Solubility of solid does not follow consistent direction of temperature dependency

[sarangbhagwat]

Describe the bug The solubility of a triacetic acid lactone in water, calculated through SLE, first decreases and then increases with increase in temperature. Additionally, the changes in solubility are very sharp at certain points.

To Reproduce

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Aug 23 12:11:15 2020

Modified from the cornstover biorefinery constructed in Cortes-Peña et al., 2020,
with modification of fermentation system for 2,3-Butanediol instead of the original ethanol

[1] Cortes-Peña et al., BioSTEAM: A Fast and Flexible Platform for the Design, 
    Simulation, and Techno-Economic Analysis of Biorefineries under Uncertainty. 
    ACS Sustainable Chem. Eng. 2020, 8 (8), 3302–3310. 
    https://doi.org/10.1021/acssuschemeng.9b07040.

All units are explicitly defined here for transparency and easy reference

@author: sarangbhagwat
"""

# %%  

# =============================================================================
# Setup
# =============================================================================

import thermosteam as tmo
from thermosteam import functional as fn

__all__ = ('TAL_chemicals', 'chemical_groups', 'soluble_organics', 'combustibles')

# chems is the object containing all chemicals used in this biorefinery
chems = TAL_chemicals = tmo.Chemicals([])

# To keep track of which chemicals are available in the database and which
# are created from scratch
database_chemicals_dict = {}
copied_chemicals_dict = {}
defined_chemicals_dict = {}

def chemical_database(ID, phase=None, **kwargs):
    chemical = tmo.Chemical(ID, **kwargs)
    if phase:
        chemical.at_state(phase)
        chemical.phase_ref = phase
    chems.append(chemical)
    database_chemicals_dict[ID] = f'{ID}: {chemical.formula}/{chemical.MW}'
    return chemical

def chemical_copied(ID, ref_chemical, **data):
    chemical = ref_chemical.copy(ID)
    chems.append(chemical)
    for i, j in data.items(): setattr(chemical, i, j)
    copied_chemicals_dict[ID] = f'{ID}: {chemical.formula}/{chemical.MW}'
    return chemical

def chemical_defined(ID, **kwargs):
    chemical = tmo.Chemical.blank(ID, **kwargs)
    chems.append(chemical)
    defined_chemicals_dict[ID] = f'{ID}: {chemical.formula}/{chemical.MW}'
    return chemical

_cal2joule = 4.184

# %% 

# =============================================================================
# Create chemical objects available in database
# Some common names might not be pointing to the correct chemical,
# therefore more accurate ones were used (e.g. NitricOxide was used instead of NO),
# data from Humbird et al. unless otherwise noted
# =============================================================================

H2O = chemical_database('H2O')

# =============================================================================
# Gases
# =============================================================================

O2 = chemical_database('O2', phase='g', Hf=0)
N2 = chemical_database('N2', phase='g', Hf=0)
H2 = chemical_database('H2', phase='g')
CH4 = chemical_database('CH4', phase='g')
CarbonMonoxide = chemical_database('CarbonMonoxide', phase='g', 
                                        Hf=-26400*_cal2joule)
CO2 = chemical_database('CO2', phase='g')
NH3 = chemical_database('NH3', phase='g', Hf=-10963*_cal2joule)
NitricOxide = chemical_database('NitricOxide', phase='g')
NO2 = chemical_database('NO2', phase='g')
H2S = chemical_database('H2S', phase='g', Hf=-4927*_cal2joule)
SO2 = chemical_database('SO2', phase='g')

# =============================================================================
# Soluble inorganics
# =============================================================================

H2SO4 = chemical_database('H2SO4', phase='l')
HCl = chemical_copied('HCl', H2SO4) # HCl giving errors; doesn't change things much for TAL SA biorefinery
HNO3 = chemical_database('HNO3', phase='l', Hf=-41406*_cal2joule)
NaOH = chemical_database('NaOH', phase='l')
KOH = chemical_database('KOH', phase = 's')

