博文

2025年01月嘲风作品集（一）

已有 252 次阅读 2025-4-2 16:06 |个人分类:作品发表|系统分类:论文交流

▲ Vol 04 Issue 01 | January, 2025

Rapid Joule-heating synthesis of metal/carbon-based electrocatalysts for efficient carbon dioxide reduction

Weijian Guo, Xueying Cao, Ao Zhou, Wenwen Cai, Jintao Zhang

Carbon-loaded metal nanoparticles (NPs) are widely employed as functional materials for electrocatalysis. In this study, a rapid thermal shock method was developed to load various metal nanoparticles onto carbon supports. Compared to conventional pyrolysis processes, Joule heating enables rapid heating to elevated temperatures within a short period, effectively preventing the migration and aggregation of metal atoms. Simultaneously, the anchoring effect of defective carbon carriers ensures the uniform distribution of NPs on the carbon supports. Additionally, nitrogen doping can significantly enhance the electronic conductivity of the carbon matrix and strengthen the metal-carbon interactions, thereby synergistically improving catalyst performance. When used as electrocatalysts for electrocatalytic CO2 reduction, bismuth-, indium-, and tin/carbon-carrier-based catalysts exhibit excellent Faraday efficiencies of 92.8%, 86.4%, and 73.3%, respectively, for formate generation in flow cells. The influence of different metals and calcination temperatures on catalytic performance was examined to provide valuable insights into the rational design of carbon-based electrocatalysts with enhanced electrocatalytic activity.

https://www.sciencedirect.com/science/article/pii/S2772571524000251

▲ Vol 37 Issue 01 | 08 January, 2025

Piezoelectric Heterojunctions as Bacteria-Killing Bone-Regenerative Implants

Youzhun Fan, Jinxia Zhai, Zhengao Wang, Zhaoyi Yin, Haoyan Chen, Maofei Ran, Zurong Zhu, Yubin Ma, Chengyun Ning, Peng Yu, Chuanbin Mao

Heterojunctions, made of piezoelectric nanocrystals and nanowires, can generate reactive oxygen species (ROS) and heat to kill bacteria under the irradiation of near-infrared light. These heterojunctions produce electric signals under the forces applied by the stem cells grown on them and such electric signals further promote bone formation. Hence, they can not only achieve osteointegration but also eradicate implant-associated infections. More details can be found in article number 2413171 by Chengyun Ning, Peng Yu, Chuanbin Mao, and co-workers.

https://onlinelibrary.wiley.com/doi/10.1002/adma.202570006

▲ Vol 97 Issue 01 | 14 January, 2025

Advanced Mass-Spectra-Based Machine Learning for Predicting the Toxicity of Traditional Chinese Medicines

Chen Jia, Xiaofang Li, Song Hu, Guohong Liu, Jiansong Fang, Xiaoxia Zhou, Xiliang Yan, Bing Yan

Traditional Chinese medicine (TCM) has been a cornerstone of health care for centuries, valued for its preventive and therapeutic properties. However, recent decades have revealed significant toxicological concerns associated with TCMs due to their complex chemical compositions. Traditional QSAR (quantitative structure–activity relationships) models, which predict toxicity based on chemical structures, face challenges with the intricate nature of TCM compounds. In this study, we effectively resolved this issue by correlating the toxicity of TCMs with advanced analytical descriptors from electron ionization mass spectra (EI-MS) data. The optimal classification model achieved a balanced accuracy of over 0.74. Through interpretable machine learning models, we identified specific toxic components, such as 13-hexyloxacyclotridec-10-en-2-one and loliolide. We applied molecular dynamics (MD) simulations to explore the interactions of identified toxic components with crucial protein targets, using hepatic cytochrome P450 3A4 as an example. This novel approach not only enhances our understanding of the toxicological profiles of TCMs but also maximizes their therapeutic benefits while minimizing adverse effects. More importantly, our findings support the application of analytical descriptor-based machine learning in predicting the toxicity of unknown mixtures in the real environment.

https://pubs.acs.org/doi/10.1021/acs.analchem.4c05311

▲ Vol 13 Issue 02 | 14 January, 2025

Surface-Buckling-Enhanced 3D Metal/Semiconductor SERS-Active Device for Detecting Organic Chemicals

Pei-Chieh Tseng, Jing-Ling Bai, Cheng-Fang Hong, Chia-Feng Lin, Han-Yu Hsueh

A novel three-dimensional metal/semiconductor nanostructured surface-enhanced Raman scattering (SERS)-active substrate was constructed through Ag nanoparticles decoration of flower-like ZnO nanorods (fZnOs) on a buckled substrate, achieving a low detection limit of 10−9 M and a high enhancement factor of 2.43 × 108. More details can be found in article 2401874 by Han-Yu Hsueh and co-workers.

https://onlinelibrary.wiley.com/doi/10.1002/adom.202570045

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