Characterization of mesoporous aluminosilicate materials by means of inverse liquid chromatography

Journal of Chromatography A 1610 (2020) 460544

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Journal of Chromatography A
journal homepage: www.elsevier.com/locate/chroma

Characterization of mesoporous aluminosilicate materials by means of
inverse liquid chromatography
K. Adamska∗, A. Voelkel, M. Sandomierski
´ , Poland
Poznan University of Technology, Institute of Chemical Technology and Engineering, ul. Berdychowo 4, 60-965 Poznan

a r t i c l e

i n f o

Article history:
Received 17 July 2019
Revised 11 September 2019
Accepted 14 September 2019
Available online 14 September 2019
Keywords:
Mesoporous aluminosilicates
Inverse liquid chromatography
Surface characterization
Hansen solubility parameters
Linear free energy relationship

a b s t r a c t
Estimation of the properties of mesoporous aluminosilicates in various environments is important when

assessing their sorption capacity. Using inverse liquid chromatography (ILC), Hansen solubility parameters
(HSP) and linear free energy relationship (LFER) parameters were calculated to determine the properties
of aluminosilicates in a protic and an aprotic system, using water and acetonitrile as the mobile phase,
respectively. The calculated Hansen parameters, reflecting the ability of the material under investigation
to different types of intermolecular interactions, slightly differ depending on the mobile phase used. It
was found that in the presence of water the surface of aluminosilicates shows a weaker ability to interact,
as evidenced by negative or near-zero e, s, a, b, v coefficients. Additionally, it was found that the Si/Al ratio
in aluminosilicates structure has little effect on the determined parameters.
© 2019 The Authors. Published by Elsevier B.V.
This is an open access article under the CC BY-NC-ND license.
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1. Introduction
Applicability of many organic and inorganic solids is often determined by their surface sorption properties. Biomaterials and
chromatographic stationary phases should be without a doubt classified to this group of materials.
In 1992 the first information on new family of mesoporous
materials which have an ordered structure was reported [1]. These
silica materials with hexagonal, cubic or linear arrangement of
mesopores structure (M41S) were synthesized under hydrothermal conditions from silicate/aluminosilicate gels which contain
organic surfactant molecules as templates [1,2]. Mesoporous materials are popular due to their unique properties and application
possibilities in many fields of science and technology. Years of
research dedicated to improving the properties of these ordered
materials led to the new low-ordered mesostructures [3]. One
of these are MSU materials characterized by higher surface area
and better thermal stability than M41S. The abbreviation MSU
refers to mesoporous silica, mesoporous alumina and mesoporous
aluminosilicates [4,5]. Initially mesoporous materials were synthesized from “zeolite seeds” of zeolites such as faujastic and
templates (alkyl ammonium bromides) [6,7]. Despite many studies
on mesoporous materials there are few reports on their preparation from a solid silicon source. Solid silicon sources provide
∗

Corresponding author.
E-mail address: (K. Adamska).

more silicon to the reaction environment than the most commonly used sodium silicates. The new direction of the synthesis
of mesoporous materials is their preparation from less toxic and
less expensive substrates. Application during synthesis other substrates, templates and various Si/Al ratio has a major impact on
the properties (surface area, pore size and volume) of the resulting
aluminosilicates what further influences the sorption properties
of the material [8,9]. The new procedure of manufacturing aluminosilicate materials of different Si/Al ratio was proposed [10].
Authors suggested the use of Aerosil 200V, sodium aluminate,
silicon dioxide as silicon/aluminium sources and hexadecyltrimethylammonium bromide as crystal template as substrates.
The surface characteristic and the results of sorption experiments for hydrocarbons on studied mesoporous materials allow
to indicate the crucial surface parameters for adsorption process.
However, these materials were characterized as dry solids. During
separation procedures, e.g. extraction process, the particles of the
sorbent are surrounded by water, hydrocarbon solvent of water solution containing salt molecules. It may significantly influence the
surface properties of mesoporous species. Therefore, it seems to
be vital to estimate mesoporous materials sorption ability in real
system i.e. in environment where it usually “works”. Biomaterial
is surrounded by body fluid, while during the use of mesoporous
materials as sorbents the process is carried out by using mobile
phase in the form, e.g. of dilute water solution of inorganic salts.
There is a number of techniques, which enable to carry out
the characteristic of surface, including FTIR, Raman spectroscopy,

