(2024) 18:136
Gondoghdi et al. BMC Chemistry
https://doi.org/10.1186/s13065-024-01243-x

BMC Chemistry

RESEARCH

Open Access

Effect of protic surfactant ionic liquids
based on ethanolamines on solubilityof acetaminophen at several temperatures:
measurement and thermodynamic correlation
Parisa Akbarzadeh Gondoghdi1, Hemayat Shekaari1*, Masumeh Mokhtarpour1,2,Mirhesam Miraghazadeh Sardroud1, Ramin Afkari1 and Mohammad Khorsandi1

Abstract
Absolute qualifications with the application of protic ionic liquids (PILs) and a recognition of the numerous thermophysical features of these materials are required in various processes. Due to the wonderful applications of thesecompounds and their high potential in the chemical and pharmaceutical industries, there is a particular eagerness
to utilize these PILs in drug solubility and delivery area. The aim of this investigation was to explore the solubilityof the acetaminophen (ACP) in three PILs base on ethanolamine laurate [(2-hydroxyethylammonium laurate [MEA]La), (bis(2-hydroxyethyl)ammonium laurate [DEA]La), and ( tris(2-hydroxyethyl)ammonium laurate [TEA]La)]. The shakeflask method has been employed in this study, and the conditions were set at T = (298.15–313.15) K and atmosphericpressure. Moreover, the experimental solubility data was correlated using a variety of empirical and thermodynamic
models, encompassing e-NRTL and Wilson activity coefficient models and the empirical models such as Van’t HoffJouyban-Acree and Modified Apelblat-Jouyban-Acree. Their performance for the system containing [MEA]La follow
the trend for activity coefficient models and empirical respectively: the Wilson > e-NRTL and Modified Apelblat–Jouyban–Acree > Van’t Hoff–Jouyban–Acree. On the other hand, [DEA]La and [TEA]La PILs followed slightly different trend
for activity coefficient models and empirical respectively: the Wilson > e-NRTL and Van’t Hoff–uyban–Acree > Modified
Apelblat–Jouyban–Acree. The Van’t Hoff and Gibbs equations were used to determine the thermodynamic propertiesof dissolution in the studied systems.
Keywords Solubility, Acetaminophen, Protic ionic liquids, Ethanolamine, Modelling, Lauric acid
Introduction
Drug formulation is a crucial factor for an appropriate
drug dosage. Numerous studies have been performed toenhance the solubility of various active pharmaceutical*Correspondence:
Hemayat Shekaari
hemayatt@yahoo.com
1
Department of Physical Chemistry, University of Tabriz, Tabriz, Iran2
Research Center for Bioscience and Biotechnology, University of Tabriz,Tabriz, Irancomponents in order to produce homogenous pharmaceutical dosage forms, as many pharmaceuticals have low
water solubility. Thus, a wide range of techniques havebeen implemented, involving pH modification, co-solvency, cyclodextrins, solid dispersions, and complexation[1]. Among these methods, co-solvency is widely used
due to its convenience and low cost, wherein the solvent
power of the primary solvent is increased by adding atiny amount of a secondary solvent [2].
The choice of solvents is crucial to control possible
chemical reactions and for the purification process and© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​
mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Gondoghdi et al. BMC Chemistry(2024) 18:136

the final drug formulation. Despite the fact that the pharmaceutical industry frequently employs classic organic
solvents including methanol, alcohols, chloroform, andethyl acetate, overuse of these volatile and dangerous
solvents can affect the environment, and there is risingpressure to minimize their usage. To address this issue,
scientists are working to replace these organic solventswith non-volatile more environmentally friendly systems, such as proticionic liquids (PILs) and low-melting
mixtures (LMMs) [3]. Ionic liquids are appealing as sustainable solvents since they present lower flammability and vapor pressure than volatile organic compounds(VOCs) and can be formulated to be biodegradable
and to present lower toxicity [4, 5]. In particular, protic
ionic liquids (PILs) which are generated by the Brønstedacid–base reaction (Fig. 1), can participate in appropriate chemical interactions, encompassing proton donation and acceptance, which might affect the solubilityof drugs. Furthermore, PILs have a lot of potential forindustrial applications due to their simple manufacturing and frequently involve inexpensive or even renewable
reactants. The properties of PILs, including solubility, canbe tailored by a careful choice of the proton acceptor andproton donor and is an important task when designing
their properties for drug formulations. Additionally, Considering they are inexpensive and environmentally safe,
ethanol-amine based protic ionic liquids have attracted a
lot of research. Numerous studies have been conductedon these materials with the goal of enhancing medicinal products. As a result, new medication formulations
and delivery methods using these PILs have been found.
These substances are noteworthy for having non-toxic
qualities, which makes them appropriate for use as cryoprotectant agents for mammalian cell lines [6, 7].
Lauric acid, is an edible saturated fatty acid that ispresent in a variety of plants life, encompassing coconut oil and other dietary supplements [8–10]. On theother hand, alkanolamines, including mono-, di-,and tri-ethanolamine, can be discovered in phospholipid biological membranes naturally and are frequently
employed as “scrubbers” in factories to remove acidic
impurities as hydrogen sulfide or carbon dioxide. They

Fig. 1 The 2D- molecular ctructure of the ACP

Page 2 of 15

may additionally act as the foundation material for PIL
production. Due to their capacity to function as a thickening, emulsifying, and detergent agents in various
formulations, their combination with fatty acids yields
surfactants, which are employed in the formulation ofhealth care products and cosmetics [11]. PILS have also
shown their ability to improve drug absorption by altering their processing and physical characteristics, particularly, solubility and controlled release of the drug.
Acetaminophen (ACP), is a widely used drug that plays
an important role in the pharmaceutical industry as
it is a prominent painkiller and antipyretic in current
treatments [12].
The current investigation builds on our previous
work [13–17], which explored the use of green solvents,
including PILs as co-solvents. In this work, we focusedon understanding how protic ILs based on alkanolamines and lauric acid affects the solubility of ACP. In
particular, three different PILs, namely ((2-hydroxyethylammonium laurate [MEA]La), (bis(2-hydroxyethyl)ammonium laurate [DEA]La), and [tris(2-hydroxyethyl)ammonium laurate [TEA]La)] have been used to evaluate their impact on ACP solubility at different temperatures and various PIL concentrations. Furthermore,
the solubility data using several thermodynamic models, the activity coefficient and emprical soulubility
models including the Van’t Hoff-Jouyban-Acree modeland Modified Apelblat-Jouyban-Acree model [18, 19].
Ultimately, the apparent thermodynamic properties
of ACP dissolution in the systems under investigation
have been determined by utilizing the Van’t Hoff andGibbs equations. This study contributes to the ongoing research on green solvents and provides valuable
insights for the pharmaceutical industry to explore
alternative solvents that are environmentally friendly
and sustainable.

