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Self-Powered Random Number Generator Based on Coupled Triboelectric and Electrostatic Induction Effects at the Liquid− Dielectric Interface Aifang Yu,†,⊥ Xiangyu Chen,†,⊥ Haotian Cui,‡,⊥ Libo Chen,† Jianjun Luo,† Wei Tang,† Mingzeng Peng,† Yang Zhang,† Junyi Zhai,*,† and Zhong Lin Wang*,†,§ †

Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, National Center for Nanoscience and Technology (NCNST), Beijing 100083, China ‡ College of Information Engineering, Northwest A&F University, Yangling 712100, China § School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0245, United States S Supporting Information *

ABSTRACT: 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. KEYWORDS: triboelectric nanogenerator, self-powered, random number generator, true random numbers

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techniques and software for random numbers are becoming increasingly insecure. If random numbers are not credible and can be decoded, the encrypted information could be stolen by the listener-in, resulting in information leakage. Consequently, a series of random number generators (RNG) with different working principles and based on different physical sources has been explored to generate credible random numbers in lieu of conventional pseudorandom numbers,6,7such as RNGs based

nformation security is increasingly important with the accelerated pace of the Internet of everything. In information security systems, cryptography is a critical technology and core approach to protect information, and random numbers are the cornerstone of all cryptography.1−4 For example, photonic information transmission with absolute security in quantum communications is encrypted by random numbers.5 Pseudorandom numbers, which are generated by software-based generation techniques, can be decrypted using an exhaustive method since the generation of random numbers is based on an algorithm and a fixed number “seed”.4 Accordingly, with the dramatically increasing computational speed and capacity for decoding, conventional generation © 2016 American Chemical Society

Received: October 18, 2016 Accepted: December 6, 2016 Published: December 6, 2016 11434

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and optical−electronic device.29 The cooperation of the mechanical, electrical, and optical signals ensures that the generator possesses a complex nonlinear input−output characteristic, which contributes to ample randomness. The random number sequences (sequences of hexadecimal numbers) are deduced from final electrical signals received by the optical−electronic device, using some familiar algorithm. The working mechanism of the random number generator, the statistical characteristic, the autocorrelation and repeatability of number sequences, and the influence of the tile angle of TENG on the randomness were systematically studied. This study provides a simple, practical, and effective method to generate true random numbers for cryptographic protocols, digital signatures, authentication, identification, etc.

on thermal noise, biometric characteristics, entanglement of photons, and polarization of light quanta.5,8−12 However, most of these existing techniques suffer from several practical constraints, including the need for highly efficient and costly single-photon-generating sources, complex electric circuitry, and low noise environments.13,14 In contrast, wind, raindrops, and ocean waves are common natural physical phenomena in our ambient environment, which possess significant random characteristics. The random characteristics of these natural phenomena justly fit the principal rules proposed by Shannon about secure communication and cryptography.15 Moreover, they are inexhaustible with abundant amounts of mechanical energy. If these natural phenomena can be used as a physical source to generate random number sequences through some simple and effective technology instead of expensive and complex equipment, it will bring positive results to information security. Recently, an effective mechanical energy harvesting technology named the triboelectric nanogenerator (TENG) has been demonstrated, which is based on the conjunction of triboelectrification and electrostatic contact/separation between two materials that possess opposite tribopolarity.16−18 Since the first report on the TENG in 2012, its performance has increased dramatically.19−23 This fast growing technology can harvest energy as sustainable self-sufficient micro/nanopower sources from the surrounding environment such as human motion, vibration, mechanical triggering, rotation energy, wind, a moving automobile, flowing water, raindrops, and ocean waves. However, because TENG is an electromechanical device, it can sensitively catch the triggers from the environment, such as amplitude, velocity, frequency, and weight of a moving object. As an effective paradigm for energy harvesting, the TENG-based self-powered system has built up a sequence of sensor devices, which can precisely detect and capture the static and dynamic processes carried by environmental energy through electrical responses without an external power supply.24−30 In these regards, we demonstrated a well-designed RNG for creating true random numbers based on coupled triboelectric and electrostatic induction effects at a liquid−dielectric interface to collect the random signal from raindrops, as shown in Figure 1. This RNG consists of a TENG, an

RESULTS AND DISCUSSION To obtain credible random numbers, we elaborately design a TENG with an irregular grating structure to harvest the random characteristics of raindrops, as shown in Figure 2a. The

