Ypso-Ionic is a predictive simulator for processes involving ionic interactions.
It is based on the understanding and the description of the fundamental phenomena at stake. It maximizes the value of your experimental data and allows to explore operating conditions via predictive simulation.
This enables the design of optimized processes with minimal experimental burden.
Enjoy the benefits...
Maximize the value of your experimental data
- Check data consistency
- Apply a reproducible methodology
Estimate parameters and investigate system imperfections
- Determine key physico-chemical parameters for mechanistic modeling
- Evaluate columns heterogeneity
Simulate system performances
- Assess the inﬂuence of operating parameters
- Compare different conﬁgurations
- Fine tune process parameters
- Design, secure and optimize puriﬁcation processes from a few experiments, in combination with reliable simulation
- Share and compare results within a standardized framework
...And the user experience
Project dedicated space
Data related to your project are stored in your project space for easy sharing and comparison. In addition to simulation data, you can save there any document related to the project like relevant literature documents or reports. Furthermore, you can import your experimental data automatically and transform them in the Ypso-Ionic format.
A common format for experimental and simulated data
The standardized Ypso-Facto ﬁle format ensures the completeness of data and the consistency of the experimental conditions and of the process information (materials and species, equipment, conﬁgurations, …) This also allows for the experimental conditions to be automatically recognized by the simulator for seamless comparison between simulation and experiments.
Property and characteristic database
Resins and sorbents
Single column systems
Simply deﬁne whether you work in isocratic or in gradient mode, whether you perform simple injections or run complex multi-step sequencing and Ypso-Ionic will simulate the corresponding process.
Get access to the most sophisticated multi-column chromatography (MCC) systems in a few clicks. Beside the conventional SMB, the main commercial MCC set-ups are pre-conﬁgured based on publicly available information. This makes comparison between commercial options straightforward. Moreover, you can design and simulate any multi-column conﬁguration and operating sequence that you have in mind.
Play with chemistry
In contrast to chromatographic simulators, Ypso-Ionic also models the ionic nature of the species, the exchange phenomenon and the solution chemistry equilibria (complexation, acid-base reactions, etc.) Add a salt or remove a species in the feed solution or in the eluent and you will immediately get access to the consequences on your process.
Take a journey to the inside of your process with the display of dynamic simulations in real time. Observe and understand the evolution of the compositions, pH, conductivity, etc. in the solution and solid phase over time, within the column(s) and at the outlet(s). Ypso-Ionic is an open sight glass on the inside of your process.
- Easily evaluate key process parameters
- Analyze titrations or batch uptake experiments, single and multi-column runs, etc.
- Pre-program a list of simulations with DynAMO (Dynamic Assessment of Models)
- Use information gathered in BSTR to design a complex multi-column system
- Identify the design space and perform PAR study of your process with Design of Simulated Experiment (DoSE)
Typical examples of use
Select the best equipment for your separation
Ypso-Ionic is a key decision making tool to compare different set-ups objectively, from few experiments.
A parameter has varied in your process? No need to run costly and time-consuming lab experiments, Ypso-Ionic can evaluate in-silico the impact on your process performances and help you decide on corrective measures.
Better train your team
Ypso-Ionic can behave as a virtual twin of your systems and be used as a training system: the users can alter parameters to observe and understand their impact on the production.
They can train to bring a deviant process back within specifications or learn how to adjust to a variation of the feed composition without endangering the actual production.