Imaging the Surface/Interface Morphologies Evolution of Silicon Anodes Using in Situ/Operando Electron Microscopy

Study of Interfacial Reaction Mechanism of Silicon Anodes with Different Surfaces by Using the In Situ Spectroscopy Technique

The interfacial reaction of a silicon anode is very complex, which is closely related with the electrolyte components and surface elements' chemical status of the Si anode. It is crucial to elucidate the formation mechanism of the solid electrolyte interphase (SEI) on the silicon anode, which promotes the development of a stable SEI. However, the interface reaction mechanism on the silicon surface is closely related to the surface components. This work systematically investigates the interfacial reaction mechanism on silicon materials with three representative coatings of graphene, TiO2, and SiO2 by ex situ X-ray photoelectron spectroscopy (XPS) and dynamic analysis in operando attenuated total reflection-Fourier transform infrared (ATR-FTIR), in situ revealing the different ring-opening mechanisms of fluoro-ethylene carbonate (FEC) and ethylene carbonate (EC) on different silicon surfaces with varying electrical conductivities. Due to the different ring-opening mechanisms, the final decomposition product of FEC on the graphene/electrolyte interface is stable LiF, while on the oxide (native SiO2 or emerging TiO2) interface, it forms an unstable solid lithium compound •CH2CHFOCO2Li. This study demonstrates that the formation mechanism of the SEI on silicon-based electrodes is related to the electron conductivity of surface elements, providing a theoretical basis for further optimization of silicon-based composite materials.

Unraveling nanosprings: morphology control and mechanical characterization

Nanosprings demonstrate promising mechanical characteristics, positioning them as pivotal components in a diverse array of potential nanoengineering applications. To unlock the full potential of these nanosprings, ongoing research is concentrated on emulating springs at the nanoscale in terms of both morphology and function. This review underscores recent advancements in the field and provides a comprehensive overview of the diverse methods employed for nanospring preparation. Understanding the general mechanism behind nanospring formation lays the groundwork for the informed design of nanosprings. The synthesis section delineates four prominent methods employed for nanospring fabrication: vapor phase synthesis, templating methods, post-treatment techniques, and molecular engineering. Each method is critically analyzed, highlighting its strengths, limitations, and potential for scalability. Mechanical properties of nanosprings are explored in depth, discussing their response to external stimuli and their potential applications in various fields such as sensing, energy storage, and biomedical engineering. The interplay between nanospring morphology and mechanical behavior is elucidated, providing insights into the design principles for tailored functionality. Additionally, we anticipate that the evolution of state-of-the-art characterization tools, such as in situ transmission electron microscopy, 3D electron tomography, and machine learning, will significantly contribute to both the study of nanospring mechanisms and their applications.

Revealing microscopic dynamics: in situ liquid-phase TEM for live observations of soft materials and quantitative analysis via deep learning

In various domains spanning materials synthesis, chemical catalysis, life sciences, and energy materials, in situ transmission electron microscopy (TEM) methods exert a profound influence. These methodologies enable the real-time observation and manipulation of gas-phase and liquid-phase reactions at the nanoscale, facilitating the exploration of pivotal reaction mechanisms. Fundamental research areas like crystal nucleation, growth, etching, and self-assembly have greatly benefited from these techniques. Additionally, their applications extend across diverse fields such as catalysis, batteries, bioimaging, and drug delivery kinetics. However, the intricate nature of 'soft matter' presents a challenge due to the unique molecular properties and dynamic behavior of these substances that remain insufficiently understood. Investigating soft matter within in situ liquid-phase TEM settings demands further exploration and advancement compared to other research domains. This research harnesses the potential of in situ liquid-phase TEM technology while integrating deep learning methodologies to comprehensively analyze the quantitative aspects of soft matter dynamics. This study centers on diverse phenomena, encompassing surfactant molecule nucleation, block copolymer behavior, confinement-driven self-assembly, and drying processes. Furthermore, deep learning techniques are employed to precisely analyze Ostwald ripening and digestive ripening dynamics. The outcomes of this study not only deepen the understanding of soft matter at its fundamental level but also serve as a pivotal foundation for developing innovative functional materials and cutting-edge devices.