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2

K. Adamska, A. Voelkel and M. Sandomierski / Journal of Chromatography A 1610 (2020) 460544

X-ray diffraction, contact angle measurements and others [11–13].
Unfortunately, the measurements methodology of all mentioned
techniques do not allow to observe the influence of environment,
surrounding examined material on sorption properties. Depending
on physicochemical properties of liquid environment, the sorption
ability of material will be changed. A large number of other analytical methods can be used to study the sorption properties of nanomaterials in solutions (e.g. liquid NMR, analytical ultracentrifugation, isothermal titration calorimetry [14–16].
Inverse liquid chromatography (ILC) is a method of surface characterization, where an examined material is situated in chromatographic column. It allows to examine the changes of surface properties in diversified environment. The principle of measurements is
based on the determination of the retention factors for the test solutes, having specified physicochemical properties. These analytes
are introduced into the chromatographic system separately. The
column is filled with the examined material, which in this case
would be one of the mesoporous materials. The test solutes are
dissolved in specified solvent which is the same as applied mobile phase and then, every individual test compound is introduced
to the chromatographic column. Depending on the force of interactions between the test solute and the examined surface, the solutes leave the column with different retention times, which is the
basis for physicochemical characterisation. The retention parameter is a result of all occurring interactions in the system i.e. solute
– solvent, solute – stationary phase and solvent – stationary phase.
There are few procedures, involving inverse liquid chromatography usually used for physicochemical characterization of commercially available stationary phases e.g. surface excess isotherms
or surface energies, silanol activity and hydrophobicity or using an
aromatic sulphonic acids as a test compounds [17–21]. One of the
most relevant and commonly applied mathematical model, that
considers a retention parameter as a result of all interactions occurring in the chromatographic system is known as a linear free
energy relationship [22].
In the condensed phases strong attractive forces arises between
molecules, expressed as molar cohesive energy. It is defined as the
molar internal energy and is related to the evaporation energy at
a given temperature or internal pressure:

Ecoh =

U=

H − RT

(1)

where: Ecoh – cohesive energy, U –evaporation energy, H – enthalpy of vaporization, R – gas constant, T – temperature.
For liquids, assuming that the intramolecular properties are the
same in the gaseous and liquid state, the molar cohesive energy
can be represented as the sum of two factors: (a) molar evaporation energy needed to convert a moll of liquid into saturated
vapour, (b) the energy required to transfer saturated vapour to an
infinite volume at a constant temperature, i.e. the energy needed
to completely separate the particles:

−E =

g
U
l

+

V =∞
V =Vpar

∂U
∂V

dV

(2)

T

The cohesive energy related to the molar volume is called the
cohesion energy density, expressed as:

c=

−E
V

(3)

The concept of the solubility parameter was proposed by
Scatchard, Hildebrand to regular solutions, i.e. solutions that do not
show an entropy effect upon mixing. In practice, such type of solutions are rare. The proposed solubility parameter referred to the
systems in which cohesion resulted only from dispersive forces. It
is defined as the square root of cohesive energy density (CED) [23].

√

δ= c=

Ecoh
=
Vm

H − RT
Vm

(4)

where: δ - solubility parameter, R- gas constant, T- temperature,
H - enthalpy of vaporization, Vm - molar volume.
In 1966, Hansen proposed the concept of a solubility parameter, referring to the systems in which aside from dispersion interactions, polar and hydrogen bonding interactions may exist.
The basic equation representing Hansen’s assumptions is:

Ecoh = Ed + E p + Eh

(5)

where: d - dispersive, p - polar, h - hydrogen bonding.
The total cohesion energy includes the energetic contribution
brought by dispersive (non-polar), polar and hydrogen bonding
(specific) interactions. Dividing the energy by the molar volume:

Ep
Ecoh
E
E
= d +
+ h
Vm
Vm
Vm
Vm

(6)

a relationship, describing the total solubility parameter (Hildebrand

solubility parameter), is obtained as the sum of the dispersive δ d ,
polar δ p and hydrogen bonding δ h components:

δT2 = δd2 + δ 2p + δh2

(7)

δ T is also called the corrected solubility parameter.
It is assumed that materials having similar values of Hansen’s
parameters show high mutual affinity.
In the case of volatile substances the value of the solubility parameter can be determined using the enthalpy of evaporation from
the Eq. (4) [24,25]. However, for more complex systems or nonvolatile materials, it was necessary to develop other procedures to
determine the solubility parameter. One of the methods is to observe the dissolution capacity of a compound (e.g. a polymer) in
solvents with known value of the Hildebrand solubility parameter
[26]. It is assumed that the solubility parameter of the tested material (dissolved substance) is approximately equal to the solubility parameter of the solvent, in which the test material dissolves
or mixes with it in all proportions, without changing the enthalpy
and volume. A similar procedure is the measurement of polymer
swelling e.g. for cross-linked polymers, as well as semi-crystalline
materials [27]. Conducted observations of the studied systems enable to classify selected solvents for good, i.e. those that show a
stronger interaction with the tested material causing, for example,
dissolution, swelling, suspension and the bad, in which no changes
are observed. In the case of dye/solvent systems, the analysis is
made on the basis of determining the degree of suspension or sedimentation. Such characteristics of the systems studied are based
on relatively strong adsorption by some liquids compared to others.
Based on knowledge of the chemical structure of the compound, the solubility parameter can be calculated using the socalled additive methods. They are based on the assumption that
the total cohesion energy is the sum of energy contributed by each
functional group of the compound molecule. They enable the estimation of the total solubility parameter value and its individual
components [28]. Additive methods have found wide application
[29–33]. The calculated solubility parameter values for hydrocarbons and other compounds are acceptable, however, in many cases,
e.g. for large functional groups located around a central atom, the

