Phase Identification (thermo.phase_identification)

This module contains functions for identifying phases as liquid, solid, and gas.

Solid identification is easy using the phase identification parameter. There is never more than one gas by definition. For pure species, the phase identification parameter is a clear vapor-liquid differentiator in the subcritical region and it provides line starting at the critical point for the supercritical region.

However for mixtures, there is no clear calcuation that can be performed to identify the phase of a mixture. Many different criteria that have been proposed are included here. The phase identification parameter or PIP. is recommended in general and is the default.

For reporting bugs, adding feature requests, or submitting pull requests, please use the GitHub issue tracker.

Phase Identification

Main Interface

thermo.phase_identification.identify_sort_phases(phases, betas, constants, correlations, settings, skip_solids=False)

Identify and sort all phases given the provided parameters.

Parameters

phaseslist[Phase]

Phases to be identified and sorted, [-]

betaslist[float]

Phase molar fractions, [-]

constantsChemicalConstantsPackage

Constants used in the identification, [-]

correlationsPropertyCorrelationsPackage

Correlations used in the identification, [-]

settingsBulkSettings

Settings object controlling the phase ID, [-]

skip_solidsbool

Set this to True if no phases are provided which can represent a solid phase, [-]

Returns

gasPhase

Gas phase, if one was identified, [-]

liquidslist[Phase]

Liquids that were identified and sorted, [-]

solidslist[Phase]

Solids that were identified and sorted, [-]

betaslist[float]

Sorted phase molar fractions, in order (gas, liquids…, solids…) [-]

Notes

This step is very important as although phase objects are designed to represent a single phase, cubic equations of state can be switched back and forth by the flash algorithms. Thermodynamics doesn’t care about gases, liquids, or solids; it just cares about minimizing Gibbs energy!

Examples

A butanol-water-ethanol flash yields three phases. For brevity we skip the flash and initialize our gas, liq0, and liq1 object with the correct phase composition. Then we identify the phases into liquid, gas, and solid.

>>> from thermo import ChemicalConstantsPackage, PropertyCorrelationsPackage, HeatCapacityGas, SRKMIX, CEOSGas, CEOSLiquid
>>> constants = ChemicalConstantsPackage(Tcs=[563.0, 647.14, 514.0], Vcs=[0.000274, 5.6e-05, 0.000168], Pcs=[4414000.0, 22048320.0, 6137000.0], omegas=[0.59, 0.344, 0.635], MWs=[74.1216, 18.01528, 46.06844], CASs=['71-36-3', '7732-18-5', '64-17-5'])
>>> properties = PropertyCorrelationsPackage(constants=constants, skip_missing=True,
...                                     HeatCapacityGases=[HeatCapacityGas(load_data=False, poly_fit=(50.0, 1000.0, [-3.787200194613107e-20, 1.7692887427654656e-16, -3.445247207129205e-13, 3.612771874320634e-10, -2.1953250181084466e-07, 7.707135849197655e-05, -0.014658388538054169, 1.5642629364740657, -7.614560475001724])),
...                                     HeatCapacityGas(load_data=False, poly_fit=(50.0, 1000.0, [5.543665000518528e-22, -2.403756749600872e-18, 4.2166477594350336e-15, -3.7965208514613565e-12, 1.823547122838406e-09, -4.3747690853614695e-07, 5.437938301211039e-05, -0.003220061088723078, 33.32731489750759])),
...                                     HeatCapacityGas(load_data=False, poly_fit=(50.0, 1000.0, [-1.162767978165682e-20, 5.4975285700787494e-17, -1.0861242757337942e-13, 1.1582703354362728e-10, -7.160627710867427e-08, 2.5392014654765875e-05, -0.004732593693568646, 0.5072291035198603, 20.037826650765965])),], )
>>> eos_kwargs = dict(Tcs=constants.Tcs, Pcs=constants.Pcs, omegas=constants.omegas)
>>> gas = CEOSGas(SRKMIX, eos_kwargs, HeatCapacityGases=properties.HeatCapacityGases)
>>> liq = CEOSLiquid(SRKMIX, eos_kwargs, HeatCapacityGases=properties.HeatCapacityGases)
>>> T, P = 361, 1e5
>>> gas = gas.to(T=T, P=P, zs=[0.2384009970908655, 0.5786839935180925, 0.1829150093910419])
>>> liq0 = liq.to(T=T, P=P, zs=[7.619975052238032e-05, 0.9989622883894993, 0.0009615118599781474])
>>> liq1 = liq.to(T=T, P=P, zs=[0.6793120076703771, 0.19699746328631124, 0.12369052904331178])
>>> res = identity_phase_states(phases=[liq0, liq1, gas], constants=constants, correlations=properties, VL_method='PIP')
>>> res[0] is gas, res[1][0] is liq0, res[1][1] is liq1, res[2]
(True, True, True, [])

