Photochemical redox reactions of copper(II)-alanine complexes in aqueous solutions

Article abstract of DOI:10.1021/ic4031238

The photochemical redox reactions of Cu(II)/alanine complexes have been studied in deaerated solutions over an extensive range of pH, Cu(II) concentration, and alanine concentration. Under irradiation, the ligand-to-metal charge transfer results in the reduction of Cu(II) to Cu(I) and the concomitant oxidation of alanine, which produces ammonia and acetaldehyde. Molar absorptivities and quantum yields of photoproducts for Cu(II)/alanine complexes at 313 nm are characterized mainly with the equilibrium Cu(II) speciation where the presence of simultaneously existing Cu(II) species is taken into account. By applying regression analysis, individual Cu(I) quantum yields are determined to be 0.094 ± 0.014 for the 1:1 complex (CuL) and 0.064 ± 0.012 for the 1:2 complex (CuL₂). Individual quantum yields of ammonia are 0.055 ± 0.007 for CuL and 0.036 ± 0.005 for CuL₂. Individual quantum yields of acetaldehyde are 0.030 ± 0.007 for CuL and 0.024 ± 0.007 for CuL₂. CuL always has larger quantum yields than CuL₂, which can be attributed to the Cu(II) stabilizing effect of the second ligand. For both CuL and CuL₂, the individual quantum yields of Cu(I), ammonia, and acetaldehyde are in the ratio of 1.8:1:0.7. A reaction mechanism for the formation of the observed photoproducts is proposed.

Full text of DOI:10.1021/ic4031238

Article
pubs.acs.org/IC
Photochemical Redox Reactions of Copper(II)−Alanine Complexes in
Aqueous Solutions
Chen-Jui Lin, Chao-Sheng Hsu, Po-Yen Wang, Yi-Liang Lin, Yu-Shiu Lo, and Chien-Hou Wu*
Department of Biomedical Engineering and Environmental Sciences, College of Nuclear Science, National Tsing Hua University,
Hsinchu 30013, Taiwan
S
* Supporting Information
ABSTRACT: The photochemical redox reactions of Cu(II)/alanine com-
plexes have been studied in deaerated solutions over an extensive range of pH,
Cu(II) concentration, and alanine concentration. Under irradiation, the ligand-
to-metal charge transfer results in the reduction of Cu(II) to Cu(I) and the
concomitant oxidation of alanine, which produces ammonia and acetaldehyde.
Molar absorptivities and quantum yields of photoproducts for Cu(II)/alanine
complexes at 313 nm are characterized mainly with the equilibrium Cu(II)
speciation where the presence of simultaneously existing Cu(II) species is taken
into account. By applying regression analysis, individual Cu(I) quantum yields
are determined to be 0.094 0.014 for the 1:1 complex (CuL) and 0.064
0.012 for the 1:2 complex (CuL2). Individual quantum yields of ammonia are
0.055 0.007 for CuL and 0.036 0.005 for CuL2. Individual quantum yields
of acetaldehyde are 0.030 0.007 for CuL and 0.024 0.007 for CuL2. CuL
always has larger quantum yields than CuL2, which can be attributed to the Cu(II) stabilizing effect of the second ligand. For
both CuL and CuL2, the individual quantum yields of Cu(I), ammonia, and acetaldehyde are in the ratio of 1.8:1:0.7. A reaction
mechanism for the formation of the observed photoproducts is proposed.
reactions of Cu(II) complexes with various organic ligands
are of crucial importance for their potential uses in environ-
mental, industrial, and biological processes.
INTRODUCTION
■
There has been growing interest in the photochemical reactions
of copper complexes in the environment and in biochemis-
try.1−8 Copper is a ubiquitous transition metal, which has two
accessible oxidation states. In natural waters and wastewaters,
Cu(II) is thought to be present primarily as complexes with
biogenic or anthropogenic ligands, many of which contain
carboxylato and amino functional groups.9−12 Copper com-
plexes can participate in a large number of photochemical redox
reactions in sunlit surface waters. The sunlight-initiated
photoreactions of Cu(II) complexes may have significant
effects on the speciation and geochemical cycling of copper,
which, in turn, can affect the bioavailability or toxicity of copper
in the upper water column.13−16 The photoreactions of Cu(II)
complexes are also accompanied by degradation of organic
ligands or pollutants, which can contribute to the pollution
abatement.3 Photooxidation of Cu(II) complexes with
pollutants, such as EDTA, NTA, and IDA, widely used in the
detergent industry has been extensively studied in homoge-
neous and heterogeneous systems.2,17−20 In the area of
medicinal chemistry, copper complexes with various drugs
may exhibit better biological activity in comparison to the drugs
themselves.21 The photoredox reactions of copper complexes
can be used acting as redox scavengers for radicals photo-
generated from drugs and biomolecules in antitoxic protective
processes.6,22,23 Several photolabile copper cages have been
prepared and evaluated to induce oxidative stress as a cancer
chemotherapy strategy.24,25 Therefore, the photochemical
Photochemical redox reactions involving Cu(II) have been
studied for many Cu(II) complex systems, such as Cu(II)/
halide, carboxylate, aminocarboxylate, and polyamine.1,2,16,26−33
Although the ligand-to-metal charge-transfer (LMCT) irradi-
ations induce the formation of Cu(I) and the decomposition of
ligands,34−36 only a few investigations have used incident light
in the environmentally relevant wavelength range (λ > 290
nm). In a series of structurally related dicarboxylate ligand
systems,28,29 equilibrium Cu(II) speciation calculations were
used to determine molar absorptivities and Cu(I) quantum
yields for individual Cu(II)/dicarboxylate complexes at 313
nm.37 Cu(I) quantum yields for these complexes were found to
be affected by two factors, the relative stability of the carbon-
centered radical and the degree of outer-sphere coordination.
The interaction of copper with amino acids is of interest due
to their prevalence in environmental and biological sys-
tems.38−40 Photochemical properties of Cu(II)/amino acid
complexes with glycine, L-valine, L-serine, L-aspartic acid, L-
glutamic acid, L-histidine, L-alanine, and β-alanine have been
studied.16,30−32 Under irradiation at 310 nm in deaerated
solutions, Cu(I) quantum yields from CuL2 were found to be
0.025, 0.063, 0.066, 0.098, and 0.001 for L = glycine, L-aspartic
Received: December 21, 2013
Published: May 8, 2014
© 2014 American Chemical Society
4934
dx.doi.org/10.1021/ic4031238 | Inorg. Chem. 2014, 53, 4934−4943

Inorganic Chemistry
Article
Table 1. Composition Matrix for the Calculated Equilibrium Speciation of Cu(II): Cu(II) Species and Their Corresponding
Components, Stoichiometric Coefficients, and Equilibrium Formation Constants
a
components
L-alanine−
equilib. constant
b
species
Cu2+
CO3
H+
PO4
Cl−
log10(β)
notes
2−
3−
Cu(L-alanine)+
1
1
1
1
1
1
1
1
1
1
1
1
2
2
3
1
1
1
1
2
8.11
14.90
0.1
0.1
0.1
3.0
0
Cu(L-alanine)2
Cu(HPO4)0
Cu(H2PO4)+
CuCl+
1
2
1
1
14.79
18.49
1
2
3
4
−0.14
−0.93
−2.95
−5.03
−7.68
−16.43
−26.81
−39.57
−5.38
−10.76
−21.42
5.88
→ 0
→ 0
→ 0
→ 0
0.1
0
Cu(Cl)2
−
Cu(Cl)3
2−
Cu(Cl)4
Cu(OH)+
−1
−2
−3
−4
−1
−2
−4
0
Cu(OH)2
→ 0
1.0
−
Cu(OH)3
2−
Cu(OH)4
Cu2(OH)3+
1.0
3.0
2+
Cu2(OH)2
0.1
2+
Cu3(OH)4
Cu(CO3)0
0.1
1
2
1
→ 0
→ 0
→ 0
2−
Cu(CO3)2
Cu(HCO3)−
9.32
1
11.25
a
All equilibrium constants reported here are for 25 °C, 1.0 atm, and ionic strength I = 0.10 M. In certain cases, equilibrium constants have been
converted from a value for another ionic strength to a value for ionic strength = 0.10 M (as listed in this table), using the Davies equation.
