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Atomically Dispersed Metals on Well-Defined Supports including Zeolites and Metal–Organic Frameworks: Structure, Bonding, Reactivity, and Catalysis
When metals in supported catalysts are atomically dispersed, they are usually cationic and bonded chemically to supports. Investigations of noble metals in this class are growing rapidly, leading to discoveries of catalysts with new properties. Characterization of these materials is challenging because the metal atoms reside on surfaces that are typically nonuniform in composition and structure. We posit that understanding of structures and catalytic properties of these materials is emerging most strongly from investigations of structurally uniform catalysts (metal atoms dispersed on crystalline supports) which can be characterized incisively with atomic-resolution electron microscopy, X-ray absorption spectroscopy, and infrared spectroscopy, bolstered by density functional theory. We assess the literature of such catalysts supported on zeotype materials, metal–organic frameworks, and covalent organic frameworks. Finally, assessing characterization, reactivity, and catalytic performance of catalysts for oxidation, hydrogenation, the water–gas shift reaction, and others, we consider metal–support interactions and ligand effects for various metal–support combinations, evaluating the degree of structural uniformity of exemplary catalysts and summarizing structure–reactivity and structure–catalytic property relationships.
Neutron Scattering Studies of Heterogeneous Catalysis
Not Available
Sustainable H 2 -Rich Syngas Production via Microwave-Assisted vs Conventional Catalysis of Pinewood
Catalytic gasification of biomass is a promising method for producing hydrogen-rich syngas, which is a valuable resource for cleanenergy applications. In this study, microwave-assisted biomass gasification was compared with conventional thermally driven biomass gasification using pinewood as the biomass without the use of external gasifying agents (such as air, steam, and CO 2 ), under non-catalytic and catalytic conditions. The catalysts consisted of either an iron or a nickel catalyst, and the pinewood used as biomass contained 42% oxygen. This comparative analysis explores the differences in reaction chemistry, product yields, and the role of key reactions such as the water gas shift (WGS) reaction, Boudouard reaction, etc. The gas-phase and liquid-phase products were analyzed using online gas chromatography, and the fresh and spent catalysts were analyzed using X-ray diffraction (XRD) techniques. It was found that microwave-assisted gasification offers advantages in terms of enhanced reaction efficiency, catalyst stability, and hydrogen yield. For the microwave-assisted reaction, the gas yield reached 87%, the char yield was 12.1%, and the tar yield was less than 1% (0.793%) at 550 °C. In contrast, thermal-assisted gasification using the same catalyst produced a gas yield of 85.796%, char yield of 11.438%, and higher tar yield of 2.8% at 900 °C. The higher microwave-assisted performance was attributed to faster heating and better control over reaction conditions, higher reaction rates, and more favorable conditions for hydrogen production.
Aerobic Partial Oxidation of Alkanes Using Photodriven Iron Catalysis
Photodriven oxidations of alkanes in trifluoroacetic acid using commercial and synthesized Fe(III) sources as catalyst precursors and dioxygen (O 2 ) as the terminal oxidant are reported. The reactions produce alkyl esters and occur at ambient temperature in the presence of air, and catalytic turnover is observed for the oxidation of methane in a pure O 2 atmosphere. Under optimized conditions, approximately 17% conversion of methane to methyl trifluoroacetate at more than 50% selectivity is observed. Furthermore, it is demonstrated that methyl trifluoroacetate is stable under catalytic conditions, and thus overoxidized products are not formed through secondary oxidation of methyl trifluoroacetate.
Regioselective Hydrosilylation Catalysis with Supported Well-Defined Pt(0) Complexes: Effects of Surface Anions and Phosphenium Ligands
Achieving stable, selective single-atom catalysts is challenging because localsurface-site structures are difficult to control. Surface organometallic chemistry and organic−inorganic hybrid materials offer partial solutions, but applications to supporting zero-valent metals are limited. We demonstrate that well-defined, ionically bound N-heterocyclic phosphenium ([NHP] + ) ligands can be generated on silylium-functionalized sulfated zirconia ([ i Pr 3 Si][SZO]). These surface-bound [NHP][SZO] ligands coordinate Pt(0) centers, forming [(NHP)Pt(0)L][SZO] precatalysts that are highly active for alkyne hydrosilylation. Systematic studies reveal that sterically bulky aromatic ligands enhance regioselectivity, achieving performances comparable to molecular Pt catalysts. Further, more-coordinating anions support more-regioselective precatalysts; therefore, SZO supports more-selective species than weaker-coordinating Al(OC(CF 3 ) 3 ) 3 - functionalized silica, a trend confirmed by molecular analogues. These results demonstrate that both the ligand and support control catalytic behavior and enable solid-state structure− activity relationships.
