Next Article in Journal
Microbial Spore-Based Biocatalysts: Properties, Applications and New Trends
Previous Article in Journal
Enzymes as Catalysts in Industrial Biocatalysis: Advances in Engineering, Applications, and Sustainable Integration
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Ternary SiO2@CuO/g-C3N4 Nanoparticles for Solar-Driven Photoelectrocatalytic CO2-to-Fuel Conversion

Suzhou Key Laboratory of Advanced Sustainable Materials and Technologies, Division of Natural and Applied Sciences, Duke Kunshan University, Kunshan 215316, China
*
Author to whom correspondence should be addressed.
Catalysts 2025, 15(9), 892; https://doi.org/10.3390/catal15090892
Submission received: 31 July 2025 / Revised: 19 August 2025 / Accepted: 25 August 2025 / Published: 17 September 2025

Abstract

Electrocatalytic CO2 reduction driven by renewable electricity offers a sustainable approach to producing valuable chemicals, though it is often hindered by low activity and selectivity. CuO, an important transition metal oxide, exhibits unique advantages in photoelectrocatalysis due to its high intrinsic catalytic activity and ability to serve as an active site for CO2 reduction. SiO2, a widely used substrate, facilitates Cu loading and increases the specific surface area of the catalyst. Meanwhile, g-C3N4 provides excellent visible-light responsiveness and efficient charge carrier mobility. Together, CuO, SiO2, and g-C3N4 are earth-abundant, low-cost, and chemically stable, making them ideal for solar-to-fuel applications. Here, a novel ternary heterojunction photocatalyst was constructed using SiO2, CuO, and g-C3N4. The heterostructure significantly improves light-harvesting efficiency, promotes efficient charge separation and transport, and simultaneously mitigates photogenerated carrier recombination and catalyst corrosion. The resulting SiO2@CuO/g-C3N4 catalyst demonstrates outstanding CO2 conversion performance, achieving a CO yield of 17 mmolg−1h−1 at 1.2 VRHE with nearly 100% selectivity. Moreover, this work systematically investigates the electrocatalytic CO2 reduction reaction (CO2RR) mechanism on Cu-based catalysts, offering insights into the formation of high-value multicarbon products and highlighting the potential of rational heterojunction design in enhancing solar-driven fuel production efficiency.

1. Introduction

The research and development of green carbon dioxide conversion technologies were considered critically important for addressing global climate change, ensuring energy security, and promoting sustainable development under the dual carbon goals. Since the Industrial Revolution, atmospheric CO2 concentrations have steadily increased, intensifying the greenhouse effect and contributing to global warming. As a result, CO2 conversion was viewed as a key strategy for advancing “negative carbon technologies.” Breakthroughs in areas such as catalyst design, electrochemical reduction, and photocatalysis had significantly improved the efficiency and cost-effectiveness of CO2 conversion [1,2,3]. “The catalytic reduction of CO2 converts gaseous into valuable fuels and chemical feedstocks, simultaneously mitigating greenhouse gas emissions and enabling sustainable carbon resource cycling.” [1,4]. However, the high stability of CO2 molecules (with a bond energy of 750 kJ/mol) necessitates significant activation energy. Although electrocatalysis requires significant electrical energy, photocatalysis faces limitations such as low efficiency (generally below 10%), insufficient selectivity, expensive catalysts, and difficulties in selectively producing high-value chemicals, making large-scale implementation challenging [5]. Therefore, by leveraging multi-disciplinary collaborative innovation, developing highly efficient catalysts, coupling light-electricity multi-energy drives, reducing energy consumption and breaking through thermodynamic limitations, the unity of environmental and economic benefits can be achieved [6].
Photocatalytic CO2 reduction technology utilizes solar energy-driven catalysis to convert carbon dioxide into green fuels such as organic matter and methane, a method that mimics the natural process of photosynthesis. However, the efficiency of photocatalytic reduction is relatively low and challenging on catalysts [6,7]. Therefore, the development of efficient catalysts and novel catalytic reduction technologies is essential to improve conversion efficiency and product selectivity. Electrochemical reduction can be carried out at ambient temperature and pressure, and higher energy utilization efficiency can be achieved compared to other chemical conversion pathways [8,9]. Electrocatalytic (EC) reduction of CO2 is a process in which an external electric field is used as the main energy source to drive a redox reaction at the electrode. It should be noted, however, that applying excessively high voltages may induce competing hydrogen evolution, thereby reducing the Faradaic efficiency of CO2 electroreduction into fuels [10,11]. Given the practical limitations of standalone photocatalytic and electrocatalytic CO2 reduction technologies, researchers have developed an innovative approach by integrating these methods into photoelectrocatalytic (PEC) systems, thereby enhancing both efficiency and overall performance. PEC is a method that utilizes sunlight to drive chemical reactions and is particularly suitable for CO2 reduction. In PEC, light energy is used to excite carriers (electrons and holes) in semiconductor materials, which then participate in redox reactions. PEC CO2 reduction can realize the rapid transfer of electrons at a low overpotential to reduce CO2 on the photocathode, which greatly improves the reduction efficiency and ultimately realizes low-energy CO2 reduction [12,13]. It has been shown that excellent PEC CO2 reduction systems can not only utilize light energy to excite and generate carriers under light conditions, effectively reducing the energy input and energy consumption of external electrons but also utilize electrical energy to accelerate the separation and transfer of electrons-holes, thus facilitating the CO2 reduction reaction [14,15].
In PEC CO2 reduction systems, the photoelectrode material must exhibit an optimal band gap to generate photoexcited charge carriers for CO2 reduction, while also demonstrating stability and high selectivity. During the PEC process, when the photoelectrode is subjected to light and an applied voltage, its electrons transition from the valence band (VB) to the conduction band (CB), generating excited state electrons [16,17]. The electrons and holes produced by light can participate in a series of chemical reactions on the surface of a catalyst or at the electrode/electrolyte interface. In a PEC CO2 reduction system, photogenerated electrons migrate to the adsorbed CO2 molecules on the catalyst surface, driving their conversion into organic products. Constructing heterojunctions in photocathodes is an effective way to improve catalytic efficiency and selectivity [15,18,19]. This typically involves integrating multiple semiconductors or catalytic active sites to promote the separation and efficient utilization of photogenerated charge carriers [8,19].
Halmann conducted pioneering research on PEC CO2 conversion [20]. Since then, researchers have made significant and exciting advancements in this field. Xiong’s group developed a facile method for cladding MOF materials on the surface of Cu2O cathodes, i.e., a photocathode with a columnar Cu3(BTC)2 MOF structure on the surface of a Cu2O film. Christiane’s group investigated the growth of Ti-O-Cu nanotubes grown on a bimetallic alloy (Ti-x-Cu; x = 0.5, 5.5, and 10 at. %) for the PEC selectivity of the CO2 reduction reaction [17,21]. Cu-based photoelectrodes exhibit great advantages in PEC CO2 reduction. First, they have excellent light absorption capacity and can effectively utilize visible light to catalyze the reduction of carbon dioxide [18,19]. Secondly, some copper-based catalysts exhibit excellent electron transfer characteristics, which contribute to effective light absorption and electron transfer in PEC, thereby enhancing the efficiency of CO2 reduction [1,20]. Finally, the active sites on the surface of Cu-based catalysts can be controlled through various methods to enhance catalytic performance and product selectivity [22]. In recent years, copper-based catalysts have developed rapidly, evolving from the initial pure copper oxide (CuO, Cu2O) to the current multi-component copper oxide and copper sulfide, as well as copper-based composite materials. As a P-type semiconductor, Cu2O can form various types of heterojunctions with semiconductors with appropriate band positions, including p-n junctions, P-N-P junctions, and Z-scheme heterojunctions, effectively suppressing the recombination of electrons and holes on the surface of photoelectrodes [23,24,25]. They play a crucial role in promoting the development of the PEC CO2 reduction field.
SiO2 is highly advantageous due to its earth abundance, non-toxicity, facile processing, and low production costs [5,6,7]. Numerous studies have explored SiO2 as a functional additive to Cu-based catalysts, demonstrating its potential to enhance performance in photoelectrochemical CO2 reduction reactions [8]. Zhang et al. found that the addition of SiO2, TiO2 or SiO2-TiO2 not only enhanced the surface area of metallic copper but also changed the adsorption performance of the catalyst [9]. Zhang et al. constructed the Cu0-Cu+-NH2 composite reaction interface by taking advantage of the excellent properties of SiO2: Firstly, it can uniformly coat inorganic nanoparticles; Second, it can be combined with silane coupling agents to introduce organic functional groups for effective electro-reduction of CO2 to C2+ products [10]. Jia et al. found that the addition of SiO2 significantly increased the specific surface area of BET and copper [11]. Among various semiconductor photocatalysts, graphitic carbon nitride (g-C3N4) exhibits distinctive advantages including remarkable chemical stability, an ideal band gap for visible-light absorption, non-toxicity, and low-cost fabrication. These superior properties make it a highly promising candidate for photocatalytic CO2 reduction applications. Wang et al. explored the photocatalytic hydrogen evolution reaction of g-C3N4 under visible light for the first time [12]. Dong and Zhang were the first to use g-C3N4 to catalyze the reduction of CO2 to CO under visible-light excitation in the presence of water vapor, demonstrating the potential of g-C3N4 for CO2 reduction [13].
Here, SiO2, CuO, and g-C3N4 were selected to construct a ternary heterojunction for photoelectrocatalytic CO2 reduction. The efficient conversion of CO2 to CO was successfully achieved. The SiO2 support enhances both Cu loading and the catalyst’s specific surface area. Moreover, CuO exhibits excellent PEC performance, serving as an active site for CO2 reduction. Meanwhile, g-C3N4, with its strong visible-light responsiveness and carrier transport capacity, acted as a photoresponsive material to effectively absorb light energy and facilitate charge transport. The integration of these three compounds into a ternary heterojunction enhanced light absorption, promoted efficient charge separation and transport, suppressed photogenerated carrier recombination, and improved catalyst stability. A provisional finding explored the photoelectrocatalytic reaction path on the SiO2@CuO/g-C3N4 catalyst, and this work provides prospects for the interface design of ternary heterojunctions for efficient CO2 conversion.

