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\DOI{10.5802/crchim.225}
\datereceived{2022-11-04}
\daterevised{2022-12-22}
\datererevised{2023-01-27}
\dateaccepted{2023-02-06}
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\dateposted{2023-03-23}
\begin{document}

\begin{noXML}

%\TopicEF{Materials and Clean Processes for Sustainable Energy and
%Environmental Applications}{Mat\'eriaux et proc\'ed\'es propres pour
%%des applications \'energ\'etiques et environnementales}

\title{Electrooxidation treatment of simulated wastewater using
mixed-metal oxide anodes for bacterial decontamination}

\author{\firstname{Poulomi} \lastname{Chandra}}
\address{School of Chemistry and Biochemistry, Thapar Institute of
Engineering and Technology (TIET), Patiala, Punjab-147004, India}
\email[P. Chandra]{pchandra\_phd19@thapar.edu}

\author{\firstname{Diptiman} \lastname{Choudhury}\CDRorcid{0000-0003-1080-4558}}
\addressSameAs{1}{School of Chemistry and Biochemistry, Thapar Institute of
Engineering and Technology (TIET), Patiala, Punjab-147004, India}
\address{TIET-VT (Virginia Tech-USA) Centre of Excellence for Emerging
Materials (CEEMS), Thapar Institute of Engineering and Technology,
Patiala, Punjab-147004, India}
\email[D. Choudhury]{diptiman@thapar.edu}

\author{\firstname{Anoop} \lastname{Verma}\CDRorcid{0000-0003-2818-6348}\IsCorresp}
\addressSameAs{2}{TIET-VT (Virginia Tech-USA) Centre of Excellence for Emerging
Materials (CEEMS), Thapar Institute of Engineering and Technology,
Patiala, Punjab-147004, India}
\address{School of Energy and Environment, Thapar Institute of
Engineering and Technology (TIET), Patiala, Punjab-147004, India}
\email[A. Verma]{anoop.kumar@thapar.edu}

\shortrunauthors

\keywords{\kwd{Electrooxidation}
\kwd{Response surface methodology}
\kwd{Bacterial consortium}
\kwd{Decentralized treatment}
\kwd{Water-based pandemic}}

\begin{abstract}
This study aims 
to explore the potential use of electro-oxidation (EO)
as a decentralized wastewater treatment method. 
The simulated wastewater comprising bacterial consortium was treated by
employing mixed metal oxide (MMO). 
In particular, a lab-scale batch electrooxidation reactor was
used at different operating parameters including NaCl dose ($n$), current
density ($j$), and treatment time ($t$) in order to optimize the process
using response surface methodology. The efficiency of the treatment
process was evaluated in terms of \% inactivation and energy
consumption which were found to be 99.2\% and 0.42 kWh/m$^{3}$,
respectively. Under optimal conditions, it was found that the proposed
technique's overall operating cost was 0.189 \$/m$^{3}$ taking into
consideration the electrical energy consumed and cost of electrodes.
\end{abstract}

\maketitle

\vspace*{35pt}

\twocolumngrid

\end{noXML}

\section{Introduction}\label{sec1}

The presence of microbial populations in nearby water bodies like
ground and surface water and their downstream effects is always a point
of concern for developing nations.
The main reason includes the
contamination through the untreated or partially treated wastewaters
from different sources. This contamination affects the water cycle
through chain reaction, thereby contaminating the whole ecosystem and
affecting the human health~\cite{1}. The established conventional
treatment technologies like membrane~\cite{2}, adsorption
\cite{3} and ozonation~\cite{4} techniques, along with advanced
oxidation processes like photocatalysis~\cite{5}, Fenton based
oxidation process~\cite{6}, are effective in removing organic and
inorganic contaminants from wastewater. However, their efficiency
towards handling the microbial load and the volume of wastewater in
large treatment plants remains a big concern~\cite{7}. There may be
different sources of the microbial population like the food industry,
laboratories, and domestic households. But, the wastewater coming from
health care facilities poses a big challenge for the conventional
treatment system for their effective removal. More specifically,
discharge from infected wards of hospitals poses a serious threat to
public health due to the presence of microbes of different
pathogenicity levels~\cite{8}. With the emergence of new viral
strains like COVID-19 and the spread of infection, there is an urgent
need for a decentralized treatment system using novel technologies to
avoid future water-based pandemics.


In this context, the present study reports the requirement of a
cost-effective decentralized wastewater treatment system in terms of
electrooxidation (EO) for tackling the pathogens/microbial load as per
their origin before heading to the sewage treatment plant (STP).

As discussed, an on-site treatment facility for the ward-specific
wastewater is needed for the hour before it mixes with the common
effluent. In recent years, the conventional methods have been replaced
by advanced technologies, which are more reliable for eliminating many
pathogenic microorganisms from
wastewater~\cite{9,10,11,12}. These technologies have made
extensive advancements in treating wastewater due to their high
efficiency and high oxidation stability~\cite{13}. One of the most
affordable and interesting techniques for the ward-specific treatment
of wastewater is electrooxidation
(EO)~\cite{14,15,16,17,18}. EO is a versatile,
eco-friendly, and cost-effective technique. The EO commercial-scale
feasibility depends on the electrode material capable of generating
various chloro-oxidant species and hydroxyl radicals~\cite{19}.\looseness=-1

The efficacy of the EO process mainly depends on the type of
electrodes. Several authors have reported the removal of microbes from
human urine by using boron-doped diamond (BDD)~\cite{20}. Despite
excellent compatibility, performance, and high oxidation
potential~\cite{21,22}, BDD is unsuitable for commercial-scale
application because of its high cost and toxic by-products
formation~\cite{21}. 

The application of mixed metal oxide (MMO) electrode has been
extensively studied in the literature. This great interest is mainly
due to it's the low production cost and the high electrochemical
stability that promotes the formation of reactive chlorine species
(RCS) and reactive oxygen species (ROS) at a low current density which
is essential as compared to BDD~\cite{22,23,24,25,26}.
The MMO anodes have shown a variety of applications for the treatment
of synthetic wastewater~\cite{27}, paper mill water~\cite{28},
pesticides, pharmaceuticals, dyes, phenols, and real
wastewater~\cite{23,24,29,30}. 

In this experimental study, the novel quaternary MMO anodes Ti/Ir/Ru/Pt
have been selected for the EO treatment of simulated wastewater
containing bacteria. In order to get more active sites, stability at
high temperature and acidic solutions, durability, resistivity, and
electrochemical stability at low current densities,
this novel
combination of metal oxides were incorporated into the titanium 
anodes~\protect\cite{31}.
This study further claims the first-time use of this ternary MMO anodes
for the EO treatment of\break bacteria.

The inactivation of bacteria through EO treatment generally occurs by
damaging the bacterial cells. Firstly, the produced RCS damages the
cell membrane permeability, leading to enzymatic changes in the
bacterial cell. Secondly, the damage to the cell membrane leads to the
impairment of intracellular components, thereby causing the loss of
deoxyribonucleic acid integrity~\cite{32}.

Although studies on the disinfection of bacteria in different
wastewater by EO have been reported~\cite{33,34,35,9}, yet
there are hardly any commercial success stories. Major reason could be
its approach as an end-of-pipe treatment where handling of large
volume of wastewater makes the process unfeasible on a commercial
scale. Through this study EO is proposed to be a reactive approach
where it can a ward-specific technique handling small volumes of waste
water, thus can be a viable solution. Moreover, efficiency of any
advanced technology is always more when it is applied to low volumes.
In order to validate the proposed model, a simulated wastewater with
bacterial consortium was taken for EO treatment for checking its
efficacy for the inactivation of bacteria with minimum range of current
density and electrolyte dose, which further validates the concept for
this technology to be a decentralized treatment system.