Equilibrium formation constants (β) and pKa values are from critical reviews.49,50 [species] = β[component 1]i [component 2]j [component 3]k ...,
where [ ] signifies molar concentration of the species/component; i, j, k,... are stoichiometric coefficients for the corresponding component (given in
the matrix above); and β is the equilibrium formation constant of the species. Blank entries in the table are zero. The pKa values of the species (25
°C, 1.0 atm, I = 0.10 M; original source, and as used here) are alanine (2.33, 9.71), H2CO3* (6.13, 9.88), where H2CO3* ≡ H2CO3(aq) + CO2(aq),
b
and H3PO4 (1.92, 6.71, 11.65). For Kw = [H+][OH−], log10(Kw) = −13.78. Ionic strength (molar) of the original source of the thermodynamic data.
acid, L-glutamic acid, β-alanine, and L-histidine, respectively.16
Transient spectra of CuL2 for L = glycine, L-valine, L-serine, L-
aspartic acid, L-glutamic acid, and β-alanine have been
investigated in flash irradiations (λ > 240 nm).30−32 Similar
copper−alkyl species are proposed as intermediates. The final
product analysis of Cu(I), NH3, and HCHO in the charge-
transfer excitation of Cu(II)(glycine)2 solutions has been
performed under deaerated conditions.32 However, photo-
products from Cu(II) complexes with other amino acids have
not been studied in detail. Besides, the previous studies used
millimolar Cu(II) concentrations, which are much higher than
those in natural aquatic environments or biological systems
varying from μM to less than nM. To the best of our
knowledge, quantum yields of photoproducts for individual
Cu(II)/amino acid complexes have not been reported, nor has
the effect of the Cu(II) complex stoichiometry on photo-
reactivity been studied.
acid by photochemical redox reactions of Cu(II)/alanine
complexes over an extensive range of pH, total Cu(II)
concentration, and total alanine concentration. The concen-
tration range of Cu(II)/alanine complexes studied has been
down to μM. The objective of this study is to characterize the
quantum yields of photoproducts for individual Cu(II)/alanine
complexes and to elucidate the effect of the Cu(II) complex
stoichiometry on quantum yields. The determination of
individual quantum yield is important for the quantitative
evaluations of the photolysis of Cu(II)/alanine complexes in
natural aquatic systems. This information is also potentially
valuable for the design and synthesis of photoswitchable and
photolabile metal complexes.24,25,44−46
EXPERIMENTAL SECTION
■
Speciation Calculations. Equilibrium concentrations of all
chemical species in Cu(II)/alanine solutions studied were calculated
using the Visual MINTEQ 3.0 program.47,48 Equilibrium constants and
pKa values used in these calculations are from critical reviews and listed
in Table 1.49,50 Ionic strength corrections were made using the Davies
equation. The use of an equilibrium speciation model to describe the
Cu(II) speciation is appropriate due to the rapid water/ligand
exchange reactions of Cu(II) in aqueous solution.
Oxygen dissolved in water can reduce Cu(I) concentration,
and HO2 /O2 and H2O2 are produced instead.3,41,42 These
oxygen species play an important role in the copper cycle as
they can act either as an oxidant or as a reductant with copper.
Moreover, Cu(II)/amino acid complexes can catalyze the
•
•−
43
•−
formation of H2O2 from O2
.
The presence of oxygen can
Materials and Solution Preparation. All chemicals were of
analytical or reagent grade, or the highest purity available from several
suppliers. CuCl2·2H2O (>99.0%), CuCl (>99.0%), NaH2PO4
(>99.5%), acetic acid (>99%), 2-mercaptoethanol (99.0%), o-
phthalaldehyde (>99%), boric acid (>99.8%), methanesulfonic acid
(MSA) (>98%), and hydroxylammonium chloride (>99.0%) were
obtained from Merck (Darmstadt, Germany). Sodium hydroxide
(>98.9%), sulfuric acid (>96.0%), hydrochloric acid (36.5−38%),
methanol, and acetonitrile were from J.T. Baker. Acetaldehyde
(>98%), L-alanine (L-α-alanine) (>99.5%), and β-alanine (>99.5%)
were obtained from Fluka (Buchs, SG, Switzerland). Ammonium
significantly affect the transient transformations induced in flash
irradiations of the Cu(II)/amino acid complexes. To
quantitatively characterize the photoproduction of Cu(I) from
Cu(II)/amino acid complexes, it is necessary to minimize the
•−
confounding effects of rapid reoxidation of Cu(I) by O2, O2
,
•
HO2 , and H2O2. Hence, it is necessary to study these reactions
under deaerated conditions.
In this study, we have investigated the formation of Cu(I)
and the decomposition of alanine (L) as a representative amino
4935
dx.doi.org/10.1021/ic4031238 | Inorg. Chem. 2014, 53, 4934−4943

Inorganic Chemistry
Article
chloride (>99.5%), sodium chloride (>99.8%) and sodium phosphate
measurements of Cu(II) solutions were carried out in Teflon-
stoppered 1.00, 5.00, or 10.00 cm quartz cuvettes (Hellma, Spectrocell,
or Starna). A monochromatic irradiation system (mainly from Spectral
Energy Corp., Kratos, Schoeffel) was constructed from a high-pressure
1000 W O3-free Hg−Xe lamp (ORC), a water filter (8 cm, Oriel
6214), a monochromator (entrance and exit slits = 2.5 mm; full
bandwidth at half-peak-height = 7−8 nm) with holographic grating
(1200 grooves/mm, Milton Roy), two 2.5 mm Hoya UV-30 optical
glass filters to filter light exiting the monochromator, a shutter, and a
black reaction chamber. The reaction chamber contains a black-
anodized Al cuvette holder that maintains a gastight 100% fused-quartz
rectangular cuvette (5.00 cm path length, Spectrocell Inc.; R-3050-I;
FUV; modified to 70 mm overall height) in a tightly fixed,
reproducible position at constant temperature between spring-loaded,
temperature-controlled side walls, and stirs the solution with a Teflon-
coated magnetic stir bar (1 mm diameter, 8 mm long). Photochemical
experiments and chemical actinometry were done in the aforemen-
tioned 5.00 cm quartz cuvettes equipped with a 12 mm Teflon-faced
silicone septum (Sun Brokers, 200594) and a Teflon screw cap.
Cu(I) was quantitatively determined using the bathocuproinedisul-
fonate method with the literature value of the Cu(I)-based molar
absorptivity at 484 nm of 1.24 × 104 M−1 cm−1.29 N2-purging was used
to remove O2 from solutions of Cu(II)/L-alanine, bathocuproine,
Cu(I), and Cu(II) to ensure an accurate measurement of Cu(I).
