Catalytic urea hydrolysis by composite metal oxide catalyst towards efficient urea-based SCR process: performance evaluation and mechanism investigation

Highlights

● Bimetallic oxide composite catalyst was designed for the urea-based SCR process.

● Surface chemical state and typical microstructure of catalyst was determined.

● Reaction route was improved based on intermediates and active site identification.

● TiO₂@Al₂O₃ presents an obvious promotion for urea hydrolysis.

Abstract

As a promising option to provide gaseous NH₃ for SCR system, catalytic urea hydrolysis has aroused great attention, and improving surface area and activity of catalysis are the crucial issues to be solved for efficient urea hydrolysis. Therefore, a composite metal oxide (TiO₂@Al₂O₃) catalyst was prepared by a simple hydrothermal method, with mesoporous alumina (γ-Al₂O₃) as substrate. The results verify the mesoporous structure and submicron cluster of TiO₂@Al₂O₃, with exposed crystal faces of (101) and (400) for TiO₂ and γ-Al₂O₃, respectively. The electronegativity difference of Ti⁴⁺ and Al³⁺ changes the charge distribution scheme around the interface, which provides abundant acid/base sites to boost the urea hydrolysis. Consequently, for an optimal proportioning with nano TiO₂ content at 10 wt.%, the hydrolysis efficiency can reach up to 35.2 % at 100 °C in 2 h, increasing by ~7.1 % than that of the blank experiment. ¹³C NMR spectrum measurements provide the impossible intermediate species during urea hydrolysis. Theoretical calculations are performed to clarify the efficient H₂O decomposition at the interface of TiO₂@Al₂O₃. The result offers a favorable technology for energy-efficiency urea hydrolysis.

Graphical abstract

Keywords

SCR / Urea hydrolysis / Catalytic / Water dissociation / Electronegativity

1 Introduction

Particulate matter (PM) is inevitable during industrial electrolysis (Ma et al., 2020b; Xu et al., 2020b). Generated PM is highly acidic due to containing acids such as sulfuric acid from zinc electrolysis (Sorour et al., 2017) or chromic acid from chrome electroplating (Shaw et al., 2020). It can also enrich heavy metals with concentrations up to thousands of times greater than in the electrolyte (Ma et al., 2020a). Such PM constitutes carcinogenic and non-carcinogenic occupational hazards to worker health (Ma et al., 2020a; Mokarram et al., 2020) and increases PM concentrations in the atmosphere. There is, therefore, an urgent need to control and reduce PM during industrial electrolysis, especially from the perspective of occupational workers’ health.

According to PM generation mechanisms, a fundamental approach to mitigating PM generation at its source involves modulating the characteristics of bubbles and altering the properties of the electrolyte. The PM is generated from the bubbles bursting at the liquid interface, including jet and film droplets (Wang et al., 2017; Deike et al., 2022). There are quantitative relationships between the bubble characteristics and the PM generation. For example, no film droplets form when the diameter of a bubble in seawater is < 1.00 mm (Wang et al., 2017), and no jet droplets form when the bubble diameter in pure water is < 8.00 μm (Ji et al., 2011). Properties of the solution, especially surface tension, also affect the total mass of PM formed, possibly by changing the thickness of the bubbles film (Ke et al., 2017). Specific to the electrolysis process, it is verified that bubble size has a noticeable effect on the amount of acid mist (Berny et al., 2021; Deike et al., 2022). The bubbles critical to PM formation are from electrochemical gas evolution reactions (usually oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER) (Luo et al., 2018; He et al., 2021). However, how the electrochemical reactions affect the formation of PM remains to be further explored.

Some effective methods for PM reduction have been put forward based on the preceding mechanisms and relationships. These include employing surfactants to reduce acid mist (Xu et al., 2020b), using ultrasonication (Ma et al., 2020b), and adopting a floating porous phase (Qu et al., 2022), and adjusting operating parameters (Al Shakarji et al., 2011b). Energy consumption and production productivity pose significant challenges to the integration of these methods into industrial practices, particularly in the context of the ongoing energy crisis and climate change (Xu et al., 2020a; Dwivedi et al., 2022). For instance, organic surfactants designed for acid mist prove to be highly efficient, modifying electrolyte surface tension or viscosity (Al Shakarji et al., 2013). However, they can present a host of issues: they may be chemically and thermally unstable, costly, toxic, or flammable. Moreover, they may augment energy consumption by a range of 3.43%–10.3% (Dhak et al., 2011; Sorour et al., 2017). Ultrasonication can reduce the size and number of bubbles (Bouakaz et al., 2005; Theerthagiri et al., 2020). It has been used to reduce PM generation during zinc electrolysis (Ma et al., 2020b) and chromium electroplating (Mason et al., 2001). Ultrasonication requires massive ultrasonic energy consumption despite saving 2.25% electrolysis energy consumption (Ma et al., 2020b). This barrier makes ultrasonication unusable in industrial applications in the foreseeable future. Electrode caps that allow bubbles to coalesce into more giant bubbles were invented and fixed to anodes to reduce PM emission by > 90% (Papachgristodoulou et al., 1985; Dusen and Smith, 1989). However, they did not affect PM < 1.00 µm in diameter, and none has been adopted for use in industrial operations (Mcginnity and Nicol, 2014). It is noteworthy that during copper electrolysis, alterations in operating parameters, including electrolyte temperature, current density, and H₂SO₄ concentration, can affect the generation of acid mist by modifying the nature of the electrolyte (Al Shakarji et al., 2013). This result indicates that adjusting operating parameters may be a practical way of PM for industrial electrolysis. However, the particular efficacies of altering these operating parameters on PM reduction and production performance are still unclear. Moreover, the specific reduction mechanisms involving electrochemical reactions, bubble characteristics, and surface tension remain to be investigated comprehensively.

In this study, a laboratory-scaled zinc electrolysis system was designed as a case study to investigate PM reduction efficacies and production performance by adjusting three operating parameters (electrolyte temperature, H₂SO₄ concentration, and current density). The optimal method to balance PM reduction with power consumption (PC) and productivity was also discussed using the response surface method. In addition, the mechanisms driving different ways of PM reduction were identified by analyzing bubble characteristics, electrochemical reactions, and surface tension. The results may provide a theoretical and practical roadmap for incorporating PM reduction in industrial production and indicate optional directions to exploring more effective and practical PM reduction methods for the electrolysis industry.

