Bulk and surface chemistry database (DB) are necessary to compute plasma parameters using plasma simulators. As the high quality of the DB is closely related to the accuracy enhancement of simulations, we attempted to gather reliable data from previously published articles. However, previous systems could not accommodate various types of information such as electron collision cross sections, rate coefficients of heavy particle reactions, sticking coefficients on the surfaces, and thermodynamic data. Therefore, we developed a new version of the DB system to provide plasma data for researchers in related fields; this new DB system is designed to retrieve data such as electron collision cross sections, rate coefficient, and thermodynamics data. About 35,000 collision cross sections and 74,000 rate coefficients for 90 chemical species and thermodynamic data for 55 chemicals are provided in the numerical and graphical forms in this DB system.

The fabrication of battery anodes simultaneously exhibiting large capacity, fast charging capability, and high cyclic stability is challenging because these properties are mutually contrasting in nature. Here, we report a rational strategy to design anodes outperforming the current anodes by simultaneous provision of the above characteristics without utilizing nanomaterials and surface modifications. This is achieved by promoting spontaneous structural evolution of coarse Sn particles to 3Dnetworked nanostructures during battery cycling in an appropriate electrolyte. The anode steadily exhibits large capacity (∼480 mAhg −1 ) and energy retention capability (99.9%) during >1500 cycles even at an ultrafast charging rate of 12 690 mAg −1 (15C). The structural and chemical origins of the measured properties are explained using multiscale simulations combining molecular dynamics and density functional theory calculations. The developed method is simple, scalable, and expandable to other systems and provides an alternative robust route to obtain nanostructured anode materials in large quantities.

We present a non-invasive approach for monitoring plasma parameters such as the electron temperature and density inside a radio-frequency (RF) plasma nitridation device using optical emission spectroscopy (OES) in conjunction with multivariate data analysis. Instead of relying on a theoretical model of the plasma emission to extract plasma parameters from the OES, an empirical correlation was established on the basis of simultaneous OES and other diagnostics. Additionally, we developed a machine learning (ML)-based virtual metrology model for real-time Te and ne monitoring in plasma nitridation processes using an in situ OES sensor. The results showed that the prediction accuracy of electron density was 97% and that of electron temperature was 90%. This method is especially useful in plasma processing because it provides in-situ and real-time analysis without disturbing the plasma or interfering with the process.

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The charging process of secondary batteries is always associated with a large volume expansion of the alloying anodes, which in many cases, develops high compressive residual stresses near the propagating interface. This phenomenon causes a significant reduction in the rate performance of the anodes and is detrimental to the development of fast‐charging batteries. However, for the Na‐Sn battery system, the residual stresses that develop near the interface are not stored, but are relieved by the generation of high‐density dislocations in crystalline Sn. Direct‐contact diffusion experiments show that these dislocations facilitate the preferential transport of Na and accelerate the Na diffusion into crystalline Sn at ultrafast rates via “dislocation‐pipe diffusion”. Advanced analyses are performed to observe the evolution of atomic‐scale structures while measuring the distribution and magnitude of residual stresses near the interface. In addition, multi‐scale simulations that combined classical molecular dynamics and first‐principles calculations are performed to explain the structural origins of the ultrafast diffusion rates observed in the Na‐Sn system. These findings not only address the knowledge gaps regarding the relationship between pipe diffusion and the diffusivity of carrier ions but also provide guidelines for the appropriate selection of anode materials for use in fast‐charging batteries.