Ammonia was measured by a purge-and-trap ion chromatography
method developed previously for the determination of trace amounts
of ammonium ion in high-salinity water samples.52,53 Aldehydes were
determined by HPLC using 2,4-dinitrophenylhydrazine (DNPH)
derivatization described previously.54 The modified HPLC-DNPH
method is particularly well-suited for the determination of aldehydes in
heavy metal containing waters. In acidic aqueous solutions, the
hydrazone derivatives could be hydrolyzed back to aldehydes and
DNPH. The formation equilibrium constant was used to compensate
the decrease of hydrazone derivatives.55,56 The equilibrium constant
for the formation of acetaldehyde DNP hydrazone derivative at 25 °C
was 3.6 × 104 M−1. Quantitative determination of amines was carried
out by vortex-assisted liquid−liquid microextraction coupled with
derivatization reported previously.57 2-Nitrobenzaldehyde (2-NB)
chemical actinometry was used to determine photon fluxes at 313
nm. Photolysis of 2-NB in aqueous solution leads to the formation of
2-nitrosobenzoic acid, and the disappearance of 2-NB could be
monitored using reverse-phase HPLC (Beckman Ultrasphere 5 um C-
18 analytical column, 15 cm) with 40% acetonitrile in water as eluent
and UV detection at 260 nm. Solution pH was measured with an
Ioncheck 45 pH meter (Radiometer Analytical) and combination glass
electrode (Mettler Toledo Inlab 439/120). The pH of the sample
solution was adjusted by adding aliquots of 0.1 or 0.01 M NaOH to
the desired pH. The pH of the buffer was checked periodically and
readjusted when necessary.
(>98%) were obtained from Riedel-deHaen (Seelze, Germany). 2,4-
̈
Dinitrophenylhydrazine (>97%, Sigma, St. Louis, MO, USA) was
recrystallized in hexane−dichloromethane with the ratio of 7:3 (v/v)
prior to use. Other reagents used were D-alanine (99%, Alfa Aesar), 2-
nitrobenzaldehyde (98%, Aldrich), and bathocuproine (sulfonated
sodium salt, GFS). Ultra-high-purity N2 (99.9995%) equipped with an
O2 trap (Oxiclear DGP-250-R1, Labclear) was used to purge solutions
of bathocuproine and Cu(II)/alanine. All solutions were prepared
using only ultra-high-purity Milli-Q water (≥18.2 MΩ·cm resistivity).
Solutions (or aliquots) were filtered through a 0.2 μm syringe filter (13
mm Teflon, or 25 mm Tuffryn; Acrodisc, Gelman). Glassware and
quartzware were cleaned using a 50/50 v/v mixture of methanol and
aqueous 3.0 M HCl and thoroughly rinsed with Milli-Q water.51
Table 2 summarizes the solution conditions used for this study,
which were optimized from the equilibrium speciation calculations.
a
Table 2. Composition of Cu(II)−L-Alanine Solutions
measurement
[Cu(II)]T, μM [alanine]T, mM
pH
6.50
molar absorbance
50
0.30−1.00
1.00
50
7.0−8.0
4.75−6.00
5.00
50
5.00
500
500
5000
5.00−40.00
50.00
3.75−5.50
4.50−6.00
20.00
Cu(I) formation
30−1000
2.00
6.00
30
50
50
50
50
50
2.00
7.00
0.06−5.00
0.10−2.00
1.00
6.00
7.00
5.50−8.00
5.25−7.00
5.00
2.00
2.00−20.00
ammonia formation
100−1000
200
2.00
5.80
1.00−40.00
2.00
5.80
200
5.50−7.50
acetaldehyde formation
50
0.3−50.00
2.00
6.00
50
5.00−7.00
6.00
50−1000
200
2.00
2.00, 40.00
5.80
a
All solutions were studied at 25 °C, contained 100 μM total
orthophosphate to buffer the pH ( 0.03), had an ionic strength of
0.10 M (adjusted with NaCl, almost always 0.10 M), and were filtered
(0.2 μm). All solutions for photochemical experiments and Cu(I)
measurements were N2-purged. All solutions for spectral measure-
ments were saturated with ambient laboratory air. Solutions did not
contain any precipitates and were below the calculated solubility limit
of all solids. [Cu(II)]T = total concentration of Cu(II). [alanine]T ≡
total concentration of alanine ligand. The exact composition of each
solution studied is described in the Supporting Information.
Data Analysis. UV−vis absorption spectra data were analyzed with
multivariate curve resolution-alternating least-squares (MCR-ALS),
one of the current chemometric techniques used for the analysis of
spectrophotometric data and the resolution of the different species
present in multiequilibria systems.58−60 The homemade program for
the MCR-ALS algorithm was implemented in Matlab (Mathworks
Inc., version R2009b). Molar absorptivities (εi, M−1 cm−1) at a given
wavelength for individual species reported here were determined as37
Typically, total initial concentration of Cu(II) ([Cu(II)]T) and total
initial concentration of L-alanine ligand ([L]T) were held constant
while pH was varied, or pH and [Cu(II)]T were kept constant while
[L]T was varied. In some cases, pH and [L]T were kept constant while
[Cu(II)]T was varied. The criteria of a minimum absorbance of ≈0.005
(at 313 nm) due solely to Cu(II) species almost always limited the
lowest total Cu(II) concentration that could be used for photo-
chemical experiments.
Analytical Equipment and Measurements. Ultraviolet−visible
absorbance measurements were made with a double-beam scanning
spectrophotometer (Shimadzu UV-1601, Tokyo, Japan) and a custom-
built constant-temperature (25 °C, Fisher 910 recirculator) variable-
path-length aluminum cuvette holder (black-anodized). Absorbance
εCu(II)
=
εf
i
∑
i
(1)
i
where εCu(II) is the experimental Cu(II)-based molar absorptivity and fi
is the equilibrium fraction of the total copper present as the ith
complex (e.g., f CuL ≡ [CuL]/[Cu(II)]T, f CuL ≡ [CuL2]/[Cu(II)]T, fin
2
≡ [Cu(II)]in/[Cu(II)]T, where fin represents the fraction of all forms
of inorganic Cu(II) species).
The quantum yield gives the probability of the excited molecules
transformed per quantum of light absorbed. As an example, the
measured total rate of Cu(I) photoproduction (RCu(I)0, M s−1) in the
4936
dx.doi.org/10.1021/ic4031238 | Inorg. Chem. 2014, 53, 4934−4943

Inorganic Chemistry
Article
solution at a given wavelength is proportional to the absorbed light
and can be expressed as
RESULTS AND DISCUSSION
Cu(II) Speciation. Alanine shows strong complexation
ability with Cu(II) and is capable of forming mono- and
dialanine complexes with Cu(II). For the conditions of molar
absorbance measurements, the complexes CuL and CuL2
■
0
RCu(I) = d[Cu(I)]/dt = ΦCu(I)Iabs
(2)
where Iabs is the fraction of the volume-averaged incident irradiance
absorbed by Cu(II) species (einstein L−1 s−1) and ΦCu(I) is the
experimental average Cu(I) quantum yield (mole einstein−1). When
the measured total absorbance of the solution (A) is due to Cu(II)
constituted at least 85% of the total Cu(II) species (fCuL
+
f CuL > 0.85), while the total inorganic Cu(II) species
2
species only, RCu(I) can be also expressed as37
0
represented less than 15% of the Cu(II) in this system (fin
<
0.15) for all 38 experiments. These values also held for the
conditions of photochemical experiments for all (74 experi-
ments) but four experiments, which were required to test the
effect of inorganic Cu(II) species. The calculated equilibrium
speciation results of all of the experimental solutions are
reported in Tables S1−S4 (Supporting Information). For the
conditions of this study, inorganic Cu(II) species represented a
minor fraction of the total Cu(II). Moreover, inorganic Cu(II)
species absorbed more weakly and photolyzed less efficiently
than Cu(II)/alanine complex species studied here.
