8.78% Efficient All-Polymer Solar Cells Enabled by Polymer Acceptors Based on a B←N Embedded Electron-Deficient Unit

Article abstract of DOI:10.1002/adma.201904585

In the field of all-polymer solar cells (all-PSCs), all efficient polymer acceptors that exhibit efficiencies beyond 8% are based on either imide or dicyanoethylene. To boost the development of this promising solar cell type, creating novel electron-deficient units to build high-performance polymer acceptors is critical. A novel electron-deficient unit containing B←N bonds, namely, BNIDT, is synthesized. Systematic investigation of BNIDT reveals desirable properties including good coplanarity, favorable single-crystal structure, narrowed bandgap and downshifted energy levels, and extended absorption profiles. By copolymerizing BNIDT with thiophene and 3,4-difluorothiophene, two novel conjugated polymers named BN-T and BN-2fT are developed, respectively. It is shown that these polymers possess wide absorption spectra covering 350–800 nm, low-lying energy levels, and ambipolar film-transistor characteristics. Using PBDB-T as the donor and BN-2fT as the acceptor, all-PSCs afford an encouraging efficiency of 8.78%, which is the highest for all-PSCs excluding the devices based on imide and dicyanoethylene-type acceptors. Considering that the structure of BNIDT is totally different from these classical units, this work opens up a new class of electron-deficient unit for constructing efficient polymer acceptors that can realize efficiencies beyond 8% for the first time.

Full text of DOI:10.1002/adma.201904585

Article
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Cite This: Energy Fuels 2019, 33, 4340−4351
Optimization of Biomethane Production in Mono-Cardboard
Digestion: Key Parameters Influence, Batch Test Kinetic Evaluation,
and DOM Indicators Variation
Dunjie Li,†,∥ Liuying Song,†,∥ Hongli Fang,† Yue Teng,‡ Hongfei Cui,† Yu-You Li,§ Rutao Liu,†
and Qigui Niu*,†
†School of Environmental Science and Engineering, China-America CRC for Environment & Health, Shandong University, 72#
Jimo Binhai Road, Qingdao 266237, Shandong, P. R. China
‡Jiangsu Key Laboratory of Anaerobic Biotechnology, Jiangnan University, Wuxi 214122, P. R. China
§Department of Civil and Environmental Engineering, Graduate School of Engineering, Tohoku University, 6-6-06 Aoba, Aramaki,
Aoba-ku, Sendai 980-8579, Japan
S
* Supporting Information
ABSTRACT: Mono-cardboard waste digestion in batch tests associated with different impact factors was investigated. The
maximum methane generation was 394 mL/gVSadd with the best F/M of 0.5 at mesophilic conditions. The highest methane
content reached 75% in the dynamic water bath feeding with an average particle size of 1−3 mm. Hydrolysis and
methanogenesis were significantly different between static and dynamic states, especially at particle size over 3 mm. The
modified Gompertz model (R2 > 0.98) and the modified Aiba model (R2 > 0.88) were the most appropriate models for methane
generation among the six kinds of models. At different TS, the variation of dissolved organic matters reflects the metabolic rate
of the microbial community. The soluble microbial product-like and protein-like components half split by excitation−emission
matrix-parallel factors significantly negatively corresponded to biomethane production. Moreover, a rapid loss of
methanogenesis was observed with high organics concentration. A strong correlation between the F/M ratio and the CH4
generation ability was observed with an optimized F/M of 0.5. The maximum energy production was also investigated based on
the optimized particle size of 2−5 mm and F/M of 0.5, in which long-term stability was maintained.
scarcely been reported. In practice, tackling the characteristics
of the mono-cardboard digestion is urgently needed for
understanding the optimum conditions for waste reduction
with energy generation and the potential engineering
application.
Moreover, mathematical models were used to observe,
predict, simulate, and optimize the system’s behavior at
different conditions. Practically, response surface methodology
facilitates statistical analysis within multidimensional design
spaces9 and the kinetic models provide the metabolic
information for the optimal management of digestion.10 In
addition, to better realize the hydrolysis of the digestion, the
dissolved organic matter (DOM) composition and variation
were evaluated to reveal the process stability.
Therefore, the main objective of this study is to evaluate the
kinetics of biomethane production, and the influence
parameters on mono-cardboard digestion, such as the
optimized feeding TS, F/M ratios, substrate particles, process
operation, temperature shocks, and the C/N. The optimal
condition with kinetic parameters of mono-cardboard
digestion is crucial for the successful operation. The obtained
sustainable waste treatment of mono-cardboard digestion
could be a possible commercial application.