Figure 2. (a) Schematic diagram of as fabricated TENG with irregular grating structure. (b) SEM image of surface morphology and contact angle of FEP before and after nano treated. (c) Working mechanism of as fabricated TENG.

raindrops were simulated by water drops generated from a bucket with unequal holes in the bottom. To obtain discrete water drops, the volume of the water in the bucket just covered the bottom of the bucket. The distance between the bucket and TENG was 20 cm. The superhydrophobic nanostructured fluorinated ethylene propylene (FEP) was used as a contact face to harvest the random characteristics of water drops. The superhydrophobic porous structures on the FEP surface were constructed using inductively coupled plasma (ICP) reactive ion etching, as shown in Figure 2b. The mean diameter of the holes determined from SEM images was approximately 300 nm. Because the porous nanostructures contained trapped air, the actual contact area between the surface and water drops was reduced, making the surface superhydrophobic. The inset photos give the change of contact angle before (95°) and after fabricating nanostructures (154°). The superhydrophobic surface will ensure that the water leaves the surface of TENG quickly, which effectively contributes to catch the characteristics of water drops through TENG.

Figure 1. A description of the random number generator based on TENG technology.

electronic−optical device, and an optical−electronic device. As the core part of the RNG, TENG has the dual functions of the power generator and the random signal collector, which greatly simplifies the structure of this RNG. Accordingly, the random characteristics of raindrops can be automatically transformed into random electrical signals by TENG without any power sources. These electrical signals generated by TENG are then transformed and converted by the electronic−optical device 11435

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Figure 3. (a−c) The electrical signals generated from the self-powered RNG when TENG was triggered by single water drop at different position as shown in the inset photo. (d) The result of the generator was triggered by water drops.

can be collected after the water drop leaves the FEP film (Figure 2c, (iii). This process produces sequences of alternating current to the external part. In the case of multiple water drops moving on top of the FEP film, the output current should be the integrated value of each water drop. For simplified understanding, if two water drops merge, the total charge density is considered to be the sum of each water drop. Figure 3 gives the typical output signal of the RNG after being triggered by water drops. In this experiment, the electronic−optical device and optical−electronic device are an LED (luminous waveform of 550 nm) and a photoresistor, respectively. The optical signals generated by TENG and received by photoresistor are all irregular. To understand this phenomenon, the signal characteristics of a single water drop are first studied as shown in Figure 3a−c. It is notable that although the weight and the shape of each water drop were precisely controlled, the amplitude of the induced output signal from TENG is not uniform, which is totally different from the other TENGs that were triggered by a period constant mechanical force.16,18This phenomenon is caused by the fact that the carried charges on each water drop may be varied due to the dynamic interaction with the pipe and the air. Meanwhile, the output of TENG is also different when water drop falls onto the different positions of the FEP film. The width of each grid electrode is changed randomly. Accordingly, the time interval for a water drop to leave one electrode and reach the next electrode is also changed randomly due to the random initial speed of water drops. Therefore, during the process of a water drop sliding across the whole film, the generated current signal will not be periodic, as shown in the inset of Figure 3a−c. In the case of multiple water drops falling at the same time, the tribo-electrification process for each water drop would be the same as in the above analysis, and the output current should be the integrated value of each water drop. Therefore, irregular output signals were observed in Figure 3d, which is the result of this structure and mechanism of this

The operation mode of TENG as shown in Figure 2c can be explained based on free-standing mode, where the width of each grid is changed randomly. Two adjacent grid electrodes belong to different groups (A or B). The electrodes in each group are all electrically short-circuited (with the same electric potential), and the potential differences between two groups are used to generate the output from the terminal parts. The working mechanism of the TENG is based on two triboelectrification processesone between water and air and the other between water and FEP film.22 It is worth noting that the charge on the water drop is positive due to the contact electrification between the water drop and air.22 Meanwhile, the contact between the water drop and FEP film also induces a positive charge on the water drop, which leaves negative charges on the FEP surface. After a series of contact-separate motions between the water drop and FEP surface, the induced negative charges on the FEP surface reach a saturated state. For example, we select the case of the triboelectrical charges on the FEP surface with a saturated state to illustrate the working principle of converting electrostatic energy to electricity (Figure 2c, (i). To introduce the mechanics, the case of a single water drop is studied first. The volume of each drop was fixed at 60 μL as controlled by a programmable syringe pump. As the positively charged water drop approached the FEP thin film (Figure 2c, (ii), a positive electric potential difference was created between two groups of grid electrodes (group A and B). In the short-circuit case, electrons were transferred from A group electrodes to the B electrodes to balance the potential difference. This process produced an instantaneous output current. The charge density on the surface of the water drop affects the inductively transferred charges between grid electrodes, which will determine the output of the TENG. When the water drop moves to the top of the FEP thin film, it alternatively covers the electrode belonging to group A and group B. Therefore, the charge transfers between two electrode groups by turns due to the electrostatic induction. No signals 11436

