Julia ecosystem for computational chemistry and thermodynamic equilibrium
Cement hydration · Aqueous geochemistry · Low-carbon materials
ChemistryTools is an open-source Julia ecosystem designed for researchers, engineers, and developers working on thermodynamic equilibrium calculations in chemistry. Built around Gibbs energy minimisation, the packages handle everything from chemical formula parsing and database interoperability (ThermoFun / Cemdata18) to full speciation and multi-phase equilibrium. The stack is ForwardDiff-compatible, SciML-native, and designed for integration with broader scientific computing workflows in Julia.
ChemistryLab.jl — Core toolkit
ChemistryLab.jl is the central package of the ecosystem. It provides chemical formula handling, species management, stoichiometric matrix construction, and database interoperability (ThermoFun and Cemdata18). Its equilibrium engine drives Gibbs energy minimisation through a composable activity model interface and supports both aqueous speciation and multi-phase solid solution assemblages.
| Feature | Details |
|---|---|
| Chemical formula handling | Parsing, molar mass, charge, Unicode / Phreeqc notation |
| Database interoperability | Import ThermoFun (.json) and Cemdata (.dat); merge datasets |
| Activity models | DiluteSolutionModel, HKFActivityModel (B-dot), DaviesActivityModel |
| Solid solutions | Ideal (IdealSolidSolutionModel) and binary non-ideal (RedlichKisterModel) |
| Chemical equilibrium | ChemicalSystem / ChemicalState / equilibrate (Gibbs minimisation) |
| Automatic differentiation | Full ForwardDiff compatibility throughout |
julia> import Pkg; Pkg.add("ChemistryLab")Full documentation and tutorials →
OptimaSolver.jl — Equilibrium solver
OptimaSolver.jl is a Julia-native primal-dual interior-point solver for Gibbs energy minimisation in equilibrium chemistry. It is a Julia port of the Optima C++ library developed by Allan Leal (ETH Zürich), adapted and extended for seamless SciML integration. OptimaOptimizer is a drop-in replacement for IpoptOptimizer in ChemistryLab.jl.
| Feature | Details |
|---|---|
| Algorithm | Log-barrier interior-point method (primal-dual) |
| Schur-complement Newton step | KKT system reduced from |
| Warm-start | Consecutive solves reuse previous solution as starting point |
| Implicit-differentiation sensitivity |
|
| Automatic differentiation | Generic Julia arithmetic — no Float64 casts |
| SciML / ChemistryLab integration |
OptimaOptimizer implements SciMLBase.AbstractOptimizationAlgorithm
|
julia> import Pkg; Pkg.add("OptimaSolver")Calcite–water equilibrium using the Cemdata18 database:
using ChemistryLab
# Load species from the bundled Cemdata18/ThermoFun database
all_species = build_species("data/cemdata18-thermofun.json")
# Select species relevant to calcite dissolution in water
species_calcite = speciation(all_species, split("Cal H2O@ CO2");
aggregate_state = [AS_AQUEOUS],
exclude_species = split("H2@ O2@ CH4@"))
dict_calcite = Dict(symbol(s) => s for s in species_calcite)
# Build the chemical system and define an initial state
cs = ChemicalSystem(collect(values(dict_calcite)))
state0 = ChemicalState(cs; T = 298.15u"K", P = 1u"bar")
set_quantity!(state0, "H2O@", 55.5u"mol")
set_quantity!(state0, "Cal", 1e-3u"mol")
set_quantity!(state0, "H+", 1e-7u"mol")
set_quantity!(state0, "OH-", 1e-7u"mol")
# Compute thermodynamic equilibrium (Gibbs energy minimisation)
state_eq = equilibrate(state0)
# Read results
pH(state_eq) # equilibrium pH (~8.3)
moles(state_eq, "Ca+2") # dissolved calciumUse OptimaSolver.jl as a faster, pure-Julia alternative to Ipopt:
using OptimaSolver
state_eq = equilibrate(state0; solver = OptimaOptimizer(tol = 1e-10))Developed by Jean-François Barthélémy and Anthony Soive, researchers at Cerema in the UMR MCD research unit.
MIT — see ChemistryLab.jl/LICENSE · OptimaSolver.jl/LICENSE
