A Simple Method To Locate the Optimal Adsorption Energy for the Best Catalysts Directly

A DFT study towards dynamic structures of iron and iron carbide and their effects on the activity of the Fischer-Tropsch process

The Fe-based Fischer-Tropsch synthesis (FTS) catalyst shows a rich phase chemistry under pre-treatment and FTS conditions. The exact structural composition of the active site, whether iron or iron carbide (FeCx), is still controversial. Aiming to obtain an insight into the active sites and their role in affecting FTS activity, the swarm intelligence algorithm is implemented to search for the most stable Fe(100), Fe(110), Fe(210) surfaces with different carbon ratios. Then, ab initio atomistic thermodynamics and Wulffman construction were employed to evaluate the stability of these surfaces at different chemical potentials of carbon. Their FTS reactivity and selectivity were later assessed by semi-quantitative micro-kinetic equations. The results show that stability, reactivity, and selectivity of the iron are all affected by the carbonization process when the carbon ratio increases. Formation of the carbide, a rather natural process under experimental conditions, would moderately increase the turnover frequency (TOF), but both iron and iron carbide are active to the reaction.

Counting d-Orbital Vacancies of Transition-Metal Catalysts for the Sulfur Reduction Reaction

The electrocatalytic sulfur reduction reaction (SRR) would allow the production of renewable high-capacity rechargeable lithium-sulfur (Li-S) batteries using sustainable and nontoxic elemental sulfur as a cathode material, but its slow reaction rate causes a serious shuttle effect and dramatically reduces the capacity. We found that a catalyst composed of Pd nanoparticles supported by ordered mesoporous carbon (Pd/OMC) had a high reaction rate in the SRR, and a Li-S battery assembled with this catalyst had a low shuttle constant of 0.031 h-1 and a high-rate performance with a specific capacity of 1527 mAh g-1 at 0.1 C which is close to the theoretical value. The high activity of Pd/OMC with a d-orbital vacancy of 0.87 e was predicted from a volcano relationship between the d charge for the metal and the adsorption activation entropy and reaction rate for the SRR by examining Pd, Au, Pt, Rh, and Ru transition-metal nanocatalysts. The strategy of using a single electronic structure descriptor to design high-efficiency SRR catalysts has suggested a way to produce practical Li-S batteries.

Electron spin modulation engineering in oxygen-involved electrocatalysis

Electrocatalytic oxygen reduction reaction (ORR) and oxygen evolution reduction (OER) are regarded as the key reactions via the sustainable system (fuel cell and water splitting), respectively. In OER, the transition from singlet oxygen species to triplet oxygen molecules is involved, meanwhile the ORR involves the transition from triplet oxygen molecules to singlet oxygen species. However, in these processes, the number of unpaired electrons is not conserved, which is not thermodynamically favorable and creates an additional energy barrier. Fortunately, regulating the electrocatalysis by spin-state modulation enables a unique effect on the catalytic performance, but the current understanding on spin-state engineering for electro-catalyzing ORR and OER is still insufficient. Herein, this review summarized the in-spin engineering for the state-of-the-art ORR and OER electrocatalysts. It began by introducing engineering of spin-state to e_gfilling for ORR and OER process, and then moved to spin polarization and spin-pinning effect for OER process. Various designed strategies focusing on how to regulate the spin-state of the active center have been summarized up. The connectivity of the structures of typical ORR (e.g. metal-nitrogen-carbon) and OER (e.g. design strategies oxides, metal organic frameworks) catalysts depending on the spin level is also discussed. Finally, we present the outlook from the aspects of template catalysts, characterization methods, regulation strategies, theoretical calculations, which will further expand the possibility of better electrocatalytic performance through spin-state modulation. This review concluded some open suggestions and prospects, which are worthy of the community's future work.

CATKINAS: A large-scale catalytic microkinetic analysis software for mechanism auto-analysis and catalyst screening

As an effective method to analyze complex catalytic reaction networks, microkinetic modeling is gaining increasing popularity in the catalytic activity evaluation and rational design of heterogeneous catalysts. An automated simulator with stable and reliable performance is especially useful and in great request. Here we introduce the CATKINAS package developed for large-scale microkinetic modeling and analysis. Featuring with a multilevel solver and a multifunctional analyzer, CATKINAS can provide both accurate solutions and various quantitative and automatic analysis for a wide range of catalytic systems. The structure and the basic workflow are overviewed with the multilevel solver particularly illustrated. Also, we take the CO methanation reaction as an example to illustrate the application and efficiency of the CATKINAS package.

SSIA: A sensitivity-supervised interlock algorithm for high-performance microkinetic solving

Microkinetic modeling has drawn increasing attention for quantitatively analyzing catalytic networks in recent decades, in which the speed and stability of the solver play a crucial role. However, for the multi-step complex systems with a wide variation of rate constants, the often encountered stiff problem leads to the low success rate and high computational cost in the numerical solution. Here, we report a new efficient sensitivity-supervised interlock algorithm (SSIA), which enables us to solve the steady state of heterogeneous catalytic systems in the microkinetic modeling with a 100% success rate. In SSIA, we introduce the coverage sensitivity of surface intermediates to monitor the low-precision time-integration of ordinary differential equations, through which a quasi-steady-state is located. Further optimized by the high-precision damped Newton's method, this quasi-steady-state can converge with a low computational cost. Besides, to simulate the large differences (usually by orders of magnitude) among the practical coverages of different intermediates, we propose the initial coverages in SSIA to be generated in exponential space, which allows a larger and more realistic search scope. On examining three representative catalytic models, we demonstrate that SSIA is superior in both speed and robustness compared with its traditional counterparts. This efficient algorithm can be promisingly applied in existing microkinetic solvers to achieve large-scale modeling of stiff catalytic networks.

Influence of surface defects on activity and selectivity: a quantitative study of structure sensitivity of Pd catalysts for acetylene hydrogenation

The structure sensitivity of Pd catalysed acetylene hydrogenation is quantitatively examined using a coverage-dependent microkinetic model. Pd(211) was found to be more active than Pd(111), but present a poorer selectivity toward ethylene.

On the optimum catalyst for structure sensitive heterogeneous catalytic reactions

Reaction rates in a two-step catalytic sequence, when plotted vs adsorption energy of the key or the most abundant surface intermediate, result in volcano shaped curves. In the current work, the optimal catalyst is discussed for structure sensitive reactions, which display dependence of activity on the cluster size of the active catalytic phase. An expression is derived relating the Gibbs energy for formation of the intermediate with the Gibbs energy changes in the overall reaction, difference in adsorption thermodynamics on edges and terraces and the cluster size. The kinetic expressions display dependence of activity vs the Gibbs energy of the adsorbed intermediate formation. Numerical analysis demonstrates that when the overall equilibrium constant K is high and the reaction is thermodynamically very favorable, the maxima in the rates vs the adsorption constant for the optimal catalyst are much broader being less dependent on the cluster size. When structure sensitivity is pronounced, there are smaller differences in the rates for the optimum and less optimal catalysts in comparison with reactions showing weak structure sensitivity.

Prediction of optimal catalysts for a given chemical reaction

We show that the optimal catalyst for a given reaction equalizes the free energies of intermediates in an adsorbed phase, and in consequence is described by a surface energy proportional to the enthalpy of this reaction.

Understanding supported noble metal catalysts using first-principles calculations

Heterogeneous catalysis on supported and nonsupported nanoparticles is of fundamental importance in the energy and chemical conversion industries. Rather than laboratory analysis, first-principles calculations give us an atomic-level understanding of the structure and reactivity of nanoparticles and supports, greatly reducing the efforts of screening and design. However, unlike catalysis on low index single crystalline surfaces, nanoparticle catalysis relies on the tandem properties of a support material as well as the metal cluster itself, often with charge transfer processes being of key importance. In this perspective, we examine current state-of-the-art quantum-chemical research for the modeling of reactions that utilize small transition metal clusters on metal oxide supports. This should provide readers with useful insights when dealing with chemical reactions on such systems, before discussing the possibilities and challenges in the field.