Material and methods
Materials

The chemicals were purchased from the following companies: ethanol from Sigma-Aldrich, lauric acid from
Merck Co. the monoethanolamine (2-hydroxyethylamine,
MEA), diethanolamine (bis(2-hydroxyethylamine), DEA),
triethanolamine (tris(2-hydroxyethylamine),TEA) from
Shazand pterochemical Co. and acetaminophen (ACP)from Dana. The each one of the chemicals which had apurity weight fraction greater than 0.99 in mass percent.
The solutions were prepared using freshly doubly distilled deionized water. The relevant information about
the chemicals used in the study, including chemical
name, their sources, CAS numbers, mass fraction (purities) are provided in Table 1.

Gondoghdi et al. BMC Chemistry(2024) 18:136

Page 3 of 15

Table 1 The comprehensive description of the chemicals name, provenance, CAS number, purity, and structure
Chemical name

Provenance

CAS NoMass fraction(apurity)

Acetaminophen (ACP)

Merck

103-90-2> 0.99Monoethanolamine (2-hydroxyethylamine, MEA)

Shazand petrochem

141-43-5> 0.99Structurecc
Diethanolamine (Bis-2-hydroxyethylamine, DEA)

Shazand petrochem

111-42-2> 0.98.5

Triethanolamine (Tris-2-hydroxyethylammonium, TEA)

Shazand petrochem

102-71-6> 0.99Lauric acidMerck

143-07-7> 0.98a

The purities were provided by the suppliersProtic ionic liquid synthesis

The present study involved the synthesis and purification of protic ionic liquids (PILs) using a neutralization
method. Encompassing MEA, DEA and TEA with lauricacid were used as starting materials to synthesize PILs.
The synthesis process involved stirring the ethanolamines in a three-neck glass flask, then gradually adding
lauric acid using a dropping funnel while stirring at room
temperature. In order to dry the synthesized PILs, a vacuum pump was employed for a duration of 3 h with up
to 1 kPa. This process was undertaken to ensure purityof the resulting product and maintain its quality andeffectiveness. The shortened version of these processes
has been presented in Table 2. These procedures ultimately lead us to achieve a high yield of about > 98%.

The aforementioned method offers a simple way to create PILs with specifc features for a variety of applications[20]. To determine the water contents of the synthesized
PILs, the Karl − Fisher titration technique (method TitroLine KF) was applied.
Solubility determination

A calibration curve for ACP was initially generated before
the solubility amounts were determined (Fig. 2). The calibration curve for the experiment was obtained by dissolving precise amounts of ACP in a solution of ethanol anddistilled deionized water using a double-beam UV–vis
spectrometer (T80 Japan) [21]. The experimental solubility results were determined using a variety of techniques,
including the shake-flask method [22]. Aqueous binary

Table 2 Physicochemical properties of the protic ionic liquids employed in this study at 298.15 K and 866 h
­ Paa
PILs

MPIL (g∙mol−1)

Purification method

Analysis method

Water
content(ppm)

2-hydroxyethylammonium laurate[2-HEA]Lau]

261.40Extraction/filtration/rotary evaporator

FT-IR-H NMR

179

bis(2-hydroxyethyl)ammonium laurate[2-HDEA]Lau]

305.46Extraction/filtration/rotary evaporator

FT-IR-H NMR

185

tris(2-hydroxyethyl)ammonium laurate[2-HTEA]Lau]

349.51

Extraction/filtration/rotary evaporator

FT-IR-H NMR

198

a

Standard uncertainty for u(T) = 0.1 K and u(P) = 10 hPa

Gondoghdi et al. BMC Chemistry(2024) 18:136

Page 4 of 15

theory. The activity of the solute in the saturated solution
has to exceed the activity of the solute in its pure solidstate form in order to determine the solubility of a solutein a solution at a specific temperature. Equation 2 statesthat this could be accomplished by employing a solid–liquid equilibrium (SLE) framework to control the solute’s
activity in the saturated solution [45]:

1.4
1.2

R² = 0.9955

Absorbance

1
0.8
0.6
0.4
0.2
0

0

0.000005

0.00001

0.000015

0.00002

�fus H 1
1
(
− )
R
Tm1
T
 T

(2)
1
1 T �CP1−dT
�CP1 dT +RT Tm1
R Tm1 Tln x1 = − ln γ1 +ACP Mass Fraction

Fig. 2 The calibration curve for acetaminophen (ACP)

mixtures based on PILs have been made utilizing an analytical balance with a ­10–4 g precision for determining
the solubility results. Glass vials with a specific amountof water + PILs were filled with the extra acetaminophen.
Following that, the samples were combined for 3 h andleft for three days in a water bath thermostat (ED, Julabo
Co., Germany) with temperature control and an uncertainty of 0.01 K. To separate the liquid and solid phases,
a Hettich D-7200 centrifuge was employed (with 4000
RPM at room temperature at 10 min). An ethanol + water
solution was applied to dilute the liquid phase after thesaturated solutions were filtered through a 0.22 m PTFE
filter. Subsequently, the drug concentration in the solutions was ascertained using a calibration curve and a
UV–vis spectrometer at 243 nm [23].
The amount of drug that dissolves in a mixture of waterand the drug, a mixture of water and ACP, or a mixture ofwater and protic ionic liquids (PILs) was calculated using
Eq. 1 [24, 25]:
w1
M1
w3
w2
M 1 + M 2 + M3

x1 = w1(1)

where Mi and Wi, respectively, indicate the weight fraction and molar mass of each component (i) in systems.
Solubility models

Thermodynamic models are important for determining
the solubility of drugs in different solvents. This is a critical parameter in the pharmaceutical industry, as it affects
the delivery and absorption of drugs. Thermodynamic
models use equations of equilibrium to calculate thesolubility of a drug in different solvents. One importantfactor in these models is the excess molar Gibbs energy­(Gex) [26]. The ­Gex is a measure of the non-ideal behavior of a mixture of solvents. Another important factor inthermodynamic models is local composition theory. The
short-range order and nonrandom molecule orientations
caused by changes in molecular size are explained by thiswhere T and Tm1 are the experimental and melting temperatures, respectively, and R is the gas constant; fus H ,γ1 and CP1 relates to the enthalpy of fusion (26.0 KJol.
Mol −1[27]), activity coefficient, and the variation inmolar heat capacity between ACP’s melting and solidstates. Subsequently suitable simplification [28], the simplified equation became as follows:

ln x1 =

�fus H 1
1(− ) − ln γ1
R
Tm T

(3)

