This document describes the development of a quantitative structure-activity relationship (QSAR) model to estimate the ecotoxicity of ionic liquids expressed as EC50 values for the bioluminescent bacteria Vibrio fischeri. The QSAR was developed using a training set of 96 data points for ionic liquids containing 9 different cations and 17 different anions. A multiple linear regression analysis was performed to correlate molecular descriptor values with experimental and literature EC50 values. The resulting QSAR model can estimate ecotoxicity values for new ionic liquids in the range of log EC50 from -0.23 to 5.00 based on their molecular structure.

1. Quantitative structure–activity relationships (QSARs) to estimate ionic liquids
ecotoxicity EC50 (Vibrio fischeri)
P. Luis ⁎, A. Garea 1
, A. Irabien 1
Departamento de Ingeniería Química y Química Inorgánica, Universidad de Cantabria, 39005, Santander, Spain
a b s t r a c ta r t i c l e i n f o
Article history:
Received 30 January 2009
Received in revised form 18 November 2009
Accepted 24 December 2009
Available online 18 January 2010
Keywords:
Aquatic environment
Vibrio fischeri
QSAR
Group contribution method
Many ionic liquids are soluble in water and their impact on the aquatic environment has to be evaluated.
However, due to the large number of ionic liquids and the lack of experimental data, it is necessary to
develop estimation procedures in order to reduce the materials and time consumption.
Quantitative structure–activity relationships (QSARs) are models that can be used to estimate the
physicochemical and toxicological properties of molecules from the molecular structure or properties of
similar compounds whose activities have already been assessed. In this work, a novel QSAR based on
multiple linear regression is applied in order to estimate the ecotoxicity of ionic liquids, expressed as EC50
(Vibrio fischeri), involving 9 kind of cations and 17 anions. The range of log EC50 values covered by the novel
QSAR is from -0.23 to 5.00. From the results, the influence of cations, anions and substitutions on the
ecotoxicity of ionic liquids is established.
© 2010 Elsevier B.V. All rights reserved.
1. Introduction
In recent years, the interest in ionic liquids has increased widely
and their use in industrial applications is already a reality. The BASIL™
(Biphasic Acid Scavenging utilising Ionic Liquids) process is probably
the most successful example of an industrial process using ionic liquid
technology, developed by BASF in 2002. Other current industrial
applications are focused on breaking azeotropes, replacing phosgene,
dissolution of cellulose, aluminium plating, isomerisation of 3,4-
epoxybut-1-ene, dimerisation of alkenes, paint additives, lithium-ion
batteries, etc. [1]. The use of ionic liquids is growing rapidly and the
environmental effects that their release may produce have to be
considered in order to achieve sustainable production and consump-
tion patterns.
Ionic liquids are liquids that are composed entirely of ions and are
fluid below 100 °C due to the asymmetry of at least one of the ions.
They are thermally robust with liquid ranges of, e.g., 300 °C, compared
to 100 °C for water, and show a very low vapour pressure [2,3], being
of great interest due to these properties. In addition, there are about
600 conventional solvents used in the industry, compared to at least
one million (106
) single ionic liquids that can be easily prepared in the
laboratory [1,3,4]. There will be 1012
binary combinations of these and
1018
ternary systems possible. The variability of the anion, the cation
and the linked chains may be used to adjust the properties of ionic
liquids, optimizing the ionic liquid for a specific application. For this
reason, ionic liquids have been referred to as “designer solvents” in
several publications [2,5–7]. At the moment only about 300 ionic
liquids are commercial, so there is a wide field to be explored.
Water solubilities of many ionic liquids are not negligible [e.g. 8–12]
and the release of ionic liquids into aquatic environments may lead to
water pollution and related risks. Toxicity of some ionic liquids has been
measured referred to different aquatic organisms: bioluminescent
bacteria (e.g. Vibrio fischeri) (e.g. [13–15]), green alga or plants (e.g.