Within this background, the main objective of the present work is to
analyze the complete disinfection of simulated wastewater of bacterial
consortium employing electrolysis using MMO anodes, paying special
attention to the durability of anodes. Anode's durability and stability
were analyzed through characterization techniques like SEM-EDS, XPS,
XRD, cyclic voltammetry. The influence of various parameters like
current density, electrolyte concentration (NaCl), and treatment time
on bacterial inactivation was studied through response surface
methodology (RSM). This study aimed to evaluate the efficiency of the
EO technique alone for removing bacteria from simulated wastewater
using MMO anodes through batch mode in a laboratory-scale reactor.     


\section{Material and methods}\label{sec2}

\subsection{Chemicals and microorganisms}\label{sec21}

Sodium sulphate with 99\% purity, potassium acetate 
(CH$_{3}$CO$_{2}$K), sodium hydroxide (NaOH), sulfuric acid
(H$_{2}$SO$_{4}$), sodium chloride (NaCl) of analytical grade, and
terephthalic acid with 99\% purity were purchased from Loba Chemicals
Pvt. Ltd.,\unskip\break India. Terephthalic acid was used to estimate the hydroxyl
radical formation in the EO process. Luria Bertani broth was purchased
from HiMedia Laboratories Pvt. Ltd. Mumbai, India. All the bacterial
strains in the present study, \textit{Escherichia coli} (MTCC no. 448),
\textit{Bacillus subtilis} (MTCC no. 441), \textit{Staphylococcus
aureus} (MTCC no. 902), \textit{Salmonella enterica} (MTCC no. 1165),
\textit{Acinetobacter calcoacetius} (MTCC no. 1948), \textit{Serratia
marcescens} (MTCC no. 2645), \textit{Listeria sp.} (MTCC no. 4214),
\textit{Enterococcus faecalis} (MTCC no. 6845) were obtained from
IMTech, Chandigarh, India. In this study, these eight different
bacterial strains were chosen since they commonly found in hospital
wastewater~\cite{36}. These bacteria were analyzed separately by
varying the current density and electrolyte concentration range as
reported previously~\cite{8}. All the solutions were prepared in
double-distilled water of high purity.


\subsection{Sample preparation and experimental setup}\label{sec22}

EO treatment of the simulated wastewater was carried out in a batch
reactor. The simulated wastewater was prepared by dissolving 3.5 g of
potassium acetate, 400 mg of sodium sulfate, and 5~mL of glacial acetic acid in 1 L of
double-distilled water. This simulated wastewater containing inorganic
salts simulates the composition of human urine. The concentration of
sodium chloride was varied according to the reaction. The bacterial
culture from log phase was taken. This culture was grown up to an
absorbance range of 0.8--1.0 nm by inoculating 1--2~$\upmu $L of
bacterial strain in Luria Broth. The concentration of bacterial culture
in the test solution was calculated in accordance with the absorbance
of the bacterial culture. The simulated wastewater solution was freshly
prepared each time. The EO treatment of simulated wastewater was
carried out in a batch mode in a glass reactor having a working volume
of 300 mL, as shown in Figure~\ref{fig1}. The MMO anode used in this study was
purchased from Tiaano Pvt. Ltd., Chennai, India. The MMO anode was
composed of a titanium sheet coated with iridium, ruthenium, and
platinum oxides. The stainless-steel cathode was purchased from a
local vendor in Mohali, India. The dimension of the electrodes was 
($70~\mathrm{mm}\times70~\mathrm{mm}\times1~\mathrm{mm}$) with a surface area of 42~cm$^{2}$ (10~mm
inter-electrode spacing). The DC power supply was purchased from
(GAYATRI ENGINEERS, Maharashtra, India, Model: 0--30~V, 0--2~A) to
maintain the current density for each experimental run. The magnetic
stirrer was used at 500--550~RPM to maintain the homogeneity of the
electrolyte concentration in the sample. All the experiments were
performed three times to ensure the reproducibility of results. All the
samples were collected at a specific time interval of 1~min. 

\begin{figure*}[t!]
\includegraphics{fig01}
\caption{\label{fig1}Schemtic representation of electrooxidation setup
under batch mode with mixed metal oxide anode and stainless-steel
cathode.}
\end{figure*}

\subsection{Analytical methods}\label{sec23}

The analytical studies of bacterial inactivation were carried out by
analyzing the bacterial samples through a UV--visible spectrophotometer
at 600~nm. The inactivation of bacteria was also confirmed by plating
the initial and final samples on Luria agar plates and incubating them
in an incubator for 24~h. The hydroxyl radical (OH$\bullet$) study was
done using a fluorescence spectrophotometer (Shimadzu RF 6000) during
the EO process. The terephthalic acid (TPA) used reacts with
OH$\bullet$ in the EO process~\cite{37} and produces a fluorescent
compound 2-hydroxy terephthalic acid (TAOH). The intensity of this
\mbox{fluorescent} compound was taken at an excitation wavelength of 315 nm
and an emission wavelength of 425~nm. Total available chlorine (TAC)
analysis was done to check the amount of chlorine produced during the
EO process. TAC analysis was performed for the untreated and treated
simulated wastewater samples by APHA standard (4500-CI B) method. The
surface morphology and elemental composition of MMO anodes were
executed by SEM-EDS (JSM-6510LV, JEOL, Japan).

The electronic state of the MMO anodes was analyzed by XPS (X-ray
photoelectron spectroscopy (PHI 5000 Versa-Probe III, Physical
Electronics)). The potassium ion leakage test was performed by APHA:
3500~K method, which confirmed the inactivation of bacteria in untreated
and treated simulated wastewater samples. 


\subsection{Experimental procedure}\label{sec24}

The EO treatment of the simulated wastewater containing eight different
bacteria was carried out under galvanostatic conditions. The pH of the
working sample was adjusted accordingly by 1N HCl and 1N NaOH. The
experimental reaction was carried out at an original pH of 4.25. The
conductivity of the simulated wastewater solution was improved by
adding NaCl as a supporting electrolyte. The initial conductivity of
the sample solution was around 2.5~mS. The NaCl concentration and
current density were varied according to the experimental reaction. At
specific time intervals, 100~$\upmu$L of the sample solution was taken
and was inoculated in 5 mL of Luria broth. The samples were then
incubated for 24 h in an incubator. After 24 h, the samples were
analyzed spectrophotometrically at a wavelength of 600 nm to measure
the absorbance of the samples for determination of \% inactivation of
bacteria. After each experimental run, the electrodes were washed by
dipping them in a 5\% H$_{2}$SO$_{4}$ solution. The complete
inactivation of the bacteria was observed within a short period of
time. Thus, the efficacy of the EO process was proved in terms of the
inactivation of bacteria.