Secondary Interfaces

thermo.phase_identification.identity_phase_states(phases, constants, correlations, VL_method='PIP', S_method='d2P_dVdT', VL_ID_settings=None, S_ID_settings=None, skip_solids=False)

Identify and the actial phase of all the given phases given the provided settings.

Parameters

phaseslist[Phase]

Phases to be identified and sorted, [-]

constantsChemicalConstantsPackage

Constants used in the identification, [-]

correlationsPropertyCorrelationsPackage

Correlations used in the identification, [-]

VL_methodstr, optional

One of VL_ID_METHODS, [-]

S_methodstr, optional

One of S_ID_METHODS, [-]

VL_ID_settingsdict[strfloat] or None, optional

Additional configuration options for vapor-liquid phase ID, [-]

S_ID_settingsdict[strfloat] or None, optional

Additional configuration options for solid-liquid phase ID, [-]

skip_solidsbool

Set this to True if no phases are provided which can represent a solid phase, [-]

Returns

gasPhase

Gas phase, if one was identified, [-]

liquidslist[Phase]

Liquids that were identified and sorted, [-]

solidslist[Phase]

Solids that were identified and sorted, [-]

thermo.phase_identification.VL_ID_METHODS = ['Tpc', 'Vpc', 'Tpc Vpc weighted', 'Tpc Vpc', 'Wilson', 'Poling', 'PIP', 'Bennett-Schmidt', 'Traces']

List of all the methods available to perform the Vapor-Liquid phase ID.

thermo.phase_identification.S_ID_METHODS = ['d2P_dVdT']

List of all the methods available to perform the solid-liquid phase ID.

Scoring Functions

thermo.phase_identification.score_phases_VL(phases, constants, correlations, method)

Score all phases given the provided parameters and a selected method.

A score above zero indicates a potential gas. More than one phase may have a score above zero, in which case the highest scoring phase is the gas, and the other is a liquid.

Parameters

phaseslist[thermo.phases.Phase]

Phases to be identified and sorted, [-]

constantsChemicalConstantsPackage

Constants used in the identification, [-]

correlationsPropertyCorrelationsPackage

Correlations used in the identification, [-]

methodstr

Setting configuring how the scoring is performed; one of ‘Tpc’, ‘Vpc’, ‘Tpc Vpc weighted’, ‘Tpc Vpc’, ‘Wilson’, ‘Poling’, ‘PIP’, ‘Bennett-Schmidt’, ‘Traces’, [-]

Returns

scoreslist[float]

Scores for the phases in the order provided, [-]

Examples

>>> from thermo import ChemicalConstantsPackage, PropertyCorrelationsPackage, CEOSGas, CEOSLiquid, PRMIX, HeatCapacityGas
>>> constants = ChemicalConstantsPackage(CASs=['124-38-9', '110-54-3'], Vcs=[9.4e-05, 0.000368], MWs=[44.0095, 86.17536], names=['carbon dioxide', 'hexane'], omegas=[0.2252, 0.2975], Pcs=[7376460.0, 3025000.0], Tbs=[194.67, 341.87], Tcs=[304.2, 507.6], Tms=[216.65, 178.075])
>>> correlations = PropertyCorrelationsPackage(constants=constants, skip_missing=True, HeatCapacityGases=[HeatCapacityGas(poly_fit=(50.0, 1000.0, [-3.1115474168865828e-21, 1.39156078498805e-17, -2.5430881416264243e-14, 2.4175307893014295e-11, -1.2437314771044867e-08, 3.1251954264658904e-06, -0.00021220221928610925, 0.000884685506352987, 29.266811602924644])), HeatCapacityGas(poly_fit=(200.0, 1000.0, [1.3740654453881647e-21, -8.344496203280677e-18, 2.2354782954548568e-14, -3.4659555330048226e-11, 3.410703030634579e-08, -2.1693611029230923e-05, 0.008373280796376588, -1.356180511425385, 175.67091124888998]))])
>>> T, P, zs = 300.0, 1e6, [.5, .5]
>>> eos_kwargs = {'Pcs': constants.Pcs, 'Tcs': constants.Tcs, 'omegas': constants.omegas}
>>> gas = CEOSGas(PRMIX, eos_kwargs, HeatCapacityGases=correlations.HeatCapacityGases, T=T, P=P, zs=zs)
>>> liq = CEOSLiquid(PRMIX, eos_kwargs, HeatCapacityGases=correlations.HeatCapacityGases, T=T, P=P, zs=zs)

