Multiscale Modelling in Computational Heterogeneous Catalysis

Diffusion-based generative AI for exploring transition states from 2D molecular graphs

The exploration of transition state (TS) geometries is crucial for elucidating chemical reaction mechanisms and modeling their kinetics. Recently, machine learning (ML) models have shown remarkable performance for prediction of TS geometries. However, they require 3D conformations of reactants and products often with their appropriate orientations as input, which demands substantial efforts and computational cost. Here, we propose a generative approach based on the stochastic diffusion method, namely TSDiff, for prediction of TS geometries just from 2D molecular graphs. TSDiff outperforms the existing ML models with 3D geometries in terms of both accuracy and efficiency. Moreover, it enables to sample various TS conformations, because it learns the distribution of TS geometries for diverse reactions in training. Thus, TSDiff finds more favorable reaction pathways with lower barrier heights than those in the reference database. These results demonstrate that TSDiff shows promising potential for an efficient and reliable TS exploration.

Adhesion Performance of Ettringite at the Interface with Silane and GO/Silane: Insights into Molecular Dynamics Simulations

The application of silane in sulfoaluminate cement repair materials can improve its waterproof, permeability, freeze-thaw, and other properties, but it would reduce the mechanical properties of sulfoaluminate cement-based materials, making it unable to better meet the engineering requirements and durability indices. The modification of silane with graphene oxide (GO) can effectively address this issue. However, the failure mechanism of the interface between silane and sulfoaluminate cement-based materials and the modification mechanism of GO remain unclear. In this paper, the interface-bonding mechanical models of isobutyltriethoxysilane (IBTS)/ettringite and GO-IBTS/ettringite are established by molecular dynamics method to study the source of interface-bonding properties of IBTS, GO-IBTS, and ettringite, as well as the failure mechanism of interface bonding, to reveal the mechanism of GO-modifying IBTS to improve the interface-bonding properties of IBTS and ettringite. This study finds that the bonding properties of the IBTS, GO-IBTS, and ettringite interface are derived from the amphiphilic nature of IBTS, which can only produce unilateral bonding with ettringite, thus becoming a weak link in interface dissociation. The double-sided nature of GO functional groups enables GO-IBTS to interact well with bilateral ettringite, thus enhancing the interface-bonding properties.

Multi-scale simulation of proton diffusion in dislocation cores in BaZrO3

Dislocations are important for their effects on the chemical, electrical, magnetic, and transport properties of oxide materials, especially for electrochemical devices such as solid fuel cells and resistive memories, but these effects are still under-studied at the atomic level. We have developed a quantum mechanical/molecular mechanical (QM/MM)-based multiscale simulation program to reveal the diffusion properties of protons on 〈100〉 edge dislocations in BaZrO₃ perovskite oxide. We find that the large free space and the presence of hydrogen bonds in the dislocation core structure lead to significant trapping of protons. The diffusion properties of protons in dislocation cores were investigated, and no evidence of pipeline diffusion was found from the calculated migration energy barriers, which not only did not accelerate ion diffusion but rather decreases the conductivity of ions. The proton diffusion properties of Y-doped BaZrO₃ (BZY), with a dislocation core structure (BZY-D) and with a grain boundary structure (BZY-GB) were also compared. In all three structures, local lattice deformation occupies an essential part in the proton transfer and rotation processes. The change in bond order is calculated and it is found that the interaction with oxygen and Zr ions during proton transfer and rotation controls the energy barrier for local lattice deformation of the O-B-O motion, which affects the proton diffusion in the structure. Our study provides insight into proton diffusion in dislocations in terms of mechanical behavior, elucidates the origin of the energy barrier associated with proton diffusion in dislocations, and provides guidance for the preparation and application of proton conductors.

