Performance degradation caused by the oxidation of carbon anodes during capacitive deionization (CDI) remains a major problem that may greatly restrict the practical application of CDI. To improve the cyclic stability of CDI, carbon-based anode materials were replaced by pseudocapacitive MnO 2 in this work. The cation-selective MnO 2 anode was assembled with an anion-selective quaternized poly(4-vinylpyridine)coated activated carbon cathode into a hybrid CDI cell. The cell exhibited inverted CDI performance with a wide operating voltage window of 1.4 V and a salt adsorption capacity (SAC) of 14.9 mg/g in 500 mg/L NaCl. The SAC retention ratio of the cell can be as high as 95.4% after 350 adsorption−desorption cycles at 1.0/0 V, while that of the CDI cell consisting of activated carbon electrodes was only 15.7% after 285 cycles. The enhanced cyclic stability of the hybrid CDI cell is attributed to the employment of the MnO 2 anode, which avoided the use and oxidation of carbon anodes.

A random walk is known as a random process which describes a path including a succession of random steps in the mathematical space. It has increasingly been popular in various disciplines such as mathematics and computer science. Furthermore, in quantum mechanics, quantum walks can be regarded as quantum analogues of classical random walks. Classical random walks and quantum walks can be used to calculate the proximity between nodes and extract the topology in the network. Various random walk related models can be applied in different fields, which is of great significance to downstream tasks such as link prediction, recommendation, computer vision, semi-supervised learning, and network embedding. In this paper, we aim to provide a comprehensive review of classical random walks and quantum walks. We first review the knowledge of classical random walks and quantum walks, including basic concepts and some typical algorithms. We also compare the algorithms based on quantum walks and classical random walks from the perspective of time complexity. Then we introduce their applications in the field of computer science. Finally we discuss the open issues from the perspectives of efficiency, main-memory volume, and computing time of existing algorithms. This study aims to contribute to this growing area of research by exploring random walks and quantum walks together.

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