Manipulating the Rate-Limiting Step in Water Oxidation Catalysis by Ruthenium Bipyridine–Dicarboxylate Complexes
In order to gain a deeper mechanistic understanding of water oxidation by [(bda)Ru(L) 2 ] catalysts (bdaH 2 = [2,2'-bipyridine]-6,6'-dicarboxylic acid; L = pyridine-type ligand), a series of modified catalysts with one and two trifluoromethyl groups in the 4 position of the bda 2– ligand was synthesized and studied using stopped-flow kinetics. The additional $-$CF 3 groups increased the oxidation potentials for the catalysts and enhanced the rate of electrocatalytic water oxidation at low pH. Stopped-flow measurements of cerium(IV)-driven water oxidation at pH 1 revealed two distinct kinetic regimes depending on catalyst concentration. At relatively high catalyst concentration (ca. ≥10 –4 M), the rate-determining step (RDS) was a proton-coupled oxidation of the catalyst by cerium(IV) with direct kinetic isotope effects (KIE > 1). At low catalyst concentration (ca. ≤10 –6 M), the RDS was a bimolecular step with k H /k D ≈ 0.8. The results support a catalytic mechanism involving coupling of two catalyst molecules. The rate constants for both RDSs were determined for all six catalysts studied. The presence of $-$CF 3 groups had inverse effects on the two steps, with the oxidation step being fastest for the unsubstituted complexes and the bimolecular step being faster for the most electron-deficient complexes. Finally, though the axial ligands studied here did not significantly affect the oxidation potentials of the catalysts, the nature of the ligand was found to be important not only in the bimolecular step but also in facilitating electron transfer from the metal center to the sacrificial oxidant.
Zirconium Metal–Organic Frameworks Assembled from Pd and Pt P N N N P Pincer Complexes: Synthesis, Postsynthetic Modification, and Lewis Acid Catalysis
Abstract not provided
O–O Radical Coupling: From Detailed Mechanistic Understanding to Enhanced Water Oxidation Catalysis
Not Available
Role of Enzyme and Active Site Conformational Dynamics in the Catalysis by α-Amylase Explored with QM/MM Molecular Dynamics
Not Available
Invariant Molecular Representations for Heterogeneous Catalysis
Catalyst screening is a critical step in the discovery and development of heterogeneous catalysts, which are vital for a wide range of chemical processes. In recent years, computational catalyst screening, primarily through density functional theory (DFT), has gained significant attention as a method for identifying promising catalysts. However, the computation of adsorption energies for all likely chemical intermediates present in complex surface chemistries is computationally intensive and costly due to the expensive nature of these calculations and the intrinsic idiosyncrasies of the methods or data sets used. This study introduces a novel machine learning (ML) method to learn adsorption energies from multiple DFT functionals by using invariant molecular representations (IMRs). To do this, we first extract molecular fingerprints for the reaction intermediates and later use a Siamese-neural-network-based training strategy to learn invariant molecular representations or the IMR across all available functionals. Our Siamese network-based representations demonstrate superior performance in predicting adsorption energies compared with other molecular representations. Notably, when considering mean absolute values of adsorption energies as 0.43 eV (PBE-D3), 0.46 eV (BEEF-vdW), 0.81 eV (RPBE), and 0.37 eV (scan+rVV10), our IMR method has achieved the lowest mean absolute errors (MAEs) of 0.18 0.10, 0.16, and 0.18 eV, respectively. These results emphasize the superior predictive capacity of our Siamese network-based representations. The empirical findings in this study illuminate the efficacy, robustness, and dependability of our proposed ML paradigm in predicting adsorption energies, specifically for propane dehydrogenation on a platinum catalyst surface.
Large-Scale First-Principles Molecular Dynamics Simulations with Electrostatic Embedding: Application to Acetylcholinesterase Catalysis
Enzymes are complicated solvated systems that typically require many atoms to simulate their function with any degree of accuracy. We have recently developed numerical techniques for large scale First-Principles molecular dynamics simulations and applied them to study the enzymatic reaction catalyzed by acetylcholinesterase. We carried out Density functional theory calculations for a quantum mechanical (QM) sub- system consisting of 612 atoms with an O(N) complexity finite-difference approach. The QM sub-system is embedded inside an external potential field representing the electrostatic effect due to the environment. We obtained finite temperature sampling by First-Principles molecular dynamics for the acylation reaction of acetylcholine catalyzed by acetylcholinesterase. Our calculations shows two energies barriers along the reaction coordinate for the enzyme catalyzed acylation of acetylcholine. In conclusion, the second barrier (8.5 kcal/mole) is rate-limiting for the acylation reaction and in good agreement with experiment.