Naturally degradable capsule provides a platform for sustained fragrance release.However,practical challenges such as low encapsulation efficiency and difficulty in sustained release are still limited in using fragran...Naturally degradable capsule provides a platform for sustained fragrance release.However,practical challenges such as low encapsulation efficiency and difficulty in sustained release are still limited in using fragranceloaded capsules.In this work,the natural materials sodium alginate and gelatine are dissolved and act as the aqueous phase,lavender is dissolved in caprylic/capric triglyceride(GTCC)as the oil phase,and SiO_(2) nanoparticles with neutralwettability as a solid emulsifier to form O/W Pickering emulsions simultaneously.Finally,multi-core capsules are prepared using the drop injection method with emulsions as templates.The results show that the capsules have been successfully prepared with a spherical morphology and multi-core structure,and the encapsulation rate of multi-core capsules can reach up to 99.6%.In addition,the multi-core capsules possess desirable sustained release performance,the cumulative sustained release rate of fragrance at 25℃over 49 days is only 32.5%.It is attributed to the significant protection of multi-core structure,Pickering emulsion nanoparticle membranes,and hydrogel network shell for encapsulated fragrance.This study is designed to deliver a new strategy for using sustained-release technology with fragrance in food,cosmetics,textiles,and other fields.展开更多
针对煤与瓦斯突出事故的复杂性以及数据获取困难导致预测准确率低的问题,提出基于密度的噪声应用空间聚类-改进哈里斯鹰优化-支持向量机(density based spatial clustering of applications with noise-improved Harris hawks optimizat...针对煤与瓦斯突出事故的复杂性以及数据获取困难导致预测准确率低的问题,提出基于密度的噪声应用空间聚类-改进哈里斯鹰优化-支持向量机(density based spatial clustering of applications with noise-improved Harris hawks optimization-support vector machine, DBSCAN-IHHO-SVM)预测模型。首先,选取瓦斯含量、瓦斯压力、煤层孔隙率、煤层坚固性系数作为预测指标,对数据中的缺失值采用均值填补处理,利用生成式对抗网络(generative adversarial network, GAN)扩充突出数据量。接着,采用DBSCAN从非突出数据中识别潜在危险数据,并将其作为新的突出数据。最后,引入IHHO调整SVM模型参数,将处理后的数据输入IHHO-SVM模型进行预测分析。结果表明,相比于原始SVM模型,DBSCAN-IHHO-SVM模型的整体预测准确率、危险数据识别率分别提升了5.87%、38.46%。在突出数据样本有限的情况下,DBSCAN-IHHO-SVM模型能有效挖掘非突出数据潜在信息,实现精准预警,为该领域研究提供了新思路。展开更多
文摘Naturally degradable capsule provides a platform for sustained fragrance release.However,practical challenges such as low encapsulation efficiency and difficulty in sustained release are still limited in using fragranceloaded capsules.In this work,the natural materials sodium alginate and gelatine are dissolved and act as the aqueous phase,lavender is dissolved in caprylic/capric triglyceride(GTCC)as the oil phase,and SiO_(2) nanoparticles with neutralwettability as a solid emulsifier to form O/W Pickering emulsions simultaneously.Finally,multi-core capsules are prepared using the drop injection method with emulsions as templates.The results show that the capsules have been successfully prepared with a spherical morphology and multi-core structure,and the encapsulation rate of multi-core capsules can reach up to 99.6%.In addition,the multi-core capsules possess desirable sustained release performance,the cumulative sustained release rate of fragrance at 25℃over 49 days is only 32.5%.It is attributed to the significant protection of multi-core structure,Pickering emulsion nanoparticle membranes,and hydrogel network shell for encapsulated fragrance.This study is designed to deliver a new strategy for using sustained-release technology with fragrance in food,cosmetics,textiles,and other fields.