A sampling of different phase identification methods is below:

>>> score_phases_VL([gas, liq], constants, correlations, method='PIP')
[1.6409446310, -7.5692120928]
>>> score_phases_VL([gas, liq], constants, correlations, method='Vpc')
[0.00144944049, -0.0001393075288]
>>> score_phases_VL([gas, liq], constants, correlations, method='Tpc Vpc')
[113.181283525, -29.806038704]
>>> score_phases_VL([gas, liq], constants, correlations, method='Bennett-Schmidt')
[0.0003538299416, -2.72255439503e-05]
>>> score_phases_VL([gas, liq], constants, correlations, method='Poling')
[0.1767828268, -0.004516837897]

thermo.phase_identification.score_phases_S(phases, constants, correlations, method='d2P_dVdT', S_ID_settings=None)

Score all phases according to how wolid they appear given the provided parameters and a selected method.

A score above zero indicates a solid. More than one phase may have a score above zero. A score under zero means the phase is a liquid or gas.

Parameters

phaseslist[thermo.phases.Phase]

Phases to be identified and sorted, [-]

constantsChemicalConstantsPackage

Constants used in the identification, [-]

correlationsPropertyCorrelationsPackage

Correlations used in the identification, [-]

methodstr

Setting configuring how the scoring is performed; one of (‘d2P_dVdT’,), [-]

S_ID_settingsdict[strfloat] or None, optional

Additional configuration options for solid-liquid phase ID, [-]

Returns

scoreslist[float]

Scores for the phases in the order provided, [-]

thermo.phase_identification.vapor_score_traces(zs, CASs, Tcs, trace_CASs=['74-82-8', '7727-37-9'], min_trace=0.0)

Compute a vapor score representing how vapor-like a phase is (higher, above zero = more vapor like) using the concept of which phase has the most of the lightest compound. This nicely sidesteps issues in many other methods, at the expense that it cannot be applied when there is only one phase and it is not smart enough to handle liquid-liquid cases.

If no trace components are present, the component with the lowest critical temperature’s concentration is returned. Because of the way this is implemented, the score is always larger than 1.0.

Parameters

zslist[float]

Mole fractions of the phase being identified, [-]

CASslist[str]

CAS numbers of all components, [-]

Tcslist[float]

Critical temperatures of all species, [K]

trace_CASslist[str]

Trace components to use for identification; if more than one component is given, the first component present in both CASs and trace_CASs is the one used, [-]

min_tracefloat

Minimum concentration to make a phase appear vapor-like; subtracted from the concentration which would otherwise be returned, [-]

Returns

scorefloat

Vapor like score, [-]

Examples

A flash of equimolar CO2/n-hexane at 300 K and 1 MPa is computed, and there is a two phase solution. The phase must be identified for each result:

Liquid-like phase:

>>> vapor_score_traces(zs=[.218, .782], Tcs=[304.2, 507.6], CASs=['124-38-9', '110-54-3'])
0.218

Vapor-like phase:

>>> vapor_score_traces(zs=[.975, .025], Tcs=[304.2, 507.6], CASs=['124-38-9', '110-54-3'])
0.975

thermo.phase_identification.vapor_score_Tpc(T, Tcs, zs)

Compute a vapor score representing how vapor-like a phase is (higher, above zero = more vapor like) using the following criteria

$$T - \sum_i z_i T_{c,i}$$

Parameters

Tfloat

Temperature, [K]

Tcslist[float]

Critical temperatures of all species, [K]

zslist[float]

Mole fractions of the phase being identified, [-]

Returns

scorefloat

Vapor like score, [-]

Examples

A flash of equimolar CO2/n-hexane at 300 K and 1 MPa is computed, and there is a two phase solution. The phase must be identified for each result:

