Citation: Jiying Huang, Yujian Yan, Yuyi Ou, Yanyan Jia, Lianpeng Sun, Qing Zhao, Hui Lu. Unraveling pharmaceuticals removal in a sulfur-driven autotrophic denitrification process: Performance, kinetics and mechanisms[J]. Chinese Chemical Letters, ;2023, 34(2): 107433. doi: 10.1016/j.cclet.2022.04.031 shu

Unraveling pharmaceuticals removal in a sulfur-driven autotrophic denitrification process: Performance, kinetics and mechanisms

Figures(5)

  • The removal of eight typical pharmaceuticals (PhACs) (i.e., ibuprofen (IBU), ketoprofen (KET), diclofenac (DIC), sulfadiazine (SD), sulfamethoxazole (SMX), trimethoprim (TMP), ciprofloxacin (CIP) and enoxacin (ENO)) in sulfur-driven autotrophic denitrification (SdAD) process were firstly investigated via long-term operation of bioreactor coupled with batch tests. The results indicated that IBU and KET can be effectively removed (removal efficiency > 50%) compared to other six PhACs in SdAD bioreactor. Biodegradation was the primary removal route for IBU and KET with the specific biodegradation rates of 5.3±0.7~18.1±1.8 µg g−1-VSS d−1 at initial concentrations of 25-200 µg/L. The biotransformation intermediates of IBU and KET were examined, and the results indicated that IBU was biotransformed to three intermediates via hydroxylation and carboxylation. KET biotransformation could be initiated from the reduction of the keto group following with a series of oxidation/reduction reactions, and five intermediates of KET were observed in this study. The microbial community composition in the system was markedly shifted when long-term exposure to PhACs. However, the functional microbes (e.g., genus Thiobacillus) showed high tolerance to PhACs, resulting in the high efficiency for PhACs, N and S removal during long-term SdAD reactor operation. The findings provide better insight into PhACs removal in SdAD process, especially IBU and KET, and open up an innovative opportunity for the treatment of PhACs-laden wastewater using sulfur-mediated biological process.
  • CO2 is the ultimate product in the process of utilizing fossil fuels and may cause serious environmental issues like greenhouse effect. It is urgently needed to convert CO2 into valuable chemicals [1-3]. The electrochemical method is one of the most promising ways [4,5]. The high limiting potential and low selectivity of catalysts are two issues for CO2 reduction reaction (CRR), and both of them depend strongly on catalysts [6-8]. Although many CRR products possess relatively low equilibrium potentials close to 0 V vs. RHE (reversible hydrogen electrode), an acceptable current density of the CRR can only be obtained at around -1.0 V, indicating a large limiting potential caused by the energy loss. Besides, the CRR yields a mixture of different products including CO, hydrocarbons, and HCOOH [9]. Therefore, obtaining high activity for a target reaction product remains a fundamental challenge. Among numerous products of CRR, hydrocarbons, such as CH4, CH3OH and C2H4, are all valuable chemicals. Cu is found as a unique catalyst that can convert CO2 into hydrocarbons efficiently in pure transition metals (TMs). However, the large limiting potential of −0.8 V on Cu still hinders its practical application. Thus, it is urgently needed to discover catalysts with high reactivity for CRR to produce hydrocarbons.

    In pioneering studies, many works have focused on the single atom catalysts (SAC). As revealed in d-band theory of Norskov, the binding energies of CRR intermediates are strongly correlated with each other on TMs via the so-called "scaling relation", which may put a significant limit on the improvement of catalysts [10-12]. SAC is a promising way for breaking the scaling relation and improved reactivity compared to TMs has also been achieved [13,14]. Norskov et al. has embedded Pt atom into defective graphene and ultralow limiting potential of -0.27 V is obtained for CRR to CH3OH [15]. In contrast, Jung et al. found that Ir is the favorable dopant for TiC based SAC [16]. The difference of the favorable doped TM atom between Norskov and Jung works can be attributed to the carrier effect. Our previous work has also demonstrated that the two-dimensional (2D) InSe substrate can regulate the metal atoms flexibly to achieve the desired CRR selectivity [17,18]. Besides, the optimal candidates can be screened quickly with the reference of conventional theory on TMs, which is different from the situations in graphene and TiC substrates [15,16,19]. Our results have sufficiently utilized the carrier effect of 2D InSe substrate. To realize quick screen of promising catalysts in a large pool of candidates, we should also make full use of d-band center and descriptors in pioneering studies. Norskov et al. have demonstrated that trends in reactivities can be understood in terms of the hybridization energy between the bonding and anti-bonding adsorbate states and the metal d-bands [20]. Moreover, the adsorbate-metal interaction is determined by the filling of the antibonding states on adsorption [21].

    Although SAC has been widely investigated in CRR area, the large amounts of candidates still hamper the development of promising catalysts. In pioneering works, Guo et al. have also demonstrated that the charge transfer between substrate and metal atoms in SAC plays an important role in promoting the CRR reaction [22]. Curvature effect is one of the most promising ways to regulate the valence of the single metal site, which can reduce the amount of candidates investigated effectively. Sun et al. have reported a curvature-dependent selectivity of CRR on Co porphyrin nanotubes (CPN) [23]. The results show that CO is preferred to be produced at low curvature and CH4 is favored as the curvature increased. Cao et al. have compared the curvature effect of Cu and Fe doped carbon nanotubes (Cu@CNT and Fe@CNT) comprehensively [24]. They found that the generation of CO, HCOOH, and CH3OH is reduced on high-curvature Cu@CNT, which is less notable on Fe@CNT. However, the effect of curvature on the coupling between electric properties, adsorption strength, and reactivity is rather limited in pioneering works, which hinders the development of advanced materials. Referenced to studies of Lei et al., this proposed strategy may benefit from many advatages, including low coordination, lateral heteroatom coordination, and axial heteroatom coordination [25,26].

