R L Molecular Research

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The authors would like to acknowledge the contributions of the following researchers J.R. DeBaun and L.S. Mullen-Rokita, for helpful discussions E.B. Cramer, for assisting with the adsorption measurements L.-S. Yu-Farina, for the water solubility and partition coefficient measurements H. Myers, for the vapor pressure measurements and R.R. Winter, for running the MACCS molecular structure analyses. 

ENSORB [ExxoN adSORBtion] A process for separating linear from branched hydrocarbons, using a zeolite molecular sieve. The adsorbed gases are desorbed using ammonia. It operates in a cyclic, not a continuous, mode. Developed by Exxon Research Engineering Company, and used by that company on a large scale at the Exxon refinery in Baytown, TX. Asher, W. J., Campbell, M. L., Epperly, W. R., and Robertson, J. LHydrocarbon Process., 1969, 48(1), 134. 

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This work was supported by operating grants to D.R.H. and L.P.K. from the Canadian Institutes for Health Research, a PDF to M.W. from the Canadian Institute of Health Research Strategic Training Grant on Membrane Proteins Linked to Disease, and the resources of the Molecular Design and Irrformation Technology Centre, University of Toronto. 

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Liu and Zhong introduced a number of QSPR models based on molecular connectivity indices [151, 152], In a first iteration, the researchers developed polymer-dependent correlations descriptors were calculated for a set of solvents and models were developed per polymer type [151], Polymer classes under consideration were polystyrene, polyethylene, poly-1-butene, poly-l-pentene, poly(4-methyl-l-pentene), polydimethylsiloxane, and polyisobutylene. As the authors fail to provide any validation for their models, it is difficult to asses their predictive power. In a subsequent iteration and general expansion of this study, mixed and therefore more general models based on the calculated connectivity indices of both solvent and polymers were developed. While it is unclear from the paper which polymer representation was used for the calculation of the connectivity indices, the best regression model (eight parameter model) yields only acceptable predictive power (R = 0.77, = 0.77, s = 34.47 for the training set, R = 0.75... 

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