Login In
2025 Volume 44 Issue 5
2025, 44(5): 100471
doi: 10.1016/j.cjsc.2024.100471
Abstract:
2025, 44(5): 100510
doi: 10.1016/j.cjsc.2024.100510
Abstract:
2025, 44(5): 100512
doi: 10.1016/j.cjsc.2025.100512
Abstract:
Rational synthesis of highly porous covalent organic frameworks for high-performance methane storage
2025, 44(5): 100514
doi: 10.1016/j.cjsc.2025.100514
Abstract:
2025, 44(5): 100516
doi: 10.1016/j.cjsc.2025.100516
Abstract:
MOF-driven interaction engineering in solid polymer electrolytes for durable lithium metal batteries
2025, 44(5): 100517
doi: 10.1016/j.cjsc.2025.100517
Abstract:
2025, 44(5): 100528
doi: 10.1016/j.cjsc.2025.100528
Abstract:
2025, 44(5): 100541
doi: 10.1016/j.cjsc.2025.100541
Abstract:
5-Hydroxymethylfurfural electrooxidation reaction (HMFOR) provides a promising route for producing high-value-added compounds. It is generally believed that NiOOH is the active species in HMFOR process, but its inherently poor electron transfer ability leads to limited catalytic activity. In this work, a W doping strategy is adopted to regulate the electron transfer between NiOOH and reaction molecules. Electrochemical results show that W-doped Ni5P4-R exhibits excellent electrochemical performance for the oxidation of HMF to FDCA with the conversion of HMF and yield of FDCA both close to ∼100%. Density functional theory and in-situ characterization reveal that the introduction of W causes the distortion of NiOOH lattice, resulting in the Jahn-Teller distortion and the elimination of orbital degeneracy, thereby broadening the eg∗ band of NiOOH. This feature is beneficial for the electron transfer between W-doped NiOOH and HMF (1.31 e−), thereby promoting the C–H bond activation of the aldehyde group in HMF and effectively reducing the energy barrier of rate-determining step (RDS).
5-Hydroxymethylfurfural electrooxidation reaction (HMFOR) provides a promising route for producing high-value-added compounds. It is generally believed that NiOOH is the active species in HMFOR process, but its inherently poor electron transfer ability leads to limited catalytic activity. In this work, a W doping strategy is adopted to regulate the electron transfer between NiOOH and reaction molecules. Electrochemical results show that W-doped Ni5P4-R exhibits excellent electrochemical performance for the oxidation of HMF to FDCA with the conversion of HMF and yield of FDCA both close to ∼100%. Density functional theory and in-situ characterization reveal that the introduction of W causes the distortion of NiOOH lattice, resulting in the Jahn-Teller distortion and the elimination of orbital degeneracy, thereby broadening the eg∗ band of NiOOH. This feature is beneficial for the electron transfer between W-doped NiOOH and HMF (1.31 e−), thereby promoting the C–H bond activation of the aldehyde group in HMF and effectively reducing the energy barrier of rate-determining step (RDS).
2025, 44(5): 100563
doi: 10.1016/j.cjsc.2025.100563
Abstract:
Anion exchange membrane (AEM), as a kind of key membrane materials, has shown great application potential in many electrochemical fields, and remarkable progress has been made in related research in recent years. In this paper, the research status of AEM is reviewed, including its material design, preparation method, performance optimization and application in the fields of hydrogen production by electrolytic water, fuel cell and water treatment. In terms of material design, new polymer skeleton structures are emerging to regulate the stability of ion conduction channels and membranes by introducing specific functional groups or changing the molecular chain structure. The preparation methods have been gradually expanded from the traditional solution casting method to more advanced technologies, such as interfacial polymerization and electrostatic spinning, which effectively improve the microstructure and property uniformity of the film. Performance optimization focuses on improving ion conductivity, reducing membrane swelling rate and enhancing chemical stability, and a variety of modification strategies are developed and applied. Despite the achievements made so far, there are still some challenges, such as the lack of long-term stability in highly alkaline environments. Future research needs to further explore new material systems and preparation processes in order to promote the wide application and sustainable development of AEM technology in energy, environmental protection and other fields.