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Figure 4. Deduced result of a single measurement when the RNG was triggered by water drops. (a) The electrical signals received by photoresistor. (b) The part of deduced hexadecimal random number sequence. (c) The statistic characteristic and (d) autocorrelation of deduced random number sequence.

Figure 5. Results of eight measurements with different sequence lengths. (a) The statistic distribution; (b) autocorrelation; and (c) repeatability.

based on TENG can harvest the irregular characteristics of water drops through the elaborately designed TENG and the transformation and conversion of the LED and photoresistor. The experimental result of the random number generator was triggered by water drops at 100s as shown in Figure 4. Figure 4a displays the electrical signals received by the photoresistor. The deduced hexadecimal random numbers by the familiar algorithm are shown in Figure 4b. The single bit length of this sequence is 160,000, which includes 5000

TENG device. These irregular characteristics of TENG are not changed even if they are inverted by the LED and photoresistor. The signals generated by TENG and received by the photoresistor have good synchronizm except that some signals were filtered out to overcome the energy consumptions of the LED and photoresistor. In contrast, the waveform received by the photoresistor is distinct from the output of TENG due to the nonlinear work characteristics of the LED and photoresistor. The results in Figure 3 indicate that RNG 11437

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Figure 6. Influence of incident angle on the randomness of random numbers. (a) The obtained electrical signals from photoresistor under different incident angle. The summarized (b) statistic characteristic and (c) autocorrelation of deduced random number sequence under different incident angle.

subsequences, and each subsequence consists of 32 bits. This length can be changed by changing the interaction time between the random number generator and water drops. Figure 4c gives the statistical results of these deduced hexadecimal numbers, which are characterized through the occurrence frequency of “0” or “1” at each bit. The distribution of “0” at each bit has good uniformity, and the occurrence frequency of “0” at each bit fluctuates around 1/2, which indicates that the sequence has good equidistribution. The inset data (red number) in Figure 4c is the monobit distribution of this sequence. The occurrence frequencies of “0” and “1” are nearly equal, which indicates that the sequence also has good uniformity. In this case, even the attacker obtained all of the information on the RNG; the probability that the attacker can correctly guess each bit is only 50%. Autocorrelation is the other important characteristic of a random sequence. According to the test standard of U.S.NIST, the calculated autocorrelation result of this sequence is displayed in Figure 3d.31 Only 1% of subsequences do not pass the verification, which indicates that the whole sequence passes the standard test and the interrelations of hexadecimal numbers are independent. This means that although all knowledge about prior bits is given, it is still impossible to predict the next random bit. Meanwhile, the randomness of the number sequence deduced from the signals generated by TENG is also studied as shown in Figure S1. The roles of the electronic−optical device and optical−electronic devices are distinct and vital. Although Figure S1c indicates that the sequence also has good uniformity, up to 3.8% do not pass the autocorrelation verification as shown in Figure S1d, which exhibits that the sequence is not a good random number sequence. Therefore, the cooperation of the electronic−optical device and optical−electronic device ensures that the generator

features complex nonlinear input−output behavior, which amplifies the randomness. The single measurement results in Figure 4 demonstrate good statistical characteristics and unpredictability. To further verify that this random number generator can generate true random numbers, eight experiments with various time lengths were executed. The statistical results are demonstrated in Figure 5a. It is significant that these sequences exhibit good uniformity. Figure 5b gives the autocorrelation results of eight sequences. The percent in each sequence that does not pass the test is 20°, the obtained sequences exhibit good uniformity. Considering the autocorrelation results, 20°< θ < 80° as marked in Figure 6c is suitable to generate true random numbers. These angles well coincide with those of TENG, which can generate significant output. This is because under suitable angles, the randomness of water drops can be harvested and converted to random electrical signals by TENG as much as possible and then be expressed by a random number sequence. Conversely, when the incident angle is too small or too large, the randomness of water drops cannot be well harvested. Consequently, the obtained random number sequences demonstrate poor randomness.