2 Materials and methods

2.1 Electrolysis experiment

Referring to our previous study (Ma et al., 2020b), galvanostatic zinc electrolysis was performed in a bench-scale home-made polymethyl methacrylate electrolysis cell (200 mm × 105 mm × 160 mm). To avoid the influence of anode age, all anodes were passivated with H₂SO₄ for 24 h and aged with electrolysis for 24 h. The schematic overview and operation details of the electrolysis experiment are presented in the supporting information (Fig. S1(a)). The electrolyte was prepared with analytical grade H₂SO₄ (> 98.0%), ZnSO₄·7H₂O, and MnSO₄·H₂O, which were purchased from the Sinopharm Chemical Reagent Co., China. The concentration of Zn²⁺ was 45.0 g/L, and that of Mn²⁺ was 3.00 g/L based on the industrial electrolyte composition. Electrolysis was performed for four hours and repeated twice for each set of parameters.

2.2 PM sampling and analysis

The flux of generated PM (GF_PM) and emission factor of generated PM (EF_PM) were measured with Eqs. (1) and (2) using the gravimetric method. GF_PM is only related to the PM generation rate, which directly influences the PM concentration in facilities and worker health. In contrast, EF_PM is related to both the PM generation rate and Zn deposition rate with relationships to a current density of the cathode, reflecting the PM emission level and the influence on the atmospheric environment. Detailed information on the sampling and analysis methods has been previously published (Ma et al., 2020b). In short, sampling was carried out in a polymethyl methacrylate box (0.5 m × 0.5 m × 1.5 m) with a gas distributor close to the bottom (Fig. S1(b)) to avoid the influence of ambient air. PM generated during electrolysis was collected on a Teflon filter (R2PL047, Pall Co. Ltd., USA) with a sampling flow rate of 16.7 L/min. Six filter samples collected in parallel were used in each test to ensure reliable data for analysis.

(1)${\mathrm{G}\mathrm{F}}_{\mathrm{P}\mathrm{M}}=\frac{M_{\mathrm{s}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e}}-M_{\mathrm{b}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{k}}}{t}$

(2)${\mathrm{E}\mathrm{F}}_{\mathrm{P}\mathrm{M}}=\frac{{\mathrm{G}\mathrm{F}}_{\mathrm{P}\mathrm{M}}}{R_{\mathrm{Z}\mathrm{n}}}$

where M_sample is the mass of aerosol or sulfuric acid mist on the filter during electrolysis (g); M_blank is the mass of aerosol or sulfuric acid mist on a blank filter (g); t is the sampling time (h); and S is the aerosol generation area of the electrolysis cell (m²).

2.3 Assessment of production performance

The production performance indicators’ values affected by the operating parameters were calculated and analyzed. Impurity content (IC), including Pb, Fe, Cd, Al, Cu, and Sn, affects the quality of the grade of zinc products. Zn_99.995 is the highest grade of Zn (pure Zn metal) with IC < 0.005%. Detailed classification of zinc grade is given in Table S1. After digestion, the percentages of impurities in the Zn product were analyzed using inductively coupled plasma mass spectrometry (ICP-MS, X series, Thermo Fisher Scientific Co. Ltd., USA). The current efficiency of Zn deposition (CE_Zn) is the ratio of theoretical deposited Zn to actual deposited Zn. CE_Zn was calculated using Eq. (3) after the Zn deposited on the cathode during electrolysis was weighed. R_Zn, the actual rate of Zn deposition, was calculated with Eq. (4). CE_Zn and R_Zn are two measures of productivity. PC, defined as the energy required for electrolysis to produce a unit mass of Zn (kWh/t Zn), serves as an indicator of the energy consumption associated with electrolysis cost. The cell voltage was measured using a multimeter (the voltage drop between the adjacent cathode and anode plates, V_cell). PC was then calculated using Eq. (5).

(3)${\mathrm{C}\mathrm{E}}_{\mathrm{Z}\mathrm{n}}=\frac{M_{\mathrm{Z}\mathrm{n}}}{1.22\times I\times t}\times 100\mathrm{\%},$

(4)$R_{\mathrm{Z}\mathrm{n}}=\frac{M_{\mathrm{Z}\mathrm{n}}}{t},$

(5)$\mathrm{P}\mathrm{C}=\frac{V_{\mathrm{c}\mathrm{e}\mathrm{l}\mathrm{l}}}{q\times {\mathrm{C}\mathrm{E}}_{\mathrm{Z}\mathrm{n}}}\times 1000.$

where M_Zn is the mass of Zn deposited on the cathode (g); I is the current (A); t is the time duration of electrolysis (h); V_cell is the cell voltage (V); and q is the electrochemical equivalent, referring to the amount of electrolytic metal produced by 1 Coulomb (C) of electricity, 1.22 g/A/h for Zn.

2.4 Characterization and analysis

2.4.1 Measurement of bubble characteristics

Bubble characteristics under different operating conditions were observed and analyzed according to a previously published method (Ma et al., 2020b). A continuous wave laser (7 W) with a 1 mm width beam illuminated the area under observation (22 mm × 40 mm × 1 mm). A 16-bit CMOS high-speed camera (PCO. Edge, PCO Co., Ltd., Germany) with a Canon EF 100 mm f/2.8 macro USM lens was used to capture bubble images. The bubbles were filmed at 50 Hz with an exposure time of 200 μs at a resolution of 2560 × 2160 pixels. The images were segmented by PIV-view software using thresholding, and the number and size of the bubbles were automatically counted by phase-size estimation software. Image resolution allowed bubbles ≥ 20 µm diameter to be observed. This method semiquantitatively indicates the number and size of the bubbles, although the concentration of bubbles varies at different locations in the system.

