WeChat Mini Program
Old Version Features

    • Highly Efficient and Recyclable Acid Catalysis Using High-Temperature Resistant O/W Emulsion Stabilized by Dodecyl Phosphonic Acid

    Ruizhao Cai, Jiao,Yang Li, Lulu Yang,Yuhai Tang, Jiale Wu, Shuangshuang Cai, Ansar Abbas,Minghui Zhang,Silong Xu

    CATALYSIS SCIENCE & TECHNOLOGY（2025）

    Cited 0|Views3
    Abstract
    Acid-catalyzed reactions play an important role in the field of organic synthesis in synthesizing a large number of organic compounds. However, conventional acid catalysts have many shortcomings, such as low stability, difficulty in product separation and poor reusability. In this study, we achieved efficient and recyclable acid catalysis via a pH-responsive O/W emulsion system stabilized by dodecyl phosphonic acid (DPA) alone. The O/W emulsion exhibited excellent characteristics of high-temperature resistance and adjustable oil-droplet size at different temperatures. Moreover, the emulsion state can undergo rapid and reversible transitions between emulsification and demulsification by adjusting the pH levels. Impressively, the emulsified acid-catalysis system significantly enhanced the reaction efficiency of the Knoevenagel condensation reaction. Subsequently, a straightforward pH adjustment effortlessly realized product separation and ensured the recyclability of the catalytic system. This environmentally friendly and economically viable system offers a new approach to achieve efficient and green catalysis in organic synthesis processes.
    More
    Translated text
    求助PDF
    上传PDF
    View via Publisher
    Bibtex
    AI Read Science
    AI Summary
    AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
    Example
    Background
    Key content
    Introduction
    Methods
    Results
    Related work
    Fund
    Key content
    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
    • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
    Upload PDF to Generate Summary
    Must-Reading Tree
    Example
    Generate MRT to find the research sequence of this paper
    Data Disclaimer
    The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
    Chat Paper
    Summary is being generated by the instructions you defined