[16–19]), cladoceran (e.g. Daphnia magna) (e.g. [20–22]), fish (e.g. Da-
nio rerio) (e.g. [23]), frogs (e.g. [24]), etc., showing a broad range of
toxicity. Specifically, the bioluminescent bacteria assay with V. fischeri,
formerly known as Photobacterium phosphoreum, is of technical interest
due to the simple and fast experimental procedure compared to others
and it appears in the Spanish regulation as a reference of the ecotoxicity
of wastewater and waste leachates [25,26]. However, it should be noted
that studies considering different organisms should be performed to
fulfil environmental protection [27].
Nevertheless, because of the large number of ionic liquids, it is
necessary to develop estimation procedures in order to evaluate the
toxicity of ionic liquids without experimental work, reducing the
consumption of time and materials [28]. In addition, recent policy
developments worldwide have placed increased emphasis on the use
of estimation models for the hazard and risk assessment of chemicals
since these models reduce the number of laboratory organisms and
animals used in the tests [27,29,30].
Quantitative structure–activity relationships (QSARs) are the
fundamental basis of developed approaches for estimating the toxicity
of chemicals from their molecular structure and/or physicochemical
properties [31,32]. QSARs are mathematical models that can be used
Journal of Molecular Liquids 152 (2010) 28–33
⁎ Corresponding author. Tel.: +34 942 200931; fax: +34 942 201591.
E-mail address: luisp@unican.es (P. Luis).
1
Tel.: +34 942 200931; fax: +34 942 201591.
0167-7322/$ – see front matter © 2010 Elsevier B.V. All rights reserved.
doi:10.1016/j.molliq.2009.12.008
Contents lists available at ScienceDirect
Journal of Molecular Liquids
journal homepage: www.elsevier.com/locate/molliq

2. to predict the physicochemical and biological properties of molecules
considering that the biological activity of a new or untested chemical
can be inferred from the molecular structure or other properties of
similar compounds whose activities have already been assessed. The
two main objectives of QSARs are to allow prediction of the biological
properties of chemically characterized compounds that have not
been biologically tested and to obtain information on the molecular
characteristics of a compound that are important for the biological
properties [31].
Some interesting QSARs have been performed to estimate
properties of ionic liquids, such as melting point, boiling point, vapour
pressure, Henry's Law constant, octanol–water partition coefficient
and water solubilities [e.g. 12,33–38]. In addition, several QSARs which
predict toxicity values for V. fischeri, and other aquatic organisms are
being currently developed [39–42]. In a previous work [43], the
ecotoxicity (EC50 V. fischeri) for imidazolium-, pyridinium- and
pyrrolidinium-based ionic liquids was performed using a group
contribution method as QSAR. The previous QSAR model for ionic
liquids used a training set of 43 data and a good fitting was achieved. In
this work, the ionic liquids database has been increased using data
from the literature [13,15,40,43–47] and new experimental data,
starting with 96 data, which involve 9 kinds of cations and 17 anions.
The data analysis is multiple linear regression (MLR) because it is one
of the most common and simplest methods for QSAR modelling [31].
A MLR assumes that there is a linear relationship between the
molecular descriptors of a compound and its target property. The
molecular descriptors should be mathematically independent and the
number of compounds in the training set should exceed the number
of molecular descriptors by at least a factor of 5 [31]. In order to fulfil
this requirement and achieve high confidence in the obtained
descriptors, all data have been used in the training set.
The advantages of these kinds of models are that they are simple to
use and easy to interpret. From the results, the influence of cations,
anions and substitutions on the ecotoxicity of ionic liquids is shown.
2. Experimental
The QSAR model has been performed using data from experiments
and from the literature [13,15,40,43–47]. Some reported values were
found to be different depending on the reference. This may be
associated to the variability that experimental procedures have
themselves, which is another drawback that favours the application
of estimation models. In order to consider intrinsically this variability
in the prediction capacity of the model, all data have been considered
to perform the model.
Experimental ecotoxicity was determined for 21 ionic liquids by
means of the 15-min standard bioluminescence inhibition assay
according to the UNE EN ISO 11348-3 procedure [48]. Toxicity testing
is based on the bioluminescent bacterium V. fischeri using the
Microtox Model 500 toxicity analyzer. These ionic liquids were
synthesised as it has been shown elsewhere [49]. These were based on
the following cations: 1-methylimidazolium, imidazolium, 1,1,3,3-
tetramethylguanidinium, 1-butylimidazolium and melamine (4,6-
diamino-1,3,5-triazin-2-aminium); and anions: trifluoroacetate, tri-
flate (trifluoromethane sulfonate), formate, acetate and caprylate.