KCl = chemical_database('KCl', phase = 's')
# Arggone National Lab active thermochemical tables, accessed 04/07/2020
# https://atct.anl.gov/Thermochemical%20Data/version%201.118/species/?species_number=928
AmmoniumHydroxide = chemical_database('AmmoniumHydroxide', phase='l', Hf=-336.719e3)
CalciumDihydroxide = chemical_database('CalciumDihydroxide',
                                        phase='s', Hf=-235522*_cal2joule)
AmmoniumSulfate = chemical_database('AmmoniumSulfate', phase='l',
                                    Hf=-288994*_cal2joule)
NaNO3 = chemical_database('NaNO3', phase='l', Hf=-118756*_cal2joule)
# NIST https://webbook.nist.gov/cgi/cbook.cgi?ID=C7757826&Mask=2, accessed 04/07/2020
Na2SO4 = chemical_database('Na2SO4', phase='l', Hf=-1356.38e3)
# CaSO4 = chemical_database('CaSO4', phase='s', Hf=-342531*_cal2joule)
# The default Perry 151 model has a crazy value, use another model instead
# CaSO4.Cn.move_up_model_priority('Constant', 0)
# 

# =============================================================================
# Soluble organic salts
# =============================================================================

Ethanol = chemical_database('Ethanol')
Acetate = chemical_database('Acetate', phase='l', Hf=-108992*_cal2joule)
AmmoniumAcetate = chemical_database('AmmoniumAcetate', phase='l', 
                                         Hf=-154701*_cal2joule)

# Hf from a Ph.D. dissertation (Lactic Acid Production from Agribusiness Waste Starch
# Fermentation with Lactobacillus Amylophilus and Its Cradle-To-Gate Life 
# Cycle Assessment as A Precursor to Poly-L-Lactide, by Andréanne Harbec)
# The dissertation cited Cable, P., & Sitnai, O. (1971). The Manufacture of 
# Lactic Acid by the Fermentation of Whey: a Design and Cost Study. 
# Commonwealth Scientific and Industrial Research Organization, Australia, 
# which was also cited by other studies, but the origianl source cannot be found online
CalciumLactate = chemical_database('CalciumLactate', phase='l',
                                   Hf=-1686.1e3)
# Hf from Lange's Handbook of Chemistry, 15th edn., Table 6.3, PDF page 631
CalciumAcetate = chemical_database('CalciumAcetate', phase='l', Hf=-1514.73e3)

# Solubility of CalciumSuccinate is 3.2 g/L in water as Ca2+ based on 
# Burgess and Drasdo, Polyhedron 1993, 12 (24), 2905–2911, which is 12.5 g/L as CaSA
# Baseline CalciumSuccinate is ~14 g/L in fermentation broth, thus assumes all 
# CalciumSuccinate in liquid phase
CalciumSuccinate = chemical_database('CalciumSuccinate', phase='l')

# =============================================================================
# Soluble organics
# =============================================================================

AceticAcid = chemical_database('AceticAcid')
Glucose = chemical_database('Glucose', phase = 'l')

# TAL = chemical_database('Triacetic acid lactone')

# SA = chemical_database('Sorbic acid')
# KSA = chemical_database('Potassium sorbate')
# BSA = chemical_database('Butyl sorbate')

IBA = chemical_database('Isobutyraldehyde')
DPHP = chemical_database('Dipotassium hydrogen phosphate', phase = 'l')

# This one is more consistent with others
# try: Glucose.Cn.l.move_up_model_priority('Dadgostar and Shaw (2011)', 0)
# except: Glucose.Cn.move_up_model_priority('Dadgostar and Shaw (2011)', 0)
GlucoseOligomer = chemical_defined('GlucoseOligomer', phase='l', formula='C6H10O5',
                                   Hf=-233200*_cal2joule)
GlucoseOligomer.copy_models_from(Glucose, ['Hvap', 'Psat', 'Cn', 'mu', 'kappa'])
Extract = chemical_copied('Extract', Glucose)

Xylose = chemical_database('Xylose')
Xylose.copy_models_from(Glucose, ['Hvap', 'Psat', 'mu'])
XyloseOligomer = chemical_defined('XyloseOligomer', phase='l', formula='C5H8O4',
                                  Hf=-182100*_cal2joule)
XyloseOligomer.copy_models_from(Xylose, ['Hvap', 'Psat', 'Cn', 'mu'])

Sucrose = chemical_database('Sucrose', phase='l')
Sucrose.Cn.move_up_model_priority('Dadgostar and Shaw (2011)', 0)
Cellobiose = chemical_database('Cellobiose', phase='l', Hf=-480900*_cal2joule)

