A rigorous analysis of the available data presented in the literature for all the saturated aliphatic hydrocarbons from methane through n‐eicosane was conducted to establish the constants A, B, C, and D of the vapor‐pressure equation developed by Frost and Kalkwarf (21). With all the constants determined, vapor pressures can be calculated accurately from the triple to the critical point. The actual constants A, B, C, and D have been calculated from the available reported vapor‐pressure data of eighty‐seven saturated aliphatic hydrocarbons and include all the normal paraffins through eicosane and all the isomeric paraffins through the nonanes.In order to ascertain the validity of calculated‐vapor‐pressure constants, values of A, B, C, and D were produced from the molecular structure and normal boiling point for all the normal paraffins through eicosane and all the thirty‐four isomeric nonanes. The normal paraffins were selected to cover the range of the saturated aliphatic hydrocarbons; whereas the nonanes were chosen because they represent the most complex structures for which reported vapor pressures are available.With the calculated constants, vapor pressures were evaluated from the equation at several representative points and were compared with reported values to produce an overall absolute average percentage of deviation of 0.58 for the normal paraffins and 0.73 for the isomeric nonanes, or 0.68 for these fifty‐four saturated aliphatic hydrocarbons.
Al~tract-The past decade has seen significant advances in medical artificial intelligence (MAI), but its role in medicine and medical education remains fimited. The goal for the next decade must be directed towards maximizing the utility of MAI in the clinic and classroom. Fundamental to achieving this is increasing the involvement of clinicians in MAI development. MAI developers must move from "pet projects" toward generalizable tasks meeting recognized clinical needs. Clinical researchers must be made aware of knowledge engineering, so clinical data bases can be prospectively designed to contribute directly into MAI "knowledge bases". Closer involvement of MAI scientists with clinicians is also essential to further understanding of cognitive processes in medical decision-making. Technological advances in user interfaces-including voice recognition, natural language processing, enhanced graphics and videodiscs-must be rapidly introduced into MAI to increase physician acceptance. Development of expert systems in non-clinical areas must expand, particularly resource management, e.g. operating room or hospital admission scheduling. The establishment of MAI laboratories at major medical centers around the country, involving both clinicians and computer scientists, represents an ideal mechanism for bringing MAI into the mainstream of medical computing.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.