Stock solutions around 0.1 M of ionic liquids were prepared and by
means of dilutions in ultrapure water (resistivityN18 MΩ cm at 25 °C)
the endpoint (EC50, μmol L−1
) was measured. Only the 1-buthylimi-
dazolium caprylate ionic liquid required ethanol instead of water to
perform the analysis, due to the low water solubility.
3. Results
Fig. 1 shows the cations and anions of the database of the QSAR
model and Table 1 indicates the log EC50 values for the ionic liquids,
obtained from experiments and literature.
Toxicity data have been expressed on a molar basis to be
structurally comparable. In addition, the data have been converted
Fig. 1. Ionic liquids. R is the long-alkyl-chain and R1 and R2 are short chains.
29P. Luis et al. / Journal of Molecular Liquids 152 (2010) 28–33

3. Table 1
Ionic liquid ecotoxicities in μmol L−1
(log EC50), dimensionless ecotoxicity (Y⁎) and group contribution descriptors.
No. Compound Log EC50 (μmol/L) Y⁎ A1 A2 A3 C1 C2 C3 C4 C5 C6 C7 C8 C9 S1 S2 S3
1 [IM][TFA] 4.07 0.18 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0
2 [IM][Ace] 3.61 0.27 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0
3 [IM][TfO] 3.81 0.23 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0
4 [IM][Cap] 2.29 0.52 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0
5 [C1IM][TFA] 3.57 0.27 0 0 1 1 0 0 0 0 0 0 0 0 0.06 0 0
6 [C1IM][Ace] 4.07 0.18 0 0 1 1 0 0 0 0 0 0 0 0 0.06 0 0
7 [C1IM][TfO] 4.35 0.12 0 0 1 1 0 0 0 0 0 0 0 0 0.06 0 0
8 [C1IM][Cap] 2.13 0.55 0 1 0 1 0 0 0 0 0 0 0 0 0.06 0 0
9 [C1IM][For] 2.83 0.42 0 0 1 1 0 0 0 0 0 0 0 0 0.06 0 0
10 [MIM] 4.17 0.16 0 0 0 1 0 0 0 0 0 0 0 0 0 0.5 0.5
11 [C1MIM][MetSO4] 4.76 0.05 1 0 0 1 0 0 0 0 0 0 0 0 0.06 0.5 0.5
12 [C2MIM][EtSO4] 4.02 0.19 1 0 0 1 0 0 0 0 0 0 0 0 0.11 0.5 0.5
13 [C2MIM][(2-OPhO)2B] 3.00 0.38 0 0 1 1 0 0 0 0 0 0 0 0 0.11 0.5 0.5
14 [C2MIM][Cl] 4.55 0.09 1 0 0 1 0 0 0 0 0 0 0 0 0.11 0.5 0.5
15 [C2MIM][Cl] 4.33 0.13 1 0 0 1 0 0 0 0 0 0 0 0 0.11 0.5 0.5
16 [C3MIM][BF4] 3.94 0.20 1 0 0 1 0 0 0 0 0 0 0 0 0.17 0.5 0.5
17 [C4IM][TFA] 3.28 0.33 0 0 1 1 0 0 0 1 0 0 0 0 0.22 0 0
18 [C4IM][Ace] 3.32 0.32 0 0 1 1 0 0 0 1 0 0 0 0 0.22 0 0
19 [C4IM][TfO] 2.77 0.43 0 0 1 1 0 0 0 1 0 0 0 0 0.22 0 0
20 [C4IM][Cap] 2.00 0.57 0 1 0 1 0 0 0 1 0 0 0 0 0.22 0 0
21 [C4IM][For] 3.19 0.35 0 0 1 1 0 0 0 1 0 0 0 0 0.22 0 0
22 [C4MIM][PF6] 3.07 0.37 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
23 [C4MIM][BF4] 3.55 0.28 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
24 [C4MIM][BF4] 3.10 0.36 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
25 [C4MIM][BF4] 3.54 0.28 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
26 [C4MIM][Br] 3.07 0.37 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