Mannose = chemical_database('Mannose', phase='l', Hf=Glucose.Hf)
Mannose.copy_models_from(Glucose, ['Hvap', 'Psat', 'Cn', 'mu'])
MannoseOligomer = chemical_copied('MannoseOligomer', GlucoseOligomer)

Galactose = chemical_database('Galactose', phase='l', Hf=Glucose.Hf)
Galactose.copy_models_from(Glucose, ['Hvap', 'Psat', 'Cn','mu'])
GalactoseOligomer = chemical_copied('GalactoseOligomer', GlucoseOligomer)

Arabinose = chemical_database('Arabinose', phase='l', Hf=Xylose.Hf)
Arabinose.copy_models_from(Xylose, ['Hvap', 'Psat', 'mu'])
ArabinoseOligomer = chemical_copied('ArabinoseOligomer', XyloseOligomer)

SolubleLignin = chemical_database('SolubleLignin', search_ID='Vanillin', 
                                  phase='l', Hf=-108248*_cal2joule)
Protein = chemical_defined('Protein', phase='l', 
                           formula='CH1.57O0.31N0.29S0.007', 
                           Hf=-17618*_cal2joule)
Enzyme = chemical_defined('Enzyme', phase='l', 
                           formula='CH1.59O0.42N0.24S0.01', 
                           Hf=-17618*_cal2joule)
# Properties of fermentation microbes copied from Z_mobilis as in Humbird et al.
FermMicrobe = chemical_defined('FermMicrobe', phase='l',
                      formula='CH1.8O0.5N0.2', Hf=-31169.39*_cal2joule)
WWTsludge = chemical_defined('WWTsludge', phase='s', 
                             formula='CH1.64O0.39N0.23S0.0035', 
                             Hf=-23200.01*_cal2joule)

Furfural = chemical_database('Furfural')

Acetoin = chemical_database('3-Hydroxybutanone', phase = None, Hvap = 44.56*1000) # , V = 89.5e-6
Acetoin.copy_models_from(Furfural, ['Psat', 'Cn', 'mu', 'kappa', 'V'])
Acetoin.Tb = 145.4 + 273.15

Hexanol = chemical_database('Hexanol')
Heptane = chemical_database('Heptane')
Toluene = chemical_database('Toluene')
# Tb from chemspider(chemenu database)
# http://www.chemspider.com/Chemical-Structure.207215.html, accessed 04/07/2020
# https://www.chemenu.com/products/CM196167, accessed 04/07/2020
# Using Millipore Sigma's Pressure-Temperature Nomograph Interactive Tool at
# https://www.sigmaaldrich.com/chemistry/solvents/learning-center/nomograph.html,
# will give ~300°C at 760 mmHg if using the 115°C Tb at 1 mmHg (accessed 04/07/2020)
# Hfus from NIST, accessed 04/24/2020
# https://webbook.nist.gov/cgi/cbook.cgi?ID=C67470&Mask=4
HMF = chemical_database('HMF', Hf=-99677*_cal2joule, Tb=291.5+273.15, Hfus=19800)
HMF.copy_models_from(Furfural, ['V', 'Hvap', 'Psat', 'mu', 'kappa'])
HMF.Dortmund.update(chems.Furfural.Dortmund)

# TAL = chemical_copied('Triacetic acid lactone', HMF)
# SA = chemical_copied('Sorbic acid', HMF)
# KSA = chemical_copied('Potassium sorbate', HMF)
# BSA = chemical_copied('Butyl sorbate', HMF)

TAL = Triaceticacidlactone = chemical_database('Triacetic acid lactone')
TAL.copy_models_from(Furfural, ['Psat', 'Hvap']) # doesn't matter, since we never boil TAL
SA = Sorbicacid =  chemical_database('Sorbic acid')
KSA = Potassiumsorbate = chemical_database('Potassium sorbate')
BSA = Butylsorbate = chemical_database('Butyl sorbate')
HMTHP = chemical_copied('HMTHP', TAL)

TAL.Hfus = Furfural.Hfus/2.4 # !!! matters for solubility; update 
TAL.Tm = KSA.Tm = 185 + 273.15
TAL.Tb = KSA.Tb =  239.1 + 273.15