The melting temperature (Tm), activity coefficient (γ),
and enthalpy of fusion (ΔHfus) of ACP must be known inorder to assess its solubility in various solvents. This project correlated the experimental solubility data for ACP­(x1), which means that it found a mathematical relationship between the solubility of ACP and the three factors
listed above. To discribe the solubility data, activity coefficient-based models used to describe the solubility databy combining the evaluated information from Eq. 3.
The molar excess Gibbs energy ­(Gex) is shown to be thesum of two contributions in order to try to extend thee-NRTL and Wilson models for systems with many components that include electrolytes in the aqueous solution:

G ex∗
G ex∗,LR
G ex∗,SR
=
+
RT
RT
RT

(4)

where the asymmetric convention is indicated by thesuperscript ex*, short- and long-range interactions areindicated by the letters SR and LR, respectively. Pitzer[29], developed the expanded Pitzer-Debye Hückel (Gex)
PDH model, which may be employed to model interactions with long-range terms. Short-range interactions
have also been modeled utilizing other models, including
Wilson and e-NRTL.
The e‑NRTL model

A novel method for determining the activity coefficientof each species in a solution was developed by Chen

Gondoghdi et al. BMC Chemistry(2024) 18:136

Page 5 of 15(1982), Chen and Evans (1986), and it was based on theelectrolyte Nonrandom Two-Liquid (e-NRTL) model [30,31].
The Pitzer–Debye–Hückel contribution, which takes
into consideration long-range interactions between ions,and the Nonrandom Two-Liquid (e-NRTL) model contribution, which takes into account short-range interactions
between all species, add up to the activity coefficient.
Using the Nonrandom Two-Liquid (e-NRTL) model, one
can utilize Eqs. 5 and 6 to determine the activity coefficient of species γ1 in a solution:ln γi =

τij Gij xj

j=1
m
�

+
Gli xl

i=1



m
�

m
�

xr τrj Grj
xj Gij τij − r=1

m
m


�
�
j=1
Glj xlGlj xl
l=1

l=1

(6)
Gij = exp(−αij τij ),where Gij were definition as
τii = τjj = 0 and αij = αji.
Furthermore, calculating the binary interaction parameter (τij ) has been done by Eq. 7:

τij =A different framework that can be utilized to clarify the
relationship between the absolute temperature and thenatural logarithm of a solute’s mole fraction solubility ina solution is the Van’t Hoff equation:
Here is a more detailed explanation of the key terms:

ln xT = A +gij − gii
RT(7)

the gij is an energy parameter characteristic of the i–jinteractions.
The Wilson model

The Wilson model is a thermodynamic model which
can be implemented for calculating activity coefficientsin solutions. This framework considers both temperature and solution composition during evaluating activity
coefficients:nn�ki xkln γi = 1 − ln((�ij xj ) −
( n
))

j=1
k=1
(�kj xj )

(8)

j=1

where the binary interaction parameter, ij , is a measureof how the interactions between two different molecules
in a mixture differ from the ideal interactions. It is basedon the characteristic energy, , and molar volumes, υ , ofthe solute and solvents. Equation 9 can be used to calculate the binary interaction parameter:ij − ii
υj
exp −
�ij =
(9)
υi
RT

B
T

(10)

w2 w3 B3B2
) + w3 (A3 +)+Ji (w2 − w3 )iTTT2log X1,T = w2 (A2 +

i=0

(5)

ln(γi∗ ) = ln(γi∗PDH ) + ln(γi∗NRTL )m�

Van’t Hoff—Jouyban—Acree model

he model parameters are A2,B2,A3, B3,and Ji.

(11)

Modified Apelblat–Jouyban–Acree model

The relationship between temperature and solubility
might be investigated with the semi-empirical Modified
Apelblat model [32, 33]:

ln xT = A +B+ C ln T
T(12)

The solubility of ACP in particular mixed solvents at
various temperatures might be assessed with the Modified Apelblat-Jouyban-Acree model, a thermodynamic
model. It is based on the mole fraction solubility of
ACP in the selected mixed solvents at temperature T,
which is indicated by x­ T, and the three equation parameters, A, B, and C [34]

B2
+ C2 ln T )T
B3+ C3 ln T )+ w3 (A3 +T
2w2 w 3 
Ji (w2 − w3 )i+T

log X1,T =w2 (A2 +

(13)

i=0

The activity coefficients of the experimental and calexp
culated states are denoted by ln γi and ln γical , respectively, and the number of experimental points could
be represented by N. The relative deviation percent(ARD%) for the models already outlined may have been
calculated utilizing Eq. 14 to determine the discrepancy
between the calculated and experimental solubility
data:

ARD% = 100(N xexp −xcal 

i
i

i=1



 exp 
xi 

N

)

(14)

Gondoghdi et al. BMC Chemistry(2024) 18:136

Page 6 of 15

Thermodynamic dissolution properties

The Gibbs and van der Hoff equations were used todetermine the thermodynamic parameters of dissolution.
A mean harmonic temperature of 305.55 K was utilized
for the calculations, which were based on a temperature range of 298.15 K to 313.15 K [35]. The ACP stando
ard molar enthalpy of dissolution,Hsoln
was obtainedby Eq. 15 [36–38]:o�Hsoln = −R(∂ ln x1 )P∂(1 T )

(15)

∂ ln x1)P1∂( T − 1 Thm )(16)

where T is the absolute temperature and R (8.314 J∙K1∙mol-1) is the universal gas constant [39] The mole
fraction of ACP was indicated byx1. On the otherohand, Hsocan be calculated by plotting lnx1 versus

 ln
1 −1
T
Thm which is called van’t Hoff plot:o�Hsoln = −R(oGsoln = −RThm × intercept(17)

By solving Eqs. 16 and 17, we can determine the valuesooof the parameters Hsoln and Gso ln . The standard molaroentropy of dissolution, Sso ln , can then be calculatedusing the following equation [40–42]:
o
Sso
ln =

o
o
Hso
ln − Gso ln
Thm

(18)

The relative contributions of entropy and enthalpy to
the standard molar Gibbs free energy of dissolution of
ACP are explained by Eqs. 17, 18, as shown by the symbols ξH and ξTS , respectively [43]:�H o soln %ξH = (19)o  + T �S o  × 100
�Hso
ln
so ln



T �S o soln
 %ξTS = �H o  + T �S o
so ln

so ln

 × 100Characterization of the prepared PILs
FT‑IR spectrum of the synthesized PILs

(20)

