Encapsulating Metal Nanoparticles into a Layered Zeolite Precursor with Surface Silanol Nests Enhances Sintering Resistance.

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.

Dynamical Equilibrium between Brønsted and Lewis Sites in Zeolites: Framework-Associated Octahedral Aluminum.

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.

Nanoparticles Supported on Sub-Nanometer Oxide Films: Scaling Model Systems to Bulk Materials.

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 Al2 O3 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.

Towards operando computational modeling in heterogeneous catalysis.

An increased synergy between experimental and theoretical investigations in heterogeneous catalysis has become apparent during the last decade. Experimental work has extended from ultra-high vacuum and low temperature towards operando conditions. These developments have motivated the computational community to move from standard descriptive computational models, based on inspection of the potential energy surface at 0 K and low reactant concentrations (0 K/UHV model), to more realistic conditions. The transition from 0 K/UHV to operando models has been backed by significant developments in computer hardware and software over the past few decades. New methodological developments, designed to overcome part of the gap between 0 K/UHV and operando conditions, include (i) global optimization techniques, (ii) ab initio constrained thermodynamics, (iii) biased molecular dynamics, (iv) microkinetic models of reaction networks and (v) machine learning approaches. The importance of the transition is highlighted by discussing how the molecular level picture of catalytic sites and the associated reaction mechanisms changes when the chemical environment, pressure and temperature effects are correctly accounted for in molecular simulations. It is the purpose of this review to discuss each method on an equal footing, and to draw connections between methods, particularly where they may be applied in combination.

Tuning the Reactivity of Ultrathin Oxides: NO Adsorption on Monolayer FeO(111).

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.

Energy landscape exploration of sub-nanometre copper-silver clusters.

The energy landscapes of sub-nanometre bimetallic coinage metal clusters are explored with the Threshold Algorithm coupled with the Birmingham Cluster Genetic Algorithm. Global and energetically low-lying minima along with their permutational isomers are located for the Cu(4)Ag(4) cluster with the Gupta potential and density functional theory (DFT). Statistical tools are employed to map the connectivity of the energy landscape and the growth of structural basins, while the thermodynamics of interconversion are probed, based on probability flows between minima. Asymmetric statistical weights are found for pathways across dividing states between stable geometries, while basin volumes are observed to grow independently of the depth of the minimum. The DFT landscape is found to exhibit significantly more frustration than that of the Gupta potential, including several open, pseudo-planar geometries which are energetically competitive with the global minimum. The differences in local minima and their transition barriers between the two levels of theory indicate the importance of explicit electronic structure for even simple, closed shell clusters.

A theoretical study of the structures and optical spectra of helical copper-silver clusters.

The structures and optical response of helical clusters ("Bernal spirals") with compositions Ag12Cu1(+) and Ag1Cu12(+) are calculated within Kohn-Sham density functional theory and the configuration interaction singles variant of time dependent density functional theory. The effects of dopant position within the cluster on the vertical excitation spectrum are investigated according to the underlying electronic structure of the major transitions. The roles of symmetry and geometry are investigated by calculating the optical response of helical, icosahedral and nanorod-like clusters of Ag13(+), finding local structure to be significant in driving the resultant optical response at the subnanometre scale. Further, it is noted that helical clusters have optical properties which are quite distinct from those of nanorods of similar dimensions. The effect of multiple doping is studied by introducing copper atoms into the centre of the silver helix, over the composition range Ag13(+) to Ag6Cu7(+). There is a complex variation of the major plasmon-like peak over this range, attributed to subtle variations in the influence of the copper 3d band on the excitations and charge transfer for different sites within the cluster. This work suggests that coinage metal nanohelices have unusual, tunable electronic properties, which in addition to their inherent chirality makes them interesting systems to study for chiral catalysis and optoelectronics.

Migration of zeolite-encapsulated subnanometre platinum clusters via reactive neural network potentials.