    In our previous work, we have successfully predicted a BC3N2 monolayer substrate. This structure is like graphene with B, C and N atoms bonded together upon sp2 hybridization [27]. Compared with graphene, boron nitride and other graphene materials, each hexagonal primitive unit cell of the BC3N2 has one more electron than them. Such a multi-electron system may be beneficial to catalysis due to its advantages in electron transfer rate and effective mass.

    Inspired by pioneering and our previous studies, we have herein carried out systematic studies on curvature effect on 2D BC3N2 based SAC. About the single atom site, we select V as the dopant in 2D BC3N2 due to the unsaturated d orbital (denoted as V@2D-BC3N2). This character may contribute to tune the activity and selectivity of CRR via curvature. In this work, we have performed density functional theory (DFT) calculations to study CRR on curved V@2D-BC3N2 catalyst. Increased curvature can effectively enhance adsorption ability with different mechanism for low- and high- curvature systems. The curvature effect can also regulate the V@2D-BC3N2 deviated away from the scaling line between Ead[CO]~Ead[COOH] based on transition metals. 3-3 System (the V@2D-BC3N2 systems with 3-3 chirality for 2D BC3N2 nanotube) is screened as the optimal candidate for CRR to hydrocarbons, which originates from the enhanced binding ability of CRR intermediates. This character can increase the reactivity of hydrocarbons production and simultaneously hinder the production of H2 and HCOOH.

    All calculations were performed using CASTEP module with the Perdew Burke Erzerhof (PBE) functional [28]. The vacuum thickness was set to be 15 Å to avoid the imaginary interaction between periodic images. The kinetic energy cutoff for plane wave expansions was set to 400 eV and the k points was sampled by Monkhorst-Pack scheme with a grid of 1 × 2 × 1 for all of the 1D nanotubes. The electronic relaxation was performed to within an energy tolerance of 10−8 eV for self-consistency, while ionic optimizations were performed until all the residual forces were smaller than 0.005 eV/Å. Electron smearing was employed using the Gaussian-smearing technique with a width of kBT = 0.1 eV. Spin-polarized wave functions were used for all calculations. We also include van der Waals (vdW) correction with the MBD method [29,30].

    The binding strength of V atom in 2D BC3N2 are defined as follows:

    (1)

    where E[V@2D-BC3N2], E[2D-BC3N2] and E[V] denote the electronic energies of V doped 2D BC3N2 complex, 2D BC3N2 with a vacancy defect, and single V atom. For the coupled proton-electron transfer process, we use the computational hydrogen electrode (CHE) theory [31]. In the CHE scheme, the effect of applied electrode potentials on reaction thermodynamics was based on the free energy change (ΔGmax). The relation between the limiting potential (UL) of the reaction and ΔGmax was obtained as ULGmax/e. Zero point energy and entropy corrections are included for the free energy of adsorbate systems to ensure a fair and unbiased comparison with experiments at 298.15 K.

    The change in Gibbs free energy (ΔG) for all electrocatalytic steps was defined as

    (2)

    where the reaction energy (ΔE) can be directly determined by analyzing the DFT total energies. ΔEzpe and ΔS are the zero-point energy difference and the entropy difference between the products and the reactants, respectively, and T is the system temperature (T = 298.15 K in this work). For each reactant or product, its Ezpe value can be calculated by Ezpe = (1/2)Σ. The entropies of the free molecules were taken from the NIST database, while the energy contribution from the configurational entropy in the adsorbed state is neglected. The solvation effect can be crucial to the CRR, although neither of them is included in the CHE model. However, a model with implicit solvent-electrolyte methods may increase the computational cost by several-fold relative to bias-free modeling [32]. Herein, we mainly focus on screening the optimal catalysts from a large pool of materials and thus take the CHE model as a high-efficiency method.

    Partial configurations of the catalysts in the article (Fig. 1) are modelled by the Device Studio program provided by HZWTECH [33].

    Figure 1

    Figure 1.  The top and side view of the (a) pristine and (b) curved V@2D-BC3N2.

    The above methods have been widely used in pioneering studies especially in catalytic areas [34-48].

    The fully relaxed configuration of V@2D-BC3N2 is shown in Fig. 1. Two types of nanotubes were constructed denoted as armchair and zigzag types. Each type nanotubes are also constructed with different curvatures. The 2D BC3N2 exhibits a hexagonal network structure with one unit cell containing 1B, 2N and 3C atoms. The single V site are located outwards of 2D BC3N2 substrate due to the large size of V atom. The curved V@2D-BC3N2 appears to show an ellipse shape, which is likely caused by the surface tension. The configurations in Fig. 1a are periodic in the planar directions while it is nanotube structures in Fig. 1b. Thus, we have saturated the edge sites with H atoms.

    We first discuss the adsorption sites for V atoms in 2D BC3N2. The V atom can replace the B, C and N sites in 2D BC3N2. The binding strength of V atom in the N site is generally enhanced compared to other situations (Fig. S1 in Supporting information). We thus select the systems of V doped in N defects as the candidates for this study. The values of binding energies range from −8.8 eV to −9.6 eV referenced to isolated metal atoms in a vacuum. The large values illustrate the thermodynamic stability of our designed catalyst. Referenced to the cohensive energies of V 4-atom (−1.94 eV) and 6-atom (−2.57 eV) cluster [49,50], the binding energies of V in BC3N2 nanotubes are significantly larger than the cohensive energies of V clusters. This may indicate that the subsize clusters of V are unlikely to nuclear in our systems. In addition to binding energy, the adsorption energies of *CO and *COOH have exhibited two tendencies for V in N sites: Some candidates comply with the conventional scaling line based on transition metals and others deviate away from the scaling line significantly. In contrast, the adsorption energies of *CO and *COOH for V in B and C sites have totally break the traditional scaling line (Fig. S2 in Supporting information), leading to a difficulty in screening promising catalysts.

