今日获知，贺喜雪同学的论文Machine Learning Empowers Electrocatalytic CO2 Reduction Reaction被Green Chemistry接收。论文受到国家自然科学基金、陕西省杰出青年科学基金的资助。论文摘要如下：

As global decarbonization imperatives intensify, the electrocatalytic CO2 reduction reaction (CO2RR) has emerged as a key area of research in sustainable energy research. Conventional experimental methods are constrained by factors such as prolonged catalyst screening cycles and unclear reaction mechanisms. Machine learning (ML), a data-driven modeling approach, has revolutionized catalyst development by significantly accelerating discovery and reducing associated costs.  This review is structured as follows: It initially outlines the ML-assisted design workflow specifically for electrocatalytic CO2RR. Subsequently, it reviews the current progress of ML applications in CO2RR, with a particular emphasis on catalyst design and screening, optimization of reaction conditions, and mechanistic understanding. Finally, the article discusses the challenges and future perspectives of employing ML in this field, thereby aiming to provide useful insights for ongoing and future research efforts.