27 [C4MIM][Br] 4.01 0.19 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
28 [C4MIM][Br] 3.27 0.33 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
29 [C4MIM][Cl] 3.71 0.25 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
30 [C4MIM][Cl] 3.39 0.31 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
31 [C4MIM][Cl] 3.40 0.31 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
32 [C4MIM][Cl] 3.47 0.29 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
33 [C4MIM][Cl] 3.34 0.32 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
34 [C4MIM][N(CN2)2] 3.67 0.25 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
35 [C4MIM][8OSO3] 1.85 0.60 0 0 1 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
36 [C4MIM][N(CF3SO2)2] 3.39 0.31 0 0 1 1 0 0 0 1 0 0 0 0 0.22 0.5 0.5
37 [C4MIM][N(CF3SO2)2] 2.48 0.48 0 0 1 1 0 0 0 1 0 0 0 0 0.22 0.5 0.5
38 [C4MIM][N(CF3)2] 3.48 0.29 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
39 [C4MIM][pTS] 3.52 0.28 1 0 0 1 0 0 0 0 0 0 0 0 0.22 0.5 0.5
40 [C4EIM][BF4] 2.80 0.42 1 0 0 1 0 0 0 0 0 0 0 0 0.22 1 0.5
41 [C5MIM][BF4] 3.14 0.36 1 0 0 1 0 0 0 0 0 0 0 0 0.28 0.5 0.5
42 [C6MIM][Br] 1.42 0.68 1 0 0 1 0 0 0 0 0 0 0 0 0.33 0.5 0.5
43 [C6MIM][Cl] 1.94 0.58 1 0 0 1 0 0 0 0 0 0 0 0 0.33 0.5 0.5
44 [C6MIM][Cl] 2.18 0.54 1 0 0 1 0 0 0 0 0 0 0 0 0.33 0.5 0.5
45 [C6MIM][Cl] 2.91 0.40 1 0 0 1 0 0 0 0 0 0 0 0 0.33 0.5 0.5
46 [C6MIM][Cl] 2.32 0.51 1 0 0 1 0 0 0 0 0 0 0 0 0.33 0.5 0.5
47 [C6MMIM][Cl] 1.74 0.62 1 0 0 1 0 0 0 0 0 0 0 0 0.33 0.5 1
48 [C6MIM][PF6] 2.17 0.54 1 0 0 1 0 0 0 0 0 0 0 0 0.33 0.5 0.5
49 [C6MIM][PF6] 2.11 0.55 1 0 0 1 0 0 0 0 0 0 0 0 0.33 0.5 0.5
50 [C6MIM][BF4] 3.18 0.35 1 0 0 1 0 0 0 0 0 0 0 0 0.33 0.5 0.5
51 [C6EIM][BF4] 2.15 0.54 1 0 0 1 0 0 0 0 0 0 0 0 0.33 1 0.5
52 [C7MIM][BF4] 2.44 0.49 1 0 0 1 0 0 0 0 0 0 0 0 0.39 0.5 0.5
53 [C8MIM][Br] 0.63 0.84 1 0 0 1 0 0 0 0 0 0 0 0 0.44 0.5 0.5
54 [C8MIM][Cl] 1.19 0.73 1 0 0 1 0 0 0 0 0 0 0 0 0.44 0.5 0.5
55 [C8MIM][Cl] 0.94 0.78 1 0 0 1 0 0 0 0 0 0 0 0 0.44 0.5 0.5
56 [C8MIM][Cl] 1.01 0.76 1 0 0 1 0 0 0 0 0 0 0 0 0.44 0.5 0.5
57 [C8MIM][PF6] 0.95 0.77 1 0 0 1 0 0 0 0 0 0 0 0 0.44 0.5 0.5
58 [C8MIM][PF6] 0.70 0.82 1 0 0 1 0 0 0 0 0 0 0 0 0.44 0.5 0.5
59 [C8MIM][BF4] 1.41 0.69 1 0 0 1 0 0 0 0 0 0 0 0 0.44 0.5 0.5
60 [C9MIM][BF4] 0.72 0.82 1 0 0 1 0 0 0 0 0 0 0 0 0.50 0.5 0.5
61 [C10MIM][Cl] 0.50 0.86 1 0 0 1 0 0 0 0 0 0 0 0 0.56 0.5 0.5
62 [C10MIM][Cl] −0.23 1.00 1 0 0 1 0 0 0 0 0 0 0 0 0.56 0.5 0.5
63 [C10MIM][BF4] −0.18 0.99 1 0 0 1 0 0 0 0 0 0 0 0 0.56 0.5 0.5
64 [C14MIM][Cl] −0.15 0.98 1 0 0 0 1 0 0 0 0 0 0 0 0.78 0.5 0.5
65 [C16MIM][Cl] 0.23 0.91 1 0 0 0 0 1 0 0 0 0 0 0 0.89 0.5 0.5
66 [C18MIM][Cl] 1.45 0.68 1 0 0 0 0 0 1 0 0 0 0 0 1 0.5 0.5
67 [MPy] 3.07 0.37 0 0 0 0 0 0 0 0 1 0 0 0 0 0.5 0.5