Molar Absorptivities of Individual Cu(II) Complexes.
Figure 1A shows the ultraviolet−visible (UV−vis) absorption
spectra for Cu(II)/alanine complexes at different pH values.
Absorbance of Cu(II)/alanine complexes shows significant pH
dependence in the UV region (below 350 nm) and visible
region (above 450 nm). Absorption in the visible region is
attributed to weak d−d transitions, which give the solution a
0
RCu(I) = ΦCu(I)I0{1 − exp[−ln(10)(A)]}
(3)
where I0 is the volume-averaged incident irradiance (einstein L−1 s−1).
For an aqueous Cu(II) solution with low total absorbance (A ≤ 0.042)
where the Beer’s law is valid and where the conversion of Cu(II) to
Cu(I) is limited to <10% of the total initial Cu(II) concentration, the
initial rate of Cu(I) photoproduction can be expressed as
0
RCu(I) = [ln(10)]I0DΦ
ε
Cu(I) Cu(II)[Cu(II)]T = jCu(I)[Cu(II)]T
(4)
where D is the optical path length (cm) and A is equal to
εCu(II)D[Cu(II)]T. The apparent first-order rate constant for Cu(I)
photoproduction (jCu(I)) at 313 nm was determined from the linear-
regression slope of a plot of ln{[Cu(II)]T/([Cu(II)]T − [Cu(I)])}
versus illumination time. The initial Cu(I) photoproduction rate is the
sum of the initial photoreaction rates of individual Cu(II) species;
thus, Cu(I) quantum yields (ΦCu(I),i, mole einstein−1) for individual
Cu(II) species can be determined from37
ΦCu(I) Cu(II)
ε
=
(ΦCu(I),iεif )
i
∑
(5)
i
where the quantity ΦCu(I)εCu(II) is determined from jCu(I), I0, and D (eq
4) and the various individual Cu(I) quantum yields (mole einstein−1)
are ΦCu(I),CuL for CuL, ΦCu(I),CuL for CuL2, and ΦCu(I),in for the average
2
(mean) of all inorganic Cu(II) species.
Under previous conditions, the initial photoformation rates of
ammonia (RNH 0, M s−1) and acetaldehyde (RCH CHO0, M s−1) at a
3
3
given wavelength exhibit the same expression forms as eq 4 after
substituting NH3 and CH3CHO for Cu(I), respectively. Quantum
yields of ammonia and acetaldehyde (ΦNH and ΦCH CHO) for
3
3
individual Cu(II) species can be determined from
ΦNH εCu(II)
=
(ΦNH ,iεif )
i
∑
3
3
(6)
i
and
ΦCH CHOεCu(II)
=
(ΦCH CHO,iεif )
i
∑
3
3
(7)
i
where ΦNH and ΦCH CHO are the experimental average quantum yields
3
3
of ammonia and acetaldehyde (mole einstein−1), respectively, and the
various individual quantum yields of ammonia and acetaldehyde are
Φ
NH ,CuL and ΦCH CHO,CuL for CuL and ΦNH ,CuL and ΦCH CHO,CuL for
3
3
3
2
3
2
CuL2, respectively.
Values of the volume-averaged incident irradiance I0 (einstein L−1
s−1) at 313 nm were determined by 2-nitrobenzaldehyde chemical
actinometry (2-NB)
I0 = j2‐NB/([ln(10)]Φ2‐NBε2‐NBD)
(8)
where the first-order rate constant j2‑NB for actinometer loss was
determined from the linear-regression slope of the plot of ln([2-NB]/
[2-NB]0) versus illumination time and a quantum yield (Φ2‑NB) of 0.41
0.02 for 2-NB photolysis in water is recommended.61
Φ2‑NBε2‑NB is
Figure 1. (A) UV−vis absorption spectra for Cu(II)/alanine complex
solutions at different pH values. (B) Molar absorptivity at 313 nm and
species distribution of the Cu(II)/alanine system as a function of pH.
[Cu(II)]T = 5.0 mM, [alanine]T = 20.0 mM, 100 μM phosphate buffer,
and 0.1 M ionic strength (NaCl).
the product of the quantum yield and the molar absorptivity for 2-NB
(650 33 L einstein−1 s−1 at 313 nm). Measured experimental values
of I0 at 313 nm ranged from 0.51 to 1.74 μ(einstein) L−1 s−1, and
values of I0D ranged from 2.5 to 8.7 n(einstein) cm−2 s−1 for these
experiments.
4937
dx.doi.org/10.1021/ic4031238 | Inorg. Chem. 2014, 53, 4934−4943

Inorganic Chemistry
Article
blue color but does not produce detectable photoredox
reaction. Absorbance in the UV region is ascribed to LMCT,
which involves the reduction of the copper and the oxidation of
the ligand. UV−vis absorption spectra data were analyzed with
MCR-ALS, and resolved pure spectra of two major
chromophores (CuL and CuL2) are obtained in Figure S1
(Supporting Information). Two isosbestic points were observed
at 300 and 700 nm, respectively. In order to understand
sunlight-initiated photochemical reactions, the molar absorptiv-
ities for individual Cu(II) complex species are characterized at
wavelengths that occur in the terrestrial solar spectrum. Figure
1B shows the absorbance changes at 313 nm at various pH
values. As pH increases, the molar fraction of CuL2 increases
yet the absorbance decreases, implying that the molar
absorptivity of CuL2 is lower than that of CuL at 313 nm.
The best-fit curve, using two linear regression parameters,
confirms the existence of two major species. To determine
more precisely the molar absorptivities for individual Cu(II)
complex species (CuL and CuL2) at 313 nm, 38 absorbance
measurements were made in a wide range of the solution
conditions, varying in [Cu(II)]T, [L]T, or pH (see the
Supporting Information). The relationship between the
quantity (εCu(II) − εin fin) and the calculated equilibrium
fractions of CuL (fCuL) was investigated over a range of
different experimental conditions.
Figure 3. Kinetic behavior of Cu(I) photoproduction at 313 nm in the
Cu(II)/alanine system with [Cu(II)]T = 50 μM, [alanine]T = 2.0 mM,
pH = 5.00−7.00 (100 μM phosphate buffer), and 0.1 M ionic strength
(NaCl). The slope of this plot gives the apparent first-order rate
constant for Cu(I) photoproduction, jCu(I) (eq 4).
experiments) but six experiments. Equilibrium speciation
calculations for these systems (where inorganic Cu(II) species
are negligible and the ligand is in large excess) indicate that the
equilibrium Cu(II) speciation should not change significantly
over the initial course of the reaction.
Figure 2 illustrates the quality of fit of eq 1 where calculated
values agree well with measured ones and data in Figure 1B. All
Dark control experiments show that the production rate of
Cu(I), NH3, or CH3CHO from thermal reactions of the
Cu(II)/alanine system is less than 4% of the photoformation
rate. In any case, for each kinetic data point, the small
concentration of Cu(I), NH3, or CH3CHO formed thermally
was subtracted from the measured total concentration of Cu(I),
ammonia, or acetaldehyde formed in the photolyzed solution. L
and D forms of optical isomers for alanine were also examined
on the rate of the Cu(I) photoproduction under the same
experimental conditions, and no differences were observed. It
indicates that L and D isomeric forms of alanine share the same
reaction mechanism in the photolysis of Cu(II)/alanine
complexes.