# https://pubchem.ncbi.nlm.nih.gov/compound/Sorbic-acid#section=Stability-Shelf-Life
SA.Tb = 228 + 273.15

BSA.Tm = 130 + 273.15
BSA.Tb = 226.5 + 273.15

VitaminA = chemical_database('VitaminA')
VitaminD2 = chemical_database('VitaminD2')
# Hfus from NIST, condensed phase, accessed 04/07/2020
# https://webbook.nist.gov/cgi/cbook.cgi?ID=C87990&Mask=4
Xylitol = chemical_database('Xylitol', phase='l', Hf=-243145*_cal2joule, Hfus=-1118.6e3)

# Hfus from NIST, accessed 04/07/2020
# https://webbook.nist.gov/cgi/cbook.cgi?ID=C50215&Mask=4
# LacticAcid = chemical_database('LacticAcid', Hfus=11.34e3)
LacticAcid = chemical_database('LacticAcid')
LacticAcid.Hfus = 11.34e3

SuccinicAcid = chemical_database('SuccinicAcid', phase_ref='s')

EthylAcetate = chemical_database('EthylAcetate')
# Hf from DIPPR value in Table 3 of Vatani et al., Int J Mol Sci 2007, 8 (5), 407–432
EthylLactate = chemical_database('EthylLactate', Hf=-695.08e3)

EthylSuccinate = chemical_database('EthylSuccinate')
# Cannot find data on Hf of CalciumSuccinate, estimate here assuming
# Hrxn for Ca(OH)2 and SA and Ca(OH)2 and LA are the same 
CalciumSuccinate.Hf = CalciumLactate.Hf + (SuccinicAcid.Hf-2*LacticAcid.Hf)

# =============================================================================
# Insoluble organics
# =============================================================================

Glucan = chemical_defined('Glucan', phase='s', formula='C6H10O5', Hf=-233200*_cal2joule)
Glucan.copy_models_from(Glucose, ['Cn'])
Mannan = chemical_copied('Mannan', Glucan)
Galactan = chemical_copied('Galactan', Glucan)

Xylan = chemical_defined('Xylan', phase='s', formula='C5H8O4', Hf=-182100*_cal2joule)
Xylan.copy_models_from(Xylose, ['Cn'])
Arabinan = chemical_copied('Arabinan', Xylan)

Lignin = chemical_database('Lignin', phase='s')
# Hf scaled based on vanillin
Lignin.Hf = -108248*_cal2joule/tmo.Chemical('Vanillin').MW*Lignin.MW

# =============================================================================
# Insoluble inorganics
# =============================================================================

# Holmes, Trans. Faraday Soc. 1962, 58 (0), 1916–1925, abstract
# This is for auto-population of combustion reactions
P4O10 = chemical_database('P4O10', phase='s', Hf=-713.2*_cal2joule)
Ash = chemical_database('Ash', search_ID='CaO', phase='s', Hf=-151688*_cal2joule,
                        HHV=0, LHV=0)
# This is to copy the solid state of Xylose,
# cannot directly use Xylose as Xylose is locked at liquid state now
Tar = chemical_copied('Tar', Xylose, phase_ref='s')

# =============================================================================
# Mixtures
# =============================================================================

# CSL is modeled as 50% water, 25% protein, and 25% lactic acid in Humbird et al.,
# did not model separately as only one price is given
CSL = chemical_defined('CSL', phase='l', formula='CH2.8925O1.3275N0.0725S0.00175', 
                      Hf=Protein.Hf/4+H2O.Hf/2+LacticAcid.Hf/4)

# Boiler chemicals includes amine, ammonia, and phosphate,
# did not model separately as composition unavailable and only one price is given
BoilerChems = chemical_database('BoilerChems', search_ID='DiammoniumPhosphate',
                                phase='l', Hf=0, HHV=0, LHV=0)

# =============================================================================
# Filler
# =============================================================================

BaghouseBag = chemical_defined('BaghouseBag', phase='s', MW=1, Hf=0, HHV=0, LHV=0)
BaghouseBag.Cn.add_model(0)
CoolingTowerChems = chemical_copied('CoolingTowerChems', BaghouseBag)

# =============================================================================
# Not currently in use
# =============================================================================