68 [C4Py][Br] 3.40 0.31 1 0 0 0 0 0 0 0 1 0 0 0 0.22 0 0
69 [C4MPy][Br] 2.75 0.43 1 0 0 0 0 0 0 0 1 0 0 0 0.22 0.5 0.5
70 [C4MMPy][Br] 2.69 0.44 1 0 0 0 0 0 0 0 1 0 0 0 0.22 0.5 1
71 [C4Py][Cl] 3.41 0.30 1 0 0 0 0 0 0 0 1 0 0 0 0.22 0 0
72 [C4Py][Cl] 3.18 0.35 1 0 0 0 0 0 0 0 1 0 0 0 0.22 0 0
73 [C4Py][N(CN2)2] 3.31 0.32 1 0 0 0 0 0 0 0 1 0 0 0 0.22 0 0
74 [C4MPy][N(CN2)2] 2.66 0.45 1 0 0 0 0 0 0 0 1 0 0 0 0.22 0.5 0.5
75 [C4MMPy][N(CN2)2] 2.38 0.50 1 0 0 0 0 0 0 0 1 0 0 0 0.22 0.5 1
30 P. Luis et al. / Journal of Molecular Liquids 152 (2010) 28–33

4. into a logarithmic scale to reduce statistical problems with the
regression analysis [31] and a dimensionless toxicity, Y⁎, between 0
and 1 is defined to reduce the influence of the absolute values of the
variable:
Y⁎ =
logEC50;max− logEC50
logEC50;max− logEC50;min
ð1Þ
where log EC50,min and logEC50,max are the minimum and maximum
values of log EC50 in the database, −0.23 and 5.00, respectively.
The QSAR model is based on group contribution methods, where
properties of a molecule can be assumed to be the summation of the
contributions of its atoms and/or fragments. In this work, the
structure of ionic liquids has been described by three main groups
of descriptors: Anions (A), Cations (C) and Substitutions (S). Thus, the
dimensionless ecotoxicity can be estimated as the summation of the
contributions of each group:
Y⁎ = ∑
i
ai⋅Ai + ∑
j
cj⋅Cj + ∑
k
sk⋅Sk ð2Þ
Ai and Cj are encoded in a Boolean manner (0/1), thus, they are
equal to 1 if the group is in the molecule and 0 if not. However, Sk
takes a value related to the number of carbon atoms in the R chains
(see Fig. 1). Table 1 shows the assigned values to these descriptors for
each ionic liquid and Table 2 clarifies the meaning of the considered
descriptors. Because it was noticed that some cation–anion combina-
tions did not show the common tendency observed in most of the
ionic liquids with the same anion or cation, some extra descriptors
(i.e. C5 and C8) have been included in order to take into account this
specific behaviour and achieve a better fitting for them. They are also
encoded in a Boolean manner according to Table 2. In addition,
descriptors with similar contribution have been grouped, such as the
group of anions in A1 and A3 or the group of cations C6 and C7. The
groupings of anions or cations have been performed according to a
previous work [43]. Basically, it consists of putting cations (or anions)
with similar contributions into the same group because there is no
statistical difference. It is important to highlight that some risk exists
on lose of information but from the point of view of computational
toxicology, they have to be grouped.