Effect of Chloride Concentration. The effect of chloride
concentration on the Cu(I) photoformation rate is shown in
Figure 4. The rate was found to be very sensitive to chloride
concentration, increasing with the increase of chloride
concentration from 0.001 to 1.0 M. This dependence is in
agreement with previous studies where the oxidation rate of
Cu(I) was strongly affected by chloride concentration, which
could be attributed to the ability of chloride to form strong
complexes with Cu(I).62−65 The stability of Cu(I) in high NaCl
solutions could not only minimize the rapid reoxidation of
Cu(I) in air-saturated solutions but also increase the reduction
of Cu(II) in the photolysis of Cu(II)/alanine systems studied
here. Although Cu(I) photoproduction followed first-order
kinetics in different chloride concentrations, the linear
regression R2 values varied from 0.859 to 0.998 and the
optimum chloride concentration with the best value of R2
occurred at 0.1 M NaCl. To quantitatively characterize the
photoproduction of Cu(I) from Cu(II) complexes, 0.1 M NaCl
was selected for further study where the chloride concentration
would not change notably during these experiments.
Figure 2. Comparison of measured and calculated molar absorptivities
at 313 nm for 38 Cu(II)/alanine systems over a wide range of
experimental conditions (see Table 2). Best-fit values were determined
from eq 1.
results for the Cu(II)/alanine systems show a higher value of
the molar absorptivity at 313 nm for CuL (40 M−1 cm−1) than
for CuL2 (29 M−1 cm−1).
Kinetics of Photoproductions from Cu(II) Complexes.
As an example, Figure 3 shows the results of Cu(I)
photoproduction (313 nm) for Cu(II)/alanine systems. As
expected from eq 4, Cu(I) photoproduction follows first-order
kinetics that is characterized by an apparent first-order rate
constant for Cu(I) photoproduction (jCu(I), s−1, as defined in eq
4). With a similar kinetic behavior, photoproductions of NH3
and CH3CHO (313 nm) for Cu(II)/alanine systems are shown
in Figures S2 and S3 (Supporting Information). For all of the
Cu(II)/alanine systems studied, linear regression R2 values for
first-order kinetic plots of this type were ≥0.98 for all (73
Quantum Yields of Individual Cu(II) Complexes.
Equation 5 indicates that the observed value, ΦCu(I)εCu(II), is a
linear combination of the weighted values of ΦCu(I),CuLεCuL and
Φ
Cu(I),CuL εCuL . Therefore, eq 5 was used to determine values of
2 2
4938
dx.doi.org/10.1021/ic4031238 | Inorg. Chem. 2014, 53, 4934−4943

Inorganic Chemistry
Article
Figure 4. Effect of chloride concentration on the Cu(I) photo-
formation efficiency for Cu(II)/alanine complex solutions. [Cu(II)]T
= 50 μM, [alanine]T = 2.0 mM, pH = 6.0, and 100 μM phosphate
buffer.
Φ
Cu(I),CuLεCuL and ΦCu(I),CuL εCuL from which values of
2
2
ΦCu(I),CuL and ΦCu(I),CuL were derived. As an example, Figure
2
5 illustrates the quality of fit of eq 5 for the Cu(II)/alanine
system as a function of pH, total initial concentration of alanine
([L]T), and total initial concentration of Cu(II). Each value of
an apparent first-order rate constant for Cu(I) photoproduction
(jCu(I), s−1) at a given experimental condition is shown as a
single data point in Figure 5. On the basis of the regression
best-fit parameters (e.g., ΦCu(I),CuLεCuL and ΦCu(I),CuL εCuL ) and
2
2
on the independently calculated equilibrium Cu(II) speciation
(e.g., fin, fCuL, and f CuL ), values of the quantity ΦCu(I)εCu(II)
−
2
ΦCu(I),inεin fin were also successfully quantified by eq 5 for all 48
Cu(II)/alanine solutions. Values determined in this study were
consistent within 10−20%. Since these measurements involve
considerable errors in the determination of incident irradiance
as well as in the analytical procedures for photoproducts, errors
of the order of 10−20% are common and acceptable. These
results indicate that the values of individual Cu(I) quantum
yields for CuL and CuL2 are independent of pH, [L]T, and
[Cu(II)]T. Unlike the quenching effect of malonate in the
photoformation of Fe(II) or Cu(I), free uncomplexed alanine
has no apparent effect on the photoreactivity of Cu(II)
complexes.29,66,67 Similarly, quantum yields of NH3 and
CH3CHO (ΦNH and ΦCH CHO) for individual Cu(II) species
Figure 5. Comparison of measured and calculated photochemical
parameters for Cu(I) photoformation and species distribution of the
Cu(II)/alanine system as a function of (A) pH, (B) total
concentration of alanine [L]T, and (C) total concentration of Cu(II)
[Cu(II)]T. Best-fit values (multivariate linear regression) were
determined from eq 5.
3
3
can be determined from eqs 6 and 7, respectively. The quality
of fit for the Cu(II)/alanine system as a function of pH, [L]T,
and [Cu(II)]T is shown in Figures S4 and S5 (Supporting
Information).
Figure 6 illustrates the relationship between the quantity
(ΦPεCu(II) − ΦP,inεin fin) and the calculated equilibrium fraction
of CuL (f CuL) over a wide range of different experimental
conditions, where P represents a photoproduct: Cu(I), NH3, or
CH3CHO. Because of the nature of multivariate linear
regression, the best-fit lines shown here are not a continuous
function in two dimensions. These results indicate that
variations in the photoformation efficiency of Cu(I), NH3,
and CH3CHO in Cu(II)/alanine systems can be mainly
explained based on the Cu(II) speciation. As shown in Figure
6, plots of the quantity ΦPεCu(II) versus f CuL display a linear
trend line. This could be estimated as follows. Assuming that
the complexes CuL and CuL2 constitute at least 85% of the
total Cu(II) species in the system, then applying f CuL ≈ 1 −
2
f CuL into eq 5, 6, or 7 gives a linear equation where the slope of
the line is (ΦP,CuL)(εCuL) − (ΦP,CuL )(εCuL ) and the intercept is
2
2
(ΦP,CuL )(εCuL ). Both the slope and the intercept exhibit the
2
2
following trend for photoformation efficiency: Cu(I) > NH3 >
CH3CHO. Values of molar absorptivities and quantum yields of
Cu(I), NH3, and CH3CHO for the individual Cu(II) complexes
are summarized in Table 3.
Cu(I) quantum yields were also determined for photolyses of
the Cu(II)/alanine complexes at wavelengths of 280 and 578
4939
dx.doi.org/10.1021/ic4031238 | Inorg. Chem. 2014, 53, 4934−4943

Inorganic Chemistry
Article
quantum yields include contributions from both primary
photochemical processes and secondary reactions involving
the carbon-centered radicals. The stability of carbon-centered
radicals is expected to affect not only the Cu(I) quantum yields
but also the quantum yields of NH3 and CH3CHO.
Nevertheless, since the LMCT irradiations induce the reduction
of Cu(II) to Cu(I) and the concomitant oxidation of alanine,
which produces NH3 and CH3CHO, the quantum yields of
NH3 and CH3CHO display a similar fashion.
On the basis of the results of this study and the literature, a
plausible mechanistic pathway for the photoredox reactions of
Cu(II)/alanine complexes for the 1:1 complex (CuL) is
depicted in Figure 7.16,28−33,68−70 A comparable mechanism
Figure 6. Comparison of measured and calculated photochemical
parameters for photoproduction efficiency in the Cu(II)/alanine
system as a function of the calculated equilibrium fraction of CuL
(f CuL) over a wide range of experimental conditions (see Table 2).
◊
○
▲
Photoproduct symbols: ( ) Cu(I); ( ) ammonia; ( ) acetaldehyde.
