Saturated R-32 Properties

Liquid and vapor density, enthalpy, and entropy of saturated R-32 (difluoromethane, CH₂F₂) at selected temperatures, computed using CoolProp.

# Install CoolProp if it is missing (e.g., on Google Colab)
try:
    import CoolProp
except ImportError:
    %pip install -q CoolProp

import numpy as np
import pandas as pd
from CoolProp.CoolProp import PropsSI

pd.set_option('display.float_format', '{:.4f}'.format)
pd.set_option('display.max_columns', 20)

fluid = 'R32'
temperatures = [253, 273, 283, 293, 308, 318, 328]  # K

rows = []
for T in temperatures:
    P_sat = PropsSI('P', 'T', T, 'Q', 0, fluid) / 1e5  # bar

    rho_L = PropsSI('D', 'T', T, 'Q', 0, fluid)        # kg/m³
    h_L   = PropsSI('H', 'T', T, 'Q', 0, fluid) / 1e3  # kJ/kg
    s_L   = PropsSI('S', 'T', T, 'Q', 0, fluid) / 1e3  # kJ/(kg·K)

    rho_V = PropsSI('D', 'T', T, 'Q', 1, fluid)        # kg/m³
    h_V   = PropsSI('H', 'T', T, 'Q', 1, fluid) / 1e3  # kJ/kg
    s_V   = PropsSI('S', 'T', T, 'Q', 1, fluid) / 1e3  # kJ/(kg·K)

    rows.append({
        'T (K)':          T,
        'P_sat (bar)':    P_sat,
        'ρ_L (kg/m³)':   rho_L,
        'h_L (kJ/kg)':   h_L,
        's_L (kJ/kg·K)': s_L,
        'ρ_V (kg/m³)':   rho_V,
        'h_V (kJ/kg)':   h_V,
        's_V (kJ/kg·K)': s_V,
    })

df = pd.DataFrame(rows).set_index('T (K)')

print('Saturated R-32 Properties (CoolProp)')
print('=' * 80)
print(df.to_string())

Saturated R-32 Properties (CoolProp)
================================================================================
       P_sat (bar)  ρ_L (kg/m³)  h_L (kJ/kg)  s_L (kJ/kg·K)  ρ_V (kg/m³)  h_V (kJ/kg)  s_V (kJ/kg·K)
T (K)                                                                                               
253         4.0346    1121.0274     165.6900         0.8710      11.0963     509.9215         2.2316
273         8.0920    1055.7748     199.7380         0.9991      21.9846     515.2715         2.1549
283        11.0198    1020.2031     217.4720         1.0618      30.0934     516.6472         2.1190
293        14.6845     981.9809     235.8394         1.1243      40.6745     516.9034         2.0836
308        21.8159     917.7454     264.9994         1.2189      63.0679     514.5267         2.0290
318        27.8486     868.0674     285.9805         1.2837      84.4830     510.3765         1.9894
328        35.0803     809.2929     308.9210         1.3521     114.4470     503.0721         1.9440

# Styled display for notebooks
df.style \
    .set_caption('Saturated R-32 Properties') \
    .format({
        'P_sat (bar)':    '{:.4f}',
        'ρ_L (kg/m³)':   '{:.2f}',
        'h_L (kJ/kg)':   '{:.4f}',
        's_L (kJ/kg·K)': '{:.6f}',
        'ρ_V (kg/m³)':   '{:.4f}',
        'h_V (kJ/kg)':   '{:.4f}',
        's_V (kJ/kg·K)': '{:.6f}',
    })

Table 1: Saturated R-32 Properties

	P_sat (bar)	ρ_L (kg/m³)	h_L (kJ/kg)	s_L (kJ/kg·K)	ρ_V (kg/m³)	h_V (kJ/kg)	s_V (kJ/kg·K)
T (K)
253	4.0346	1121.03	165.6900	0.870987	11.0963	509.9215	2.231586
273	8.0920	1055.77	199.7380	0.999054	21.9846	515.2715	2.154855
283	11.0198	1020.20	217.4720	1.061832	30.0934	516.6472	2.118988
293	14.6845	981.98	235.8394	1.124336	40.6745	516.9034	2.083599
308	21.8159	917.75	264.9994	1.218865	63.0679	514.5267	2.029018
318	27.8486	868.07	285.9805	1.283731	84.4830	510.3765	1.989379
328	35.0803	809.29	308.9210	1.352072	114.4470	503.0721	1.943996

# Export to CSV (opens directly in Excel)
# utf-8-sig adds a BOM so Excel recognises the encoding on both Mac and Windows
csv_path = 'R32_saturation.csv'
df.to_csv(csv_path, encoding='utf-8-sig')
print(f'Saved: {csv_path}')

Saved: R32_saturation.csv

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