Review on Hydrodesulfurization over Zeolite-Based Catalysts

Interplay Between Ni and Brønsted and Lewis Acid Sites in the Hydrodesulfurization of Dibenzothiophene

Ni-MoS2/γ-Al2O3 catalysts are commonly used in hydrotreating to enhance fossil fuel quality. The extensive research on these catalysts reveals a gap in understanding the role of Ni, often underestimated as an inactive sulfide phase or just a MoS2 promoter. In this work, we focused on analyzing whether well-dispersed supported nickel nanoparticles can be active in the hydrodesulfurization of dibenzothiophene. We dispersed Ni by Strong Electrostatic Adsorption (SEA) method across four supports with different types of acidity: silica (~ neutral acidity), γ-Al2O3 (Lewis acidity), H+-Y zeolite, and microporous-mesoporous H+-Y zeolite (both with Brønsted-Lewis acidity). Our findings reveal that Ni is indeed active in dibenzothiophene hydrodesulfurization, even with alumina and silica as supports, although their catalytic activity declines abruptly in the first hours. Contrastingly, the acid nature of zeolites imparts sustained stability and performance, attributed to robust metal-support interactions. The efficacy of the SEA method and the added mesoporosity in zeolites further amplify catalytic efficiency. Overall, we demonstrate that Ni nanoparticles may perform as a hydrogenating metal in the same manner as noble metals such as Pt and Pd perform in hydrodesulfurization. We discuss some of the probable reasons for such performance and remark on the role of Ni in hydrotreatment.

Hydrodesulfurization of Dibenzothiophene: A Machine Learning Approach

The hydrodesulfurization (HDS) process is widely used in the industry to eliminate sulfur compounds from fuels. However, removing dibenzothiophene (DBT) and its derivatives is a challenge. Here, the key aspects that affect the efficiency of catalysts in the HDS of DBT were investigated using machine learning (ML) algorithms. The conversion of DBT and selectivity was estimated by applying Lasso, Ridge, and Random Forest regression techniques. For the estimation of conversion of DBT, Random Forest and Lasso offer adequate predictions. At the same time, regularized regressions have similar outcomes, which are suitable for selectivity estimations. According to the regression coefficient, the structural parameters are essential predictors for selectivity, highlighting the pore size, and slab length. These properties can connect with aspects like the availability of active sites. The insights gained through ML techniques about the HDS catalysts agree with the interpretations of previous experimental reports.

Uncovering the Critical Factors that Enable Extractive Desulfurization of Fuels in Ionic Liquids and Deep Eutectic Solvents from Simulations

Environmental regulatory agencies have implemented stringent restrictions on the permissible levels of sulfur compounds in fuel to reduce harmful emissions and improve air quality. Problematically, traditional desulfurization methods have shown low effectiveness in the removal of refractory sulfur compounds, e.g., thiophene (TS), dibenzothiophene (DBT), and 4-methyldibenzothiophene (MDBT). In this work, molecular dynamics (MD) simulations and free energy perturbation (FEP) have been applied to investigate the use of ionic liquids (ILs) and deep eutectic solvents (DESs) as efficient TS/DBT/MDBT extractants. For the IL simulations, the selected cation was 1-butyl-3-methylimidazolium [BMIM] and the anions included chloride [Cl], thiocyanate [SCN], tetrafluoroborate [BF₄], hexafluorophosphate [PF₆], and bis(trifluoromethylsulfonyl)amide [NTf₂]. The DESs were composed of choline chloride with ethylene glycol (CCEtg) or with glycerol (CCGly). Calculation of excess chemical potentials predicted the ILs to be more promising extractants with energies lower by 1-3 kcal/mol compared to DESs. Increasing IL anion size was positively correlated to enhanced solvation of S-compounds, which was influenced by energetically dominant solute-anion interactions and favorable solute-[BMIM] π-π stacking. For the DESs, the solvent components offered a range of synergistic, yet comparatively weaker, electrostatic interactions that included hydrogen bonding and cation-π interactions. An in-depth analysis of the structure of IL and DES systems is presented, along with a discussion of the critical factors behind experimental trends of S-compound extraction efficiency.

A 3D extra-large-pore zeolite enabled by 1D-to-3D topotactic condensation of a chain silicate

Zeolites are microporous silicates with a large variety of applications as catalysts, adsorbents, and cation exchangers. Stable silica-based zeolites with increased porosity are in demand to allow adsorption and processing of large molecules but challenge our synthetic ability. We report a new, highly stable pure silica zeolite called ZEO-3, which has a multidimensional, interconnected system of extra-large pores open through windows made by 16 and 14 silicate tetrahedra, the least dense polymorph of silica known so far. This zeolite was formed by an unprecedented one-dimensional to three-dimensional (1D-to-3D) topotactic condensation of a chain silicate. With a specific surface area of more than 1000 square meters per gram, ZEO-3 showed a high performance for volatile organic compound abatement and recovery compared with other zeolites and metal-organic frameworks.

Metal Sites in Zeolites: Synthesis, Characterization, and Catalysis

Zeolites with ordered microporous systems, distinct framework topologies, good spatial nanoconfinement effects, and superior (hydro)thermal stability are an ideal scaffold for planting diverse active metal species, including single sites, clusters, and nanoparticles in the framework and framework-associated sites and extra-framework positions, thus affording the metal-in-zeolite catalysts outstanding activity, unique shape selectivity, and enhanced stability and recyclability in the processes of Brønsted acid-, Lewis acid-, and extra-framework metal-catalyzed reactions. Especially, thanks to the advances in zeolite synthesis and characterization techniques in recent years, zeolite-confined extra-framework metal catalysts (denoted as metal@zeolite composites) have experienced rapid development in heterogeneous catalysis, owing to the combination of the merits of both active metal sites and zeolite intrinsic properties. In this review, we will present the recent developments of synthesis strategies for incorporating and tailoring of active metal sites in zeolites and advanced characterization techniques for identification of the location, distribution, and coordination environment of metal species in zeolites. Furthermore, the catalytic applications of metal-in-zeolite catalysts are demonstrated, with an emphasis on the metal@zeolite composites in hydrogenation, dehydrogenation, and oxidation reactions. Finally, we point out the current challenges and future perspectives on precise synthesis, atomic level identification, and practical application of the metal-in-zeolite catalyst system.

Porous liquids - the future is looking emptier

The development of microporosity in the liquid state is leading to an inherent change in the way we approach applications of functional porosity, potentially allowing access to new processes by exploiting the fluidity of these new materials. By engineering permanent porosity into a liquid, over the transient intermolecular porosity in all liquids, it is possible to design and form a porous liquid. Since the concept was proposed in 2007, and the first examples realised in 2015, the field has seen rapid advances among the types and numbers of porous liquids developed, our understanding of the structure and properties, as well as improvements in gas uptake and molecular separations. However, despite these recent advances, the field is still young, and with only a few applications reported to date, the potential that porous liquids have to transform the field of microporous materials remains largely untapped. In this review, we will explore the theory and conception of porous liquids and cover major advances in the area, key experimental characterisation techniques and computational approaches that have been employed to understand these systems, and summarise the investigated applications of porous liquids that have been presented to date. We also outline an emerging discovery workflow with recommendations for the characterisation required at each stage to both confirm permanent porosity and fully understand the physical properties of the porous liquid.