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      Synchronous nanogenerator with intermittent sliding friction self-excitation for water wave energy harvesting

      , , , , , , , ,
      Nano Energy
      Elsevier BV

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          Flexible triboelectric generator

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            Triboelectric nanogenerators as new energy technology and self-powered sensors - principles, problems and perspectives.

            Zhong Wang (2014)
            Triboelectrification is one of the most common effects in our daily life, but it is usually taken as a negative effect with very limited positive applications. Here, we invented a triboelectric nanogenerator (TENG) based on organic materials that is used to convert mechanical energy into electricity. The TENG is based on the conjunction of triboelectrification and electrostatic induction, and it utilizes the most common materials available in our daily life, such as papers, fabrics, PTFE, PDMS, Al, PVC etc. In this short review, we first introduce the four most fundamental modes of TENG, based on which a range of applications have been demonstrated. The area power density reaches 1200 W m(-2), volume density reaches 490 kW m(-3), and an energy conversion efficiency of ∼50-85% has been demonstrated. The TENG can be applied to harvest all kinds of mechanical energy that is available in our daily life, such as human motion, walking, vibration, mechanical triggering, rotation energy, wind, a moving automobile, flowing water, rain drops, tide and ocean waves. Therefore, it is a new paradigm for energy harvesting. Furthermore, TENG can be a sensor that directly converts a mechanical triggering into a self-generated electric signal for detection of motion, vibration, mechanical stimuli, physical touching, and biological movement. After a summary of TENG for micro-scale energy harvesting, mega-scale energy harvesting, and self-powered systems, we will present a set of questions that need to be discussed and explored for applications of the TENG. Lastly, since the energy conversion efficiencies for each mode can be different although the materials are the same, depending on the triggering conditions and design geometry. But one common factor that determines the performance of all the TENGs is the charge density on the two surfaces, the saturation value of which may independent of the triggering configurations of the TENG. Therefore, the triboelectric charge density or the relative charge density in reference to a standard material (such as polytetrafluoroethylene (PTFE)) can be taken as a measuring matrix for characterizing the performance of the material for the TENG.
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              Toward large-scale energy harvesting by a nanoparticle-enhanced triboelectric nanogenerator.

              This article describes a simple, cost-effective, and scalable approach to fabricate a triboelectric nanogenerator (NG) with ultrahigh electric output. Triggered by commonly available ambient mechanical energy such as human footfalls, a NG with size smaller than a human palm can generate maximum short-circuit current of 2 mA, delivering instantaneous power output of 1.2 W to external load. The power output corresponds to an area power density of 313 W/m(2) and a volume power density of 54,268 W/m(3) at an open-circuit voltage of ~1200 V. An energy conversion efficiency of 14.9% has been achieved. The power was capable of instantaneously lighting up as many as 600 multicolor commercial LED bulbs. The record high power output for the NG is attributed to optimized structure, proper materials selection and nanoscale surface modification. This work demonstrated the practicability of using NG to harvest large-scale mechanical energy, such as footsteps, rolling wheels, wind power, and ocean waves.
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                Author and article information

                Journal
                Nano Energy
                Nano Energy
                Elsevier BV
                22112855
                May 2022
                May 2022
                : 95
                : 106994
                Article
                10.1016/j.nanoen.2022.106994
                f1f41003-501d-4a49-a12c-64f55dee0552
                © 2022

                https://www.elsevier.com/tdm/userlicense/1.0/

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