\begin{table*}[t!]
\caption{\label{tab1}The experimental results of BBD matrix for
electrooxidation treatment of simulated wastewater}
\begin{tabular}{lccccccc}
\thead
Std& Run  & Block    & \parbox[t]{1.5cm}{\centering NaCl dose (g/L)}  & 
\parbox[t]{2.3cm}{\centering Current density (mA/cm$^2$)}  & 
\parbox[t]{1.2cm}{\centering Time (min)}
& \% Inactivation  & \parbox[t]{3.2cm}{\centering Energy
consumption (kWh/m$^3$)}\vspace*{2pt}  \\
\endthead
\06  & \01    & Block 1  & 2.50  & \07.14   & \02.00   & 17.79  & \00.1254  \\
12 & \02    & Block 1  & 1.50  & 11.90  & 16.00  & 99.61  & 1.995   \\
15 & \03    & Block 1  & 1.50  & \07.14   & \09.00   & 96.71  & 0.525   \\
16 & \04    & Block 1  & 1.50  & \07.14   & \09.00   & 96.47  & 0.585   \\
\04  & \05    & Block 1  & 2.50  & 11.90  & \09.00   & \01.7\0    & 1.075   \\
17 & \06    & Block 1  & 1.50  & \07.14   & \09.00   & 99.97  & 0.615   \\
\05  & \07    & Block 1  & 0.50  & \07.14   & \02.00   & 12.88  & \00.1518  \\
13 & \08    & Block 1  & 1.50  & \07.14   & \09.00   & 97.75  & 0.57\0    \\
\07  & \09    & Block 1  & 0.50  & \07.14   & 16.00  & 84.94  & \01.1172  \\
\01  & 10   & Block 1  & 0.50  & \02.38   & \09.00   & 99.42  & 0.14\0    \\
\03  & 11   & Block 1  & 0.50  & 11.90  & \09.00   & 99.82  & 1.25\0    \\
10 & 12   & Block 1  & 1.50  & 11.90  & \02.00   & 44.29  & \00.2915  \\
\09  & 13   & Block 1  & 1.50  & \02.38   & \02.00   & \01.89   & 0.033   \\
\02  & 14   & Block 1  & 2.50  & \02.38   & \09.00   & 44.01  & 0.185   \\
11 & 15   & Block 1  & 1.50  & \02.38   & 16.00  & 64.22  & \00.3014  \\
\08  & \01    & Block 1  & 2.50  & \07.14   & 16.00  & 98.42  & 1.064   \\
14 & 17   & Block 1  & 1.50  & \07.14   & \09.00   & 98.35  & 0.585 
\botline 
\end{tabular}
\end{table*}

\subsection{Experimental design and analysis}\label{sec25}

Response Surface Methodology (RSM), a three-level Box-Behnken design
(BBD) based statistical technique is used to optimize the operational
parameters as well as to reduce the number of experimental runs. In
addition, it is used to analyze inter-parametric interactions of the
input parameters and their effects on the responses~\cite{38}. The
RSM technique works according to the equation $N=s^{2}+s+m_{p}$,
where $s$ is the number of factors and $m_{p}$ is the
replicating number of central points~\cite{39}. The three initial
input parameters in this study are NaCl dose ($n$)
($X_{1}$), current density ($j$) ($X_{2}$), and treatment
time ($t$) ($X_{3}$) which were coded by three levels designated as ${-}$1
(low), 0 (center), ${+}$1 (high) as shown in Table~S1. All the statistical
plots have been generated by the software Design-Expert V-6.0.8. The
experimental range for each process parameter was determined based on a
literature survey and preliminary tests~\cite{40,10}. In
this study, there were 17 experimental runs designed by BBD under a
three-level factorial design, as shown in Table~\ref{tab1}.
The efficacy of the
EO process was determined by analyzing the responses of \% inactivation
($Q_{1}$) and energy consumption ($Q_{2}$). The energy
consumption ($E$) in (kWhrm$^{-3}$) and \% inactivation
was calculated by the Equation (\ref{eq1})~\cite{41}.
{\begin{eqnarray}
E&=&{V\times I\times t}/S_{v} \quad  \& \nonumber\\
&&\%~\mathrm{Inactivation}=(\mbox{Initial conc}.-\mbox{Final conc}.)/\nonumber\\
&& \mbox{Initial conc}. \times 100.
\label{eq1}
\end{eqnarray}}\unskip
Here, $V =$ voltage, $I =$ current (A), $t=$ treatment time  (h) and
$S_v=$ volume of sample in (m$^{3}$).

To fit the experimental data of the input variables on the response $Q$,
a second-order polynomial equation~(\ref{eq2}) was used by considering all
square terms, linear terms, and linear by linear interaction terms, the
quadratic response model~\cite{42} can be 
expressed~as:\looseness=1\pagebreak
{\begin{eqnarray}
Z&=&a_{0}+\sum _{i=1}^{4}\alpha _{i} X_{i}+\sum _{i=1}^{4}
\alpha _{i}{X}_{i}^{2}\nonumber\\
&&+\,\sum _{i=j }^{3}\sum _{i=j+1}^{4}
\alpha _{\mathit{ij}}X_{\mathit{ij}}+ei .\label{eq2}
\end{eqnarray}}\unskip
Here, $Z$ is the response, ${\upalpha}_{o}$, ${\upalpha}$,
$\upalpha_{\mathit{ii}}$, and ${\upalpha}_{\mathit{ij}}$ are the constant coefficients,
$X_{i}$, $X_{\mathit{ii}}$, and $X_{\mathit{ij}}$ are the input variables, and $ei$ is the
error. The $F$-test, lack of fit test, and other measures were used for
the acceptability of the chosen polynomial model. In this study, two
responses are involved, i.e. (\% inactivation and energy consumption).
Therefore, the multiple response process optimization and the
desirability function approach were used to optimize the input
parameters of the EO process~\cite{43,44}. The value of the
desirability function lies between 0 and 1, indicating the prudence of
the response to its ideal value~\cite{45}.

\section{Results and discussion}\label{sec3}

\subsection{Statistical analysis with BBD}\label{sec31}

The BBD of RSM developed by a statistical Design-Expert software of
6.0.8 version (STAT-Ease Inc., Minneapolis, US) was used for the EO
bacteria treatment. The results of \% inactivation and energy
consumption were analysed by the EO experimental runs suggested by the
BBD design set process, as shown in Table~\ref{tab1}. The lack of fit tests,
sequential model sum of squares, and model summary statistics tests
were used to select the best regression models among various other
models of linear, modified, mean, cubic, 2FI, and
quadratic~\cite{46,47}. Among the nine transformations of RSM,
the none transformation was used for both the responses, and the cubic
and quadratic models were used to analyse \% inactivation and energy
consumption, respectively. The model summary statistics for \%
inactivation showed the cubic model's $R^{2}$ and adjusted $R^{2}$
values to be 0.997 and 0.9987, respectively. The cubic model here is
aliased. In the case of the quadratic model, the $R^{2}$ and adjusted $R$
values for energy consumption were 0.9987 and 0.9971, respectively.
Here, the quadratic model is suggested. 

The relationship between the responses and the input parameters in
terms of coded factors obtained from the RSM software were expressed by
the quadratic model equation as shown in  Equations (\ref{eq3}) 
and~(\ref{eq4}). 
{\begin{eqnarray}
&&\text{\% Inactivation}=+97.85+4.60\times {X}_{1}+
19.45\times {X}_{2}\nonumber\\
&&\quad+\,29.41\times {X}_{3}-17.80\times {{X}}_{1}^{2}-
18.81{{X}}_{2}^{2}-26.54\times {{X}}_{3}^{2}\nonumber\\
&&\quad-\,10.68\times {X}_{1}\times {X}_{2}+
2.14\times {X}_{1}\times {X}_{3}\nonumber\\
&&\quad -\,1.75\times {X}_{2}\times {X}_{3}-29.92
\times {{X}}_{1}^{2}{X}_{2}+8.76\times 
{{X}}_{1}^{2}\times {X}_{3}\nonumber\\
&&\quad-\,42.98\times {X}_{1}\times {{X}}_{1}^{2}
\label{eq3}\Seqnsplit
&&\text{Energy consumption}=+0.58-0.026\times {X}_{1}\nonumber\\
&&\quad+\, 0.49\times {X}_{2}+0.48\times {X}_{3}
+0.023\times {{X}}_{1}^{2}\nonumber\\
&&\quad+\,0.064\times {{X}}_{2}^{2}+
0.016\times {{X}}_{3}^{2}-0.055\times {X}_{1}\times X_{2}\nonumber\\
&&\quad-\,6.700 \times 10^{-3}\times {X}_{1}\times {X}_{3}+
0.36\times {X}_{2}\times {X}_{3} \label{eq4}
\end{eqnarray}}\unskip
where $X_{1}$, $X_{2}$, $X_{3}$, are NaCl dose, current density and
treatment time respectively. 