2. Discussion

2.1. Elemental Composition and Surface Chemistry

The elemental composition and crystal structure of the SiO2@CuO/g-C3N4 electrode were analyzed by XRD, Raman and XPS characterization. The structure, phase and purity of SiO2@CuO/g-C3N4 were investigated by X-ray diffraction analysis. Figure 1a–c indicates that the silica (SiO2) nanoparticles are amorphous with a wide peak around 2θ ≈ 24.5 which agreement with other works. The XRD pattern showed the formation of the pure and polycrystalline phase of CuO nanoparticles with a monoclinic structure with (002), (111), (202), (113), and (311) orientations [5]. The characteristic peaks of SiO2@CuO/g-C3N4 samples prepared with different CuO contents were basically the same, which proved that the phase structure of the metal did not change during the synthesis of the bimetallic catalyst. These results show the successful preparation of SiO2@CuO/g-C3N4. The Raman spectrum of g-C3N4 shows a G band at around 1614 cm−1 and a D band at around 1356 cm−1 (Figure 1d). D peak was the vibration mode of phonons, which reflects the defect and disorder degree of carbon nanotubes. G and G′ peaks reflect the degree of order in the arrangement of carbon atoms. Besides the D and G bands, the additional Raman characteristic spectra of carbon at ~2700 cm−1, known as 2D (or G′) band, was also weakly found in both samples. The intensity of the 2D band in both samples is very low and a highly broadened 2D band was also observed. The 2D band is Raman active for crystalline graphitic materials. Raman spectra of CuO exhibits a peak at 282 cm−1 which is characteristic of Ag mode.
The XPS Cu 2p spectrum in Figure 2 shows the peaks at 934.1 and 954.2 eV which are assigned to Cu 2p3/2 and Cu 2p1/2. The appearance of shakeup satellites with peaks at ∼942 eV and ∼962 eV is also characteristic for the presence of Cu2+ and is unique for the CuIIO structure. Furthermore, the structure of CuO is also confirmed by the Auger peak analysis with the characteristic Cu at 917.1 eV. The XPS O 1s spectrum shows the presence of different peaks with binding energy (BE) of 529.7, 532.5, 533.2, and 534.3 eV. The peak at 529.7 eV is assigned to the bulk lattice oxygen of CuO, as established in the literature. Hence, with bulk lattice oxygen as the reference, the 3 shifts observed in the O 1s spectra are +1.7, +3.5, and +4.9 eV. These XPS shifts (and corresponding binging energy) are widely observed in the literature for CuO O 1s spectra. However, the assignment of these BE to surface moieties (and their adsorption configurations) is either absent, inconsistent or disputed. For instance, +1.7 eV can correspond to the oxygen adsorbed on the surface of CuO in molecular or dissociated form, +3.5 eV can correspond to the hydroxyl groups or H2O adsorbed on the surface of CuO, and +4.9 eV can correspond to the hydroxyl groups or H2O adsorbed on the surface of CuO [26].
The morphology and microstructure of the catalysts were observed by SEM and TEM. Figure 3 shows the SEM images of SCCN-10(SiO2@CuO (10)/g-C3N4) and SCCN-15 (SiO2@CuO (15)/g-C3N4). These images show that the prepared silica nanoparticles are spherical, regular, and dispersed with distinct boundaries. The average diameter of silica (SiO2) nanoparticles was estimated to be about 15 nm. The resulting nanoparticles also have a uniform distribution. The FE-SEM image (Figure 3a,b) of SiO2/CuO nanoparticles show that the SiO2 spheres are completely covered with copper oxide nanoparticles and the distribution of nanoparticles is almost uniform, and the average size of these nanoparticles is estimated to be circa. 20 nm. At the same time, these uniformly distributed SiO2/CuO nanoparticles are covered with layers of nitrogen carbide. The TEM images reveal the size and shape of the nanoparticles with an accuracy of about a tenth of a nanometer, depending on the type of material and device used. Figure 3e–g shows the TEM images of the SiO2@CuO (10 wt%)/g-C3N4. The figure shows two sets of clear lattice fringes, with the corresponding crystal plane spacings of 0.27 nm and 0.275 nm, respectively, both marked as (110) crystal planes. This image shows high-resolution lattice fringes, indicating that the sample has good crystallinity [18].