Anion exchange membrane (AEM), as a kind of key membrane materials, has shown great application potential in many electrochemical fields, and remarkable progress has been made in related research in recent years. In this paper, the research status of AEM is reviewed, including its material design, preparation method, performance optimization and application in the fields of hydrogen production by electrolytic water, fuel cell and water treatment. In terms of material design, new polymer skeleton structures are emerging to regulate the stability of ion conduction channels and membranes by introducing specific functional groups or changing the molecular chain structure. The preparation methods have been gradually expanded from the traditional solution casting method to more advanced technologies, such as interfacial polymerization and electrostatic spinning, which effectively improve the microstructure and property uniformity of the film. Performance optimization focuses on improving ion conductivity, reducing membrane swelling rate and enhancing chemical stability, and a variety of modification strategies are developed and applied. Despite the achievements made so far, there are still some challenges, such as the lack of long-term stability in highly alkaline environments. Future research needs to further explore new material systems and preparation processes in order to promote the wide application and sustainable development of AEM technology in energy, environmental protection and other fields.
2025, 44(5): 100568
doi: 10.1016/j.cjsc.2025.100568
Abstract:
Bio-polyol is considered as a core material to synthesize eco-friendly polyurethane products. However, one of the popular bio-polyols, polytrimethylene ether glycol (PO3G), is reluctant to crystallize and therefore exhibits a cold crystallization behavior. This abnormal behavior causes unstable mechanical properties at low-temperature and limits its applications in shape memory devices where crystallization is an essential mechanism. To analyze the unusual phenomenon, we compared different ether polyols focusing on symmetry characteristics and the even-odd effect of carbon backbones. It is found that PO3G has a slow crystallization rate because its ether linkages require specific chain arrangement for attractive interactions. Consequently, a thermal learning mechanism is developed to restore the normal crystallization behavior of elastomers synthesized from the bio-polyol. Repetitive heating and cooling cycles with high-temperature annealing induce urethane exchange reaction and reconstruct the chain orientations for fast crystallization. Results suggest the degree of crystallizations in polyurethane elastomer can be precisely controlled by introducing repetitive thermal treatments to enhance the potential applications of bio-polyols in polymer industries.
Bio-polyol is considered as a core material to synthesize eco-friendly polyurethane products. However, one of the popular bio-polyols, polytrimethylene ether glycol (PO3G), is reluctant to crystallize and therefore exhibits a cold crystallization behavior. This abnormal behavior causes unstable mechanical properties at low-temperature and limits its applications in shape memory devices where crystallization is an essential mechanism. To analyze the unusual phenomenon, we compared different ether polyols focusing on symmetry characteristics and the even-odd effect of carbon backbones. It is found that PO3G has a slow crystallization rate because its ether linkages require specific chain arrangement for attractive interactions. Consequently, a thermal learning mechanism is developed to restore the normal crystallization behavior of elastomers synthesized from the bio-polyol. Repetitive heating and cooling cycles with high-temperature annealing induce urethane exchange reaction and reconstruct the chain orientations for fast crystallization. Results suggest the degree of crystallizations in polyurethane elastomer can be precisely controlled by introducing repetitive thermal treatments to enhance the potential applications of bio-polyols in polymer industries.