2.4.2 Quantification of gas production

The current efficiencies of OER (CE_OER) and HER (CE_HER) and the gas generation rates (R_i) were estimated to quantify the amount of gas produced. Electrolyte at the inlet and outlet of the electrolysis cell was collected to quantify dissolved Mn; the current efficiency of Mn²⁺ oxidation (CE_Mn) was then calculated using Eq. (6). Next, CE_OER was calculated using Eq. (7), which ignored the effect on the current efficiency of Pb corrosion (Zhang et al., 2018), and CE_HER was calculated using Eq. (8). Finally, the gas generation rates of O₂ ($R_{{\mathrm{O}}_2}$) and H₂ ($R_{{\mathrm{H}}_2}$) were also calculated by Eq. (9):

(6)${\mathrm{C}\mathrm{E}}_{\mathrm{M}\mathrm{n}}=\frac{{(C}_{\mathrm{i}\mathrm{n}}-C_{\mathrm{o}\mathrm{u}\mathrm{t}})\times V\times n\times F}{I\times t}\times 100\mathrm{\%},$

(7)${\mathrm{C}\mathrm{E}}_{\mathrm{O}\mathrm{E}\mathrm{R}}=100\mathrm{\%}-{\mathrm{C}\mathrm{E}}_{\mathrm{M}\mathrm{n}},$

(8)${\mathrm{C}\mathrm{E}}_{\mathrm{H}\mathrm{E}\mathrm{R}}=100\mathrm{\%}-{\mathrm{C}\mathrm{E}}_{\mathrm{Z}\mathrm{n}},$

(9)$R_i=\frac{{I\times \mathrm{C}\mathrm{E}}_i\times V}{n\times F},$

where C_in and C_out represent the respective concentrations of Mn dissolved in the electrolyte at the cell inlet and outlet (mol/L); V is the volume of the electrolyte (L); n is the number of electrons participating in the reaction. In this case, n = 2 due to the reaction product being the solid MnO₂. F is the Faraday constant (C).

2.4.3 Electrochemical characterization

Linear sweep voltammetry (LSV) was used to explain the changes in electrochemical reactions and energy consumption under different operating parameters. Using a three-electrode system, the experiments were conducted on an electrochemical workstation (CHI608D, Shanghai CH Instruments Company in China). A saturated mercury sulfate electrode (MSE) was selected as the reference electrode to avoid introducing additional impurities. For anodic reactions, a lead-based alloy with an effective area of 1 cm² was used as the working electrode, and an aluminum sheet with an area of 6 cm² was used as the counter electrode. The starting and ending voltages of linear scanning were 1.26 and 1.60 V. Pure aluminum with a geometric area of 0.79 cm² was used as a working electrode, and a graphite plate of 6.00 cm² was used as the counter electrode for cathodic reactions. The starting and ending voltages of linear scanning were −1.46 and −1.85 V, respectively. The scan rates for anodic and cathodic reactions were 0.001 V/ms. Before the experiment, the working electrode was sanded with 1200-grade sandpaper until its surface was smooth, and the electrode surface was washed with absolute ethanol, followed by high-purity water.

2.4.4 Measurement of surface tension of the electrolyte

Surface tension was also measured to identify its effects on PM generation under variable operating parameters. An automatic surface tension meter (K100, KRUSS, Germany) using a Wilhelmy plate was used to measure the surface tension of the electrolyte for various temperatures and different H₂SO₄ concentrations.

2.5 Experiment design and optimization parameters

A single-factor laboratory experiment was designed to identify the specific influence of electrolyte temperature, the current density of the cathode, and H₂SO₄ concentration on PM generation. Table S2 shows the values set for each parameter. The values of these three parameters were chosen based on industrial zinc electrolysis practices. The response surface methodology (RSM) based on central composite design (CCD) optimized the PM reduction rate and zinc production performance. The experiment matrix was designed by Design-Expert® Software Version 12, and the design scheme consisted of 15 experimental runs with each variable evaluated at three levels (Table S3). Statistical significance and adequacy of the model were examined by ANOVA and determined by Fisher’s F-test, respectively. The effects of independent parameters on GF_PM, EF_PM, CE_Zn, and PC were fitted using multivariate regression analysis. The polynomial expressions and the probability values (p-value) of Fisher’s F-test were also analyzed.

3 Results and discussion

3.1 PM reduction by optimizing the operating parameters

As Fig.1(a) and 1(b) shows, GF_PM was positively correlated with electrolyte temperature, H₂SO₄ concentration, and current density. EF_PM varied in the same way as GF_PM with the change of electrolyte temperature and H₂SO₄ concentration but decreased first and then increased as current density increased. For example, as the electrolyte temperature increased from 298 to 328 K, GF_PM rose from 14.6 to 258 g/h, and EF_PM increased from 1.27 to 22.5 kg/t Zn. Unlike GF_PM, the minimum value of EF_PM (9.83 kg/t Zn) appeared at 500 A/m² when the current density increased because it is affected by both GF_PM and the Zn deposition rate. The analysis of variance for the single factor showed that the difference among the three treatments is statistically significant (p < 0.0001). These results indicate that PM generation reduction can be accomplished in three ways: decreasing electrolyte temperature, reducing H₂SO₄ concentration, or decreasing current density. Of the three methods identified, lowering the electrolyte temperature is the most effective, second only to using the most efficient surfactants, and diminishing the H₂SO₄ concentration is the least effective. Specifically, starting with conventional values of the three operating parameters (313 K, 160 g/L, 500 A/m²), GF_PM was reduced by 89.0%, 12.6%, and 19.1% if the parameters decreased to 298 K, 110 g/L, and 300 A/m². The GF_PM at different electrolyte temperatures and current densities are the same as those obtained in a previous study of copper electrolysis (Al Shakarji et al., 2013). Contrary to this study which suggests that higher acidity results in lower acid mist, our proposed adjustment of H₂SO₄ concentration presents a contrasting viewpoint. The difference may be explained by copper electrolysis having different electrolytes and using other electrode materials, so the H₂SO₄ concentration affects the gas evolution reactions differently.

Fig.1 Influences of three operational parameters on (a) the generation flux of aerosols (GFPM), (b) emission factor of PM (EFPM), (c) Pb content in the Zn product (ICPb) and Zn deposition rate (RZn), and (d) current efficiency of Zn deposition (CEZn) and PC.