The migration of atoms and small clusters is an important process in sub-nanometre scale heterogeneous catalysis, affecting activity, accessibility and deactivation through sintering. Control of migration can be partially achieved via encapsulation of sub-nanometre metal particles into porous media such as zeolites. However, a general understanding of the migration mechanisms and their sensitivity to particle size and framework environment is lacking. Here, we extend the time-scale and sampling of atomistic simulations of platinum cluster diffusion in siliceous zeolite frameworks, by introducing a reactive neural network potential of density functional quality. We observe that Pt atoms migrate in a qualitatively different manner from clusters, occupying the dense region of the framework and avoiding the free pore space. We also find that for cage-like zeolite CHA there exists a maximum in self diffusivity for the Pt dimer beyond which, confinement effects hinder intercage migration. By extending the quality of sampling, NNP-based methods allow for the discovery of novel dynamical processes at the atomistic scale, bringing modelling closer to operando experimental characterization of catalytic materials.

A reactive neural network framework for water-loaded acidic zeolites.

Under operating conditions, the dynamics of water and ions confined within protonic aluminosilicate zeolite micropores are responsible for many of their properties, including hydrothermal stability, acidity and catalytic activity. However, due to high computational cost, operando studies of acidic zeolites are currently rare and limited to specific cases and simplified models. In this work, we have developed a reactive neural network potential (NNP) attempting to cover the entire class of acidic zeolites, including the full range of experimentally relevant water concentrations and Si/Al ratios. This NNP has the potential to dramatically improve sampling, retaining the (meta)GGA DFT level accuracy, with the capacity for discovery of new chemistry, such as collective defect formation mechanisms at the zeolite surface. Furthermore, we exemplify how the NNP can be used as a basis for further extensions/improvements which include data-efficient adoption of higher-level (hybrid) references via Δ-learning and the acceleration of rare event sampling via automatic construction of collective variables. These developments represent a significant step towards accurate simulations of realistic catalysts under operando conditions.

A themed collection in memory of Petr Nachtigall.

Professor RNDr. Petr Nachtigall, PhD passed away on 28 December 2022. He was an internationally recognized expert in computational materials science; working at Charles University in the Department of Physical and Macromolecular Chemistry. We honor his memory.

The need for operando modelling of 27Al NMR in zeolites: the effect of temperature, topology and water.

Solid state (ss-) 27Al 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 27Al 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 27Al 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.

Correction: The need for operando modelling of 27Al NMR in zeolites: the effect of temperature, topology and water.

[This corrects the article DOI: 10.1039/D3SC02492J.].

The effect of water on the validity of Löwenstein's rule.

The common understanding of zeolite acidity is based on Löwenstein's rule, which states that Al-O-Al aluminium pairs are forbidden in zeolites. This rule is generally accepted to be inviolate in zeolites. However, recent computational research using a 0 K DFT model has suggested that the rule is violated for the acid form of several zeolites under anhydrous conditions [Fletcher et al., Chem. Sci., 8, (2017), 7483]. The effect of water loading on the preferred aluminium distribution in zeolites, however, has so far not been taken into account. In this article, we show by way of ab initio molecular dynamics simulations that Löwenstein's rule is obeyed under high water solvation for acid chabazite (H-CHA) but disobeyed under anhydrous conditions. We find that varying the water loading in the pores leads to dramatic effects on the structure of the active sites and the dynamics of solvation. The solvation of Brønsted protons in the surrounding water was found to be the energetic driving force for the preferred Löwenstein Al distribution and this driving force is absent in non-Löwenstein (Al-O(H)-Al) moieties. The preference for solvated protons further implies that the catalytically active species in zeolites is a protonated water cluster, rather than a framework Brønsted site. Hence, an accurate treatment of the solvation conditions is crucial to capture the behaviour of zeolites and to properly connect simulations to experiments. This work should lead to a change in modelling paradigm for zeolites, from single molecules towards high solvation models where appropriate.

2D Oxide Nanomaterials to Address the Energy Transition and Catalysis.