obtained data may be affected by a large error. In molecules in
which, for example, spatial effects or couplings may exist, it can be
difficult to clearly determine the total cohesion energy. It should
be noted that in molecules in which there are several strongly
interacting functional groups (e.g. hydroxyl groups) additional intramolecular interactions, affecting the total cohesion energy of the
molecule, may appear apart from intermolecular interaction [29].
There are also other, indirect methods for determining the solubility parameter using, for example, molecular modeling.
Smidsrod and Guillet [34] were the first to apply the inverse gas
chromatography technique in studies of the interaction between


K. Adamska, A. Voelkel and M. Sandomierski / Journal of Chromatography A 1610 (2020) 460544

the solvent (test compound) and the polymer as the stationary
phase. As a result of interaction between them the obtained retention data are used to calculate the solubility parameter δ from
the Flory-Huggins interaction parameter χ1∞,2 .
The procedure proposed by Guillet has used Price [35,36] in
his research to determine the solubility parameter for compounds
with low molecular weights. According to his assumption, the
total solubility parameter resulted from the shares of two factors – dispersive δ d and polar δ p interactions. Voelkel and Janas
[37] have extended the group of test compounds to apply the
three-parameter Hansen equation.
The solubility parameter found the application in the description of the properties of diluted solutions, especially non-polar.
There are a number of relations that combine the solubility parameter with other physicochemical quantities, e.g. surface tension or
thermal expansion coefficient, so the concept of solubility parameter can be used in many fields to interpret some phenomena including mixing, adsorption and dissolution processes [38–41]. The
Hansen solubility parameter has found wide application in the selection of a solvent or solvent system for a particular material in
the industry coatings industry, cleaning agents or printing inks
[39,42–44]. Solubility parameters have been applied extensively in
the pharmaceutical sciences. The use of this parameter in the pharmaceutical industry has been described in detail by Hancock et al.
[45], showing how this factor is used to assess the properties of

unknown materials, the impact of technological processes on the
properties of materials, as well as estimation of interactions and
incompatibilities between materials. It can be used also to assess
the bioavailability/solubility of various types of active substances
[46–49]. The concept of the Hansen Solubility Parameter (HSP) has
been also used in the studies on the affinity between the adsorbent and organic solvent [50], a dispersion of carbon fillers and
polymer matrix [51] or to determine the inter-molecular interactions in ionic liquid/solvent system [52].
Karger et al. [53] described various chromatographic processes
using the concept of solubility parameter. The authors used components of solubility parameters, responsible for different types of
intermolecular interactions to describe retention in various types
of chromatography: gas - solid, gas - liquid, liquid - solid and liquid
- liquid. The general description of the model was based on evaporation, dissolution, mixing and adsorption processes taking place in
the chromatographic system. These considerations gave the background of our investigations.
The energy of interactions between solid adsorbent (ad) and
sorbate (test solute) (i) ( Elsc ) is given by the Eq. (8) [53]. One
should take into account also interaction between the molecules
of adsorbing test solute and molecules of mobile phase (j).

EA

Elsc = −n

j/ad

− ( E s )i/ j +

EA

i/ j

+

EA

(8)

i/ad

where: j = mobile phase; ad – adsorbent; i = solute; EA – energy
of adsorption, Es – solubilization energy.
The respective energetic contribution may be expressed in
terms of components of solubility parameter [53]:

( E s )i/ j = V i δ j

2

i
− 2δdi δdj − 2δoi δoj − 2δin
δinj − 2δai δbj − 2δaj δbi

EA

i/ad

= Vi

δdi δdad + δoi δoad + δinad δdi + δini δdad + δai δbad + δaad δbi
(10)

Elsc =

E

A

Ai
−
i/ad
Aj

E

A

parameter corresponding to dispersive, orientation forces, inductive, proton donor ability and proton acceptor ability interactions,
respectively.