2.2. Optical Properties

The effects of CuO content and g-C3N4 introduction on the photoresponse of the catalyst were investigated by photophysical characterization. The UV/Vis diffuse reflectance spectroscopy (DRS) shows SiO2@CuO catalysts (Figure 4a) display greatly enhanced absorption of visible and near-infrared light with the increase in CuO content. Compared to the SiO2@CuO catalysts, the UV-visible spectrum of SiO2@CuO/g-C3N4 (Figure 4b) shows complete visible spectral absorption, possibly due to the darker color of the catalyst sample and the introduction of g-C3N4. The UV-VIS absorption spectrum of the sample was tested after grinding, and it was found that the absorption range of visible light increased with the increase in Cu doping.

2.3. Electrochemical Properties

Figure 5 depicts the electrochemical impedance spectroscopy (EIS) and transient photocurrent response (TPR) of the photocatalyst. Electrochemical impedance spectroscopy (EIS) was used to reveal the transfer behavior of photocarriers. The arc radius of SCCN-10 heterostructure is significantly smaller than that of SCCN-15, indicating that the charge transfer rate of SCCN-10 catalyst is accelerated. In addition, the TPR intensity of SiO2@CuO/g-C3N4 ternary heterojunction catalyst is SCCN-20 > SCCN-10 > SCCN-15, indicating that SCCN-10 catalyst improves the electron transport efficiency.
During the photoelectrocatalytic reduction of carbon dioxide, the SiO2@CuO/g-C3N4 composite material has significant advantages over the individual CuO/g-C3N4 or SiO2/CuO. The binary system of CuO/g-C3N4, where the catalyst is directly anchored on the carrier, leads to agglomeration [27]. Therefore, the direct use of CuO2 is not pursued, and the covering of a layer of SiO2 on another layer of g-CN (CuO/g-C3N4) without the support of SiO2 is not adopted. Amorphous SiO2 typically possesses a rich mesoporous structure, which can significantly increase the specific surface area of the material, providing more anchoring sites for the dispersion of CuO and exposing more catalytic active centers [28]. Instead, a layer of graphitic carbon nitride is chosen to be added to form a ternary SiO2@CuO/g-C3N4 composite material, because graphite carbon nitride is a good electron transfer material and is used to form a complex of photosensitizer and photocatalyst to achieve the electroreduction of carbon dioxide [29]. The SiO2@CuO and SiO2@CuO/g-C3N4 samples were characterized by ultraviolet-visible diffuse reflectance spectroscopy (UV-Vis DRS), and the influence of the introduction of g-C3N4 on the photocatalytic response characteristics of the catalyst was studied. The experimental results show that compared with SiO2@CuO, the SiO2@CuO/g-C3N4 sample (Figure 4b) has a wider visible light absorption range, which may be due to the expansion of the light response range caused by the introduction of g-C3N4. SiO2@CuO/g-C3N4 combines the structural advantages of SiO2 and the semiconductor properties of g-C3N4 (wide spectral response, efficient charge separation) [30]. Therefore, it has more advantages in photocatalytic carbon dioxide reduction compared to the individual CuO/g-C3N4 or SiO2/CuO materials, highlighting its strong potential for efficiently converting solar energy into chemical fuel.

2.4. Photoelectrocatalytic Performanc for CO2RR

2.4.1. PEC Performance and Faraday Efficiency of the Catalysts

To study the influence of the photoelectric effect on the catalytic performance of the samples, the photoelectric reduction of CO2 was evaluated in the electrochemical analysis workstation (CHI 760) under the dual drive of simulated sunlight and electrical energy. Figure 6a shows the CO2 photoreduction activities of various catalysts under photoelectric dual drive conditions. It can be clearly seen that all the samples have a high selectivity for CO2-to-CO and only produce a small amount of C2H4. SCCN-10 exhibited a relatively high CO yield, while SCCN-20 showed a higher C2H4 yield. This might be because the Cu content comprehensively affects the activity and selectivity of CO2RR by regulating the properties of active sites, electronic structure, competitive reactions and mass transfer processes [31,32,33]. Optimizing the dispersion degree, valence state and interaction with the carrier of Cu is the key. An increase in Cu content may provide more active sites, but it is not a linear relationship. When the Cu content is low, the active sites are insufficient, limiting the reaction rate. When it is too high, it may lead to the agglomeration of Cu particles and reduce the effective surface area. An appropriate amount of Cu (SCCN-10) can optimize the adsorption of *COOH intermediates and promote the generation of CO. Also, large-particle Cu may tend to compete for hydrogen evolution reaction (HER), reducing the selectivity of CO.

2.4.2. Comparison of PEC Performance at Different Potentials

To reveal the relationship between the activity of the catalyst and the overpotential, the overpotential (η) is the difference between the actual potential that drives the reaction and the thermodynamic equilibrium potential (for example, the equilibrium potential of CO2/CO is −0.11 V vs. RHE). The minimum overpotential required for the catalyst to achieve a high current density (activity) and measure its energy efficiency. The electrocatalytic activity of the catalyst was evaluated, respectively, under different overpotentials. Figure 7 showed photoelectrocatalytic performance at three different potentials. It can be seen from Figure 7a that the CO yield of SCCN−10 is the highest at −1.2 VRHE, reaching 17 mmol g−1 h−1. It shows better performance advantages compared with the reported literature (Table 1). The ethylene yields gradually increased with the increase in potential and reached 4.3 mmol g−1 h−1under the condition of −1.4 VRHE. The Faraday efficiency graph in Figure 7b shows that CO exhibits the highest Faraday efficiency at −1.0 V, approaching 17%. At −1.2 VRHE, the highest FEC2H4 = 12% was exhibited.