The analysis of variance (ANOVA) results is shown in Table~\ref{tab2},
obtained
from the second-order polynomial equation for both the responses for
the EO treatment of bacteria using MMO. The model $F$-values 1011.24 and
619.97 for \% inactivation and energy consumption, respectively, imply
that the model is significant. Values of ``Prob $> F$'' $<$ 0.05
indicate that the model terms are significant~\cite{48}. There is
only a 0.01\% chance that the ``Model-$F$ values'' this large could
occur due to the noise. In case of \% inactivation, the ANOVA results
suggests that the model\linebreak terms, NaCl dose, current density, time, NaCl
dose$^{2}$, current density$^{2}$, time$^{2}$, NaCl dose $\times$ current
density, NaCl dose $\times$ time, NaCl dose$^{2}$ current density, NaCl
dose$^2$ time, NaCl dose current density$^{2}$ are significant terms.
For energy consumption, the significant model terms are NaCl dose,
current density, time, current density$^{2}$, NaCl dose $\times$ current
density, and current density $\times$ time. The adequate precision ratio was
79.548 and 91.025 for \% inactivation and energy consumption,
respectively. A ratio greater than 4 indicates that the model is
desirable and can be used to navigate the design space~\cite{49}.

\begin{table*}[t!]
\caption{\label{tab2}The table shows the ANOVA results as suggested by
BBD for \% inactivation and energy \unskip\break consumption\vspace*{-2pt}}
\fontsize{9.5}{11.3}\selectfont
\tabcolsep=3.7pt
\begin{tabular}{lcccccccccc}
\thead
\xmorerows{1}{Sources} & \multicolumn{5}{c}{\% Inactivation, ($Q_1$)} &
\multicolumn{5}{c}{Energy consumption, ($Q_2$)}
\\\cline{2-6}\cline{7-11}
& \parbox[t]{1cm}{\centering Sum of square} & DF & 
\parbox[t]{1cm}{\centering Mean square} & $F$-value & $\mathrm{Prob}
> F$ &  \parbox[t]{1cm}{\centering Sum of square} & DF &
\parbox[t]{1cm}{\centering Mean  square} &  $F$-value &
$\mathrm{Prob}>F$ \vspace*{2pt}\\
 \endthead
Model & 24,143.53 & 12\0 & 2011.96 & 1011.24 & $<$0.0001 & 4.38  & 9 & 0.49 & \0619.97  & $<$0.0001 \vspace*{2pt}\\
$X_{1}$ & \,\0\0\084.55 & 1 & \0\084.55 & \0\042.49 & \mn0.0029 & 5.492$\times 10^{-3}$ & 1 & 5.492$\times 10^{-3}$ & \0\0\06.99  & \mn0.0333 \vspace*{2pt}\\
$X_{2}$ & \,\01512.82 & 1 & 1512.82 & \0760.36 & $<$0.0001 & 1.95  & 1 & 1.95  & 2484.57 & $<$0.0001 \vspace*{2pt}\\
$X_{3}$ & \,\03460.38  & 1 & 3460.38  & 1739.23  & $<$0.0001 & 1.88  & 1 & 1.88  & 2389.69  & $<$0.0001 \vspace*{2pt}\\
$X_{1}^{2}$ & \,\01334.63  & 1 & 1334.63  & \0670.80  & $<$0.0001 & 2.215$\times 10^{-3}$ & 1 & 2.215$\times 10^{-3}$ & \0\0\02.82  & \mn0.1370 \vspace*{2pt}\\
$X_{2}^{2}$ & \,\01489.55  & 1 & 1489.55  & \0748.67  & $<$0.0001 & 0.017  & 1 & 0.017  & \0\021.65  & \mn0.0023 \vspace*{2pt}\\
$X_{3}^{2}$ & \,\02965.50  & 1 & 2965.50  & \0149.50  & $<$0.0001 & 1.033$\times 10^{-3}$ & 1 & 1.033$\times 10^{-3}$ & \0\0\01.31  & \mn0.2893 \vspace*{2pt}\\
$X_{1}X_{2}$ & \,\0\0456.04  & 1 & \0456.04  & \0229.21  & \mn0.0001 & 0.012  & 1 & 0.012  & \0\015.40  & \mn0.0057  \vspace*{2pt}\\
$X_{1}X_{3}$ & \,\0\0\018.36  & 1 & \0\018.36  & \0\0\09.23  & \mn0.0385 & 1.796$\times 10^{-4}$ & 1 & 1.796$\times 10^{-4}$ & \0\0\00.23  & \mn0.6472 \vspace*{2pt}\\
$X_{2}X_{3}$ & \,\0\0\012.29  & 1 & \0\012.29  & \0\0\06.17  & \mn0.0679  & 0.51  & 1 & 0.51  & \0655.23 & $<$0.0001 \vspace*{2pt}\\
$X_{1}X_{3}$ & \,\0\0333.06 & 1 & \0333.06 & \0\069.92 & $<$0.0001 &  &  &  &  &  \vspace*{2pt}\\
$X_1^{3}$ & \,\0\0\0\0\00.000  & 0 &  &  &  &  &  &  &  &  \vspace*{2pt}\\
$X_2^{3}$ & \,\0\0\0\0\00.000  & 0 &  &  &  &  &  &  &  &  \vspace*{2pt}\\
$X_3^{3}$ & \,\0\0\0\0\00.000  & 0 &  &  &  &  &  &  &  &  \vspace*{2pt}\\
$X_{1}^{2}X_{2}$ & \,\01791.01  & 1 & 1791.01  & \0900.19  & $<$0.0001 &  &  &  &  &  \vspace*{2pt}\\
$X_{1}^{2}X_{3}$ & \,\0\0153.48  & 1 & \0153.48  & \0\077.14 & \mn0.0009 &  &  &  &  &  \vspace*{2pt}\\
$X_{1}X^{2}_{2}$ & \,\03694.56  & 1 & 3694.56  & 1856.94  & $<$0.0001 &  &  &  &  &  \vspace*{2pt}\\
$X_{1}X^{2}_{3}$ & \,\0\0\0\0\00.000 & 0 &  &  &  &  &  &  &  &  \vspace*{2pt}\\
$X_{2}^{2}X_{3}$ & \,\0\0\0\0\00.000 & 0 &  &  &  &  &  &  &  &  \vspace*{2pt}\\
$X_{2}X_{3}^{2}$ & \,\0\0\0\0\00.000 & 0 &  &  &  &  &  &  &  &  \vspace*{2pt}\\
$X_{1}X_{2}X_{3}$& \,\0\0\0\0\00.000 & 0 &  &  &  &  &  &  &  & \vspace*{2pt}\\
Pure error                         &\,\0\0\0\07.96       & 4  & \0\0\01.99 & && 4.320$\times 10^{-3}$ &4  &1.080$\times 10^{-3}$  & &    \vspace*{2pt}\\
Cor total                          & 24,151.49  & 16\0  &    & && 4.39       &16\0 &    &    &\vspace*{2pt}\\
Residual                           &  ---      & &  & &    & 5.501$\times 10^{-3}$ & 7 &7.858$\times 10^{-4}$  &     &\vspace*{2pt}\\
Lack of fit                        &  ---      & &  & &    & 1.181$\times 10^{-3}$ & 3 & 3.935$\times 10^{-4}$ & \0\0\00.36 &   \mn0.7834
\botline 
\end{tabular}
\vspace*{-2pt}
\end{table*}