Elsc = −RT lnVNi

(12)

VNi

– net retention volume of the test solute “i” in ILC experiment.
It leads to

Vi

δdi δ add + δoi δoad + δinad δdi + δini δdad + δai δbad + δaad δbi

−

Ai i
V
Aj

δdj δdad + δoj δoad + δinad δdj + δinj δdad + δaj δbad + δaad δbj = − RT lnVNi
(13)

and finally to

−RT lnVNi
= δdad
Vi

δdi + δini −

δi

δj

Ai , Aj – molecular area of “i” and “j”;
– solubility parameter
of “i” and “j”; indices d, o, in, a, b – denote component of solubility

δai −

Ai j
δ

Aj a

+ δoad

δoi −

Ai j
δ
Aj o

−RT lnVNi
ad
= δdadW 1 + δoadW 2 + δin
W 3 + δbadW 4 + δaadW 5
Vi

(15)

+ δbad

+ δaad

δbi −

Eq. (15) is polynomial where:

δdi + δini −

W1 =

W2 =

δoi −

Ai j
δ
Aj o

W3 =

δdi −

Ai j
δ
Aj d

W4 =

δai −

Ai j
δ
Aj a

W5 =

δbi −

Ai j
δ

Aj b

Ai
Aj

δdj + δinj

However, there is a lack of the respective data for components
expressing the ability to inductive and orientation interactions.
Therefore, we have adapted the idea of Hansen solubility parameter to solve this problem. For the system in liquid-solid chromatography (LSC) one obtains:
Eqs. (11) and (12) remain unchanged and

δai + δbi = δhi

(16)

δaj + δbj = δhj

(17)

δai + δbi · δaj + δbj = δai δaj + δai δbj + δbi δaj + δbi δbj

(18)

but δai δa = 0 and δbi δb = 0 as the proton donor ability or proton
acceptor ability of test solute and mobile phase molecules do not
influence the magnitude of their interactions.
This leads to
j

δhi · δhj = δai δbj + δbi δaj

(11)

j/ad

δdj + δinj

(14)

δdi −

Ai j
δ
Aj d

Ai
Aj

Ai j
δ
Aj b

ad
+ δin

j

(9)

3

Vi

i ad
−
δdi δ add + δ ip δ ad
p + δh δh

(19)
Ai i
V
Aj

j ad
= −RT lnVNi
δdj δ add + δ pj δ ad
p + δh δh

(20)


4

K. Adamska, A. Voelkel and M. Sandomierski / Journal of Chromatography A 1610 (2020) 460544

We have introduced the component corresponding to ability to polar interactions (δ ip ) instead of orientation and inductive forces –
due to the unavailability of such data in the literature.

Vi

δ add δdi −

Ai j
δ
Aj d

+ δ ad
p

δ ip −

Ai j
δ
Aj p

+ δhad

δhi −

Ai j
δ
Aj h

= −RT lnVNi
−RT lnVNi
= δ add
Vi

(21)

δdi −

Ai j
δ
Aj d

+ δ ad
p

δ ip −

Ai j
δ
Aj p

+ δhad

δhi −

Ai j
δ
Aj h
(22)

The values in brackets on the right side of Eq. (22) are constant for
the given adsorbent, the test solute and the mobile phase (molecular area of the molecule of mobile phase is required). The values of HSP for the adsorbent (examined material) are unknown
and these values might be calculated by using multilinear regression. A more detailed description of HSP determination is given in
Section 2.4.
The linear free energy relationship (LFER) was used, which involves five independent parameters characterising physiochemical

properties of the examined surface [54].
Since 1980’s the mathematical correlation of the retention parameters with physicochemistry of solute-sorbent interaction has
attracted more attention. Abraham and co-workers adapted Kamlet and Taft solvatochromic methods to chromatographic analysis, giving it the form of linear free energy relationship (LFER)
[20]. In this mathematical relationship, the retention parameter
depends on solute solvation process, which has been identified
and dissected into four types of solute-solvent interaction: cavity formation-dispersive interaction, dipolarity-polarizability interaction and acidity or basicity hydrogen bonding interaction. In
the case of liquid chromatography, one can observe three types
of interactions: solute-stationary phase, solute-mobile phase and
stationary phase-mobile phase. All these interactions have a major influence on the observed retention parameter. One of more
widely accepted symbolic representations of LFER model in the
form of multiple linear regression equation was presented by
Abraham:

log k = c + eE + sS + aA + bB + vV

(23)

where: log k is the logarithm of the solute retention factor, c is
the linear regression coefficient. The capital letters E, S, A, B and
V corresponds to the solute descriptors, independent on the mobile/stationary phase used; E is the excess molar refraction, S –
dipolarity/polarizability descriptors, A and B correspond to the solute hydrogen bond acidity and basicity respectively, and V is the
McGowan volume of the solute. The lowercase letters e, s, a, b,
v are the system parameters reflecting the difference in solute
interaction between the mobile and stationary phase. Therefore,
the value of the above-mentioned parameters might be useful for
description of the physicochemical properties of material surface
(in a given chromatographic conditions: mobile phase composition
and temperature) and estimation of the surface ability to different
types of intermolecular interactions.
The aim of the study was to introduce the new procedure for

