pysorb 0.2.2

Python solvers for adsorption isotherm fitting, mixture prediction, breakthrough simulation, Crank diffusion, and ZLC modelling.

pysorb

pysorb is a Python library for adsorption modelling across equilibrium and dynamic kinetic workflows. It connects reusable numerical solvers for scripted scientific computing with GUI-facing adsorption workflows.

The current package supports pure-component isotherm fitting, multicomponent mixture prediction, fixed-bed breakthrough simulation, Crank diffusion uptake analysis, and zero length column (ZLC) modelling. The numerical routines use NumPy and SciPy, with Numba-compatible kernels used in the mixture and breakthrough solvers for repeated numerical evaluation.

The package contains five solver areas:

• pysorb.mix for multicomponent equilibrium calculations.
• pysorb.bt for fixed-bed breakthrough simulations.
• pysorb.fit for adsorption isotherm fitting.
• pysorb.crank for Crank diffusion uptake calculations.
• pysorb.zlc for zero length column simulations.

The current package release is 0.2.2; version 0.1.0 was used as an initial PyPI test release.

Citation

Citation metadata is provided in CITATION.cff.

Archived release DOI: 10.5281/zenodo.20478633

Installation

pip install pysorb

For local development from this repository:

pip install -e .

Basic Usage

from pysorb.crank import crank_uptake, fit_D_R2
from pysorb.zlc import linmodel
from pysorb.mix import parse, unary, ext, iast
from pysorb.fit import fit_isotherm
from pysorb.bt import run_simulation

Crank diffusion

from pysorb.crank import crank_uptake

q_over_qinf = crank_uptake([0, 1, 2], D_R2=0.001)

ZLC

from pysorb.zlc import linmodel

t, c, c_preload, q, q_preload, sigsum = linmodel(
    Lsat=20,
    DR2=6.4e-3,
    gamma=0.001,
    tsat=50,
    t_end=80,
    NN="auto",
)

Mixture equilibrium

from pysorb.mix import parse, iast

components = [
    {"MoleculeName": "A", "isotherms": [["Langmuir", 1.0, 0.5]]},
    {"MoleculeName": "B", "isotherms": [["Langmuir", 2.0, 0.2]]},
]

parsed = parse(components)
result = iast([1.0, 0.5], parsed=parsed)

Isotherm fitting

import numpy as np
from pysorb.fit import fit_isotherm

P = np.array([0.1, 0.3, 0.7, 1.2, 2.0])
T = np.full_like(P, 298.15)
q = 1.5 * 0.8 * P / (1 + 0.8 * P)

fit = fit_isotherm(P, q, T, "Langmuir", mode="single")
print(fit.parameters)

Breakthrough

from pysorb.bt import run_simulation

# Pass the same input dictionary shape used by the existing BT solver.
result = run_simulation(inputs)