    In order to clarify the curvature and chirality effect of V@2D-BC3N2 nanotubes. We therefore performed density of states (DOS) analysis to investigate the orbital distribution in the bands near Fermi level, which can interact with adsorbates of CRR actively (Fig. 2). As depicted in d-band central theory, the coupling between adsorbate and metal sp state is dominant and constant across different metals. In contrast, the coupling between the adsorbate and metal d state determines the variation of adsorption energy from one metal to the next. In addition, the reactivity of TMs primarily originates from their unsaturated d orbitals. Thus, the comparison of states distribution of V@2D-BC3N2 at different curvature is necessary to reveal the electronic properties.

    Figure 2

    Figure 2.  (a-d) The density of states (DOS) of the d-band for V@2D-BC3B2 with different curvature and chiralities.

    We first discuss the curvature effect in armchair systems. The adsorption energy of CO increases as the curvature increase from 0.12 Å−1 (13-13) to 0.50 Å−1 (3-3) (Fig. 3 and Table S1 in Supporting information). As shown in Figs. 2a and b, the 10-10 V@2D-BC3N2 exhibits increased tendency in the unoccupied states of V d-band above Fermi level compared to 13-13 V@2D-BC3N2 and the situation for occupied states is opposite, suggesting that the V atom is positively charged caused by increased curvature. This character indicates that V site can act as an electron-acceptor role and eventually lead to an enhanced adsorption strength for CO. In addition, the 8-8 system demonstrates a wider distribution of states above Fermi level compared to 10-10. Thus, the ability of gaining electrons is enhanced from 13-13 to 8-8, leading to the increased adsorption ability of V@2D-BC3N2. The significant increase of occupied V d-band from 8-8 to 3-3 is beneficial to transfer electrons from V site to adsorbate and eventually contribute to CO adsorption. A change of mechanism has experienced between large and small curvature systems and 8-8 can be treated as the turning point. Thus, the correlation between curvature and adsorption energies can be plotted as two broken lines relation, classified with different adsorption mechanism (Fig. 3). The chirality can also regulate the distribution of V d-states of V@2D-BC3N2 with similar curvature (Figs. 2c and d). These characters of the rolled V@2D-BC3N2 can be treated as the origin of the flexible regulation for reactivity via curvature.

    Figure 3

    Figure 3.  Correlations between adsorption energies of CO and curvatures.

    The regulation of curvature can eventually realize the changed adsorption property of CRR intermediates (Fig. S2 and Fig. 4a). The pioneering studies have revealed that binding energies of CRR intermediates correlate with each other via scaling relationship due to d-band theory on TMs [11]. However, this relationship will be disturbed on SAC systems. In addition, our previous work has also demonstrated that the traditional theory of CRR on TMs is still established on SACs that obey the scaling line of TM systems [17]. Referenced to these results, we compare the adsorption energies (Ead) of *CO and *COOH on V@2D-BC3N2. Among numerous doping sites of V, N-site systems are particularly interesting. Some systems, such as 4-4, 5-5 and 12-0, comply with the scaling line of TMs and most candidates deviate significantly away from the line. In contrast, the C/N-site systems all possess remarkably high adsorption strength for *CO and *COOH, which may lead to the poisoning effect of active sites. Thus, the N-site systems are the most favorable candidates as CRR catalyst.

    Figure 4

    Figure 4.  (a) The correlation between adsorption energies of *CO and *COOH on V@2D-BC3N2 (red triangles) and transition metal (111) surfaces (black asterisks). The doping sites of V locate at N vacancies; (b) The hydrogen evolution reaction on different V@2D-BC3N2 nanotubes.

    It is known that the hydrocarbons production for CRR depends significantly on the binding of *CO and *COOH. We thus analyze the reaction pathway and reactivity based on the adsorption properties in the following part.

    The CRR to hydrocarbons on V@2D-BC3N2 begins by protonation of CO2 to carboxyl (*COOH) on the catalysts and *COOH can be further protonated to form *CHO or *COH (Fig. S3 in Supporting information). The formation of *COH is energetically less favorable than *CHO in all cases (Fig. S3 and Table S2 in Supporting information). Additional protonation of *CHO can form either *CH2OH or *CH3O. Based on the comparison of free energy change, the minimum energy pathway is generally demonstrated as follows: *CO2*COOH → *CO → *CHO → *CH2O → *OCH3*O + CH4. The protonation of *OCH3 favors the formation of CH4 compared to CH3OH, indicating a strong binding ability of *O on V@2D-BC3N2. The rate controlling step (RCS) of CRR to hydrocarbon are all *CO → *CHO step, except for 3-3 system (*COOH → *CO). The change of mechanism in 3-3 system is an interesting phenomenon that should be emphasized (Fig. S4 in Supporting information). This can be interpreted from the general tendency between adsorption energy of *COOH (Ead[*COOH]) and limiting potentials (UL). For the systems that comply with the scaling line, the limiting potentials are UL = -0.63 V, -0.5 V, and -0.55 V on 4-4, 5-5, and 12-0 systems, respectively. The values are all favorable than that on Cu (-0.8 V). This may indicate that the change of adsorption energies of *CO/*COOH, complying with the scaling line of TM, can realize the improvement of reactivity. For the systems that disturb the scaling line, the systems exhibit a gradual increased deviation distance from the scaling line in the order of 5-5, 7-0, 11-11, 14-0, 3-3 with the reaction energy (Gr) of *CO → *COOH as Gr = 0.5 eV, Gr = 0.44 eV, Gr = 0.33 eV, Gr = 0.29 eV, and Gr = -0.14 eV, respectively. The deviation away from the scaling line of TMs illustrates an enhanced binding strength of *COOH relative to *CO, which may lead to a decreased Gr of RCS (*CO → *COOH). Especially for 3-3 system, the *CO → *CHO step has become exothermic unlike other systems, which is due to the significant enhancement of *COOH binding with respect to *CO. Besides, the RCS has changed from *CO → *CHO to *COOH → *CO with an ultralow reaction energy of 0.16 eV, corresponding to a changed mechanism and improved reactivity. This suggests that the curvature effect can indeed change the adsorption properties of CRR intermediates and eventually bring about remarkable reactivity.