Full size|PPT slide

In addition to environmental benefits, PC and consequent economic benefits are also concerns that drive practical application. Efficient industrial electrolysis demands higher product output, fewer product impurities, and less energy consumption. The performances of R_Zn, CE_Zn, IC_Pb, and PC were investigated, and their results are shown in Fig.1(c) and Fig.1(d). Among all impurities, Pb content (IC_Pb) was only discussed here due to the negligible percentages of other impurities, such as Cd and Fe (Table S4). It is favorable that the three methods of reducing PM generation all improved product quality with Pb reduction by 4.35%–21.7% (Fig.1(c)) compared with conventional electrolysis. The other three performance indicators became significant factors in the industrial application of these three methods. With the increasing electrolyte temperature, R_Zn and CE_Zn increased obviously, but PC decreased. When H₂SO₄ concentration increased from 110 to 210 g/L, R_Zn, CE_Zn, and average PC, all decreased slightly. As current density increased, R_Zn and PC increased, but CE_Zn decreased. These results indicate the drawbacks of the three PM reduction methods. Specifically, reducing the electrolyte temperature resulted in lower CE_Zn and an additional 10.7% power. A reduction in H₂SO₄ concentration bolstered Zn productivity, though the PM reduction efficiency remained minimal and was associated with a slight increase in PC. A decrease in current density, on the other hand, led to a reduced R_Zn and a higher EF_PM. Overall, a contradiction appears to exist between the PM reduction rate and certain production performance indicators.

To balance the PM reduction rate with performance indicators, the results from the CCD design based on RSM methodology were analyzed to find the optimal operational parameter combination. Polynomial expressions and the probability values (p-value) of Fisher’s F-test are demonstrated in SI (S.1). The three-dimensional graph of the factors’ effects and their combined effects on GF_PM, EF_PM, CE_Zn, and PC are presented in Fig.2(a)–Fig.2(d). For GF_PM and EF_PM, the influence of the electrolyte temperature and current density proved significant, while the effect of H₂SO₄ concentration was insignificant and ignorable, aligning with the impact of a single factor. GF_PM showed a linear response to changes in electrolyte temperature and current density with an adjusted R² of 0.893 (Table S5). Meanwhile, EF_PM exhibited a quadratic response to electrolyte temperature and current density with an adjusted R² of 0.926. The validity of the fitted equations was subsequently corroborated under random conditions.

Fig.2 Response surface graphs showing the effects of operating parameters: (a) generation flux of PM, GFPM; (b) emission factor of PM, EFPM; (c) current efficiency of Zn deposition, CEZn; and (d) energy consumption by electrolysis, PC. And PM reduction effects and Zn production performance indicators: (e) GFPM; (f) EFPM; (g) CEZn; and (h) PC, at the optimized conditions. (a, b, and d were drawn at H2SO4 concentration of 160 g/L and c was drawn at current density of 500 A/m2; Optimization 1: 295 K, 110 g/L, and 373 A/m2; Optimization 2: 301 K, 110 g/L, and 347 A/m2).

Full size|PPT slide

The obtained polynomial expressions were employed to propose specific operating parameters and further optimize the PM reduction rate and Zn production performance based on multi-objectives. An optimized condition for PM reduction was proposed to be 295 K, 110 g/L, and 373 A/m² with the premise of invariable CE_Zn and PC. The predicted reduction rates of GF_PM and EF_PM, illustrated in Fig.2(e) and Fig.2(f), are 86.3% and 79.3%, respectively. However, unlike PM, the potential for improving CE_Zn and PC was slight, with the maximum calculated efficiencies in this study falling below 5.19% and 5.94%, respectively. With the objectives of minimizing GF_PM and EF_PM and maximizing CE_Zn and PC, the parameters were predicted to be 301 K, 110 g/L, and 347 A/m².

The corresponding reduction rates of GF_PM, EF_PM, and PC were 60.4%, 30.2%, and 2.02%, respectively, with an increase of 0.66% in CE_Zn (Fig.2(g) and Fig.2(h)). Despite certain practical constraints—such as the amplification effect during industrial production—these optimized conditions suggest the existence of at least one optimal combination of conditions capable of simultaneously reducing PM generation and emissions, promoting Zn production, and exerting a minimal effect on energy consumption.

3.2 PM reduction mechanisms of varying operating parameters

This section delves into the impacts of adjusting operating parameters on both the reduction of PM generation and the enhancement of Zn production performance from the perspectives of bubble characteristics, surface tension, and electrochemical reactions. An overarching mechanism is outlined to guide further exploration of cleaner reduction methods.

3.2.1 Electrolyte temperature

Electrolyte temperature mainly affects GF_PM by changing microbubble characteristics rather than changing surface tension. As Fig. S2(a) shows, surface tension increased as electrolyte temperature decreased. Larger surface tension should increase GF_PM because the bubble film is thicker when a bubble bursts at the solute surface (Ke et al., 2017). It has been empirically verified that the electrolyte’s surface tension is proportional to the sulfuric acid mist concentration during copper electrolysis (Al Shakarji et al., 2011b). However, in contrast to surface tension, bubble characteristics oppose PM generation at varying electrolyte temperatures. Fig.3(a)–Fig.3(c) shows the number-size distribution of bubbles in electrolyte at different electrolyte temperatures, H₂SO₄ concentrations, and current densities. As the electrolyte temperature decreased, both the number and size of microbubbles diminished, illustrated in Fig.3(a), Fig.3(d), and Fig.3(e), aligning with the results observed in copper electrolysis (Al Shakarji et al., 2011a). Fewer and smaller microbubbles should contribute to a decline in GF_PM (Ma et al., 2020a). The positive correlation between GF_PM and electrolyte temperature (Fig.1(a)) indicates that bubble characteristics are the determinant factors of GF_PM. In other words, the reduction in PM generation brought about by the decreased number and size of microbubbles surpassed the increase in PM generation resulting from enhanced surface tension.

Fig.3 Bubble characteristics for different operational parameters: (a–c) number–size distribution of bubbles; (d) the total number of bubbles in observed ozone; (e) mean calculated bubble diameter.

