Adsorption-Induced Liquid-to-Solid Phase Transition of Cu Clusters in Catalytic Dissociation of CO2

Entropy in catalyst dynamics under confinement

Entropy during the dynamic structural evolution of catalysts has a non-trivial influence on chemical reactions. Confinement significantly affects the catalyst dynamics and thus impacts the reactivity. However, a full understanding has not been clearly established. To investigate catalyst dynamics under confinement, we utilize the active learning scheme to effectively train machine learning potentials for computing free energies of catalytic reactions. The scheme enables us to compute the reaction free energies and entropies of O2 dissociation on Pt clusters with different sizes confined inside a carbon nanotube (CNT) at the timescale of tens of nanoseconds while keeping ab initio accuracy. We observe an entropic effect owing to liquid-to-solid phase transitions of clusters at finite temperatures. More importantly, the confinement effect enhances the structural dynamics of the cluster and leads to a lower melting temperature than those of the bare cluster and cluster outside the CNT, consequently facilitating the reaction to occur at lower temperatures and preventing the catalyst from forming unfavorable oxides. Our work reveals the important influence of confinement on structural dynamics, providing useful insight into entropy in dynamic catalysis.

Machine Learning Molecular Dynamics Shows Anomalous Entropic Effect on Catalysis through Surface Pre-melting of Nanoclusters

Due to the superior catalytic activity and efficient utilization of noble metals, nanocatalysts are extensively used in the modern industrial production of chemicals. The surface structures of these materials are significantly influenced by reactive adsorbates, leading to dynamic behavior under experimental conditions. The dynamic nature poses significant challenges in studying the structure-activity relations of catalysts. Herein, we unveil an anomalous entropic effect on catalysis via surface pre-melting of nanoclusters through machine learning accelerated molecular dynamics and free energy calculation. We find that due to the pre-melting of shell atoms, there exists a non-linear variation in the catalytic activity of the nanoclusters with temperature. Consequently, two notable changes in catalyst activity occur at the respective temperatures of melting for the shell and core atoms. We further study the nanoclusters with surface point defects, i.e. vacancy and ad-atom, and observe significant decrease in the surface melting temperatures of the nanoclusters, enabling the reaction to take place under more favorable and milder conditions. These findings not only provide novel insights into dynamic catalysis of nanoclusters but also offer new understanding of the role of point defects in catalytic processes.

Copper nanoparticles encapsulated in zeolitic imidazolate framework-8 as a stable and selective CO2 hydrogenation catalyst

Metal-organic frameworks have drawn attention as potential catalysts owing to their unique tunable surface chemistry and accessibility. However, their application in thermal catalysis has been limited because of their instability under harsh temperatures and pressures, such as the hydrogenation of CO2 to methanol. Herein, we use a controlled two-step method to synthesize finely dispersed Cu on a zeolitic imidazolate framework-8 (ZIF-8). This catalyst suffers a series of transformations during the CO2 hydrogenation to methanol, leading to ~14 nm Cu nanoparticles encapsulated on the Zn-based MOF that are highly active (2-fold higher methanol productivity than the commercial Cu-Zn-Al catalyst), very selective (>90%), and remarkably stable for over 150 h. In situ spectroscopy, density functional theory calculations, and kinetic results reveal the preferential adsorption sites, the preferential reaction pathways, and the reverse water gas shift reaction suppression over this catalyst. The developed material is robust, easy to synthesize, and active for CO2 utilization.

Frustrations of supported catalytic clusters under operando conditions predicted by a simple lattice model

The energy landscape with a number of close minima separated by low barriers is a well-known issue in computational heterogeneous catalysis. In the framework of the emerging out-of-equilibrium material science, the navigation through such involved landscapes is associated with the functionality of materials. Current advancements in the cluster catalysis has brought and continues to bring essential nuances to the topic. One of them is the possibility of frustration of the catalytic centre under operando conditions. However, this conjecture is difficult to check either experimentally or theoretically. As a step in this direction, as-simple-as-possible lattice model is used to estimate how the supposed frustrations may couple with the elementary reaction and manifest themselves at the macroscopic scale.

Structural dynamics of Ru clusters during nitrogen dissociation in ammonia synthesis

The dynamic evolution of catalyst structures greatly influences the reactivity, especially sub-nanometer clusters, exhibiting complex configurational fluctuation. In the present work, we study the structural dynamics of a Ru₁₉ cluster during the dissociation of N₂ and calculate the reaction free energies using ab initio molecular dynamics (AIMD). Our AIMD calculation predicts a peak-shaped reaction entropy curve due to the adsorption-induced phase transition of the Ru₁₉ cluster. The low melting points of sub-nanometer clusters make it possible to activate N₂ at low temperatures. This work demonstrates that the dynamic changes of cluster structures have a non-negligible effect on reaction free energy and offer an opportunity for achieving ammonia synthesis under mild conditions.

Size-dependent phase transitions boost catalytic activity of sub-nanometer gold clusters

The characterization and identification of the dynamics of cluster catalysis are crucial to unraveling the origin of catalytic activity. However, the dynamical catalytic effects during the reaction process remain unclear. Herein, we investigate the dynamic coupling effect of elementary reactions with the structural fluctuations of sub-nanometer Au clusters with different sizes using ab initio molecular dynamics and the free energy calculation method. It was found that the adsorption-induced solid-to-liquid phase transitions of the cluster catalysts give rise to abnormal entropy increase, facilitating the proceeding of reaction, and this phase transition catalysis exists in a range of clusters with different sizes. Moreover, clusters with different sizes show different transition temperatures, resulting in a non-trivial size effect. These results unveil the dynamic effect of catalysts and help understand cluster catalysis to design better catalysts rationally.