2025, 44(5): 100569
doi: 10.1016/j.cjsc.2025.100569
Abstract:
Piezo-photocatalysis is an emerging photocatalytic technology in which the piezoelectric electric field drives photogenerated carriers to separate, thereby improving the photocatalytic activity of the catalyst. Herein, solid phase and one-step molten salt processes were used to prepare SrBi2Nb2O9 (SBN) powders with granular and sheet morphologies, respectively. The influence of micromorphology on the piezo-photocatalytic performances of SBN was determined by degrading ciprofloxacin hydrochloride (CIP). SBN nanosheets demonstrate remarkable piezo-photocatalytic performance, achieving an 89.13% CIP degradation rate in 60 min and an apparent rate constant of 34.73 × 10−3 min−1. This performance is approximately 2.65 times higher than that of granular SBN and outperformed many recently reported piezo-photocatalysts under similar experimental conditions. Free radical trapping techniques, electron spin resonance spectroscopy and liquid chromatography-mass spectrometry are utilized to study the potential paths and mechanisms of CIP degradation. Piezoresponse force microscopy and finite element simulation show that the piezo-response of SBN nanosheets is significantly higher than that of granular SBN. SBN nanosheets achieve high degradation efficiency due to their optimized conduction band positions and enhanced piezoelectric effect, facilitated by the two-dimensional nanosheet structures. In this work, the piezoelectric internal electric field of piezoelectric catalysts can be increased by tuning the catalyst morphology, which points to a possible direction for the production of high-performance piezoelectric catalysts.
Piezo-photocatalysis is an emerging photocatalytic technology in which the piezoelectric electric field drives photogenerated carriers to separate, thereby improving the photocatalytic activity of the catalyst. Herein, solid phase and one-step molten salt processes were used to prepare SrBi2Nb2O9 (SBN) powders with granular and sheet morphologies, respectively. The influence of micromorphology on the piezo-photocatalytic performances of SBN was determined by degrading ciprofloxacin hydrochloride (CIP). SBN nanosheets demonstrate remarkable piezo-photocatalytic performance, achieving an 89.13% CIP degradation rate in 60 min and an apparent rate constant of 34.73 × 10−3 min−1. This performance is approximately 2.65 times higher than that of granular SBN and outperformed many recently reported piezo-photocatalysts under similar experimental conditions. Free radical trapping techniques, electron spin resonance spectroscopy and liquid chromatography-mass spectrometry are utilized to study the potential paths and mechanisms of CIP degradation. Piezoresponse force microscopy and finite element simulation show that the piezo-response of SBN nanosheets is significantly higher than that of granular SBN. SBN nanosheets achieve high degradation efficiency due to their optimized conduction band positions and enhanced piezoelectric effect, facilitated by the two-dimensional nanosheet structures. In this work, the piezoelectric internal electric field of piezoelectric catalysts can be increased by tuning the catalyst morphology, which points to a possible direction for the production of high-performance piezoelectric catalysts.
2025, 44(5): 100570
doi: 10.1016/j.cjsc.2025.100570
Abstract:
Ni-based catalysts hold great potential in the light-driven dry reforming of methane (DRM) for syngas production due to their low cost and comparable catalytic performance to conventional noble-metal catalysts. However, the currently available Ni-based catalysts are confronted with low light-driven DRM efficiency and poor stability attributed to the coking. Herein, an atomically dispersed Ni-loaded CeO2 (Ni/CeO2) for light-driven DRM is prepared by employing a polyol-mediated doping method to allow the high loading concentration of Ni on the CeO2, which overcomes the conventional atomically dispersed metal problem of low loading content. The atomically dispersed nature of the Ni can induce enormous CH4 activation sites for the reaction and photothermal effects for driving the reaction, while the CeO2 can facilitate CO2 activation. Therefore, the optimized atomically dispersed Ni-loaded CeO2 demonstrates an excellent light-driven DRM performance for H2 (626.5 mmol gcat−1 h−1) and CO (728.5 mmol gcat−1 h−1) production. More importantly, the optimized sample sustains its DRM performance after 100 h of continuous test, and such excellent stability of the presence of enormous Ni–O pairs can prevent the rapid conversion of CHx intermediates into coke. This work demonstrates the meticulous design of non-noble metal catalysts for the light-driven DRM with both high performance and stability.
