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Abstract The development and design of energy materials are essential for improving the efficiency, sustainability, and durability of energy systems to address climate change issues. However, optimizing and developing energy materials can be challenging due to large and complex search spaces. With the advancements in computational power and algorithms over the past decade, machine learning (ML) techniques are being widely applied in various industrial and research areas for different purposes. The energy material community has increasingly leveraged ML to accelerate property predictions and design processes. This article aims to provide a comprehensive review of research in different energy material fields that employ ML techniques. It begins with foundational concepts and a broad overview of ML applications in energy material research, followed by examples of successful ML applications in energy material design. We also discuss the current challenges of ML in energy material design and our perspectives. Our viewpoint is that ML will be an integral component of energy materials research, but data scarcity, lack of tailored ML algorithms, and challenges in experimentally realizing ML-predicted candidates are major barriers that still need to be overcome. 

With the development of advanced micro/nanoscale technologies, two-dimensional materials have emerged from laboratories and have been applied in practice. To investigate the mechanisms of solid– liquid interactions in potential applications, molecular dynamics simulations are employed to study the flow behavior of n-dodecane (C12) molecules confined in black phosphorus (BP) nanochannels. Under the same external conditions, a significant difference in the velocity profiles of fluid molecules is observed when flowing along the armchair and zigzag directions of the BP walls. The average velocity of C12 molecules flowing along the zigzag direction is 9-fold higher than that along the armchair direction. The friction factor at the interface between C12 molecules and BP nanochannels and the orientations of C12 molecules near the BP walls are analyzed to explain the differences in velocity profiles under various flow directions, external driving forces, and nanochannel widths. The result shows that most C12 molecules are oriented parallel to the flow direction along the zigzag direction, leading to a relatively smaller friction factor hence a higher average velocity. In contrast, along the armchair direction, most C12 molecules are oriented perpendicular to the flow direction, leading to a relatively larger friction factor and thus a lower average velocity. This work provides important insights into understanding the anisotropic liquid flows in nanochannels. 

Abstract Wide‐bandgap semiconductors (WBGS) with energy bandgaps larger than 3.4 eV for GaN and 3.2 eV for SiC have gained attention for their superior electrical and thermal properties, which enable high‐power, high‐frequency, and harsh‐environment devices beyond the capabilities of conventional semiconductors. Pushing the potential of WBGS boundaries, current research is redefining the field by broadening the material landscape and pioneering sophisticated synthesis techniques tailored for state‐of‐the‐art device architectures. Efforts include the growth of freestanding nanomembranes, the leveraging of unique interfaces such as van der Waals (vdW) heterostructure, and the integration of 2D with 3D materials. This review covers recent advances in the synthesis and applications of freestanding WBGS nanomembranes, from 2D to 3D materials. Growth techniques for WBGS, such as liquid metal and epitaxial methods with vdW interfaces, are discussed, and the role of layer lift‐off processes for producing freestanding nanomembranes is investigated. The review further delves into electronic devices, including field‐effect transistors and high‐electron‐mobility transistors, and optoelectronic devices, such as photodetectors and light‐emitting diodes, enabled by freestanding WBGS nanomembranes. Finally, this review explores new avenues for research, highlighting emerging opportunities and addressing key challenges that will shape the future of the field.