Welcome to the web site of the Electrolyte Thermodynamics Joint Industry Project (JIP). This project federates nine partners over a four year period, and has three aims:
The diversity of the industrial partners collaborating within the EleTher JIP makes it possible to be as exhaustive as possible in the identification of the challenges. As was already pointed out during a round-table held during ESAT 2021 meeting, they strongly depend on the application:
- sometimes (leaching or scale fomation applications) the solubility limit of salts in various types of solutions are needed
- elsewhere (in stripping or distillation applications) the volatility of the molecular compounds is important
- in some cases, the design of an extractive solvent requires the understanding of liquid-liquid equilibria
- in corrosion or electrochemical applications, the activity of ioninc species is of direct interest as they contribute in the reaction scheme
In all cases, modelling tools are needed in order to be able to design the most adequate process. There are today only a limited number of commercially available tools, and they are generally difficult to parameterize for novel applications.
Applied Thermodynamics has been identified as one of the key enabling technologies for several of the UN sustainable development goals. Electrolytes were there selected as a family of systems that requires important progress in the understanding of the underlying physics so as to make available industrial.
In order to progress in that direction, the EleTher JIP groups several important industrial partners and wants to be an advocate to point towards promising research directions. We believe that only collaborative efforts, targeted to needs that have been validated by industry will help in developing tools that can effectively be used for strongly needed applications.
For developing an adequate model, three stages need to be valicated:
1. At first, data must be available
When data exist, they may be unreliable or far awy from the operational conditions. For this, it is necessary to perform concsistency analysis: internal consistency and external consistency.
2. The second step consists in extrapolating the data to the operational conditions. This can be done in several ways:
- use of graphical presentations to understand the trends of the exixsting data
- use of theoretical models that use fundamental physical principles
3. Finally, a model that is available within a commercial simulator should be calibrated to the best possible data: those that are consistent and close to the operational conditions. The number of parameters is often large in this stage, so that simplifying assumptions may be needed to optain the best results.