The primary objectives of this work were to formulate, blend, and characterize a set of four ultralow-sulfur diesel surrogate fuels in quantities sufficient to enable their study in single-cylinder-engine and combustion-vessel experiments. The surrogate fuels feature increasing levels of compositional accuracy (i.e., increasing exactness in matching hydrocarbon structural characteristics) relative to the single target diesel fuel upon which the surrogate fuels are based. This approach was taken to assist in determining the minimum level of surrogate-fuel compositional accuracy that is required to adequately emulate the performance characteristics of the target fuel under different combustion modes. For each of the four surrogate fuels, an approximately 30 L batch was blended, and a number of the physical and chemical properties were measured. This work documents the surrogate-fuel creation process and the results of the property measurements.

Using the Kohonen neural network, the electrostatic potentials on the molecular surfaces of 14 styrylquinoline derivatives were drawn as comparative two-dimensional maps and compared with their known human immunodeficiency virus (HIV)-1 replication blocking potency in cells. A feature of the potential map was discovered to be related with the HIV-1 blocking activity and was used to unmask the activity of further five analogues, previously described but whose cytotoxicity precluded an estimation of their activity, and to predict the activity of 10 new compounds while the experimental data were unknown. The measurements performed later turned out to agree with the predictions.