Self-Powered Random Number Generator Based on Coupled Triboelectric and Electrostatic Induction Effects at the Liquid–Dielectric Interface

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• 作者：Aifang Yu ; Xiangyu Chen ; Haotian Cui ; Libo Chen ; Jianjun Luo ; Wei Tang ; Mingzeng Peng ; Yang Zhang ; Junyi ZhaiZhong Lin Wang
• 刊名：ACS Nano
• 出版年：2016
• 出版时间：December 27, 2016
• 年：2016
• 卷：10
• 期：12
• 页码：11434-11441
• 全文大小：580K
• ISSN：1936-086X

文摘

Modern cryptography increasingly employs random numbers generated from physical sources in lieu of conventional software-based pseudorandom numbers, primarily owing to the great demand of unpredictable, indecipherable cryptographic keys from true random numbers for information security. Thus, far, the sole demonstration of true random numbers has been generated through thermal noise and/or quantum effects, which suffers from expensive and complex equipment. In this paper, we demonstrate a method for self-powered creation of true random numbers by using triboelectric technology to collect random signals from nature. This random number generator based on coupled triboelectric and electrostatic induction effects at the liquid–dielectric interface includes an elaborately designed triboelectric generator (TENG) with an irregular grating structure, an electronic–optical device, and an optical–electronic device. The random characteristics of raindrops are harvested through TENG and consequently transformed and converted by electronic–optical device and an optical–electronic device with a nonlinear characteristic. The cooperation of the mechanical, electrical, and optical signals ensures that the generator possesses complex nonlinear input–output behavior and contributes to increased randomness. The random number sequences are deduced from final electrical signals received by an optical–electronic device using a familiar algorithm. These obtained random number sequences exhibit good statistical characteristics, unpredictability, and unrepeatability. Our study supplies a simple, practical, and effective method to generate true random numbers, which can be widely used in cryptographic protocols, digital signatures, authentication, identification, and other information security fields.