2020 Virtual AIChE Annual Meeting
(83d) A Model-Data Driven Chemical Analysis System for Products and Associated Processes
Authors
Currently, more than one million chemicals can be found on planet earth and thousands of new chemical products are entering the global market every year. However, for only a fraction of these chemicals some of the important properties have been measured. Therefore, it is not feasible to simply perform needed chemical analysis based on measured experimental data. A more practical approach is to employ a model-data driven chemical analysis system that can quickly, efficiently and reliably identify the harmful chemicals in our products and also suggest alternatives that are more benign. The paper will highlight the current status of collected measured data, a suite of verified models to predict the missing data and the latest version of a systematic methodology for chemical substitution (1). Application of the new features will be illustrated through a case study highlighting the identity of the problem chemical, its function in the product as well as suggestions, including testing, of acceptable alternatives.
- S Jhamb, X Liang, R Gani, GM Kontogeorgis, 2019, A Systematic Model-based Methodology for Substitution of Hazardous Chemicals, ACS Sustainable Chemistry & Engineering 7, 7652-7666