EXPERIMENTAL METHODS Fabrication of the Triboelectric Nanogenerator with Irregular Grating Structure. In this part, an acrylic mask was curved first by a laser cutter. Then the mask was attached on another acrylic substrate for the deposition of Au/Cr interdigital electrodes by a RF magnetron sputtering system. The dimensions of the acrylic substrate used in this paper were 6 cm × 12 cm in width and length. The width of each Au/Cr electrode is not equal from 1 mm to 5 mm. The distance of adjacent electrodes belonging to one groups grid electrodes is fixed and around 2 cm. Two conducting wires were connected to the interdigital electrodes as leads for subsequently electric measurements. Then a FEP film with nanostructure was adhered onto the acrylic plate. The nanostructures on the FEP surface were fabricated by using the inductively coupled plasma (ICP) reactive ion etching. In the etching process, a Cu film with the thickness of about 50 nm as the mask was deposited on the FEP surface. A mixed gas including Ar, O2, and CF4 was introduced in the ICP chamber, where the corresponding flow rates are 15.0, 10.0, and 30 sccm, respectively. The nanostructure was etched under one power source of 200 W to generate a large density of plasma. Algorithm. First, the original signal (x (t)) was converted to a digital signal (X[n]), and two subsignals A[m] and B[m] from X[n] (m ≥ 20) were intercepted. Then, we use convolution to create new signal c[i] by A[m] and B[m]: c[i] = A[m]*B[m] The c[i] was transformed by Vihar wavelet to separate the highfrequency portion φ[w] and the low part of ψ[w]:

φ[w] = (c[i] + c[i + 1])/2 ψ [w] = (c[i] − c[i + 1])/2 We calculate the absolute value of average value of matrix (φ[w])’s (avg) and the absolute value of summation value of matrix (ψ[w]) (sum) and then use this under formula to calculate a 16-bit binary number “hb”.

CONCLUSION In this paper, we successfully demonstrated a well-designed selfpowered RNG for creating true random numbers based on coupled triboelectric and electrostatic induction effects at a liquid−dielectric interface. The RNG include an elaborated TENG with an irregular grating structure, an electronic−optical device, and an optical−electronic device. Under suitable angles (20°< θ < 80°), TENG can precisely extract the random

hb = bin[sum/avg*1000] We discrete Fourier transforms of the signal c[i] to get the information on the frequency domain: N−1