Ni-based catalysts hold great potential in the light-driven dry reforming of methane (DRM) for syngas production due to their low cost and comparable catalytic performance to conventional noble-metal catalysts. However, the currently available Ni-based catalysts are confronted with low light-driven DRM efficiency and poor stability attributed to the coking. Herein, an atomically dispersed Ni-loaded CeO2 (Ni/CeO2) for light-driven DRM is prepared by employing a polyol-mediated doping method to allow the high loading concentration of Ni on the CeO2, which overcomes the conventional atomically dispersed metal problem of low loading content. The atomically dispersed nature of the Ni can induce enormous CH4 activation sites for the reaction and photothermal effects for driving the reaction, while the CeO2 can facilitate CO2 activation. Therefore, the optimized atomically dispersed Ni-loaded CeO2 demonstrates an excellent light-driven DRM performance for H2 (626.5 mmol gcat−1 h−1) and CO (728.5 mmol gcat−1 h−1) production. More importantly, the optimized sample sustains its DRM performance after 100 h of continuous test, and such excellent stability of the presence of enormous Ni–O pairs can prevent the rapid conversion of CHx intermediates into coke. This work demonstrates the meticulous design of non-noble metal catalysts for the light-driven DRM with both high performance and stability.
2025, 44(5): 100571
doi: 10.1016/j.cjsc.2025.100571
Abstract:
Electrocatalytic carbon dioxide reduction (CO2ER) driven by renewable energy sources to produce high-value-added chemicals is a highly promising strategy for achieving a closed carbon cycle. Cu is the only highly active catalyst capable of producing multi-carbon (C2+) products through CO2ER. However, due to the constraints of existing scaling relationships and competing hydrogen evolution reaction, it is still challenging to achieve high selectivity of a single desired product. In this work, high-entropy alloy (HEA) CuMoRuFeW surface skin on Cu nanorods was obtained by a one-pot co-reduction method. It is revealed that Fe could effectively facilitate the co-reduction of Mo and W precursors and the formation of HEA surface on Cu nanorod. The Faradaic efficiency (FE) for ethylene and ethanol in CO2ER reaches 49.5% and 20.4%, respectively, with a total FEC2 of 69.9% and current density of 250 mA cm−2 at −1.1 V vs. RHE. Theoretical calculations reveal that the Cu–W–Fe combination site is more active in CO2 activation and C–C coupling for C2 products than other sites. This work underscores the importance of HEA in overcoming the constraints of linear scaling relationships and improving the selectivity for C2 products in CO2ER.
Electrocatalytic carbon dioxide reduction (CO2ER) driven by renewable energy sources to produce high-value-added chemicals is a highly promising strategy for achieving a closed carbon cycle. Cu is the only highly active catalyst capable of producing multi-carbon (C2+) products through CO2ER. However, due to the constraints of existing scaling relationships and competing hydrogen evolution reaction, it is still challenging to achieve high selectivity of a single desired product. In this work, high-entropy alloy (HEA) CuMoRuFeW surface skin on Cu nanorods was obtained by a one-pot co-reduction method. It is revealed that Fe could effectively facilitate the co-reduction of Mo and W precursors and the formation of HEA surface on Cu nanorod. The Faradaic efficiency (FE) for ethylene and ethanol in CO2ER reaches 49.5% and 20.4%, respectively, with a total FEC2 of 69.9% and current density of 250 mA cm−2 at −1.1 V vs. RHE. Theoretical calculations reveal that the Cu–W–Fe combination site is more active in CO2 activation and C–C coupling for C2 products than other sites. This work underscores the importance of HEA in overcoming the constraints of linear scaling relationships and improving the selectivity for C2 products in CO2ER.
2025, 44(5): 100572
doi: 10.1016/j.cjsc.2025.100572
Abstract:
Aberration-corrected annular dark-field scanning transmission electron microscopy (ADF-STEM) is a powerful tool for structural and chemical analysis of materials. Conventional analyses of ADF-STEM images rely on human labeling, making them labor-intensive and prone to subjective error. Here, we introduce a deep-learning-based workflow combining a pix2pix network for image denoising and either a mathematical algorithm local intensity threshold segmentation (LITS) or another deep learning network UNet for chemical identification. After denoising, the processed images exhibit a five-fold improvement in signal-to-noise ratio and a 20% increase in accuracy of atomic localization. Then, we take atomic-resolution images of Y–Ce dual-atom catalysts (DACs) and Fe-doped ReSe2 nanosheets as examples to validate the performance. Pix2pix is applied to identify atomic sites in Y–Ce DACs with a location recall of 0.88 and a location precision of 0.99. LITS is used to further differentiate Y and Ce sites by the intensity of atomic sites. Furthermore, pix2pix and UNet workflow with better automaticity is applied to identification of Fe-doped ReSe2 nanosheets. Three types of atomic sites (Re, the substitution of Fe for Re, and the adatom of Fe on Re) are distinguished with the identification recall of more than 0.90 and the precision of higher than 0.93. These results suggest that this strategy facilitates high-quality and automated chemical identification of atomic-resolution images.
