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At least 109 records · Page 6

Diffusion-mediated passing of molecular species in linear nanopores constrained by orientational alignment

For diffusion-mediated catalytic conversion reactions in materials with narrow linear nanopores, e.g., mesoporous silica MCM-41, a key parameter is the propensity for product species to be able to pass reactant species and thus to efficiently exit the pore. For elongated species, this can require orientational alignment with the pore axis. In this work, we perform benchmark analyses for such solution-phase systems where one of these species is elongated in order to quantify the dependence of this passing propensity, P, on pore diameter and on the rotational diffusion coefficient, Dr, of the elongated species. In particular, we consider the passing of a spherical and an elongated spherocylindrical shaped species in a cylindrical pore in an implicit solvent, where these species cannot overlap. Passing is mediated by diffusive Brownian motion of these species as described by strongly damped Langevin dynamics. We quantify scaling of P for pore width just above the threshold where passing is sterically blocked, and also reveal a significant decrease in P for lower Dr. We also consider the dependence of P on the aspect ratio of the elongated species and obtain an exact result in the limiting regime of large aspect ratio.

Brownian motion↗

Runtime performance of a GAMESS quantum chemistry application offloaded to GPUs

Summary Computational chemistry is at the forefront of solving urgent societal problems, such as polymer upcycling and carbon capture. The complexity of modeling these processes at appropriate length and time scales is mainly manifested in the number and types of chemical species involved in the reactions and may require models of several thousand atoms and large basis sets to accurately capture the chemical complexity and heterogeneity in the physical and chemical processes. The quantum chemistry package General Atomic and Molecular Electronic Structure System (GAMESS) has a wide array of methods that can efficiently and accurately treat complex chemical systems. In this work, we have used the GAMESS Effective Fragment Molecule Orbital (EFMO) method for electronic structure calculation of a challenging mesoporous silica nanoparticle (MSN) model surrounded by about 4700 water molecules to investigate the strong scaling and GPU offloading on hybrid CPU‐GPU nodes. Experiments were performed on the Perlmutter platform at the National Energy Research Scientific Computing Center. Good strong scaling and load balancing have been observed on up to 88 hybrid nodes for different settings of the execution parameters for the calculation considered here. When GPUs are oversubscribed by offloading work from multiple CPU processes, using the NVIDIA multi‐process service (MPS) has consistently reduced time to solution and energy consumed. Additionally, for some configuration parameter settings, oversubscription with MPS improved performance by up to 5.8% over the case without oversubscription.

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High-Performance CO 2 Capture from Air by Harnessing the Power of CaO- and Superbase-Ionic-Liquid-Engineered Sorbents

Direct air capture (DAC) of CO 2 by solid porous materials represents an attractive “negative emission” technology. However, state-of-the-art sorbents based on supported amines still suffer from unsolved high energy consumption and stability issues. For this work, taking clues from the CO 2 interaction with superbase-derived ionic liquids (SILs), high-performance and tunable sorbents in DAC of CO 2 was developed by harnessing the power of CaO- and SIL-engineered sorbents. Deploying mesoporous silica as the substrate, a thin CaO layer was first introduced to consume the surface-OH groups, and then active sites with different basicities (e. g., triazolate and imidazolate) were introduced as a uniformly distributed thin layer. The as-obtained sorbents displayed high CO 2 uptake capacity via volumetric (at 0.4 mbar) and breakthrough test (400 ppm CO 2 source), rapid interaction kinetics, facile CO 2 releasing, and stable sorption/desorption cycles. Operando diffuse reflectance infrared Fourier transformation spectroscopy (DRIFTS) analysis under simulated air atmosphere and solid-state NMR under 13 CO 2 atmosphere demonstrated the critical roles of the SIL species in low-concentration CO 2 capture. The fundamental insights obtained in this work provide guidance on the development of high-performance sorbents in DAC of CO 2 by leveraging the combined advantages of porous solid scaffolds and the unique features of CO 2 -philic ionic liquids.