Figures S1 − S3 presents the FT-IR spectra of three synthesized PILs (protic ionic liquids): 2 hydroxyethylammonium laurate [MEA]La, bis- 2 hydroxyethylammonium
laurate [DEA]La, and tris- 2 hydroxyethylammonium laurate [TEA]La. Each PIL has its specifc set of FT-IR index
peaks, which are listed as follows. For 2 hydroxyethylammonium laurate [MEA]La, the FT-IR peaks (KBr, c­ m−1)

are observed at 530.81, 593.21, 720.25, 869.95, 924.69,
1013.10, 1047.01, 1077.01, 1135.19, 1315.58, 1413.11,
1465.85, 1548.57, 1644.86, 1720.87, 2851.75, 2921.02,
and 3295.55. For bis-2 hydroxyethylammonium laurate [DEA]La, the FT-IR peaks (KBr, c­ m−1) appeared at566.69, 720.48, 806.46, 965.67, 1013.10, 1047.01, 1064.36,
1407.65, 1463.61, 1560.29, 1620.98, 1724.41, 2851.72,
2921.58, and 3353.54. For tris-2-hydroxyethylammonium laurate [TEA]La, the FT-IR peaks (KBr, c­m−1)
are observed at 531.04, 566.69, 718.37, 915.24, 1031.92,
1082.54, 1408.08, 1468.05, 1562.47, 2852.12, 2920.76,
3151.51, and 3357.97. Comparing Figures S1 − S3 reveals
some signifcant features. The peaks at 566 and 719 ­cm−1
indicate the presence of the COO − functional group.
Additionally, the strong characteristic peaks at 2849 and2920 ­cm−1 correspond to the antisymmetric and symmetric stretching vibrations of the CH2 groups, respectively, suggesting the presence of a long chain alkyl group.
The presence of carboxylic acid carbonyls is evident
from the peak at 1709 ­cm−1 (C = O peak). The antisymmetric stretching vibration peaks of CH3 are observed at1094 ­cm−1, appearing as two weak peaks. Peaks around914, 1468, and 1253 ­cm−1 represent the in-plane bending,symmetric, and out-ofplane bending vibrations, respectively, of the fatty acid carboxyl (COOH) groups [44]. The
presence of a peak around 3357 ­cm−1 in the spectra corresponds to the N − H bond, which is a strong bond, andcan be observed in PILs [45].
H NMR spectrum of the synthesized PILs

Figures S4 − S6 present the H NMR spectra of three synthesized PILs: 2 hydroxyethylammonium laurate [MEA]
La, bis-2 hydroxyethylammonium laurate [DEA]La, andtris-2 hydroxyethylammonium laurate [TEA]La. EachPIL has its specifc set of H NMR index peaks, which arelisted as follows. For 2 hydroxyethylammonium laurate[MEA]La, the H NMR peaks are observed at (500 MHz,DMSO) δ 6.15 (s, 3H), 3.51 − 3.45 (m, 2H), 2.74 − 2.66(m, 2H), 1.99 (q, J = 7.4 Hz, 2H), 1.46 − 1.39 (m, 2H), 1.23
(s, 16H), 0.85 (t, J = 6.5 Hz, 3H). For bis-2-hydroxyethylammonium laurate [DEA]La—[Lau], the H NMR peaks
are observed at (500 MHz, DMSO) δ 5.53 (s, 1H), 3.49
(ddt, J = 8.6, 5.5, 3.0 Hz, 6H), 2.68 (dt, J = 5.7, 2.9 Hz, 4H),
2.08 (ddd, J = 7.5, 4.7, 2.9 Hz, 2H), 1.45 (t, J = 7.2 Hz, 2H),
1.23 (s, 16H), 0.86 − 0.84 (m, 3H). For tris-2 hydroxyethylammonium laurate [TEA]La, the H NMR peaks areobserved at (500 MHz, DMSO) δ 5.40 (s,1H), 5.02 (s, 3H),
4.32 (s, 6H), 2.50 (s, 6H), 2.01 (s, 2H), 1.43 (s, 2H), 1.23
(s, 16H), 0.85 (s, 3H). By analyzing the H NMR spectra,
it has been noted that the synthesized PILs in this study
exhibit a purity of surpassing 98% approximately [46].

Gondoghdi et al. BMC Chemistry(2024) 18:136

Page 7 of 15

Table 3 The experimental ( x1 )a and calculated ( x1cal ) solubilitiesof acetaminophen (ACE) in the aqueous protic ionic liquid (PIL)
solutions at different temperatures (T), PIL mass fraction in the
aqueous mixture (w3), and pressure (dp = 866 hPa), as predictedby the Wilson and e-NRTL models, are presented

Table 3 (continued)

