Search for: All records

Abstract In the past, Cu‐oxo or ‐hydroxy clusters hosted in zeolites have been suggested to enable the selective conversion of methane to methanol, but the impact of the active site's stoichiometry and structure on methanol production is still poorly understood. Herein, we apply theoretical modeling in conjunction with experiments to study the impact of these two factors on partial methane oxidation in the Cu‐exchanged zeolite SSZ‐13. Phase diagrams developed from first‐principles suggest that Cu‐hydroxy or Cu‐oxo dimers are stabilized when O₂or N₂O are used to activate the catalyst, respectively. We confirm these predictions experimentally and determine that in a stepwise conversion process, Cu‐oxo dimers can convert twice as much methane to methanol compared to Cu‐hydroxyl dimers. Our theoretical models rationalize how Cu‐di‐oxo dimers can convert up to two methane molecules to methanol, while Cu‐di‐hydroxyl dimers can convert only one methane molecule to methanol per catalytic cycle. These findings imply that in Cu clusters, at least one oxo group or two hydroxyl groups are needed to convert one methane molecule to methanol per cycle. This simple structure–activity relationship allows to intuitively understand the potential of small oxygenated or hydroxylated transition metal clusters to convert methane to methanol. 

Liquid crystals (LCs), when supported on reactive surfaces, undergo changes in ordering that can propagate over distances of micrometers, thus providing a general and facile mechanism to amplify atomic-scale transformations on surfaces into the optical scale. While reactions on organic and metal substrates have been coupled to LC ordering transitions, metal oxide substrates, which offer unique catalytic activities for reactions involving atmospherically important chemical species such as oxidized sulfur species, have not been explored. Here we investigate this opportunity by designing LCs that contain 4′-cyanobiphenyl-4-carboxylic acid (CBCA) and respond to surface reactions triggered by parts-per-billion concentrations of SO2 gas on anatase (101) substrates. We used electronic structure calculations to predict that the carboxylic acid group of CBCA binds strongly to anatase (101) in a perpendicular orientation, a prediction that we validated in experiments in which CBCA (0.005 mol%) was doped into a LC (4’-n-pentyl-4-biphenylcarbonitrile). Both experiment and computational modeling further demonstrated that SO3-like species, produced by a surface-catalyzed reaction of SO2 with H2O on anatase (101), displace CBCA from the anatase surface, resulting in an orientational transition of the LC. Experiments also reveal the LC response to be highly selective to SO2 over other atmospheric chemical species (including H2O, NH3, H2S, and NO2), in agreement with our computational predictions for anatase (101) surfaces. Overall, we establish that the catalytic activities of metal oxide surfaces offer the basis of a new class of substrates that trigger LCs to undergo ordering transitions in response to chemical species of relevance to atmospheric chemistry. 

Cu-Exchanged zeolites are promising materials for the selective conversion of methane to methanol. Their activity is attributed to the presence of small Cu-oxo and Cu-hydroxy clusters, but the nature of active centers in various zeolite structures is still under debate. In this contribution, we combine time dependent density functional theory with spin–orbit coupling to predict the optical spectra of various Cu monomers and dimers in SSZ-13. We furthermore compare theoretical results to experimental measurements and find that the presence of Cu-hydroxy dimers and Cu monomers could potentially explain the experimentally observed UV-vis-NIR spectra. 

Computational methods can provide first-principles insights into the thermochemistry and kinetics of reactions at interfaces, but this capability has not been widely leveraged to design soft materials that respond selectively to chemical species. Here we address this opportunity by demonstrating the design of micrometer-thick liquid crystalline films supported on metal-perchlorate surfaces that exhibit selective orientational responses to targeted oxidizing gases. Initial electronic structure calculations predicted Mn 2+ , Co 2+ , and Ni 2+ to be promising candidate surface binding sites that (1) coordinate with nitrile-containing mesogens to orient liquid crystal (LC) phases and (2) undergo redox-triggered reactions upon exposure to humid O 3 leading to a change in the strength of binding of the nitrile group to the surface. These initial predictions were validated by experimental observations of orientational transitions of nitrile-containing LCs upon exposure to air containing parts-per-billion concentrations of O 3 . Additional first-principles calculations of reaction free energies of metal salts and oxidizing gases predicted that the same set of metal cations, if patterned on surfaces at distinct spatial locations, would provide LC responses that allow Cl 2 and O 3 to be distinguished while not responding to environmental oxidants such as O 2 and NO 2 . Experimental results are provided to support this prediction, and X-ray diffraction measurements confirmed that the experimentally observed LC responses can be understood in terms of the relative thermodynamic driving force for formation of MnO 2 , CoOOH, or NiOOH from the corresponding metal cation binding sites in the presence of humid O 3 and Cl 2 . 

The development of responsive soft materials with tailored functional properties based on the chemical reactivity of atomically precise inorganic interfaces has not been widely explored. In this communication, guided by first-principles calculations, we design bimetallic surfaces comprised of atomically thin Pd layers deposited onto Au that anchor nematic liquid crystalline phases of 4′- n -pentyl-4-biphenylcarbonitrile (5CB) and demonstrate that the chemical reactivity of these bimetallic surfaces towards Cl 2 gas can be tuned by specification of the composition of the surface alloy. Specifically, we use underpotential deposition to prepare submonolayer to multilayers of Pd on Au and employ X-ray photoelectron and infrared spectroscopy to validate computational predictions that binding of 5CB depends strongly on the Pd coverage, with ∼0.1 monolayer (ML) of Pd sufficient to cause the liquid crystal (LC) to adopt a perpendicular binding mode. Computed heats of dissociative adsorption of Cl 2 on PdAu alloy surfaces predict displacement of 5CB from these surfaces, a result that is also confirmed by experiments revealing that 1 ppm Cl 2 triggers orientational transitions of 5CB. By decreasing the coverage of Pd on Au from 1.8 ± 0.2 ML to 0.09 ± 0.02 ML, the dynamic response of 5CB to 1 ppm Cl 2 is accelerated 3X. Overall, these results demonstrate the promise of hybrid designs of responsive materials based on atomically precise interfaces formed between hard bimetallic surfaces and soft matter. 

Chemoresponsive liquid crystal (LC) sensors are promising platforms for the detection of vapor-phase analytes. Understanding the transport of analyte molecules within LC films could guide the design of LC sensors with improved selectivity. In this work, we use molecular dynamics simulations to quantify the partitioning and diffusion of nine small-molecule analytes, including four common atmospheric pollutants, in model systems representative of LC sensors. We first parameterize all-atom models for 4-cyano-4′-pentylbiphenyl (5CB), a mesogen typically used for LC sensors, and all analytes. We validate these models by reproducing experimentally determined 5CB structural parameters, 5CB diffusivity, and analyte Henry's law constants in 5CB. Using the all-atom models, we calculate analyte solvation free energies and diffusivities in bulk 5CB. These simulation-derived quantities are then used to parameterize an analytical mass-transport model to predict sensor activation times. These results demonstrate that differences in analyte–LC interactions can translate into distinct activation times to distinguish activation by different analytes. Finally, we quantify the effect of LC composition by calculating analyte solvation free energies in TL205, a proprietary LC mixture. These calculations indicate that varying the LC composition can modulate activation times to further improve sensor selectivity. These results thus provide a computational framework for guiding LC sensor design by using molecular simulations to predict analyte transport as a function of LC composition.