Thermochemical comparison of fuels

This notebook compares the thermal behavior of three fuels of interest in energy systems, using pyglenn:

Species	Fuel
CH4	Methane (natural gas / biogas)
C2H5OH	Ethanol (biofuel)
C3H8	Propane (LPG)

We will visualize \(C_p(T)\), \(S^\circ(T)\) and the sensible enthalpy change \(\Delta H(298.15\,\mathrm{K} \to T)\) over a temperature range relevant to combustion.

Requires matplotlib — install with pip install -e ".[examples]".

Note on CH₄: the bundled NASA-7 coefficients for methane show a systematic \(C_p\) bias (>5% vs NIST-JANAF); CH₄ is therefore excluded from the NIST cross-validation audit. The comparison below is illustrative.

import matplotlib.pyplot as plt

from pyglenn import ThermochemicalCalculator

FUELS = {
    'CH4': 'Methane (natural gas)',
    'C2H5OH': 'Ethanol',
    'C3H8': 'Propane (LPG)',
}

Resolving the identifiers

get_available_species with exact_match=True performs a case-insensitive exact lookup, returning only the species whose name matches the pattern (e.g. 'O2' returns O₂, not Al₂O₂ or Be₃N₂).

with ThermochemicalCalculator() as calc:
    ids = {
        name: calc.get_available_species(name, exact_match=True)[0].id
        for name in FUELS
    }

for name, sid in ids.items():
    print(f'{name:8} -> id {sid}')

CH4      -> id 296
C2H5OH   -> id 370
C3H8     -> id 393

Collecting properties over 300–2000 K

We use get_properties_range to evaluate all temperatures at once. The 300–2000 K range spans from ambient conditions up to typical flames.

temperatures = list(range(300, 2001, 50))

data = {}
with ThermochemicalCalculator() as calc:
    for name, sid in ids.items():
        span = calc.get_properties_range(sid, temperatures)
        Ts = sorted(span)
        data[name] = {
            'T': Ts,
            'cp': [span[T].cp for T in Ts],
            's': [span[T].s for T in Ts],
        }
        # Sensible ΔH relative to 298.15 K
        data[name]['dh'] = [
            calc.calculate_enthalpy_change(sid, 298.15, T) / 1000.0 for T in Ts
        ]  # kJ/mol

print('Properties collected for:', ', '.join(data))

Properties collected for: CH4, C2H5OH, C3H8

Specific heat \(C_p(T)\)

\(C_p\) rises with temperature as more vibrational modes become active. Larger molecules (ethanol, propane) have higher \(C_p\) because they have more degrees of freedom.

fig, ax = plt.subplots(figsize=(7, 4.5))
for name, d in data.items():
    ax.plot(d['T'], d['cp'], label=FUELS[name], linewidth=2)
ax.set_xlabel('Temperature (K)')
ax.set_ylabel(r'$C_p$  (J·mol$^{-1}$·K$^{-1}$)')
ax.set_title('Molar specific heat at constant pressure')
ax.legend()
ax.grid(True, alpha=0.3)
fig.tight_layout()
plt.show()

Sensible enthalpy \(\Delta H(298.15\,\mathrm{K} \to T)\)

This is the heat required to warm 1 mol of fuel from 298.15 K up to \(T\) — a central quantity in energy balances for preheating and heat recovery (HRSG).

fig, ax = plt.subplots(figsize=(7, 4.5))
for name, d in data.items():
    ax.plot(d['T'], d['dh'], label=FUELS[name], linewidth=2)
ax.axhline(0, color='gray', linewidth=0.8)
ax.set_xlabel('Temperature (K)')
ax.set_ylabel(r'$\Delta H$  (kJ·mol$^{-1}$)')
ax.set_title('Sensible enthalpy relative to 298.15 K')
ax.legend()
ax.grid(True, alpha=0.3)
fig.tight_layout()
plt.show()

Numerical summary at reference points

Direct comparison of \(C_p\) and \(S^\circ\) at three temperatures of interest.

targets = [300, 1000, 2000]

print(f"{'Fuel':<22} {'T (K)':>6} {'Cp':>10} {'S°':>10}")
print('-' * 50)
for name, d in data.items():
    for T in targets:
        i = d['T'].index(T)
        print(f'{FUELS[name]:<22} {T:>6} {d["cp"][i]:>10.3f} {d["s"][i]:>10.3f}')
    print()

Fuel                    T (K)         Cp         S°
--------------------------------------------------
Methane (natural gas)     300     35.760    186.592
Methane (natural gas)    1000     73.676    248.331
Methane (natural gas)    2000    101.443    309.449

Ethanol                   300     65.593    280.998
Ethanol                  1000    142.690    404.552
Ethanol                  2000    178.202    516.952

Propane (LPG)             300     73.956    270.771
Propane (LPG)            1000    174.614    417.341
Propane (LPG)            2000    221.956    556.445

Reading the results

• Ethanol and propane, being larger molecules, show higher \(C_p\) and \(S^\circ\) than methane across the whole range.

• The sensible enthalpy grows almost linearly at high temperatures, reflecting the plateau of \(C_p\).

• These data feed energy balances in combustion chambers, gasifiers and power cycles — see the applications in the project README.