    About the different regulation level of curvature for *CO and *COOH, it can be interpreted from the adsorption configurations. The *COOH interacts with V@2D-BC3N2 bidentate with both C and O atoms while it is monodentate with only C for *CO. This can be treated as the originate for the stabilization of *COOH with respect to *CO.

    In addition to hydrocarbons, the production of HCOOH and H2 are also essential pathways that we cannot ignore. The reaction energies are shown in Fig. 4b and Figs. S5-S7 (Supporting information).

    For HCOOH production, the initial protonation of CO2 can form *HCOO, which can further react to form *HCOOH. The RCSs of HCOOH production are all *HCOO → *HCOOH on V@2D-BC3N2. We have also calculated the corresponding reaction pathway for the protonation of *HCOOH to *CHO. The RCS for this process is significantly hindered by the *HCOO → *HCOOH process with ultrahigh reaction energies of 0.87~1.15 eV (Figs. S5-S7). Thus, *CHO can only be produced via *COOH intermediate. The limiting potential of HCOOH production on 3-3 system is -1.92 eV, indicating that HCOOH can be effectively hindered via curvature regulation. Compared with other systems like 12-0 system, the adsorption energy of *HCOO (*HCOOH) is enhanced from -0.99 (-0.89) eV to -1.43 (-1.08) eV. The value has increased 0.44 eV for *HCOO and it is only 0.19 for *HCOOH, indicating that *HCOO is considerably stabilized with respect to *HCOOH at high curvature state. This can be treated as the origin of high selectivity for hydrocarbons compared to HCOOH on 3-3 system.

    Similar conclusion can also be found for H2 production. The hydrogen adsorption free energy (ΔGH) is always treated as the measurement of reactivity. As the systems deviate away from the scaling line of TMs in the order of 12-0, 7-0, 11-11, 14-0, 3-3, the ΔGH exhibits a negative shift tendency (0.18, 0.02, -0.08, -0.15 and -0.25 eV for 12-0, 11-11, 14-0 and 3-3, respectively) and eventually leads to a high limiting potential of -0.25 V on 3-3. Thus, CRR is more preferred on 3-3 than HER and the opposite regulation tendency between curvature and reactivity is particularly interesting.

    Above all, the high-curvature states may lead to enhanced binding ability for CRR/HER intermediates. This is beneficial for hydrocarbons production and unfavorable for H2 and HCOOH production.

    In this work, we have performed density functional theory calculations to study CRR to hydrocarbons on curved V@2D-BC3N2 catalyst. Curvature can effectively enhance adsorption ability with different mechanism. For low (high) curvature systems, the unoccupied (occupied) d-states are increased with increasing curvature and V acts as the electron acceptor (donor). 8-8 system is the tuning point with wider distributed d-states. The curvature effect can also regulate the V@2D-BC3N2 systems with different deviation distance from the scaling line between Ead[CO]~Ead[COOH] based on transition metals. The high curvature state (3-3 system) can induce high binding ability for CRR intermediates, which can induce increased (decreased) reactivity for hydrocarbons (HCOOH and H2) production. Thus, 3-3 system is screened as the optimal candidate for CRR to hydrocarbons with different rate controlling step of *COOH → *CO compared to other systems (*CO → *CHO), which is due to the stabilization of *COOH with respect to *CO.

    The authors declare that they have no known competing finacial interests or personal relationships that could have appeared to influence the work reported in this paper.

    This work was supported by the National Natural Science Foundation of China (No. 21603109), the Henan Joint Fund of the National Natural Science Foundation of China (No. U1404216), the Special Fund of Tianshui Normal University, China (No. CXJ2020-08) and the Scientific Research Program Funded by Shaanxi Provincial Education Department (No. 20JK0676). This work was also supported by Natural Science Basic Research Program of Shanxi (Nos. 2022JQ-108, 2022JQ-096). In addition, this work was also partially supported by the Postgraduate Research Opportunities Program of HZWTECH (No. HZWTECH-PROP).

    Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.cclet.2022.107897.


