May 2025
With the Predici Maxwell release and the next version of Petro‑SIM, several powerful new features are now available for integrated process simulation.
A key addition is the new shooting control mechanism, enabling seamless modeling of countercurrent cooling in plug flow reactors (PFRs) and dynamic online tuning of process behavior.
Predici models — including those using full distribution mode — can now be effortlessly embedded into Petro‑SIM flowsheets, allowing detailed kinetic and polymer modeling to be part of plant-wide simulations.
This extended interoperability opens up new possibilities for polymerization modeling within larger process frameworks.
The integration was developed in collaboration with KBC (a Yokogawa company) and is available to licensed users.
The Predici–Petro‑SIM collaboration began in 2022, combining Predici’s strength in polymer reaction modeling with Petro‑SIM’s advanced flowsheeting capabilities for steady-state and dynamic simulation. From the start, the goal was to make detailed, reusable polymer models directly accessible within larger process designs — without added coding or interface development.
🔔 Predici 64-bit is coming in 2025
August 2025
We’re excited to announce that a new version of Predici is in development — built on the latest compiler and library architecture.
As always, we’re committed to using state-of-the-art development tools to ensure performance, reliability, and long-term compatibility.
⚡  Significantly faster than the 32-bit version — for both deterministic and Monte Carlo simulations
🧠No memory limitations, enabling large-scale variation and extended training runs
🤖 Better support for ML workflows: more simulations, deeper recipe exploration, and scalable model training
This marks a major step forward in simulation capability and performance.
More updates coming soon.
✅ New Predici Release Available
August 2025
Version 11.7.1.37 is now available for download by registered users through their usual access point.
Polymer Reaction Engineering XII
June 2025
CiT founder Dr. Michael Wulkow delivered a keynote address at Polymer Reaction Engineering XII and hosted an open, three-hour hands-on workshop introducing key concepts of model building and parameter estimation using Predici.
It was great to reconnect with many colleagues and users at PRE!
CiT continues partnership with KBC
May 2025
With the Predici Maxwell release and the next version of Petro‑SIM, several powerful new features are now available for integrated process simulation.
A key addition is the new shooting control mechanism, enabling seamless modeling of countercurrent cooling in plug flow reactors (PFRs) and dynamic online tuning of process behavior.
Predici models — including those using full distribution mode — can now be effortlessly embedded into Petro‑SIM flowsheets, allowing detailed kinetic and polymer modeling to be part of plant-wide simulations.
This extended interoperability opens up new possibilities for polymerization modeling within larger process frameworks.
The integration was developed in collaboration with KBC (a Yokogawa company) and is available to licensed users.
The Predici–Petro‑SIM collaboration began in 2022, combining Predici’s strength in polymer reaction modeling with Petro‑SIM’s advanced flowsheeting capabilities for steady-state and dynamic simulation. From the start, the goal was to make detailed, reusable polymer models directly accessible within larger process designs — without added coding or interface development.
Free-Radical Homopolymerization Kinetics of Biobased Dibutyl Itaconate
Multiscale modeling of the microbial production of polyhydroxyalkanoates using two carbon sources
PhD thesis of Niklas Wulkow, former CiT researcher: Modelling Observations of Dynamical Systems with Memory
Determination of reactivity ratios for acrylic acid and its dimer from classical parameter estimation and Bayesian approach
Deterministic and Stochastic Parameter Estimation for Polymer Reaction Kinetics I: Theory and Simple Examples
WILEY-VHC : Modeling and Simulation in Polymer Reaction Engineering - AÂ Modular Approach Hungenberg, Klaus-Dieter / Wulkow, Michael