Novel alternating copolyoxamides with high crystallinity and heat resistance

Two series of novel alternating copolyoxamides (PAnT-alt-n2 and PAn2-alt-62) are synthesized via solution/solid-state polycondensation (SSP). The alternating structures are analyzed carefully with ¹H NMR and ¹³C NMR spectra. The melting behaviors, thermal stabilities, crystal structures and crystallinities are systematically evaluated by DSC, TGA and WAXD. The results reveal that these alternating copolyoxamides possess almost perfect alternating chain structures and have high melting temperature (T_m > 270 °C), high crystallinity (X_c > 32%) and high decomposition temperature (T₅ > 405 °C) as well as low saturated water absorption (<3.5 wt%), which suggests that they have high potential as engineering plastic of high heat resistant.     

A Novel Biaryl Derivative from Hydrangea chinensis

Chemistry of Natural Compounds - A novel bibenzyl derivative, hydrangchinenin (1), was isolated from the stems of Hydrangea chinensis Maxim. (Hydrangeaceae). Its structure was determined on the...     

Isoflavonoids from Astragalus membranaceus Hairy Roots

Chemistry of Natural Compounds -     

Effect of temperature on the interactions between cellulose and lignin via molecular dynamics simulations

Cellulose - Heating is essential in various biomass pre-treatments and thermal conversion processes. It is of practical significance to study the characteristics of cellulose-lignin and...     

Auto-deposition of 210Bi and 210Po on nickel discs and their application in the analysis of natural waters

Journal of Radioanalytical and Nuclear Chemistry - This study presents a time-efficient method of analysing 210Pb, 210Bi, and 210Po in natural waters. The optimum pH (1.00), temperature...     

直通链路技术的发展与展望

直通链路技术己广泛应用于车联网场景。对于直通链路技术的潜在技术方向给出可行的建议，包括传统直通链路技术的增强方向，如载波聚合、使用非授权频谱等；侧行链路对于中继场景的应用扩展，包括终端到终端之间的中继，以及中继的多链接场景；在高精度定位场景使用直通链路技术。并且，给出直通链路技术与各种新技术的融合应用，如智能反射面与区块链技术，从而解决直通链路技术自身的缺陷。     

基于1D CNN与XGBoost的恶意代码纹理检测

恶意代码数量已经呈现爆炸式增长,对于恶意代码的检测防护显得尤为重要.近几年,基于深度学习的恶意代码检测方法开始出现,基于此,提出一种新的检测方法,将恶意代码二进制文件转化为十进制数组,并利用一维卷积神经网络(1 Dimention Convolutional Neural Networks,1D CNN)对数组进行分类和识别.针对代码家族之间数量不平衡的现象,该算法选择在分类预测上表现良好的XGBoost,并对Vision Research Lab中的25个不同恶意软件家族的9458个恶意软件样本进行了实验.实验结果表明,所提的方法分类预测精度达到了97％.     

Excellent UV-absorbing cotton fabric with high durability and hydrophobicity based on surface-initiated ATRP of polymerizable organic UV-absorber

Cellulose - Ultraviolet (UV) protective cotton fabric is a convenient and reliable way to protect human body from sunlight. Herein, a polymerizable UV-absorber,...