def chung(target, Cv='pore.heat_capacity', acentric_factor=
    'pore.acentric_factor', mol_weight='pore.molecular_weight', viscosity=
    'pore.viscosity', temperature='pore.temperature', critical_temperature=
    'pore.critical_temperature'):
    """
    Uses Chung et al. model to estimate thermal conductivity for gases with
    low pressure(<10 bar) from first principles at conditions of interest

    Parameters
    ----------
    target : OpenPNM Object
        The object for which these values are being calculated.  This
        controls the length of the calculated array, and also provides
        access to other necessary thermofluid properties.

    acentric_factor : string
        Dictionary key containing the acentric factor of the component

    Cv : string
        Dictionary key containing the heat capacity at constant volume
        (J/(mol.K))

    mol_weight : string
        Dictionary key containing the molecular weight of the component
        (kg/mol)

    viscosity : string
        The dictionary key containing the viscosity values (Pa.s)

    temperature : string
        The dictionary key containing the temperature values (K)

    critical_temperatre: string
        The dictionary key containing the critical temperature values (K)

    Returns
    -------
    value : NumPy ndarray
        Array containing thermal conductivity values in [W/m.K]

    """
    Cv = target[Cv]
    acentric = target[acentric_factor]
    MW = target[mol_weight]
    R = 8.314
    T = target[temperature]
    mu = target[viscosity]
    Tc = target[critical_temperature]
    Tr = T / Tc
    z = 2.0 + 10.5 * Tr ** 2
    beta = 0.7862 - 0.7109 * acentric + 1.3168 * acentric ** 2
    alpha = Cv / R - 3 / 2
    s = 1 + alpha * ((0.215 + 0.28288 * alpha - 1.061 * beta + 0.26665 * z) /
        (0.6366 + beta * z + 1.061 * alpha * beta))
    value = 3.75 * s * mu * R / MW
    return value