2.4.3. Comparison of Photoelectrocatalytic Performance and Stability Test

In the photoelectrocatalytic CO2 reduction reaction (PEC CO2RR), the role of light is far more than just providing energy. It profoundly affects the reaction pathway, catalytic activity and product selectivity by influencing the generation and separation of photogenerated carriers and the adsorption of reaction intermediates [26,34]. Taking the photocatalyst SCCN-10 as the optimal catalyst, a comparative experiment on electrocatalytic and photocatalytic performance was conducted, as shown in Figure 7e,f. It can be clearly seen that under photoelectrocatalysis, the yields of CO and C2H4 have significantly increased, as the introduction of light further promotes the CO2 reduction reaction. Taking the catalyst SCCN-10 as the optimal catalyst, the stability of the catalyst was tested, and the results are shown in Figure 7f. After the photoelectrocatalytic CO2 reduction reaction for 16 h, the catalyst still maintained relatively stable catalytic activity. The production rates of both products over the SCCN-10 catalyst exhibit minor fluctuations. Overall, the CO production rate increases, while the C2H4 production rate shows a slight decrease. This is beneficial in terms of the selectivity of CO. The KHCO3 electrolyte may affect the reaction environment pH due to the co26nsumption of HCO3 and the migration of K+. Such changes may influence the adsorption strength of intermediates (such as COOH and CO), thereby altering the selectivity of CO products. In the reported literature, the valence state of Cu and the physical or chemical changes in the catalyst carrier affect the product selectivity [35,36]. At the same time, during the long-term stability reduction reaction process, catalytic performance also typically shows stable fluctuations in both directions [37,38]. Overall, during the 16 h reduction reaction process, the CO production rate increases, while the C2H4 production rate shows a slight decrease, which is beneficial in terms of the selectivity of CO.
Table 1. CO2RR properties of Cu-based electrocatalysts in different electrolytes.
Table 1. CO2RR properties of Cu-based electrocatalysts in different electrolytes.
CatalystsConditionsReactorCOC2H4Ref.
Cu2O/Zn-Cr-LDHs200 W Hg-Xe lampH-type Cell1.3125 μmol/g/h [1]
Cu2O/Cu/Cu3V2O7(OH)2·2H2O300 W Xe lamp (λ > 400 nm)H-type cell6.97 μmol/g/h [2]
3D porous Cu2O300 W Xe lamp (λ > 420 nm)H-type cell26.8 μmol/g/h0.66 μmol/g/h[3]
BiVO4/C/Cu2O nanowires300 W Xe lamp (λ > 420 nm)H-type cell3.01 μmol/g/h [4]
g-C3N4/Cu2O Flow cell8.182 μmol/g/h [5]
FeCuP−1.6 VFlow cell1.44 μmol/h [11]
Co-ZIF-9/g-C3N4NAFlow cell495 μmol/g/h [13]
NH2/MOF−1.2 VFlow cell1.7 mmol/g/h [14]
Re@NH2-MOF−1.2 VFlow cellCO = 14.85 mmol/g/h [14]
Cu2O/Sn/PTFE−1.2 VFlow cellCO = 68.31 μmol/h/cm2 [15]
Au-Cu/SrTiO3/TiO2NAFlow cell3.7mmol/gcat/h [16]
Ni/g-C3N4300 W Xe lampFlow cell19.85 μmol/g/h [17]
α-Fe2O3/g-C3N4300 W Xe lampFlow cell27.2 μmol/g/h [18]
Cu/ZnO/g-C3N4400 W Hg lampH-type cell65.1 μmol/g/h [39]
Ru/Zn-g-C3N4-1/20300 W Xe lampH-type cell288.42 μmol/g/h [40]
Pt/TiO2/g-C3N4300 W Xe lampH-type cell3.8 μmol/g/h [41]
SiO2@CuO (10 wt%)/g-C3N4300 W, −1.2 VRHE, 2 h, 0.1 M KHCO3H-type cell17 mmol/g/h2305.1 μmol/g/hThis work

2.5. DFT Calculations

To further explore the photoelectrocatalysis reduction reaction path of CO2 on SCCN-10 catalyst, the DFT method was used to calculate the energy required to convert CO2 to *CO. CO2 forms the activation energy of *COOH (0.532 eV) on SCCN-10, and *COOH intermediate reacts with a proton to release a water molecule and generate CO. Based on the DFT, a probable CO2 conversion pathway is proposed: * + CO2 → *CO2 + H+ → *COOH + H+ →*CO + H2O → CO. In general, CO2 can be reduced first to CO through the *COOH pathway, and the adsorbed CO is a common intermediate of C2+ products in CO2RR [42]. The DFT results show that the hydrogenation of *CO to *CHCO plays an important role in the enhancement of C2+ products. In this case, the possible reaction pathways in the C-C coupling step are as follows: *CO + CO → *2CO → *OCCO + H+ → *HOCCO + H+ → *CCO + H+ → *CHCO + H+ → *CHCHO + H+ → *CH2CHO + H+ → *CH2CHOH + H+ → *CH2CH2OH + H+ → * + C2H4 + H2O. Correspondingly, the Gibbs free energy change (ΔG) for each step is calculated, as shown in Figure 8. For SCCN-10, the conversion of *HOCCO to *CCO is identified as the rate-limiting step.

3. Materials and Methods

3.1. Materials

Tetraethoxysilane (TEOS), Ethanol (C2H6O), Copper (II) Chloride Dihydrate (CuCl2·2H2O) and Ammonium hydroxide (NH3·H2O) was purchased from Shanghai Titan Technology Co., Ltd. (Shanghai, China). Melamine was provided by Beijing Aladdin Future Technology Co., Ltd. (Beijing, China). Deionized water was used in the experiments. potassium bicarbonate (KHCO3) was provided by Titan Co., Ltd. (Shanghai, China). All the chemical substances used in this study were of analytical grade and were not further purified. The Nafion was purchased from Titan Co., Ltd. (Shanghai, China).

3.2. Synthesis of the SiO2@Cu and SiO2@CuO/g-C3N4 Catalyst and Working Electrodes

Synthesis of SiO2@Cu. 300 mL of ethanol and 56 mL of water were placed in a 500 mL three-necked flask, 7 mL of ammonia water was added and stirred at 30 °C for 1 h. Subsequently, 12 mL of tetraethyl orthosilicate (TEOS) was added and continued to react for 20 h. A white colloidal solution was formed. Then 5 wt.% Cu was added to the above solution mixture, the solution changes from white to dark blue. At the same time, an additional 10 mL of ammonium hydroxide (with a concentration of 25%) was added was heated to 85 °C and stirred for 6 h. Once the reaction ended, it was washed several times with water and ethanol, respectively, and then dried at 60 °C overnight. The Cu content was changed to 10 wt.%, 15 wt.%, and 20 wt%, respectively, to obtain catalysts SiO2@Cu (x wt.%) with different Cu contents.
Synthesis of SiO2@CuO/g-C3N4. 0.5 g of SiO2@Cu and 2.5 g of melamine powder were thoroughly mixed and ground using a pestle and mortar. The powder mixture was subsequently heated in a muffle furnace at a heating rate of 5 °C/min up to 550 °C and maintained for 3 h to obtain SiO2@CuO/g-C3N4.
Synthesis of working electrodes. The electrochemical experiments were performed in a three-electrode cell using a potentiostat (CHI 760). A reversible hydrogen electrode (RHE) immersed in the working electrolyte and a graphite rod were used as reference and counter electrodes, respectively. The working electrodes were prepared as follows: 4 mg of the electrocatalyst was suspended and ultrasonic in 1 mL of a 0.2 wt.% Nafion and 20 wt.% isopropanol aqueous solution. 300 μL of the 4 mg mL−1 suspension was dropped-cast onto the carbon paper.

