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.

Clear-Box Machine Learning for Virtual Screening of 2D Nanozymes to Target Tumor Hydrogen Peroxide

Targeting tumor hydrogen peroxide (H₂ O₂ ) with catalytic materials has provided a novel chemotherapy strategy against solid tumors. Because numerous materials have been fabricated so far, there is an urgent need for an efficient in silico method, which can automatically screen out appropriate candidates from materials libraries for further therapeutic evaluation. In this work, adsorption-energy-based descriptors and criteria are developed for the catalase-like activities of materials surfaces. The result enables a comprehensive prediction of H₂ O₂ -targeted catalytic activities of materials by density functional theory (DFT) calculations. To expedite the prediction, machine learning models, which efficiently calculate the adsorption energies for 2D materials without DFT, are further developed. The finally obtained method takes advantage of both interpretability of physics model and high efficiency of machine learning. It provides an efficient approach for in silico screening of 2D materials toward tumor catalytic therapy, and it will greatly promote the development of catalytic nanomaterials for medical applications.

Electrocatalytic Hydrogen Oxidation in Alkaline Media: From Mechanistic Insights to Catalyst Design

With the potential to circumvent the need for scarce and cost-prohibitive platinum-based catalysts in proton-exchange membrane fuel cells, anion-exchange membrane fuel cells (AEMFCs) are emerging as alternative technologies with zero carbon emission. Numerous noble metal-free catalysts have been developed with excellent catalytic performance for cathodic oxygen reduction reaction in AEMFCs. However, the anodic catalysts for hydrogen oxidation reaction (HOR) still rely on noble metal materials. Since the kinetics of HOR in alkaline media is 2-3 orders of magnitude lower than that in acidic media, it is a major challenge to either improve the performance of noble metal catalysts or to develop high-performance noble metal-free catalysts. Additionally, the mechanisms of alkaline HOR are not yet clear and still under debate, further hampering the design of electrocatalysts. Against this backdrop, this review starts with the prevailing theories for alkaline HOR on the basis of diverse activity descriptors, i.e., hydrogen binding energy theory and bifunctional theory. The design principles and recent advances of HOR catalysts employing the aforementioned theories are then summarized. Next, the strategies and recent progress in improving the antioxidation capability of HOR catalysts, a thorny issue which has not received sufficient attention, are discussed. Moreover, the significance of correlating computational models with real catalyst structure and the electrode/electrolyte interface is further emphasized. Lastly, the remaining controversies about the alkaline HOR mechanisms as well as the challenges and possible research directions in this field are presented.