Liquid-like phase:

>>> vapor_score_Tpc(T=300.0, Tcs=[304.2, 507.6], zs=[0.21834418746784942, 0.7816558125321506])
-163.18879226903942

Vapor-like phase:

>>> vapor_score_Tpc(T=300.0, Tcs=[304.2, 507.6], zs=[0.9752234962374878, 0.024776503762512052])
-9.239540865294941

In this result, the vapor phase is not identified as a gas at all! It has a mass density of ~ 20 kg/m^3, which would usually be called a gas by most people.

thermo.phase_identification.vapor_score_Vpc(V, Vcs, zs)

Compute a vapor score representing how vapor-like a phase is (higher, above zero = more vapor like) using the following criteria

$$V - \sum_i z_i V_{c,i}$$

Parameters

Vfloat

Molar volume, [m^3/mol]

Vcslist[float]

Critical molar volumes of all species, [m^3/mol]

zslist[float]

Mole fractions of the phase being identified, [-]

Returns

scorefloat

Vapor like score, [-]

Examples

A flash of equimolar CO2/n-hexane at 300 K and 1 MPa is computed, and there is a two phase solution. The phase must be identified for each result:

Liquid-like phase:

>>> vapor_score_Vpc(V=0.00011316308855449715, Vcs=[9.4e-05, 0.000368], zs=[0.21834418746784942, 0.7816558125321506])
-0.000195010604079

Vapor-like phase:

>>> vapor_score_Vpc(V=0.0023406573328250335, Vcs=[9.4e-05, 0.000368], zs=[0.9752234962374878, 0.024776503762512052])
0.002239868570

thermo.phase_identification.vapor_score_Tpc_weighted(T, Tcs, Vcs, zs, r1=1.0)

Compute a vapor score representing how vapor-like a phase is (higher, above zero = more vapor like) using the following criteria, said to be implemented in ECLIPSE [1]:

$$T - T_{pc}$$

$$T_{p,c} = r_1 \frac{\sum_j x_j V_{c,j}T_{c,j}}{\sum_j x_j V_{c,j}}$$

Parameters

Tfloat

Temperature, [K]

Tcslist[float]

Critical temperatures of all species, [K]

Vcslist[float]

Critical molar volumes of all species, [m^3/mol]

zslist[float]

Mole fractions of the phase being identified, [-]

r1float

Tuning factor, [-]

Returns

scorefloat

Vapor like score, [-]

References

1

Bennett, Jim, and Kurt A. G. Schmidt. “Comparison of Phase Identification Methods Used in Oil Industry Flow Simulations.” Energy & Fuels 31, no. 4 (April 20, 2017): 3370-79. https://doi.org/10.1021/acs.energyfuels.6b02316.

Examples

A flash of equimolar CO2/n-hexane at 300 K and 1 MPa is computed, and there is a two phase solution. The phase must be identified for each result:

Liquid-like phase:

>>> vapor_score_Tpc_weighted(T=300.0, Tcs=[304.2, 507.6], Vcs=[9.4e-05, 0.000368], zs=[0.21834418746784942, 0.7816558125321506])
-194.0535694431

Vapor-like phase:

>>> vapor_score_Tpc_weighted(T=300.0, Tcs=[304.2, 507.6], Vcs=[9.4e-05, 0.000368], zs=[0.9752234962374878, 0.024776503762512052])
-22.60037521107

As can be seen, the CO2-phase is incorrectly identified as a liquid.

thermo.phase_identification.vapor_score_Tpc_Vpc(T, V, Tcs, Vcs, zs)

Compute a vapor score representing how vapor-like a phase is (higher, above zero = more vapor like) using the following criteria, said to be implemented in Multiflash [1]:

$$VT^2 - V_{pc} T_{pc}^2$$

Parameters

Tfloat

Temperature, [K]

Vfloat

Molar volume, [m^3/mol]

Tcslist[float]

Critical temperatures of all species, [K]

Vcslist[float]

Critical molar volumes of all species, [m^3/mol]

zslist[float]

Mole fractions of the phase being identified, [-]

Returns

scorefloat

Vapor like score, [-]

References

1

Bennett, Jim, and Kurt A. G. Schmidt. “Comparison of Phase Identification Methods Used in Oil Industry Flow Simulations.” Energy & Fuels 31, no. 4 (April 20, 2017): 3370-79. https://doi.org/10.1021/acs.energyfuels.6b02316.