T/K

ACP (1) + water (2) + ([MEA]La) (3)exp

Wilson model
105x1exp

105x1calxe− NRTL modelexp−x calx1

100 1 exp 1

105x1calx

exp−x calx1

100 1 exp 1

ACP (1) + water (2) + ([MEA]La) (3)w3 = 0.0000

T/K

Wilson model
5

10 x1

exp

5

cal

10 x1

100

exp
x1 −x1calexp
x1

e− NRTL model
105x1calxexp

298.15

2.492

2.490

1.35

2.462

1.19

303.15

3.159

3.152

0.57

3.135

0.76

308.15

3.555

3.549

0.75

3.534

0.58

313.15

3.722

3.718

0.22

3.693

0.77

w3 = 0.0500

298.15

1.839

1.840

− 0.041.847− 0.46298.15

3.181

3.179

0.70

3.161

0.64

303.15

2.239

2.243

− 0.16

2.253− 0.61

303.15

3.576

3.576

0.68

3.581

− 0.13308.15

2.545

2.548

− 0.102.556− 0.44308.15

3.917

3.919

0.75

3.903

0.36

313.15

3.009

3.013

− 0.133.021− 0.41

313.15

4.227

4.227

0.63

4.217

0.24

298.15

2.750

2.744

0.20

2.712

1.35

303.15

3.417

3.410

0.19

3.397

0.57

w3 = 0.0200

w3 = 0.0700
298.15

3.452

3.457

− 0.11

3.443

0.27

303.15

3.977

3.974

− 1.17

3.976

0.03

308.15

3.802

3.790

0.33

3.774

0.75

308.15

4.167

4.171

− 0.06

4.159

0.19

313.15

4.007

4.001

0.17

3.999

0.22

313.15

4.514

4.516

− 0.234.517− 0.09298.15

3.256

3.261

− 0.18

3.233

0.70

303.15

3.861

3.868

− 0.17

3.835

0.68

w3 = 0.0500

w3 = 0.1000
298.15

3.849

3.852

− 0.493.856− 0.17303.15

4.220

4.222

− 0.41

4.236− 0.39308.15

4.055

4.060

− 0.13

4.024

0.75

308.15

4.793

4.788

− 0.884.829− 0.75313.15

4.320

4.327

− 0.16

4.293

0.63

313.15

5.266

5.258

− 0.445.271− 0.10298.15

3.884

3.881

0.07

3.888

− 0.11

303.15

4.588

4.585

0.07

4.642

− 1.17

w3 = 0.0700

w3 = 0.1500
298.15

4.290

4.292

− 0.274.301− 0.27303.15

4.611

4.615

− 0.974.638− 0.59308.15

4.675

4.676

− 0.034.677− 0.06308.15

5.038

5.043

− 0.48

5.030

0.15

313.15

5.025

5.025

0.01

5.037

− 0.23313.15

5.633

5.634

− 0.765.642− 0.17298.15

4.380

4.381

− 0.034.401− 0.49303.15

4.807

4.817

− 0.204.827− 0.41

w3 = 0.1000

w3 = 0.2000
298.15

4.669

4.664

0.58

4.666

0.07

303.15

5.223

5.214

0.43

5.175

0.92

308.15

5.407

5.403

0.06

5.454

− 0.88308.15

5.710

5.708

0.80

5.689

0.37

313.15

5.600

5.603

− 0.06

5.625− 0.44313.15

6.188

6.185

0.40

6.158

0.48

298.15

4.962

4.969

− 0.144.975− 0.27303.15

5.658

5.659

− 0.025.712− 0.97308.15

6.128

6.129

− 0.01

6.158− 0.48313.15

6.665

6.664

0.02

6.716

− 0.76

w3 = 0.1500

ACP (1) + water (2) + ([TEA]La) (3)w3 = 0.2000
298.15

5.589

5.587

0.04

5.557

0.58

303.15

6.123

6.123

0.01

6.096

0.43

308.15

6.695

6.697

− 0.03

6.641

0.80

313.15

7.337

7.339

− 0.03

7.308

0.40

ACP (1) + water (2) + ([DEA]La) (3)w3 = 0.0000
298.15

1.839

1.839

− 0.461.849− 0.52303.15

2.239

2.240

− 0.612.241− 0.08w3 = 0.0000
298.15

1.839

1.844

− 0.291.860− 1.15303.15

2.239

2.247

− 0.362.553− 14.04

308.15

2.545

2.548

− 0.13

2.248

11.67

313.15

3.009

3.012

− 0.093.015− 0.21

w3 = 0.0200
298.15

2.161

2.163

− 0.052.165− 0.16303.15

2.632

2.634

− 0.072.926− 11.16308.15

2.940

2.939

0.04

2.624

10.73

313.15

3.334

3.333

0.01

3.325

0.26

w3 = 0.0500
298.15

2.597

2.593

0.16

2.592

0.18

303.15

2.944

2.944

0.00

3.205

− 8.88308.15

2.545

2.545

− 0.442.547− 0.09308.15

3.210

3.213

− 0.09

2.942

8.34

313.15

3.009

3.010

− 0.41

3.014− 0.16313.15

3.521

3.523

− 0.05

3.520

0.03

w3 = 0.0200−x calx1

100 1 exp 1

w3 = 0.0700

Gondoghdi et al. BMC Chemistry(2024) 18:136

Page 8 of 15

Table 3 (continued)
Wilson model
exp

10 x1

5

cal

10 x1

100

exp
x1 −x1calexp
x1

e− NRTL model
105x1calx

exp−x calx1

7

100 1 exp 1

6

ACP (1) + water (2) + ([MEA]La) (3)298.15

2.908

2.907

0.02

2.917

− 0.31

303.15

3.461

3.462

− 0.02

3.576− 3.32308.15

3.584

3.583

0.03

3.462

3.40

313.15

3.929

3.930

− 0.01

3.924

0.12

3

298.15

3.094

3.093

0.06

3.051

1.40

2

303.15

3.834

3.817

0.44

4.206

− 9.70308.15

4.208

4.208

0.00

3.845

8.63

313.15

4.349

4.355

− 0.13

4.348

0.02

10 x 15
3

4

w3 = 0.1000

1
0.15

3.958

3.941

0.43

4.026

− 1.73303.15

4.151

4.151

− 0.014.951− 19.28308.15

4.940

4.921

0.40

4.154

15.91

313.15

5.167

5.157

0.19

5.171

− 0.08

0.10

W
ILs

w3 = 0.1500
298.15

312
310
308
306
304
302
300

/K

5

T

T/K

0.05

0.00

Fig. 4 The relationship between temperature, weight fractionof PILs, ­wPILs, and mole fraction ­x1 in aqueous [DEA]La solutions
and the solubility of ACP

w3 = 0.2000
298.15

4.309

4.319

− 0.234.336− 0.62303.15

4.778

4.787

− 0.195.355− 12.08308.15

5.362

5.372

− 0.20

4.745

11.49

313.15

5.751

5.758

− 0.125.755− 0.076

4

3

10 x 1

5

3

8
7

/K

6

T

1

5

0.15

3

10 x 1

312
310
308
306
304
302
300

2

4
3

312
310
308
306
304
302
300

/K

2

W
ILs

0.05

0.00

Fig. 5 The relationship between temperature, weight fractionof PILs, ­wPILs, and mole fraction ­x1 in aqueous [TEA]La solutions
and the solubility of ACP

T

1

0.10

0.15

0.10

W
ILs

0.05

0.00

Fig. 3 The relationship between temperature, weight fractionof PILs, ­wPILs, and mole fraction ­x1 in aqueous [MEA]La solutions
and the solubility of ACPResults of the solubility

Three protic ionic liquids, [MEA] La, [DEA] La, and[TEA] La, were present in binary solutions intended
for examining the solubility of acetaminophen (ACP).
Table 3 and Figs. 3, 4, and 5 illustrate the various temperatures (298.15 K, 303.15 K, 308.15 K, and 313.15 K)

Gondoghdi et al. BMC Chemistry(2024) 18:136

Page 9 of 15

at which the experiments were carried out. Based on theevaluated experimental solubility, the results show that as
the temperature and weight fraction of systems containing the protic ionic liquids increased, the dissolution of
ACP is larger. The results indicate that the solubility of
ACP increases with temperature and weight fractionof systems containing protic ionic liquids, based on theevaluated experimental data. According to the size of thecation in the surfactant molecule structure, one could
suppose that the bilayers that result from monoethanolammonium laurate are more packed with stronger
intermolecular hydrogen bonding networks than thediethanolammonium laurate and triethanolammonium
laurate structures, whose larger cation decreases the selfassembly ability. In particular, the solubility of ACP in
the [MEA]La PIL at each temperature is higher than in[DEA]La and [TEA]La PILs [47].
An ACP solubility value of 2.65 × ­10–3 (mole fraction)
at 298.15 K in the co-solvent system methanol + waterwith 0.1 methanol weight fraction has been reported
by Muoza et al. [48]. Compared to this value and at thesame temperature and weight fraction, the solubility of
ACP was higher in all co-solvent [MEA]La, [DMEA]La
and [TEA]La systems being highest for [MEA]La PIL.
ACP was also substantially less soluble at 298.15 K in the
co-solvent system propylene glycol + water with an 0.1
weight fraction of propylene glycol (x1PG = 2.37 × ­10–3)
than in the co-solvent system containing [MEA]La,[49]. ACP’s solubility in solvent mixtures like aqueous