Regarding ai, cj and sk, these are the contribution of each group to
the toxicity, and the summation is taken over all groups. Subscripts
indicate anions (i), cations (j) and substitutions (k). The sign of the
coefficients ai, cj and sk shows whether the molecular descriptors
contribute positively or negatively to the target property, and their
Table 1 (continued)
No. Compound Log EC50 (μmol/L) Y⁎ A1 A2 A3 C1 C2 C3 C4 C5 C6 C7 C8 C9 S1 S2 S3
76 [C6MPy][Br] 2.06 0.56 1 0 0 0 0 0 0 0 1 0 0 0 0.33 0.5 0.5
77 [C6MPy][Cl] 1.44 0.68 1 0 0 0 0 0 0 0 1 0 0 0 0.33 0.5 0.5
78 [C8MPy][Br] 0.79 0.80 1 0 0 0 0 0 0 0 1 0 0 0 0.44 0.5 0.5
79 [C4PyRR][Cl] 4.30 0.13 1 0 0 0 0 0 0 0 0 1 0 0 0.22 0 0
80 [C4Pyrrol][N(CF3SO2)2] 2.54 0.47 0 0 1 0 0 0 0 0 0 1 0 0 0.22 0 0
81 [C6MPyrrol][Cl] 2.99 0.38 1 0 0 0 0 0 0 0 0 1 0 0 0.33 0.5 0.5
82 [C4MMorp][Br] 4.30 0.13 1 0 0 0 0 0 0 0 0 1 0 0 0.22 0.5 0.5
83 [C4MMorp][N(CF3SO2)2] 2.49 0.48 0 0 1 0 0 0 0 0 0 1 0 0 0.22 0.5 0.5
84 [C4MPiper][Br] 4.27 0.14 1 0 0 0 0 0 0 0 0 1 0 0 0.22 0.5 0.5
85 [C4MPiper][N(CF3SO2)2] 2.56 0.47 0 0 1 0 0 0 0 0 0 1 0 0 0.22 0.5 0.5
86 [C4(CH3)2N-Py][Cl] 2.52 0.47 1 0 0 0 0 0 0 0 1 0 0 0 0.22 0 0
87 [C4(CH3)2N-Py] [N(CF3SO2)2] 1.85 0.60 0 0 1 0 0 0 0 0 1 0 0 0 0.22 0 0
88 [Choline][Cl] 5.00 0.00 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0
89 [Choline][N(CF3SO2)2] 4.15 0.16 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0
90 [TMG][TFA] 0.47 0.87 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0
91 [TMG][Ace] 3.17 0.35 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0
92 [TMG][TfO] 3.52 0.28 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0
93 [TMG][Cap] 2.29 0.52 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0
94 [Melanime][TFA] 2.24 0.53 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0
95 [Melanime][Ace] 2.39 0.50 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0
96 [Melanime][TfO] 2.45 0.49 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0
References: 1 to 9, 17 to 21, 90 to 96 from this work; 10, 53 from [44]; 11, 12, 30, 44, 49, 55, 58 from [15]; 13, 25, 31, 35, 37, 38 from [46]; 14, 43, 47, 77, 81 from [43]; 15, 32, 45, 56, 62,
64 to 66, 72, 79, 80, 82 to 87 from [47]; 16, 23, 26, 39 to 41, 50 to 52, 59 to 61, 63 from [13]; 22, 24, 28, 33, 46, 48, 54, 57 from [45]; 27, 29, 34, 36, 42, 67 to 71, 73 to 76, 78, 88, 89 from
[40].
Table 2
Descriptors of the QSAR model (15 descriptors).