The diagnostic plots for the actual versus predicted experimental
values were analysed to evaluate the data points and check the
mathematical model's accuracy. These plots indicate the relation
between the predicted and the actual experimental values~\cite{50}.
The data points for this plot are very close to the straight diagonal
line, thus suggesting a good relationship between the actual
experimental values and the predicted data values by the mathematical
model, as shown in Figure~S1~\cite{51}. To study the
effect of the operational parameters on both the responses, the 3D
response surface graphs were analysed for each parameter.

{\vspace*{-2pt}}

\subsection{Effect of process parameters}\label{sec32}

\subsubsection{Effect of current density ($j$) on \% inactivation}\label{sec321}

Current density is one of the significant process parameters in the EO
treatment from both cost-effectiveness and mechanistic study point of
view. The generation of ROS and RCS on the electrodes~\cite{52} and
the electron transfer mechanism depend on the current density values by
following reactions (\ref{eq5})--(\ref{eq11})~\cite{30}. The maximum inactivation
efficiency at acidic pH was due to the adsorption rate of $\bullet$OH
on the surface of MMO anode was high which leads to direct oxidation of
contaminants, as at basic pH, the adsorption rate of $\bullet$OH
decreases due to transformation of $\bullet$OH into lower potential
oxidants like H$_{2}$O$_{2}$ and HO$_{2}\bullet$. Moreover, at acidic
pH, the production rate of high potential oxidants like HOCl, Cl$_{2}$,
ClO$^-$ was maximum. Furthermore, the pH of the solution
during the EO process was $\sim$4.5~\cite{53}. The
production rate of chloro-oxidant species increases by increasing the $j$
value up to a certain limit which also depends on the $n$
value~\cite{54}. The EO treatment process works best at low $j$
values with MMO because\vadjust{\break} of the low oxygen evolution potential, as there
is no side \mbox{reaction} and therefore increases the process efficiency.
From Figure~\ref{fig2}a, the effect of $j$ and $n$ on \% inactivation can
be analyzed. With the increase in $j$ values from 2.38 to 
11.90~mA/cm$^{2}$, there is a gradual decrease in the \% inactivation of
bacteria. High $j$ values would not effectively inactivate the bacteria at 
high electrolyte (NaCl) concentration because the effect of NaCl dose is 
very low
which is again a significant parameter for RCS generation.
Although higher $j$ values may lead to an increase in temperature of the
solution, even using only bacterial consortium alone without any
organic load may also result in an increase in temperature, but the
temperature increase in this situation is not enough to denature the
bacterial proteins or inactivate the bacterial enzyme. 
Hence, it may be concluded that electrolyte (NaCl) concentration plays
an important role at high and low current densities~\cite{55}. At a
low $j$ value of 2.38~mA/cm$^{2}$ and a minimum $n$ value of 0.5 g/L, the
\% inactivation is maximum at around 96\% because of low  oxygen
evolution potential which disfavours other side reaction and increases
the inactivation rate. Further, with a gradual increase in $n$ value from
0.5 to 1.50 g/L, the \% inactivation remains constant. But from 2.0 to
2.50~g/L, there is a gradual decrease in \% inactivation.\looseness=-1
{\begin{eqnarray}
\label{eq5}
&&2\mathrm{C}\mathrm{l}^{-}\rightarrow \mathrm{C}
\mathrm{l}_{2}+2\mathrm{e}^{-} \Seqnsplit
\label{eq6}
&&\mathrm{C}\mathrm{l}_{2}+\mathrm{H}_{2}\mathrm{O}\rightarrow 
\text{HOCl}+\mathrm{H}^{+}+\mathrm{C}\mathrm{l}^{-} \Seqnsplit
\label{eq7}
&&\text{HOCl }\rightarrow \mathrm{H}^{+}+\mathrm{OC}\mathrm{l}^{-} \Seqnsplit
\label{eq8}
&&\mathrm{H}_{2}\mathrm{O}\rightarrow \bullet \mathrm{OH}+
\mathrm{H}^{+}+\mathrm{e}^{-} \Seqnsplit
\label{eq9}
&&2\text{OH }\rightarrow \mathrm{H}_{2}\mathrm{O}_{2} \Seqnsplit
\label{eq10}
&&\mathrm{H}_{2}\mathrm{O}_{2}\rightarrow \mathrm{O}_{2}+
2\mathrm{H}^{+}+2\mathrm{e}^{-} \Seqnsplit
\label{eq11}
&&\mathrm{O}_{2}+\bullet \mathrm{O}\rightarrow \mathrm{O}_{3}
\end{eqnarray}}\unskip

\begin{figure*}[t!]
\includegraphics{fig02}
\caption{\label{fig2} The 3D response surface graph shows the effect of
process  parameters on \% Inactivation (a) $j$ and $n$; (b) $t$ and $n$;
(c) $t$ and $j$.}
\end{figure*}                                                       

\subsubsection{Effect of NaCl dose (n) on \% inactivation}\label{sec322}

The NaCl concentration in the EO process determines the efficiency and
the amount of RCS formed during the process at MMO anodes. By
increasing the $n$, the bacterial inactivation increases due to the
formation of hypochlorite and chloride ions which get adsorbed on the
surface of the anode either electrochemically or chemically as shown by
the following reactions (\ref{eq12})--(\ref{eq14})~\cite{56}. At an acidic pH, the
generation of HOCl oxidant species in bulk was maximum which dominates
over other oxidant species like Cl$_{2}$, ClO$^-$, thus leading to
indirect oxidation. The production of these ions reacts with the
bacterial cell leading to its inactivation either directly on the
anode's surface or through OH$\bullet$ and indirectly by RCS generated
in bulk. Therefore, the maximum efficiency of this EO process is due to
the synergistic effect between RCS and OH$\bullet$~\cite{45}. From
Figure~\ref{fig2}b, the effect of $t$ and $n$ on \% inactivation can be
analyzed. At lesser $t$ values, the \% inactivation is minimum with high
$n$. With the gradual increase in $t$ values, the \% inactivation also
increases. From 2 to 9~min, the \% inactivation is minimum compared to
the time values from 9 to 16~min, where a gradual increase in \%
inactivation can be observed. With $n$ values of 0.5 to 1.5 g, the \%
inactivation increases with increasing $t$. Further, increase in, $n$
values from 1.5 to 2.5 g, the \% inactivation is maximum (99.59\%) from
12.50 to 16~min which may be due to the synergistic effect of RCS and
OH$\bullet$ radicals which propagated maximum inactivation during the
treatment process.\looseness=-1
{\begin{eqnarray}
&& 6\text{HOCl}+3\mathrm{H}_{2}\mathrm{O}\rightarrow 2\mathrm{Cl}
{\mathrm{O}}_{3}^{-}+4\mathrm{C}\mathrm{l}^{-}+
12\mathrm{H}^{+}+1.5\mathrm{O}_{2}+6\mathrm{e}^{-}\nonumber\\
\label{eq12}\Seqnsplit
&& 3\mathrm{C}{\mathrm{l}_{2}}_{(\mathrm{g})}+6
\mathrm{NaO}\mathrm{H}_{(\mathrm{aq})}\rightarrow 
\text{NaCl}\mathrm{O}_{3}+5\text{NaCl}+3\mathrm{H}_{2}\mathrm{O}\label{eq13}\Seqnsplit
&&3\mathrm{Cl}\mathrm{O}^{-}\rightarrow \mathrm{Cl}
{\mathrm{O}}_{3}^{-}+2\mathrm{C}\mathrm{l}^{-}\label{eq14}
\end{eqnarray}}\unskip