3.3. Catalysts Characterization

X-ray powder diffraction (XRD) spectra were performed on benchtop Aeris equipped with Cu Kα radiation with the scanned range of 10–80°. The morphology was characterized by Scanning electron microscope (SEM) (Regulus 8100, JEOL Ltd., Tokyo, Japan) and High-Resolution Transmission Electron Microscope (HRTEM) (JEM-F200, JEOL Ltd., Tokyo, Japan) and Energy Dispersive X-Ray Spectroscopy (EDX) (JEM-F200, Japan) were conducted on Fei G2 F30 to examine morphologies and elemental compositions. The visible absorption range and band gap were recorded by UV-vis diffuse reflectance spectroscopy (DRS) (Shimadzu UV3600, Shimadzu Corporation, Tokyo, Japan). Raman measurements were carried out using a Horiba LabRAM HR Evolution Raman microscope (LabRAM HR Evolution, Horiba Ltd., Paris, France). A 532 nm laser was used, and signals were recorded using a 20 s integration and by averaging two scans. X-ray photoelectron spectroscopy (XPS) was recorded on Thermo Fisher ESCALAB XI+ (Thermo Fisher, Waltham, MA, USA). UV-vis diffuse reflectance spectroscopy (UV-DRS) spectra were tested on Shimadzu UV-2600i. Transient photoluminescence (PL) spectra were obtained at room temperature using a FLS-1000 spectrometer (FLS1000, Edinburgh Instruments, Edinburgh, UK). Steady PL spectra were determined with an RF-5301PC Spectro fluorophotometer (Shimadzu RF-5301PC, Shimadzu Corporation, Tokyo, Japan). Inductively coupled plasma optical emission spectrometry (ICP-MS) measurements were carried out using Agilent 720 (Tokyo, Japan).

3.4. Electrochemical Test

Photoelectrochemical measurements of the samples were analyzed with an electrochemical workstation (CHI 760) using a conventional three-electrode system The Pt electrode and Ag/AgCl electrode (saturated with KCl) were used as the counter electrode and reference electrode, respectively. The working electrode was prepared on 10 × 15 mm conductive carbon paper (TGP-H-060). The method was as follows: 4 mg of the sample was dispersed in 1mL of a solution containing ethanol, water and Nafion, and then ultrasonically dropped onto the conductive carbon paper after 30 min. The electrochemical characterization test of instantaneous photoelectrocatalytic CO2 reduction performance was carried out in 0.1 M potassium bicarbonate electrolyte.

3.5. Photoelectrocatalytic CO2 Reduction

The CO2RR testing was carried out in a gastight H-type electrolytic cell separated by a Nafion 117 membrane. In both chambers, 0.1 M KHCO3 were used as cathode and anode electrolyte. A three-electrode system, in which SiO2@CuO/g-C3N4 used as work electrode, Ag/AgCl (3 M KCl) and Pt (1 cm × 2 cm) plate as reference and counter electrode with an electrochemical station (CHI 760) was adopted to electrochemical measurements and a circulating water device to maintain a constant temperature of 25 °C. CO2 (99.999%) was passed into the cathode at a rate of 20 mL/min for 30 min, followed by constant potential photoelectrochemical CO2 reduction. A 300 W xenon lamp (λ ≥ 420 nm) with 570 mW/cm2 was used for the PEC CO2 reduction tests. The gaseous products were detected by gas chromatography (Fuli GC7970, Ar as a carrier gas) equipped with a flame ionization detector and a column (TDX-01). The column temperature was maintained at 180 °C and the detector temperature at 200 °C. In this study, the potentials were converted by the following equation:
ERHE = EAg/AgCl + 0.0591 × pH + 0.199 V
V % of gaseous products can be obtained from the GC peak areas and calibration curves for the TCD detector. Since the flow rate of the outlet was monitored to be constant, the moles of gaseous products can be calculated. The Faradaic efficiency of gaseous product is
FE = models of product/Q/nF × 100%
(Q: charge (C); F: Faradaic constant (96,485 C/mol); n: the number of electrons required to generate the product)

3.6. DFT Calculations Method

The DFT implemented in the Vienna Ab initio Simulation Package (VASP) is used in all calculations [14]. The Perdew–Burke–Ernzerhof generalized gradient approximation (GGA-PBE) is utilized to describe the exchange-correlation potential [15]. The interaction between the ionic core and valence electrons is treated using the projection-enhanced wave (PAW) method. The plane wave cutoff energy is fixed at 500 eV and relaxes the given structural model until the Hermann–Feynman force is less than −0.02 eV/Å and the energy change is less than 10−5 eV. Artificial interactions between the periodic images were avoided by adding a 20 Å vacuum layer perpendicular to the sheet in the heterostructure. And the dispersive interactions were corrected by the DFT-D3 method [16]. The Gibbs free energy (G) is computed by correcting the DFT energy (E) with the following formula:
G = E + Z P E + Δ H t T Δ S
where T is thermodynamic temperature (set to 298.15 K), ZPE is zero-point energy, Δ H t is enthalpy change and T Δ S is the entropy correction.

4. Conclusions

In conclusion, A unique ternary heterojunction electrocatalyst for photoelectrocatalytic CO2 reduction, composed of SiO2, CuO, and g-C3N4, was developed. SiO2 enhanced Cu dispersion and increased the catalyst’s specific surface area; CuO served as an active site with excellent photoelectrocatalytic performance; and g-C3N4, with strong visible-light responsiveness and carrier mobility, acted as a photoresponsive component to facilitate light absorption and charge transport. The synergistic integration of these three earth-abundant and stable materials enabled efficient CO2 conversion, achieving a CO yield of 17 mmolg−1h−1 at 1.2 VRHE with nearly 100% selectivity—surpassing many reported systems. In addition to demonstrating high performance, this study provided mechanistic insights into CO2 electroreduction over Cu-based catalysts, including the formation pathways of C2+products. This work offers a promising strategy for the rational design of advanced ternary heterojunctions and broadens the prospects for efficient, scalable photoelectrocatalysis and solar-to-fuel technologies.

Author Contributions

Synthesis, characterize, and testing of the photo electrocatalysts, and wrote the original draft, Z.L.; Conceptualization, supervision, funding acquisition, and contribution to original draft writing, review, and editing, K.L.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

The research results of this article are sponsored by the Kunshan Municipal Government research funding. The authors would also like to thank Zi-Yian Lim, Huiling Wang and Ye Wang for their support of this work.