Group Molecular
descriptor
Meaning
Anion (A) A1 Anions: Cl−
, BF4
−
, N(CN)2
−
, MetSO4
−
, EtSO4
−
, Br−
, PF6
−
,
pTs−
, and N(CF3)2
−
. Value=1 if it exists and 0 if not.
A2 Caprylate anion. Value=1 if it exists and 0 if not.
A3 Anions: Ace−
, For−
, TfO−
, 8OSO3
−
, (2-OPhO)2B−
,
N(CF3SO2)2
−
, and TFA−
. Value=1 if it exists and 0
if not.
Cation (C) C1 Imidazolium cation with Cb14 in R chain. Value=1
if it exists and 0 if not.
C2 Imidazolium cation with C=14 in R chain. Value=1
if it exists and 0 if not.
C3 Imidazolium cation with C=16 in R chain. Value=1
if it exists and 0 if not.
C4 Imidazolium cation with C=18 in R chain. Value=1
if it exists and 0 if not.
C5 Specific contribution of imidazolium with
N(CF3SO2)2
−
and specific contribution of
buthylimidazolium with TFA−
, Ace−
, TfO−
, Cap−
and For−
. Value=1 if it exists and 0 if not.
C6 Pyridinium, (dimethylamino)pyridinium, TMG and
choline cations. Value=1 if it exists and 0 if not.
C7 Pyrrolidinium, morpholinium and piperidinium
cations. Value=1 if it exists and 0 if not.
C8 Specific contribution of TMG with TFA−
. Value=1
if it exists and 0 if not.
C9 Melamine cation. Value=1 if it exists and 0 if not.
Substitution
(S)
S1 Number of carbons in long chain (S1 =C/Cmax;
C=number of carbons in R chain; and Cmax =18).
S2 Number of carbons in R1 chain (S1 =C1 /C1max;
C1 =number of carbons in R1 chain; and C1max =2).
S3 Number of short chains (S3 =n/nmax; n=number
of short chains; and nmax2).
31P. Luis et al. / Journal of Molecular Liquids 152 (2010) 28–33

5. magnitudes indicate the relative importance of the descriptors to the
target property, according to multiple linear regression models [31].
The data set has been fitted to the QSAR model using Polymath 5.0
software. The contributions (ai, cj and sk) of each group are shown in
Table 3 according to Eq. (2). The statistics of the fitting and the
distribution of the residuals are given in Tables 4 and 5, respectively.
In addition, a comparison between the experimental data for the
dimensionless ecotoxicity (Y⁎) of ionic liquids and the predicted value
based on the novel QSAR is shown in Fig. 2. Examination of the
residuals and visual analysis of Fig. 2 indicates that there are not any
outliers and 89% of the data show residuals lower than 0.10.
4. Discussion
From the performed QSAR model, the aquatic ecotoxicity (EC50
V. fischeri) of a broad number of ionic liquids can be predicted. The
model includes new cations and anions compared to previous works
[43], leading to a broader predictive range. From 96 experimental data
the number of ionic liquids whose ecotoxicity to V. fischeri can be
predicted is 10×6×18=1080, which are the anion–cation-substitu-
tions included in the statistical confidence (95%) of the model.
The influence of structural groups of the ionic liquids on the
ecotoxicity may be deduced from the contribution of each descriptor
(Table 3). According to the literature [13,44,47,50], ionic liquids with
the same cation and different anions do not show any statistical
difference in toxicity. This is true for the studied anions grouped in the
descriptor A1. In addition, they tend to decrease the ecotoxicity due to
the negative sign. However, when the caprylate anion is present in the
molecule, higher toxicity is expected because its contribution takes a
value of 0.28. On the other hand, more information related to the
anions grouped in the descriptor A3 is needed to get conclusions of its
ecotoxicity effect.
Regarding cations, it can be assumed that pyridinium, (dimethy-
lamino)pryridinium, tetramethylguanidine (TMG) and choline groups
contribute in a similar manner to the ecotoxicity. (Dimethylamino)
pryridinium is included in the descriptor C6 because of statistical
results but a deeper study should be performed since it would be
expected to have higher ecotoxicity than pyridinium or choline
cations, according to the literature [47]. These cations, grouped in the
descriptor C6, give higher toxicity to the ionic liquid (about 26%) than
the imidazolium cation (16%) but lower than the melamine cation
(50%), which is the most toxic studied cation.
