Publications by authors named "Fernando H Garzon"

Efficient conversion of methane to value-added products such as olefins and aromatics has been in pursuit for the past few decades. The demand has increased further due to the recent discoveries of shale gas reserves. Oxidative and non-oxidative coupling of methane (OCM and NOCM) have been actively researched, although catalysts with commercially viable conversion rates are not yet available.

View Article and Find Full Text PDF

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for pure components in liquid, gas and super critical phases. The ANNs were tested on an experimental database of 6625 self-diffusion constants for 118 different chemical compounds. The presence of multiple phases results in a heavy skew in the distribution of diffusion constants and multiple approaches were used to address this challenge.

View Article and Find Full Text PDF
Article Synopsis
  • Different machine learning methods, specifically Random Forest (RF) and Artificial Neural Nets (ANN), were examined to predict self-diffusion in Lennard-Jones fluids using a database from molecular dynamics simulations.
  • The study highlighted the importance of feature engineering in enhancing the performance of the RF models.
  • Ultimately, the ANN models outperformed existing empirical relationships in accurately predicting diffusion in these fluids.
View Article and Find Full Text PDF

We report herein a density functional theory study of the nitrogen electroreduction and hydrogen evolution reactions on cubic molybdenum carbide (MoC) in order to investigate the viability of using this material as an electro-catalyst for ammonia synthesis. Free energy diagrams for associative and dissociative Heyrovsky mechanisms showed that nitrogen reduction on cubic MoC(111) can proceed via an associative mechanism and that small negative potentials of -0.3 V vs.

View Article and Find Full Text PDF

The structural equilibrium parameters, the adsorption energies, and the vibrational frequencies of the nitrogen molecule and the hydrogen atom adsorbed on the (111) surface of rhodium have been investigated using different generalized-gradient approximation (GGA), nonlocal correlation, meta-GGA, and hybrid functionals, namely, Perdew, Burke, and Ernzerhof (PBE), Revised-RPBE, vdW-DF, Tao, Perdew, Staroverov, and Scuseria functional (TPSS), and Heyd, Scuseria, and Ernzerhof (HSE06) functional in the plane wave formalism. Among the five tested functionals, nonlocal vdW-DF and meta-GGA TPSS functionals are most successful in describing energetics of dinitrogen physisorption to the Rh(111) surface, while the PBE functional provides the correct chemisorption energy for the hydrogen atom. It was also found that TPSS functional produces the best vibrational spectra of the nitrogen molecule and the hydrogen atom on rhodium within the harmonic formalism with the error of -2.

View Article and Find Full Text PDF

We used density functional theory to study the electrochemical conversion of nitrogen to ammonia on the (001), (100/010), (101), and (111) surfaces of γ-Mo2N. Based on the calculated free energy profiles for the reduction of nitrogen by the associative and dissociative mechanisms, reactivity was found to decrease in the order (111) > (101) > (100/010) ≈ (001). Namely, the cell potentials needed to drive the reduction to ammonia increase in the following order: -0.

View Article and Find Full Text PDF

In this article, selective and sensitive detection of trace amounts of pentaerythritol tetranitrate (PETN), 2,4,6-trinitrotoluene (TNT) and cyclotrimethylenetrinitramine (RDX) is demonstrated. The screening system is based on a sampling/concentrator front end and electrochemical potentiometric gas sensors as the detector. Preferential hydrocarbon and nitrogen oxide(s) mixed potential sensors based on lanthanum strontium chromite and Pt electrodes with yttria stabilized zirconia (YSZ) solid electrolyte were used to capture the signature of the explosives.

View Article and Find Full Text PDF

A new non-precious metal oxygen reduction catalyst was developed via heat treatment of in situ polymerized polyaniline onto TiO(2) particles in the presence of Fe species. The TiO(2) provides for improved performance relative to a carbon black-based catalyst and, at a high catalyst loading, allows for reducing the performance gap between non-precious-metal catalyst and Pt/C to ca. 20 mV in RDE testing.

View Article and Find Full Text PDF