    1. [1]

      A. Sengar, A. Vijayanandan, Sci. Total Environ. 807 (2022) 150677.  doi: 10.1016/j.scitotenv.2021.150677

    2. [2]

      M. Huerta-Fontela, M.T. Galceran, F. Ventura, Water Res. 45 (2011) 1432-1442.  doi: 10.1016/j.watres.2010.10.036

    3. [3]

      R. Loos, G. Locoro, S. Comero, et al., Water Res. 44 (2010) 4115-4126.  doi: 10.1016/j.watres.2010.05.032

    4. [4]

      A.S. Adeleye, J. Xue, Y. Zhao, et al., J. Hazard. Mater. 424 (2022) 127284.  doi: 10.1016/j.jhazmat.2021.127284

    5. [5]

      M. Ashfaq, K. Nawaz Khan, M. Saif Ur Rehman, et al., Ecotox. Environ. Safe. 136 (2017) 31-39.  doi: 10.1016/j.ecoenv.2016.10.029

    6. [6]

      A.Y. Lin, T. Yu, C. Lin, Chemosphere 74 (2008) 131-141.  doi: 10.1016/j.chemosphere.2008.08.027

    7. [7]

      S.A. Ortiz De García, G. Pinto Pinto, P.A. García-Encina, et al., Ecotoxicology 23 (2014) 1517-1533.  doi: 10.1007/s10646-014-1293-8

    8. [8]

      B. Ren, X. Shi, X. Jin, et al., Chem. Eng. J. 404 (2021) 127024.  doi: 10.1016/j.cej.2020.127024

    9. [9]

      G. Wang, D. Wang, Y. Xu, et al., Sci. Total Environ. 739 (2020) 140166.  doi: 10.1016/j.scitotenv.2020.140166

    10. [10]

      J. Wang, H. Lu, G. Chen, et al., Water Res. 43 (2009) 2363-2372.  doi: 10.1016/j.watres.2009.02.037

    11. [11]

      H. Lu, D. Wu, D.T.W. Tang, et al., Water Sci. Technol. 63 (2011) 2149-2154.  doi: 10.2166/wst.2011.342

    12. [12]

      J. Qian, R. Liu, L. Wei, et al., Water Res. 80 (2015) 189-199.  doi: 10.1016/j.watres.2015.05.005

    13. [13]

      D. Wu, G.A. Ekama, H. Wang, et al., Water Res. 49 (2014) 251-264.  doi: 10.1016/j.watres.2013.11.029

    14. [14]

      Y. Jia, S.K. Khanal, H. Zhang, et al., Water Res. 119 (2017) 12-20.  doi: 10.1016/j.watres.2017.04.040

    15. [15]

      Y. Jia, S.K. Khanal, H. Shu, et al., Water Res. 136 (2018) 64-74.  doi: 10.1016/j.watres.2018.02.057

    16. [16]

      T. Alvarino, S. Suarez, J.M. Lema, et al., J. Hazard. Mater. 278 (2014) 506-513.  doi: 10.1016/j.jhazmat.2014.06.031

    17. [17]

      S. Suarez, J.M. Lema, F. Omil, Water Res. 44 (2010) 3214-3224.  doi: 10.1016/j.watres.2010.02.040

    18. [18]

      N.H. Tran, T. Urase, O. Kusakabe, J. Hazard. Mater. 171 (2009) 1051-1057.  doi: 10.1016/j.jhazmat.2009.06.114

    19. [19]

      T.A. Ternes, N. Herrmann, M. Bonerz, et al., Water Res. 38 (2004) 4075-4084.  doi: 10.1016/j.watres.2004.07.015

    20. [20]

      Y. Jia, L. Yin, S.K. Khanal, et al., Water Res. 170 (2020) 115303.  doi: 10.1016/j.watres.2019.115303

    21. [21]

      T. Alvarino, S. Suarez, J. Lema, et al., Sci. Total Environ. 615 (2018) 297-306.  doi: 10.1016/j.scitotenv.2017.09.278

    22. [22]

      T. Alvarino, P. Nastold, S. Suarez, et al., Sci. Total Environ. 542 (2016) 706-715.  doi: 10.1016/j.scitotenv.2015.10.140

    23. [23]

      E. Ferrer-Polonio, J. Fernández-Navarro, M. Iborra-Clar, et al., J. Environ. Manage. 263 (2020) 110368.  doi: 10.1016/j.jenvman.2020.110368

    24. [24]

      I. Martínez-Alcalá, J.M. Guillén-Navarro, C. Fernández-López, Chem. Eng. J. 316 (2017) 332-340.  doi: 10.1016/j.cej.2017.01.048

    25. [25]

      Y. Tang, X.M. Li, Z.C. Xu, et al., Biotechnol. Appl. Biochem. 61 (2014) 333-341.

    26. [26]

      B. Almeida, A. Oehmen, R. Marques, et al., Bioresource Technol. 133 (2013) 31-37.  doi: 10.1016/j.biortech.2013.01.035

    27. [27]

      C. Boix, M. Ibáñez, J.V. Sancho, et al., J. Hazard. Mater. 302 (2016) 175-187.  doi: 10.1016/j.jhazmat.2015.09.053

    28. [28]

      L. Ferrando-Climent, N. Collado, G. Buttiglieri, et al., Sci. Total Environ. 438 (2012) 404-413.  doi: 10.1016/j.scitotenv.2012.08.073

    29. [29]

      M.M. Ismail, T.M. Essam, Y.M. Ragab, et al., Biotechnol. Lett. 38 (2016) 1493-1502.  doi: 10.1007/s10529-016-2145-9

    30. [30]

      J. Quintana, S. Weiss, T. Reemtsma, Water Res. 39 (2005) 2654-2664.  doi: 10.1016/j.watres.2005.04.068

    31. [31]

      Q. Yan, J. Min, Y. Yu, et al., Chemosphere 186 (2017) 823-831.  doi: 10.1016/j.chemosphere.2017.08.064

    32. [32]

