A Systematic Study of Isomorphically Substituted H-MAlPO-5 Materials for the Methanol-to-Hydrocarbons Reaction

Transitioning from Methanol to Olefins (MTO) toward a Tandem CO2 Hydrogenation Process: On the Role and Fate of Heteroatoms (Mg, Si) in MAPO-18 Zeotypes

The tandem CO2 hydrogenation to hydrocarbons over mixed metal oxide/zeolite catalysts (OXZEO) is an efficient way of producing value-added hydrocarbons (platform chemicals and fuels) directly from CO2via methanol intermediate in a single reactor. In this contribution, two MAPO-18 zeotypes (M = Mg, Si) were tested and their performance was compared under methanol-to-olefins (MTO) conditions (350 °C, PCH3OH = 0.04 bar, 6.5 gCH3OH h-1 g-1), methanol/CO/H2 cofeed conditions (350 °C, PCH3OH/PCO/PH2 = 1:7.3:21.7 bar, 2.5 gCH3OH h-1 g-1), and tandem CO2 hydrogenation-to-olefin conditions (350 °C, PCO2/PH2 = 7.5:22.5 bar, 1.4-12.0 gMAPO-18 h molCO2-1). In the latter case, the zeotypes were mixed with a fixed amount of ZnO:ZrO2 catalyst, well-known for the conversion of CO2/H2 to methanol. Focus was set on the methanol conversion activity, product selectivity, and performance stability with time-on-stream. In situ and ex situ Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), solid-state nuclear magnetic resonance (NMR), sorption experiments, and ab initio molecular dynamics (AIMD) calculations were performed to correlate material performance with material characteristics. The catalytic tests demonstrated the better performance of MgAPO-18 versus SAPO-18 at MTO conditions, the much superior performance of MgAPO-18 under methanol/CO/H2 cofeeds, and yet the increasingly similar performance of the two materials under tandem conditions upon increasing the zeotype-to-oxide ratio in the tandem catalyst bed. In situ FT-IR measurements coupled with AIMD calculations revealed differences in the MTO initiation mechanism between the two materials. SAPO-18 promoted initial CO2 formation, indicative of a formaldehyde-based decarboxylation mechanism, while CO and ketene were the main constituents of the initiation pool in MgAPO-18, suggesting a decarbonylation mechanism. Under tandem CO2 hydrogenation conditions, the presence of high water concentrations and low methanol partial pressure in the reaction medium led to lower, and increasingly similar, methanol turnover frequencies for the zeotypes. Despite both MAPO-18 zeotypes showing signs of activity loss upon storage due to the interaction of the sites with ambient humidity, they presented a remarkable stability after reaching steady state under tandem reaction conditions and after steaming and regeneration cycles at high temperatures. Water adsorption experiments at room temperature confirmed this observation. The faster activity loss observed in the Mg version is assigned to its harder Mg2+-ion character and the higher concentration of CHA defects in the AEI structure, identified by solid-state NMR and XRD. The low stability of a MgAPO-34 zeotype (CHA structure) upon storage corroborated the relationship between CHA defects and instability.

Operando Modeling of Zeolite-Catalyzed Reactions Using First-Principles Molecular Dynamics Simulations