Conflicts of Interest

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

References

  1. Kumaravel, V.; Bartlett, J.; Pillai, S.C. Photoelectrochemical Conversion of Carbon Dioxide (CO2) into Fuels and Value-Added Products. ACS Energy Lett. 2020, 5, 486–519. [Google Scholar] [CrossRef]
  2. Zhang, Y.; Pan, D.; Tao, Y.; Shang, H.; Zhang, D.; Li, G.; Li, H. Photoelectrocatalytic Reduction of CO2 to Syngas via SnOx-Enhanced Cu2O Nanowires Photocathodes. Funct. Mater. 2021, 32, 2109600. [Google Scholar] [CrossRef]
  3. Yu, H.; Cohen, H.; Neumann, R. Photoelectrochemical Reduction of Carbon Dioxide with a Copper Graphitic Carbon Nitride Photocathode. Chem. Eur. J. 2021, 27, 13513–13517. [Google Scholar] [CrossRef]
  4. Dutta, N.; Bagchi, D.; Chawla, G.; Peter, S.C. A Guideline to Determine Faradaic Efficiency in Electrochemical CO2 Reduction. ACS Energy Lett. 2024, 9, 323–328. [Google Scholar] [CrossRef]
  5. Guo, C.; Guo, Y.; Shi, Y.; Lan, X.; Wang, Y.; Yu, Y.; Zhang, B. Electrocatalytic Reduction of CO2 to Ethanol at Close to Theoretical Potential via Engineering Abundant Electron-Donating Cuδ+ Species. Angew. Chem. Int. Ed. 2022, 134, e202205909. [Google Scholar] [CrossRef]
  6. Wang, W.; Zhang, W.; Deng, C.; Sheng, H.; Zhao, J. Accelerated Photocatalytic Carbon Dioxide Reduction and Water Oxidation under Spatial Synergy. Angew. Chem. Int. Ed. 2024, 136, e202317969. [Google Scholar] [CrossRef]
  7. Wang, K.; Liu, Y.; Wang, Q.; Zhang, Y.; Yang, X.; Chen, L.; Liu, M.; Qiu, X.; Li, J.; Li, W. Asymmetric Cu-N sites on copper oxide photocathode for photoelectrochemical CO2 reduction towards C2 products. App. Catal. B Environ. 2022, 316, 121616. [Google Scholar] [CrossRef]
  8. Chen, Y.; Xiang, C.; Lin, M. Performance assessment of photoelectrochemical CO2 reduction photocathodes with patterned electrocatalysts: A multi-physical model-based approach. Energy Environ. Sci. 2024, 17, 3032–3041. [Google Scholar] [CrossRef]
  9. Abbas, T.; Yahya, H.S.M.; Amin, N.A.S. Insights and Progress on Photocatalytic and Photoelectrocatalytic Reactor Configurations and Materials for CO2 Reduction to Solar Fuels. Energy Fuels 2023, 37, 18330–18368. [Google Scholar] [CrossRef]
  10. Wang, Q.; Zhang, Y.; Liu, Y.; Wang, K.; Qiu, W.; Chen, L.; Li, J.; Li, W. Core–Shell In/Cu2O Nanowires Schottky Junction for Enhanced Photoelectrochemical CO2 Reduction under Visible Light. Ind. Eng. Chem. Res. 2022, 61, 16470–16478. [Google Scholar] [CrossRef]
  11. Liang, H.; Li, M.; Li, Z.; Xie, W.; Zhang, T.; Wang, Q. Photoelectrochemical CO2 reduction with copper-based photocathodes. J. CO2 Util. 2024, 79, 102639. [Google Scholar] [CrossRef]
  12. Merino-Garcia, I.; Castro, S.; Irabien, A.; Hernández, I.; Rodríguez, V.; Camarillo, R.; Rincón, J.; Albo, J. Efficient photoelectrochemical conversion of CO2 to ethylene and methanol using a Cu cathode and TiO2 nanoparticles synthesized in supercritical medium as photoanode. J. Environ. Chem. Eng. 2022, 10, 107441. [Google Scholar] [CrossRef]
  13. Guo, L.; Cao, J.; Zhang, J.; Hao, Y.; Bi, K. Photoelectrochemical CO2 reduction by Cu2O/Cu2S hybrid catalyst immobilized in TiO2 nanocavity arrays. J. Mater. Sci. 2019, 54, 10379–10388. [Google Scholar] [CrossRef]
  14. Jiao, Y.; Zheng, Y.; Chen, P.; Jaroniec, M.; Qiao, S.-Z. Molecular Scaffolding Strategy with Synergistic Active Centers to Facilitate Electrocatalytic CO2 Reduction to Hydrocarbon/Alcohol. J. Am. Chem. Soc. 2017, 139, 18093–18100. [Google Scholar] [CrossRef]
  15. Chen, P.; Zhang, Y.; Zhou, Y.; Dong, F. Photoelectrocatalytic carbon dioxide reduction: Fundamental, advances and challenges. Nano Mater. Sci. 2021, 3, 344–367. [Google Scholar] [CrossRef]
  16. Kecsenovity, E.; Endrődi, B.; Tóth, P.S.; Zou, Y.; Dryfe, R.A.W.; Rajeshwar, K.; Janáky, C. Enhanced Photoelectrochemical Performance of Cuprous Oxide/Graphene Nanohybrids. J. Am. Chem. Soc. 2017, 139, 6682–6692. [Google Scholar] [CrossRef] [PubMed]
  17. Deng, X.; Li, R.; Wu, S.; Wang, L.; Hu, J.; Ma, J.; Jiang, W.; Zhang, N.; Zheng, X.; Gao, C.; et al. Metal–Organic Framework Coating Enhances the Performance of Cu2O in Photoelectrochemical CO2 Reduction. J. Am. Chem. Soc. 2019, 141, 10924–10929. [Google Scholar] [CrossRef]
  18. Qadir, M.I.; Albo, J.; de Pedro, I.; Cieslar, M.; Hernández, I.; Brüner, P.; Grehl, T.; Castegnaro, M.V.; Morais, J.; Martins, P.R.; et al. Nanoarchitectonics of CuNi bimetallic nanoparticles in ionic liquids for LED-assisted synergistic CO2 photoreduction. Mol. Cat. 2022, 531, 112654. [Google Scholar] [CrossRef]
  19. Su, X.; Jiang, Z.; Zhou, J.; Liu, H.; Zhou, D.; Shang, H.; Ni, X.; Peng, Z.; Yang, F.; Chen, W.; et al. Complementary Operando Spectroscopy identification of in-situ generated metastable charge-asymmetry Cu2-CuN3 clusters for CO2 reduction to ethanol. Nat. Commun. 2022, 13, 1322. [Google Scholar] [CrossRef] [PubMed]
