纳米限域与疏水性离子液体双调控策略在低浓度CO2电还原中实现高甲醇选择性

doi:10.1016/S1872-2067(26)65253-9

催化学报 ›› 2027, Vol. 92: 328-339.DOI: 10.1016/S1872-2067(26)65253-9

纳米限域与疏水性离子液体双调控策略在低浓度CO₂电还原中实现高甲醇选择性

张震^a^,^b, 张香娅^b, 张迈^b, 杨逸飞^b, 吴怡彤^b, 张琳琳^b^,^*(), 廖建军^b^,^*(), 宋春风^a^,^*()

^a 天津大学环境科学与工程学院, 天津市室内空气环境质量控制重点实验室, 天津 330354
^b 海南大学环境科学与工程学院, 海南省农林环境过程与生态调控重点实验室, 海南海口 570228

收稿日期:2026-03-26 接受日期:2026-06-26 出版日期:2027-01-02 发布日期:2026-10-30
通讯作者: *电子信箱: chunfeng.song@tju.edu.cn (宋春风),
liaojianjun008@163.com (廖建军),
6962zhanglinlin@163.com (张琳琳).
基金资助:
海口市科技计划项目(2024-030);国家自然科学基金(52403087);海南省科技专项基金(ZDYF2024SHFZ115);海南省自然科学基金(525RC701);海南大学科研启动基金(kyqd(zr)22185)

Nano-confinement and hydrophobic ionic-liquid engineering for methanol-selective CO₂ electroreduction from dilute streams

Zhen Zhang^a^,^b, Xiangya Zhang^b, Mai Zhang^b, Yifei Yang^b, Yitong Wu^b, Linlin Zhang^b^,^*(), Jianjun Liao^b^,^*(), Chunfeng Song^a^,^*()

^a Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin 330354, China
^b Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province, School of Environmental Science and Engineering, Hainan University, Haikou 570228, Hainan, China

Received:2026-03-26 Accepted:2026-06-26 Online:2027-01-02 Published:2026-10-30
Contact: *E-mail: chunfeng.song@tju.edu.cn (C. Song),
liaojianjun008@163.com (J. Liao),
6962zhanglinlin@163.com (L. Zhang).
Supported by:
Haikou City Science and Technology Plan Project(2024-030);National Natural Science Foundation of China(52403087);Hainan Province Science and Technology Special Fund(ZDYF2024SHFZ115);Natural Science Foundation of Hainan Province(525RC701);Hainan University Research Start-up Fund (kyqd(zr)22185)

摘要/Abstract

摘要：

电化学二氧化碳还原(CO₂RR)被认为是将废弃CO₂转化为燃料与化学品的重要路线, 尤其甲醇因可作为液体能源载体并具备碳一基础化工品的衔接优势而广受关注. 然而, 将CO₂高选择性、高效率地还原为甲醇受限于反应动力学缓慢和析氢反应(HER)竞争, 并且这些问题在低浓度CO₂进料下(如烟道气, 通常约10%‒15% CO₂)会进一步加剧, 导致传质限制与界面CO₂耗尽. 因此, 发展能够在低浓度CO₂进料条件下实现CO₂富集、抑制析氢反应, 并稳定关键中间体的催化策略, 对于推动CO₂制甲醇的实际应用与碳资源可持续利用具有重要意义.