Conclusions have not been obtained for the pyrrolidinium,
morpholinium and piperidinium groups due to the lack of data,
leading to a low confidence in the obtained contribution (C7).
In addition to this, the longer the R chain, the higher the toxicity;
this is in good agreement with previous results and this shows a
strong relationship between the ecotoxicity of an ionic liquid and
its hydrophobic character. The effect of short carbon chains on
ecotoxicity cannot be established due to the low confidence for these
contributions (S2 and S3).
However, it is worth noting the effect that long carbon chains
(longer than 14 carbon atoms) has in the ecotoxicity of imidazolium-
based ionic liquids. The descriptors C2, C3 and C4 indicate that a
decrease in toxicity is expected when the long carbon chain has 14, 16
and 18 carbon atoms, respectively, according to experimental data
[47]. This means that an increase in toxicity with each –CH2 group
diminishes (‘solubility cutoff’) for alkyl chains longer than 14 carbon
atoms.
Specific contributions (c5) have been found when the anion
N(CF3SO2) is present in an imidazolium-based ionic liquid or
the anions TFA, acetate, TfO, caprylate or formate are present in
butylimidazolium-based ionic liquids. These combinations reduce
the ecotoxicity (23%). However, the combination between the TMG
cation and TFA anion (c8) leads to a significant increase in ecotoxicity
(60%).
As it can be observed from the group contributions (Table 3), the
largest coefficient corresponds to the alkyl chain length descriptor and
it is not encoded in a Boolean manner, which emphasizes its higher
effect on the ionic liquid ecotoxicity for V. fischeri bacteria. This is in
good agreement with results shown in the literature [13,43,47,51,52]
that establish a strong relationship between the ecotoxicity and the
Table 4
Regression analysis.
Number of data 96
Number of descriptors 15
r2
0.924
radj
2
0.911
rmsd 0.0064
Variance 0.0046
Table 5
Distribution of residuals, calculated as the differences (absolute values) between the
experimental and estimated dimensionless ecotoxicity by the QSAR model.
Range QSAR model %
b0.10 85 89
[0.10–0.15] 8 8
N0.15 3 3
b0.20 All (96) 100
Fig. 2. Parity plot of dimensionless ecotoxicity.
Table 3
Group contributions to the dimensionless ecotoxicity.
Contribution of descriptors Value 95% confidence
a1 −0.303 0.104
a2 0.283 0.126
a3 0.006a
0.108
c1 0.161 0.108
c2 −0.210 0.181
c3 −0.482 0.187
c4 −0.915 0.194
c5 −0.229 0.063
c6 0.259 0.102
c7 0.011a
0.119
c8 0.605 0.140
c9 0.500 0.132
s1 1.843 0.140
s2 0.032a
0.138
s3 0.078a
0.124
a
Statistically with low confidence. More data are needed.
32 P. Luis et al. / Journal of Molecular Liquids 152 (2010) 28–33

6. hydrophobic character of the ionic liquid related to the ease of the
molecule to enter through cellular membranes.
5. Conclusions
A QSAR model to estimate the ecotoxicity (EC50 V. fischeri) of ionic
liquids has been carried out based on previous works and performing
the application to 96 data [43]. The model shows a group contribution
method that considers three main groups of descriptors in the ionic
liquid structure: the anion, the cation and the substitutions (carbon
chains linked to the cation). Based on these descriptors, their
contribution to the ecotoxicity of the ionic liquid has been evaluated
by means of a multilinear regression model. The data range for log
EC50 values is between 5 and −0.23 and it covers 9 kinds of cations
and 17 anions. The results were well correlated (r2
=0.924) but some
influences cannot be statistically established (e.g. pyrrolidinium,
morpholinium and piperidinium based ionic liquids). The main
contribution to the ecotoxicity is associated to the alkyl chain length
which is in good agreement with recent literature [13,43,47,51,52].
Acknowledgement
This research has been funded by the Spanish Ministry of Science
and Technology (Project CTM2006-00317).
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