Examples

A flash of equimolar CO2/n-hexane at 300 K and 1 MPa is computed, and there is a two phase solution. The phase must be identified for each result:

Liquid-like phase:

>>> vapor_score_Tpc_Vpc(T=300.0, V=0.00011316308855449715, Tcs=[304.2, 507.6], Vcs=[9.4e-05, 0.000368], zs=[0.21834418746784942, 0.7816558125321506])
-55.932094761

Vapor-like phase:

>>> vapor_score_Tpc_Vpc(T=300.0, V=0.0023406573328250335, Tcs=[304.2, 507.6], Vcs=[9.4e-05, 0.000368], zs=[0.9752234962374878, 0.024776503762512052])
201.020821992

thermo.phase_identification.vapor_score_Wilson(T, P, zs, Tcs, Pcs, omegas)

Compute a vapor score representing how vapor-like a phase is (higher, above zero = more vapor like) using the Rachford-Rice Wilson method of Perschke [1].

After calculating Wilson’s K values, the following expression is evaluated at $\frac{V}{F} = 0.5$; the result is the score.

$$\sum_i \frac{z_i(K_i-1)}{1 + \frac{V}{F}(K_i-1)}$$

Parameters

Tfloat

Temperature, [K]

Pfloat

Pressure, [Pa]

zslist[float]

Mole fractions of the phase being identified, [-]

Tcslist[float]

Critical temperatures of all species, [K]

Pcslist[float]

Critical pressures of all species, [Pa]

omegaslist[float]

Acentric factors of all species, [-]

Returns

scorefloat

Vapor like score, [-]

References

1

Chang, Yih-Bor. “Development and Application of an Equation of State Compositional Simulator,” 1990. https://repositories.lib.utexas.edu/handle/2152/80585.

Examples

A flash of equimolar CO2/n-hexane at 300 K and 1 MPa is computed, and there is a two phase solution. The phase must be identified for each result:

Liquid-like phase:

>>> vapor_score_Wilson(T=300.0, P=1e6, zs=[.218, .782], Tcs=[304.2, 507.6], Pcs=[7376460.0, 3025000.0], omegas=[0.2252, 0.2975])
-1.16644793

Vapor-like phase:

>>> vapor_score_Wilson(T=300.0, P=1e6, zs=[.975, .025], Tcs=[304.2, 507.6], Pcs=[7376460.0, 3025000.0], omegas=[0.2252, 0.2975])
1.397678492

This method works well in many conditions, like the Wilson equation itself, but fundamentally it cannot do a great job because it is not tied to the phase model itself.

A dew point flash at P = 100 Pa for the same mixture shows both phases being identified as vapor-like:

>>> T_dew = 206.40935716944634
>>> P = 100.0
>>> vapor_score_Wilson(T=T_dew, P=P, zs=[0.5, 0.5], Tcs=[304.2, 507.6], Pcs=[7376460.0, 3025000.0], omegas=[0.2252, 0.2975])
1.074361930956633
>>> vapor_score_Wilson(T=T_dew, P=P, zs=[0.00014597910182360052, 0.9998540208981763], Tcs=[304.2, 507.6], Pcs=[7376460.0, 3025000.0], omegas=[0.2252, 0.2975])
0.15021784286075726

thermo.phase_identification.vapor_score_Poling(kappa)

Compute a vapor score representing how vapor-like a phase is (higher, above zero = more vapor like) using the isothermal compressibility kappa concept by Poling [1].

$$\text{score} = (\kappa - 0.005 \text{atm}^{-1})$$

Parameters

kappafloat

Isothermal coefficient of compressibility, [1/Pa]

Returns

scorefloat

Vapor like score, [-]

Notes

A second criteria which is not implemented as it does not fit with the scoring concept is for liquids:

$$\frac{0.9}{P} < \beta < \frac{3}{P}$$

References

1

Poling, Bruce E., Edward A. Grens, and John M. Prausnitz. “Thermodynamic Properties from a Cubic Equation of State: Avoiding Trivial Roots and Spurious Derivatives.” Industrial & Engineering Chemistry Process Design and Development 20, no. 1 (January 1, 1981): 127-30. https://doi.org/10.1021/i200012a019.

