An Efficient Way to Model Complex Iron Carbides: A Benchmark Study of DFTB2 against DFT.

Iron carbides have attracted increasing attention in recent years due to their enormous potential in catalytic fields, such as Fischer-Tropsch synthesis and the growth of carbon nanotubes. Theoretical calculations can provide a more thorough understanding of these reactions at the atomic scale. However, due to the extreme complexity of the active phases and surface structures of iron carbides at the operando conditions, calculations based on density functional theory (DFT) are too costly for realistically large models of iron carbide particles. Therefore, a cheap and efficient quantum mechanical simulation method with accuracy comparable to DFT is desired. In this work, we adopt the spin-polarized self-consistent charge density functional tight-binding (DFTB2) method for iron carbides by reparametrization of the repulsive part of the Fe-C interactions. To assess the performance of the improved parameters, the structural and electronic properties of iron carbide bulks and clusters obtained with DFTB2 method are compared with the previous experimental values and the results obtained with DFT approach. Calculated lattice parameters and density of states are close to DFT predictions. The benchmark results show that the proposed parametrization of Fe-C interactions provides transferable and balanced description of iron carbide systems. Therefore, spin-polarized DFTB2 is valued as an efficient and reliable method for the description of iron carbide systems.

Theoretical Mechanism on the Cellulose Regeneration from a Cellulose/EmimOAc Mixture in Anti-Solvents.

The experiments on cellulose dissolution/regeneration have made some achievements to some extent, but the mechanism of cellulose regeneration in ionic liquids (ILs) and anti-solvent mixtures remains elusive. In this work, the cellulose regeneration mechanism in different anti-solvents, and at different temperatures and concentrations, has been studied with molecular dynamics (MD) simulations. The IL considered is 1-ethyl-3-methylimidazolium acetate (EmimOAc). In addition, to investigate the microcosmic effects of ILs and anti-solvents, EmimOAc-nH2O (n = 0-6) clusters have been optimized by Density Functional Theory (DFT) calculations. It can be found that water is beneficial to the regeneration of cellulose due to its strong polarity. The interactions between ILs and cellulose will become strong with the increase in temperature. The H-bonds of cellulose chains would increase with the rising concentrations of anti-solvents. The interaction energies between cellulose and the anions of ILs are stronger than that of cations. Furthermore, the anti-solvents possess a strong affinity for ILs, cation-anion pairs are dissociated to form H-bonds with anti-solvents, and the H-bonds between cellulose and ILs are destroyed to promote cellulose regeneration.

Probing the mechanism of the conversion of methyl levulinate into γ-valerolactone catalyzed by Al(OiPr)3 in an alcohol solvent: a DFT study.

Biomass-derived γ-valerolactone (GVL) is a versatile chemical that can be used in various fields. As an efficient, cheap, and sustainable catalyst, Al(OiPr)3 has been successfully used in the conversion of methyl levulinate (ML) to GVL in the solvent isopropanol (IPA). However, the molecular mechanism of this conversion catalyzed by Al(OiPr)3 remains ambiguous. To investigate the mechanism of the conversion of ML to GVL catalyzed by Al(OiPr)3, the reaction pathways, including the transesterification, Meerwein-Ponndorf-Verley (MPV) hydrogenation, and ring-closure steps, were probed using density functional theory (DFT) calculations at the M062X-D3/def2-TZVP level. Among the elementary steps, it is found that ring-closure is the rate-determining step and that Al3+ can coordinate with the oxygen of 2-hydroxy-isopropyl levulinate (2HIPL) to catalyze the last ring-closure step. A four-centered transition state can be formed, and Al(OiPr)3 shows a strong catalytic effect in the two steps of the ester exchange reaction. The center of Al(OiPr)3 mainly coordinates with the carbonyl oxygen atom of the ester to catalyze the reaction. The present study provides some help in understanding the conversion mechanism of ML to GVL and designing more effective catalysts for use in biomass conversion chemistry.

