Enhance cycling performance of LiMn2O4 cathode by Sr2+ and Cr3+ doping

Spinel LiSr_0·1Cr_0·1Mn_1·8O₄ was synthesised by high temperature solid state method in order to enhance the electrochemical performance. The LiSr_0·1Cr_0·1Mn_1·8O₄ (LSCMO) materials were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM) and electrochemical tests. The XRD and SEM studies confirm that LSCMO had spinel crystal structure with a space group of Fd3m, and the particle of LSCMO shows irregular shape. The cyclic voltammetry data illustrated that the heavy current charge–discharge performance of LMO was improved by Sr²⁺ and Cr³⁺ doping. The galvanostatic charge–discharge of LSCMO cathode materials was measured at 1, 5, 10 and 20 C. The results indicated that LSCMO improved the capacity retention.     

E-voting scheme using secret sharing and K-anonymity

E-voting maybe replaces the traditional voting scheme in the future, however, the security threat must be paid enough attention. In this paper, a novel e-voting scheme is proposed using secret sharing and k-anonymity, which not only satisfies the basic security goals such as the non-cheating, the universal verifiability, the confidentiality, and the anonymity, but also achieves the addition properties including coercion-resistance and unconditional security since the security of the proposed scheme does not rely on any computational hard problem.

     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Ni-Foam Structured Ni-Phyllosilicate Ensemble as an Efficient Monolithic Catalyst for CO2 Methanation

This work proposed a new path to synthesize Ni-phyllosilicate through the reaction of nickel hydroxide and silica sol on the surface of Ni-foam to form the monolithic Ni-phyllosilicate/Ni-foam catalyst. Ni-phyllosilicate could reprint the morphology of nickel hydroxid and firmly anchor on the framework of Ni-foam, which obtained fine Ni particles of 2.8 nm after reduction in H₂ at 650 °C, resulting in high catalytic activity for CO₂ methanation. In addition, the Ni-phyllosilicate/Ni-foam catalyst showed high long-term stability in a 100 h-lifetime test owing to the combined effects of surface confinement of Ni-phyllosilicate, firm anchoring between Ni-phyllosilicate and Ni-foam, as well as the high heat transfer property of Ni-foam.

Graphical Abstract

     

Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...