Machine-learning descriptor search on the density of states profile of bimetallic alloy systems and comparison with the d-band center theory

In this study, the electronic density of states (DOSs) calculated with density functional theory (DFT) were analyzed by the machine-learning techniques. More than 400 pure metal and bimetallic alloy systems were calculated with DFT, and obtained the surface DOSs and the CH3 adsorption energy (Ead). By fitting the Gaussian functions to the DOS, multiple descriptors, such as the Gaussian peak positions, heights, and widths were extracted. Several regression methods, such as the least absolute shrinkage of selection operator (LASSO), random-forest, gradient-boosting, and extra-tree were used to find the relationship between these descriptors and the Ead. The results show that the energy position of the peaks in the d-projected DOS is the most important descriptor, in agreement with the previously known d-band center theory. It was also shown that the peak position in d-projected DOS improves the regression model in addition to the d-band center, since it reduces the regression error.

Work Function-Guided Electrocatalyst Design

The development of high-performance electrocatalysts for energy conversion reactions is crucial for advancing global energy sustainability. The design of catalysts based on their electronic properties (e.g., work function) has gained significant attention recently. Although numerous reviews on electrocatalysis have been provided, no such reports on work function-guided electrocatalyst design are available. Herein, a comprehensive summary of the latest advancements in work function-guided electrocatalyst design for diverse electrochemical energy applications is provided. This includes the development of work function-based catalytic activity descriptors, and the design of both monolithic and heterostructural catalysts. The measurement of work function is first discussed and the applications of work function-based catalytic activity descriptors for various reactions are fully analyzed. Subsequently, the work function-regulated material-electrolyte interfacial electron transfer (IET) is employed for monolithic catalyst design, and methods for regulating the work function and optimizing the catalytic performance of catalysts are discussed. In addition, key strategies for tuning the work function-governed material-material IET in heterostructural catalyst design are examined. Finally, perspectives on work function determination, work function-based activity descriptors, and catalyst design are put forward to guide future research. This work paves the way to the work function-guided rational design of efficient electrocatalysts for sustainable energy applications.

Unveiling the Role of Termination Groups in Stabilizing MXenes in Contact with Water

MXenes are versatile 2D materials demonstrating outstanding electrochemical and physical properties, but their practical use is limited, because of fast degradation in an aqueous environment. To prevent the degradation of MXenes, it is essential to understand the atomistic details of the reaction and to identify active sites. In this letter, we provided a computational analysis of the degradation processes at the interface between MXene basal planes and water using enhanced sampling ab initio molecular dynamics simulations and symbolic regression analysis. Our results indicate that the reactivity of Ti sites toward the water attack reaction depends on both local coordination and chemical composition of the MXene surfaces. Decreasing the work function of the Ti3C2Tx surfaces and avoiding Ti sites that are loosely anchored to the subsurface (e.g., O-coordinated) can improve surface stability. The developed computational framework can be further used to investigate other possible culprits of the degradation reaction, including the role of defects and edges.

Key role of subsurface doping in optimizing active sites of IrO2 for the oxygen evolution reaction

The oxygen evolution reaction (OER) over a family of metal-doped rutile IrO2 catalysts is theoretically investigated by controlling the species and position of doped elements. The subsurface substitution doping is demonstrated to efficiently regulate the eg-filling of surface iridium sites and lower the adsorption strength of oxygen intermediates, improving the catalytic activity for the OER. Finally, based on screening, subsurface Cu- and Li-doped IrO2 models stand near the top of the volcano plot and display high levels of structural stability toward acidic OER.

A weakened Fermi level pinning induced adsorption energy non-charge-transfer mechanism during O2 adsorption in silicene/graphene heterojunctions

Understanding the mechanisms of gas adsorption on a solid surface and making this process tunable are of great significance in fundamental science and industrial applications. Bond creation and charge transfer are often used to explain the origin of adsorption energy (Ead). However, in this study, a new mechanism is observed in O2 adsorption on pure silicene (PS) and silicene/graphene heterojunction (SGH) surfaces, in which the charge distribution remains almost unchanged, but Ead still has a significant change in the order of 0.3 eV. The weakened Fermi level pinning effect is found to be responsible for this interesting behavior and the variation of Ead is approximately equal to the change of work function. Furthermore, this effect is independent of the twist angles in the van der Waals SGH. Our results are consistent with experimental observations in overcoming the degradation of silicene in air.

Machine Learning Descriptors for Data-Driven Catalysis Study

Traditional trial-and-error experiments and theoretical simulations have difficulty optimizing catalytic processes and developing new, better-performing catalysts. Machine learning (ML) provides a promising approach for accelerating catalysis research due to its powerful learning and predictive abilities. The selection of appropriate input features (descriptors) plays a decisive role in improving the predictive accuracy of ML models and uncovering the key factors that influence catalytic activity and selectivity. This review introduces tactics for the utilization and extraction of catalytic descriptors in ML-assisted experimental and theoretical research. In addition to the effectiveness and advantages of various descriptors, their limitations are also discussed. Highlighted are both 1) newly developed spectral descriptors for catalytic performance prediction and 2) a novel research paradigm combining computational and experimental ML models through suitable intermediate descriptors. Current challenges and future perspectives on the application of descriptors and ML techniques to catalysis are also presented.