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Fluorescence Microscopic Investigations of Molecular Dynamics in Self–Assembled Nanostructures

Many analytical methods employ self-assembled nanostructured materials as chemical recognition media. Molecular permeation through these materials exhibits unique selectivity owing to nanoconfinement-induced enhancement of permeant–nanostructure interactions. This Personal Account introduces our efforts to investigate the detailed dynamics of single or a small number of molecules in nanostructured materials. Here, we developed new experimental and analysis approaches built upon laser-based fluorescence microscopy to measure the detailed translational and orientational dynamics of molecules diffusing in horizontally-oriented, cylindrical nanostructures, including surfactant micelles, silica mesopores, block copolymer microdomains, and bolaamphiphile-based organic nanotubes. Our studies clarified nanoscale details on the structural/chemical heterogeneity of the nanostructures, and their impacts on molecular mass transport dynamics.

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Densification of non-radioactive porous siliceous particles loaded with cesium potassium copper hexacyanoferrate by spark plasma sintering

In the development of a conditioning process for cesium-bearing sorbents from the decontamination of aqueous waste streams, the treatment of a granular material composed of (Cs,K) 2 CuFe(CN) 6 loaded onto mesoporous silica particles has been investigated in an additive-free two-step conditioning process involving (i) calcination at 1000 °C to remove volatile species and (ii) densification by spark plasma sintering. A 92.0 % dense pellet was obtained after 10 min sintering at 850 °C under 100 MPa. Density and microstructural measurements indicate that densification is first driven by the viscous flow of a vitreous phase containing Cs, formed during calcination. Additionally, the density of the sample then increases further during sintering by grain boundary diffusion. However, a limited but non negligible part of cesium is lost during densification.

36 MATERIALS SCIENCE↗

Combining fast magic angle spinning dynamic nuclear polarization with indirect detection to further enhance the sensitivity of solid-state NMR spectroscopy

Dynamic nuclear polarization (DNP) and indirect detection are two commonly applied approaches for enhancing the sensitivity of solid-state NMR spectroscopy. However, their use in tandem has not yet been investigated. With the advent of low-temperature fast magic angle spinning (MAS) probes with 1.3-mm diameter rotors capable of MAS at 40 kHz it becomes feasible to combine these two techniques. In this study, we performed DNP-enhanced 2D indirectly detected heteronuclear correlation (idHETCOR) experiments on 13 C, 15 N, 113 Cd and 89 Y nuclei in functionalized mesoporous silica, CdS nanoparticles, and Y 2 O 3 nanoparticles. The sensitivity of the 2D idHETCOR experiments was compared with those of DNP-enhanced directly-detected 1D cross polarization (CP) and 2D HETCOR experiments performed with a standard 3.2-mm rotor. Due to low CP polarization transfer efficiencies and large proton linewidth, the sensitivity gains achieved by indirect detection alone were lower than in conventional (non-DNP) experiments. Nevertheless, despite the smaller sample volume the 2D idHETCOR experiments showed better absolute sensitivities than 2D HETCOR experiments for nuclei with the lowest gyromagnetic ratios. Finally, for 89 Y, 2D idHETCOR provided 8.2 times better sensitivity than the 1 D 89 Y-detected CP experiment performed with a 3.2-mm rotor.

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A Review on Direct Air Capture of Carbon Dioxide: Sorbent Materials, Process Engineering, Industrial Scale-Up, and Future Perspectives

The relentless accumulation of anthropogenic greenhouse gases has driven atmospheric carbon dioxide concentrations to approximately 426 ppm, necessitating the aggressive deployment of negative-emission technologies to achieve net zero by 2050. Direct air capture (DAC) offers a scalable, location-independent approach to atmospheric carbon removal; however, it is fundamentally constrained by the significant thermodynamic barriers associated with capturing CO 2 from ultradilute ambient conditions, requiring minimum thermodynamic energy inputs substantially higher than those for postcombustion point sources. This comprehensive review critically examines the technological landscape of DAC, focusing on the interdependent triad of sorbent material design, contactor engineering, and regeneration thermodynamics. We evaluate the fundamental boundaries of adsorption, emphasizing that an optimal adsorption enthalpy and isosteric heat of adsorption must balance the high CO 2 uptake capacity with the energetic penalties of sorbent regeneration. A systematic, comparative analysis of state-of-the-art sorbents is presented, encompassing mesoporous silicas, zeolites, carbon-based materials (CBMs), metal−organic frameworks (MOFs), porous organic polymers (POPs), and polymeric membranes. Special attention is devoted to surface functionalization strategies, particularly amine grafting and impregnation, which transition capture mechanisms from physisorption to chemisorption to enhance selectivity under ambient moisture and low partial pressures. Furthermore, we assess the operational merits of various reactor configurations, including gas−solid, gas−liquid, and membrane contactors, alongside regeneration cycles such as temperature, vacuum, pressure, and moisture swing adsorption. Finally, the review bridges fundamental materials science with industrial application by chronicling the scale-up milestones of pioneering entities and providing a strategic roadmap for advancing DAC technology readiness levels toward global deployment.