Full size|PPT slide

The decrease in the number and size of microbubbles at the lower electrolyte temperature may be due to inhibited OER. The current efficiencies of the main electrolytic reactions and the gas evolution rates were calculated with results shown in Fig.4(a)–Fig.4(c). The CE_OER at the anode rose from 87.9% to 98.7%, and $R_{{\mathrm{O}}_2}$ increased from 216 to 247 mL/min as the electrolyte temperature increased from 298 to 328 K, demonstrated in Fig.4(a) and Fig.4(d). The lower CE_OER and $R_{{\mathrm{O}}_2}$ at lower electrolyte temperature verified the inhibited OER and less generated O₂. On the cathode, electrolyte temperature variation should affect both Zn deposition and HER. In comparison, Zn deposition should be more susceptible to electrolyte temperature than HER, because the electrolyte temperature influences Zn²⁺ transfer rate more significantly but H⁺ concentration in electrolyte is large enough so as to the same surface and bulk concentrations of H⁺ (Lasia, 2019). Higher temperature could boost the Zn²⁺ transfer rate, leading to a higher CE_Zn (Fig.1(d)). Thus, the calculated CE_HER decreased from 13.1% to 5.95% as the electrolyte temperature increased from 298 to 328 K, presented in Eq. (8). Consequently, the H₂ generation was anticipated to increase, leading to a higher calculated ${\mathrm{R}}_{{\mathrm{H}}_2}$ at a lower electrolyte temperature. It is essential that the decrease in $R_{{\mathrm{O}}_2}$ (38.2 mL/h) was more significant than the increase in $R_{{\mathrm{H}}_2}$ (22.1 mL/h). Therefore, the total gas evolution rate decreased at the lower electrolyte temperature, thus decreasing both the number and size of microbubbles. The lower temperature can also reduce the total gas volume and the size of microbubbles by the ideal gas law under constant mass and pressure conditions (Xue et al., 2019).

Fig.4 Current efficiency of electrochemical reactions on anode and cathode for different operational parameters: (a) electrolyte temperature; (b) H2SO4 concentration; (c) current density; and gas evolution rates for three operational parameters: (d) electrolyte temperature; (e) H2SO4 concentration; (f) current density.

Full size|PPT slide

The impact mechanism of electrolyte temperature on Zn production performance indicators was also investigated. Variations in polarization curves and dynamic potentials at both anode and cathode are shown in Fig.5. At the anode, the potentials at a given current density of 50 mA/cm² were 1.482, 1.417, and 1.407 V at electrolyte temperatures of 298, 313, and 328 K with Mn²⁺ (Fig.5(a)). The anodic polarization curve, depicted in the absence of Mn²⁺ in the electrolyte, representing soly OER activity at the anode, exhibits a similar trend (Fig.5(b)). These findings are consistent with the conclusions of a previous study (Zhang et al., 2018), indicating a higher anodic potential at lower electrolyte temperatures. During the potential sweeping of the cathode, the current density peaked at around −1.48 V (MSE; see Fig.5(c)), corresponding to the deposition of Zn (Wu et al., 2014). The polarization curves exhibited a negative shift as the electrolyte temperature decreased, resulting in the more negative potentials of Zn deposition and HER at 50 mA/cm². For HER, the corresponding overpotentials were estimated to increase by 102 and 70 mV at 313 and 328 K, respectively, compared to the values observed at 298 K. The higher potentials necessarily would result in higher cell voltage and PC. The weakened CE_Zn is mainly due to the enhanced concentration polarization of Zn deposition at lower electrolyte temperatures. Specifically, lower temperature leads to a lower diffusion rate of ions (Maslova et al., 2020) and the possible existence of a quiet Zn²⁺ concentration zone near the cathode. Thus, the Zn deposition was less selective than HER.

Fig.5 Polarization curves under different operational parameters: (a–c) electrolyte temperatures; (d–f) H2SO4 concentrations.

Full size|PPT slide

3.2.2 H₂SO₄ concentration

The slight influence of H₂SO₄ concentration on GF_PM was observed as a combined effect of surface tension and bubble characteristics. As H₂SO₄ concentration decreased, the surface tension decreased (Fig. S2(b)), contributing to fewer and smaller microbubbles and, therefore, a decreased GF_PM. On the other hand, a decrease in H₂SO₄ concentration slightly reduced gas generation and, thus, the size of microbubbles. Specifically, as the H₂SO₄ concentration decreased from 160 to 110 g/L, CE_OER and $R_{{\mathrm{O}}_2}$ were affected with increases of 0.94% and 2.45 mL/h, respectively (see Fig.4), showing OER was slightly enhanced. However, the decrease of CE_HER (1.17%, Fig.4(b)) and the decrease of R_H2 (6.08 mL/h, Fig.4(e)) demonstrate that lower H₂SO₄ concentration inhibited HER and therefore reduced the quantity of H₂ generated. As a result, the total gas evolution rate slightly decreased by 3.63 mL/h (1.22% of the total gas evolution rate at 160 g/L). Thus, fewer and smaller microbubbles were observed (Fig.3(b), 3(d), and 3(e)). In addition, the more minor variations of gas evolution rate and bubble characteristics caused by H₂SO₄ concentration than that caused by electrolyte temperature accounted for the insignificant model item for predicted GF_PM and EF_PM in Section 3.1.

Variations in polarization curves and dynamic potentials at both anode and cathode at different H₂SO₄ concentrations in Fig.5(d)–Fig.5(f). Lower H₂SO₄ concentrations resulted in larger potentials of electrode reactions, especially the cathodic reactions, compared with conventional 160 g/L. The potential to catalyze the HER is primarily controlled by the Nernstian potential for the HER, the ohmic potential drop, and the reaction overpotential (Zeng and Li, 2015). The more negative potential of HER can be mainly attributed to the lower H₂SO₄ concentration, which reduced the HER overpotential by 0.01 V and the Nernstian potential for the HER by 0.003V. This is based on the premise of no concentration gradient existing on the cathodic electrode, along with the electrolyte conductivity remaining constant (Kargl-Simard et al., 2003). Additionally, the lower H₂SO₄ concentration also noticeably made the potential of Zn deposition at 50 mA/cm² more negative, illustrated in Fig.5(f). Given that the Zn²⁺ concentration and electrolyte temperature remained unchanged, the Nernstian potential remained constant. The higher overpotential of Zn deposition (calculated to be 0.03 V, excluding the influence of Zn²⁺ concentration polarization) and ohmic potential drop both contributed to an increase in the potential of Zn deposition. The results verified the higher PC at lower H₂SO₄ concentrations.

