Computational Chemical Engineering

Computational Chemical Engineering develops open, reusable software for modeling chemical reactors and the transport phenomena that govern them — from mass transfer and reaction in multiphase reactors to fluid flow, particle packing, and diffusion at the pore scale.

Our tools grow out of research and teaching in the Chemical Engineering & Chemistry department at Eindhoven University of Technology (TU/e), led by Frank Peters. His work centres on the modeling and simulation of (multiphase) reactors and transport phenomena — the same themes that shape everything you find here. Everything is released under permissive open-source licenses so that students, researchers, and engineers can learn from it, build on it, and contribute back.

Two active flagship projects anchor the organization today: pymrm for reactor-scale modeling, and Peclet for high-performance transport-phenomena simulation. Each ships with a companion project — a book and an examples gallery — so you can go from first principles to running code.

What it is. pymrm is a Python package for building and solving multiphase reactor models. Born as a Matlab toolset for the Multiphase Reactor Modeling course at TU/e, it has been reborn as an open, Python-native library. The aim. Make reactor modeling approachable without sacrificing rigor — give students and practitioners composable building blocks for diffusion, convection, reaction, and mass transfer, assembled into sparse discretized systems that are easy to read, extend, and trust. Highlights 🧩 Building blocks for diffusion · convection · reaction · mass transfer 🧮 Sparse finite-volume construction with boundary-condition helpers 🎓 Tutorial- and example-driven, built for teaching and research 📦 One-line install: pip install pymrm Learn it — the pymrm-book. A companion Jupyter Book that walks through the theory and the package hands-on. 📖 Read it online: https://computational-chemical-engineering.github.io/pymrm-book

The PyMRM logo, from the pymrm-book.

_{Rotating drum of cubic particles, computed with Peclet — from peclet-examples.}

What it is. Peclet is a suite of codes for simulating transport phenomena — Eulerian CFD (incompressible Navier–Stokes), Lagrangian DEM (particle packing), and mixed Voronoi methods — sharing one MPI block domain decomposition, signed-distance-field geometry, a common immersed-boundary methodology, GPU support, and Python bindings.

The aim. Provide a portable, high-performance foundation for pore- and particle-scale transport, where the same source runs multi-threaded on a laptop or across GPUs (CUDA / HIP) on a supercomputer. The name nods to the Péclet number — the ratio of advection to diffusion at the dimensionless heart of transport phenomena.

Highlights

• 🌊 CFD · 🧱 DEM · 🔷 Voronoi on a shared Kokkos + block-decomposition core
• ⚡ GPU (CUDA/HIP) and multi-rank MPI; multi-core wheels via pip install peclet
• 🧊 Cut-cell immersed boundaries over SDF-described solids
• 🐍 Unified peclet.* Python namespace

See it work — peclet-examples. A gallery of runnable, reproducible worked examples (channel MMS, cut-cell Poiseuille, packed-bed permeability, and more). 📖 Browse it: https://computational-chemical-engineering.github.io/peclet-examples

The Peclet suite is modular — peclet-core, peclet-flow, peclet-dem, peclet-voro, and peclet-morton each live in their own repository. Browse them all from the organization page.

• ⭐ Star the projects you find useful — it helps others discover them.
• 🐛 Open an issue to report bugs or request features.
• 🔧 Contribute — pull requests are welcome; see each repository's CONTRIBUTING guide.
• 🎓 Learn — start with the pymrm-book or the peclet-examples gallery.