本文通过将非化学计量硒化铜(Cu_2-_xSe)纳米晶锚定于介孔含氮碳纳米纤维(CSNC)的多级孔骨架中, 利用孔道空间的纳米限域效应在稀释进料条件下将CO₂有效富集于活性位周围, 提高CO₂RR反应驱动力. 在此基础上, 引入疏水性离子液体1-乙基-3-甲基咪唑四氟硼酸盐([Emim][BF₄])对CSNC孔道进行浸渍负载, 设计了CSNC/[Emim][BF₄]电催化剂. 接触角测试表明, CSNC/[Emim][BF₄]的接触角从CSNC的83.4°升至138.7°, 呈现近超疏水状态, 有效降低了水分子到达催化活性位的可及性, 从源头上削弱HER竞争. 同时, [Emim]⁺对CO₂的高亲和力进一步强化局部CO₂预富集, BF₄^-的低配位特性降低局部水活度, 实现CO₂富集与HER抑制的双重协同. 实验结果表明在H型电解池中, CSNC/[Emim][BF₄]在-0.52 V vs. RHE获得甲醇法拉第效率(FE)峰值为79.4%, 显著优于Cu_2-_xSe和CSNC, 且可维持> 70% FE长达48 h. 在气体扩散流动电池中, 该催化剂在-0.82 V vs. RHE下于纯CO₂中甲醇FE达到78.8%, 电流密度在-1.4 V vs. RHE可达303 mA/cm². 在模拟烟气的10%CO₂进料条件下甲醇FE保持72.3%, 相较CSNC提升1.67倍, 相较于纯CO₂工况FE仅下降8.2%, 且可稳定运行24 h. 机理研究方面, 进料切换实验表明CSNC/[Emim][BF₄]以CO₂或甲酸为碳源时产生大量甲醇, 而CO进料下仅生成痕量甲醇, 证明反应主要经由甲酸盐通路而非CO中间体路径进行. 原位拉曼光谱未检测到CO特征峰, 而在~1068 cm^-1观察到CO₃^2-峰, 表明限域微环境中碳酸盐积累降低了质子给体可用性. 原位红外光谱确认了吸附态甲酸盐中间体的生成. 密度泛函理论计算表明, CSNC/[Emim][BF₄]表面H的吉布斯自由能高于Cu_2-_xSe和CSNC, 证明[Emim][BF₄]通过提高HER能垒抑制析氢. 含氮位点通过Cu-N配位稳定COOH中间体, 促进其沿甲酸盐通路向甲醇深度加氢转化.

综上, 本工作以纳米限域与疏水调节协同策略有效构筑了CO₂局部富集和抑制HER界面, 实现了稀薄CO₂高选择性制甲醇, 阐明了CO₂制甲醇的甲酸盐通路机制, 为面向低浓度CO₂高效电催化剂设计和合成提供了新思路.

关键词: 低浓度CO₂电还原, 离子液体, Cu_2-_xSe, 纳米限域, 甲醇

Abstract:

The electrocatalytic reduction of dilute carbon dioxide (CO₂) to methanol faces dual challenges of sluggish reaction kinetics and the competing hydrogen evolution reaction (HER). This study presents a nanoconfined ionic liquid catalyst strategy, in which Cu_2‒_xSe nanocrystals are anchored as catalytic engines within mesoporous nitrogen-doped carbon nanofibers (CSNC), followed by impregnation with the ionic liquid [Emim][BF₄] to modulate the reaction microenvironment. The multilevel pore structure of the catalyst enables local enrichment of CO₂ through a nanoconfinement effect, while the homogeneous distribution of the ionic liquid combined with a hydrophobic interface collectively suppresses HER, thereby enhancing methanol selectivity. In an H-type cell with 0.5 mol/L KHCO₃, CSNC/[Emim][BF₄] achieves a peak methanol Faradaic efficiency (FE) of 79.4% at -0.52 V vs. RHE, sustaining > 70% FE over 48 h. In a flow cell with 1 mol/L KOH, FE reaches 78.8% under pure CO₂ and 72.3% under 10% CO₂ (simulating flue gas), 1.67 times higher than CSNC alone, with stable performance over 24 h. In situ spectroscopy and feedstock-switching experiments reveal N-coordination stabilizes *COOH intermediates, favoring methanol via the formate pathway. This strategy advances selective, stable CO₂-to-methanol conversion from dilute streams, promoting sustainable carbon utilization and industrial flue gas valorization.

Key words: Low-concentration CO₂ electroreduction, Ionic liquids, Cu_2-xSe, Nano-confinement, Methanol

张震, 张香娅, 张迈, 杨逸飞, 吴怡彤, 张琳琳, 廖建军, 宋春风. 纳米限域与疏水性离子液体双调控策略在低浓度CO₂电还原中实现高甲醇选择性[J]. 催化学报, 2027, 92: 328-339.

Zhen Zhang, Xiangya Zhang, Mai Zhang, Yifei Yang, Yitong Wu, Linlin Zhang, Jianjun Liao, Chunfeng Song. Nano-confinement and hydrophobic ionic-liquid engineering for methanol-selective CO₂ electroreduction from dilute streams[J]. Chinese Journal of Catalysis, 2027, 92: 328-339.

×
扫码分享

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.cjcatal.com/CN/10.1016/S1872-2067(26)65253-9

https://www.cjcatal.com/CN/Y2027/V92/I1/328

图/表 6

Fig. 1. (a) Preparation of CSNC/[Emim][BF4] composite catalysts. (b) XRD patterns of the samples. High-resolution XPS spectra of Cu2-xSe, 30-CSNC and CSNC/[Emim][BF4]: Cu 2p (c), Cu LMM (d), Se 3d (e), N 1s (f), and F 1s and B 1s (g).