\subsubsection{Effect of treatment time ($t$) on \% inactivation}\label{sec323}

The treatment time is a crucial operating factor in the EO process
since it controls the reaction rate and affects the process economy. To
analyze the effect of time and current density on \% inactivation, the
3-D graph was studied as shown in Figure~\ref{fig2}c. At lower values
of $j$, with an increase in $t$, the \% inactivation was also increasing.
At the same $t$ with higher $j$ values, the \% inactivation was minimum
($\sim$35\%). From $t$ values of 12.50 to 16~min, the \% inactivation
was maximum (99.86\%) and was constant for lower $j$ values. According to
literature, an impermeable layer is generated on the surface of the
electrode during electrolysis, leading to the inactivation of the
electrode surface. Hence, it increases the $t$ of the EO process and
decreases its efficiency~\cite{51}. However, no such problem was
observed in this study, as the used MMO electrode links both the direct
and mediated oxidation process and helps prevent electrode inactivation
during electrolysis.\looseness=-1


\subsubsection{Effect of current density ($j$) and NaCl dose ($n$) on
energy consumption}\label{sec324}

Energy consumption depends on the process parameters and the type of
electrode used. From Figure~\ref{fig3}a, it can be seen that with an
increase in $j$ at lower values of $n$, the energy consumption was maximum
due to the lower solution conductivity and the increase in voltage
drop. But with an increase in $n$ at lower values of $j$, the energy
consumption was constant. At lower $j$ values from 2.38 to 
4.76~mA/cm$^{2}$, the energy consumption was maximum with an increase inn.
At higher $j$ values with increasing $n$ values from 0.5 to 1.0~g/L, the
energy consumption was increasing. Further, increasing the $n$ from 1.50
to 2.50 g/L decreased the energy consumption at higher $j$ values because
of ease in flow of current through the electrolytic solution.

\begin{figure*}[t!]
\includegraphics{fig03}
\caption{\label{fig3}The 3D response  graph showing the effect of
process  parameters on energy consumption  (a) $j$ and $n$; (b) $t$ and $j$.}
\end{figure*}

\subsubsection{Effect of current density ($j$) and treatment time ($t$) on
energy consumption}\label{sec325}

Figure~\ref{fig3}b shows that at higher $j$ values, the energy
consumption gradually increases with $t$ values. Such behaviour may be
attributed to a decrease in ionic concentration, leading to lower
conductance and other side reaction resulting in maximum energy
consumption. At a low $j$ value of 2.38~mA/cm$^{2}$, the energy
consumption increases with an increase in $t$. This might occur as the
electricity consumption is directly proportional to $t$~\cite{43}.

\begin{table*}[t!]
\caption{\label{tab3}Comparative study with previous literature\vspace*{-2pt}}
\fontsize{9.5}{12}\selectfont
\tabcolsep=4.8pt
\begin{tabular}{lccccc}
\thead
Wastewater            & {Microbe}  & {Technique used} &
Removal efficiency &   Current density& References \\
\endthead

\parbox[t]{1.7cm}{\raggedright Synthetic water}       &
\parbox[t]{3cm}{\raggedright\textit{Pseudomonas aeurigonosa}}  &
\parbox[t]{2.5cm}{\raggedright Electrooxidation with boron doped diamond
(BDD) and RuO$_{2}$/IrO$_{2}$ DSA} & \parbox[t]{3cm}{\raggedright{$>$}5
log-unit reduction at 30~min}  &  33.33 mA/cm$^{2}$
&\cite{72}\vspace*{6pt} \\

\parbox[t]{1.7cm}{\raggedright Synthetic urine}       &
\parbox[t]{3cm}{\raggedright\textit{Escherichia coli},
\textit{Pseudomonas aeurigonosa}} &\parbox[t]{2.5cm}{\raggedright 
Electrooxidation with boron doped diamond (BDD)}&
\parbox[t]{3cm}{\raggedright 10$^6$ CFU/mL removal at 60~min for
\textit{E. coli} and 120~min for \textit{P.~aeurigonosa}}&  
5--100 A/m$^{2}$ &\cite{20}\vspace*{6pt} \\

\parbox[t]{1.7cm}{\raggedright Simulated wastewater}  &
\parbox[t]{3cm}{\raggedright\textit{Escherichia coli}}  &
\parbox[t]{2.5cm}{\raggedright Electrooxidation with graphite electrodes}
& \parbox[t]{3cm}{\raggedright 3.2 log reduction at 5~min} & 2--8
mA/cm$^{2}$ &\cite{73}\vspace*{6pt} \\

\parbox[t]{1.7cm}{\raggedright Synthetic urine}       &
\parbox[t]{3cm}{\raggedright\textit{Klebsiella pneumoniae}} &
\parbox[t]{2.5cm}{\raggedright Electrooxidation with mixed metal oxide
(MMO)} & \parbox[t]{3cm}{\raggedright 7 log reduction before 120~min} 
& 5--50 A/m$^{2}$ &\cite{74}\vspace*{6pt} \\

\parbox[t]{1.7cm}{\raggedright Synthetic urine}       &
\parbox[t]{3cm}{\raggedright\textit{Escherichia coli}}  &
\parbox[t]{2.5cm}{\raggedright Electrooxidation with BDD, IrO$_{2}$,
RuO$_{2}$, Pt} & 
\parbox[t]{3cm}{\raggedright Complete deactivation} & 1.34
Ah/dm$^{3}$&\cite{9} \vspace*{6pt} \\

\parbox[t]{1.7cm}{\raggedright Simulated wastewater}  &
\parbox[t]{3cm}{\raggedright\textit{Escherichia coli}, \textit{Bacillus
subtilis}, \textit{Staphylococcus aureus}, \textit{Salmonella
enterica}, \textit{Acinetobacter calcoacetius},  \textit{Serratia
marcescens}, \textit{Listeria} sp., \textit{Enterococcus faecalis}}  &
\parbox[t]{2.5cm}{\raggedright Electrooxidation with mixed metal oxide
(MMO)}& \parbox[t]{3cm}{\raggedright 99.96\% inactivation at 10~min} & 
6.34 mA/cm$^{2}$&\parbox[t]{1cm}{\raggedright Present
study}\vspace*{2pt}
\botline
\end{tabular}
\vspace*{-2pt}
\end{table*}

\subsection{Optimization}\label{sec33}

This study optimized the process parameters such as current density,
time, and NaCl dose to get the maximum bacterial inactivation and
minimum energy consumption by using MMO anodes. The optimum conditions
for the two responses, $Q_{1}$ and $Q_2$, were not the same. Using the
desirability function approach, the optimum conditions for $Q_{1}$ were
selected as maximum, and for $Q_{2}$ as a minimum. Some constraints
were applied to input process parameters to obtain this integer, as
shown in Table~S2.