Within this Perspective, we critically reflect on the role of first-principles molecular dynamics (MD) simulations in unraveling the catalytic function within zeolites under operating conditions. First-principles MD simulations refer to methods where the dynamics of the nuclei is followed in time by integrating the Newtonian equations of motion on a potential energy surface that is determined by solving the quantum-mechanical many-body problem for the electrons. Catalytic solids used in industrial applications show an intriguing high degree of complexity, with phenomena taking place at a broad range of length and time scales. Additionally, the state and function of a catalyst critically depend on the operating conditions, such as temperature, moisture, presence of water, etc. Herein we show by means of a series of exemplary cases how first-principles MD simulations are instrumental to unravel the catalyst complexity at the molecular scale. Examples show how the nature of reactive species at higher catalytic temperatures may drastically change compared to species at lower temperatures and how the nature of active sites may dynamically change upon exposure to water. To simulate rare events, first-principles MD simulations need to be used in combination with enhanced sampling techniques to efficiently sample low-probability regions of phase space. Using these techniques, it is shown how competitive pathways at operating conditions can be discovered and how broad transition state regions can be explored. Interestingly, such simulations can also be used to study hindered diffusion under operating conditions. The cases shown clearly illustrate how first-principles MD simulations reveal insights into the catalytic function at operating conditions, which could not be discovered using static or local approaches where only a few points are considered on the potential energy surface (PES). Despite these advantages, some major hurdles still exist to fully integrate first-principles MD methods in a standard computational catalytic workflow or to use the output of MD simulations as input for multiple length/time scale methods that aim to bridge to the reactor scale. First of all, methods are needed that allow us to evaluate the interatomic forces with quantum-mechanical accuracy, albeit at a much lower computational cost compared to currently used density functional theory (DFT) methods. The use of DFT limits the currently attainable length/time scales to hundreds of picoseconds and a few nanometers, which are much smaller than realistic catalyst particle dimensions and time scales encountered in the catalysis process. One solution could be to construct machine learning potentials (MLPs), where a numerical potential is derived from underlying quantum-mechanical data, which could be used in subsequent MD simulations. As such, much longer length and time scales could be reached; however, quite some research is still necessary to construct MLPs for the complex systems encountered in industrially used catalysts. Second, most currently used enhanced sampling techniques in catalysis make use of collective variables (CVs), which are mostly determined based on chemical intuition. To explore complex reactive networks with MD simulations, methods are needed that allow the automatic discovery of CVs or methods that do not rely on a priori definition of CVs. Recently, various data-driven methods have been proposed, which could be explored for complex catalytic systems. Lastly, first-principles MD methods are currently mostly used to investigate local reactive events. We hope that with the rise of data-driven methods and more efficient methods to describe the PES, first-principles MD methods will in the future also be able to describe longer length/time scale processes in catalysis. This might lead to a consistent dynamic description of all steps-diffusion, adsorption, and reaction-as they take place at the catalyst particle level.

Challenges in modelling dynamic processes in realistic nanostructured materials at operating conditions

The question is addressed in how far current modelling strategies are capable of modelling dynamic phenomena in realistic nanostructured materials at operating conditions. Nanostructured materials used in applications are far from perfect; they possess a broad range of heterogeneities in space and time extending over several orders of magnitude. Spatial heterogeneities from the subnanometre to the micrometre scale in crystal particles with a finite size and specific morphology, impact the material's dynamics. Furthermore, the material's functional behaviour is largely determined by the operating conditions. Currently, there exists a huge length-time scale gap between attainable theoretical length-time scales and experimentally relevant scales. Within this perspective, three key challenges are highlighted within the molecular modelling chain to bridge this length-time scale gap. Methods are needed that enable (i) building structural models for realistic crystal particles having mesoscale dimensions with isolated defects, correlated nanoregions, mesoporosity, internal and external surfaces; (ii) the evaluation of interatomic forces with quantum mechanical accuracy albeit at much lower computational cost than the currently used density functional theory methods and (iii) derivation of the kinetics of phenomena taking place in a multi-length-time scale window to obtain an overall view of the dynamics of the process. This article is part of a discussion meeting issue 'Supercomputing simulations of advanced materials'.

Two-Step Dry Gel Method Produces MgAPO-11 with Low Aspect Ratio and Improved Catalytic Performance in the Conversion of Methanol to Hydrocarbons

In this article, the synthesis, characterization and catalytic performance of three MgAPO-11 catalysts with distinct crystal morphologies (sunflower, ball and candy) are presented. Among the three samples, the candy-like MgAPO-11-C, with high crystallinity and uniform particle size (of about 1 µm), was synthesized for the first time by using a unique two-step dry gel method. Despite the similar acid strength of the three samples, the different and distinct morphologies of the catalysts resulted in very different methanol-to-hydrocarbons (MTH) performances. In particular, the candy-like MgAPO-11-C presented the best MTH performance with the highest total conversion capacity (4.4 gMeOH·gcatalyst−1 h−1) and the best selectivity to C5+ aliphatics (64%).

MAPO-18 Catalysts for the Methanol to Olefins Process: Influence of Catalyst Acidity in a High-Pressure Syngas (CO and H2) Environment