1. INTRODUCTION
The rapidly developing e-commerce in China, especially the
huge amount of cardboard produced by express business has
caused environmental issues. There were 4 billion boxes used
for express in 2017. Particularly, 2 billion cardboards were
generated by the business.1 Traditionally, the cardboard was
disposed by burning or landfilling, which could cause
secondary pollution impacting the environment and personal
health. In addition, paper and cardboard were the major
biodegradable organic fractions of municipal solid waste based
on the data survey.2,3 Understanding the cardboard digestion
was essential for the municipal solid waste treatment.
Meanwhile, anaerobic digestion (AD) is considered as one
of the most successful technologies commonly employed to
stabilize and reduce the organic wastes for sustainable
alternative energy recovery (biomethane). Digestion as a
sustainable waste management solution for cardboard could be
used in a wider range of applications.4 The successful digestion
application needs to be monitored and controlled to maintain
good performance especially for mono-cardboard digestion
and on-site digestion system.5 Previous studies have mostly
focused on the co-digestion with food waste,6 adjusting the C/
N with other substrates7 and the effect of shredding
pretreatment.2 Also, Ferraro8 used to improve biomethane
production from lignocellulosic materials by bioaugmentation.
However, the contribution of mono-cardboard waste in
digestion and its potential for methane generation have
Received: February 11, 2019
Revised: April 22, 2019
Published: April 23, 2019
© 2019 American Chemical Society
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the reaction and transferred to the standard atmospheric
pressure.
2. METHODOLOGY
2.1. Feedstock and Inoculums. The anaerobic inoculum
was obtained from a good condition UASB reactor in this
study. Cardboard was taken from packaging case with
pretreatment of grinding granularity from 0.1 to 1 cm. Serial
batch tests were analyzed with cardboard under different
conditions. The characteristics of cardboard and seed sludge
are shown in Table 1.
2.3. Excitation−Emission Matrix (EEM)-Parallel Factor
(PARAFAC) Analysis. Fluorescence EEMs were measured on
an F-4600 spectrophotometer (Hitachi, Japan) with emission
spectra from 200 to 550 nm at 0.5 nm increments and the
excitation wavelengths from 200 to 450 nm at 5 nm
increments. The inner-filter effect of fluorescence of each
sample was corrected by deducting Milli-Q water blank. The
split-half validation was carried out with MATLAB 8.5
(MathWorks, Natick, MA) based on the modified drEEM
toolbox protocol.12
Table 1. Characteristics of Seed Sludge and Cardboard
Waste for the Batch Experiments
a
2.4. Chemical and Statistical Kinetics Simulations.
The pH, alkalinity, COD, NH+4, TS, VS, TN, and TP were
analyzed according to standard methods.13 The C, H, O, N,
and S organic elements were measured by an organic
elementar (Vario Macro Cube). The methane content was
measured by a saturated NaOH solution to capture CO2. As
described in our previous study,14 free volatile fatty acid (VFA)
concentration was calculated according to the equilibrium eq 1
component
seed sludge
cardboard waste
TS
VS
COD
nitrogen
TP
C
H
O
N
S
12.94%
9.52%
0.17 g/g*
37.60 mg/g
33.07 mg/g

93.6%
87.6%
1.26 g/g
5 mg/g
4.6 mg/g
40.7%
5.22%
53.06%
0.38%


TVFA
free VFA =

(1 + 10−pK +pΗ
)
a
(1)

0.65%
a
: no detection; *: g/g (wet sludge).
where free VFA = free VFA concentration (mg/L); TVFA =
total VFA concentration (mg/L); pKa = dissociation constants
of the individual VFAs, with values of 4.757, 4.874, 4.812, and
4.835 for acetic, propionic, butyric, and valeric acids at 25 °C,
respectively.
The biogas and biomethane were simulated using a
modification of the first-order kinetics15 (eq 2), the modified
Gompertz model16 (eq 3), the Fitzhugh model17 (eq 4), the
cone model18 (eq 5), the transference model19 (eq 6), and the
modified second-order model20 (eq 7), which can be written as
2.2. Experimental Design. Design-Expert 8.05 software
was used to make a design for the surface response analysis
focusing on the TS fraction, temperature (T), and substrate C/
N. The details of the experiment are described in the
Supporting Information. One factor analysis was conducted
in a batch vial with an effective volume of 100 mL. Each vial
was inoculated by seed sludge with 10 g of NaHCO3 buffer
solution to keep the initial pH around 7.5. Pure nitrogen gas
was used for gasifying the oxygen outside the headspace and
liquid phase for 25 min. The batch tests were performed by
shaking at 120 rpm (except the static digestion) in mesophilic
condition at 35 2 °C press-balanced after 5 min warming.
