simple, high symmetry model systems such as CHA do not transfer well to more complex zeolites and can lead to qualitatively wrong interpretations of peak positions, Al assignment and even the number of signals. We use machine learning regression to develop a simple yet robust relationship between chemical shift and local structural parameters in Al-zeolites. This work highlights the need for sophisticated models and high-quality sampling in the field of NMR modelling and provides correlations which allow for the accurate prediction of chemical shifts from dynamical simulations., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

While the structures of Brønsted acid sites (BAS) in zeolites are well understood, those of Lewis acid sites (LAS) remain an active area of investigation. Under hydrated conditions, the reversible formation of framework-associated octahedral aluminum has been observed in zeolites in the acidic form. However, the structure and formation mechanisms are currently unknown. In this work, combined experimental 27 Al NMR spectroscopy and computational data reveal for the first time the details of the zeolite framework-associated octahedral aluminium. The octahedral LAS site becomes kinetically allowed and thermodynamically stable under wet conditions in the presence of multiple nearby BAS sites. The critical condition for the existence of such octahedral LAS appears to be the availability of three protons: at lower proton concentration, either by increasing the Si/Al or by ion-exchange to non-acidic form, the tetrahedral BAS becomes thermodynamically more stable. This work resolves the question about the nature and reversibility of framework-associated octahedral aluminium in zeolites., (© 2023 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH.)

Ultrathin layers of oxides deposited on atomically flat metal surfaces have been shown to significantly influence the electronic structure of the underlying metal, which in turn alters the catalytic performance. Upscaling of the specifically designed architectures as required for technical utilization of the effect has yet not been achieved. Here, we apply liquid crystalline phases of fluorohectorite nanosheets to fabricate such architectures in bulk. Synthetic sodium fluorohectorite, a layered silicate, when immersed into water spontaneously and repulsively swells to produce nematic suspensions of individual negatively charged nanosheets separated to more than 60 nm, while retaining parallel orientation. Into these galleries oppositely charged palladium nanoparticles were intercalated whereupon the galleries collapse. Individual and separated Pd nanoparticles were thus captured and sandwiched between nanosheets. As suggested by the model systems, the resulting catalyst performed better in the oxidation of carbon monoxide than the same Pd nanoparticles supported on external surfaces of hectorite or on a conventional Al 2 O 3 support. XPS confirmed a shift of Pd 3d electrons to higher energies upon coverage of Pd nanoparticles with nanosheets to which we attribute the improved catalytic performance. DFT calculations showed increasing positive charge on Pd weakened CO adsorption and this way damped CO poisoning., (© 2020 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH.)

Ultrathin metal oxides exhibit unique chemical properties and show promise for applications in heterogeneous catalysis. Monolayer FeO films supported on metal surfaces show large differences in reactivity depending on the metal substrate, potentially enabling tuning of the catalytic properties of these materials. Nitric oxide (NO) adsorption is facile on silver-supported FeO, whereas a similar film grown on platinum is inert to NO under similar conditions. Ab initio calculations link this substrate-dependent behavior to steric hindrance caused by substrate-induced rumpling of the FeO surface, which is stronger for the platinum-supported film. Calculations show that the size of the activation barrier to adsorption caused by the rumpling is dictated by the strength of the metal-oxide interaction, offering a straightforward method for tailoring the adsorption properties of ultrathin films., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The novel surface mode of the Birmingham Cluster Genetic Algorithm (S-BCGA) is employed for the global optimisation of noble metal tetramers upon an MgO (100) substrate at the GGA-DFT level of theory. The effect of element identity and alloying in surface-bound neutral subnanometre clusters is determined by energetic comparison between all compositions of PdnAg(4-n) and PdnPt(4-n). While the binding strengths to the surface increase in the order Pt > Pd > Ag, the excess energy profiles suggest a preference for mixed clusters for both cases. The binding of CO is also modelled, showing that the adsorption site can be predicted solely by electrophilicity. Comparison to CO binding on a single metal atom shows a reversal of the 5σ-d activation process for clusters, weakening the cluster-surface interaction on CO adsorption. Charge localisation determines homotop, CO binding and surface site preferences. The electronic behaviour, which is intermediate between molecular and metallic particles allows for tunable features in the subnanometre size range.