Adsorption↗

Porting Fragmentation Methods to Graphical Processing Units Using an OpenMP Application Programming Interface: Offloading the Fock Build for Low Angular Momentum Functions

Here, a framework to offload four-index two-electron repulsion integrals to graphical processing units (GPUs) using OpenMP is discussed. The method has been applied to the Fock build for low angular momentum s and p functions in both the restricted Hartree–Fock (RHF) and in the effective fragment molecular orbital (EFMO) framework. Benchmark calculations for the GPU code for the pure RHF method show an increasing speedup relative to the existing OpenMP CPU code in GAMESS from 1.04 to 52× for clusters of 70–569 water molecules. The parallel efficiency on 24 NVIDIA V100 GPU boards also increases when increasing the system size: from 75 to 94% for water clusters that contain 303–1120 molecules. In the EFMO framework, the GPU Fock build shows a high linear scalability up to 4608 V100s with a parallel efficiency of 96% for calculations on a solvated mesoporous silica nanoparticle system with ~67,000 basis functions.

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The Effective Fragment Molecular Orbital Method: Achieving High Scalability and Accuracy for Large Systems

The effective fragment molecular orbital (EFMO) method has been developed to predict the total energy of a very large molecular system accurately (with respect to the underlying quantum mechanical method) and efficiently by taking advantage of the locality of strong chemical interactions and employing a two-level hierarchical parallelism. The accuracy of the EFMO method is partly attributed to the accurate and robust intermolecular interaction prediction between distant fragments, in particular, the many-body polarization and dispersion effects, which require the generation of static and dynamic polarizability tensors by solving the coupled perturbed Hartree–Fock (CPHF) and time-dependent HF (TDHF) equations, respectively. Solving the CPHF and TDHF equations is the main EFMO computational bottleneck due to the inefficient (serial) and I/O-intensive implementation of the CPHF and TDHF solvers. In this work, the efficiency and scalability of the EFMO method are significantly improved with a new CPU memory-based implementation for solving the CPHF and TDHF equations that are parallelized by either message passing interface (MPI) or hybrid MPI/OpenMP. Here, the accuracy of the EFMO method is demonstrated for both covalently bonded systems and noncovalently bound molecular clusters by systematically examining the effects of basis sets and a key distance-related cutoff parameter, R cut . R cut determines whether a fragment pair (dimer) is treated by the chosen ab initio method or calculated using the effective fragment potential (EFP) method (separated dimers). Decreasing the value of Rcut increases the number of separated (EFP) dimers, thereby decreasing the computational effort. It is demonstrated that excellent accuracy (<1 kcal/mol error per fragment) can be achieved when using a sufficiently large basis set with diffuse functions coupled with a small R cut value. With the new parallel implementation, the total EFMO wall time is substantially reduced, especially with a high number of MPI ranks. Given a sufficient workload, nearly ideal strong scaling is achieved for the CPHF and TDHF parts of the calculation. For the first time, EFMO calculations with the inclusion of long-range polarization and dispersion interactions on a hydrated mesoporous silica nanoparticle with explicit water solvent molecules (more than 15k atoms) are achieved on a massively parallel supercomputer using nearly 1000 physical nodes. In addition, EFMO calculations on the carbinolamine formation step of an amine-catalyzed aldol reaction at the nanoscale with explicit solvent effects are presented.

