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Special topics


Special topics

Within each issue of National Science Review, you will find comprehensive coverage of a specific research area with significant research progress either in China or internationally. Special Topics include an overview of major advances in the field, extensive review articles, perspectives, research highlights, and interviews with prominent scientists.

Explore the collection of Special Topics published in National Science Review below.

Abstract: Research in advanced materials is continuously driving modern technologies forward. For example, semiconductors have laid the foundation for today’s electronics industry. While constantly searching for new materials in nature, another approach is to craft novel composite materials beyond the naturally available properties. This is accomplished by directly designing the arrangement of the ‘atoms’ into a desired architecture or geometry, instead of chemical compositions in natural materials. This new type of artificial material is called metamaterial—a new frontier of science, which first emerged in the field of optics and photonics. In the past two decades, we have witnessed an explosion of the meta-concept, bending the fundamental rules of light. This consequently realized the full exploitation of dielectric and metallic properties in the permittivity–permeability plane, leading to unique optical effects, such as negative optical refractive index and superlenses. These intriguing light–matter interaction behaviors, enabled by metamaterials, provide the further prospect of new functional photonic technology…
National Science Review, Volume 5, Issue 2, March 2018.

Machine Learning
Abstract: The name ‘machine learning’ was coined in 1959 [1], while the most widely quoted formal definition—‘A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E’—was given in the first textbook about machine learning by T. Mitchell in 1997 [2]. Roughly speaking, machine learning aims to enable computers to improve performance by experience. As experience usually appear as data examples, the main focus of machine learning is actually about the study and construction of learning algorithms that are able to build predictive or descriptive models from data. With the increasing demand of computerized data analysis, machine learning becomes more and more important, and stirs up the current artificial intelligence (AI) boom…
National Science Review, Volume 5, Issue 1, January 2018.

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