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In terms of the theoretical calculation of surface energy for the rare metal Yttrium (Y) with hexagonal close-packed structure, earlier reports failed to predict the precise results. Here, a logical method was employed to evaluate the surface energy of Y (0001) surface, and the obtained value (1. 141 J/M²) is well consistent with the experimental outcome (1. 125 J/M²). Subsequently, the behaviors of Y (0001) surface adsorbing NO at different sites, i. e. hollow (H1, H2, and H3), bridge (B), and top (T) sites were investigated theoretically. It was found that hollow site H1 has a great ability to adsorb NO molecule, of which the adsorption energy is over 5 eV. Meanwhile, a remarkable elongation of N-O distance (about 24%) at H1 site is observed, coupled with the NO molecule being at the surface parallelly. A variation range of N-O elongation for all adsorption sites is from 0. 2Å (T) to 0. 42Å (H1). This theoretical extension of NO at H1 site is obviously more than those of NO being adsorbed on other transition metal surface. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To solve the disadvantages of the most PV models parameter identification algorithms at present, which have low accuracy and poor reliability, this paper proposed an improved symbiotic organisms search ( SOS) algorithm for parameter identification of PV module models. First, to enhance the performance of original SOS, this paper proposed a novel improved SOS algorithm, named as ImSOS. In ImSOS, it employed a quasi-reflection-based learning( QRBL) scheme in the population initialization step of original SOS. Moreover, it used the strategy of the modifications of benefit factors in the mutualism phase of SOS. It adopted a strategy of narrowing the search range of randomly generated coefficients in the commensalism phase of SOS. And then, it detailed the procedures and flowchart of employing the ImSOS for solving the PV module models parameter identification problem based on experimental current versus voltage(I-V) data of a real PV module. Finally,the ImSOS was demonstrated on the parameter identification of different PV module models of the Sharp ND-R250A5 PV module. Experimental results and comparisons with original SOS and the other seven novel intelligent optimization algorithms implies the effectiveness and superiority of the ImSOS. Therefore, the ImSOS becomes a new effective method to accurately and reliably identify PV module models parameters. [ABSTRACT FROM AUTHOR]

With the development of information and communication technology, the cyber-physical system (CPS) has become an interdependent and deeply integrated large-scale binary composite network. Studying its information network framework，architecture, properties of large data and fragmented knowledge is of great significance to the future smart grid theory research and practical engineering applications. In view of the characteristics of the Internet of Things, big data knowledge and so on， which bring human society into the era of information and knowledge explosion, we mainly discusses the opportunities and challenges which the CPS will face in the future. The development trend of new energy interconnection, the increase of the ratio of electronic information devices，and multi-energy and multi-network convergence are presented. The application prospects of large data and artificial intelligence knowledge are proposed from the aspects of generation, transmission，transformation, deployment and utilization, which are helpful for future information-based scientific decision-making and deployment of smart grid. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Southern Agriculture is the property of Journal of Southern Agriculture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)