ethanol and dioxan has been the subject of some reports[50–52]. Furthermore, the order of experimental solubility enhancement is [MEA]La > [DEA]La > [TEA]La.
The solubility increase is due to the numerous factors,
including solute–solvent interactions, polarity, hydrogen bonding interactions, enthalpy of fusion, and melting point. [26, 53]. The presence of hydrogen bonding
interactions between ACP acting as the hydrogen bondacceptor, and the PILs as the hydrogen bond donor
could explain the enhanced solubility of ACP in aqueous PIL co-solvent systems. In simpler terms, based on
the experimental solubility data, the dissolution of ACP
is directly influenced by the presence of ethanol aminegroups and their ability to stablish strong hydrogenbonding interactions [26, 54]. These interactions could
be mainly from the OH groups of ethanolamine (ETA)as ­NH3+ will be having electrostatic interaction with thecarboxylic group of these acids. Notably, a liquid phase
was only formed when ethanolamine was mixed withcarboxylic acids in a 1:1 molar ratio, mirroring the composition of many protic ionic liquids (PILs) and deep
eutectic solvents (DESs) generated through hydrogenbond interactions between two equivalents of a hydrogen bond donor and one equivalent of a hydrogen bondacceptor. This raises the question of whether hydrogenbond interactions between ethanolamine molecules,
with the former acting as a hydrogen-bond acceptor(HBA) and the latter as a hydrogen-bond donor (HBD),
could lead to the formation of PILs or DESs liquids at

Table 4 The Modified Apelblat-Jouyban-Acree model’s parameters for the ACP in the investigated systems
ACP (1) + [MEA]La (2) + (water) (3)T/K

A1103 B1C1A2

104 B2103 C2

10–3 J0

10–4 J1

10–4 J2

298.150.001− 0.313− 0.286− 5.258− 2.077− 0.146

0.258

0.241

0.405

303.150.026

24.000− 0.756− 3.367− 1.527− 0.428− 1.332− 892.030

0.070

308.15− 0.288− 0.078− 2.019− 5.374− 1.298− 0.047

0.016− 1.105− 0.836

313.1512.202− 6.498

222.700− 5.502− 0.1210.001− 0.007− 51.950− 16.950

C1A2

105 B2104 C2

10–5 J0

10–5 J1

10–4 J2

ACP (1) + [DEA]La (2) + (water) (3)T/K

A1105 B1

298.150.155− 1.464− 27.386− 6.214− 18.050

1.167

0.878

0.678

2.843

303.1537.765− 1.424128.990− 5.849− 16.850

1.133− 4.350− 2.851− 8.558

308.15

0.385

1.707

360.480− 5.599− 3.898

0.579− 0.118− 7.957− 25.160

313.15

0.385

1.707

353.834− 5.565− 3.898

0.579− 0.119− 8.001− 25.420

C1A2

104 B2104 C2

10–5 J0

10–5 J1

10–5 J2

ACP (1) + [TEA]La (2) + (water) (3)T/K

A1105 B1

298.15

0.626

3.529

82.087− 6.214− 12.2200.145− 2.626− 1.798− 0.576303.15− 193.290− 1.465

1.289− 6.122− 11.950

1.158

1.048

0.756

0.281

308.15− 824.550− 2.930

5.144− 5.927− 30.650

2.317

4.475

2.883

0.856

313.15− 0.001− 1.470

52.840− 5.676− 29.617

1.157− 1.879− 1.478− 0.578

Gondoghdi et al. BMC Chemistry(2024) 18:136

Page 10 of 15

Table 5 The Van’t Hoff-Jouyban-Acree mode parameters for the ACP in the investigated systems
ACP (1) + [MEA]La (2) + (water) (3)
T/K

A1

103B1

A2

103B2

J0

10–4 J1

10–4 J2

298.15− 1.632

0.813− 6.090

0.594

0.872

0.241

0.405

303.15− 4.293

7.000− 5.8134.750− 1.851− 0.0890.070

308.15− 11.860

0.203− 5.646

0.148

0.054

− 1.105− 0.836

313.15− 10.313

0.102− 5.588

0.074

0.013

− 0.970− 0.739

B1

A2

B2

10–4 J1

10–4 J2

ACP (1) + [DEA]La (2) + (water) (3)T/K

10−3A1

10–4 J0

298.15− 0.200

0.054− 6.216

0.038

11.240

8.437

3.369

303.15

0.772

0.027

− 5.8480.019− 43.360− 28.420− 8.529308.15

1.830

0.027

− 5.6140.019− 104.900− 70.500− 22.280

313.15− 0.2220.054− 5.7240.038

12.670

8.434

2.762

B1

A2

B2

10–6 J0

10–5 J1

10–4 J2

ACP (1) + [TEA]La (2) + (water) (3)T/KA1

298.15471.155

0.006− 6.2130.005− 0.264− 1.809− 5.797303.152191.000

0.053− 5.953

0.038− 1.234− 8.268− 25.950308.15− 682.989

0.053− 5.920

0.038

0.383

2.450

7.174

313.15

303.657

0.107− 5.676

0.077− 0.188− 1.478− 5.780

Table 6 The Wilson parameters of wilson model for the ACP in the investigated systems
T/K

105 Λwd

Λdw

103ΛCadΛdCa

104ΛCaw

103ΛwCaACP (1) + [MEA]La (2) + (water) (3)298.15− 0.043

3.442

4.225

0.076

− 1.21311.000303.15

1.382

2.932

4.249

0.053

− 1.2139.571

308.15

1.389

2.764

4.243

0.063

− 1.21315.000313.15

1.388

2.603

4.250

0.076

− 1.21325.000105 Λwd

Λdw

103ΛCadΛdCa

104ΛCaw

103ΛwCaT/K

ACP (1) + [DEA]La (2) + (water) (3)298.1596.280

3.024

4.070

0.101

− 1.2112.108

303.15

1.976

2.931

5.229

0.038

− 1.2197.560

308.15

2.078

2.763

4.685

0.015

− 320.000

2.280

313.15− 1.942

2.602

4.152

0.043

− 1.21213.000105 Λwd

Λdw

ΛCad

105ΛdCa

104ΛCaw

103ΛwCaLACP (1) + [TEA]La (2) + (water) (3)298.15− 1.589

3.105− 0.065− 1.705− 1.212− 3.897303.15− 2.294

2.934− 0.067− 1.594− 1.213− 3.883308.15− 16.530

2.762− 0.071− 9.193− 1.228− 5.820313.15− 16.530

2.601− 0.071− 9.186− 1.228− 6.000

w = water, d = drug (ACP), Ca = cation (2-hydroxyethylammonium (MEA) Bis-2-hydroxyethylammonium (DEA) Tris-2-hydroxyethylammonium (TEA) and anion (Lauricacid)

room temperature. Partial atom-to-atom radial distribution functions (pRDFs) indicated the presence ofhydrogen bonding between the carboxyl group of the
carboxylic acid (-COOH) and both the primary amine(-NH2) and hydroxyl group (-OH) of ETAH + .[55]. The

enhanced solubility of ACPs in systems containing PILs
is attributed to the presence of diverse intermolecularinteractions, including strong ion–dipole interactions,dipole–dipole interactions, and hydrogen bonding [56].