The optimized values of the process parameters and the responses and
the desirability values for individual and simultaneous optimization
are shown\linebreak in Table S3. The optimum conditions for the process\linebreak variables
were NaCl dose $=$ 1.77~g/L, current density $=$ 6.34 mA/cm$^{2}$, time
$=$ 10~min. At this optimized condition, the responses $Q_{1}$ and
$Q_{2}$, as proposed by BBD, were 99.96\% and 0.58 kWh/m$^3$,
respectively, along with a desirability value of $D = 0.884$. The
experiment was performed under these optimized conditions to
check the
developed model's efficacy. The responses, $Q_{1}$ and $Q_{2}$ at these
optimized conditions, came out to be 99.2\% and  0.42~kWh/m$^3$,
respectively. These values are very close to the ones predicted by the
model, as shown in Table S4. During electrolysis, various ions like
OH$\bullet$, HOCl, Cl$_{2}$, and Cl$^-$ were generated, leading to
direct and indirect oxidation.

Further, the OH$\bullet$ generated in the process helps in direct
oxidation and readily gets converted to H$_{2}$O$_{2}$ and
HO$_{2}\bullet$, thus leading to indirect oxidation. Further, the
presence of RCS also helps in indirect oxidation. Hence, bacterial
inactivation occurs due to direct and indirect oxidation at optimized
conditions. Moreover, the obtained results have been critically
analyzed with the reported studies as depicted in  Table~\ref{tab3}.
The present study uses the novel composition of MMO anode
(TiO$_{2}$/IrO$_{2}$/RuO$_{2}$/PtO$_{2}$) with low current
density of 6.34 mA/cm$^{2}$ for the complete inactivation of bacterial
consortium within a treatment time of 10~min. Thus, it is concluded
that the technique is economically feasible at lower current density
and treatment time.\looseness=-1

\begin{figure*}[t!]
\includegraphics{fig04}
\caption{\label{fig4}SEM and EDS images of MMO anode showing peaks of
Ti, Ru, O, Lr, Pt along with their atomic composition (a) Fresh MMO and (b)
Recycled MMO.
%\vspace*{-5pt}
}
\end{figure*}

\subsection{Characterization of MMO anodes}\label{sec34}


\subsubsection{SEM/EDS analysis}\label{sec341}

To characterize the surface morphology and elemental composition of MMO
anodes, SEM-EDS was performed for both fresh and recycled
anodes Figure~\ref{fig4}a,b. The SEM images for both fresh and
recycled anodes show almost similar structural characteristics even
after 50 cycles, thus indicating the uniform layer of metal oxides. The
incorporation of Ir, Ru, and Pt oxides in the titanium metal sheet has
made the electrode surface porous and smooth with slight cracks, thus
preventing the electrodes from corrosion and increasing the stability
for a more extended period~\cite{57}. The pronounced peaks of all
the three metals, i.e., Ir, Ru, and Pt in the recycled anode, along
with the peaks of Ti, and O, have proved the durability of electrodes
even after 50 cycles. The quantitative analysis of the electrodes was
performed by EDS. It depicts that the atomic concentration of the metal
oxides of Ti, Ru, Ir, Pt, and O were almost similar for both fresh and
recycled anodes after 50 cycles. Such results confirm the stability of
electrodes after 50 experimental runs as shown in 
Figure~\ref{fig4}a,b.\looseness=1

\subsubsection{XPS analysis}\label{sec342}

The XPS spectra of both fresh and recycled anodes Figure~\ref{fig5}
was performed in order to analyze the metal elements' oxidation state
and to study the molecular information associated with electrode
surface chemistry~\cite{58,59}. The results indicate no drastic
change in the oxidation state of the metals as well as each metal
element present after 50 cycles. As shown in Figure~\ref{fig5}a, in
the Ti 2p spectrum, the two peaks at 458.5~eV and 464.3~eV correspond
to the binding energies of Ti $2\mathrm{p}_{3/2}$ and Ti $2\mathrm{p}_{1/2}$ states for
both the fresh and recycled anodes~\cite{60}. Figure~\ref{fig5}e,
shows the spectrum of O 1s signal at 531.47~eV, which corresponds to a
broad peak due to the formation of Ti--O bonds.
Figure~\ref{fig5}b,c and d, shows the spectrum signal of Ir 4f, Ru 3d, and
Pt 4f for both fresh and recycled anodes. Pt signal spectrum is
indicated at 74.2~eV. It shows the signal of the Pt (v) oxidation state
at the $4\mathrm{f}_{5/2}$ level, which further corresponds to the formation of
Pt--Ti bonds. However, for Ru, the peak was observed at 284.8~eV while
for Ir, the peaks were observed at 61.6~eV and 63.2~eV. The signals
obtained from the Ru and Ir spectrum were linked with Ru $3\mathrm{d}_{3/2}$,
and Ir $4\mathrm{f}_{7/2}$, Ir $4\mathrm{f}_{5/2}$, respectively, indicating the
formation of hydrated metal oxides of RuO$_{2}$ and IrO$_{2}$. The
studies reported in the previous literature correspond to the results
in the present study~\cite{61,62,63}.

\begin{figure*}[t!]
\includegraphics{fig05}
\caption{\label{fig5}XPS graph of both fresh and recycled MMO long with
their spectrum (a) Ti 2p, (b) Ir 4f, (c)~Ru~3d, (d) Pt 4f and (e) O 1s.}
\end{figure*}

\subsubsection{XRD analysis}\label{sec343}

The X-ray diffraction study was performed for both fresh and recycled
MMO anodes. The XRD \unskip\break analysis was applied to study the crystalline
structure of the metal oxides coated on titanium sheet. Further,
prominent peaks of the metal oxides of Ti, Ru, Ir and, Pt was observed
in the recycled anode even after 50 experimental runs thus proving the
metals' intactness as shown in Figure~S2. The diffraction peaks of
titanium (JCPDS card: 01-089-3073), titanium oxide (JCPDS card:
01-089-8303), iridium oxide (JCPDS card: 01-088-0288), ruthenium oxide
(JCPDS card: 00-040-1290), and platinum oxide (JCPDS card:
00-021-0613).

\subsubsection{Electrochemical analysis}\label{sec344}

The cyclic voltammetry (CV) study was done in order to characterize the
electrochemical activity of MMO anodes as shown in Figure~S3. The
reference electrode was a calomel electrode with platinum as a counter
electrode with a scanning rate of 500~mV/s. The full CV scan of the MMO
anode was recorded in the potential range of $-$1.0 to 0.4 V. As it can
be seen that for cycle 1 the oxidation peak was observed at ${\sim}$7~mA, 
but for cycles 15, 30, 45 and, 50 the oxidation peak was stable at
${\sim}$20~mA. Thus, the stability of MMO anodes after 50 experimental
runs is proved~\cite{64,65,66}.

\begin{figure*}
\includegraphics{fig06}
\caption{\label{fig6}Plot of mineralization at an optimized condition
of (current density $=$ 6.34~mA/cm$^{2}$, NaCl dose~$=$~1.77~g, time
$=$ 10~min). (a)~TAC graph of before and after treatment of simulated
wastewater containing bacterial consortium. (b)~Potassium ion leakage
graph of simulated wastewater at different time intervals under
optimized condition. (c)~Durability graph of MMO anodes after 50
recycles showing no loss in the inactivation efficiency of electrodes.}
\end{figure*}