the estimation of Hansen Solubility Parameters. Moreover the goal

of this work was to estimate physicochemical properties of mesoporous materials surface in aquatic and non-aqueous systems. To
estimate those properties, we planned to use five descriptors (e, s,
a, b, v) of linear free energy relationship adopted for liquid chromatography as well as HSPs data.
2. Experimental
2.1. Materials
Mesoporous aluminosilicates with a different Si/Al ratio
(Table 1) were prepared according to the following procedure
(Table 2): NaOH (A) and NaAlO2 (B) were dissolved in the distilled
water (C). Then, a silicon source: silicon dioxide (D) or Aerosil
200V (D) was added to NaOH (E) dissolved in the distilled water
(F). Next silicon and aluminum mixtures were mixed in different
ratios and stirred (700 rpm) for 1 hour and then heated and stirred
at 100 °C for 24 h. Subsequently mixture was mixed with solution
of hexadecyltrimethylammonium bromide (CTAB, 18 g in 572 ml
of distilled water). After 1 h stirring H2 SO4 was added to obtain
pH = 9–10 and then mixture was stirred for 24 h. The samples
were crystallized for 48 h at 100 °C. The resulting materials were
filtered, washed with distilled water and dried. The last step was
removal of the template by calcination at 540 °C for 7 h. A detailed analysis of the materials is presented in the following publications [55–57]. The real Si/Al ratio, given in Table 1, was determined from EDS results obtained using EDS Octane SDD detector
made by EDAX. The maximum size of agglomerated particles is
60 μm for AS4 material [55,56]. In the case of others it does not
exceed 20 μm.
2.2. ILC experiments
ILC experiments were conducted by using Dionex Ultimate
30 0 0 liquid chromatograph. equipped with refractive detector
(Shodex, Ltd. USA). Empty stainless steel column (2.0 mm
i.d × 100 mm) were used. Columns were filled with materials in
the dry state using a semi-automated column packer designed for

packing of inverse gas chromatographic columns (Surface Measurements System Ltd. London, UK). Column ends were sealed with
stainless steel frit inserts. After packing, the column were conditioned at the measuring temperature of 30 °C and with a mobile
phase flow of 0.2 ml/min before the experiment started, in order
to stabilize the pressure in the column and the base line of the detector. The mobile phase used in experiments were acetonitrile for
HPLC (Sigma-Aldrich) and distilled water. All test compounds were
dissolved in proper mobile phase at concentration 10 mg/ml. The
injection volume was 10 μl. Test solutes were injected separately
and due to this on ILC chromatograms single peaks were recorded.
Examples are presented in Fig. 1.
Retention factor is given as:

k=

t
tR − t0
= R
t0
t0

(24)

where: k is the retention factor, t R – the corrected retention times,
t0 – the retention time of the non-retained substance.

Table 1
Description of the examined materials.
Material abbreviation

Silicon source

Assumed Si/Al ratio

Real Si/Al ratio

AS1
AS2
AS4
M4

silicon dioxide
silicon dioxide
silicon dioxide
Aerosil 200V

18:2
13:7
7:13
7:13

13.16
2.61
0.71
0.69


K. Adamska, A. Voelkel and M. Sandomierski / Journal of Chromatography A 1610 (2020) 460544
Table 3
Descriptors of the test solutes [59–62].

Table 2

The amount of substrates used during the synthesis [g].
Material

A

B

C

D

E

F

AS1
AS2
AS4
M4

0.9
3.15
5.85
5.85

2
7
13
13

16
56
104
104

18
13
7
7

9.4
6.79
3.66
3.66

40
29
15.5
15.5

5

Test
solute

Descriptor

1,3-diaminopropane
1,3-propanediol
1,4-dioxane

1-propanol
Acetic acid
Acetonitrile
Acetophenone
Aniline
Benzonitrile
Butanone
Caffeine
Cyclohexanone
Cyclohexanol
Diethyl ether
Ethyl acetate
Geraniol
N,N-dimethylformamide
Phenol
Propylamine
Pyridine
Tetrahydrofuran

E

S

A

B

V

0.446

0.397
0.329
0.236
0.265
0.237
0.818
0.955
0.742
0.166
1.500
0.403
0.460
0.041
0.106
0.513
0.367
0.805
0.225
0.631
0.289

