Artificial intelligence in nanotechnology

被引:75
作者
Sacha, G. M. [1 ]
Varona, P. [1 ]
机构
[1] Univ Autonoma Madrid, Grp Neurocomp Biol, Escuela Politecn Super, E-28049 Madrid, Spain
关键词
NEURAL-NETWORKS; STRUCTURAL-PROPERTIES; TUNNELING MICROSCOPE; DIELECTRIC RESPONSE; MOLECULAR-DYNAMICS; CARBON NANOTUBES; FORCE MICROSCOPY; PARTICLE-SIZE; DESIGN; SURFACE;
D O I
10.1088/0957-4484/24/45/452002
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.
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页数:13
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