      D. Pokorna, J. Zabranska, Biotechnol. Adv. 33 (2015) 1246-1259.  doi: 10.1016/j.biotechadv.2015.02.007

    33. [33]

      N. Jakus, N. Blackwell, D. Straub, et al., FEMS Microbiol. Ecol. 97 (2021) fiab145.  doi: 10.1093/femsec/fiab145

    34. [34]

      C. Juncher Jørgensen, O.S. Jacobsen, B. Elberling, et al., Environ. Sci. Technol. 43 (2009) 4851-4857.  doi: 10.1021/es803417s

    35. [35]

      P. Charoensuk, W. Thongnueakhaeng, P. Chaiprasert, Int. J. Environ. Sci. Te. 16 (2019) 5767-5782.  doi: 10.1007/s13762-018-2132-x

    36. [36]

      I. Mustakhimov, M.G. Kalyuzhnaya, M.E. Lidstrom, et al., J. Bacteriol. 195 (2013) 2207-2211.  doi: 10.1128/JB.00069-13

    37. [37]

      K. Takai, M. Suzuki, S. Nakagawa, et al., Int. J. Syst. Evol. Micr. 56 (2006) 1725-1733.  doi: 10.1099/ijs.0.64255-0

    38. [38]

      M. Zhu, M. Zhang, Y. Yuan, et al., J. Environ. Manage. 289 (2021) 112473.  doi: 10.1016/j.jenvman.2021.112473

    39. [39]

      Y. Feng, Z. Li, Y. Long, et al., Environ. Pollut. 292 (2022) 118357.  doi: 10.1016/j.envpol.2021.118357

    1. [1]

      A. Sengar, A. Vijayanandan, Sci. Total Environ. 807 (2022) 150677.  doi: 10.1016/j.scitotenv.2021.150677

    2. [2]

      M. Huerta-Fontela, M.T. Galceran, F. Ventura, Water Res. 45 (2011) 1432-1442.  doi: 10.1016/j.watres.2010.10.036

    3. [3]

      R. Loos, G. Locoro, S. Comero, et al., Water Res. 44 (2010) 4115-4126.  doi: 10.1016/j.watres.2010.05.032

    4. [4]

      A.S. Adeleye, J. Xue, Y. Zhao, et al., J. Hazard. Mater. 424 (2022) 127284.  doi: 10.1016/j.jhazmat.2021.127284

    5. [5]

      M. Ashfaq, K. Nawaz Khan, M. Saif Ur Rehman, et al., Ecotox. Environ. Safe. 136 (2017) 31-39.  doi: 10.1016/j.ecoenv.2016.10.029

    6. [6]

      A.Y. Lin, T. Yu, C. Lin, Chemosphere 74 (2008) 131-141.  doi: 10.1016/j.chemosphere.2008.08.027

    7. [7]

      S.A. Ortiz De García, G. Pinto Pinto, P.A. García-Encina, et al., Ecotoxicology 23 (2014) 1517-1533.  doi: 10.1007/s10646-014-1293-8

    8. [8]

      B. Ren, X. Shi, X. Jin, et al., Chem. Eng. J. 404 (2021) 127024.  doi: 10.1016/j.cej.2020.127024

    9. [9]

      G. Wang, D. Wang, Y. Xu, et al., Sci. Total Environ. 739 (2020) 140166.  doi: 10.1016/j.scitotenv.2020.140166

    10. [10]

      J. Wang, H. Lu, G. Chen, et al., Water Res. 43 (2009) 2363-2372.  doi: 10.1016/j.watres.2009.02.037

    11. [11]

      H. Lu, D. Wu, D.T.W. Tang, et al., Water Sci. Technol. 63 (2011) 2149-2154.  doi: 10.2166/wst.2011.342

    12. [12]

      J. Qian, R. Liu, L. Wei, et al., Water Res. 80 (2015) 189-199.  doi: 10.1016/j.watres.2015.05.005

    13. [13]

      D. Wu, G.A. Ekama, H. Wang, et al., Water Res. 49 (2014) 251-264.  doi: 10.1016/j.watres.2013.11.029

    14. [14]

      Y. Jia, S.K. Khanal, H. Zhang, et al., Water Res. 119 (2017) 12-20.  doi: 10.1016/j.watres.2017.04.040

    15. [15]

      Y. Jia, S.K. Khanal, H. Shu, et al., Water Res. 136 (2018) 64-74.  doi: 10.1016/j.watres.2018.02.057

    16. [16]

      T. Alvarino, S. Suarez, J.M. Lema, et al., J. Hazard. Mater. 278 (2014) 506-513.  doi: 10.1016/j.jhazmat.2014.06.031

    17. [17]

      S. Suarez, J.M. Lema, F. Omil, Water Res. 44 (2010) 3214-3224.  doi: 10.1016/j.watres.2010.02.040

    18. [18]

      N.H. Tran, T. Urase, O. Kusakabe, J. Hazard. Mater. 171 (2009) 1051-1057.  doi: 10.1016/j.jhazmat.2009.06.114

    19. [19]

      T.A. Ternes, N. Herrmann, M. Bonerz, et al., Water Res. 38 (2004) 4075-4084.  doi: 10.1016/j.watres.2004.07.015

    20. [20]

      Y. Jia, L. Yin, S.K. Khanal, et al., Water Res. 170 (2020) 115303.  doi: 10.1016/j.watres.2019.115303

    21. [21]

      T. Alvarino, S. Suarez, J. Lema, et al., Sci. Total Environ. 615 (2018) 297-306.  doi: 10.1016/j.scitotenv.2017.09.278

    22. [22]

      T. Alvarino, P. Nastold, S. Suarez, et al., Sci. Total Environ. 542 (2016) 706-715.  doi: 10.1016/j.scitotenv.2015.10.140