  20. Yu, J.; González-Cobos, J.; Dappozze, F.; Vernoux, P.; Caravaca, A.; Guillard, C. Basic comprehension and recent trends in photoelectrocatalytic systems. Green Chem. 2024, 26, 1682–1708. [Google Scholar] [CrossRef]
  21. Ma, L.; Guan, R.; Kang, W.; Sun, Z.; Li, H.; Li, Q.; Shen, Q.; Chen, C.; Liu, X.; Jia, H.; et al. Rational synthesis of two isostructural thiophene-containing metal-organic frameworks toward photocatalytic degradation of organic pollutants. J. Colloid Interface Sci. 2024, 660, 381–392. [Google Scholar] [CrossRef]
  22. Schreier, M.; Gao, P.; Mayer, M.T.; Luo, J.; Moehl, T.; Nazeeruddin, M.K.; Tilley, S.D.; Grätzel, M. Efficient and selective carbon dioxide reduction on low cost protected Cu2O photocathodes using a molecular catalyst. Energy Environ. Sci. 2015, 8, 855–861. [Google Scholar] [CrossRef]
  23. Jiang, Z.; Wan, W.; Li, H.; Yuan, S.; Zhao, H. A Hierarchical Z-Scheme α-Fe2O3/g-C3N4 Hybrid for Enhanced Photocatalytic CO2 Reduction. Adv. Mater. 2018, 30, 1706108. [Google Scholar] [CrossRef]
  24. Castro, S.; Albo, J.; Irabien, A. Continuous conversion of CO2 to alcohols in a TiO2 photoanode-driven photoelectrochemical system. J. Chem. Technol. Biotechnol. 2020, 95, 1876–1882. [Google Scholar] [CrossRef]
  25. Autthawong, T.; Namsar, O.; Yu, A.; Sarakonsri, T. Cost-effective production of SiO2/C and Si/C composites derived from rice husk for advanced lithium-ion battery anodes. J. Mater. Sci.: Mater. Electron. 2020, 31, 9126–9132. [Google Scholar] [CrossRef]
  26. Wang, P.; Yang, H.; Tang, C.; Wu, Y.; Zheng, Y.; Cheng, T.; Davey, K.; Huang, X.; Qiao, S.Z. Boosting electrocatalytic CO2–to–ethanol production via asymmetric C–C coupling. Nat. Commun. 2022, 13, 3754. [Google Scholar] [CrossRef]
  27. Chen, J.-J.; Li, Y.-Y.; Cui, T.-L.; Shi, Y.; Wang, R.-R.; Liu, X.-M.; Liu, G.; Chen, K.-K. Preparation and Properties of g-C3N4 Photocatalysts with Hierarchical Porous Structure. Chin. J. Inorg. Chem. 2020, 36, 835–840. [Google Scholar]
  28. Wang, X.; Wang, S.; Hu, W.; Cai, J.; Zhang, L.; Dong, L.; Zhao, L.; He, Y. Synthesis and photocatalytic activity of SiO2/g-C3N4 composite photocatalyst. Mater. Lett. 2014, 115, 53–56. [Google Scholar] [CrossRef]
  29. Tang, D.; Zhang, G. Fabrication of AgFeO2/g-C3N4 nanocatalyst with enhanced and stable photocatalytic performance. Appl. Surf. Sci. 2017, 391, 415–422. [Google Scholar] [CrossRef]
  30. Yuan, Y.; Huang, G.-F.; Hu, W.-Y.; Xiong, D.-N.; Zhou, B.-X.; Chang, S.; Huang, W.-Q. Construction of g-C3N4/CeO2/ZnO ternary photocatalysts with enhanced photocatalytic performance. J. Phys. Chem. Solids 2017, 106, 1–9. [Google Scholar] [CrossRef]
  31. Merino-Garcia, I.; García, G.; Hernández, I.; Albo, J. An optofluidic planar microreactor with photoactive Cu2O/Mo2C/TiO2 heterostructures for enhanced visible light-driven CO2 conversion to methanol. J. CO2 Util. 2023, 67, 102340. [Google Scholar] [CrossRef]
  32. Zhang, L.; Cao, H.; Lu, Y.; Zhang, H.; Hou, G.; Tang, Y.; Zheng, G. Effective combination of CuFeO2 with high temperature resistant Nb-doped TiO2 nanotube arrays for CO2 photoelectric reduction. J. Colloid Interface Sci. 2020, 568, 198–206. [Google Scholar] [CrossRef] [PubMed]
  33. Pan, Z.; Han, E.; Zheng, J.; Lu, J.; Wang, X.; Yin, Y.; Waterhouse, G.I.N.; Wang, X.; Li, P. Highly Efficient Photoelectrocatalytic Reduction of CO2 to Methanol by a p–n Heterojunction CeO2/CuO/Cu Catalyst. Nano-Micro-Lett. 2020, 12, 18. [Google Scholar] [CrossRef]
  34. Gu, X.; Qian, L.; Zheng, G. Photoelectrochemical CO2 reduction to syngas by a ZnO–CdS–Cu nanocomposite. Mol. Cat. 2020, 492, 110953. [Google Scholar] [CrossRef]
  35. Wang, L.; Peng, H.; Lamaison, S.; Gregoire, J.; Abild-Pedersen, F. Bimetallic effects on Zn-Cu electrocatalysts enhance activity and selectivity for the conversion of CO2 to CO. Chem. Catal. 2021, 1, 663–680. [Google Scholar] [CrossRef]
  36. Shi, L.; Yang, Y.; Song, J.; Yang, L.; Dai, Z.; Yao, L.; Jiang, W. A carbon quantum dot (CQD) modified-CuZn bimetallic catalyst for efficient electrocatalytic CO2 reduction. J. Mater. Chem. A 2025, 13, 5068–5080. [Google Scholar] [CrossRef]
  37. Fan, J.; Shi, L.; Ge, H.; Liu, J.; Deng, X.; Li, Z.; Liang, Q. Regulating the Oxygen Vacancy on Bi2MoO6/Co3O4 Core-Shell Nanocage Enables Highly Selective CO2 Photoreduction to CH4. Adv. Funct. Mater. 2025, 35, 2412078. [Google Scholar] [CrossRef]
  38. Ren, Z.; Li, B.; Wu, Y.; Liu, H.; Guo, F.; Tian, S.; Yang, J. Sn doping in In2O3-x nanoparticle achieving its synergy with oxygen vacancy towards high-efffciency electrocatalytic CO2 reduction and upcycling of spent liquid crystal display panels. Chem. Eng. J. 2025, 507, 160394. [Google Scholar] [CrossRef]
  39. Zhu, Z.; Chen, C.-Y.; Wu, R.-J. Hydrocarbon production by addition of Cu-ZnO on g-C3N4 for CO2 conversion. J. Chin. Chem. Soc. 2020, 67, 1654–1660. [Google Scholar] [CrossRef]
