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Featured Application: A paper-based triboelectric nanogenerator using carbon nanotube composite papers, as developed in this study, has the potential to be used as an energy harvester in fields such as the Internet of Things (IoT). A unique triboelectric nanogenerator (TENG) using carbon nanotube (CNT) composite papers is proposed in this work. CNT composite papers can be fabricated easily using a method based on the production of Japanese washi paper. To obtain and evaluate the proposed TENGs, several types of CNT composite papers and aluminum plates were prepared. As the CNT composite paper contained many paper fibers, it was expected to be negatively charged, and the aluminum plate was expected to be positively charged across the triboelectric series. Through various experiments, it was confirmed that CNT composite papers could be used as TENGs. In addition, it was found that when a CNT composite paper was used, it contributed to triboelectricity generation, and the contained CNTs efficiently transferred the generated charge to the electrodes. Furthermore, output voltages approaching a maximum RMS value of 300 mV could be obtained. The results of this study will aid in the practical application of paper-based TENGs in the near future. [ABSTRACT FROM AUTHOR]

We propose a new type of soft actuator based on carbon nanotube (CNT) composite paper (CNTCP), i.e., a paper actuator. In our previous study, we demonstrated that actuator operation was possible when using CNTCPs as electrodes with ordinary paper containing ionic liquid between the electrodes; however, their bending motion was not sufficient. Therefore, we here attempt to modify the paper actuator. For this, we tried to soften CNTCPs by first reducing the ratio of contained CNTs. In addition, as a new strategy, we took advantage of the fact that the proposed actuator was made of paper and introduced the Kirigami (introducing periodical slits to papers) technique into the structure of our paper actuator. As a result, the performance of the actuator was improved, and its bending motion became visibly larger. The response of the improved actuator to the input voltage was investigated in detail, and the detailed operating conditions could be clarified. Moreover, it was found that not only a bending motion but also a twisting motion could be realized in specific slit patterns. It is thought that the fact that the variation in movement can be increased simply by adding incisions is unique to the proposed paper actuator. [ABSTRACT FROM AUTHOR]

We propose a new type of CNT hydrogel that has unique conductive and reversible characteristics. We found in previous studies that CNT dispersions became gelatinous without any gelators when a specific CNT was combined with a specific dispersant. This hydrogel has conductive properties derived mainly from the CNTs it contains; and even after gelation, it can be returned to a liquid state by ultrasonic irradiation. Furthermore, the liquid is gelable again. In this study, we prepared several types of CNTs and several types of dispersants, experimentally verified the possibility of gelation by combining them, and geometrically investigated the gelation mechanism to determine how this unique hydrogel is formed. As a result, we found that the experimental results and the theory examined in this study were consistent with the combination of materials that actually become hydrogels. We expect that this study will allow us to anticipate whether or not an unknown combination of CNTs and dispersants will also become gelatinous. [ABSTRACT FROM AUTHOR]

We propose a new single-electron circuit (SEC) that mimics the behaviours of slime molds. The SEC has unique properties and many advantages including extremely low power consumption. However, the most appropriate information processing way on the SEC has not been established yet. As one approach to find the suitable way, we focus on a natural phenomenon, specifically, the behaviours of slime molds. These molds can feed efficiently and their behaviours can be regarded as performing information processing. Their information-processing-like behaviours can be divided into three functions. Therefore, if we can express these functions on the circuit, it can mimic the slime mold behaviour, i.e. it can operate as a slime-mold-inspired information-processing circuit. In this study, we designed a slime-mold-inspired SEC that utilised three functions based on three types of behaviours, and attempted to imitate these functions by using a multi-layered structure. Our circuit has four layers; three for mimicking the divided functions and the last for output. We evaluated its operation by Monte Carlo simulation and confirmed its operation was correct. This paper indicates design of a new single-electron circuit (SEC). For the SEC to process information efficiently, we focus on the behaviors of slime molds. It is known that these molds can feed efficiently and their behaviors can be regarded as performing information processing. In this study, we designed a slime-mold-inspired SEC having a multi-layered structure. We evaluated its operation by Monte Carlo simulation and confirmed its operation was correct. Figure shows a sample operation of our circuit. (a) is the input pattern and (b) is the output pattern, respectively. The optimal path was revealed. [ABSTRACT FROM AUTHOR]

Recently, neural networks (NN) have attracted much attention because they have many advantages such as parallel-processing and noise-harnessing functions. An NN is composed of many neurons, which operate in parallel and each one operates stochastically. Although each neuron is sensitive to noise and behaves randomly, a network based on the neurons can operate with high reliability. Moreover, it is known that the network exhibits various complicated functions. In this study, we attempt to mimic such useful functions of the NN by nanoelectronic circuits – i.e. single-electron (SE) circuits. The SE circuit also operates stochastically, like a biological neuron, because of the probabilistic electron tunneling phenomenon. Therefore, it can be used for implementing the stochastic neuron operation. In this work, we propose a method for hardware NN implementation on the SE circuit and confirm that it can perform the associative memory function by computer simulation. First, we simulate the circuit operation without noise. This simulation demonstrates that our circuit can store some patterns and recall them from a given noisy or related pattern. However, it fails to recall some input patterns. In the next step, we simulate thermal noise in the circuit. As a result, we can improve the failure rate in recall and increase circuit performance. [ABSTRACT FROM AUTHOR]