This review highlights recent advances in machine learning (ML)‐assisted design of energy
materials. Initially, ML algorithms were successfully applied to screen materials databases …

This review article explores how emerging generative artificial intelligence (GenAI) models,
such as large language models (LLMs), can enhance solution methodologies within process …

Density functional theory (DFT) has been a cornerstone in computational chemistry, physics,
and materials science for decades, benefiting from advancements in computational power …

Material selection is a crucial step in conceptual design due to its significant impact on the
functionality, aesthetics, manufacturability, and sustainability impact of the final product. This …

Non‐trivial relationships link individual materials properties to device‐level performance.
Device optimization therefore calls for new automation approaches beyond the laboratory …

The development of high-performance solid-state lithium-ion batteries (LIBs) requires
designing solid-state electrolytes (SEs) with high ionic conductivity and excellent …

Hydrogen storage materials play a pivotal role in the development of a sustainable
hydrogen economy. However, the discovery and optimization of high-performance storage …

With the advantages of high energy density and low cost, aqueous metal batteries have
received widespread attention as energy conversion and storage devices. Polymer gels are …

The Na super ionic conductor (NASICON), which has outstanding structural stability and a
high operating voltage, is an appealing material for overcoming the limits of low specific …

All solid-state lithium batteries (ASSLBs) have high safety and high energy density, and thus,
are considered one of the most promising directions for battery development. However, solid …