0.610
0.910
0.750
0.420
0.640
0.900
1.010
0.960
1.110

0.700
1.600
0.860
0.540
0.250
0.620
0.630
1.310
0.890
0.350
0.840
0.520

0.430
0.770
0.000
0.370
0.620
0.070
0.000
0.260
0.000
0.000
0.000
0.000
0.320
0.000
0.000
0.390
0.000

0.600
0.160
0.000
0.000

1.140
0.850
0.640
0.480
0.44
1.739
0.480
0.500
0.330
0.510
1.330
0.560
0.570
0.450
0.450
0.660
0.740
0.300
0.610
0.452
0.480

0.731
0.649
0.681

0.590
0.4648
0.404
1.014
0.816
0.871
0.688
1.363
0.861
0.904
0.731
0.747
1.490
0.647
0.775
0.631
0.675
0.622

2.3. LFER calculations
Each test compound was injected five times. Q-Dixon Test was
applied to reject of outliers. The average value of retention time
was used to calculate the log k. The LFER coefficients were calculated according to Eq. (23) using the test compound descriptors
given on Table 3.
2.4. HSP calculations

Fig. 1. Caffeine chromatograms for AS2 material, mobile phase (a) water, (b) acetonitrile.

The retention time of the non-retained substance was calculated according to the equation:

V0 = F · t0

(25)

t0 = V0 /F

(26)

where: V0 – the void volume, F – the flow rate [ml/min].
The void volume of the filled column was determined by the
pycnometric method [58]. Using such procedure four different solvents having different densities were used: acetonitrile, dioxane,
heptane and dichloromethane (Sigma-Aldrich). The void volume
was calculated from the following equation:

V0 = (w1 − w2 )/(d1 − d2 )

(27)

where: w1 , w2 are the mass of the column filled with solvent [g]
with different densities d1 and d2 .
Group of selected test solutes with different chemical structure and properties i.a. polarity, electron donor-acceptor were
chosen for ILC experiments. All test solutes were at least of analytical grade: aniline, butanone, diethyl ether, phenol, pyridine, propylamine (AVANTOR), benzonitrile, cyklohexanol, cyclohexanone,
1,3-diaminopropane, 1,4-dioxane, geraniol, caffeine, acetic acid,
N,N-dimethyloformamide, ethyl acetate, propanol, 1,3-propanediol,
tetrahydrofurane (Sigma-Aldrich), acetophenone (Fluka).

HSPs parameters were found by solving Eq. (22). One should
collect the retention data for series of the test solutes. The set of
Eq. (22) equal to the number of applied test solutes is obtained.
Molar volume of the test solute, molecular area of adsorbing test

solute, molecular area of the molecule of mobile phase as well as
HSPs data for test solute are collected in Table 4.
Molecular area of test solutes was calculated using procedure
proposed by Diaz et al. [63] assuming a spherical molecular shape
in a hexagonal close-packing configuration [64]:

A = 1.09 × 1014

M
ρN

2/3

(28)

where: M – molecular mass, ρ – density, N – Avogadro number.
3. Results and discussion
The main purpose of the work was to estimate the physicochemical characteristic of mesoporous materials surface in aquatic
and non-aqueous systems. The experiments were carried out in
two polar solvents of various chemical nature - protic water and
aprotic acetonitrile.
The physicochemical characteristics were calculated using the
values of retention coefficients calculated for a range of the test
compounds. Application of Hansen solubility parameters concept
allowed the determination of the ability of a materials surface to
different intermolecular interaction, whereas parameters calculated
from Abraham model reflect the behaviour of the materials in different systems.
Differences in the properties of the examined, materials depending on the mobile phase used can be observed by comparing the data of retention factors, obtained for a series of test

6

K. Adamska, A. Voelkel and M. Sandomierski / Journal of Chromatography A 1610 (2020) 460544
Table 4
Physicochemical data for HSPs calculation.
Physicochemical parameter∗
Test
solute

δd

1,3-diaminopropane
1,3-propanediol
1,4-dioxane
1-propanol
Acetic acid
Acetonitrile
Acetophenone
Aniline
Benzonitrile
Butanone
Caffeine
Cyclohexanone
Cyclohexanol
Diethyl ether
Ethyl acetate
Geraniol
N,N-dimethylformamide
Phenol
Propylamine

Pyridine
Tetrahydrofuran
Ibuprofen
Water
∗

[MPa0.5 ]

[MPa0.5 ]

δp

[MPa0.5 ]

δh

A
[m2 ]∗ 10−19

V
[cm3 mol−1 ]