DAP = chemical_database('DAP', search_ID='DiammoniumPhosphate',
                             phase='l', Hf= -283996*_cal2joule)
Methanol = chemical_database('Methanol')
MethylAcetate = chemical_database('MethylAcetate')
Denaturant = chemical_database('Denaturant', search_ID='n-Heptane')
DenaturedEnzyme = chemical_copied('DenaturedEnzyme', Enzyme)

# Hf from DIPPR value in Table 3 of Vatani et al., Int J Mol Sci 2007, 8 (5), 407–432
MethylLactate = chemical_database('MethylLactate', Hf=-643.1e3)
FermMicrobeXyl = chemical_copied('FermMicrobeXyl', FermMicrobe)

# %% 

# =============================================================================
# Group chemicals
# =============================================================================

#!!! Sarang please review and update this dict, it affects simulation
chemical_groups = dict(
    OtherSugars = ('Arabinose', 'Mannose', 'Galactose', 'Cellobiose', 'Sucrose'),
    SugarOligomers = ('GlucoseOligomer', 'XyloseOligomer', 'GalactoseOligomer',
                      'ArabinoseOligomer', 'MannoseOligomer'),
    OrganicSolubleSolids = ('AmmoniumAcetate', 'SolubleLignin', 'Extract', 'CSL',
                            # 'Triacetic acid lactone',
                            'Sorbic acid', 'HMTHP',
                            'Potassium sorbate', 'Butyl sorbate', 'VitaminA', 'VitaminD2'),
                            # 'LacticAcid', 'CalciumLactate', 'CalciumAcetate',
                            # 'EthylLactate', 'EthylAcetate', 'SuccinicAcid',
                            # 'CalciumSuccinate', 'EthylSuccinate', 
                            # 'Methanol', 'MethylLactate', 'MethylAcetate'),
    InorganicSolubleSolids = ('AmmoniumSulfate', 'NaOH', 'HNO3', 'NaNO3',
                              # 'DAP',
                              'BoilerChems', 'Na2SO4', 'AmmoniumHydroxide'),
    Furfurals = ('Furfural', 'HMF'),
    #!!! I suspect you want to add some chemicals here
    OtherOrganics = ('Denaturant', 'Xylitol'),
    COSOxNOxH2S = ('NitricOxide', 'NO2', 'SO2', 'CarbonMonoxide', 'H2S'),
    Proteins = ('Protein', 'Enzyme', 'DenaturedEnzyme'),
    CellMass = ('WWTsludge', 'FermMicrobe'),
                # 'FermMicrobeXyl'),
    # Theoretically P4O10 should be soluble, but it's the product of the
    # auto-populated combusion reactions so should in solid phase, however no
    # P4O10 will be generated in the system as no P-containing chemicals 
    # are included in "combustibles"
    OtherInsolubleSolids = ('Tar', 'Ash', 'CalciumDihydroxide', 'P4O10',
                            'BaghouseBag', 'CoolingTowerChems'),
    OtherStructuralCarbohydrates = ('Glucan', 'Xylan', 'Lignin', 'Arabinan', 
                                    'Mannan', 'Galactan'),
    SeparatelyListedOrganics = ('Ethanol', 'Glucose', 'Xylose', 'AceticAcid',
                                'Acetate', 'Lignin'),
    SpearatedlyListedOthers = ('H2O', 'NH3', 'H2SO4', 'CO2', 'CH4', 'O2', 'N2')
    )

# This group is needed in the system.py module
soluble_groups = ('OtherSugars', 'SugarOligomers', 'OrganicSolubleSolids',
                  'Furfurals', 'OtherOrganics', 'Proteins', 'CellMass',
                  'SeparatelyListedOrganics')
soluble_organics = list(sum([chemical_groups[i] for i in soluble_groups], ()))
soluble_organics.remove('WWTsludge')

solubles = tuple(soluble_organics) + chemical_groups['InorganicSolubleSolids'] + ('H2SO4',)

insoluble_groups = ('OtherInsolubleSolids', 'OtherStructuralCarbohydrates')
insolubles = sum([chemical_groups[i] for i in insoluble_groups], ('WWTsludge',))

# This group is needed in the system.py module
combustibles = soluble_organics + list(chemical_groups['OtherStructuralCarbohydrates'])
# combustibles.remove('CalciumLactate')
# combustibles.remove('CalciumAcetate')
combustibles.extend(['WWTsludge','NH3', 'NitricOxide', 'CarbonMonoxide', 'H2S', 'CH4'])

