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Zhang, Zhengcheng,Lu, Jun,Assary, Rajeev S.,Du, Peng,Wang, Hsien-Hau,Sun, Yang-Kook,Qin, Yan,Lau, Kah Chun,Greeley, Jeffrey,Redfern, Paul C.,Iddir, Hakim,Curtiss, Larry A.,Amine, Khalil American Chemical Society 2011 JOURNAL OF PHYSICAL CHEMISTRY C - Vol.115 No.51
<P>The successful development of Li-air batteries would significantly increase the possibility of extending the range of electric vehicles. There is much evidence that typical organic carbonate based electrolytes used in lithium ion batteries form lithium carbonates from reaction with oxygen reduction products during discharge in lithium-air cells so more stable electrolytes need to be found. This combined experimental and computational study of an electrolyte based on a tri(ethylene glycol)-substituted trimethylsilane (<ext-link xlink:type='simple'>1NM3</ext-link>) provides evidence that the ethers are more stable toward oxygen reduction discharge species. X-ray photoelectron spectroscopy (XPS) and FTIR experiments show that only lithium oxides and no carbonates are formed when <ext-link xlink:type='simple'>1NM3</ext-link> electrolyte is used. In contrast XPS shows that propylene carbonate (PC) in the same cell configuration decomposes to form lithium carbonates during discharge. Density functional calculations of probable decomposition reaction pathways involving solvated oxygen reduction species confirm that oligoether substituted silanes, as well as other ethers, are more stable to the oxygen reduction products than propylene carbonate. These results indicate that the choice of electrolyte plays a key role in the performance of Li-air batteries.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/jpccck/2011/jpccck.2011.115.issue-51/jp2087412/production/images/medium/jp-2011-087412_0009.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/jp2087412'>ACS Electronic Supporting Info</A></P>
A community computational challenge to predict the activity of pairs of compounds
Bansal, Mukesh,Yang, Jichen,Karan, Charles,Menden, Michael P,Costello, James C,Tang, Hao,Xiao, Guanghua,Li, Yajuan,Allen, Jeffrey,Zhong, Rui,Chen, Beibei,Kim, Minsoo,Wang, Tao,Heiser, Laura M,Realubit Nature Publishing Group, a division of Macmillan P 2014 Nature biotechnology Vol.32 No.12
Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.