The transition from integrated petrochemical complexes toward decentralized chemical plants utilizing distributed feedstocks calls for simpler downstream unit operations. Less separation steps are attractive for future scenarios and provide an opportunity to design the next-generation catalysts, which function efficiently with effluent reactant mixtures. The methanol to olefins (MTO) reaction constitutes the second step in the conversion of CO2, CO, and H2 to light olefins. We present a series of isomorphically substituted zeotype catalysts with the AEI topology (MAPO-18s, M = Si, Mg, Co, or Zn) and demonstrate the superior performance of the M(II)-substituted MAPO-18s in the conversion of MTO when tested at 350 °C and 20 bar with reactive feed mixtures consisting of CH3OH/CO/CO2/H2. Co-feeding high pressure H2 with methanol improved the catalyst activity over time, but simultaneously led to the hydrogenation of olefins (olefin/paraffin ratio < 0.5). Co-feeding H2/CO/CO2/N2 mixtures with methanol revealed an important, hitherto undisclosed effect of CO in hindering the hydrogenation of olefins over the Brønsted acid sites (BAS). This effect was confirmed by dedicated ethene hydrogenation studies in the absence and presence of CO co-feed. Assisted by spectroscopic investigations, we ascribe the favorable performance of M(II)APO-18 under co-feed conditions to the importance of the M(II) heteroatom in altering the polarity of the M-O bond, leading to stronger BAS. Comparing SAPO-18 and MgAPO-18 with BAS concentrations ranging between 0.2 and 0.4 mmol/gcat, the strength of the acidic site and not the density was found to be the main activity descriptor. MgAPO-18 yielded the highest activity and stability upon syngas co-feeding with methanol, demonstrating its potential to be a next-generation MTO catalyst.

Real-time regeneration of a working zeolite monitored via operando X-ray diffraction and crystallographic imaging: how coke flees the MFI framework

X-ray diffraction is used to investigate regeneration of an H-ZSM-5 zeolite catalyst used in the conversion of methanol to hydrocarbons.

Improved lifetime and stability of copper species in hierarchical, copper-incorporated CuSAPO-34 verified by catalytic model reactions

The first successful synthesis of hierarchical CuSAPO-34 (3.9 wt% Cu) is reported using the polymer Pluronic F127 as a mesoporous structure directing agent (SDA). X-Ray absorption spectroscopy (XAS) revealed single site Cu2+ with 4 nearest oxygen neighbours at 1.96 Å. A catalytic model reaction, the selective reduction of NO with different sized hydrocarbons as reductants, explained that Cu2+ is accessible and reactive in both micro- and mesopores of the hierarchical CuSAPO-34. The presence of mesopores resulted in superior lifetime of the hierarchical CuSAPO-34 in the catalytic model reaction, selective oxidation of propene.

Designing Multi-Dopant Species in Microporous Architectures to Probe Reaction Pathways in Solid-Acid Catalysis

The introduction of two distinct dopants in a microporous zeotype framework can lead to the formation of isolated, or complementary catalytically active sites. Careful selection of dopants and framework topology can facilitate enhancements in catalysts efficiency in a range of reaction pathways, leading to the use of sustainable precursors (bioethanol) for plastic production. In this work we describe our unique synthetic design procedure for creating a multi-dopant solid-acid catalyst (MgSiAPO-34), designed to improve and contrast with the performance of SiAPO-34 (mono-dopant analog), for the dehydration of ethanol to ethylene. We employ a range of characterization techniques to explore the influence of magnesium substitution, with specific attention to the acidity of the framework. Through a combined catalysis, kinetic analysis and computational fluid dynamics (CFD) study we explore the reaction pathway of the system, with emphasis on the improvements facilitated by the multi-dopant MgSiAPO-34 species. The experimental data supports the validation of the CFD results across a range of operating conditions; both of which supports our hypothesis that the presence of the multi-dopant solid acid centers enhances the catalytic performance. Furthermore, the development of a robust computational model, capable of exploring chemical catalytic flows within a reactor system, affords further avenues for enhancing reactor engineering and process optimisation, toward improved ethylene yields, under mild conditions.

General scaling relations and prediction of transition state energies in CHA/AlPO-34-structured zeolite catalysis related to the methanol-to-olefins conversion

Scaling relations of transition state (TS) energies with the acid strength were established. The inherent scaling relations and the acidity sensitivity dependence on charge variation enable fast prediction of TS energies in zeolite catalysis.

Ti-Based Catalysts and Photocatalysts: Characterization and Modeling

This perspective article aims to underline how cutting-edge synchrotron radiation spectroscopies such as extended X-ray absorption spectroscopy (EXAFS), X-ray absorption near edge structure (XANES), high resolution fluorescence detected (HRFD) XANES, X-ray emission spectroscopy (XES) and resonant inelastic X-ray scattering (RIXS) have played a key role in the structural and electronic characterization of Ti-based catalysts and photocatalysts, representing an important additional value to the outcomes of conventional laboratory spectroscopies (UV-Vis, IR, Raman, EPR, NMR etc.). Selected examples are taken from the authors research activity in the last two decades, covering both band-gap and shape engineered TiO₂ materials and microporous titanosilicates (ETS-10, TS-1 and Ti-AlPO-5). The relevance of the state of the art simulation techniques as a support for experiments interpretation is underlined for all the reported examples.