# Chemicals that will be modeled in Distallation/Flash units,
# list is in ascending order of Tb,
# Xylitol is not included due to high Tm and Tb thus will stay in liquid phase

# phase_change_chemicals = ['Methanol', 'Ethanol', 'H2O', 'EthylAcetate', 'Denaturant',
#                           'AceticAcid', 'MethylAcetate', 'MethylLactate',
#                           'EthylLactate', 'Furfural', 'SuccinicAcid', 'LacticAcid', 'HMF']

#!!! Sarang please review and update this, I'm not sure what chemicals are used
# in the biorefinery, getting rid of unused chemicals (i.e., exclude them from chems)
# should help reduce simulation time
phase_change_chemicals = ['Methanol', 'Ethanol', 'H2O', 'EthylAcetate', 'Denaturant',
                          'AceticAcid', 'MethylAcetate', 'MethylLactate',
                          'EthylLactate', 'Furfural', 'EthylSuccinate',
                          'SuccinicAcid', 'LacticAcid', 'HMF']

for chem in chems:
    if chem.ID in phase_change_chemicals: pass
    elif chem.locked_state: pass
    else: 
        # Set phase_ref to avoid missing model errors
        if chem.phase_ref == 'g':
            chem.at_state('g')
        if chem.ID in solubles:
            chem.phase_ref = 'l'
            chem.at_state('l')
        if chem.ID in insolubles:
            chem.phase_ref = 's'
            chem.at_state('s')

# %% 

# =============================================================================
# Set assumptions/estimations for missing properties
# =============================================================================

# Set chemical heat capacity
# Cp of biomass (1.25 J/g/K) from Leow et al., Green Chemistry 2015, 17 (6), 3584–3599
for chemical in (CSL, Protein, Enzyme, WWTsludge, 
                 DenaturedEnzyme, FermMicrobe, FermMicrobeXyl):
    chemical.Cn.add_model(1.25*chemical.MW)

# Set chemical molar volume following assumptions in lipidcane biorefinery,
# assume densities for solulables and insolubles to be 1e5 and 1540 kg/m3, respectively
# !!! This has significant impacts on results, need to double-check accuracy
def set_rho(chemical, rho):       
    V = fn.rho_to_V(rho, chemical.MW)
    chemical.V.add_model(V, top_priority=True)

for chemical in chems:
    if chemical.ID in phase_change_chemicals: pass
    elif chemical.ID in solubles: set_rho(chemical, 1e5)
    elif chemical.ID in insolubles: set_rho(chemical, 1540)

# The Lakshmi Prasad model gives negative kappa values for some chemicals
for chemical in chems:
    if chemical.locked_state:
        try: chemical.kappa.move_up_model_priority('Lakshmi Prasad', -1)
        except: pass

# Default missing properties of chemicals to those of water,
for chemical in chems: chemical.default()

# %%

# Though set_thermo will first compile the Chemicals object,
# compile beforehand is easier to debug because of the helpful error message
chems.compile()
tmo.settings.set_thermo(chems)
chems.set_synonym('CalciumDihydroxide', 'Lime')
chems.set_synonym('3-Hydroxybutanone', 'Acetoin')
chems.set_synonym('Triacetic acid lactone', 'TAL')
chems.set_synonym('Triacetic acid lactone', 'Triaceticacidlactone')
chems.set_synonym('Sorbic acid', 'SA')
chems.set_synonym('Sorbic acid', 'Sorbicacid')
chems.set_synonym('Potassium sorbate', 'KSA')
chems.set_synonym('Potassium sorbate', 'Potassiumsorbate')
chems.set_synonym('Butyl sorbate', 'BSA')
chems.set_synonym('Butyl sorbate', 'Butylsorbate')
chems.set_synonym('Dipotassium hydrogen phosphate', 'DPHP')
chems.set_synonym('H2O', 'Water')
chems.set_synonym('H2SO4', 'SulfuricAcid')
chems.set_synonym('NH3', 'Ammonia')
chems.set_synonym('AmmoniumSulfate', 'NH4SO4')
chems.set_synonym('Denaturant', 'Octane')
chems.set_synonym('CO2', 'CarbonDioxide')
chems.set_synonym('CarbonMonoxide', 'CO')
chems.set_synonym('NitricOxide', 'NO')
# chems.set_synonym('CaSO4', 'Gypsum')
chems.set_synonym('P4O10', 'PhosphorusPentoxide')
chems.set_synonym('Na2SO4', 'SodiumSulfate')
chems.set_synonym('AmmoniumHydroxide', 'NH4OH')
chems.set_synonym('Isobutyraldehyde', 'IBA')