Addressing Dynamics at Catalytic Heterogeneous Interfaces with DFT-MD: Anomalous Temperature Distributions from Commonly Used Thermostats

Density functional theory-based molecular dynamics (DFT-MD) has been widely used for studying the chemistry of heterogeneous interfacial systems under operational conditions. We report frequently overlooked errors in thermostated or constant-temperature DFT-MD simulations applied to study (electro)catalytic chemistry. Our results demonstrate that commonly used thermostats such as Nosé-Hoover, Berendsen, and simple velocity-rescaling methods fail to provide a reliable temperature description for systems considered. Instead, nonconstant temperatures and large temperature gradients within the different parts of the system are observed. The errors are not a "feature" of any particular code but are present in several ab initio molecular dynamics implementations. This uneven temperature distribution, due to inadequate thermostatting, is well-known in the classical MD community, where it is ascribed to the failure in kinetic energy equipartition among different degrees of freedom in heterogeneous systems (Harvey et al. J. Comput. Chem. 1998, 726-740) and termed the flying ice cube effect. We provide tantamount evidence that interfacial systems are susceptible to substantial flying ice cube effects and demonstrate that the traditional Nosé-Hoover and Berendsen thermostats should be applied with care when simulating, for example, catalytic properties or structures of solvated interfaces and supported clusters. We conclude that the flying ice cube effect in these systems can be conveniently avoided using Langevin dynamics.

Mapping the Finite-Temperature Behavior of Conformations to Their Potential Energy Barriers: Case Studies on Si6B and Si5B Clusters

Dynamical simulations of molecules and materials have been the route to understand the rearrangement of atoms within them at different temperatures. Born-Oppenheimer molecular dynamical simulations have further helped to comprehend the reaction dynamics at various finite temperatures. We take a case study of Si₆B and Si₅B clusters and demonstrate that their finite-temperature behavior is rather mapped to the potential energy surface. The study further brings forth the fact that an accurate description of the dynamics is rather coupled with the accuracy of the method in defining the potential energy surface. A more precise potential energy surface generated through the coupled cluster method is finally used to identify the most accurate description of the potential energy surface and the interconnected finite-temperature behavior.

Size-Sensitive Dynamic Catalysis of Subnanometer Cu Clusters in CO2 Dissociation

Small cluster catalysts are highly size-dependent and exhibit complex structural dynamic effects during catalytic reactions. Understanding their structural dynamics is of great importance in tuning the catalytic performances of small clusters that widely exist in supported catalysts. However, very little is known about the size dependence of the dynamic effect of small clusters. In this work, we systematically study the free energies and barriers of catalytic dissociation of CO₂ at different temperatures on dynamical Cu clusters with different sizes by ab initio molecular dynamics. The reaction shows an abnormal entropic effect on Cu clusters, and more interestingly, it shows size sensitivity. On the Cu₇ cluster, the entropy curve shows a reverse peak shape with increasing temperature, and it is surprising to find that it has a complex pulse shape on the Cu₁₉ cluster. The detailed analysis shows that such temperature dependences can be attributable to the nontrivial behaviors of adsorption-induced phase transitions of the subnanometer Cu clusters during the dissociation of CO₂. Our work not only demonstrates the complexity of the temperature dependence of the surface reaction on cluster sizes but also provides useful insight into the phase transition catalysis of dynamic clusters.

Role of Small Moiety of a Large Ligand: Tyrosine Templated Copper Nanoclusters

To explore the underlying formation mechanism of luminescent metal nanoclusters (NCs) using a small moiety such as amino acids (outside the milieu of a protein environment) as templates, herein we report blue-emitting copper nanoclusters (CuNCs) using l-tyrosine (l-Tyr) as a capping agent as well as a reducing agent. We also demonstrate the effect of an in situ fibrillation of Tyr on the luminescence and structural properties of NCs. Fluorescence studies along with microscopic imaging revealed the rapid formation of a dityrosine (di-Tyr) moiety in an alkaline medium followed by an aggregated "Tamarix dioica leaf"-like fibrillar pattern along with CuNCs. Our present investigation delineates the role played by π-π interactions in the formation of the fibrillar structures. We substantiated the fundamentals of using a small molecule of a large ligand that can serve as a template and also show how these NCs once formed destroy the fibrils of di-Tyr as a function of time.

Light Driven Mechanism of Carbon Dioxide Reduction Reaction to Carbon Monoxide on Gold Nanoparticles: A Theoretical Prediction

Insightful understanding of the light driven CO₂ reduction reaction (CO₂RR) mechanism on gold nanoparticles is one of the important issues in the plasmon mediated photocatalytic study. Herein, time-dependent density functional theory and reduced two-state model are adopted to investigate the photoinduced charge transfer in interfaces. According to the excitation energy and orbital coupling, the light driven mechanism of CO₂RR on gold nanoparticles can be described as follows: the light induces electron excitation and then transfers to the physisorbed CO₂, and CO₂ can relax to a bent structure adsorbed on gold nanoparticles, and the adsorbed C-O bonds are dissociated finally. Moreover, our calculated results demonstrate that the s, p, and d electron excitations of gold nanoparticles are the major contribution for the CO₂ adsorption and the C-O dissociation process, respectively. This work would promote the understanding of the light driven electron transfer and photocatalytic CO₂RR on the noble metal.