相关论文: Atom-by-atom design of metal oxide catalysts for t…
The transition to sustainable green hydrogen production demands innovative electrocatalyst design strategies that can overcome current technological limitations. This study introduces a comprehensive data-driven approach to predicting and…
The correlation between ex situ electronic conductivity, oxygen vacancy content, flat-band potential (Efb), and the oxygen evolution reaction (OER) activity for a wide range of perovskite compositions are investigated experimentally and…
The oxygen evolution reaction (OER) is considered a key reaction for electrochemical energy conversion but slow kinetics hamper application in electrolyzers, metal-air batteries and other applications that rely on sustainable protons from…
Symbolic regression (SR) is an emerging method for building analytical formulas to find models that best fit data sets. Here, SR was used to guide the design of new oxide perovskite catalysts with improved oxygen evolution reaction (OER)…
Transition metal oxides are state-of-the-art materials for catalysing the oxygen evolution reaction (OER), whose slow kinetics currently limit the efficiency of water electrolysis. However, microscale physicochemical heterogeneity between…
Discovering new materials that efficiently catalyze the oxygen reduction and evolution reactions is critical for facilitating the widespread adoption of solid oxide fuel cell and electrolyzer (SOFC/SOEC) technologies. Here, we develop…
Oxygen evolution reaction (OER) with intractable high overpotential is the rate-limiting step for rechargeable metal-air battery, water electrolysis systems, and solar fuels devices. There exists a spin state transition from spin singlet…
Perovskite oxides are promising catalysts for oxygen evolution reaction (OER), yet the huge chemical space remains largely unexplored due to the lack of effective approaches. Here, we report the distilling of accurate descriptors from…
Explainable machine learning can help to discover new physical relationships for material properties. To understand the material properties that govern the activation energy for oxygen diffusion in perovskites and pyrochlores, we build a…
The efficiency of $H_2$ production via water electrolysis is typically limited to the sluggish oxygen evolution reaction (OER). As such, significant emphasis has been placed upon improving the rate of OER through the anode catalyst. More…
Developing advanced catalysts for acidic oxygen evolution reaction (OER) is crucial for sustainable hydrogen production. This study introduces a novel, multi-stage machine learning (ML) approach to streamline the discovery and optimization…
The development of machine learning models for electrocatalysts requires a broad set of training data to enable their use across a wide variety of materials. One class of materials that currently lacks sufficient training data is oxides,…
Understanding and predicting the activity of oxide perovskite catalysts for the oxygen evolution reaction (OER) requires descriptors that are both accurate and physically interpretable. While symbolic regression (SR) offers a path to…
This work highlights the potential of earth-abundant mixed-metal oxide catalysts for the acid-based oxygen evolution reaction. These catalysts offer numerous combinations of metal-centre compositions, which can enhance catalytic activity…
The discovery and design of new materials which can efficiently catalyze the oxygen reduction and evolution reactions at reduced temperatures is important for facilitating the widespread adoption of fuel cell and electrolyzer technologies.…
Electrocatalytic water splitting, which produces hydrogen and oxygen through water electrolysis, is a promising method for generating renewable, carbon-free alternative fuels. However, its widespread adoption is hindered by the high costs…
Metal-organic frameworks (MOFs) provide a versatile and tailorable material platform that embody many desirable attributes for photocatalytic water-splitting. The approach taken in this study was to use Density Functional Theory (DFT) to…
In this study, we address the significant challenge of overcoming limitations in catalytic efficiency for the oxygen evolution reaction (OER). The current linear scaling relationships hinder the optimization of electrocatalytic performance.…
A comprehensive understanding of the electrode-electrolyte interface in energy conversion systems remains challenging due to the complex and multifaceted nature of interfacial processes. This complexity hinders the development of more…
The discovery and optimization of high-performance materials is the basis for advancing energy conversion technologies. To understand composition-property relationships, all available data sources should be leveraged: experimental results,…