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Polyethylene in Dead-End Silica Nanopores: Forces and Mobility from Non-Equilibrium Statistical Mechanics and Exchange Spectroscopy Nuclear Magnetic Resonance

Billions of tons of plastic have been produced, and only a small fraction of this has been recycled. Tennakoon et al. [Nature Catalysis 3, 893 (2020)] developed a catalyst that repeatedly cleaves C 10 –C 30 hydrocarbons from the end of a polyethylene chain. The reaction occurs at a Pt nanoparticle at the base of a cylindrical silica mesopore with a diameter of 2 nm and a length of 110 nm. Portions of the polymer situated inside the pore can be differentiated from those outside using 13 C nuclear magnetic resonance (NMR), allowing the dynamics and extent of polymer threading to be monitored using two-dimensional (2D) exchange spectroscopy NMR. Here we construct a Fokker–Planck equation for the polymer dynamics by assuming a reptation diffusivity and a graduated adsorption free energy that depends linearly on the depth of polymer penetration in the pore. The solutions allow us to predict the intensities of the 2D NMR resonances as a function of time. We use the solutions to extract a polymer diffusivity at each temperature and estimate the per-segment desorption free energy, enthalpy, and entropy. Random and systematic errors are examined to test key assumptions in the theory and interpretation of the experiments.

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Catalytic Mechanism of Interfacial Water in the Cycloaddition of Quadricyclane and Diethyl Azodicarboxylate

"On-water" catalysis, the unusual activity of water molecules at the organic solvent-water interface, has been demonstrated in many organic reactions. However, the catalytic mechanism has remained unclear, largely because of the irreproducibility of the organic-water interface under the common stirring condition. In this work, the interfacial area was controlled by employing adsorbed water on mesoporous silica nanoparticles as the catalyst. Reliable kinetics of the cycloaddition reaction of quadricyclane and diethyl azodicarboxylate (DEAD) at the toluene-water interface within the nanoparticle pores were measured. Data reveal an Eley-Rideal mechanism, wherein DEAD adsorbs at the toluene-water interface via hydrogen bonds formed with interfacial water, which lower the activation energy of the cycloaddition reaction. The mechanistic insights gained and preparation of surface water in silica pores described herein may facilitate the future design of improved "on-water" catalysts.

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Insights into Waterflooding in Hydrocarbon-Bearing Nanochannels of Varying Cross Sections from Mesoscopic Multiphase Flow Simulations

Waterflooding is one of the geotechnique used to recover fuel sources from nanoporous geological formations. The scientific understanding of the process that involves the multiphase flow of nanoconfined fluids, however, has lagged, mainly due to the complex nanopore geometries and chemical compositions. To enable benchmarked flow of nanoconfined fluids, the architected geomaterials, such as synthesized mesoporous silica with tunable pore shapes and surface chemical properties, are used for designing and conducting experiments and simulations. This work uses a modified many-body dissipative particle dynamics (mDPD) model with accurately calibrated parameters to perform parametric flow simulations for studying the influences of waterflooding driven power, pore shape, surface roughness, and surface wettability on the multiphase flow in heptane-saturated silica nanochannels. Remarkably, up to 80\% reduction in the effective permeability is found for water-driven heptane flow in a baseline 4.5 nm-wide slit channel, when compared with the Hagen–Poiseuille equation. In the 4.5 nm-wide channels with architected surface roughness, the flow rate is found either higher or lower than the baseline case, depending on the shape and size of cross-sections. High wettability of the solid surface to water is essential for achieving high recovery of heptane, regardless of surface roughness. When the solid surface is less wetting or non-wetting to water, the existence of an optimal waterflooding driven power is found to allow for the highest possible recovery. A detailed analysis on the evolution of the transient water-heptane interface in those nanochannels is presented to elucidate the underlying mechanisms that impact or dictate the multiphase flow behaviors.

