Breaking the Responsivity-Bandwidth Trade-Off Limit in GaN Photoelectrodes for High-Response and Fast-Speed Optical Communication Application

Underwater optical communication (UOC) has attracted considerable interest in the continuous expansion of human activities in marine/ocean environments. The water-durable and self-powered photoelectrodes that act as a battery-free light receiver in UOC are particularly crucial, as they may directly face complex underwater conditions. Emerging photoelectrochemical (PEC)-type photodetectors are appealing owing to their intrinsic aqueous operation characteristics with versatile tunability of photoresponses. Herein, a self-powered PEC photodetector employing n-type gallium nitride (GaN) nanowires as a photoelectrode, which is decorated with an iridium oxide (IrO_x) layer to optimize charge transfer dynamics at the GaN/electrolyte interface, is reported. Strikingly, the constructed n-GaN/IrO_x photoelectrode breaks the responsivity-bandwidth trade-off limit by simultaneously improving the response speed and responsivity, delivering an ultrafast response speed with response/recovery times of only 2 µs/4 µs while achieving a high responsivity of 110.1 mA W⁻¹. Importantly, the device exhibits a large bandwidth with 3 dB cutoff frequency exceeding 100 kHz in UOC tests, which is one of the highest values among self-powered photodetectors employed in optical communication system.     

Developing a stochastic model to predict the strength and crack path of random composites

We characterize fracture and effective stress–strain graphs in 2D random composites subjected to a uniaxial in-plane uniform strain. The fibers are arranged randomly in the matrix. Both fibers and matrix are isotropic and elastic–brittle. We conduct this analysis numerically using a very fine two-dimensional triangular spring network and simulate the crack initiation and propagation by sequentially removing bonds which exceed a local fracture criterion. In particular, we focus on effect of geometric randomness on crack path of random composites. Based on that two stochastic micro-mechanic models are presented that can predict with confidence the failure probability of random matrix–inclusion composites.     

The joint effect of shape and size of reinforcement on progressive damage of random composites

The properties of composites made by placing inclusions in a matrix are often controlled by the shape and size of the particles. In order to study the joint effect of shape and size of inclusions, we characterize the random shape of particles in composite mathematically by applying Fourier series, then generating random mesostructure of composite for cases of inclusions with (1) same size and different shape, (2) different size and same shape, or (3) random size and shape. Crack paths and effective stress–strain curves of these cases are predicted using spring network method which is given in detail. The study shows we need more elaborate statistical evaluation due to the random nature of composites. This paper outlines an approach to study effect of inclusion geometry on the elastic properties and crack of random composites.