Fig. 2. SEM images of 20-CSNC (a), 30-CSNC (b), and 40-CSNC (c). TEM images of 20-CSNC (d), 30-CSNC (e), and 40-CSNC (f). (g) HRTEM image of CSNC/[Emim][BF4]. (h) EDX elemental mapping images of CSNC/[Emim][BF4].

Fig. 3. (a) Static contact angle and nitrogen adsorption-desorption isotherms for Cu2‒xSe (b), 30-CSNC (c), and CSNC/[Emim][BF4] (d).

Fig. 4. (a) LSV curves of catalysts in CO2-saturated 0.5 mol/L KHCO3 electrolyte. Cdl of catalysts (b) and Faradaic efficiency (c) of the methanol process using different catalysts. Faradaic efficiency of the CO2RR by Cu2‒xSe (d), 30-CSNC (e), and CSNC/[Emim][BF4] (f). (g) Performance comparison of reported CO2RR-to-methanol electrocatalysts in H-type cells. (h) Stability test of CSNC/[Emim][BF4] at -0.52 V vs. RHE in 0.5 mol/L KHCO3 electrolyte.

Fig. 5. (a) LSV curves of catalysts. (b) Faradaic efficiency of the CO2RR by CSNC/[Emim][BF4]. (c) Methanol Faradaic efficiency of the catalyst under different carbon dioxide concentrations. (d) Methanol Faradaic efficiency of the catalyst under different pH conditions. (e) Stability test of CSNC/[Emim][BF4] at -0.82 V vs. RHE in 10% CO2 concentration.

Fig. 6. (a) Schematic diagram of the pathway for forming methanol through CO2RR. (b) Faradaic efficiency of CSNC/[Emim][BF4] at ‒0.52 V vs. RHE in a 0.5 mol/L KHCO3 electrolyte with different feedstocks: CO2, HCOOH, and CO. (c) In situ Raman and (d) In situ IR spectra of the CSNC/[Emim][BF4] catalyst under various applied potentials. The observed absorption bands correspond to adsorbed intermediates: *CO (2070 cm‒1), *CHO (1750 cm‒1), *H2O (1640 cm‒1), *CH2O (1450 cm‒1), *CH3O (1070 cm‒1) and *COOH (1280, 1390, and 1570 cm‒1). Dashed lines and arrows indicate these characteristic bands. Density functional theory (DFT) calculation. (e) reaction free energy profile of H2O dissociation over 30-CSNC and CSNC/[Emim][BF4] catalysts. (f) Gibbs free energy curves of the reaction pathways for the reduction of CO2 to CH3OH and CH4 by different catalysts.