\subsubsection{Hydroxyl radical test}\label{sec345}

In order to see the efficacy of the EO process, EO has been performed
under optimized conditions to confirm the production of OH$\bullet$ at
MMO. Experiments were performed in absence and in presence of NaCl in
an aqueous solution containing 0.5~mM TPA in 1M NaOH.
Figure~S4s confirmed that the production of OH$\bullet$ was
maximum at 2~min, and with increasing time, the generation of
OH$\bullet$ decreased when NaCl was added to the solution. However,
from Figure~S4, it was concluded that the generation of OH$\bullet$ at
an acidic pH of 3.8 was maximum for 10~min. With increasing time, the
generation of OH$\bullet$ was increased when no NaCl was added to the
solution. This concludes that at an acidic pH, the rate of OH$\bullet$
adsorption is high on MMO anodes leading to the direct oxidation of the
compound. To verify the synergistic effect of RCS and OH$\bullet$, an
experiment was performed to measure the \% inactivation rate Figure~S5.
Here, the absorbance of the sample solution having bacterial consortium
with NaCl and TPA (scavenger of OH$\bullet$) was measured at 600~nm in
order to observe the effect on the \% inactivation rate. No significant
elimination of bacterial consortium was observed when the sample
solution was treated with only current and TPA. In contrast, ${\sim}$95\% 
and ${\sim}$98\% inactivation was observed when the bacterial
\mbox{consortium} was treated with NaCl and both NaCl and TPA respectively.
Thus, it is concluded that the inactivation rate depends mainly on the
RCS\break generation.

\subsection{Durability study}\label{sec35}
The durability and the stability of MMO anodes have been studied in
order to check the economic cost and the practical feasibility of the
EO process on a commercial scale. In particular, the durability of the
electrodes has been evaluated in terms of the number of recycles and
the inactivation efficiency of bacteria, as shown in
{{Figure~\ref{fig6}c.}}
The electrodes were thoroughly used for 50 cycles
without any significant loss of the metal oxides. Conditions for 50
cycles were according to the experimental runs as suggested in
Table~\ref{tab1}. The high activeness of the MMO anodes was due to
the~minimum amount of NaCl concentration used at lower current density
values. Due to the \mbox{presence} of IrO$_{2}$ in the MMO anodes, it can be
used for a maximum of 5 years. These MMO anodes can produce a
magnificent amount of RCS and ROS due to TiO$_{2}$, IrO$_{2}$, and Pt,
leading to direct and indirect oxidation~\cite{67}. The durability
of MMO after 50 cycles was further confirmed through SEM-EDS, and XPS
analysis, as discussed in Section~\ref{sec34}.


\subsection{TAC analysis (total available chlorine)}\label{sec36}

To check the quality of the untreated and treated simulated wastewater,
analytical test such as TAC was performed under optimized conditions.
From Figure~\ref{fig6}a, it was observed that the TAC level increased
during the EO treatment of simulated wastewater after a treatment time
of 10~min. The TAC is a mixture of reactive intermediates comprising
chloramines such as (NH$_{2}$Cl) and free chlorine (Cl$_{2}$,
HOCl)~\cite{68}. Thus, it is concluded that the RCS produced
during electrolysis using MMO anode is responsible for the inactivation
of bacteria present in the simulated\break wastewater. 

\subsection{Bacterial cell damage checked by potassium ion leakage
test}\label{sec37}

The outer membrane of the bacterial cell serves an essential function
of barrier to the permeability of the intracellular substances. The
bacterial cell damage was due to RCS, which damages the cell wall and
the outer membrane of bacteria produced during the EO treatment of
simulated wastewater. Thus, It leads to  nd increased permeability and
leakage of intracellular substances like $\mathrm{K}^{+}$ from the
cell~\cite{11}. The leakage of $\mathrm{K}^{+}$ ions from the damaged
bacterial cell was studied for 10~min. The $\mathrm{K}^{+}$ ion concentration
increased from 1.63 ppm to 1.78 ppm Figure~\ref{fig6}b. The $\mathrm{K}^{+}$
ion was released entirely from the inactivated bacterial cell after a
treatment of 10~min. Thus, it is concluded that the membrane
permeability of bacterial cells was disrupted during the EO process.

\subsection{Operating cost analysis}\label{sec38}
To commercialize the EO treatment technology at large scale, it is
mandatory to estimate the total cost of the treatment process, which
should be economically feasible. Hence, the electrical energy consumed
and the cost of the electrodes have been considered for the economic
evaluation of the treatment process. The total operating cost for the
inactivation of bacteria in simulated wastewater was determined to be
0.189 \$/m$^{3}$ (Table S5). Such value indicates that the EO process
by MMO is economically feasible. Few researchers have reported the
operating cost analysis for the treatment of different
wastewaters~\cite{68,69,70,71}. Further, 
the operating
cost can be minimized during the scale-up studies by modifying the
design of the electrolytic reactor and the operating\break conditions.

\section{Conclusion}\label{sec4}

The EO treatment of bacteria using titanium-based MMO was performed.
The optimized process parameters from BBD were found to be NaCl\unskip\break dose $=$
1.77~g/L, current density $=$ 6.34~mA/cm$^{2}$, time $=$ 10~min for
obtaining the maximum degradation. At these optimized conditions, the
values of responses $Q_{1}$ and $Q_{2}$ were 99.2\% and 
0.42~kWh/m$^{3}$, respectively, and a combined desirability 
$D = 0.884$. The bacterial inactivation was found to be maximum because of
both direct and indirect oxidation involvement due to the formation of
strong oxidants, OH$\bullet$ and RCS like HOCl, Cl$_{2}$, and Cl$^-$.
Further, TAC proved the inactivation of bacteria in simulated
wastewater after a treatment time of 10~min. The characterization
studies like SEM-EDS and XPS proved the stability and durability of MMO
anodes for bacterial inactivation even after 50 cycles. The potassium
ion leakage test further confirmed the bacterial damage. The present
study indicates the efficiency of MMO anodes for further research
analysis towards eco-sanitation and opens up a new approach for the
on-site treatment of wastewater.

\section*{Conflicts of interest}

The authors declare no competing interest.

\section*{Authorship statement}

All authors certify that they have participated sufficiently in the
work to take public responsibility for the content, including
participation in the concept, design, analysis, writing, or revision of
the manuscript. Furthermore, each author certifies that this material
or similar material has not been and will not be submitted to or
published in any other publication.

\section*{Authorship contributions}
\begin{enumerate}[(1)]
\item Conception and design of the study: AV, DC, PC

\item Experimentation: PC

\item Analysis/Interpretation of Data: PC

\item Drafting the Manuscript: PC, AV, DC

\item Revising the manuscript critically for important intellectual
content: AV.
\end{enumerate}

\section*{Ethics approval}

Not applicable.

\section*{Consent to participate} 

The authors have read and approved the final manuscript.

\section*{Consent for publication}

The authors agree to publication in this journal.

\section*{Funding}
This research did not receive any specific grant from funding agencies
in the public, commercial, or not-for-profit sectors. PC is thankful to
the Thapar Institute of Engineering and Technology for providing the
fellowship.

\section*{Acknowledgments}
The authors would like to thanks the Sophisticated Analytical
Instruments Laboratories, TIET, Punjab and IIT Roorkee, India for
providing their facilities for the characterization of samples.


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\section*{Supplementary data}

Supporting information for this article is available on the journal's
website under \printDOI\ or from the author.  

\CDRsupplementaryTwotypes{supplementary-material}{\cdrattach{crchim-225-suppl.pdf}}

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