    23. [23]

      E. Ferrer-Polonio, J. Fernández-Navarro, M. Iborra-Clar, et al., J. Environ. Manage. 263 (2020) 110368.  doi: 10.1016/j.jenvman.2020.110368

    24. [24]

      I. Martínez-Alcalá, J.M. Guillén-Navarro, C. Fernández-López, Chem. Eng. J. 316 (2017) 332-340.  doi: 10.1016/j.cej.2017.01.048

    25. [25]

      Y. Tang, X.M. Li, Z.C. Xu, et al., Biotechnol. Appl. Biochem. 61 (2014) 333-341.

    26. [26]

      B. Almeida, A. Oehmen, R. Marques, et al., Bioresource Technol. 133 (2013) 31-37.  doi: 10.1016/j.biortech.2013.01.035

    27. [27]

      C. Boix, M. Ibáñez, J.V. Sancho, et al., J. Hazard. Mater. 302 (2016) 175-187.  doi: 10.1016/j.jhazmat.2015.09.053

    28. [28]

      L. Ferrando-Climent, N. Collado, G. Buttiglieri, et al., Sci. Total Environ. 438 (2012) 404-413.  doi: 10.1016/j.scitotenv.2012.08.073

    29. [29]

      M.M. Ismail, T.M. Essam, Y.M. Ragab, et al., Biotechnol. Lett. 38 (2016) 1493-1502.  doi: 10.1007/s10529-016-2145-9

    30. [30]

      J. Quintana, S. Weiss, T. Reemtsma, Water Res. 39 (2005) 2654-2664.  doi: 10.1016/j.watres.2005.04.068

    31. [31]

      Q. Yan, J. Min, Y. Yu, et al., Chemosphere 186 (2017) 823-831.  doi: 10.1016/j.chemosphere.2017.08.064

    32. [32]

      D. Pokorna, J. Zabranska, Biotechnol. Adv. 33 (2015) 1246-1259.  doi: 10.1016/j.biotechadv.2015.02.007

    33. [33]

      N. Jakus, N. Blackwell, D. Straub, et al., FEMS Microbiol. Ecol. 97 (2021) fiab145.  doi: 10.1093/femsec/fiab145

    34. [34]

      C. Juncher Jørgensen, O.S. Jacobsen, B. Elberling, et al., Environ. Sci. Technol. 43 (2009) 4851-4857.  doi: 10.1021/es803417s

    35. [35]

      P. Charoensuk, W. Thongnueakhaeng, P. Chaiprasert, Int. J. Environ. Sci. Te. 16 (2019) 5767-5782.  doi: 10.1007/s13762-018-2132-x

    36. [36]

      I. Mustakhimov, M.G. Kalyuzhnaya, M.E. Lidstrom, et al., J. Bacteriol. 195 (2013) 2207-2211.  doi: 10.1128/JB.00069-13

    37. [37]

      K. Takai, M. Suzuki, S. Nakagawa, et al., Int. J. Syst. Evol. Micr. 56 (2006) 1725-1733.  doi: 10.1099/ijs.0.64255-0

    38. [38]

      M. Zhu, M. Zhang, Y. Yuan, et al., J. Environ. Manage. 289 (2021) 112473.  doi: 10.1016/j.jenvman.2021.112473

    39. [39]

      Y. Feng, Z. Li, Y. Long, et al., Environ. Pollut. 292 (2022) 118357.  doi: 10.1016/j.envpol.2021.118357

  • 加载中
    1. [1]

      Yuxin ZengYan LuoYao HeKaihang ZhangBinbin ZhuYuanzheng ZhangJunfeng Niu . Photo-assisted electrocatalysis with bimetallic PdCu/TiOx catalysts: Enhancing denitrification and economic viability. Chinese Chemical Letters, 2025, 36(6): 110514-. doi: 10.1016/j.cclet.2024.110514

    2. [2]

      Ping Wang Tianbao Zhang Zhenxing Li . Reconstruction mechanism of Cu surface in CO2 reduction process. Chinese Journal of Structural Chemistry, 2024, 43(8): 100328-100328. doi: 10.1016/j.cjsc.2024.100328

    3. [3]

      Jun JiangTong GuoWuxin BaiMingliang LiuShujun LiuZhijie QiJingwen SunShugang PanAleksandr L. VasilievZhiyuan MaXin WangJunwu ZhuYongsheng Fu . Modularized sulfur storage achieved by 100% space utilization host for high performance lithium-sulfur batteries. Chinese Chemical Letters, 2024, 35(4): 108565-. doi: 10.1016/j.cclet.2023.108565

    4. [4]

      Feng CaoChunxiang XianTianqi YangYue ZhangHaifeng ChenXinping HeXukun QianShenghui ShenYang XiaWenkui ZhangXinhui Xia . Gelation-pyrolysis strategy for fabrication of advanced carbon/sulfur cathodes for lithium-sulfur batteries. Chinese Chemical Letters, 2025, 36(3): 110575-. doi: 10.1016/j.cclet.2024.110575

    5. [5]

      Qihou LiJiamin LiuFulu ChuJinwei ZhouJieshuangyang ChenZengqiang GuanXiyun YangJie LeiFeixiang Wu . Coordinating lithium polysulfides to inhibit intrinsic clustering behavior and facilitate sulfur redox conversion in lithium-sulfur batteries. Chinese Chemical Letters, 2025, 36(5): 110306-. doi: 10.1016/j.cclet.2024.110306

    6. [6]