Gondoghdi et al. BMC Chemistry(2024) 18:136

Page 11 of 15

Table 7 The e-NRTL mode parameters for the ACP in the investigated systems.
T/K

104 Δgwd

Δgdw

103ΔgCad

103ΔgdCa

103ΔgCaw

103ΔgwCa

ACP (1) + [MEA]La (2) + (water) (3)298.15

0.924

2.001

4.144

1.711

− 0.048− 0.400

303.15

1.083

1.022

6.794

0.572

− 3.693− 0.607308.15

1.104

1.385

4.354

4.778

− 4.451− 5.550313.15

1.140

1.019

5.096

0.585

− 4.545− 0.621103ΔgdCa

103ΔgCaw

ΔgwCa

T/K

104Δgwd

Δgdw

103ΔgCadACP (1) + [DEA]La (2) + (water) (3)298.15

0.928

2.151

4.541

1.946

− 0.045− 412.982

303.15

0.845

0.360

2.195

− 0.3491.589

364.955

308.15

1.116

2.464

4.830

0.366

− 4.215− 403.353

313.15

1.112

2.460

2.487

0.372

− 6.121− 409.642

104 Δgwd

103Δgdw

103ΔgCad

103ΔgdCa

103ΔgCaw

103ΔgwCa

L

ACP (1) + [TEA]La (2) + (water) (3)298.151.850

19.424

4.272

1.380

− 13.690− 1.822303.151.094

35.310

3.368

1.157

− 4.974− 1.465

308.151.076

35.302

3.377

1.155

− 4.994− 1.463313.15

1.107

35.317

3.361

1.150

− 4.961− 1.462w = water, d = drug (ACP), Ca = cation cation (2-hydroxyethylammonium (MEA) Bis-2-hydroxyethylammonium (DEA) Tris-2-hydroxyethylammonium (TEA)) and anion(Lauric acid)

Modeling results

The experimental solubility data were further analyzed
using various thermodynamic models, including theModified Apelblat-Jouyban-Acree, Van’t Hoff-JouybanAcree, Wilson, and e-NRTL models, with the lattertwo serving as local composition models. The obtained
results and corresponding model parameters are presented in Tables 4, 5, 6 and 7. Additionally, Table 8 summarizes the average relative deviation percent (ARD%)
for each model’s correlation performance. For the system
containing [MEA]La, the adequacy of the models in predicting ACP solubility in aqueous PIL solutions within
the temperature range of 298.15 to 313.15 K followed
the order: Wilson > e-NRTL > Modified Apelblat-Jouyban-Acree > Van’t Hoff-Jouyban-Acree. Similarly, for the[DEA]La and [TEA]La co-solvent systems, the order ofmodel adequacy was: Wilson > e-NRTL > Van’t Hoff-Jouyban-Acree > Modified Apelblat-Jouyban-Acree.
Activity coefficients play a pivotal role in understanding and quantifying nonideal effects in solubility behavior. They bridge the gap between ideal and real-world
solutions, allowing us to explore deviations and makeaccurate predictions. in this regard, importance of considering activity coefficients to describe the nonideal
effects in the solubility behavior of the studied mixtures. Table 9 and Fig. 6 presents the calculated activity

coefficients (γ1) for ACP in the systems using the Wilson
model for the [MEA]La co-solvent system at different
temperatures. The solubility of ACP is directly related
to its activity coefficient. When the activity coefficientis high, the ACP molecules are less likely to escape into
the solvent, resulting in lower solubility. Conversely,
when the activity coefficient is low, the ACP molecules
are more prone to disperse into the solvent, leading tohigher solubility. according to the mentioned explanation
and activity coefficent values, it could observed that γ1
values decrease with an increase in the weight fraction of
the protic ionic liquids present in the systems. The results
show that as the experimental solubility increases withtemperature, the activity coefficient decreases, indicating enhanced interactions between ACP and co-solvent.
This observation confirms that the activity coefficientdecreases as a result of increased interactions [57].
Thermodynamic properties of dissolution results

Figure 7 presents the van’t Hoff plots of ACP solubility data for the [MEA]La system. Fom the results, thevalue of the thermodynamic parameters of dissolution
o
o
o
(Hso
ln , Tm Sso ln and Gso ln ) were calculated and listedoin Table 10. The positive values of (ΔG0soln) and (Hsoln )show an endothermic process for the dissolution of ACP
in these aqueous PIL systems. The ΔG0soln values were

Gondoghdi et al. BMC Chemistry(2024) 18:136

Page 12 of 15

Table 8 The calculated activity coefficient of ACP, ln γ1, based on
Wilson model in aqueous PILs solutions at different temperatures
respectively
PILs
weightfractionT = 298.15 K

T = 303.15 K

T = 308.15 K

T = 313.15 K

ACP (1) + [MEA]La (2) + (water) (3)0.00002.8782

3.18883.22893.22340.02002.47832.76982.83172.93980.05002.30572.64382.76292.86140.07002.13172.47372.62162.71190.10002.01052.42432.477

2.60290.15001.88452.26322.351

2.42950.20001.76742.18452.26242.3331

Fig. 7 Plot of lnx1 vs (1/T- 1/Thm); in aqueous [MEA]La solutions
at different weight fraction of the PILs (wPILs): 0.0000(♦), 0.0200 (■),
0.0500 (▲), 0.0700 (●), 0.1000 (□), 0.1500 (o), 0.2000 (△)

ACP (1) + [DEA]La (2) + (water) (3)0.00003.21393.18983.22993.22430.02002.91082.84852.89733.01320.05002.66672.72232.79832.88480.07002.58292.61672.73602.81860.10002.47472.55622.59802.66640.15002.36652.46712.54612.59740.20002.28332.34522.42212.5041