Understanding the effect of mechanical strains on the catalytic activity of transition metals

The effect of elastic strains on the catalytic activity for the hydrogen evolution reaction (HER) and the oxygen reduction reaction (ORR) was analyzed on thirteen late transition metals: eight (111) surfaces of fcc metals (Ni, Cu, Pd, Ag, Pt, Au, Rh, Ir) and five (0001) surfaces of hcp metals (Co, Zn, Cd, Ru, and Os). The corresponding adsorption energies for the different intermediate reactions up to strains dictated by the mechanical stability limits were previously obtained by means of density functional theory calculations. It was found that the elastic strains can be used to tune the catalytic activity of different metals by reducing the energy barrier of the rate limiting step and even to reach the cusp of the volcano plot. The largest changes in catalytic activity with strain for the HER were found in Pt, Au, and Ir while Co and Ni were very insensitive to this strategy. In the case of the ORR, the catalytic activity of Au could be enhanced by the application of tensile strains while that of Cu, Ni, Pt, Pd, Rh, Co, Ru, and Os was improved by the application of compressive strains. However, the catalytic activity of Ir was rather insensitive to mechanical deformations. Elastic strains were able to modify the rate limiting reaction in Au, Pt, Ag, and Os and it was possible to achieve the cusp of the volcano plot in these metals. Final, mechanical instabilities were attained at small strains in Zn and Cd, which did not lead to significant changes in the catalytic activity for the HER and the ORR. These results provide a framework to systematically investigate the application of elastic strains in the design of new catalysts.

Modulation rate on adsorption and catalysis of 2D Pt: the effects of adsorbate-induced surface stress

Recently it is reported for ultrathin 2D metals, positive surface stress of clean surface (τ1) can induce considerable compressive lattice strain towards optimized adsorption energy and catalytic properties (Science 363,...

Molecular-level insights into the electronic effects in platinum-catalyzed carbon monoxide oxidation

A molecular-level understanding of how the electronic structure of metal center tunes the catalytic behaviors remains a grand challenge in heterogeneous catalysis. Herein, we report an unconventional kinetics strategy for bridging the microscopic metal electronic structure and the macroscopic steady-state rate for CO oxidation over Pt catalysts. X-ray absorption and photoelectron spectroscopy as well as electron paramagnetic resonance investigations unambiguously reveal the tunable Pt electronic structures with well-designed carbon support surface chemistry. Diminishing the electron density of Pt consolidates the CO-assisted O2 dissociation pathway via the O*-O-C*-O intermediate directly observed by isotopic labeling studies and rationalized by density-functional theory calculations. A combined steady-state isotopic transient kinetic and in situ electronic analyses identifies Pt charge as the kinetics indicators by being closely related to the frequency factor, site coverage, and activation energy. Further incorporation of catalyst structural parameters yields a novel model for quantifying the electronic effects and predicting the catalytic performance. These could serve as a benchmark of catalyst design by a comprehensive kinetics study at the molecular level.

New insights into O and OH adsorption on the Pt-Co alloy surface: effects of Pt/Co ratios and structures

In this study, the electronic structure and adsorption properties of O and OH for a series of Pt-Co alloys with different Pt/Co ratios (5 : 1, 2 : 1, 1 : 1, 1 : 2, and 1 : 5) were systematically studied using density functional theory calculations. Our computational results demonstrated that the introduced Co atoms have multiple effects on the surface electronic structure in different atomic layers of the alloy, leading to the discrepancies in the electronic structure between Pt-skin structures and non-Pt-skin structures. Moreover, the influence of the surface electronic structure on the adsorption of O and OH slightly differs. Indeed, the adsorption of O is more remarkably affected by the Pt/Co ratio than the OH adsorption and better follows the d-band center theory. Due to the difference of the alloy structure and the effect of different layer Co atoms, the adsorption of O and OH on the alloy configurations with the same Pt/Co ratio has different outcomes. Our results suggested that the oxygen reduction reaction (ORR) activity is related not only to the Pt/Co ratio of alloy surfaces but also to the specific surface structure. Our research can provide theoretical insights into the development of ORR catalysts.