  40. Li, N.; Li, Y.; Jiang, R.; Zhou, J.; Liu, M. Controllable microstructure of polymer-small molecule blends thin films for high-performance organic field-effect transistors. Appl. Surf. Sci. 2019, 498, 143861. [Google Scholar] [CrossRef]
  41. Li, K.; Peng, B.; Jin, J.; Zan, L.; Peng, T. Dynamic oxygen storage modeling in a three-way catalyst for natural gas engines: A dual-site and shrinking-core diffusion approach. Appl. Catal. B 2017, 203, 910–916. [Google Scholar] [CrossRef]
  42. Zhan, C.; Dattila, F.; Rettenmaier, C.; López, N.; Cuenya, B.R. Key intermediates and Cu active sites for CO2 electroreduction to ethylene and ethanol. Nat. Energy 2024, 9, 1485–1496. [Google Scholar] [CrossRef] [PubMed]
Figure 1. (a) The XRD spectra of SiO2@CuO (5), SiO2@CuO (10) and SiO2@CuO (15). (b) The XRD spectra of photocatalyst in the range of 2θ = 40–80. (c) The XRD spectra of SiO2@CuO (15)/g-C3N4 and SiO2@CuO (10)/g-C3N4. (d) The Raman spectrum of SiO2@CuO (10)/g-C3N4.
Figure 1. (a) The XRD spectra of SiO2@CuO (5), SiO2@CuO (10) and SiO2@CuO (15). (b) The XRD spectra of photocatalyst in the range of 2θ = 40–80. (c) The XRD spectra of SiO2@CuO (15)/g-C3N4 and SiO2@CuO (10)/g-C3N4. (d) The Raman spectrum of SiO2@CuO (10)/g-C3N4.
Catalysts 15 00892 g001
Figure 2. (af) X-ray photoelectron spectroscopy (XPS) of SiO2@CuO (10)/g-C3N4. (a) Survey of SiO2@CuO (10)/g-C3N4, (b) C 1s, (c) N 1s, (d) O 1s, (e) Si 2p and (f) Cu 2p.
Figure 2. (af) X-ray photoelectron spectroscopy (XPS) of SiO2@CuO (10)/g-C3N4. (a) Survey of SiO2@CuO (10)/g-C3N4, (b) C 1s, (c) N 1s, (d) O 1s, (e) Si 2p and (f) Cu 2p.
Catalysts 15 00892 g002
Figure 3. (a,b) SEM patterns of SiO2@CuO (10 wt%) @g-C3N4; (c,d), SiO2@CuO (15 wt.%) @g-C3N4and mapping image of SiO2@CuO (10 wt.%) @g-C3N4. (e) TEM patterns of SiO2@CuO (10 wt.%). (f) g-C3N4. (g) SiO2@CuO (10 wt.%) @g-C3N4.
Figure 3. (a,b) SEM patterns of SiO2@CuO (10 wt%) @g-C3N4; (c,d), SiO2@CuO (15 wt.%) @g-C3N4and mapping image of SiO2@CuO (10 wt.%) @g-C3N4. (e) TEM patterns of SiO2@CuO (10 wt.%). (f) g-C3N4. (g) SiO2@CuO (10 wt.%) @g-C3N4.
Catalysts 15 00892 g003
Figure 4. UV-VIS patterns of: (a) SiO2@CuO-5, SiO2@CuO-10, SiO2@CuO-15 and SiO2@CuO-20; and (b) SiO2@CuO/g-C3N4-5, SiO2@CuO/g-C3N4-10, SiO2@CuO/g-C3N4-15 and SiO2@CuO/g-C3N4-20.
Figure 4. UV-VIS patterns of: (a) SiO2@CuO-5, SiO2@CuO-10, SiO2@CuO-15 and SiO2@CuO-20; and (b) SiO2@CuO/g-C3N4-5, SiO2@CuO/g-C3N4-10, SiO2@CuO/g-C3N4-15 and SiO2@CuO/g-C3N4-20.
Catalysts 15 00892 g004
Figure 5. Electrochemical impedance spectroscopy and photocurrent curve of four catalysts: (a) EIS; and (b) TPR.
Figure 5. Electrochemical impedance spectroscopy and photocurrent curve of four catalysts: (a) EIS; and (b) TPR.
Catalysts 15 00892 g005
Figure 6. Photoelectrocatalysis CO2 reduction performance and Faraday efficiency of catalysts with different Cu contents: (a) Yield of CO2 PER to CO and C2H4; (b) FE of CO2 PER to and C2H4.
Figure 6. Photoelectrocatalysis CO2 reduction performance and Faraday efficiency of catalysts with different Cu contents: (a) Yield of CO2 PER to CO and C2H4; (b) FE of CO2 PER to and C2H4.
Catalysts 15 00892 g006
Figure 7. Photoelectrocatalysis CO2 reduction performance and Faraday efficiency of SCCN-10 (a,b) and SCCN-15 (c,d) catalysts under different electric potentials. (e) Comparison of photoelectrocatalysis performance and electrocatalytic performance of catalyst SCCN-10. (f) And catalyst SCCN-10 undergoes four cycles of photocatalytic performance.
Figure 7. Photoelectrocatalysis CO2 reduction performance and Faraday efficiency of SCCN-10 (a,b) and SCCN-15 (c,d) catalysts under different electric potentials. (e) Comparison of photoelectrocatalysis performance and electrocatalytic performance of catalyst SCCN-10. (f) And catalyst SCCN-10 undergoes four cycles of photocatalytic performance.
Catalysts 15 00892 g007
Figure 8. Free energy diagrams for CO2 photoelectrocatalysis over SCCN-10 catalyst.
Figure 8. Free energy diagrams for CO2 photoelectrocatalysis over SCCN-10 catalyst.
Catalysts 15 00892 g008
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Li, Z.; Choy, K.L. Ternary SiO2@CuO/g-C3N4 Nanoparticles for Solar-Driven Photoelectrocatalytic CO2-to-Fuel Conversion. Catalysts 2025, 15, 892. https://doi.org/10.3390/catal15090892

AMA Style

Li Z, Choy KL. Ternary SiO2@CuO/g-C3N4 Nanoparticles for Solar-Driven Photoelectrocatalytic CO2-to-Fuel Conversion. Catalysts. 2025; 15(9):892. https://doi.org/10.3390/catal15090892

Chicago/Turabian Style

Li, Zhen, and Kwang Leong Choy. 2025. "Ternary SiO2@CuO/g-C3N4 Nanoparticles for Solar-Driven Photoelectrocatalytic CO2-to-Fuel Conversion" Catalysts 15, no. 9: 892. https://doi.org/10.3390/catal15090892

APA Style

Li, Z., & Choy, K. L. (2025). Ternary SiO2@CuO/g-C3N4 Nanoparticles for Solar-Driven Photoelectrocatalytic CO2-to-Fuel Conversion. Catalysts, 15(9), 892. https://doi.org/10.3390/catal15090892

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop