Understanding ZIF particle chemical etching dynamics and morphology manipulation: in situ liquid phase electron microscopy and 3D electron tomography application

Pore-Specific Anisotropic Etching of Zeolitic Imidazolate Frameworks by Carboxylic Acid Vapors

Anisotropic etching is a powerful way to customize metal-organic frameworks with advanced nanostructures, but it is still in its infancy. Herein, we proposed an unprecedented etching strategy that created anisotropic hollow structures in various zeolitic imidazolate framework (ZIF) nano/single crystals via pore-specific carving. The etching occurred through a newly discovered gas-solid reaction where carboxylic acid vapors bind with ligands in ZIFs at room temperature to form ionic liquid (IL). A series of experiments were conducted to decode the origin of anisotropy and the "hollowing out" effect. We found that large pore openings on {111} facets provide access for the entry of carboxylic acid vapors and the outflow of the IL, resulting in pore-dependent anisotropy features. The unique "etching after adsorption" mechanism and the adsorption capacity of the IL enable acid vapors to hollow out nanocrystals and even single crystals. By altering carboxylic acids and ligands in ZIFs, the etching process can be precisely tuned from the inside out or the outside in. This new method demonstrates broad universality and brings unprecedented morphologies and complexities. It may offer great opportunities for achieving purposeful modification of ZIFs and the rational construction of intricate architectures.

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.