Biogas production was measured using a syringe and converted
to the standard conditions. The carbon dioxide contents were
captured completely by a saturated NaOH solution, with the
measured value for biomethane, as described in our previous
report.11 The biogas and biomethane were measured following
dM(t)
dt
G(t) =
G(t) =
G(t) =
= B0(1 − exp(−Kmaxt))
(2)
Ä
É
Å
Å
Å
Ñ
Ñ
Ñ
K
maxe
B0
dM(t)
dt
Å
Å
Å
Ñ
Ñ
Ñ
= B exp
(λ − t) + 1
0
Å
Å
Ñ
Ñ
Å
Ñ
(3)
(4)
Å
Ç
Ñ
Ö
dM(t)
dt
= B0(1 − exp(−Kmaxt)n)
Figure 1. Simulation of bio-CH4 yield at different F/M ratios by six kinetic models.
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Figure 2. Biogas production simulation at different particle sizes both in static (35 °C of 5, 2, and 1 mm) and dynamic states (35 °C, 120 rpm of 5,
2, 1, 0.5, 0.15 mm, and 1 cm).
B0
2, resulting in biomethane yield even lower than 190 mL
(Figure 1). High F/M means that the quantitative micro-
organisms were subjected to high organic loads and even
exceed the microorganisms handling capacity, which could
cause the failure of digestion (Figure S2). Moreover, the
decreased trend in this study was consistent with previous
findings that high F/M exceeds the consumption capacity of
the inoculum in the system.22 Subsequently, the kinetic
analysis had indicated that there is a demarcation point at F/
M of 0.5 (Table 2). The maximum methane potential B0
estimated by the five models showed a downward trend from
F/M of 0.5 to F/M of 2. This observation was in line with the
previous study by Hamza,23 who found that the favorite F/M
ratio of 0.5−1.0 gCOD/gSS was beneficial to the stable long-
term granule stability, but methane production showed a
downward trend over the optimal ratio. Meanwhile, the lag
phase times of all of the experiments were short even with the
longest time of 2 h at the F/M of 0.5. This indicated that the
sludge had a high activity and the mono-cardboard has high
biodegradability. Moreover, the methane production tmax was
found in two peaks, the first peak was found at the time of 75 h
for most tests since the degradable organic matters in the
substrate were converted into methane, while the second peak
was found at 275 h with the gradual methanogenesis followed
the hydrolysis (Figure S2). The multipeak of tmax revealed that
the hydrolysis is the rate-limited step in the digestion, and the
capacity of methanogenesis was high with a well-worked
metabolic network.
It is worth mentioning that a strong correlation was found
between the F/M ratio and biomethane production (Figure 1
and Table 2). The results indicated that the high F/M was not
feasible for the methanogenesis of cardboard digestion. The
inappropriate substrate to inoculum ratio led to the excessive
production of organic matter, which was immediately trans-
formed into VFAs in the acidogenesis phase causing
inhibition.24,25 Therefore, based on the experiment, the
optimized F/M was suggested to be 0.5 in the mono-digestion
of cardboard.
3.1.2. Mesophilic Methane Production at Different
Particle Sizes. The particle size was closely related to
hydrolysis,26 especially for the high molecular compound
biodegradation for avoiding both the substantial mechanical
problems and energy consumption.27 In this study, different
dM(t)
dt
G(t) =
=
1 + (Kmaxt)n
(5)
dM(t)
dt
G(t) =
G(t) =
= B0(1 − exp(−Kmax(t − A)/B0)
(6)
dM(t)
dt
= B0 × t × t/(t2 + Kmaxt + Kmax Kmax
)
2
2
(7)
where G is the methane production rate (mL/gVS/d), B0 is the
biogas or biomethane accumulation concentration (mg/L),
Kmax is the maximum biogas (biomethane) accumulation rate;
Kmax is the maximum removal rate of two-phase model; λ is
defined as the x-axis intercept of this tangent (mg/L); and n is
the shape factor.