Aberration-corrected annular dark-field scanning transmission electron microscopy (ADF-STEM) is a powerful tool for structural and chemical analysis of materials. Conventional analyses of ADF-STEM images rely on human labeling, making them labor-intensive and prone to subjective error. Here, we introduce a deep-learning-based workflow combining a pix2pix network for image denoising and either a mathematical algorithm local intensity threshold segmentation (LITS) or another deep learning network UNet for chemical identification. After denoising, the processed images exhibit a five-fold improvement in signal-to-noise ratio and a 20% increase in accuracy of atomic localization. Then, we take atomic-resolution images of Y–Ce dual-atom catalysts (DACs) and Fe-doped ReSe2 nanosheets as examples to validate the performance. Pix2pix is applied to identify atomic sites in Y–Ce DACs with a location recall of 0.88 and a location precision of 0.99. LITS is used to further differentiate Y and Ce sites by the intensity of atomic sites. Furthermore, pix2pix and UNet workflow with better automaticity is applied to identification of Fe-doped ReSe2 nanosheets. Three types of atomic sites (Re, the substitution of Fe for Re, and the adatom of Fe on Re) are distinguished with the identification recall of more than 0.90 and the precision of higher than 0.93. These results suggest that this strategy facilitates high-quality and automated chemical identification of atomic-resolution images.
2025, 44(5): 100573
doi: 10.1016/j.cjsc.2025.100573
Abstract:
The sulfur-fumigation process not only induces the chemical transformation of Lycium barbarum (Lb, a widely used traditional Chinese medicine) but also severely influences human health. Given the existing challenges like the complex and time-consuming operation, as well as the high technical demands of the current detection methods for sulfur-fumed Lycium barbarum (SF-Lb), this paper employs a simple chemiresistor to carry out discrimination research between Lb and SF-Lb which have significant differences in volatolomics. The sensor is constructed by a conductive metal-organic framework (cMOF) thin film, Cu3(HHTP)2, due to its abundant active sites, excellent electron transfer performance as well as the capacity to detect specific groups of volatile organic compounds (VOCs). Consequently, the response values of Cu3(HHTP)2-based sensor to 0.5 g SF-Lb (151.74%) are significantly higher than those to normal Lb (80.07%), identifying SF-Lb simply and rapidly with an accuracy of ∼100%. Our work investigates volatolomics of SF-Lb and establishes a new rapid discrimination method for sulfur-fumed traditional Chinese herbs.
The sulfur-fumigation process not only induces the chemical transformation of Lycium barbarum (Lb, a widely used traditional Chinese medicine) but also severely influences human health. Given the existing challenges like the complex and time-consuming operation, as well as the high technical demands of the current detection methods for sulfur-fumed Lycium barbarum (SF-Lb), this paper employs a simple chemiresistor to carry out discrimination research between Lb and SF-Lb which have significant differences in volatolomics. The sensor is constructed by a conductive metal-organic framework (cMOF) thin film, Cu3(HHTP)2, due to its abundant active sites, excellent electron transfer performance as well as the capacity to detect specific groups of volatile organic compounds (VOCs). Consequently, the response values of Cu3(HHTP)2-based sensor to 0.5 g SF-Lb (151.74%) are significantly higher than those to normal Lb (80.07%), identifying SF-Lb simply and rapidly with an accuracy of ∼100%. Our work investigates volatolomics of SF-Lb and establishes a new rapid discrimination method for sulfur-fumed traditional Chinese herbs.