参考文献

[1]	X. Mei, C. Liu, D. Zhang, J. Cao, R. Ge, J. Wang, W. Xu, Adv. Energy Mater., 2024, 14, 2303889.
[2]	Z. Jin, D. Jiao, Y. Dong, L. Liu, J. Fan, M. Gong, X. Ma, Y. Wang, W. Zhang, L. Zhang, Z. Yu, D. Voiry, W. Zheng, X. Cui, Angew. Chem. Int. Ed., 2024, 63, e202318246.
[3]	Y. Wang, H. Xu, Y. Liu, J. Jang, X. Qiu, E. P. Delmo, Q. Zhao, P. Gao, M. Shao, Angew. Chem. Int. Ed., 2024, 63, e202313858.
[4]	Q. Zhu, C. L. Rooney, H. Shema, C. Zeng, J. A. Panetier, E. Gross, H. Wang, L. R. Baker, Nat. Catal., 2024, 7, 987-999.
[5]	T. Yang, F. Yang, T. Wang, W. Zhang, F. Deng, C. Zhong, Q. Peng, C. Liu, X. Chen, Z. Zhang, Y. Li, Y. Feng, X. Li, K. Wang, C. Zhang, Y. Zhou, X. Lu, W. Zhu, Y. Wei, L. Xie, W. Huang, Adv. Mater., 2026, 38, e11233.
[6]	I. Hussain, H. Alasiri, W. Ullah Khan, K. Alhooshani, Coord. Chem. Rev., 2023, 482, 215081.
[7]	H. Ren, H. M. C. M. Jayawardana, S. Meng, Y. Li, C. Xia, L. Zhao, M. Xie, Y. Xu, Energy Mater. Adv., 2026, 7, 0154.
[8]	Y. Fang, M. Li, Y. Wen, P. Li, Y. Gao, T. Ma, B. Shan, Nat. Catal., 2026, 9, 211-222.
[9]	J. Lai, Y. Xiong, A. Habadati, M. Li, M. Zhang, T. Fang, K. Yi, Y. Ding, X. Liu, X. Jia, ACS Catal., 2026, 16, 3647-3661.
[10]	G. Sun, Y. Ma, Y. Cao, H.-T. Wang, D. Li, M. Sun, C.-F. Lee, C.-K. Hsu, Y.-R. Lu, W. Zhang, L. Han, Angew. Chem. Int. Ed., 2026, 65, e23844.
[11]	Q. Mo, C. Chen, S. Li, H. Song, L. Zhang, Nano Res., 2025, 18, 94907893.
[12]	Y. Zhang, Q. Yu, Z. Wang, W. Zhang, X. She, Q. Zhang, Y. Liu, H. Li, H. Xu, ACS Catal., 2025, 15, 7352-7360.
[13]	B. Ren, X. Zhang, L. Yang, G. Wen, S. Dong, H. Xiong, Y. Liu, X. Duan, L. Tan, X. Wang, Z. Chen, Nat. Commun., 2025, 16, 8383.
[14]	Y. Lei, Y. Niu, X. Tang, X. Yu, X. Huang, X. Lin, H. Yi, S. Zhao, J. Jiang, J. Zhang, F. Gao, J. Energy Chem., 2024, 97, 593-611.
[15]	S. Kuld, M. Thorhauge, H. Falsig, C. F. Elkjær, S. Helveg, I. Chorkendorff, J. Sehested, Science, 2016, 352, 969-974.
[16]	C. Du, Y. Zhu, L. Yang, R. Jiang, M. Jin, Q. Zhang, S. He, T. Song, X. Ma, C. Cao, M. Zou, Energy Storage Mater., 2025, 79, 104304.
[17]	D. Yang, Q. Zhu, C. Chen, H. Liu, Z. Liu, Z. Zhao, X. Zhang, S. Liu, B. Han, Nat. Commun., 2019, 10, 677.
[18]	C. He, D. Duan, J. Low, Y. Bai, Y. Jiang, X. Wang, S. Chen, R. Long, L. Song, Y. Xiong, Nano Res., 2023, 16, 4494-4498.
[19]	S. Liang, T. Zhang, Y. Zheng, T. Xue, Z. Wang, Q. Wang, H. He, Appl. Catal. B, 2023, 333, 122801.
[20]	W. Zhang, M. Dai, Z. Zeng, Y. Wang, Y. Zhang, W. Ni, S. Wang, S. Zhang, Angew. Chem. Int. Ed., 2025, 64, e202424104.
[21]	Y. Sha, J. Zhang, X. Cheng, M. Xu, Z. Su, Y. Wang, J. Hu, B. Han, L. Zheng, Angew. Chem. Int. Ed., 2022, 61, e202200039.
[22]	H. Yu, W. Zhao, J. Wang, W. Wang, L.-L. Shen, G.-R. Zhang, D. Mei, Appl. Catal. B, 2026, 382, 126006.
[23]	R. Chen, Q. Wu, J. Zhu, S. Wang, Z. Hu, J. Hu, J. Zhu, H. Zhang, B. Ye, Y. Sun, Y. Xie, J. Am. Chem. Soc., 2025, 147, 7921-7931.