Examples

CO2 vapor properties computed with Peng-Robinson at 300 K and 1 bar:

>>> vapor_score_Poling(1.0054239121594122e-05)
1.013745778995

n-hexane liquid properties computed with Peng-Robinson at 300 K and 10 bar:

>>> vapor_score_Poling(2.121777078782957e-09)
-0.00478501093

thermo.phase_identification.vapor_score_PIP(V, dP_dT, dP_dV, d2P_dV2, d2P_dVdT)

Compute a vapor score representing how vapor-like a phase is (higher, above zero = more vapor like) using the PIP concept.

$$\text{score} = -(\Pi - 1)$$

$$\Pi = V \left[\frac{\frac{\partial^2 P}{\partial V \partial T}} {\frac{\partial P }{\partial T}}- \frac{\frac{\partial^2 P}{\partial V^2}}{\frac{\partial P}{\partial V}} \right]$$

Parameters

Vfloat

Molar volume at T and P, [m^3/mol]

dP_dTfloat

Derivative of P with respect to T, [Pa/K]

dP_dVfloat

Derivative of P with respect to V, [Pa*mol/m^3]

d2P_dV2float

Second derivative of P with respect to V, [Pa*mol^2/m^6]

d2P_dVdTfloat

Second derivative of P with respect to both V and T, [Pa*mol/m^3/K]

Returns

scorefloat

Vapor like score, [-]

References

1

Venkatarathnam, G., and L. R. Oellrich. “Identification of the Phase of a Fluid Using Partial Derivatives of Pressure, Volume, and Temperature without Reference to Saturation Properties: Applications in Phase Equilibria Calculations.” Fluid Phase Equilibria 301, no. 2 (February 25, 2011): 225-33. doi:10.1016/j.fluid.2010.12.001.

Examples

CO2 vapor properties computed with Peng-Robinson at 300 K and 1 bar:

>>> vapor_score_PIP(0.024809176851423774, 337.0119286073647, -4009021.959558917, 321440573.3615088, -13659.63987996052)
0.016373735005

n-hexane liquid properties computed with Peng-Robinson at 300 K and 10 bar:

>>> vapor_score_PIP(0.00013038156684574785, 578477.8796379718, -3614798144591.8984, 4.394997991022487e+17, -20247865009.795322)
-10.288635225

thermo.phase_identification.vapor_score_Bennett_Schmidt(dbeta_dT)

Compute a vapor score representing how vapor-like a phase is (higher, above zero = more vapor like) using the Bennet-Schmidt temperature derivative of isobaric expansion suggestion.

$$\text{score} = -\left(\frac{\partial \beta}{\partial T}\right)$$

Parameters

dbeta_dTfloat

Temperature derivative of isobaric coefficient of a thermal expansion, [1/K^2]

Returns

scorefloat

Vapor like score, [-]

References

1

Bennett, Jim, and Kurt A. G. Schmidt. “Comparison of Phase Identification Methods Used in Oil Industry Flow Simulations.” Energy & Fuels 31, no. 4 (April 20, 2017): 3370-79. https://doi.org/10.1021/acs.energyfuels.6b02316.

Examples

CO2 vapor properties computed with Peng-Robinson at 300 K and 1 bar:

>>> vapor_score_Bennett_Schmidt(-1.1776172267959163e-05)
1.1776172267959163e-05

n-hexane liquid properties computed with Peng-Robinson at 300 K and 10 bar:

>>> vapor_score_Bennett_Schmidt(7.558572848883679e-06)
-7.558572848883679e-06

Sorting Phases

thermo.phase_identification.sort_phases(liquids, solids, constants, settings)

Identify and sort all phases given the provided parameters. This is not a thermodynamic concept; it is just a convinience method to make the results of the flash more consistent, because the flash algorithms don’t care about density or ordering the phases.

Parameters

liquidslist[Phase]

Liquids that were identified, [-]

solidslist[Phase]

Solids that were identified, [-]

constantsChemicalConstantsPackage

Constants used in the identification, [-]

correlationsPropertyCorrelationsPackage

Correlations used in the identification, [-]

settingsBulkSettings

Settings object controlling the phase sorting, [-]

Returns

liquidslist[Phase]

Liquids that were identified and sorted, [-]

solidslist[Phase]

Solids that were identified and sorted, [-]

Notes

The settings object uses the preferences liquid_sort_method, liquid_sort_prop, liquid_sort_cmps, liquid_sort_cmps_neg, and phase_sort_higher_first.