13.9
16.8
17.5
16.0
14.5
15.3
18.8
20.1

18.8
16.0
19.5
17.8
17.4
14.5
15.8
16.3
17.4
18.5
16.0
19.0
16.8
16.6
15.6

12.9
13.5
1.8
6.8
8.0
18.0
9.0
5.8
12.0
9.0
10.1
8.4
4.1
2.9

5.3
4.1
13.7
5.9
4.9
6.5
5.7
6.9
16.0

14.7
23.2
9.0
17.4
13.5
6.1
4.0
11.2
3.3
5.1
13.0
5.1
13.5
5.1
7.2
11.3
11.3
14.9
8.6
5.9

8.0
10.0
42.3

7.27
5.16
7.33
5.61
3.28
2.73
13.6
8.35
10.6
8.04
25.0
10.7
10.9
10.8
9.56
30.2
6.00
7.73
6.71
6.50
6.59
39.7
10.60

74.1
72.5

85.7
75.1
57.6
52.9
99.2
91.6
103.2
90.2
157.9
104.2
105.7
104.8
98.6
173.5
77.0
88.9
83.0
80.9
81.9
199.0
18.0

HSPiP software

Table 5
Values of retention factor - k of test solutes for materials; mobile phase – acetonitrile and water.

Test
solute
1,3-diaminopropane

1,3-propanediol
1,4-dioxane
1-propanol
Acetic acid
Acetonitrile
Acetophenone
Aniline
Benzonitrile
Butanone
Caffeine
Cyclohexanone
Cyclohexanol
Diethyl ether
Ethyl acetate
Geraniol
N,N-dimethylformamide
Phenol
Propylamine
Pyridine
Tetrahydrofuran

Acetonitrile
k
AS1
0.185
0.790
0.320
nd
0.357
nd

0.203
0.239
0.197
0.223
0.916
0.241
0.330
0.239
0.208
0.226
0.839
0.195
0.166
0.834
0.305

Water
k

AS2
∗

nd
0.308
0.341
0.403
0.151
nd
0.189
0.348

0.144
0.263
0.771
0.165
0.618
0.217
0.159
0.666
0.389
0.510
0.489
nd
0.298

AS4

M4

AS1

AS2

AS4

M4

0.119
nd
0.212
nd

0.103
nd
0.118
0.209
0.117
0.139
1.152
0.137
0.189
0.130
0.124
0.820
0.863
0.181
0.110
0.104
0.174

0.136
0.119
0.171
nd
0.167
nd
0.135
0.227
0.130
0.140
0.965
0.154

0.306
0.141
0.142
0.818
0.753
0.476
0.128
0.450
0.174

nd
0.632
0.620
0.596
0.599
0.605
nd
0.626
nd
0.660
0.667
0.603
0.615
nd
nd
nd
0.655
0.656
nd
0.618

0.661

nd
0.195
0.256
0.241
0.222
0.211
nd
0.257
nd
0.200
0.350
0.255
0.200
nd
nd
nd
0.206
0.215
nd
0.255
0.215

nd
0.238
0.231
0.234
0.235
0.210

nd
0.242
nd
0.233
0.289
0.212
0.233
nd
nd
nd
0.239
nd
nd
0.241
0.208

nd
0.014
0.072
0.011
0.166
0.013
nd
0.284
nd
0.115
0.310
0.063
0.255
nd

nd
nd
0.203
nd
nd
0.113
0.112

(nd∗ ) – no data (no retention data obtained).

solutes in water and acetonitrile (Table 5) with a standard deviation of 0.001–0.01. Considering water the retention factors values of the test compounds are very similar, what indicates lower
selectivity of the system. In the case of acetonitrile, more varied values of retention factors were obtained. The most retained
test solutes in acetonitrile was caffeine. This may be due to the
fact that caffeine has two functional groups - the tertiary amine
and amide groups. They can form hydrogen bonds with hydroxyl
group of aluminosilicates just using the lone pair on the nitrogen. In water such interactions between caffeine and the surface
of aluminosilicates can be disturbed as a result of the formation of dimers or higher order aggregates by caffeine in aqueous
media.

It can be observed that ability of the materials to a specific type
of interaction, described using the Hansen parameters, slightly differ depending on the mobile phase used (Tables 6 and 7).
The materials in acetonitrile characterizes slightly higher values of HSP data. Higher values for dispersive interactions are observed, whereas values for polar and hydrogen bonding are almost
the same.
Material AS2 exhibits the highest values for polar, hydrogen
bonding and total solubility parameter both in water and acetonitrile as mobile phase from all of the examined materials.
In water as mobile phase the ability to interactions is insignificantly lover as evidenced by the lower values of the HSP components, what can be caused by the formation of the hydration layer


K. Adamska, A. Voelkel and M. Sandomierski / Journal of Chromatography A 1610 (2020) 460544
Table 6

Hansen solubility parameters for examined mesoporous materials (mobile phase –
acetonitrile).