3.2.3 Current density

The mechanism of GF_PM reduction caused by lowering current efficiency is the synchronously reduced $R_{{\mathrm{O}}_2}$ and $R_{{\mathrm{H}}_2}$ that causes fewer and smaller microbubbles. Lower current density means reduced power supply and decreased number of electrons participating in the reaction; thus, $R_{{\mathrm{O}}_2}$ and $R_{{\mathrm{H}}_2}$ should proportionally decrease by 37.5%. $R_{{\mathrm{O}}_2}$ and $R_{{\mathrm{H}}_2}$ were lower than the theoretical value because lower current density also promoted CE_OER and CE_HER by 1.39% and 1.48% (Fig.4(c)). Whereas the increased CE_OER and CE_HER are too little to balance the reduction due to decreased power supply. Consequently, the total gas quantity is still reduced, leading to smaller and fewer microbubbles and further GF_PM. The measured number and size of bubbles in Fig.3(c)–Fig.3(e), in agreement with a previous study (He et al., 2022), verified the mechanism. The influence of surface tension on particulate matter generation resulting from bubble bursting was significant (Ghabache and Seon, 2016; Deike et al., 2022). The current density also possibly influences the surface tension, subsequently affecting particulate matter generation. However, based on the discussion about electrolyte temperature and H₂SO₄ concentration, this effect is possibly less significant in comparison to the role of electrochemical reactions. Still, the electrolyte’s surface tension could not be quantified for different current densities due to the limitation of the testing technologies.

The larger CE_Zn at a lower current density is related to the unaffected Zn²⁺ diffusion. Zn deposition kinetics play a significant role around 100 A/m² (Cai et al., 2022). However, at higher current densities (e.g., 600–1000 A/m²), Zn²⁺ to the electrode would be exhausted quickly, resulting in a diffusion-controlled case (Cai et al., 2022), inducing a lower Zn deposition rate and thus lower CE_Zn. The difference of Zn²⁺ near the cathode also affects Zn deposition overpotential. Further, the overpotential of Zn deposition should be reduced because of relatively more Zn²⁺ near the cathode region at a lower current density. Lower overpotential and higher CE_Zn contributed to lower PC at lower current density.

4 Conclusions

Zinc electrolysis laboratory experiments were conducted to investigate methods of reducing the production of hazardous PM by controlling three operating parameters. Results show that controlling operating parameters is feasible for decreasing PM generation flux and PM emission factor. Of the three methods identified, lowering the electrolyte temperature is the most effective (89.0% reduction rate of GF_PM), followed by decreasing current density and decreasing H₂SO₄ concentration. However, these methods are always accompanied by higher PC or lower current efficiency of Zn deposition. The optimal combination of these three operating parameters was found by RSM methodology, which can simultaneously reduce PM generation and emission and maintain or promote Zn production and power conservation. Finally, the general reduction mechanism was inferred: reductions in electrolyte temperature, H₂SO₄ concentration, and current density inhibited the gas evolution reactions (OER and HER individually or together) to decrease the total amount of gas produced, thus reducing the number and size of microbubbles and decreasing GF_PM. In particular, lowering the electrolyte temperature inhibits OER and gas compression; decreasing the H₂SO₄ concentration inhibits HER and decreases surface tension. Reducing current density inhibits both OER and HER by decreasing the reaction current. Future research should concentrate on the industrial application of optimization operating parameters to minimize PM and promote Zn production. Further, developing new approaches to controlling gas generation and microbubble characteristics is also significant for PM reduction in the electrolysis process. This will ensure cleaner industrial electrolysis processes and create more sustainable industrial zinc electrolysis.

References

[1] Baithy M, Mukherjee D, Rangaswamy A, Reddy B M. (2022). Structure–activity relationships of WO_x-promoted TiO₂–ZrO₂ solid acid catalyst for acetalization and ketalization of glycerol towards biofuel additives. Catalysis Letters, 152(5): 1428–1440

[2] Bernhard A M, Peitz D, Elsener M, Schildhauer T, Kröcher O. (2013). Catalytic urea hydrolysis in the selective catalytic reduction of NO_x: catalyst screening and kinetics on anatase TiO₂ and ZrO₂. Catalysis Science & Technology, 3(4): 942–951

[3] Cai J, Zheng W, Wang Q. (2021). Effects of hydrogen peroxide, sodium carbonate, and ethanol additives on the urea-based SNCR process. Science of the Total Environment, 772: 145551

[4] Chen Q, Zhang X, Li B, Niu S, Zhao G, Wang D, Peng Y, Li J, Lu C, Crittenden J. (2021a). Insight into the promotion mechanism of activated carbon on the monolithic honeycomb red mud catalyst for selective catalytic reduction of NO_x. Frontiers of Environmental Science & Engineering, 15(5): 92

[5] Chen Z, Yin H, Wang C, Wang R, Peng Y, You C, Li J. (2021b). New insights on competitive adsorption of NO/SO₂ on TiO₂ anatase for photocatalytic NO oxidation. Environmental Science & Technology, 55(13): 9285–9292

[6] Chen Z, Yin H, Wang R, Peng Y, You C, Li J. (2022). Efficient electron transfer by plasmonic silver in SrTiO₃ for low-concentration photocatalytic NO oxidation. Environmental Science & Technology, 56(6): 3604–3612

[7] Dan M, Mihet M, Borodi G, Lazar M D. (2021). Combined steam and dry reforming of methane for syngas production from biogas using bimodal pore catalysts. Catalysis Today, 366: 87–96