Multi-scale dynamical cross-talk in zeolite-catalyzed methanol and dimethyl ether conversions

Establishing a comprehensive understanding of the dynamical multiscale diffusion and reaction process is crucial for zeolite shape-selective catalysis and is urgently demanded in academia and industry. So far, diffusion and reaction for methanol and dimethyl ether (DME) conversions have usually been studied separately and focused on a single scale. Herein, we decipher the dynamical molecular diffusion and reaction process for methanol and DME conversions within the zeolite material evolving with time, at multiple scales, from the scale of molecules to single catalyst crystal and catalyst ensemble. Microscopic intracrystalline diffusivity is successfully decoupled from the macroscopic experiments and verified by molecular dynamics simulation. Spatiotemporal analyses of the confined carbonaceous species allow us to track the migratory reaction fronts in a single catalyst crystal and the catalyst ensemble. The constrained diffusion of DME relative to methanol alleviates the high local chemical potential of the reactant by attenuating its local enrichment, enhancing the utilization efficiency of the inner active sites of the catalyst crystal. In this context, the dynamical cross-talk behaviors of material, diffusion and reaction occurring at multiple scales is uncovered. Zeolite catalysis not only reflects the reaction characteristics of heterogeneous catalysis, but also provides enhanced, moderate or suppressed local reaction kinetics through the special catalytic micro-environment, which leads to the heterogeneity of diffusion and reaction at multiple scales, thereby realizing efficient and shape-selective catalysis.

Molecular behaviour of methanol and dimethyl ether in H-ZSM-5 catalysts as a function of Si/Al ratio: a quasielastic neutron scattering study

Qualitative and quantitative differences are found in methanol and dimethyl ether mobility in H-ZSM-5 catalysts of varying Si/Al ratios (Brønsted acid site concentrations) using quasielastic neutron scattering.

Adaptive and automated system-optimization for heterogeneous flow-hydrogenation reactions

The autonomous hydrogenation of carbonyl compounds and N-heterocycles over solid catalysts with H₂ is achieved in 3D parameter space by integrating analytics, control and hardware.

Towards operando computational modeling in heterogeneous catalysis

An increased synergy between experimental and theoretical investigations in heterogeneous catalysis has become apparent during the last decade. Experimental work has extended from ultra-high vacuum and low temperature towards operando conditions. These developments have motivated the computational community to move from standard descriptive computational models, based on inspection of the potential energy surface at 0 K and low reactant concentrations (0 K/UHV model), to more realistic conditions. The transition from 0 K/UHV to operando models has been backed by significant developments in computer hardware and software over the past few decades. New methodological developments, designed to overcome part of the gap between 0 K/UHV and operando conditions, include (i) global optimization techniques, (ii) ab initio constrained thermodynamics, (iii) biased molecular dynamics, (iv) microkinetic models of reaction networks and (v) machine learning approaches. The importance of the transition is highlighted by discussing how the molecular level picture of catalytic sites and the associated reaction mechanisms changes when the chemical environment, pressure and temperature effects are correctly accounted for in molecular simulations. It is the purpose of this review to discuss each method on an equal footing, and to draw connections between methods, particularly where they may be applied in combination.

Molecular Modelling for Reactor Design

Chemical reactor modelling based on insights and data on a molecular level has become reality over the last few years. Multiscale models describing elementary reaction steps and full microkinetic schemes, pore structures, multicomponent adsorption and diffusion inside pores, and entire reactors have been presented. Quantum mechanical (QM) approaches, molecular simulations (Monte Carlo and molecular dynamics), and continuum equations have been employed for this purpose. Some recent developments in these approaches are presented, in particular time-dependent QM methods, calculation of van der Waals forces, new approaches for force field generation, automatic setup of reaction schemes, and pore modelling. Multiscale simulations are discussed. Applications of these approaches to heterogeneous catalysis are demonstrated for examples that have found growing interest over the last few years, such as metal-support interactions, influence of pore geometry on reactions, noncovalent bonding, reaction dynamics, dynamic changes in catalyst nanoparticle structure, electrocatalysis, solvent effects in catalysis, and multiscale modelling.