2
The methane production rate at tmax eq 3 was obtained when
G achieves Kmax (at tmax point), which can be calculated as
P
Kmax
tmax = λ +
e
(8)
3. RESULTS AND DISCUSSION
3.1. Batch Performance and Kinetic Analysis.
3.1.1. Mesophilic Methane Production at Different Food-
to-Microorganism Ratio (F/M). The cumulative biogas and
biomethane production of each batch test was measured in
individual regular patterns (Figures 1 and S1). The control
batch test showed that less than 100 mL of biogas were
generated. However, at an F/M of 0.5, a maximal biogas
production of 650 mL was obtained with a methane content of
69%, which was 5.8 times higher than the control. The
maximum biogas and biomethane yields were 621 and 476 mL,
respectively. Additionally, the high F/M to led a low biogas
and biomethane production with a gradual decrease followed
by the F/M ratio increase. Particularly, at the F/M ratio from 1
to 2, the biogas yield remained around 200 mL, which was less
than half compared to an F/M of 0.5. Similar results of a large
inoculum amount allowed successful digestion in a batch
process without pH adjustment in the assessment of the
biomethane potential production.21 However, at an F/M of
1.5, the biogas and biomethane yields were decreased to 269
and 197 mL, respectively. Meanwhile, the F/M increased up to
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Table 4. Kinetic Simulation of Different Models for Biogas and Biomethane at Different TS Feeding
TS (%)
0.5
2.5
5
10
30
20
y = B0(1 − exp(−kx))
y = B0(1 − exp(−kx)n)
B0
k
B0
k
136.71
0.008
136.71
0.09
120.41
0.01
120.41
0.10
120.00
0.011
120.00
0.11
114.43
0.013
114.43
0.11
98.67
0.013
98.67
0.11
102.72
0.012
102.72
0.11
n
B0
k
0.09
126.77
0.01
0.10
172.63
0.01
0.11
158.48
0.01
0.11
128.08
0.02
0.11
157.92
0.01
0.11
130.14
0.01
y = B0/(1 + (kx)(−n)
)
n
1.86
0.95
1.00
1.30
0.79
1.06
y = B0(1 − exp(−k(x − A)/B0))
P exp(−exp(K × 2.72 × (A − x)/P + 1))
y = Pxx/(xx + K1x + K2K2)
B0
k
A
P
K
A
P
K1
K2
130.84
1.26
5.80
113.04
1.01
10.65
201.27
165.99
0.00
122.77
1.17
−3.15
112.65
0.75
−10.45
164.25
114.31
0.00
121.54
1.36
−2.45
113.90
0.84
−10.08
159.08
93.63
0.00
114.29
1.52
0.25
107.26
0.97
−3.70
150.29
83.43
0.00
101.57
1.16
−5.59
95.97
0.68
−16.67
126.93
78.47
0.00
103.76
1.21
−1.91
97.02
0.76
−8.77
135.73
90.17
0.00
Figure 3. Batch experiment performance of VFA analysis at 15 °C (a), 35 °C (b), 55 °C (c), DOM analyzed of extra and inner cell (d−f) by EEM.
particle sizes in batch tests in both static and dynamic states
were conducted to investigate biomethane production (Table
3). Significantly, the substrate particle size was more critical in
the dynamic state than in the static state, which was mainly
dominated by energy consumption and biomass transfer. In the
dynamic state, the mass transfer was faster than in the static
state due to the particle size reduction.28,29 Although, it was
hypothesized that small particles increased the available surface
area of digestive enzymes, while larger particles led to longer
transit time of absorption and metabolism. Zhang30 also
pointed out that the utilization rate of the maximum substrate
was doubled when the average particle size of FW decreased
from 2.14 to 1.02 mm, more specifically, cellulolytic enzymes
were important for the breakdown of cardboard.31 Interest-
ingly, the results showed that there was no significant trend
between the static and dynamic states. The particle size
between 0.5 and 3 mm in static conditions and between 2 and
5 mm in dynamic conditions all obtained high methane
generation (Figures 2 and S3). According to their research, the
maximum cumulative methane production was obtained at the
particle size of 0.6 mm. Consequently, the particle sizes below
1 cm had a positive effect on the rate of VS reduction,
accompanied by an increase in the total production of VFAs.
3.1.3. Thermophilic Methane Production at Different TS.
To investigate the optimal TS of feeding, a series of TS were
used for the kinetic evaluation (Table 4). Concerning the
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Figure 4. Response surface curve of the relationship between TS, T, and C/N (a−c); EEM-PARAFAC (d) of extra cell DOM (e) and inner cell
DOM (f) variation.
stability of digesters, pH values were stable (6.8−7.5). Except
for the modified 1 order model (eq 7), the other simulated
models obtained a high fitting rate with the R2 over 0.97. The
first-order kinetics model (eq 2), the modified Gompertz
model (eq 3), and the Fitzhugh model (eq 4) fitted the result
well with R2 of 0.997, 0.95, and 0.993, respectively. The highest
simulated Kmax of different feeding were all obtained at TS of
10% with 0.013 of the first-order kinetics, 0.11 of the Fitzhugh
model, 0.02 of the Cone model, 1.52 of the Transference
model, and 0.97 of the modified Gompertz model. For the
Transference model and the modified Gompertz model, there
was no obvious lag phase on the TS adding. Evaluation of the
kinetic models’ results suggested that the hydrolysis constant
(k) may not be a universal constant because it is specifically
calculated for a given sample under certain conditions.