Best-fit values were determined from eq 5, 6, or 7
nm. The similarity of quantum yields at 280 and 313 nm
implies that the charge-transfer state is indeed reactive and that
the quantum yields of Cu(I) formation are independent of the
excitation wavelength in the region of the charge-transfer
absorptions. In contrast, excitation at 578 nm in the d−d
absorption band did not result in detectable photoreduction of
Cu(II)/alanine complexes.
Proposed Mechanism and Quantum Yields of Photo-
products. The photochemical redox reactions of Cu(II)/
alanine complexes produced Cu(I), NH3, and CH3CHO under
the conditions of this study. Individual quantum yields of
photoproducts listed in Table 3 vary by 4-fold from 0.094 for
the Cu(I) quantum yield of CuL to 0.024 for the quantum yield
of CH3CHO of CuL2. For both CuL and CuL2, the individual
quantum yields of Cu(I), NH3, and CH3CHO are in the ratio
of 1.8:1:0.7. These results are in good agreement with the rates
of product formation of Cu(I), NH3, and CH3CHO in the ratio
of 2:1:1 in the charge-transfer excitation of Cu(II)(alanine)2
solutions at 230 nm under deaerated conditions.32 It was also
found that the photolysis of Cu(II)(alanine)2 behaved rather
similarly to that of Cu(II)(glycine)2, giving the final products,
Cu(I), NH3, and HCHO. The ratio of individual quantum
yields of photoproducts could be explained by the oxidation of
the ligand to NH3 and CH3CHO and reduction of an
equivalent amount of Cu(II) to Cu(I). It implies that Cu(I)
Figure 7. Proposed reaction scheme for the photoreaction of Cu(II)/
alanine complexes.
would apply to the 1:2 complex (CuL2). The irradiation of the
LMCT absorption band of the Cu(II) complex initiates the
primary photochemical processes that lead to an electronically
excited state. The excited state undergoes two major competing
reactions: it can return to the ground state by one or more
mechanisms or transfer one electron from a carboxylate-
centered orbital to a Cu(II)-centered orbital. The ligand radical
within the water solvent cage with Cu(I) can undergo two
competing reactions: it can decarboxylate, giving CO2 and a
Cu(I)/carbon-centered radical pair, or receive back the electron
from Cu(I) to reform the parent Cu(II) complex. Since
Table 3. Summary of Molar Absorptivities (εCuL and εCuL , M−1 cm−1) and Quantum Yields of Cu(I), Ammonia, and
2
Acetaldehyde (ΦCu(I),CuL and ΦCu(I),CuL , mole einstein−1) for the Individual Cu(II) Complexes [Cu(alanine)+(CuL) and
2
a
Cu(alanine)2(CuL2)], at 313 and 280 nm
photoproduct
εCuL
40
εCuL
ΦP,CuL
ΦP,CuL
(ΦP,CuL)(εCuL
)
(ΦP,CuL )(εCuL
)
Φ
P,CuL/ΦP,CuL
2
2
2
2
2
photolysis at 313 nm
Cu(I)
4
29
2
0.094 0.014
0.055 0.007
0.030 0.007
0.064 0.012
0.036 0.005
0.024 0.007
3.74 0.43
2.18 0.18
1.20 0.25
1.87 0.32
1.04 0.12
0.70 0.20
1.5
1.5
1.2
ammonia
acetaldehyde
photolysis at 280 nm
Cu(I)
500 21
779 15
0.094 0.011
0.087 0.005
46.8 5.3
67.8 3.3
1.1
a
Best value 1 standard deviation for 25 °C and 0.10 M ionic strength (NaCl). Solutions were purged with ultra-high-purity N2 for the quantum
yield determinations. The range of solution compositions used to determine these values is given in Table 2 and in the Supporting Information.
4940
dx.doi.org/10.1021/ic4031238 | Inorg. Chem. 2014, 53, 4934−4943

Inorganic Chemistry
Article
carboxylate-to-Cu(II) charge-transfer states are placed at lower
energies than the amino-to-Cu(II) charge-transfer states,
decarboxylation rapidly follows an efficient LMCT process.1,30
The efficiency of the back electron transfer affects the Cu(I)
quantum yield. With the existence of an amino group, an
efficient depopulation of the photoactive state retards the
decomposition of the carboxylate radical, so the electron on the
reduced Cu(I) center may be more likely to transfer back to the
carboxylate radical, resulting in a low reactivity or low quantum
yield of Cu(I) production. This could explain why the Cu(I)
quantum yield at 313 nm for Cu(II)(alanine) is smaller than
those for Cu(II)(dicarboxylate) with oxalate, malonate, or
succinate.28,29
Although the carbon-centered radical can undergo two
competing reactions, oxidation of the carbon-centered radical
by bulky Cu(II) complexes, such as Cu2+, CuL, and CuL2, is
favored by the dissimilar ratio of Cu(II) to Cu(I)
concentrations. In contrast, the photolysis of Cu(II)(β-
alanine)2 under monochromatic radiation at 230 or 313 nm
led to an ethylamine (CH3CH2NH2) product and neither NH3
nor CH3CHO was detected.32,57 By comparison, the photo-
products from Cu(II)/α-alanine (or L-α-alanine) and Cu(II)/β-
alanine can be interpreted in terms of the reactions
number of bonds that must be broken to release each Fe(II)
increases.41,76,77
A plausible explanation for this phenomenon relates to the
stabilizing effect of the second ligand molecule on the copper
center. The ligands studied presumably exhibit a strong
preference for binding to Cu(II) rather than to Cu(I). Thus,
the presence of the second ligand molecule could lower the
probability of ligand-to-Cu(II) charge (electron) transfer in
CuL2 relative to that in CuL because the second ligand
stabilizes copper in the II oxidation state. This Cu(II)-
stabilizing effect opposes the driving force to reduce Cu(II)
to Cu(I) and hence lowers the Cu(I) quantum yield for CuL2
relative to CuL. Also, delocalizing the LMCT excitation over
two carboxylate groups may stabilize the linkage and reduce
chances for elimination of carbon dioxide as well.
CONCLUSIONS
■
In this study, molar absorptivities and quantum yields of
photoproducts for Cu(II)/alanine complexes have been
measured over an extensive range of experimental conditions.
Individual quantum yields of Cu(I), ammonia, and acetalde-
hyde are determined and characterized mainly with the
equilibrium Cu(II) speciation where the presence of CuL and
CuL2 is taken into account. The ratio of individual quantum
yields of photoproducts could be explained by the oxidation of
the ligand to NH3 and CH3CHO and reduction of an
equivalent amount of Cu(II) to Cu(I) where both direct and
indirect photochemical reactions contribute to the Cu(I)
quantum yield. No differences were observed in the photolysis
of Cu(II) complexes with L or D forms of alanine. Visible
excitation into the d−d bands was ineffective at inducing
decomposition. In view of the Cu(II)-complex stoichiometry,
CuL always has larger quantum yields than CuL2, which implies
that the photoreactivities of Cu(II)/amino acid complexes
could be underestimated in natural aquatic systems.
Cu(II)/α‐alanine + hν
→ Cu(I) + CO2 + NH3 + CH3CHO
(9)
Cu(II)/β‐alanine + hν → Cu(I) + CO2 + CH3CH2NH2
(10)
The difference in photoproducts probably reflects the
distinctive structures of Cu(II) complexes with a five-
membered chelate ring for α-alanine and a six-membered
chelate ring for β-alanine.71 Different carbon-centered radicals
derived from decarboxylation have different degrees of stability
and form different photoproducts.
