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FeOs - fused-chain functional
Fused-chain Helmholtz energy functional implemented in the feos framework.
For details on the development of the model, check out our publication:
Installation
Rust
Add this to your Cargo.toml
[dependencies]
feos-fused-chains = "0.1"
Python
From within a Python virtual environment with maturin installed, type
maturin build --release --out dist --no-sdist
to build the wheel. To directly install the package into the virtual environment, use
maturin develop --release
The package can also be directly installed (needs the Rust compiler and maturin) with
pip install git+https://github.com/feos-org/feos-fused-chains
Example
For simple systems, an instance of the functional can be created using either of the following constructors:
from feos_fused_chains import *
func = FusedChainFunctional.new_monomer(1.0)
func = FusedChainFunctional.new_dimer(1.0, 0.8, 0.5)
func = FusedChainFunctional.new_trimer(0.8, 1.0, 0.8, 0.5, 0.7)
func = FusedChainFunctional.new_homosegmented(5, 1.0, 0.6)
More general fluids can be specified by creating FusedChainRecords first
from feos_fused_chains import *
import numpy as np
dimer = FusedChainRecord(np.array([1.0, 1.0]), [(0, 1, 0.5)])
trimer = FusedChainRecord(np.array([0.6, 1.0, 0.8]), [(0, 1, 0.8), (1, 2, 0.9)])
chain = FusedChainRecord(np.array([1.0] * 5), [(i, i+1, 0.8) for i in range(4)])
func = FusedChainFunctional.from_records([dimer, trimer, chain])
The functional can then be used with all applicable features of the FeOs framework.
Example: calculate the density profile of a dimer in a slit pore
from feos_fused_chains import *
from feos_fused_chains.si import *
import matplotlib.pyplot as plt
dimer = FusedChainFunctional.new_dimer(1.0, 1.0, 0.6)
bulk = State(dimer, KELVIN, density=0.4/NAV/ANGSTROM**3)
profile = Pore1D(dimer, Geometry.Cartesian, 11*ANGSTROM, ExternalPotential.HardWall(1.0)).initialize(bulk).solve()
plt.plot(profile.z/ANGSTROM, (profile.density*NAV*ANGSTROM**3).T)
plt.axis([0,5,0,1.5])