High TS significantly decreased the biomethane yield and
the production rate (Table 4), since the low available water
concentration could affect the microbial mobility or nutrients
and enzymes transport. Moreover, among the composition of
cardboard, cellulose and hemicellulose are fermentable after
hydrolysis, but lignocellulosic biomass was resistant to
degradation by microbes. The accumulation of digestion
intermediates, such as ammonia and volatile fatty acids
(VFAs), may lead to system instability. The low water contents
could slow the mass transfer between the inoculum or
feedstock and decreased the mass transfer about 60% when
TS increased from 20 to 30%.32,33 The inhibited biomethane at
high TS in this study agreed with previous studies of batch AD,
which amended with 14% TS.34 In this study, the degradable
properties of the organic compositions were required to be less
than the TS of 10%.
3c) with the EEM variation. More information can be found in
Figures S4 and S5. While at the fixed C/N of the initial
experiment without nitrogen addition, the biomethane
production increased with the increase of T. The highest
biomethane appeared at 55 °C and a TS of 10% (Figure 4).
Moreover, according to this diagram at a C/N of 75, the
optimum biomethane production was achieved at a TS of 10%
at 55 °C and a TS of 30% at 15 °C; however, the increased C/
N of 150 shows the opposite result, i.e., optimum biomethane
production at a TS of 30% and 15 °C. This phenomenon may
explain that there was more free ammonia in the system at high
temperature (T) causing inhibition. The relationship between
C/N and T showed a gentle positive effect of T on the
methane generation both at the TS of 10 and 20%, but a
significant difference at a TS of 30%. However, the TS was
changed to 30%, and without this effect, the methane
production increased significantly with increasing C/N at 15
°C. Our results showed low TS digestion due to high
biomethane production (Figure 4a) and Kmax of biomethane
production rate (Figure 4b) even at low temperature.
However, the low TS and low T led to a longer lag phase at
a fix optimized C/N of 60 (Figure 4c). Response surface
methodology was well applied for this study based on the
previous study.35
Moreover, the results of this study strongly supported that
the temperature shock decreased the activity of methanogens.
Even though the microbial community could adapt to the
environment, however, a temperature shock could affect
microhabitat, making the activity weak, especially for
acetogenic methanogens. A similar decrease of the genus and
the specific functional genus in activity treatment was reported
by Tian.36 The microbe could not afford or resist the shock in
such a narrow time; moreover, the activity of microbes that
accommodated mesophilic conditions was decreased while
transferred to thermophilic conditions directly. In addition, for
biomethane production, the terms of C/N and TS showed a
significantly positive effect on the production and production
rate. The effect of interaction among the TS, C/N, and
3.2. Response Surface Analysis of the Impactor
Factor of TS, T, and C/N. 3.2.1. Methane Production and
Kinetic Analysis. Three central impacted factors, TS, temper-
ature, and C/N, in batch experiment were selected to generate
the response surface curve for mono-cardboard digestion
(Figures 3 and 4). The performance of VFA analysis is shown
at 15 °C (Figure 3a), 35 °C (Figure 3b), and 55 °C (Figure
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Figure 5. Pearson’s correlation analysis between the PARAFAC component and the parameters in different TS digestion (a), and response surface
analysis experiment (b). The strength of correlation is defined by a color code with red indicating positive correlation and blue indicating negative
correlation (***p < 0.01; **p < 0.05).
temperature on the biomethane production can be observed by
three-dimensional response surface plots, as shown in Figure
4a. The greatest biomethane generation was observed at a
temperature of 35 °C and a TS of 10%. These findings strongly
suggested that the synthetic interactions of hydrolysis,
acidogenesis, acetogenesis, and methanogenesis took place
rapidly and developed a stable conversion rate. This
phenomenon was corresponding to the optimization of TS,
C/N, and temperature.
Analysis of variance analysis showed that the TS was a
significant factor, in addition to the interaction of T and TS.
