Compared to conventional alloys, multicomponent high-entropy alloys (HEAs) have
received considerable attention in recent years owing to their exceptional phase stability …

Photonic neural networks (PNNs), utilizing light-based technologies, show immense
potential in artificial intelligence (AI) and computing. Compared to traditional electronic …

The application of machine learning (ML) to materials chemistry can accelerate the design
process, and when coupled with a detailed explanation, can guide future research. Shapley …

The prediction of chemical synthesis pathways plays a pivotal role in materials science
research. Challenges, such as the complexity of synthesis pathways and the lack of …

The field of catalysis holds paramount importance in shaping the trajectory of sustainable
development, prompting intensive research efforts to leverage artificial intelligence (AI) in …

In recent years, machine learning leveraging neural networks has emerged as a potent tool
across various domains, including natural language processing, image recognition, game …

Machine learning with neural networks is now becoming a more and more powerful tool for
various tasks, such as natural language processing, image recognition, winning the game …

The control of low dimensional materials holds potential for revolutionizing the electronic,
thermal, and thermoelectric materials engineering. Through strategic manipulation and …