[24]	Z. Tan, J. Zhang, Y. Yang, J. Zhong, Y. Zhao, Y. Teng, B. Han, Z. Chen, Nat. Commun., 2025, 16, 1843.
[25]	H. Wang, X. Bi, Y. Yan, Y. Zhao, Z. Yang, H. Ning, M. Wu, Adv. Funct. Mater., 2023, 33, 2214946.
[26]	P. Zhou, S. Qi, M. Zhang, L. Wang, Q. Huang, Z. Su, Z. Guo, Y. Hu, Y. Wang, S. Chen, Electrochim. Acta, 2021, 367, 137449.
[27]	H. Wang, A. Gao, A. Bari, M. Gu, X. Zhang, G. Wang, ACS Appl. Nano Mater., 2024, 7, 6810-6819.
[28]	Y. Ma, L. Yang, Y. Li, H. Li, Y. Huang, J. Chen, Small, 2024, 20, 2308650.
[29]	J. Yuan, B. Yu, D. Pan, X. Hu, J. Chen, M. Aminua, Y. Liu, L. Sheng, Y. Chen, Y. Wu, H. Zhan, Z. Wen, Adv. Funct. Mater., 2023, 33, 2305503.
[30]	C. Lv, K. Huang, Y. Fan, J. Xu, C. Lian, H. Jiang, Y. Zhang, C. Ma, W. Qiao, J. Wang, L. Ling, Nano Energy, 2023, 111, 108384.
[31]	K. Meesombad, K. Srisawad, P. Khemthong, T. Butburee, C. Sukpattanacharoen, K. Faungnawakij, P. Chakthranont, ACS Appl. Nano Mater., 2024, 7, 20046-20057.
[32]	X. Li, L. Li, G. Chen, X. Chu, X. Liu, C. Naisa, D. Pohl, M. Löffler, X. Feng, Nat. Commun., 2023, 14, 4034.
[33]	Z. Xing, L. Hu, D. S. Ripatti, X. Hu, X. Feng, Nat. Commun., 2021, 12, 136.
[34]	T. Cheng, A. Fortunelli, W. A. Goddard III, Proc. Natl. Acad. Sci. USA, 2019, 116, 7718-7722.
[35]	S. Chongdar, R. Chatterjee, S. Reza, S. Pal, R. Thapa, R. Bal, A. Bhaumik, Adv. Energy Mater., 2025, 15, 2403809.
[36]	H. Kim, J. Lee, S. Lee, S. Park, Y. Lee, G. Lee, H. S. Jeon, M. H. Han, S. Jin, H.-W. Lee, A. Soon, J. Kim, J. Ryu, Adv. Mater., 2025, 37, 2501021.
[37]	X. Yang, J. Cheng, X. Yang, Y. Xu, W. Sun, J. Zhou, Chem. Eng. J., 2022, 431, 134171.
[38]	H. Yu, X. Han, Z. Hua, W. Yang, X. Wu, Y. Wu, S. Chen, W. Hong, S. Deng, J. Zhang, J. Wang, ACS Catal., 2024, 14, 12783-12791.
[39]	Y. Zhang, L. Zhang, X. Feng, G. Zhang, Y. Zhang, Small, 2025, 21, e05892.
[40]	M. K. Yadav, A. Dutta, A. Lal, H. Porat, T. Zidki, A. Borenstein, ACS Appl. Energy Mater., 2025, 8, 12641-12650.
[41]	S. Biswas, T. Tanaka, H. Song, M. Ogami, Y. Shingyouchi, S. Hossian, M. Kamiyama, T. Kosaka, R. Nakatani, Y. Niihori, S. Das, T. Kawawaki, D.-E. Jiang, Y. Negishi, Small Sci., 2025, 5, 2400465.
[42]	Z. Liang, J. Wang, P. Tang, W. Tang, L. Liu, M. Shakouri, X. Wang, J. Llorca, S. Zhao, M. Heggen, R. E. Dunin-Borkowski, A. Cabot, H.-B. Wu, J. Arbiol, Appl. Catal. B, 2022, 314, 121451.
[43]	J. Liu, D. Yang, Y. Zhou, G. Zhang, G. Xing, Y. Liu, Y. Ma, O. Terasaki, S. Yang, L. Chen, Angew. Chem. Int. Ed., 2021, 60, 14473-14479.
[44]	W. Deng, P. Zhang, B. Seger, J. Gong, Nat. Commun., 2022, 13, 803.
[45]	R.-P. Ye, J. Ding, W. Gong, M. D. Argyle, Q. Zhong, Y. Wang, C. K. Russell, Z. Xu, A. G. Russell, Q. Li, M. Fan, Y.-G. Yao, Nat. Commun., 2019, 10, 5698.
[46]	F. Huang, A. Xu, X. Chen, H. Sun, S. He, D. Wei, B. Wang, A. Guan, X. Yin, J. Xu, H. He, ACS Catal., 2025, 15, 20864-20878.
[47]	Z. Zhang, H. Guo, S. Li, S. Gao, X. Wang, M. Li, W. Yan, H. Xu, Nat. Commun., 2025, 16, 7559.