Multivariate statistical analysis in terms of actual factors is
described as below in eq 9
Similar to CH4 production, the methane production rate Kmax
had the biggest contribution of TS for single-factor interaction
and the most significant interaction of TS and C/N for the
two-factor interaction. While referring to the methane
production lag phase time, the equation can be described as
follows (eq 11)
A = −24.17144 + 0.20621 × T + 2.49418 × TS
+ 0.10260 × C/N − 0.037997 × T × TS
− 1.73073 × 10−4 × T × C/N − 5.32117 × 10−3
(11)
× TS × C/N
This response surface study allowed us to establish a rapid
method for investigating the effects of temperature (T),
substrate TS, and C/N ratio on the methane production.
3.2.2. EEM Variation and Process Indicator. The results of
biogas/methane (Figure S4) and VFA-DOM variation in both
extracellular and intracellular conditions showed a significant
difference among the batch tests (Figure 3). DOM as an
important indicator of digestion contains different kinds of
soluble matters such as soluble microbial production (SMP),
carbohydrates/polysaccharides, amino acids/peptides/pro-
teins, lipids, humiclike substances, and anthropogenic organic
pollutants.37 In the present study, the fluorescence peaks were
divided into six dominated components (Figure 3d). The
components of DOM which were closely associated with
hydrolysis and acidogenesis in the digestor were described as
individual samples by the half-spilt model, according to a
similar previous report.38−40
BCH = +597.01916 − 6.53552 × T − 15.56593 × TS
4
− 0.88524 × C/N + 0.16472 × T × TS
− 1.14640 × 10−3 × T × C/N + 0.046870
(9)
× TS × C/N
The effect of TS was higher than T and C/N, while the
interaction of TS and C/N was more important than other
factors. The Kmax of biomethane production rate can be
described as in eq 10
Kmax = 4.14177 − 0.040708 × T − 0.11142 × TS
C
N
− 6.68247 × 10−3
×
+ 1.12701 × 10−3 × T
× TS − 8.22192 × 10−6 × T × C/N
+ 3.38623 × 10−4 × TS × C/N
(10)
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Figure 6. Optimized biomethane production of mono-cardboard digestion particle size (a), F/M (b), TS (c), energy output response to TS (d),
and energy output response to F/M (e).
Component 1 (C1) exhibited a primary fluorescence peak at
λex/em = 220/260 nm, which can be characterized as tyrosine-
like protein. C2 exhibited at λex/em = 270/350 nm were usually
defined as SMP-like organics including bio-protein and
biological production, while C3 at λex/em = 220/350 nm is
usually defined as tryptophan-like aromatic protein. The
microbial protein-like component at λex/em = 230(280)/280
nm (C4) shows a mixture peak traditionally defined in ref 41.
Component 5 as the humiclike organic matter shows a broad
peak at λex/em = 250−400/350−500 nm in the limited
fluorescence scanning range.38,39,42−45 Moreover, C6 had a
fluorescence peak at λex/em = 420/470 nm, which was
confirmed as a specific enzyme of F420 in the digester.46
The PARAFAC components were significantly different in
DOM and intercell. In particular, C1 (tyrosine-like) was high
in the intercell due to the high content of endoenzyme. The
SMP-like (C2) in the batch test under low temperature was
higher than that in the batch test under mesophilic condition
(Figure S4). However, under thermophilic conditions, the
highest content of C2 was observed, even 4 times higher than
that at low temperature, while tryptophan-like (C3) and
microbial protein-like (C4) have no significant variation
among of the tests. Interestingly, in thermophilic conditions,
no C4 was detected in test 7 and test 8. It should be pointed
out that some non-protein-like fluorophores, including
polyphenolic compounds in humiclike substances (e.g., lignin,
gallic acid), exhibited the same peak with the critical molecular
structure like phenol or aniline.47 C4 increased following the
biomethane production and decreased since the increase of
biomethane production rate. Moreover, the microbial protein-
like (C4) is an effective indicator of pollution by artificial
human activities and biological metabolites (Figure 4e,f).
Pearson’s correlation analysis between the PARAFAC
component and the parameters is illustrated in the heatmap
(Figure 5). For the TS experiment, the biomethane production
rate Kmax was significantly correlated with TS feeding (Figure
5a), while the DOM component of C4 was correlated with
NADH, protein, and tryptophan at the p level of 0.01. C3 and
C6 were significantly correlated with the free VFA at the p <
0.05 level. Moreover, C6 also has a significant level of TS at the
0.01 level, followed by propionic and butyric acid.
