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To date, numbers of polymeric hole-transporting materials (HTMs) have been developed to improve interfacial charge transport to achieve high-performance inverted perovskite solar cells (PSCs). However, molecular design for passivating the underlying surface defects between perovskite and HTMs is a neglected issue, which is a major bottleneck to further enhance the performance of the inverted devices. Herein, we design and synthesize a new polymeric HTM PsTA

Designing dopant-free hole-transport materials (HTMs) is a facile and effective strategy to realize high-performance organic-inorganic hybrid perovskite (OIHP) photodetectors. Herein, a novel phenothiazine polymer, poly[4-(10H-phenothiazin-10-yl)

For achieving high-performance p-i-n perovskite solar cells (PSCs), hole transporting materials (HTMs) are critical to device functionality and represent a major bottleneck to further enhancing device stability and efficiency in the inverted devices. Three dopant-free polymeric HTMs are developed based on different linkage sites of triphenylamine and phenylenevinylene repeating units in their main backbone structures. The backbone curvatures of the polymeric HTMs affect the morphology and hole mobility of the polymers and further change the crystallinity of perovskite films. By using PTA-mPV with moderate molecular curvature, p-i-n PSCs with high efficiency of 19.5% and long-term stability can be achieved. The better performance is attributed to the more effective hole extraction ability, higher charge-carrier mobility, and lower interfacial charge recombination. Furthermore, these three polymeric HTMs are synthesized without any noble metal catalyst, and show great advantages in future application owing to the low-cost.

Distortion representation is the key to the rectification of distorted document images. The text-lines are considered to be one of the most significant features of the images, which are extensively used by a majority of rectification algorithms. However, it is quite a challenge to accurately extract the text-lines of document images with distortions and other disruptive factors, such as non-textural objects. In this approach, we present a general document rectification method based on local distortion representation that is depicted by text-features instead of the text-lines. Specially, firstly, according to the similarity of local distortion, we divide the document image into local blocks. Secondly, a text-feature is exploited to depict the warping distortion of each block by considering the skew angle. Then, the rectification problem is formulated utilizing a reverse strategy according to the text-features. Finally, a perspective distortion is restored by making use of random sample consensus. The proposed method is appropriate for document images of multi-column layouts, multi-type fonts and non-textural objects. Various experiments have demonstrated the flexibility and high performance of the approach.

Geometry image is an important representation for geometry models. High compressibility will be beneficial for preserving more graphics information when geometry images are compressed. In this paper, we propose a mesh parameterization method aiming to increasing the compressibility of geometry images that generated from open meshes. Firstly, we design a compressibility aware energy of the mesh by studying the relationship between the one-ring neighbors of the mesh vertex and the pixel neighbors of the image point. Secondly, we solve the parameterization problem by minimizing the energy defined as a weighted sum of a compressibility aware term and a conformal term. As a result, a geometry image with high image compressibility can be constructed by uniformly resampling the parameterized mesh in its parameter domain. Experimental results illustrate that the proposed method always achieves better local linear correlation and lower reconstruction error for different sampling resolutions of geometry images.

Geometry images are important representations of 3D geometry models. Smooth geometry images contributes to low approximation error and high image compressibility. We present an adapted parameterization method to generate a smooth geometry image. It is quite challenging to directly modify the parameter domain to smooth geometry images. Our novel idea is that we use an indirect way to construct a resulting parameter domain according to the desired geometry image. We first move image pixels according to the current parameter domain to decrease the local linear error. Then we formulate a relationship between the moved image pixels and the current parameter domain. Finally, we use the relationship to update the parameter domain by restituting the image pixels to their original positions. The process will continue until the local linear error is less than a given threshold or the number of iterations is larger than a given threshold. Experimental results illustrate that geometry images generated by our method have low linear errors and low approximation errors under different sampling resolutions.