Effect of Stoichiometry of Cu(II) Complexes on
Photoreactivity. As can be seen from Table 3, the ratios of
ASSOCIATED CONTENT
■
S
* Supporting Information
Φ
P,CuL to ΦP,CuL are estimated to be 1.5 for Cu(I), 1.5 for NH3,
2
Listings of tables and figures containing additional information
about the molar absorptivities and quantum yields of
photoproducts for Cu(II)/alanine complexes studied here.
This material is available free of charge via the Internet at
http://pubs.acs.org.
and 1.2 for CH3CHO. The quantum yields for the 1:1 complex
(CuL) are always larger than those for the 1:2 complex (CuL2).
These results are crucial because it implies that the photo-
reactivities of Cu(II)/amino acid complexes are underestimated
when the evaluations are based on previous studies where CuL2
is the major species. Generally, CuL is a dominant species in
natural aquatic environments or biological systems where
typical concentrations of Cu(II) complexes vary from μM to
less than nM.
AUTHOR INFORMATION
■
Corresponding Author
*Tel: 886-3-5715131, ext. 35856. Fax: 886-3-5718649. E-mail:
chwu@mx.nthu.edu.tw.
A similar effect of multiple ligands has been reported in other
systems.1,41,72−77 Kinetics of the reduction of neptunium(VI)
by dicarboxylic acids show that the NpO2L22− complex is much
less labile in redox reactions than NpO2L (L2− = dicarboxylate
ligand).72 The photoreactivity of the chlorocuprate(II)
complexes changes with the number of the coordinated
ligands.1 Individual quantum yields for photoreduction of
chlorocuprate(II) complexes in acetonitrile at 313 nm were
determined to be 0.16 for CuCl+, 0.098 for CuCl2, 0.028 for
Notes
The authors declare no competing financial interest.
ACKNOWLEDGMENTS
■
We would like to thank the editor and three anonymous
reviewers for their valuable comments. This work was
supported by the Ministry of Science and Technology of the
Republic of China (Taiwan) under Grant Numbers NSC 90-
2113-M-007-025, NSC 91-2113-M-007-013, NSC 92-2113-M-
007-063, NSC 98-2113-M-007-015, and NSC 100-2113-M-
007-004.
−
CuCl3 , and 0.0089 for CuCl42−. The complexes containing a
higher number of Cl− ligands proved to be less efficient. A
similar trend is also reported for the quantum yields of Fe(II)
formation from Fe(III)−oxalato complexes.73−75 The photo-
reactivity of Fe(III)−hydroxy species decreases as the mean
4941
dx.doi.org/10.1021/ic4031238 | Inorg. Chem. 2014, 53, 4934−4943

Inorganic Chemistry
Article
(36) Torres, S.; Ferraudi, G.; Aguirre, M. J.; Isaacs, M.; Matsuhiro, B.;
Chandia, N. P.; Mendoza, L. Helv. Chim. Acta 2011, 94, 293−300.
(37) Faust, B. C. Environ. Sci. Technol. 1996, 30, 1919−1922.
(38) Rode, B. M.; Suwannachot, Y. Coord. Chem. Rev. 1999, 190−
192, 1085−1099.
REFERENCES
■
(1) Horvath, O.; Stevenson, K. L. Charge Transfer Photochemistry of
Coordination Compounds; VCH: New York, 1993; pp 35−70.
(2) Sykora, J. Coord. Chem. Rev. 1997, 159, 95−108.
(3) Ciesla, P.; Kocot, P.; Mytych, P.; Stasicka, Z. J. Mol. Catal. A:
Chem. 2004, 224, 17−33.
(4) Armaroli, N.; Accorsi, G.; Cardinali, F.; Listorti, A. Top. Curr.
Chem. 2007, 280, 69−115.
(5) Sakamoto, R.; Kusaka, S.; Hayashi, M.; Nishikawa, M.; Nishihara,
H. Molecules 2013, 18, 4090−4119.
(6) Szacilowski, K.; Macyk, W.; Drzewiecka-Matuszek, A.; Brindell,
M.; Stochel, G. Chem. Rev. 2005, 105, 2647−2694.
(7) Jiang, Q.; Xiao, N.; Shi, P.; Zhu, Y.; Guo, Z. Coord. Chem. Rev.
2007, 251, 1951−1972.
(8) Pitie, M.; Pratviel, G. Chem. Rev. 2010, 110, 1018−1059.
(9) Kogut, M. B.; Voelker, B. M. Environ. Sci. Technol. 2003, 37, 509−
518.
(39) Yamauchi, O.; Odani, A.; Takani, M. J. Chem. Soc., Dalton Trans.
2002, 3411−3421.
(40) Shimazaki, Y.; Takani, M.; Yamauchi, O. Dalton Trans. 2009,
7854−7869.
(41) Faust, B. C. In Aquatic and Surface Photochemistry; Helz, G. R.,
Zepp, R. G., Crosby, D. G., Eds.; CRC Press: Boca Raton, FL, 1994;
pp 3−37.
(42) Faust, B. C. In Environmental Photochemistry; Boule, P., Ed.;
Springer: Berlin, Germany, 1999; pp 101−122.
(43) Cabelli, D. E.; Bielski, B. H. J.; Holcman, J. J. Am. Chem. Soc.
1987, 109, 3665−3669.
(44) Sasaki, Y.; Iwamoto, S.; Mukai, M.; Kikuchi, J. J. Photochem.
Photobiol., A 2006, 183, 309−314.
(10) Hsu-Kim, H. Environ. Sci. Technol. 2007, 41, 2338−2342.
(11) Vilar, V. J. P.; Botelho, C. M. S.; Boaventura, R. A. R. In Security
of Industrial Water Supply and Management; Atimtay, A. T., Sikdar, S.
K., Eds.; Springer: Dordrecht, The Netherlands, 2011; pp 159−173.
(12) Clara, M.; Windhofer, G.; Weilgony, P.; Gans, O.; Denner, M.;
Chovanec, A.; Zessner, M. Chemosphere 2012, 87, 1265−1272.
(13) Kieber, R. J.; Skrabal, S. A.; Smith, C.; Willey, J. D. Environ. Sci.
Technol. 2004, 38, 3587−3594.
(45) Ordronneau, L.; Nitadori, H.; Ledoux, I.; Singh, A.; Williams, J.
A. G.; Akita, M.; Guerchais, V.; Bozec, H. L. Inorg. Chem. 2012, 51,
5627−5636.
(46) Marchi, E.; Baroncini, M.; Bergamini, G.; van Heyst, J.; Vogtle,
F.; Ceroni, P. J. Am. Chem. Soc. 2012, 134, 15277−15280.
(47) Gustafsson, J. P. MINTEQA2 version 4.0 and Visual MINTEQ
version 3.0; Department of Land and Water Resources Engineering,
Royal Institute of Technology (KTH): Stockholm, Sweden, 2012.
(48) Allison, J. D.; Brown, D. S.; Novo-Gradac, K. J. MINTEQA2/
PRODEFA2, A Geochemical Assessment Model for Environmental
Systems, Version 4.0; EPA/600/3-91/021; U. S. Environmental
Protection Agency: Athens, GA, 1999.
(14) Buerge-Weirich, D.; Sulzberger, B. Environ. Sci. Technol. 2004,
38, 1843−1848.
(15) Witt, M. L. I.; Skrabal, S.; Kieber, R.; Willey, J. J. Atmos. Chem.
2007, 58, 89−109.
(16) Hayase, K.; Zepp, R. G. Environ. Sci. Technol. 1991, 25, 1273−
1279.
(49) Smith, R. M.; Martell, A. E. Critical Stability Constants; Plenum:
New York, 1976−1989: Vols. 1−6.