58 GEOSCIENCES↗

Enhanced Catalytic Performance of a Ce/V Oxo Cluster through Confinement in Mesoporous SBA-15

To increase catalytic efficiency, mesoporous supports have been widely applied to immobilize well-defined metal oxide clusters due to their ability to stabilize highly dispersed clusters. Here, for this study, a redox-active heterometallic Ce 12 V 6 -oxo cluster (CeV) was first presynthesized and then incorporated into mesoporous silica, SBA-15, via a straightforward impregnation method. Scanning transmission electron microscopy (STEM) and Fourier transform infrared spectroscopy (FTIR), in concert with scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDS), verified the successful introduction of the CeV cluster inside the pore of SBA-15. The 51 V magic angle spinning solid-state nuclear magnetic resonance ( 51 V MAS NMR) spectroscopy and differential pair distribution function (dPDF) analysis confirmed the structural integrity of the CeV cluster inside the SBA-15. The composite was then benchmarked for liquid-phase oxidation of 2-chloroethyl ethyl sulfide (CEES) under mild conditions and gas-phase oxidative dehydrogenation (ODH) of propane under high temperatures (up to 550 °C). The catalytic reactivity results demonstrated 8- and 14-fold increase in turnover frequency (TOF) values of the composite (CeV@10SBA-2) than the bulk CeV cluster under the same conditions for CEES oxidation and ODH, respectively. These results highlight the improved reactivity of the catalytically active CeV cluster as attributed to the higher dispersion of the discrete cluster upon immobilization within the SBA-15 support.

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Heterobinuclear Molecular Precursors Direct the Formation of Supported Subnanometer Cu–M Clusters with Tunable Catalytic Behavior

Subnanometer bimetallic clusters hold great promise for catalytic applications due to their unique electronic properties and high surface-to-volume ratios. However, precise control over their composition and size remains a major challenge, particularly for immiscible metal pairs. Here, we report a surface-anchored molecular approach for synthesizing ∼0.7–0.8 nm Cu–M (M = Ru, Mo, W, Fe) bimetallic clusters on mesoporous silica supports, using heterobinuclear N-heterocyclic carbene (NHC)-based complexes as precursors. The NHC ligand functionalized with an alkoxysilane anchor enables robust grafting to the silica interface. Controlled calcination and reduction lead to subnanometer clusters with tunable composition, dictated by the metal–metal bond stability in the precursor. In situ transmission electron microscopy reveals cluster growth proceeds via sintering of adjacent surface-bound units, while elevated temperatures above 300 °C triggering diffusion and phase separation. Catalytic testing in ethylene hydrogenation demonstrates composition-dependent activity and kinetics, with CuRu and CuW clusters exhibiting lower apparent activation energy barriers compared with monometallic Cu nanoparticles. This study establishes a generalizable strategy for the interfacial synthesis of alloyed clusters from molecular precursors and provides mechanistic insight into how precursor design governs nanostructure formation and catalytic behavior.

N-heterocyclic carbene↗

Propane Dehydrogenation Catalyzed by Supported Group IV (Ti, Zr, Hf) Organometallics on Silicon Nitride

Mesoporous silicon nitride (Si 3 N 4 ) enables access to chemisorbed group IV organometallics catalysts active for propane dehydrogenation (PDH) compared to the organometallic analogues on mesoporous silica under the same reaction conditions. The series of Si 3 N 4 -supported materials are active catalysts, (Zr > Hf > Ti k f = 290, 232, and 162 mol mol Metal -1 h -1 at 450 °C with 2% C 3 H 8 in Ar, respectively) with selectivity above 95%, demonstrating additional examples of Ti and Hf systems for PDH. However, the underlying mechanism of the improved performance relative to oxide supported homologues is not well-understood. Characterization of thermally treated samples (DRIFTS, XAS and SSNMR) and computational modeling of this catalyst series was utilized to differentiate between potential amido - (C-H activation along the M-N bond) and imido - (C-H activation along the M=N bond) mechanisms. Due to remaining mechanistic ambiguity, a Ga analogue was synthesized and evaluated for PDH activity as an indirect probe to experimentally differentiate pathways. An inversion of the oxide/nitride performance trend is observed for the Ga congener which does not form a Ga=N bond, most consistent with different mechanisms dictating the performance of the group IV/Si 3 N 4 catalysts vs Ga/Si 3 N 4 .

heterolytic cleavage↗

Stable and Recyclable Photocatalysts of CsPbBr 3 @MSNs Nanocomposites for Photoinduced Electron Transfer RAFT Polymerization