Simulation Study on the Reaction-Diffusion Coupling in Simple Pore Structures

Most porous media (just like catalyst pellets) have complicated pore structures, and understanding the coupling of the diffusion and reaction processes in these pores is very important for improving their performance. In this work, a diffusion factor (D) and a reaction factor (R) are proposed to quantitatively describe the diffusion and reaction performance in these pores respectively at molecular level. The yield in unit time is used to quantify their productivity and is expressed as the product of D and R. Molecular dynamic simulations with the hard-sphere algorithm are carried out to study the reaction-diffusion coupling in several simple pore structures with the same volume, such as straight, T-shaped, and cross-shaped pores. The reaction formula based on activation energy is given for a simple irreversible reaction process from A to B. In terms of the proposed factors, D and R, analysis on the simulation results shows clearly that the overall productivity of these pore structures depends on the competition of D and R, which are both determined by the size and shape of the pore structures. The results demonstrate the effectiveness of the simulation approach used for evaluating the performance of the simple pore structures for simple reactions and the potential of its application in more complicated and practical cases. It also suggests the effectiveness of the proposed factors, D and R, for charactering the diffusion and reaction processes at molecular level.

Future Challenges in Heterogeneous Catalysis: Understanding Catalysts under Dynamic Reaction Conditions

In the future, (electro-)chemical catalysts will have to be more tolerant towards a varying supply of energy and raw materials. This is mainly due to the fluctuating nature of renewable energies. For example, power-to-chemical processes require a shift from steady-state operation towards operation under dynamic reaction conditions. This brings along a number of demands for the design of both catalysts and reactors, because it is well-known that the structure of catalysts is very dynamic. However, in-depth studies of catalysts and catalytic reactors under such transient conditions have only started recently. This requires studies and advances in the fields of 1) operando spectroscopy including time-resolved methods, 2) theory with predictive quality, 3) kinetic modelling, 4) design of catalysts by appropriate preparation concepts, and 5) novel/modular reactor designs. An intensive exchange between these scientific disciplines will enable a substantial gain of fundamental knowledge which is urgently required. This concept article highlights recent developments, challenges, and future directions for understanding catalysts under dynamic reaction conditions.

Grand challenges for catalysis in the Science and Technology Roadmap on Catalysis for Europe: moving ahead for a sustainable future

This perspective discusses the general concepts that will guide future catalysis and related grand challenges based on the Science and Technology Roadmap on Catalysis for Europe prepared by the European Cluster on Catalysis.

Automated Transition State Searches without Evaluating the Hessian

Accurate and speedy determination of transition structures (TSs) is essential for computational studies on reaction pathways, particularly when the process involves expensive electronic structure calculations. Many search algorithms require a good initial guess of the TS geometry, as well as a Hessian input that possesses a structure consistent with the desired saddle point. Among the double-ended interpolation methods for generation of the guess for the TS, the freezing string method (FSM) is proven to be far less expensive compared to its predecessor, the growing string method (GSM). In this paper, it is demonstrated that the efficiency of this technique can be improved further by replacing the conjugate gradient optimization step (FSM-CG) with a quasi-Newton line search coupled with a BFGS Hessian update (FSM-BFGS). A second crucial factor that affects the speed with which convergence to the TS is achieved is the quality and cost of the Hessian of the energy for the guessed TS. For electronic structure calculations, the cost of calculating an exact Hessian increases more rapidly with system size than the energy and gradient. Therefore, to sidestep calculation of the exact Hessian, an approximate Hessian is constructed, using the tangent direction and local curvature at the TS guess. It is demonstrated that the partitioned-rational function optimization algorithm for locating TSs with this approximate Hessian input performs at least as well as with an exact Hessian input in most test cases. The two techniques, FSM and approximate Hessian construction, therefore can significantly reduce costs associated with finding TSs.