纳米限域与疏水性离子液体双调控策略在低浓度CO₂电还原中实现高甲醇选择性

Nano-confinement and hydrophobic ionic-liquid engineering for methanol-selective CO₂ electroreduction from dilute streams

RichHTML

PDF

Supporting Information

可视化

摘要/Abstract

引用本文

使用本文

扫码分享

图/表 6

参考文献

相关文章 15

编辑推荐

Metrics

[1]	赵洁, 徐广远, 陈飔, 严欢. Cu-ZrO₂界面精准调控用于CO₂加氢制甲醇反应[J]. 催化学报, 2027, 92(1): 316-327.
[2]	杨利芳, 张雨格, 刘勇, 杨治军, 李广慧, 周建伟, 孟苏刚. 单层硫化铟锌纳米片锌空位锚定银团簇用于高效双功能光催化[J]. 催化学报, 2027, 92(1): 285-299.
[3]	李勇, 刘一凡, 乔翠, 付梦倩, 杨子锋, 李雨浓, 张锁江. 聚离子液体-富吡咯氮碳材料锚定痕量钯实现自优化CO₂制DMC电催化过程[J]. 催化学报, 2027, 92(1): 340-354.
[4]	张家雨, 王昆, 于晶露, 徐凯洋, 杨璐, 饶佳丽, 宋树芹, 王毅. Mn掺杂调控NiCo LDH活性位点用于H₂O₂与甲酸盐的节能耦合电合成[J]. 催化学报, 2026, 88(9): 307-321.
[5]	张心怡, 董威辰, 曹毅, 周彩霞, 郭家秀, 张海龙. Cu-KFI分子筛催化剂上甲烷直接转化高效连续合成甲醇[J]. 催化学报, 2026, 88(9): 369-381.
[6]	王松玲, 黄安华, 尹风星, 卢瑞祥, 刘文刚, 张云, 乔波涛. 原位合成双氧水用于甲烷高选择性氧化制甲醇[J]. 催化学报, 2026, 88(9): 347-355.
[7]	王佳豪, 高启梁, 李超, 高秀娟, 弓建, 宋法恩, 张俊峰, 韩怡卓, 张清德. 铜掺杂的NASICON双功能催化剂上甲醇和乙酸高效合成丙烯酸及其酯[J]. 催化学报, 2026, 85(6): 356-370.
[8]	陈兰兰, 圣利, 周亚男, 罗其全, 李震宇, 张文华, 杨金龙. Ni₁-MoS₂单原子催化剂用于CO₂加氢制甲醇的优越性: 密度泛函理论与微观动力学研究[J]. 催化学报, 2026, 85(6): 143-152.
[9]	刘芷瑶, 刘唐康, 秦川, 刘国亮, 郑安民. 氧化锆介导界面催化在CO₂加氢反应中的研究进展[J]. 催化学报, 2026, 84(5): 1-24.
[10]	李金河, 姚霞喜, 于晓慧, 周小松, 任伟, 王乐乐, 王伟康, 刘芹芹. Mo₂N QDs/ZnIn₂S₄异质结中的等离激元-激子-声子协同作用实现光生电子与空穴的同步高值化利用[J]. 催化学报, 2026, 83(4): 219-230.
[11]	王浩伊, 张延凯, 司春英, 齐运彪, 张全兴, 江伟. 双功能离子液体催化剂实现废弃聚苯乙烯向苯甲酸的高效光氧化升级回收[J]. 催化学报, 2026, 83(4): 231-243.
[12]	肖卫平, 张跃, 王娜, 杨小飞. 电极-电解质协同耦合实现高熵金属间化合物电催化剂的高效稳定氧还原性能[J]. 催化学报, 2026, 82(3): 92-104.
[13]	宋殿坤, 吴云云, 华家辉, 邵春风, 魏朝阳, 王键吉, 代凯. 咪唑阳离子调控银电极界面促进电化学CO₂还原作用的研究[J]. 催化学报, 2026, 81(2): 206-215.
[14]	王心怡, 王朝旗, 杨淼, 王晓光, 左越中, 张壮壮, 吴一墨, 韩晶峰, 李冰, 黄玮, 任利敏, 魏迎旭, 刘欣梅, 田鹏, 刘中民. 机器学习辅助发现具有超高初始选择性的甲醇制烯烃分子筛催化剂[J]. 催化学报, 2026, 81(2): 124-135.
[15]	张晓, 王雨欣, 孙书涵, 熊贤强, 李覃, 吕康乐. 电荷-光热-催化协同提升ZnCdS/Co₂SnO₄光催化产氢与苯甲醇氧化性能[J]. 催化学报, 2026, 90(11): 184-196.