The emergence of multifunctional wearable electronics over the past decades has triggered the exploration of flexible energy storage devices. As an important component of flexible batteries, novel electrodes with good flexibility, mechanical stability and high energy density are required to adapt to mechanical deformation while powering devices. Electrodes with sophisticated designed structures are key to achieving novel batteries and supercapacitors with extended lifetimes under long-term deformation exposures. Many different novel structures including serpentine, auxetic and biomimetic are explored to construct electrodes thanks to their excellent mechanical deformability in three dimensions. This paper considers the various design strategies established for fabricating flexible electrodes using novel structural modifications. The current state-of-the-art developments of novel structures made of two-dimensional (2D) planar and three-dimensional (3D) cellular, interconnected architectures for flexible energy storage with different functionalities, are discussed. The key tunable geometrical parameters of structures for achieving high performance are critically assessed, and the challenges and limitations of electrodes facing their practical application are revealed, to offer new insights into future prospects of this field.
As an emerging carbon-based material, carbon quantum dots (CQDs) have shown unstoppable prospects in the field of bionic electronics with their outstanding optoelectronic properties and unique biocompatible characteristics. In this study, a novel CQD-based memristor is proposed for neuromorphic computing. Unlike the models that rely on the formation and rupturing of conductive filaments, it is speculated that the resistance switching mechanism of CQD-based memristors is due to the conductive path caused by the hybridization state transition of the sp2 carbon domain and sp3 carbon domain induced by the reversible electric field. This avoids the drawback of uncontrollable nucleation sites leading to the random formation of conductive filaments in resistive switching. Importantly, it illustrates that the coefficient of variation (CV) of the threshold voltage can be as low as -1.551% and 0.083%, which confirms the remarkable uniform switching characteristics. Interestingly, the Pavlov's dog reflection as an important biological behavior can be demonstrated by the samples. Finally, the accuracy recognition rate of MNIST handwriting can reach up to 96.7%, which is very close to the ideal number (97.8%). A carbon-based memristor based on a new mechanism presented provides new possibilities for the improvement of brain-like computing.
Photocatalytic technology has been well studied as a means to achieve sustainable energy generation through water splitting or chemical synthesis. Recently, a low C/N atomic ratio carbon nitride allotrope, C3N5, has been found to be highly prospective due to its excellent electronic properties and ample N-active sites compared to g-C3N4. Tangentially, crystalline g-C3N4 has also been a prospective candidate due to its improved electron transport and extended π-conjugated system. For the first time, our group successfully employed a one-step molten salt calcination method to prepare novel N-rich crystalline C3N5 and elucidate the effect of calcination temperature on the heptazine/triazine phase. Calcination temperatures of 500 °C (CC3N5-500) and 550 °C (CC3N5-550) lead to crystalline carbon nitride with both heptazine and triazine phases, forming an intimate isotype heterojunction for robust interfacial charge separation. An excellent photocatalytic hydrogen evolution rate (359.97 μmol h-1; apparent quantum efficiency (AQE): 12.86% at 420 nm) was achieved using CC3N5-500, which was 15-fold higher than that of pristine C3N5. Furthermore, CC3N5-500 exhibited improved activity for simultaneous benzyl alcohol oxidation and hydrogen production, as well as H2O2 production (AQE: 9.49% at 420 nm), signifying its multitudinous photoredox capabilities. Moreover, the recyclability tests of the optimal CC3N5-500 on a 3D-printed substrate also showed a 92% performance retention after 4 cycles (16 h). This highlights that crystalline C3N5 significantly augmented the reaction performance for diverse multifunctional solar-driven applications. As such, these results serve as a guide toward the structural tuning of 2D metal-free carbon nanomaterials with tunable crystallinity toward achieving boosted photocatalysis.
Memristors have revolutionized the path forward for brain-inspired computing. However, the instability of the nucleation process of conductive filaments based on active metal electrodes leads to the discrete distribution of switching parameters, which hinders the realization of high-performance and low-power devices for neuromorphic computing. In response, a carbon conductive filament-induced robust memristor is demonstrated with variation coefficients as low as 3.9%/-1.18%, a threshold power as low as 10-9 W, and 3 × 106 s retention and 107 cycle endurance behaviors can be maintained. The recognition accuracy for Modified National Institute of Standards and Technology (MNIST) handwriting is as high as 96.87%, attributed to the high linearity of the iterative updating of synaptic weights. The demodulation and storage functions of the American Standard Code for Information Interchange (ASCII) are demonstrated by programmable pulse modulation. Notably, the transmission electron microscopy (TEM) images allow the observation of carbon conductive filament paths formed in the low resistance state. First-principles calculations analyze the energetics of defects involved in the diffusion of carbon atoms into MoTe2 films. This work presents a novel guideline for studying memristor-based neuromorphic computing.