大尺寸电阻加热式碳化硅晶体生长热场设计与优化

大尺寸低缺陷碳化硅(SiC)单晶体是功率器件和射频(RF)器件的重要基础材料,物理气相传输(physical vapor transport, PVT)法是目前生长大尺寸SiC单晶体的主要方法。获得大尺寸高品质晶体的核心是通过调节组分、温度、压力实现气相组分在晶体生长界面均匀定向结晶,同时尽可能减小晶体的热应力。本文对电阻加热式8英寸(1英寸=2.54 cm)碳化硅大尺寸晶体生长系统展开热场设计研究。首先建立描述碳化硅原料受热分解热质输运及其多孔结构演变、系统热输运的物理和数学模型,进而使用数值模拟方法研究加热器位置、加热器功率和辐射孔径对温度分布的影响及其规律,并优化热场结构。数值模拟结果显示,通过优化散热孔形状、保温棉的结构等设计参数,电阻加热式大尺寸晶体生长系统在晶锭厚度变化、多孔介质原料消耗的情况下均能达到较低的晶体横向温度梯度和较高的纵向温度梯度。     

离子对反相高效液相色谱法同时测定尿液中复方α-酮酸片的5种有效成分

建立了同时测定尿液中复方α-酮酸片5种有效成分(消旋羟蛋氨酸钙(HMACa)、酮缬氨酸钙(KVCa)、消旋酮异亮氨酸钙(KILCa)、酮亮氨酸钙(KLCa)和酮苯丙氨酸钙(KPACa))的离子对反相高效液相色谱法。分别考察了离子对试剂浓度、缓冲盐浓度和流动相pH值等参数对分离情况的影响。最终采用Waters Symmetry C18色谱柱(250 mm×4.6 mm,5μm);以乙腈和含15 mmol/L四丁基氢氧化铵的20 mmol/L磷酸盐缓冲液(pH 7.0)为流动相进行梯度洗脱,流速为1.0 mL/min;柱温为35℃;检测波长为210 nm。在上述条件下,5种有效成分得到很好的分离,并且不受尿液中内源性基质的干扰,在20~200 mg/L范围内线性关系良好(r≥0.999 0);HMACa、KVCa、KILCa、KLCa和KPACa的检出限(S/N=3)分别为3.0、5.0、3.6、5.7和2.5 mg/L;定量限(S/N=10)分别为9.6、16.7、12.0、19.0和8.3 mg/L;日间、日内精密度均小于7%;平均回收率在86.79%~112.00%之间,RSD小于9%(n=5)。该方法准确,灵敏度高,重现性好,适用于尿液中这5种有效成分的检测。     

Regiocontrol in the oxidative Heck reaction of indole by ligand-enabled switch of the regioselectivity-determining step

Efficient control of regioselectivity is a key concern in transition-metal-catalyzed direct C–H functionalization reactions. Various strategies for regiocontrol have been established by tuning the selectivity of the C–H activation step as a common mode. Herein, we present our study on an alternative mode of regiocontrol, in which the selectivity of the C–H activation step is no longer a key concern. We found that, in a reaction where the C–H activation step exhibits a different regio-preference from the subsequent functionalization step, a ligand-enabled switch of the regioselectivity-determining step could provide efficient regiocontrol. This mode has been exemplified by the Pd(ii)-catalyzed aerobic oxidative Heck reaction of indoles, in which a ligand-controlled C3-/C2-selectivity was achieved for the first time by the development of sulfoxide-2-hydroxypyridine (SOHP) ligands.

Ligand-enabled switch of the regioselectivity-determining step allowed for efficient regiocontrol in the aerobic oxidative Heck reaction of indole.     

NO分子宏观气体热力学性质的理论研究

采用量子统计系综理论,研究了基态NO分子宏观气体摩尔熵、摩尔内能、摩尔热容等热力学性质.首先应用课题组前期建立的变分代数法(variational algebraic method, VAM)计算获得了基态NO分子的完全振动能级,得到的VAM振动能级作为振动部分,结合欧拉-麦克劳林渐进展开公式的转动贡献,应用于经典的热力学与统计物理公式中,从而计算得到了1000-5000 K温度范围内NO宏观气体的摩尔内能、摩尔熵和摩尔热容.将不同方法计算得到的摩尔热容结果分别与实验值进行比较,结果表明基于VAM完全振动能级获得的结果优于其他方法获得的理论结果.振动部分采用谐振子模型对无限能级求和计算热力学性质的方法有一定的局限性,应当使用有限的完全振动能级进行统计求和.     

紫色球杆菌视紫红质光谱特性的机器学习研究

近年来，机器学习等人工智能技术被应用于蛋白质工程，其在蛋白质结构、功能预测、催化活性等研究中具有独特优势。在未知蛋白质结构的情况下，将蛋白质序列和功能特性与机器学习相结合，基于序列-活性关系（innovative sequence-activity relationship，ISAR）算法，将蛋白质氨基酸序列数字化，用快速傅里叶变换（fast four transform，FFT）进行预处理，再进行偏最小二乘回归建模，可在数据集较少情况下拟合得到最佳模型。通过机器学习对紫色球杆菌视紫红质（gloeobacter violaceus rhodopsin，GR）的突变体蛋白质氨基酸序列与光谱最大吸收波长进行建模，获得了最佳模型。用最佳索引LEVM760106建模得到的确定系数R² 为0.944，均方误差E为11.64。用小波变换进行的预处理，其R² 虽也约为0.944，但E大于11.64，不及FFT进行的预处理。方法较好地解决了蛋白质序列与功能特性之间的数学建模问题，在蛋白质工程中可为预测更优的突变体提供支持。     

Flame-retardant effect of cross-linked phosphazene derivatives and pentaerythritol derivatives on polypropylene

Journal of Thermal Analysis and Calorimetry - A phosphazene-based flame retardant (PBFA) was synthesized by hexachlorocyclotriphosphazene and N-aminoethylpiperazine. To improve the flame retardancy...     

Unlocking the Drug Potential of the Bryostatin Family: Recent Advances in Product Synthesis and Biomedical Applications

Bryostatins are a class of naturally occurring macrocyclic lactones with a unique fast developing portfolio of clinical applications, including treatment of AIDS, Alzheimer's disease, and cancer. This comprehensive account summarizes the recent progress (2014–present) in the development of bryostatins, including their total synthesis and biomedical applications. An emphasis is placed on the discussion of bryostatin 1 , the most-studied analogue to date. This review highlights the synthetic and biological challenges of bryostatins and provides an outlook on their future development.     

A New Method of Testing and Evaluating the Quality of Refined Montan Wax: Digital Color and GC Fingerprint

To establish a new method of testing and evaluating the quality of refined montan wax (RMW), digital color and GC fingerprint technology were introduced and applied. CIE Lab color mode was used to digitize the exterior colors of RMW, and the score obtained through a fitting function was also used to reflect its quality. It is shown that they were in complete accord with the human visual perception trend. The GC fingerprint was used to characterize the internal chemical information of RMW, and the composition of its internal features was reflected through the relative retention time (RRT) and relative peak area (RPA) values. It is shown that there was a high degree of similarity between the fingerprints, while certain differences also existed. This can be used to implement effective application of RMW to aspects such as quality control, adulteration identification, and origin attributions.