[8] Ebrahimian V, Nicolle A, Habchi C. (2012). Detailed modeling of the evaporation and thermal decomposition of urea-water solution in SCR systems. AIChE Journal. American Institute of Chemical Engineers, 58(7): 1998–2009

[9] Elsener M, Nuguid R J G, Kröcher O, Ferri D. (2021). HCN production from formaldehyde during the selective catalytic reduction of NO_x with NH₃ over V₂O₅/WO₃-TiO₂. Applied Catalysis B: Environmental, 281: 119462

[10] Fan X, Kang S, Li J. (2020). Plasma-enhanced hydrolysis of urea and SCR of NO over V₂O₅-MoO₃/TiO₂: decrease of reaction temperature and increase of NO conversion. Fuel, 277: 118155

[11] Gan L, Li K, Niu H, Peng Y, Chen J, Huang Y, Li J. (2021). Simultaneous removal of NO_x and chlorobenzene on V₂O₅/TiO₂ granular catalyst: Kinetic study and performance prediction. Frontiers of Environmental Science & Engineering, 15(4): 70

[12] Gan X, Yao D, Wu F, Dai J, Wei L, Li X. (2016). Modeling and simulation of urea-water-solution droplet evaporation and thermolysis processes for SCR systems. Chinese Journal of Chemical Engineering, 24(8): 1065–1073

[13] Hu X, Qu W, Chen J, Xu D, Liu J, Dong Y, Liu R, Ma Z, Tang X. (2022). Speeding up low-temperature SCR with reactants-coupling dual catalytic sites. Chemical Engineering Journal, 440: 135832

[14] Huang H, Chen Y, Li Z, Wang H, Hao B, Chen Y, Lei H, Guo X. (2020). Analysis of deposit formation mechanism and structure optimization in urea-SCR system of diesel engine. Fuel, 265: 116941

[15] Jayaprakash S, Dewangan N, Jangam A, Das S, Kawi S. (2021). LDH-derived Ni–MgO–Al₂O₃ catalysts for hydrogen-rich syngas production via steam reforming of biomass tar model: effect of catalyst synthesis methods. International Journal of Hydrogen Energy, 46(35): 18338–18352

[16] Kapusta Ł J, Sutkowski M, Rogóż R, Zommara M, Teodorczyk A. (2019). Characteristics of water and urea-water solution sprays. Catalysts, 9(9): 750

[17] Khan M M, Jin L, Khan M M, Li Y, Saulat H, Zhang Y, Sarfraz M, Zhu J, Hu H. (2021). CO₂ reforming of methane over activated carbon-Ni/MgO-Al₂O₃ composite catalysts for syngas production. Fuel Processing Technology, 211: 106595

[18] KröcherO, ElsenerM, JacobE (2009). A model gas study of ammonium formate, methanamide and guanidinium formate as alternative ammonia precursor compounds for the selective catalytic reduction of nitrogen oxides in diesel exhaust gas. Applied Catalysis B: Environmental, 88(1–2): 66–82

[19] Li F, Wang L, Xu S, Liang S, Zhang N. (2021). Readily-fabricated supported MgO catalysts for efficient and green synthesis of diethyl carbonate from ethyl carbamate and ethanol. RSC Advances, 11(25): 15477–15485

[20] Li Y, Chen Z, Zhan G, Yuan B, Wang L, Li J. (2022). Inducing efficient proton transfer through Fe/Ni@COF to promote amine-based solvent regeneration for achieving low-cost capture of CO₂ from industrial flue gas. Separation and Purification Technology, 298: 121676

[21] Liu L, Jiang Y, Zhao H, Chen J, Cheng J, Yang K, Li Y. (2016). Engineering coexposed {001} and {101} facets in oxygen-deficient TiO₂ nanocrystals for enhanced CO₂ photoreduction under visible light. ACS Catalysis, 6(2): 1097–1108

[22] Liu W M, Li J. (2021). Pyridinic N-reduced graphene oxide and ZnO composite synergistically enhance photocatalytic performance. Environmental Science and Pollution Research International, 28(5): 5398–5406

[23] Ma Y, Wu X, Zhang J, Ran R, Weng D. (2018). Urea-related reactions and their active sites over Cu-SAPO-34: formation of NH₃ and conversion of HNCO. Applied Catalysis B: Environmental, 227: 198–208

[24] Pan J, Dong Z, Wang B, Jiang Z, Zhao C, Wang J, Song C, Zheng Y, Li C. (2019). The enhancement of photocatalytic hydrogen production via Ti³⁺ self-doping black TiO₂/g-C₃N₄ hollow core-shell nano-heterojunction. Applied Catalysis B: Environmental, 242: 92–99

[25] Raza H, Woo S, Kim H. (2022). Investigation of an ammonium carbamate–based SCR system for NO_x reduction in diesel engines under transient conditions. Energy, 251: 123918

[26] Sadashiva Prabhu S, Nayak N S, Kapilan N, Hindasageri V. (2017). An experimental and numerical study on effects of exhaust gas temperature and flow rate on deposit formation in Urea-Selective Catalytic Reduction (SCR) system of modern automobiles. Applied Thermal Engineering, 111: 1211–1231

[27] Schweigert D, Damson B, Lüders H, Börnhorst M, Deutschmann O. (2019). Heat transfer during spray/wall interaction with urea water solution: an experimental parameter study. International Journal of Heat and Fluid Flow, 78: 108432

[28] Shang H, Li M, Li H, Huang S, Mao C, Ai Z, Zhang L. (2019). Oxygen vacancies promoted the selective photocatalytic removal of NO with Blue TiO₂ via simultaneous molecular oxygen activation and photogenerated hole annihilation. Environmental Science & Technology, 53(11): 6444–6453

[29] Shen S, Li M, Li B, Zhao Z. (2014). Catalytic hydrolysis of urea from wastewater using different aluminas by a fixed bed reactor. Environmental Science and Pollution Research International, 21(21): 12563–12568

[30] Shi J, Zhang Z, Chen M, Zhang Z, Shangguan W, Gu S, Shin-Ichi H. (2018). Effect of alumina and zirconia as binders on the activity of Fe-BEA for NH₃-SCR of NO. Frontiers of Environmental Science & Engineering, 12(1): 15