C[k] =

∑ c[i]e−jk(2π / N )i ,

k = 0, 1, 2 , ..., N − 1

i=0

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(5) Wootters, W. K.; Zurek, W. H. A. Single Quantum Cannot be Cloned. Nature 1982, 299, 802−803. (6) Mart’Nez-Peláez, R.; Rico-Novella, F. Weaknesses of an Efficient and Secure Dynamic ID-Based Remote UserAuthentication Scheme. Procedia Technol. 2012, 3, 351−353. (7) Tsai, C. S.; Lee, C. C.; Hwang, M. S. Password Authentication Schemes: Current Status and Key Issues. Int. J. Network Security 2006, 3, 101−115. (8) Petrie, C. S.; Connelly, J. A. A Noise-Based IC Random Number Generator for Applications in Cryptography. IEEE Trans. Circuits Syst. I-Regul. Pap. 2000, 47, 615−621. (9) Nellore, V.; Xi, S.; Dwyer, C. Self-Assembled Resonance Energy Transfer Keys for Secure Communication over Classical Channels. ACS Nano 2015, 9, 11840−11848. (10) Stipcević, M.; Rogina, B. M. Quantum random number generator based on photonic emission in semiconductors. Rev. Sci. Instrum. 2007, 78, 045104. (11) Tokunaga, C.; Blaauw, D.; Mudge, T. True Random Number Generator With a Metastability-Based Quality Control. IEEE J. SolidState Circuits 2008, 43, 78−85. (12) Uchida, A.; Amano, K.; Inoue, M.; Hirano, K.; Naito, S.; Someya, H.; Oowada, I.; Kurashige, T.; Shiki, M.; Yoshimori, S. Fast physical random bit generation with chaotic semiconductor lasers. Nat. Photonics 2008, 2, 728−732. (13) Chen, X. M.; Wang, L.; Li, B. X.; Wang, Y.; Li, X.; Liu, Y. P.; Yang, H. Z. Modeling Random Telegraph Noise as a Randomness Source and its Application in True Random Number Generation. IEEE Trans. Comput-Aided Des. Integr. Circuits Syst. 2016, 35, 1435−1448. (14) Brassard, G.; Lutkenhaus, N.; Mor, T.; Sanders, B. C. Limitationson Practical Quantum Cryptography. Phys. Rev. Lett. 2000, 85, 1330−1333. (15) Shannon, C. E. Communication Theory of Secrecy Systems. Bell Syst. Tech. J. 1948, 28, 656−715. (16) Fan, F. R.; Tian, Z. Q.; Wang, Z. L. Flexible Triboelectric Generator. Nano Energy 2012, 1, 328−334. (17) Lee, K. Y.; Chun, J.; Lee, J. H.; Kim, K. N.; Kang, N. R.; Kim, J. Y.; Kim, M. H.; Shin, K. S.; Gupta, M. K.; Baik, J. M.; Kim, S. W. Hydrophobic Sponge Structure-Based Triboelectric Nanogenerator. Adv. Mater. 2014, 26, 5037−42. (18) Huang, L. B.; Xu, W.; Bai, G. X.; Wong, M.-C; Yang, Z. B.; Hao, J. H. Wind energy and blue energy harvesting based on magneticassisted noncontact triboelectric nanogenerator. Nano Energy 2016, 30, 36−42. (19) Han, M. D.; Zhang, X. S.; Liu, W.; Sun, X. M.; Peng, X. H.; Zhang, H. X. Low-Frequency Wide-Band Hybrid Energy Harvester Based on Piezoelectric and Triboelectric Mechanism. Sci. China: Technol. Sci. 2013, 56, 1835−1841. (20) Zhu, G.; Zhou, Y. S.; Bai, P.; Meng, X. S.; Jing, Q. S.; Chen, J.; Wang, Z. L. A Shape-Adaptive Thin-Film-Based Approach for 50% High-Efficiency Energy Generation Through Micro-Grating Sliding Electrification. Adv. Mater. 2014, 26, 3788−3796. (21) Tang, W.; Jiang, T.; Fan, F. R.; Yu, A. F.; Zhang, C.; Cao, X.; Wang, Z. L. Liquid-Metal Electrode for High-Performance Triboelectric Nanogenerator at an Instantaneous Energy Conversion Efficiency of 70.6%. Adv. Funct. Mater. 2015, 25, 3718−3725. (22) Lin, Z. H.; Cheng, G.; Lee, S. M.; Pradel, K. C.; Wang, Z. L. Harvesting Water Drop Energy by a Sequential Contact-Electrification and Electrostatic-Induction Process. Adv. Mater. 2014, 26, 4690−4696. (23) Jeong, C. K.; Baek, K. M.; Niu, S. M.; Nam, T. W.; Hur, Y. H.; Park, D. Y.; Hwang, G.-T.; Byun, M.; Wang, Z. L.; Jung, Y. K.; Lee, K. J. Topographically-Designed Triboelectric Nanogenerator via Block Copolymer Self-Assembly. Nano Lett. 2014, 14, 7031−7038. (24) Lee, S. H.; Jeong, C. K.; Hwang, G. T.; Lee, K. J. Self-powered flexible inorganic electronic system. Nano Energy 2015, 14, 111− 12523. (25) Cui, N. Y.; Liu, J. M.; Gu, L.; Bai, S.; Chen, X. B.; Qin, Y. Wearable Triboelectric Generator for Powering the Portable Electronic Devices. ACS Appl. Mater. Interfaces 2015, 7, 18225−18230.

i=m

E=

∑ c(i)2 i=1 k=m

lb = bin[ ∑ C[k] × E*1000] k=1

to negate the “lb” and use OR operation between it and “hb” to get a new 16-bit binary number “F”; to use the XOR operation between “lb” and “hb” to get new 16-bit binary number “T”; to use the XOR operation between F’s high four bits and low four bits and use XOR operation between F’s second high four bits and low four bits to get a new 16-bit binary number “F1”; and to use the XOR operation between T’s high seven bits and F1’s low seven bits and use XOR operation between F’s high nine bits and T’s low nine bits to get a new 16-bit binary number “T1”. Characterizations and Measurements. The output voltage of the device was measured using a Lecroy 610Zi oscilloscope with four channels and load resistance of 10 MΩ. The morphology of nanostructures was characterized by scanning electronic microscope (Hitachi SU8020).