In contrast, in the batch experiment, the extracellular and
intracellular were cultured into two groups with C3, C2, C2
cell, C3 cell having a negative relation to biogas and
biomethane (Figure 5b). Free VFA had a significant impact
on all of the components at the p level of 0.01. Figure S6 shows
that C2 and C3 have a distinctly negative correlation with C1,
C4, and C5, whereas C1, C4, and C5 have an obviously
positive correlation with each other. C6 only has a significant
negative correlation with Kmax. The above results indicate that
C2 and C3 have a common source with C1, C4, and C5, but
C6 and another component do not have the same source.
Similarly, the TS and VFA have a significant positive
correlation with each other, while the NADH, protein, and
F420 have no significant correlation with TS and individual
VFA. The above results suggest that C2 and C3 are more
suitable to assess biodegradability.
3.3. Optimization of the Mono-Cardboard Methane
Generation. As described above, the present study inves-
tigated the best F/M, particle size, and feeding TS with static
and dynamic states for optimized operation conditions. Based
on the results (Figure 6), we calculated the thermotical energy
production of all of the experiment responses to the
parameters. Figure 6a shows the net methane generation at
different particle sizes within 64 h digestion. In the static
running, the biogas production was around 150 mL/gVS of the
particle size from 1 to 3 mm but decreased at 1 cm. In contrast,
in the dynamic state, a higher biomethane yield of 200 mL/
gVS was obtained at a particle size of 2 mm to 1 cm. In
contrast, the particle size of 1−2 mm obtained a biomethane
from 100 to 150 mL/gVS in the dynamic state. The low
biomethane generation at small size agrees with previous
studies.48,49 Smaller particle size increases the surface area
available to the microorganisms, accompanied by increasing
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Table 5. Comparison of Biomethane Conversion of Cardboard in the Literature
substrate
cardboard
co-ratio digester F/M
batch
temperature
particle
TS
YCH
refs
4
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
thermophilic
thermophilic
mesophilic
mesophilic
thermophilic
thermophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
thermophilic
thermophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
mesophilic
semi-solid
27.50%
27.50%
35%
66 mL/gTVS
(Pena Contreras et al., 2018)
1.86
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
0.25
0.25
0.25
1
0.02
0.02
0.02
0.02
0.5
409 11 mLCH4/gVS
393 9 mLCH4/gVS
401 16 mLCH4/gVS
0 mLCH4/gVS
221 mL/gVS
272 mL/gVS
188 mL/gVS
171 mL/gVS
372 mLCH4/gVS
food waste: cardboard
1
1
4
(Capson-Tojo et al., 2018)
27.50%
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
liquid
10%
0
<2 mm
20−100
<2 mm
20−100
corrugated cardboard
dirty paper
(Krause et al., 2017)
(Naroznova et al., 2016)
(Prokudina et al., 2016)
0.6
271 mLCH4/gVS
office paper
paper mixture
318.3 mL/g substrate
96.6 mL/g substrate
277 25 mLCH4/gVS
287 14 mLCH4/gVS
192 17 mLCH4/gVS
231 28 mLCH4/gVS
214 13 mLCH4/gVS
208 9 mLCH4/gVS
75 6 mLCH4/gVS
96 11 mLCH4/gVS
281.8 mLCH4/g substrate
treated filter paper
treated office paper
treated newspaper
treated cardboard
untreated filter paper
untreated office paper
untreated newspaper
untreated cardboard
office paper
cardboard
office paper
cardboard
cardboard
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
batch
(Yuan et al., 2012)
252.43 mLCH4/g substrate (Tsavkelova et al., 2012)
245.5 mLCH4/g substrate
240.88 mLCH4/g substrate
batch
batch
272.8 7.9 mL/gVS fed
208 16 mLCH4/gVS
132 mLCH4/gDM
143 mLCH4/gDM
155 mLCH4/gDM
146 25 m3/t waste
34 6.1 m3/t waste
243 18 m3/t waste
310 25 mL/gVS
100 25 mL/gVS
50 25 mL/gVS
(Guo et al., 2011)
(Sell et al., 2011)
cardboard waste
100 mm
20 mm
<1 mm
paper and cardboard
(Pommier et al., 2010)
(Jokela et al., 2005)
this study
cardboard
newsprint
office paper
cardboard 1
cardboard 2
cardboard 3
1.5
1.5
1.5
0.5
1
0.5
10
batch
mesophilic
2
10%
hydrolysis with the production of soluble organic materials like
VFAs, resulting in excessive acidification and causing
inhibition.48 Accordingly, the particle size from 2 mm to 1
cm in the form of dynamic condition exhibited relatively high
degradation and biomethane production, since the cardboard
easily absorbs water and degrades with utilizable DOM
generated.