[31] Song K, Zhu S, Lu Y, Dao G, Wu Y, Chen Z, Wang S, Liu J, Zhou W, Hu H Y. (2022). Modelling the thresholds of nitrogen/phosphorus concentration and hydraulic retention time for bloom control in reclaimed water landscape. Frontiers of Environmental Science & Engineering, 16(10): 129

[32] SulaemanU, Yin S, SatoT (2011). Solvothermal synthesis and photocatalytic properties of chromium-doped SrTiO₃ nanoparticles. Applied Catalysis B: Environmental, 105(1–2): 206–210

[33] Sun Q, Li J, Wang C, Chen A, You Y, Yang S, Liu H, Jiang G, Wu Y, Li Y. (2022). Research progress on distribution, sources, identification, toxicity, and biodegradation of microplastics in the ocean, freshwater, and soil environment. Frontiers of Environmental Science & Engineering, 16(1): 1

[34] Tao H, Xing J, Pan G, Pleim J, Ran L, Wang S, Chang X, Li G, Chen F, Li J. (2022). Impact of anthropogenic heat emissions on meteorological parameters and air quality in Beijing using a high-resolution model simulation. Frontiers of Environmental Science & Engineering, 16(4): 44

[35] Tischer S, Börnhorst M, Amsler J, Schoch G, Deutschmann O. (2019). Thermodynamics and reaction mechanism of urea decomposition. Physical Chemistry Chemical Physics, 21(30): 16785–16797

[36] Wang D, Dong N, Niu Y, Hui S. (2019). A review of urea pyrolysis to produce NH₃ used for NO_x removal. Journal of Chemistry, 2019: 1–11

[37] Wang Z T, Wang Y G, Mu R, Yoon Y, Dahal A, Schenter G K, Glezakou V A, Rousseau R, Lyubinetsky I, Dohnálek Z. (2017). Probing equilibrium of molecular and deprotonated water on TiO₂(110). Proceedings of the National Academy of Sciences of the United States of America, 114(8): 1801–1805

[38] Wu Y J, Wang F, Tang W, Kakwani R, Hou Y, Feng G. (2020). Urea Decomposition and implication for NO_x reduction with Cu‐Zeolite and vanadia‐selective catalytic reduction. Chemical Engineering & Technology, 43(9): 1758–1764

[39] Xing L, Wei K, Li Y, Fang Z, Li Q, Qi T, An S, Zhang S, Wang L. (2021). TiO₂ coating strategy for robust catalysis of the metal-organic framework toward energy-efficient CO₂ capture. Environmental Science & Technology, 54: 13944–13952

[40] Yan L, Ji Y, Wang P, Feng C, Han L, Li H, Yan T, Shi L, Zhang D. (2020). Alkali and phosphorus resistant zeolite-like catalysts for NO_x reduction by NH₃. Environmental Science & Technology, 54(14): 9132–9141

[41] Yao Y, Gui S, Yang J, Wei J, Zhang W, Li P, Xue F, Su J, Liu X. (2021). Cause analysis and countermeasure of blockage in urea pyrolysis denitration system of coal-fired power plant. IOP Conference Series. Earth and Environmental Science, 651(2): 022058

[42] Yu T, Hao T, Fan D, Wang J, Shen M, Li W. (2014). Recent NH₃-SCR mechanism research over Cu/SAPO-34 catalyst. Journal of Physical Chemistry C, 118(13): 6565–6575

[43] Yuan B, Zhan G, Chen Z, Li Y, Wang L, You C, Li J. (2022). Intrinsic insight of energy-efficiency optimization for CO₂ capture by amine-based solvent: effect of mass transfer and solvent regeneration. International Journal of Greenhouse Gas Control, 118: 103673

[44] Zhang C, Sun C, Wu M, Lu K. (2019). Optimisation design of SCR mixer for improving deposit performance at low temperatures. Fuel, 237: 465–474

[45] Zhang N, He H, Wang D, Li Y. (2020). Challenges and opportunities for manganese oxides in low-temperature selective catalytic reduction of NO_x with NH₃:H₂O resistance ability. Journal of Solid State Chemistry, 289: 121464

[46] Zhang Q, Huang Y, Peng S, Huang T, Cao J J, Ho W, Lee S. (2018a). Synthesis of SrFe_xTi_1−xO₃-δ nanocubes with tunable oxygen vacancies for selective and efficient photocatalytic NO oxidation. Applied Catalysis B: Environmental, 239: 1–9

[47] Zhang X, Hong J, Liu H, Luo X, Olson W, Tontiwachwuthikul P, Liang Z. (2018b). SO₄²⁻/ZrO₂ supported on γ-Al₂O₃ as a catalyst for CO₂ desorption from CO₂-loaded monoethanolamine solutions. AIChE Journal. American Institute of Chemical Engineers, 64(11): 3988–4001

[48] Zhang X, Xuan Y, Wang B, Gao C, Niu S, Zhao G, Wang D, Li J, Lu C, Crittenden J C. (2022). Precise regulation of acid pretreatment for red mud SCR catalyst: targeting on optimizing the acidity and reducibility. Frontiers of Environmental Science & Engineering, 16(7): 88

[49] Zinchenko V F. (2021). Solid-phase complex compounds and composites of metal oxides, fluorides, and chalcogenides as materials for interference coatings: a review. Theoretical and Experimental Chemistry, 57(4): 262–271

Acknowledgements

The present study is supported by the Science and Technology Projects of China Huaneng Group Co., Ltd. (No. HNKJ21-H15), the National Natural Science Foundation of China (No. 22106084), and the Special Projects of China Postdoctoral Science Foundation (No. 2022T150350).

Author Contributions

Yuchen Li planned the project, carried out experiments and wrote the paper; Zhen Chen did the DFT calculation section and carried out experiments; Xiangyu Zhang, Kun Yang, Lidong Wang and Junhua Li analyzed data and reviewed the article. All the authors participated in discussion of the research.

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11783-023-1658-4 and is accessible for authorized users.

RIGHTS & PERMISSIONS

2023 Higher Education Press