Applied thermodynamics in chemical technology: current practice and future challenges

Examples are used to illuminate ways in which applied thermodynamics is being successfully deployed in chemical technology and the challenges that need to be overcome. -acid plant modeling was very difficult two decades ago because of the complexity of the thermodynamic properties and the need to describe kinetic and mass-transfer limitations in the process equipment. This complex process and other similar processes are routinely modeled today thanks largely to advances in applied thermodynamics. In fact, applied thermodynamics is an established cornerstone of chemical engineering. is an effective tool for custom applications and teaching since most scientists and engineers use it regularly. We demonstrate that the Excel add-in for Aspen Properties facilitates the creation of useful custom applications (e.g., analysis and understanding of flammability limits and analysis of pressure variation in batch reactors) – usually within a few hours – enabling big improvements in education and wide deployment of chemical technology. software enables modeling of complex processes – and highlights the challenging areas. This point is elucidated through a promising process for hydrogen production via thermochemical water splitting: the sulfur iodine cycle. The sulfuric acid decomposition section of this process can be simulated accurately, but other sections (acid generation and hydrogen iodide decomposition) illustrate the difficulty of modeling phase behavior, particularly liquid-phase immiscibility, in complex electrolyte systems. The difficulties arise from model inadequacies as well as a lack of fundamental data. However, these difficulties will likely be overcome soon mainly through new data, but also through advance in molecular-thermodynamic models. ty estimation and data regression have progressed as independent silos for the development of applied thermodynamic models. We discuss the seminal contribution of a recent proposal that combines a segment-based NRTL model with a few (3–4) solubility measurements for a target solute to develop a predictive method for the solubility of this solute in most solvents and solvent mixtures of interest. This proposal creates an effective and efficient work process for solvent selection in the pharmaceutical and specialty chemical industries. per concludes by summarizing challenges that remain for the future use of applied thermodynamics in chemical technology.