This research suggests two new group contribution methods to facilitate phase behavior calculation when reliable experimental data are lacking. The first method pertains to the implementation of an updated version of the Elliott and Natarajan method to the Statistical Associating Fluid Theory (SAFT) and Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) equations of state. Shape factor parameters have been correlated for 878 compounds including different variety of families and the parameters from Elliott and Natarajan have been updated to improve accuracy for alcohols. Thereafter, thermodynamic properties such as boiling temperatures and vapor pressures have been predicted. We obtain 36%, 65%, and 32% AAD% in pressures for the ESD, SAFT, and PC-SAFT equations of state. Additionally, we have compared our GC-PC-SAFT to the one by Tihic et al., applying their suggested First-Order and Second-Order groups for 650 non-associating compounds. We observed higher accuracy for our method relative to the Tihic et al. The resulting P AAD% were 53% for Tihic FOG and 42% for Tihic SOG. The second method suggests a new group contribution model for Tb at 760mmHg and Tb at 10 mmHg. These correlations recognize a finite limit in boiling temperature as infinite molecular weight is approached. The availability of two vapor pressures enables straightforward application of the Clausius-Clapeyron equation to estimate boiling temperatures at other points. In the presented approach, there are 3 parameters and 72 functional groups for each temperature which are regressed through a database consisting of 336 hydrocarbons and 642 non-hydrocarbons. The average absolute percent deviations (AAD%) between the correlated and experimental temperatures are calculated in comparison with Joback-Reid and Gani approaches. We obtain 3.5, 4.7, and 4.1 AAD% in temperature for the present work, Joback, and Gani methods, respectively. Additionally, the accuracy of the present work is evaluated by calculating the vapor pressures from the DIPPR correlation at the predicted temperatures of each model. We obtained 33.2, 104.3 and 48.1 AAD% in pressure for the present work, Joback, and Gani methods. Finally, the accuracy of the presented correlations are tested against Asher and Pankow model, UNIFAC-PL°, for 66 volatile compounds in the temperature range of 290-320 K. For the vapor pressure at the 10mmHg boiling temperature, we obtain 36.9 AAD% for the present work and 94.5 AAD% for the Asher method. Overall, these group contribution methods establish a standard for comparison of more fundamental methods like molecular simulations with transferable potentials. Transferable potentials generally provide accuracy of 10-30AAD% in pressure, but have only been developed for relatively small databases over narrow temperature ranges.

J.-P. CALISTE, A. TRUYOL AND J. WESTBROOK The Series, "Data and Knowledge in a Changing World", exemplifies CODATA's primary purpose of collecting, from widely different fields, a wealth of information on efficient exploitation of data for progress in science and technology and making that information available to scientists and engineers. A separate and complementary CODATA Reference Series will present Directories of compiled and evaluated data and Glossaries of data-related terms. The present book "Thermodynamic Modeling and Materials Data Engineering" discusses thermodynamic, structural, systemic and heuristic approaches to the modeling of complex materials behavior in condensed phases, both fluids and solids, in order to evaluate their potential applications. Itwas inspired by the Symposium on "Materials and Structural Properties" held during the 14th International CODATA Conference in Chambery, France. The quality of the contributions to this Symposium motivated us to present" a coherent book of interest to the field. Updated contributions inspired by Symposium discussions and selections from other CODATA workshops concerning material properties data and Computer Aided Design combine to highlight the complexity of material data issues on experimental, theoretical and simulation levels Articles were selected for their pertinence in three areas. Complex data leading to interesting developments and tools such as: • new developments in state equations and their applications, • prediction and validation of physical and energy data by group correlations for pure compounds, • modeling and prediction of mixture properties.

Determining the correct conformation of a molecule in the COSMO solvation theories is important, especially for flexible molecules. A straightforward way to select the structure of a solute molecule is by choosing the geometry with lowest energy, though this can be difficult if there are many conformations with different structures but similar energies. Another important issue is the essential approximation in COSMO theory that the structure of the solute is unchanged in going from the gas phase to the perfect conductor phase, and then to the real solvent. Here we have tested this assumption using COSMO-SAC for the ensembles of liquid structures from Monte Carlo simulation to see how changes in the phase (and therefore the local environment) in going from a gas to a liquid result in differences in molecular conformations, and how these affect thermodynamic property predictions.

The combustion properties of organic materials are used to assess their safety specifications. This knowledge is necessary to avoid potentially disastrous fires. The experimental determination of the combustion properties of a new organic compound is laborious and sometimes even impossible. This book describes methods for the determination and prediction of the combustion properties of organic compounds, along with some examples and exercises. This 2nd Edition includes an updated and improved presentation of the application of different new models for reliable prediction of diverse aspects of flammability of organic compounds.

For more than 100 years the Beilstein Handbook has been publishing checked and evaluated data on organic compounds. It has become the major reference book for the chemical and physical properties of organic com pounds. The prediction of these physical properties was the subject of the Beilstein workshop. The ability to predict physical properties is for several reasons of great interest to the Beilstein Institute. It is of primary importance to be able to check the abstracted data for accuracy and to eliminate simple mistakes like typing errors. Presently all the work whether manuscript writing or evaluation of data is carried out manually. This is very time consuming, with the entry of Beilstein into electronic data gathering and publication, the opportunity for computerized consistency checking has become available. Contrary to belief, when one examines the Beilstein Handbook or Chemical Abstracts there is a dearth of chemical information. There are a great many compounds but few are well defined resulting in large gaps in the information available to the chemist. These information gaps could be filled by using algorithmic methods to estimate the properties of interest. An important question to answer is "What is the chemist's reaction to estimated data?" Will he accept it for use, within limits defined by the method, or will it be unacceptable and therefore detrimental for the data base. However if one could partly fill gaps in the data base the increase in the power of the search techniques would be marked.

The selection of the most adequate thermodynamic model in a process simulation is an issue that most process engineer has to face sooner or later. This book, conceived as a practical guide, aims at providing adequate answers by analysing the questions to be looked at. The analysis (first chapter) yields three keys that are further discussed in three different chapters. (1) A good understanding of the properties required in the process, and their method of calculation is the first key. The second chapter provides to that end in a synthetic manner the most important equations that are derived from the fundamental principes of thermodynamics. (2) An adequate description of the mixture, which is a combination of models and parameters, is the second key. The third chapter makes the link between components and models, both from a numerical (parameterisation) and physical (molecular interactions) point of view. Finally, (3) a correct view of the phase behaviour and trends in regard of the process conditions is the third key. The fourth chapter illustrates the phase behaviour and makes model recommendations for the most significant industrial systems. A decision tree is provided at the end of this chapter. In the last chapter, the key questions are reviewed for a number of typical processes. This book is intended for process engineers, who are not specialists of thermodynamics but are confronted with this kind of problems and need a reference book, as well as process engineering students who will find an original approach to thermodynamics, complementary of traditional lectures