(17) Andrianirinaharivelo, S. L.; Bolte, M. J. Photochem. Photobiol., A
(50) Martell, A. E.; Smith, R. M.; Motekaitis, R. J. NIST Standard
Reference Database 46: NIST Critically Selected Stability Constants of
Metal Complexes, Version 7.0; NIST: Gaithersburg, MD, 2003.
(51) Lin, T. Y.; Wu, C. H. J. Catal. 2005, 232, 117−126.
(52) Wang, P. Y.; Wu, J. Y.; Chen, H. J.; Lin, T. Y.; Wu, C. H. J.
Chromatogr. A 2008, 1188, 69−74.
1993, 73, 213−216.
(18) Mailhot, G.; Andrianirinaharivelo, S. L.; Bolte, M. J. Photochem.
Photobiol., A 1995, 87, 31−36.
(19) Andrianirinaharivelo, S.; Mailhot, G.; Bolte, M. Sol. Energy
Mater. Sol. Cells 1995, 38, 459−474.
(20) Yang, J. K.; Davis, A. P. Environ. Sci. Technol. 2000, 34, 3789−
3795.
(21) Repicka, Z.; Izakovic, M.; Mazur, M.; Sima, J.; Valigura, D. Acta
Chim. Slov. 2010, 3, 30−37.
(22) Szacilowski, K.; Macyk, W.; Stochel, G.; Stasicka, Z.; Sostero, S.;
Traverso, O. Coord. Chem. Rev. 2000, 208, 277−297.
(23) Campanella, L.; Battilotti, M.; Lecce, R. Int. J. Environ. Health
2007, 1, 98−119.
(53) Lin, T. Y.; Pan, Y. T.; Lee, H. Y.; Wang, P. Y.; Wu, C. H. J. Chin.
Chem. Soc. 2012, 59, 718−726.
(54) Lin, Y. L.; Wang, P. Y.; Hsieh, L. L.; Ku, K. H.; Yeh, Y. T.; Wu,
C. H. J. Chromatogr. A 2009, 1216, 6377−6381.
(55) Uchiyama, S.; Kaneko, T.; Tokunaga, H.; Ando, M.; Otsubo, Y.
Anal. Chim. Acta 2007, 605, 198−204.
(56) Zhou, X.; Huang, G.; Civerolo, K.; Schwab, J. Environ. Sci.
Technol. 2009, 43, 2753−2759.
(24) Ciesienski, K. L.; Haas, K. L.; Dickens, M. G.; Tesema, Y. T.;
Franz, K. J. J. Am. Chem. Soc. 2008, 130, 12246−12247.
(25) Ciesienski, K. L.; Haas, K. L.; Franz, K. J. Dalton Trans. 2010,
39, 9538−9546.
(57) Chang, W. Y.; Wang, C. Y.; Jan, J. L.; Lo, Y. S.; Wu, C. H. J.
Chromatogr. A 2012, 1248, 41−47.
(58) Rodriguez-Rodriguez, C.; Amigo, J. M.; Coello, J.; Maspoch, S. J.
Chem. Educ. 2007, 84, 1190−1192.
(26) Das, S.; Johnson, G. R. A. J. Chem. Soc., Faraday Trans. 1 1980,
76, 1779−1789.
(59) Cavanillas, S.; Alberich, A.; Serrano, N.; Diaz-Cruz, J. M.; Arino,
C.; Esteban, M. Analyst 2012, 137, 5420−5427.
(27) Glebov, E. M.; Plyusnin, V. F.; Grivin, V. P.; Krupoder, S. A.;
Liskovskaya, T. I.; Danilovich, V. S. J. Photochem. Photobiol., A 2000,
133, 177−183.
(60) De Luca, M.; Ioele, G.; Mas, S.; Tauler, R.; Ragno, G. Analyst
2012, 137, 5428−5435.
(61) Galbavy, E. S.; Ram, K.; Anastasio, C. J. Photochem. Photobiol., A
2010, 209, 186−192.
(28) Sun, L.; Wu, C.-H.; Faust, B. C. J. Phys. Chem. A 1998, 102,
8664−8672.
(62) Millero, F. J. Physical Chemistry of Natural Waters; Wiley: New
York, 2001; pp 515−581.
(29) Wu, C.-H.; Sun, L.; Faust, B. C. J. Phys. Chem. A 2000, 104,
4989−4996.
(63) Gonzalez-Davila, M.; Santana-Casiano, J. M.; Gonzalez, A. G.;
Perez, N.; Millero, F. J. Marine Chem. 2009, 115, 118−124.
(64) Pham, A. N.; Rose, A. L.; Waite, T. D. J. Phys. Chem. A 2012,
116, 6590−6599.
(30) Natarajan, P.; Ferraudi, G. Inorg. Chem. 1981, 20, 3708−3712.
(31) Namasivayam, C.; Natarajan, P. J. Polym. Sci., Polym. Chem. Ed.
1983, 21, 1371−1384.
(32) Das, S.; Johnson, G. R. A.; Nazhat, N. B.; Saadalla-Nazhat, R. J.
Chem. Soc., Faraday Trans. 1 1984, 80, 2759−2766.
(33) Natarajan, E.; Ramamurthy, P.; Natarajan, P. Proc. Indian Acad.
Sci., Chem. Sci. 1990, 102, 319−328.
(34) Rorabacher, D. B. Chem. Rev. 2004, 104, 651−697.
(35) Holm-Jorgensen, J. R.; Jensen, M.; Bjerrum, M. J. Inorg. Chem.
2011, 50, 12705−12713.
(65) Yuan, X.; Pham, A. N.; Xing, G.; Rose, A. L.; Waite, T. D.
Environ. Sci. Technol. 2012, 46, 1527−1535.
(66) Wang, Z.; Chen, X.; Ji, H.; Ma, W.; Chen, C.; Zhao, J. Environ.
Sci. Technol. 2010, 44, 263−268.
(67) Weller, C.; Horn, S.; Herrmann, H. J. Photochem. Photobiol., A
2013, 268, 24−36.
4942
dx.doi.org/10.1021/ic4031238 | Inorg. Chem. 2014, 53, 4934−4943

Inorganic Chemistry
Article
(68) Karpel Vel Leitner, N.; Berger, P.; Legube, B. Environ. Sci.
Technol. 2002, 36, 3083−3089.
(69) Goldstein, S.; Czapski, G.; Cohen, H.; Meyerstein, D. Inorg.
Chem. 1992, 31, 2439−2444.
(70) Matsushita, M.; Tran, T. H.; Nosaka, A. T.; Nosaka, Y. Catal.
Today 2007, 120, 240−244.
(71) Martell, A. E.; Hancock, R. D. Metal Complexes in Aqueous
Solutions; Plenum: New York, 1996.
(72) Rao, L. F.; Choppin, G. R. Inorg. Chem. 1984, 23, 2351−2354.
(73) Zuo, Y.; Hoigne, J. Environ. Sci. Technol. 1992, 26, 1014−1022.
(74) Faust, B. C.; Zepp, R. G. Environ. Sci. Technol. 1993, 27, 2517−
2522.
(75) Weller, C.; Horn, S.; Herrmann, H. J. Photochem. Photobiol., A
2013, 255, 41−49.
(76) Lee, C.; Yoon, J. Chemosphere 2004, 57, 1449−1458.
(77) Arakaki, T.; Saito, K.; Okada, K.; Nakajima, H.; Hitomi, Y.
Chemosphere 2010, 78, 1023−1027.
4943
dx.doi.org/10.1021/ic4031238 | Inorg. Chem. 2014, 53, 4934−4943