Search

Most previous fiber-shaped solar cells were based on photoelectrochemical systems involving liquid electrolytes, which had issues such as device encapsulation and stability. Here, we deposited classical semiconducting polymer-based bulk heterojunction layers onto stainless steel wires to form primary electrodes and adopted carbon nanotube thin films or densified yarns to replace conventional metal counter electrodes. The polymer-based fiber cells with nanotube film or yarn electrodes showed power conversion efficiencies in the range 1.4% to 2.3%, with stable performance upon rotation and large-angle bending and during long-time storage without further encapsulation. Our fiber solar cells consisting of a polymeric active layer sandwiched between steel and carbon electrodes have potential in the manufacturing of low-cost, liquid-free, and flexible fiber-based photovoltaics.

With the rapid development of robust principal component analysis (RPCA), it has been widely used in signal processing, pattern recognition, computer vision and other fields. The RPCA model has characteristics of complete reconstruction of the original signal from the noise pollution, high-dimensional and high-order complex signals. In order to solve the problems of slow iteration speed and low recovery accuracy in typical algorithms, an improved robust principal component analysis (RPCA) algorithm is studied. Firstly, the idea of smooth approximate zero norm is introduced to build the objective optimization function, then the inertial momentum is used to optimize each iteration of the matrix recovery process, finally, the model parameters are optimized by the grid method. Through simulation and comparative analysis, the results show that the improved algorithm has high accuracy, fast processing speed and remarkable application effect in field of logging data processing.