3.2286

3.2237

3.21113.1868ARD%
T/K

ACP (1) + [TEA]La (2) + (water) (3)0.0000

Table 9 The average relative deviation percent (ARD%) for the
ACP’s solubility in the aqueous PILs solutions at a T / ­Ka = 298.15
to 313.15 and a pressure of ­Pa = 866 hPa, as determined by theutilized models
Modified
Van’t HoffApelblatJouybanJouyban-Acree Acree

Wilsone-NRTL0.02003.05203.02783.0861

3.12230.05002.87052.91682.99703.06690.07002.75602.75472.88792.9577298.15

1.484

1.495

0.099

0.564

0.10002.69432.65692.72712.8550303.15

1.819

1.827

0.117

0.689

ACP (1) + [MEA]La (2) + (water) (3)0.15002.45192.57312.57062.6860308.15

2.019

2.148

0.097

0.594

0.20002.36022.43052.48282.5757313.15

1.358

1.883

0.082

0.441

Average

1.690

1.838

0.099

0.572

ACP (1) + [DEA]La (2) + (water) (3)298.15

0.502

0.550

0.073

0.448

303.15

1.027

0.650

0.098

0.415

308.15

0.993

0.888

0.078

0.345

313.15

2.562

1.647

0.058

0.287

Average

1.271

0.934

0.077

0.456

ACP (1) + [TEA]La (2) + (water) (3)Fig. 6 The following is the relationship between the solubilityof ACP and the calculated activity coefficient in the aqueous solution
containing [MEA]La from the Wilson model at various temperatures;
298.15(■), 303.15 (♦), 308.15 (▲), 313.15 (●)

smaller as the weight fraction of PILs increased as can beoseen in Fig. 8. Moreover, the Thm Ssoln values are positive for the dissolution process. The relative contributionsof enthalpy and entropy to the standard molar Gibbs freeenergy of dissolution of ACP in PIL based systems was

298.15

1.933

1.681

0.177

0.793

303.15

2.619

1.198

0.156

0.264

308.15

1.026

1.111

0.127

0.218

313.15

0.696

1.409

0.089

0.113

Average

1.568

1.350

0.137

0.331

a

Standard uncertainty u(T) = 0.01 KbStandard uncertainty u(P) = 10 hPa

expressed in ξH and ξTS (eqs. 17 and 18). The relatively
lower entropy values compared to the enthalpy of dissolution suggest that the enthalpy of dissolution plays amore significant role in the ACP dissolution process inthese aqueous PIL systems [58].

Gondoghdi et al. BMC Chemistry(2024) 18:136

Page 13 of 15◦

Fig. 8 The Gso ln values relative to dissolution process of ACP
in the aqueous PILs solutions at 305.548 K, [MEA]La (●), [DEA]La (♦),[TEA]La (▲)

Conclusions
In the present study, the effect of three protic ionic liquids [MEA]La, [DEA]La, and [TEA]La on the experimental aqueous solubility of acetaminophen (ACP) drugat different temperatures and weight fractions of the
PILs was measured. The results presented that enhancement in ACP solubility by increasing the temperature and weight fraction of the PILs . Due to its stronghydrogen bonding interactions, [MEA]La revealed thegreatest solubility improvement. Besides, various thermodynamic models, including the Wilson, e-NRTL andthe emprical models, Van’t Hoff-Jouyban-Acree, andModified Apelblat-Jouyban-Acree were applied to correlate the experimental aquous ACP solubility data. The
performance for the system containing [MEA]La follow the trend for activity coefficient and empirical models, respectively: the Wilson > e-NRTL and Modified

Table 10 Thermodynamic functions for dissolution process at different weight fractions of PIL (­ w3) a at mean temperature b◦ /kJ∙mol−1
Hso
ln

w3

◦ /kJ∙mol−1
TM Hsoln◦/kJ∙mol−1
Gso
ln

ξH

ξTS

ACP (1) + [MEA]La (2) + (water) (3)0.000024.9339.576

15.35672.25027.7500.020019.2844.888

14.39579.77720.2230.050013.991− 0.131

14.12299.0760.924

0.070012.336− 1.378

13.71489.95310.0470.100013.299− 0.148

13.44798.8981.102

0.150015.0051.931

13.07488.60011.4000.200014.056

1.225

12.83191.9828.018

ACP (1) + [DEA]La (2) + (water) (3)0.000024.9339.576

15.35672.25027.7500.020020.6126.015

14.59877.41122.5890.050014.6710.450

14.22197.0242.976

0.070013.237− 0.784

14.02194.4075.593

0.100016.5692.841

13.72785.361

14.6390.150014.041

0.514

13.52896.4723.528

0.200014.5151.260

13.25692.0157.985

ACP (1) + [TEA]La (2) + (water) (3)0.000024.9339.576

15.35672.25027.7500.020021.931

6.937

14.99475.97024.0300.050015.5350.819

14.71694.9925.008

0.070014.6000.198

14.40298.6591.341

0.100017.384

3.253

14.131

84.23515.7650.150015.1131.400

13.71391.5228.478

0.200015.242

1.793

13.44989.476

10.524aStandard uncertainty u is u(w3) = 0.0002bStandard uncertainty u(T) = 0.01 K

Gondoghdi et al. BMC Chemistry(2024) 18:136

Apelblat—Jouyban—Acree > Van’t
Hoff—Jouyban—
Acree. On the other hand, [DEA]La and [TEA]La PILs
followed slightly different trend for activity coefficientmodels and empirical respectively: the Wilson > e-NRTL
and Van’t Hoff–Jouyban–Acree > Modified Apelblat–
Jouyba–Acree. Subsequently, an overview of the thermodynamic dissolution process of ACP in the systems underinvestigation was carried out. The outcomes demonstrated that enthalpy drives the endothermic dissolving
process in all utilized co-solvents.
Abbreviations(VOCs)	Volatile organic compounds(LMMs)	Low-melting mixtures(PILs)	Protic ionic liquids(ACP)	Acetaminophen[MEA]La	2-Hydroxyethylammonium laurate[DEA]La	Bis(2-hydroxyethyl)ammonium laurate[TEA]La	Tris(2-hydroxyethyl)ammonium laurate

Page 14 of 15

5.
6.
7.

8.
9.
10.
11.
12.
13.

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s13065-​024-​01243-x.
Supplementary file 1.

14.

15.

Author contributions
The manuscript was written through contributions of all authors. All authors
have given approval to the final version of the manuscript.

16.

Funding
The University of Tabriz’s Graduate Council provided financial support (Funding Declaration), for which the authors are thankful.

17.

Availability of data and materials
The datasets utilized and/or analyzed during this study are available from thecorresponding author on reasonable request.

18.

Declarations

19.

Ethics approval and consent to participate
Not applicable.

20.

Consent for publication
Not applicable.

21.

Competing interests
The authors declare no competing interest.

22.
23.

Received: 3 February 2024 Accepted: 8 July 2024
24.
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