Data-driven science and technology offer transformative tools and methods to science. This review article highlights the latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS), i.e., plasma science whose progress is driven strongly by data and data analyses. Plasma is considered to be the most ubiquitous form of observable matter in the universe. Data associated with plasmas can, therefore, cover extremely large spatial and temporal scales, and often provide essential information for other scientific disciplines. Thanks to the latest technological developments, plasma experiments, observations, and computation now produce a large amount of data that can no longer be analyzed or interpreted manually. This trend now necessitates a highly sophisticated use of high-performance computers for data analyses, making artificial intelligence and machine learning vital components of DDPS. This article contains seven primary sections, in addition to the introduction and summary. Following an overview of fundamental data-driven science, five other sections cover widely studied topics of plasma science and technologies, i.e., basic plasma physics and laboratory experiments, magnetic confinement fusion, inertial confinement fusion and high-energy-density physics, space and astronomical plasmas, and plasma technologies for industrial and other applications. The final section before the summary discusses plasma-related databases that could significantly contribute to DDPS. Each primary section starts with a brief introduction to the topic, discusses the state-of-the-art developments in the use of data and/or data-scientific approaches, and presents the summary and outlook. Despite the recent impressive signs of progress, the DDPS is still in its infancy. This article attempts to offer a broad perspective on the development of this field and identify where further innovations are required.

SiO2 and Si etching in a CF4/O2/Ar plasma has been carried out in an electron cyclotron resonance etcher over a wide range of conditions. The etch rate has been compared with the ion energy flux to the wafer surface, JiEi, and the atomic fluorine density in the gas phase, nF. It is found that the etch rate can be divided into two regimes by a critical value of nF/(JiEi), the ratio of the atomic fluorine density to the ion energy flux. The critical value can be determined from a contour plot of the etch rate as a function of the ion energy flux and the atomic fluorine density. The critical value of nF/(JiEi) for Si is higher than that for SiO2. For nF/(JiEi) higher than the critical value, the SiO2 etch rate linearly increases with the ion energy flux, and the Si etch rate shows a nonlinear increase with the ion energy flux. For nF/(JiEi) lower than the critical value, both SiO2 and Si etch rates linearly increase with the atomic fluorine density.