# %%

# from TAL.utils import get_chemical_properties 
# get_chemical_properties(chems, 400, 101325, output=True)

>>> from thermosteam import indexer, equilibrium, settings
>>> imass = indexer.MolarFlowIndexer(l=[('Triacetic acid lactone', 304), ('Water', 1000)], phases=('s', 'l'))
>>> sle = equilibrium.SLE(imass)

>>> sle('Triacetic acid lactone', T=193.15)
>>> sle

>>> sle('Triacetic acid lactone', T=293.15)
>>> sle

>>> sle('Triacetic acid lactone', T=298.15)
>>> sle

>>> sle('Triacetic acid lactone', T=450)
>>> sle

Expected behavior If the heat given off in the dissolving reaction is less than the heat required to break apart the solid, the net dissolving reaction is endothermic and solubility increases with temperature; if the opposite is true, solubility decreases with temperature. I don't think the trend changes at different temperature ranges.

Actual behavior SLE(imol=MolarFlowIndexer(phases=('l', 's'), l=[('H2O', 1000), ('Triacetic acid lactone', 304)]), thermal_condition=ThermalCondition(T=193.15, P=101325))

SLE(imol=MolarFlowIndexer(phases=('l', 's'), l=[('H2O', 1000), ('Triacetic acid lactone', 304)]), thermal_condition=ThermalCondition(T=293.15, P=101325))

SLE(imol=MolarFlowIndexer( l=[('H2O', 1000), ('Triacetic acid lactone', 8.457)], s=[('Triacetic acid lactone', 295.5)]), thermal_condition=ThermalCondition(T=298.15, P=101325))

SLE(imol=MolarFlowIndexer(phases=('l', 's'), l=[('H2O', 1000), ('Triacetic acid lactone', 304)]), thermal_condition=ThermalCondition(T=450.00, P=101325))

Version Latest github master version as of 8:56 PM, 11/7/2020.

[yoelcortes]

Thanks for asking! This is actually a result of activity coefficients. At low temperatures, non-idealities become less significant and activity coefficients approach 1. So this increases solubility as temperatures decrease. You might want to double check with experimental data to verify the accuracy of this prediction.

Also, a couple of notes:

• Seems like you are running the SLE algorithm with huge amounts of TAL and just a little water (note that these are in moles): 300 mol TAL and 1000 mol water is equivalent to 37833.012 g TAL and 18015.28 g Water. I went ahead and reduced the TAL to 1/10th in the example.

*If you go at too low temperatures (e.g 193 K), chemical properties may be inaccurate. So I evaluate starting T=283 in the example.

from thermosteam import indexer, equilibrium, settings
imol = indexer.MolarFlowIndexer(l=[('Triacetic acid lactone', 30), ('Water', 1000)], phases=('s', 'l'))
sle = equilibrium.SLE(imol)
def get_solubility(T):
    sle('Triacetic acid lactone', T=T)
    return sle.imol['l', 'Triacetic acid lactone'] / sle.imol['Triacetic acid lactone']
Ts = [283 + 10 * i for i in range(30)]
print('T' + 3*' ' + 'solubility')
for T in Ts:
    print(T, get_solubility(T))

T   solubility
283 0.4519957177476145
293 0.3248377690872403
303 0.24983476346190198
313 0.2010369285390943
323 0.16745507219739286
333 0.14351998679706587
343 0.12609088766787183
353 0.11326822751010779
363 0.1038478888802174
373 0.09704370788562734
383 0.09233606895371384
393 0.08938530729531985
403 0.08798112729266495
413 0.08801372355974119
423 0.08945943329423467
433 0.09237777059012608
443 0.09691954631892778
453 0.10334869761343447
463 0.11208482888283494
473 0.12378197490822472
483 0.13947863538336552
493 0.16088988099137885
503 0.19112377518388746
513 0.23650692458862585
523 0.31321600034380453
533 0.4945337786230477
543 1.0
553 1.0
563 1.0
573 1.0