Figure 6b shows the literature comparison of the
methanogen effects of cardboard under different F/M ratios.
The maximum methane production (392 mL/gVS) obtained
at an F/M ratio of 0.5 in our study was higher than most
literature reported values,50 while the value was also slightly
lower than the result reported in co-digestion of food waste.51
The mono-cardboard waste digestion could be inoculated with
the F/M ratio of 0.5−1 for the engineering application (Table
5), while Figure 6c shows the response of methane production
to the TS feeding. Our results strongly supported lower than
10% TS addition obtained high methane production, since low
TS and high water content made the hydrolysis easier (Figure
6c). A corrective linear biological uptake rate for the water
content between 0 and 80% was investigated on a larger range
(no activity at 80% TS, full activity at 0% TS). Similar results
of a constant linear decrease of the biologically specific
methanogenic activity between 18 and 35% TS in cellulose
digestion was also reported by Le Hyaric.52 Meanwhile, the
same trend was found in the batch test of cardboard digestion
inoculum at a very high F/M of 2053 as well as corn stover as
substrate (also in batch tests) at an F/M ratio of 2.50
The biomethane achieved a relatively high methane
generation with TS lower than 5%, while a significant decrease
of methane generation was found when TS increased from 5 to
30%, similarly to the previous report.51 Benbelkacem et al.54
also found a consistent decline in methane production, when
TS increased from 5 to 20% during co-digestion with food
waste. The results of EEM responded to relative activity, which
was inferred from biomethane production and thus confirmed
the optimized biomethane production of mono-cardboard
digestion. The energy production based on the thermotical
calculation is shown in Figure 6d,e. For the TS feeding test, a
5% TS was obtained with the highest energy production of 8.8
kJ/gVS (Figure 6d), while the F/M test suggested that
following the F/M increase, the net energy decreased. If the F/
M was 0.5, the highest energy production of 70 kJ/gVS was
achieved (Figure 6e).
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468.
4. CONCLUSIONS
Mono-cardboard digestion was a feasible and promising
treatment with methane generation. An appropriate F/M of
0.5 resulted in the highest methane generation and methane
production rate with optimized particle size between 0.5 and 3
mm in both static and dynamic states. Both the kinetic model
and first model simulated the dynamics of biogas and
biomethane production well. The surface response analysis
indicated that the T and TS have a significant effect on
methane production. Moreover, the EEM-PARAFAC of F420-
like C6 had a strong correlation with biomethane production.
Statistical modeling revealed no significant difference below
the TS of 10% with a maximum net energy production of 8.5
kJ/gVS.
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ASSOCIATED CONTENT
* Supporting Information
The Supporting Information is available free of charge on the
ACS Publications website at DOI: 10.1021/acs.energy-
fuels.9b00423.
■
S
Experimental design; simulation of biogas yield at
different F/M ratios by six kinetic models (Figure S1);
biomethane production rate of F/M (a), particle size
(b), response surface analysis experiment (c), and TS(d)
(Figure S2), the biogas production simulation at
different particle size both in static and dynamic states
(Figure S3), the gas production, extra and inner cell
EEM of response surface analysis at 15 °C(a), 35 °C(b),
55 °C(c) (Figure S4), response surface plots for the
orthogonal experiment (Relationship between impact
factors) (Figure S5) and the Pearson’s correlation
analysis of TS experiment (Figure S6). (PDF)
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AUTHOR INFORMATION
Corresponding Author
*E-mail: niuqg@sdu.edu.cn.
ORCID
Yu-You Li: 0000-0003-4067-8855
Rutao Liu: 0000-0002-7451-0682
Qigui Niu: 0000-0002-0997-8967
■
Author Contributions
∥D.L. and L.S. contributed equally to this work.
Notes
The authors declare no competing financial interest.
ACKNOWLEDGMENTS
■
This study was supported by the National Natural Science
Foundation of China (Grant nos. 51608304 and U1806216)
and the Young Scholars Program of Shandong University
(2018WLJH53). Research Fund of Tianjin Key Laboratory of
Aquatic Science and Technology (TJKLAST-ZD-2017-04)
and Research Fund of Jiangsu Key Laboratory of Anaerobic
Biotechnology (JKLAB201702) also partly supported this
work. “The Fundamental Research Funds of Shandong
University” and China Postdoctoral Science Foundation
(2017M622209) are also acknowledged.
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estimate maximum methane production in a batch-fed anaerobic
reactor. J. Chem. Technol. Biotechnol. 2004, 79, 1174−1178.
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