J IRAN CHEM SOC
until the reaction was completed. The same procedure was
applied on 1.0 9 10-2 M of NaBH4 and 4.0 9 10-4 M of
MFB. After each addition, the solutions were stirred for
3 min and the absorbance spectra were recorded over the
reagent and blank (NaBH4 solution was added to pure
solvent in the same concentrations as blank).
respectively. Herein, C and S are containing, respectively,
the concentration profiles and pure spectra of the species
coexisting in the studied reactions. Equation (1) proposes
the matrix notation valid for the general MCR procedures:
D ¼ CST þ R
ð1Þ
where R (m 9 n) is being the matrix of residual variation
of the data matrix not modeled by the employed MCR
method [20].
For monitoring of the acetylation reaction, a 3.0-ml
portion of 5.0 9 10-5 M of PAP in acetonitrile was
transferred to the quartz cell and certain amounts (i.e.,
10.0 lL) of the acetyl chloride solution (3.0 9 10-3 M) in
acetonitrile was added to the sample solution. After each
addition, the resulting solutions were stirred for 3 min
following with UV–vis measurement in the same manner
as explained for reduction of MFB.
Since its introduction, MCR-ALS method has received
wide applications among the scientific community. The
first step in MCR-ALS is determination of r (i.e., the
number of systematic contributions in the data matrix D).
Here, the absorbance data matrix was subjected to factor
analysis (FA) [21] to evaluate the number of significant
components. The next step involves in an initiate estima-
tion for either C or S. In this regard, we used evolving
factor analysis (EFA) [22] to suggest an estimate of con-
centration profile (C).
Each recorded absorbance spectrum was digitized in
1 nm intervals and saved as a row vector of length of n,
where n is the number of absorbance readings per spec-
trum. Thus, the digitized absorbance spectra obtained in a
course of a reaction were collected below each other to
form an absorbance data matrix (D) of size of (m 9 n),
where m is number of recorded spectra per experiment or
the number of molar ratios of reagent to substrate, at which
the absorbance spectra were recorded.
It should be noted that the reduction of MFB was
monitored at two different initial concentrations of sub-
strate, while the molar ratios of reagent to substrate at two
experiments were taken the same, whereas wavelength
ranges were different. In this case, row augmentation of the
absorbance data matrices was adapted and MCR-ALS was
run on individual matrices as well as the augmented data
matrix.
Chemometrics procedure
Multivariate curve resolution techniques, as types of soft-
modeling methods, have been proposed for the recovery of
the response profiles (spectra, pH profiles, time profiles,
elution profiles) that comprise more than one component in
an unresolved mixture (obtained from evolutionary pro-
cesses). These methods have been when little or no back-
ground is available about the nature and composition of the
mixture [19]. MCR methods attempt to resolve mixed
evolutionary profiles without presupposing a well-defined
shape function. Instead, concerning the general shape of
the profile and spectra, they impose known constraints such
as: (1) unimodality constraint (each component profiles has
only one maximum); (2) non-negativity constraint (all
points in the concentration and component spectra profiles
must be greater than or equal to zero); and (3) closure
constraint (the sum of species concentration is a known
constant value, i.e., in reaction-based systems, it is known
as mass balance equation). MCR produce a mathematical
decomposition of a multivariate multicomponent experi-
mental data matrix D (m 9 n), which represents the total
instrumental response of a system, into the product of two
simpler matrices C (m 9 r) and ST (r 9 n), which are the
pure response profiles of the r individual contributions
making up the system. The scalar r can be considered as
the number of light-absorbing species evolved or decayed
in the course of reaction. The matrices C and ST are related
to the data variation in the row and column directions of D,
The MCR-ALS subroutine written by Tauler and
coworkers was applied to resolve the components pure
spectra and their corresponding concentration profiles. The
Results and discussion
Reduction of MFB by sodium borohydride
Herein, we aimed to represent a simple analytical meth-
odology to monitor the progress of organic reactions, by
which we can judge the selectivity at each reaction stage.
MFB was used as a model substrate (Fig. 1) due to having
both aldehyde and ester groups. According to the literature
[23], NaBH4 as a mild reducing agent, first attacks the
aldehyde functional group and then attack that of ester for
both electronic and steric reasons [23, 24]. We used a
spectroscopic method, as an alternative to separation
methods, to confirm the above statement.
The changes in the absorbance spectra of the ethanolic
solution of MFB (4.0 9 10-5 M) upon addition of differ-
ent quantity of reductant are represented in Fig. 2a. We
used this concentration to have more precise absorbance
data (1.0 \ absorbance \ 0.5). As it is observed, the MFB
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