Machine learning accelerated high-throughput screening of zeolites for the selective adsorption of xylene isomers.

The production of widely used polymers such as polyester currently relies upon the chemical separation of and transformation of xylene isomers. The least valuable but most prevalent isomer is -xylene which can be selectively transformed into the more useful and expensive -xylene isomer using a zeolite catalyst but at a high energy cost. In this work, high-throughput screening of existing and hypothetical zeolite databases containing more than two million structures was performed, using a combination of classical simulation and deep neural network methods to identify promising materials for selective adsorption of -xylene.

Hydration Structures on γ-Alumina Surfaces With and Without Electrolytes Probed by Atomistic Molecular Dynamics Simulations.

A wide range of systems, both engineered and natural, feature aqueous electrolyte solutions at interfaces. In this study, the structure and dynamics of water at the two prevalent crystallographic terminations of gamma-alumina, [110] and [100], and the influence of salts─sodium chloride, ammonium acetate, barium acetate, and barium nitrate on such properties─were investigated using equilibrium molecular dynamics simulations. The resulting interfacial phenomena were quantified from simulation trajectories via atomic density profiles, angle probability distributions, residence times, 2-D density distributions within the hydration layers, and hydrogen bond density profiles.

Strain effects in core-shell PtCo nanoparticles: a comparison of experimental observations and computational modelling.

Strain in Pt nanoalloys induced by the secondary metal has long been suggested as a major contributor to the modification of catalytic properties. Here, we investigate strain in PtCo nanoparticles using a combination of computational modelling and microscopy experiments. We have used a combination of molecular dynamics (MD) and large-scale density functional theory (DFT) for our models, alongside experimental work using annular dark field scanning transmission electron microscopy (ADF-STEM).

Exploring fuel cell cathode materials using ab initio high throughput calculations and validation using carbon supported Pt alloy catalysts.

We employ a combined density functional theory (DFT) and experimental approach to screen different elements (M) and PtM alloys (M = Sc, Y, V, Nb, Ta, Ti, Zr, Hf, Cr, Fe, Ru, Os, Co, Rh, Ir, Ni, Pd, Cu, Ag, Au and Al) for oxygen reduction reaction (ORR) activity and stability. The results of the calculations are validated using a series of carbon supported alloy nanoparticles measured within membrane electrode assembly (MEA) environments. We assess the reliability of descriptors such as surface d-band centre and O adsorption energy as computed from DFT calculations.

Modification of O and CO binding on Pt nanoparticles due to electronic and structural effects of titania supports.

Metal oxide supports often play an active part in heterogeneous catalysis by moderating both the structure and the electronic properties of the metallic catalyst particle. In order to provide some fundamental understanding on these effects, we present here a density functional theory (DFT) investigation of the binding of O and CO on Pt nanoparticles supported on titania (anatase) surfaces. These systems are complex, and in order to develop realistic models, here, we needed to perform DFT calculations with up to ∼1000 atoms.

Ideal versus real: simulated annealing of experimentally derived and geometric platinum nanoparticles.

Platinum nanoparticles find significant use as catalysts in industrial applications such as fuel cells. Research into their design has focussed heavily on nanoparticle size and shape as they greatly influence activity. Using high throughput, high precision electron microscopy, the structures of commercially available Pt catalysts have been determined, and we have used classical and quantum atomistic simulations to examine and compare them with geometric cuboctahedral and truncated octahedral structures.

Perspective: Methods for large-scale density functional calculations on metallic systems.

Current research challenges in areas such as energy and bioscience have created a strong need for Density Functional Theory (DFT) calculations on metallic nanostructures of hundreds to thousands of atoms to provide understanding at the atomic level in technologically important processes such as catalysis and magnetic materials. Linear-scaling DFT methods for calculations with thousands of atoms on insulators are now reaching a level of maturity. However such methods are not applicable to metals, where the continuum of states through the chemical potential and their partial occupancies provide significant hurdles which have yet to be fully overcome.

Ammonia mobility in chabazite: insight into the diffusion component of the NH3-SCR process.

The diffusion of ammonia in commercial NH3-SCR catalyst Cu-CHA was measured and compared with H-CHA using quasielastic neutron scattering (QENS) and molecular dynamics (MD) simulations to assess the effect of counterion presence on NH3 mobility in automotive emission control relevant zeolite catalysts. QENS experiments observed jump diffusion with a jump distance of 3 Å, giving similar self-diffusion coefficient measurements for both Cu- and H-CHA samples, in the range of ca. 5-10 × 10(-10) m(2) s(-1) over the measured temperature range.

Can Palladium Acetate Lose Its "Saltiness"? Catalytic Activities of the Impurities in Palladium Acetate.

Commercially available palladium acetate often contains two major impurities, whose presence can impact the overall catalytic efficacy. This systematic study provides a comparison of the differences in catalytic activity of pure palladium acetate, Pd3(OAc)6, with the two impurities: Pd3(OAc)5(NO2) and polymeric [Pd(OAc)2]n in a variety of cross-coupling reactions. The solid state (13)C NMR spectra of all three compounds in conjunction with DFT calculations confirm their reported geometries.