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...     

A Novel Ternary Composite of Polyurethane/Polyaniline/Nanosilica with Antistatic Property and Excellent Mechanical Strength: Preparation and Mechanism

Chinese Journal of Polymer Science - Antistatic and strength properties are of vital importance for polyurethane rubber used in moving parts of many industrial instruments. Herein, polyurethane was...     

新型功能碳材料的高压截获

高性能功能材料在诸多领域具有广泛的应用前景,是人们一直关注的研究热点。高压可以有效地改变物质的原子间距和成键方式,是获得新型功能材料的重要途径。在碳材料的高压研究中,许多有趣的功能碳材料,如光学透明碳、高强度弹性碳和超硬非晶碳等,已经通过不同的碳前驱体合成。本文简要介绍了作者近年来在低维碳基纳米复合材料高压研究中取得的进展,基于设计的不同低维碳前驱体,高压下截获了具有超硬特性、新型压致共价聚合及发光增强的碳材料。     

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...     

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,...     

Special John-Nirenberg-Campanato spaces via congruent cubes

Let p ∈ [1, ∞), q ∈ [1, ∞), α∈ R, and s be a non-negative integer. Inspired by the space JNp introduced by John and Nirenberg(1961) and the space B introduced by Bourgain et al.(2015), we introduce a special John-Nirenberg-Campanato space JN^con_(p,q,s) over Rⁿ or a given cube of R;with finite side length via congruent subcubes, which are of some amalgam features. The limit space of such spaces as p →∞ is just the Campanato space which coincides with the space BMO(the space of functions with bounded mean oscillations)when α = 0. Moreover, a vanishing subspace of this new space is introduced, and its equivalent characterization is established as well, which is a counterpart of the known characterization for the classical space VMO(the space of functions with vanishing mean oscillations) over Rⁿ or a given cube of Rⁿ with finite side length.Furthermore, some VMO-H¹-BMO-type results for this new space are also obtained, which are based on the aforementioned vanishing subspaces and the Hardy-type space defined via congruent cubes in this article. The geometrical properties of both the Euclidean space via its dyadic system and congruent cubes play a key role in the proofs of all these results.     

基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高.