2D oxide nanomaterials constitute a broad range of materials, with a wide array of current and potential applications, particularly in the fields of energy storage and catalysis for sustainable energy production. Despite the many similarities in structure, composition, and synthetic methods and uses, the current literature on layered oxides is diverse and disconnected. A number of reviews can be found in the literature, but they are mostly focused on one of the particular subclasses of 2D oxides. This review attempts to bridge the knowledge gap between individual layered oxide types by summarizing recent developments in all important 2D oxide systems including supported ultrathin oxide films, layered clays and double hydroxides, layered perovskites, and novel 2D-zeolite-based materials. Particular attention is paid to the underlying similarities and differences between the various materials, and the subsequent challenges faced by each research community. The potential of layered oxides toward future applications is critically evaluated, especially in the areas of electrocatalysis and photocatalysis, biomass conversion, and fine chemical synthesis. Attention is also paid to corresponding novel 3D materials that can be obtained via sophisticated engineering of 2D oxides.

Fast room temperature lability of aluminosilicate zeolites.

Aluminosilicate zeolites are traditionally used in high-temperature applications at low water vapour pressures where the zeolite framework is generally considered to be stable and static. Increasingly, zeolites are being considered for applications under milder aqueous conditions. However, it has not yet been established how neutral liquid water at mild conditions affects the stability of the zeolite framework. Here, we show that covalent bonds in the zeolite chabazite (CHA) are labile when in contact with neutral liquid water, which leads to partial but fully reversible hydrolysis without framework degradation. We present ab initio calculations that predict novel, energetically viable reaction mechanisms by which Al-O and Si-O bonds rapidly and reversibly break at 300 K. By means of solid-state NMR, we confirm this prediction, demonstrating that isotopic substitution of 17O in the zeolitic framework occurs at room temperature in less than one hour of contact with enriched water.

Pd(n)Ag(4-n) and Pd(n)Pt(4-n) clusters on MgO (100): a density functional surface genetic algorithm investigation.

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.

Size-dependent subnanometer Pd cluster (Pd4, Pd6, and Pd17) water oxidation electrocatalysis.

Water oxidation is a key catalytic step for electrical fuel generation. Recently, significant progress has been made in synthesizing electrocatalytic materials with reduced overpotentials and increased turnover rates, both key parameters enabling commercial use in electrolysis or solar to fuels applications. The complexity of both the catalytic materials and the water oxidation reaction makes understanding the catalytic site critical to improving the process. Here we study water oxidation in alkaline conditions using size-selected clusters of Pd to probe the relationship between cluster size and the water oxidation reaction. We find that Pd4 shows no reaction, while Pd6 and Pd17 deposited clusters are among the most active (in terms of turnover rate per Pd atom) catalysts known. Theoretical calculations suggest that this striking difference may be a demonstration that bridging Pd-Pd sites (which are only present in three-dimensional clusters) are active for the oxygen evolution reaction in Pd6O6. The ability to experimentally synthesize size-specific clusters allows direct comparison to this theory. The support electrode for these investigations is ultrananocrystalline diamond (UNCD). This material is thin enough to be electrically conducting and is chemically/electrochemically very stable. Even under the harsh experimental conditions (basic, high potential) typically employed for water oxidation catalysts, UNCD demonstrates a very wide potential electrochemical working window and shows only minor evidence of reaction. The system (soft-landed Pd4, Pd6, or Pd17 clusters on a UNCD Si-coated electrode) shows stable electrochemical potentials over several cycles, and synchrotron studies of the electrodes show no evidence for evolution or dissolution of either the electrode material or the clusters.

Structure and stability of charged clusters.

When a cluster or nanodroplet bears charge, its structure and thermodynamics are altered and, if the charge exceeds a certain limit, the system becomes unstable with respect to fragmentation. Some of the key results in this area were derived by Rayleigh in the nineteenth century using a continuum model of liquid droplets. Here we revisit the topic using a simple particle-based description, presenting a systematic case study of how charge affects the physical properties of a Lennard-Jones cluster composed of 309 particles. We find that the ability of the cluster to sustain charge depends on the number of particles over which the charge is distributed-a parameter not included in Rayleigh's analysis. Furthermore, the cluster may fragment before the charge is strong enough to drive all charged particles to the surface. The charged particles in stable clusters are therefore likely to reside in the cluster's interior even without considering solvation effects.