MXene-enhanced environmentally stable organohydrogel ionic diode toward harvesting ultralow-frequency mechanical energy and moisture energy

With the accelerating advancement of distributed sensors and portable electronic devices in the era of big data,harvesting energy from the surrounding environment to power electrical devices has become increasingly attractive.However,most mechanical energy harvesters often require high operating frequencies to function properly.Moreover,for practical applications,the survivability of devices in harsh operating environments is a vital issuewhich must be addressed.Besides,the single-stimulus responsiveness limits their further applications in complex external environments.Here,a pressure and moisture dual-responsive ionic diode consisting of two organohydrogels with opposite charges as an energy harvester is proposed.The organohydrogel ionic diode utilizes the migration of cations and anions to form the depletion zone and followed by an enhancement of the built-in potential along the depletion zone as a result of mechanical stress or humidity,converting ultralow-frequency mechanical energy or moisture energy into electrical energy.Meanwhile,this mechanism is further confirmed by the finite element analysis.With the increased rectification ratio due to the introduction of MXene,the ionic diode exhibits a relatively large output current(∼10.10μA cm^(−2))and power density(∼0.10μW cm^(−2))at a mechanical pressure of 0.01 Hz,outperforming most currently available mechanical energy harvesters.More impressively,the incorporation of ethylene glycol provides the hydrogel ionic diode with excellent temperature tolerance and long-term environmental stability.The organohydrogel ionic diode can also be applied as a moisture-driven power generator and self-powered humidity sensor.This study presents promising prospects for the efficient collection of renewable and sustainable energy and the practical application of hydrogel-based energy harvesters in extreme environments.

Deep Reinforcement Learning Enabled Bi-level Robust Parameter Optimization of Hydropower-dominated Systems for Damping Ultra-low Frequency Oscillation

This paper proposes a robust and computationally efficient control method for damping ultra-low frequency oscillations(ULFOs) in hydropower-dominated systems. Unlike the existing robust optimization based control formulation that can only deal with a limited number of operating conditions, the proposed method reformulates the control problem into a bi-level robust parameter optimization model. This allows us to consider a wide range of system operating conditions. To speed up the bi-level optimization process, the deep deterministic policy gradient(DDPG) based deep reinforcement learning algorithm is developed to train an intelligent agent. This agent can provide very fast lower-level decision variables for the upper-level model, significantly enhancing its computational efficiency. Simulation results demonstrate that the proposed method can achieve much better damping control performance than other alternatives with slightly degraded dynamic response performance of the governor under various types of operating conditions.

Numerical and Experimental Investigations on Tunable Low-frequency Locally Resonant Metamaterials

In this paper,a tunable locally resonant metamaterial is proposed for low-frequency band gaps.The local resonator composed of two pairs of folded slender beams and a proof mass is designed based on the theory of compliant mechanism.The design optimization on geometric parameters is carried out to fulfil the quasi-zero-stiffness property.The locally resonant metamaterial is formed by periodically arranged unit cells,and the transmittance of longitudinal wave is studied through three aspects:numerical predictions,finite element simulations and experimental tests.The variation trends revealed by these three methods match well with one another:the band gap moves to lower frequency and both its depth and width get smaller and smaller with the increase of pre-compression(Δ).The band gap overlays the frequency range of 73.10–92.38 Hz and 16.78–19.49 Hz atΔ=0mm andΔ=10mm,respectively,providing a wide range of tunability.Besides,the ultralow-frequency band gap can be achieved asΔapproaches 10 mm.This study may provide an avenue for achieving the tunable ultralow-frequency locally resonant band gap.