δd

Material

[MPa0.5 ]

AS1
AS2
AS4
M4

15.93
16.32
15.69
16.66

±
±
±
±

δp

δh

[MPa0.5 ]
0.12

0.13
0.11
0.12

13.19
13.68
12.25
12.65

±
±
±
±

0.09
0.11
0.08
0.19

δT

[MPa0.5 ]

[MPa0.5 ]

12.50 ± 0.12
12.84 ± 0.12
12.33 ± 0.12
9.83 ± 0.12

24.16
24.87
23.41
23.12

±
±
±
±

0.09
0.05
0.06
0.10

Table 7
Hansen solubility parameters for examined mesoporous materials (mobile phase –
water).

δd

Material

[MPa0.5 ]

AS1
AS2
AS4
M4

16.52
16.27
15.62
15.54

±
±
±
±

δp

δh

[MPa0.5 ]
0.13
0.12
0.11
0.18

12.23
13.09
12.23
12.18

±
±
±
±

0.08
0.10
0.05
0.10

δT

[MPa0.5 ]

[MPa0.5 ]

10.02 ± 0.08
12.72 ± 0.09
12.10 ± 0.07
9.33 ± 0.10

23.52
24.45
23.23
21.84

±
±
±
±

0.14
0.15
0.14
0.22

Table 8
Abraham parameters for examined mesoporous materials (mobile
phase – water).
Material

e

s

a

b

v

AS1
AS2
AS4
M4

0.027
0.024
0.003
−0.405

0.037
−0.071
0.037
1.748

−0.039
−0.046
0.023
0.424

−0.014
0.0427
−0.055
−3.214

−0.031
0.008
−0.002
1.802

7

Table 9
Abraham parameters for examined mesoporous materials (mobile
phase – acetonitrile).
Material

e

s

a

b

v

AS1
AS2
AS4
M4

−0.141
0.151
−0.464
0.104

0.530
−0.264
0.878
0.401

0.039
0.362
0.251
0.243

0.329
0.291
0.561
−0.146

−0.317
0.348

−0.078
−0.312

4. Conclusions
Mesoporous materials were examined by means of inverse liquid chromatography. Hansen solubility parameters and Abraham
parameters were used to express the ability of mesoporous aluminosilicates to interact with different environment. The relatively
weak influence of the composition (Si/Al ratio) of these materials on the presented characteristics was found. Much more important was the influence of the environment of material (the mobile phase used). The comparison of the values of both groups of
estimated parameters showed that the presence of protic solvent
decreases the activity of examined material. The findings of this
paper are important as they present the ability to characterize the
material which may change their properties in changing surrounding. Calculated parameters may be useful in assessing the suitability of mesoporous materials in sorption processes during the solidphase extraction process from various solutions.
Declaration of Competing Interest

on the surface, blocking the active group and reducing the ability
to interaction in the presence of water. In water as mobile phase
together with the decrease Si/Al ratio (materials AS1-AS4, M4), the
decrease of δ d is observed.
According to ref. [65] e, s, a, b, v parameters reflect the difference in interaction in solute/mobile phase and solute/stationary
phase systems. A positive values of the parameters indicate that
given type of interaction, described by Abraham parameters, is
more favorable for the stationary phase. However, if the given type
of interaction is more significant between solute and mobile phase,
the values are negative. Therefore, a positive values are taken to
consideration to characterize the properties of the stationary phase
(investigated material).
Considering the data received for water, given in Table 8 it can
be concluded, that OH groups on the surface of materials can form
hydrogen bonds with a protic solvent. As a result, the aluminosilicate surface in these conditions has a limited ability to interact
with the test solutes, as shown by close to zero or negative values
of Abraham parameters. For M4 the highest values for s, a and v

parameter are observed. This indicates that such surface is involved
in dipole-dipol (s) interactions. Additionally the highest value of
a coefficient (a = 0.424) indicates higher basicity of the surface,
which may affect stronger interaction with hydrogen-bond donor
solutes. A positive value of v term indicates, that the test solute
will preferentially transfer from the mobile phase to the stationary
phase.
Comparing the data obtained for acetonitrile (Table 9), they are
higher than for water. In addition, positive values of Abraham parameters are not close to zero, as in the case of water. This denotes
the greater ability of the surface for interaction with test solutes.
The positive value of a coefficient indicates higher basicity of aluminosilicates surface in the presence of acetonitrile, which should
reflect stronger interactions with hydrogen-bond donor solutes. For
almost all materials its acidic properties (parameter b) are little
higher than basic (parameter a). Based on this, the ability of the
surface to interaction with basic solutes should be stronger.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to
influence the work reported in this paper.
Acknowledgement
This work was supported by the National Science Centre, Poland
under research project no. UMO-2015/17/B/ST8/02388.
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