Biomass hydrodeoxygenation catalysts innovation from atomistic activity predictors

Circular economy emphasizes the idea of transforming products involving economic growth and improving the ecological system to reduce the negative consequences caused by the excessive use of raw materials. This can be achieved with the use of second-generation biomass that converts industrial and agricultural wastes into bulk chemicals. The use of catalytic processes is essential to achieve a viable upgrade of biofuels from the lignocellulosic biomass. We carried out density functional theory calculations to explore the relationship between 13 transition metals (TMs) properties, as catalysts, and their affinity for hydrogen and oxygen, as key species in the valourization of biomass. The relation of these parameters will define the trends of the hydrodeoxygenation (HDO) process on biomass-derived compounds. We found the hydrogen and oxygen adsorption energies in the most stable site have a linear relation with electronic properties of these metals that will rationalize the surface's ability to bind the biomass-derived compounds and break the C-O bonds. This will accelerate the catalyst innovation for low temperature and efficient HDO processes on biomass derivates, e.g. guaiacol and anisole, among others. Among the monometallic catalysts explored, the scaling relationship pointed out that Ni has a promising balance between hydrogen and oxygen affinities according to the d-band centre and d-band width models. The comparison of the calculated descriptors to the adsorption strength of guaiacol on the investigated surfaces indicates that the d-band properties alone are not best suited to describe the trend. Instead, we found that a linear combination of work function and d-band properties gives significantly better correlation. This article is part of a discussion meeting issue 'Science to enable the circular economy'.

Impact of Active Site Density on Oxygen Reduction Reactions Using Monodispersed Fe-N-C Single-Atom Catalysts

Exploring the impact of active site density on catalytic reactions is crucial for reaching a more comprehensive understanding of how single-atom catalysts work. Utilizing density functional theory calculations, we have systematically investigated the neighboring effects between two adjacent Fe-N-C sites of monodispersed Fe-N-C single-atom catalysts on oxygen reduction reaction (ORR). While the thermodynamic limiting potential (U_L) is strongly dependent on the intersite distance and the nature of adjacent active sites in FeN₃, it is almost invariable in FeN₄ until two FeN₄ sites are ∼4 Å apart. Further, under certain conditions, an otherwise unfavorable physisorbed-O₂-initiated 2e^- pathway becomes feasible due to charge transfer between reactive species and graphene support. Our results cast new insight into the rational design of high-density single-atom catalysts and may create an alternative route to manipulate their catalytic activities.

Adsorption energy scaling relation on bimetallic magnetic surfaces: role of surface magnetic moments

The scaling relationships between the adsorption energies of different reaction intermediates have a tremendous effect in the field of surface science, particularly in predicting new catalytic materials. In the last few decades, these scaling laws have been extensively studied and interpreted by a number of research groups which makes them almost universally accepted. In this work, we report the breakdown of the standard scaling law in magnetic bimetallic transition metal (TM) surfaces for hydrogenated species of oxygen (O), carbon (C), and nitrogen (N), where the adsorption energies are estimated using density functional theory (DFT). We propose that the scaling relationships do not necessarily rely solely on the adsorbates, they can also be strongly dependent on the surface properties. For magnetic bimetallic TM surfaces, the magnetic moment plays a vital role in the estimation of adsorption energy, and therefore towards the linear scaling relation.

Active Sites in Heterogeneous Catalytic Reaction on Metal and Metal Oxide: Theory and Practice

Active sites play an essential role in heterogeneous catalysis and largely determine the reaction properties. Yet identification and study of the active sites remain challenging owing to their dynamic behaviors during catalysis process and issues with current characterization techniques. This article provides a short review of research progresses in active sites of metal and metal oxide catalysts, which covers the past achievements, current research status, and perspectives in this research field. In particular, the concepts and theories of active sites are introduced. Major experimental and computational approaches that are used in active site study are summarized, with their applications and limitations being discussed. An outlook of future research direction in both experimental and computational catalysis research is provided.

Insight into the adsorption of a liquid organic hydrogen carrier, perhydro-i-dibenzyltoluene (i = m, o, p), on Pt, Pd and PtPd planar surfaces

Liquid organic hydrogen carriers (LOHCs) are considered to be safe and efficient hydrogen storage media with high hydrogen storage capacities. Adsorption of the LOHC perhydro-i-dibenzyltoluene (i = meta (m), ortho (o), para (p)) isomers on (100), (110) and (111) planar surfaces of Pd, Pt and a 50 : 50 PtPd alloy were investigated, using density functional theory with van der Waals corrections. The calculated heats of formation of the isomers indicated that all the isomers considered were energetically stable. Surface selectivity to isomer adsorption was investigated, using isomer adsorption preference and energies. The (110) surface was found to be highly preferred by the different isomers, compared with both the (100) and the (111) surfaces. Among the isomers, isomer-surface attachment occurred most often in the case of perhydro-m-dibenzyltoluene and perhydro-o-dibenzyltoluene adsorption. The LOHC isomer adsorption on different surfaces was found to be spontaneous, energetically stable and exothermic, with high isomer adsorption preference for Pt and PtPd surfaces, compared with Pd surfaces. This indicates the ease of loading of the LOHC on Pt and PtPd surfaces, for subsequent dehydrogenation.

Support effects on adsorption and catalytic activation of O2 in single atom iron catalysts with graphene-based substrates

The adsorption and catalytic activation of O₂ on single atom iron catalysts with graphene-based substrates were investigated systematically by density functional theory calculation.