All-inorganic metal halide perovskite CsPbX 3 (X = Cl, Br, I) nanocrystals (NCs) have demonstrated attractive optoelectronic characteristics. However, their photocatalytic properties are limited by their poor stability and easy recombination of photogenerated carriers. Herein, we introduced a CsPbBr 3 @MSNs nanocomposite (CsPbBr 3 NCs embedded in dendritic mesoporous silica nanospheres (MSNs)) as photocatalysts for photoinduced electron transfer reversible addition–fragmentation chain transfer (PET-RAFT) polymerization. In this study, the CsPbBr 3 nanocrystals (~8.1 nm; PLQY of 62 ± 2.1%) were embedded in dendritic MSNs using a nanoconfinement strategy. PET-RAFT polymerization was successfully initiated using the CsPbBr 3 @MSNs nanocomposite as the photocatalyst. Reaction variables, such as catalyst loading, monomer composition, and excitation light wavelengths, were varied to yield polymers with the desired control of molecular weight and dispersity as well as block copolymers with high chain-end fidelity. In addition, the perovskite-based photocatalysts could be readily separated and purified, which allowed effective and rapid recycling of the nanocomposites for multiple polymerization cycles.

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Commodity Thermoplastic Elastomer-Enabled Templated Synthesis of Large-Pore Ordered Mesoporous Materials

Fabrication of ordered mesoporous materials (OMMs) has predominantly relied on templating-based methods. However, these methods are constrained by several limitations, especially the limited pore sizes attainable with commercially available surfactants used as structure-directing agents. To unlock the full potential of the OMMs, it is essential to develop synthetic strategies that facilitate the production of large-pore OMMs using scalable processes and cost-effective precursors. This work demonstrates the use of thermoplastic elastomer (TPE)-derived carbon replicas for synthesizing ordered mesoporous silica (OMS) and metal oxides (OMMOs) via precursor infiltration and template removal. The nanostructural evolution of the resulting inorganic materials was systematically investigated. Specifically, using tetraethyl orthosilicate (TEOS) as a silica precursor, this method can produce an OMS with relatively large pores. To establish the generalizability of this process, the fabrication approach was extended to other commercially available TPEs with varied chemical compositions and molecular weights while consistently resulting in ordered structures. Additionally, this synthetic strategy can be successfully applied to the production of OMMOs, including tin and titanium oxide matrix chemistries, yielding pore sizes of 16.0 and 19.2 nm, respectively. By developing a general method and using low-cost precursors, this work presents a scalable approach for fabricating large-pore OMMs with tunable pore textures and matrix chemistries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Size-Controlled Nanoparticles Embedded in a Mesoporous Architecture Leading to Efficient and Selective Hydrogenolysis of Polyolefins

A catalytic architecture, comprising a mesoporous silica shell surrounding platinum nanoparticles (NPs) supported on a solid silica sphere (mSiO2/Pt-X/SiO2; X is the mean NP diameter), catalyzes hydrogenolysis of melt-phase polyethylene (PE) into a narrow C23-centered distribution of hydrocarbons in high yield using very low Pt loadings (~10 -5 g Pt/g PE). During catalysis, a polymer chain enters a pore and contacts a Pt NP where the C–C bond cleavage occurs and then the smaller fragment exits the pore. mSiO 2 /Pt/SiO 2 resists sintering or leaching of Pt and provides high yields of liquids; however, many structural and chemical effects on catalysis are not yet resolved. Here, we report the effects of Pt NP size on activity and selectivity in PE hydrogenolysis. Time-dependent conversion and yields and a lumped kinetics model based on the competitive adsorption of long vs short chains reveal that the activity of catalytic material is highest with the smallest NPs, consistent with a structure-sensitive reaction. Remarkably, the three mSiO 2 /Pt-X/SiO 2 catalysts give equivalent selectivity. We propose that mesoscale pores in the catalytic architecture template the C 23 -centered distribution, whereas the active Pt sites influence the carbon–carbon bond cleavage rate. This conclusion provides a framework for catalyst design by separating the C–C bond cleavage activity at catalytic sites from selectivity for chain lengths of the products influenced by the structure of the catalytic architecture. The increased activity, selectivity, efficiency, and lifetime obtained using this architecture highlight the benefits of localized and confined environments for isolated catalytic particles under condensed-phase reaction conditions.

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