Following the work of Austgen et al., the electrolyte nonrandom-two-liquid (NRTL) model was applied in a thermodynamically consistent manner to represent the vapor−liquid equilibrium (VLE) of the aqueous monoethanolamine (MEA)−CO2 system with rigorous chemical equilibrium consideration. Special attention was given to the accurate VLE description of the system at both absorbing and stripping conditions relevant to most aqueous MEA absorption/stripping processes for CO2 removal. The influence from chemical equilibrium constants, Henry's constant, experimental data, and data regression on the representation of the VLE of the system was discussed in detail. The equilibrium constant of the carbamate reversion reaction as well as important interaction parameters of the electrolyte NRTL model were carefully fitted to experimental data. A good agreement between the calculated values and the experimental data was achieved. Moreover, the model with newly fitted parameters was successfully applied to simulate three industrial cases for CO2 removal using a rate-based approach. The results from this work were compared with those using the model by Austgen et al.

Thermodynamic property computations using equations of state first require computation of the density root. Since higher level calculations such as single-stage flash, distillation and data regression are usually performed iteratively, properties are often demanded at conditions where the appropriate density root does not exist. A strategy of returning suitable pseudoproperties under such conditions is proposed. It has been successfully used in ASPEN (Advanced System for Process Engineering), a general process simulator developed at the Massachusetts Institute of Technology.

No abstract

Thermodynamic data are a key resource in the search for new relationships between properties of chemical systems that constitutes the basis of the scientific discovery process. In addition, thermodynamic information is critical for development and improvement of all chemical process technologies. Historically, peer-reviewed journals are the major source of this information obtained by experimental measurement or prediction. Technological advances in measurement science have propelled enormous growth in the scale of published thermodynamic data (almost doubling every 10 years). This expansion has created new challenges in data validation at all stages of the data delivery process. Despite the peer-review process, problems in data validation have led, in many instances, to publication of data that are grossly erroneous and, at times, inconsistent with the fundamental laws of nature. This article describes a new global data communication process in thermodynamics and its impact in addressing these challenges as well as in streamlining the delivery of the thermodynamic data from "data producers" to "data users". We believe that the prolific growth of scientific data in numerous and diverse fields outside thermodynamics, together with the demonstrated effectiveness and versatility of the process described in this article, will foster development of such processes in other scientific fields.