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.6b07030. Additional details and data (PDF)

AUTHOR INFORMATION Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. ORCID

Junyi Zhai: 0000-0001-8900-4638 Zhong Lin Wang: 0000-0002-5530-0380 Author Contributions ⊥

These authors contributed equally to this work.

Notes

The authors declare no competing financial interest.

ACKNOWLEDGMENTS This work was supported by NSFC 51472056, NSFC 51503108, National Key R&D Project from Minister of Science and Technology, China (2016YFA0202703, 2016YFA0202704), the “thousands talents” program for pioneer researcher and his innovation team, China, the Recruitment Program of Global Youth Experts, China. Thanks to Chao Yuan, Dr. Jin Yang, Dr. Xiong Pu, Ke Zhang, Limin Zhang, Jinzong Kou, Xiaohui Li, Longfei Wang, and Yudong Liu for technical support. REFERENCES (1) Schneier, B. Secrets & Lies: Digital Security in a Networked World. Wiley Publishing, Inc.: Indianapolis, IN, 2000; pp 163−165. (2) Suh, G. E.; Devadas, S. Physical Unclonable Functions for Device Authentication and Secret Key Generation. Proceedings of the IEEE Design Automation Conference, San Diego, CA, June 4−8, 2007; ACM: New York, 2007; pp 914 (3) Schneier, B. Applied cryptography: protocols, algorithms, and source code in C; John Wiley & Sons: Hoboken, NJ, 2007; pp 98−101. (4) Gisin, N.; Ribordy, G.; Tittel, W.; Zbinden, H. Quantum Cryptography. Rev. Mod. Phys. 2002, 74, 145−195. 11440

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Article

ACS Nano (26) Ha, M.; Park, J.; Lee, Y.; Ko, H. Triboelectric Generators and Sensors for Self-Powered Wearable Electronics. ACS Nano 2015, 9, 3421−3427. (27) Hwang, G. T.; Byun, M.; Jeong, C. K.; Lee, K. J. Flexible Piezoelectric Thin-Film Energy Harvesters and Nanosensors for Biomedical Applications. Adv. Healthcare Mater. 2015, 4, 646−658. (28) Zhong, J.; Zhang, Y.; Zhong, Q. Z.; Hu, Q. Y.; Hu, B.; Wang, Z. L.; Zhou, J. Fiber-Based Generator for Wearable Electronics and Mobile Medication. ACS Nano 2014, 8, 6273−6280. (29) Yu, A. F.; Chen, X. Y.; Wang, R.; Liu, J. Y.; Luo, J. J.; Chen, L. B.; Zhang, Y.; Wu, W.; Liu, C. H.; Yuan, H. T.; Peng, M. Z.; Hu, W. G.; Zhai, J. Y.; Wang, Z. L. Triboelectric Nanogenerator as a SelfPowered Communication Unit for Processing and Transmitting Information. ACS Nano 2016, 10, 3944−3950. (30) Jeong, C. K.; Cho, S. B.; Han, J. H.; Park, D. Y.; Yang, S.; Park, K.; Ryu, J.; Sohn, H.; Chung, Y. C.; Lee, K. J. Flexible highly-effective energy harvester a crystallographic and computational control of nanointerfacial morphotropic piezoelectric thin film. Nano Res. 2016, DOI: 10.1007/s12274-016-1304-6. (31) FIPS 140-1, Security Requirements for Cryptographic Modules; National Institute of Standards and Technology: FIPS 140-1, “Security Requirements for Cryptographic Modules, 1994. (32) Zheng, L.; Lin, Z. H.; Cheng, G.; Wu, W. Z.; Wen, X. N.; Lee, S. M.; Wang, Z. L. Silicon-Based Hybrid Cell for Harvesting Solar Energy and Raindrop Electrostatic Energy. Nano Energy 2014, 9, 291−300.

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