Enhanced hydrogen generation by reverse spillover effects over bicomponent catalysts.

The contribution of the reverse spillover effect to hydrogen generation reactions is still controversial. Herein, the promotion functions for reverse spillover in the ammonia borane hydrolysis reaction are proven by constructing a spatially separated NiO/Al2O3/Pt bicomponent catalyst via atomic layer deposition and performing in situ quick X-ray absorption near-edge structure (XANES) characterization. For the NiO/Al2O3/Pt catalyst, NiO and Pt nanoparticles are attached to the outer and inner surfaces of Al2O3 nanotubes, respectively. In situ XANES results reveal that for ammonia borane hydrolysis, the H species generated at NiO sites spill across the support to the Pt sites reversely. The reverse spillover effects account for enhanced H2 generation rates for NiO/Al2O3/Pt. For the CoOx/Al2O3/Pt and NiO/TiO2/Pt catalysts, reverse spillover effects are also confirmed. We believe that an in-depth understanding of the reverse effects will be helpful to clarify the catalytic mechanisms and provide a guide for designing highly efficient catalysts for hydrogen generation reactions.

A combined DFTB nanoreactor and reaction network generator approach for the mechanism of hydrocarbon combustion.

We explored the mechanism of ethylene combustion by combining a density functional tight-binding based nanoreactor molecular dynamic method (DFTB-NMD) and a hidden Markov model (HMM) based reaction network generator approach. The results demonstrate that the DFTB-NMD is a promising method to predict the mechanism of complicated combustion reactions.

Insights into Coke Formation and Removal under Operating Conditions with a Quantum Nanoreactor Approach.

The in situ formation and removal of coke is a critical problem in heterogeneous catalysis, but its mechanism is not well understood. This work investigates the mechanism of carbon deposition and hydrogenation on an Fe cluster under high-temperature conditions with the density functional tight-binding (DFTB) based nanoreactor molecular dynamics (NMD) method. Our study shows that successive formation of carbon chains, rings, and fused rings occurred during the carbon deposition on Fe clusters. Hydrogenation of activated carbon happens through direct C-H coupling, while the hydrogenation of graphitic carbon involves hydrogenation of the edge carbon, ring-opening reaction, and dealkylation reaction. The main function of the Fe catalyst is to provide the active sites for H2 dissociation and dissociated H spillover, while its activity toward C-C bond breaking is limited. These results highlight the role of the DFTB-NMD method as an effective tool to investigate reaction mechanisms under operating conditions in heterogeneous catalysis.

Mechanism of Graphene Formation via Detonation Synthesis: A DFTB Nanoreactor Approach.

With the development of theoretical and computational chemistry, as well as high-performance computing, molecular simulation can now be used not only as a tool to explain the experimental results but also as a means for discovery or prediction. Quantum chemical nanoreactor is such a method which can automatically explore the chemical process based only on the basic mechanics without prior knowledge of the reactions. Here, we present a new method which combines the semiempirical quantum mechanical density functional tight-binding (DFTB) method with the nanoreactor molecular dynamic (NMD) method, and we simulated the reaction process of graphene synthesis via detonation at different oxygen/acetylene mole ratios. The formation of graphene is initiated by the breaking of acetylene (C2H2) molecules by collision into pieces such as H atoms, ethynyl (HC≡C•), and vinylidene (H2C═C:) radicals. It is followed by the formation of long straight carbon chains coupled with a few branched carbon chains, which then turned into  a 2-D framework made of carbon rings. Trace oxygen could modulate the size of the rings during graphene formation and promote the formation of regular graphene with fused six-membered rings as we see, but the addition of high oxygen content makes more C-containing species oxidized to small oxide molecules instead of polymerization. The calculation speed of the DFTB nanoreactor is greatly improved compared to the ab initio nanoreactor, which makes it a valuable option to simulate chemical processes of large sizes and long time scales and to help us uncover the "unknown unknowns".