      Fangling Cui Zongjie Hu Jiayu Huang Xiaoju Li Ruihu Wang . MXene-based materials for separator modification of lithium-sulfur batteries. Chinese Journal of Structural Chemistry, 2024, 43(7): 100337-100337. doi: 10.1016/j.cjsc.2024.100337

    7. [7]

      Minjun YinYuhui LinManli ZhuangWei XiaoJie Wu . Photoredox-catalyzed synthesis of α,α-difluoromethyl-β-alkoxysulfones from sulfur dioxide. Chinese Chemical Letters, 2025, 36(3): 109926-. doi: 10.1016/j.cclet.2024.109926

    8. [8]

      Jiayi GuoLiangxiong LingQinwei LuYi ZhouXubiao LuoYanbo Zhou . Degradation of chloroxylenol by CoSx activated peroxomonosulfate: Role of cobalt-sulfur ratio. Chinese Chemical Letters, 2025, 36(4): 110380-. doi: 10.1016/j.cclet.2024.110380

    9. [9]

      Haixia WuKailu Guo . Sulfur reduction reaction mechanism elucidated with in situ Raman spectroscopy. Chinese Chemical Letters, 2025, 36(6): 110654-. doi: 10.1016/j.cclet.2024.110654

    10. [10]

      Yan WangHuixin ChenFuda YuShanyue WeiJinhui SongQianfeng HeYiming XieMiaoliang HuangCanzhong Lu . Oxygen self-doping pyrolyzed polyacrylic acid as sulfur host with physical/chemical adsorption dual function for lithium-sulfur batteries. Chinese Chemical Letters, 2024, 35(7): 109001-. doi: 10.1016/j.cclet.2023.109001

    11. [11]

      Yue WangWenli HuBinchao ShiHe JiaShilin MeiChang-Jiang Yao . Design of carbon@WS2 host with graham condenser-like structure for tunable sulfur loading of lithium-sulfur batteries. Chinese Chemical Letters, 2025, 36(6): 110065-. doi: 10.1016/j.cclet.2024.110065

    12. [12]

      Yixia ZhangCaili XueYunpeng ZhangQi ZhangKai ZhangYulin LiuZhaohui ShanWu QiuGang ChenNa LiHulin ZhangJiang ZhaoDa-Peng Yang . Cocktail effect of ionic patch driven by triboelectric nanogenerator for diabetic wound healing. Chinese Chemical Letters, 2024, 35(8): 109196-. doi: 10.1016/j.cclet.2023.109196

    13. [13]

      Yixuan WangJiexin LiZhihao ShangChengcheng FengJianmin GuMaosheng YeRan ZhaoDanna LiuJingxin MengShutao Wang . Wettability-driven synergistic resistance of scale and oil on robust superamphiphobic coating. Chinese Chemical Letters, 2024, 35(7): 109623-. doi: 10.1016/j.cclet.2024.109623

    14. [14]

      Yiming FangHuimin GaoKaiting ChengLiang BaiZhengtong LiYadong ZhaoXingtao Xu . An overview of photothermal materials for solar-driven interfacial evaporation. Chinese Chemical Letters, 2025, 36(3): 109925-. doi: 10.1016/j.cclet.2024.109925

    15. [15]

      Guoying Han Qazi Mohammad Junaid Xiao Feng . Topology-driven directed synthesis of metal-organic frameworks. Chinese Journal of Structural Chemistry, 2025, 44(3): 100447-100447. doi: 10.1016/j.cjsc.2024.100447

    16. [16]

      Jian PengYue JiangShuangyu WuYanran ChengJingyu LiangYixin WangZhuo LiSijie Lin . A nonradical oxidation process initiated by Ti-peroxo complex showed high specificity toward the degradation of tetracycline antibiotics. Chinese Chemical Letters, 2024, 35(5): 108903-. doi: 10.1016/j.cclet.2023.108903

    17. [17]

      Xinyu You Xin Zhang Shican Jiang Yiru Ye Lin Gu Hexun Zhou Pandong Ma Jamal Ftouni Abhishek Dutta Chowdhury . Efficacy of Ca/ZSM-5 zeolites derived from precipitated calcium carbonate in the methanol-to-olefin process. Chinese Journal of Structural Chemistry, 2024, 43(4): 100265-100265. doi: 10.1016/j.cjsc.2024.100265

    18. [18]

      Yiqian JiangZihan YangXiuru BiNan YaoPeiqing ZhaoXu Meng . Mediated electron transfer process in α-MnO2 catalyzed Fenton-like reaction for oxytetracycline degradation. Chinese Chemical Letters, 2024, 35(8): 109331-. doi: 10.1016/j.cclet.2023.109331

    19. [19]

      Xueyang ZhaoBangwei DengHongtao XieYizhao LiQingqing YeFan Dong . Recent process in developing advanced heterogeneous diatomic-site metal catalysts for electrochemical CO2 reduction. Chinese Chemical Letters, 2024, 35(7): 109139-. doi: 10.1016/j.cclet.2023.109139

    20. [20]

      Fengrui YangDebing WangXinying ZhangJie ZhangZhichao WuQiaoying Wang . Synergistic effects of peroxydisulfate on UV/O3 process for tetracycline degradation: Mechanism and pathways. Chinese Chemical Letters, 2024, 35(10): 109599-. doi: 10.1016/j.cclet.2024.109599

Metrics
  • PDF Downloads(4)
  • Abstract views(1130)
  • HTML views(20)

通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Address:Zhongguancun North First Street 2,100190 Beijing, PR China Tel: +86-010-82449177-888
Powered By info@rhhz.net

/

DownLoad:  Full-Size Img  PowerPoint
Return