头发锌含量测定的应用价值评价

以114例2－5岁儿童为对象，同时取其末梢血和头发，测定锌含量。以全血锌值为标准，评价头锌测定的应用价值。结果显示，头发锌测定的灵敏度可达86．1％，特异度为52．4％，符合率为73．7％。     

The Intelligent Properties of Micro－reactors for Preparating Nanoparticles

TiO2 nanoparticles were synthesized by using micro-reactors. The shape and size of the nanoparticles produced from the original micro-reactors and the five times recycled micro-reactorsmother liquor were investigated on transmission electron microscopy (TEM) by using the original sample, freeze prepared sample, and dyeing treated sample, respectively. UV-VIS spectrometry was used to study the growth process of TiO2 nanoparticles in main reactors. The results showed that micro-reactors with nanometer magnitude had spherical or oval structures, and could restore to their original structure after they were destroyed. The products prepared in the original micro-reactors were similar to that in the micro-reactors recycled for many times, suggesting that the micro-reactors had memory function.     

生物质在流化床中的空气-水蒸气气化研究

以流化床为反应器，对生物质的空气-水蒸气气化特性进行了研究。考察了一些主要参变量，如温度 (700 ℃～900 ℃)、水蒸气/生物质比(0～4.04)、空气当量比(0.19～0.27)以及生物质粒度(0.2 mm～0.9 mm)等对气化结果的影响。在实验研究的条件范围内，生物质产气率在1.43 m3/kg～2.57 m3/kg范围内变化，产气的低热值在6 741 kJ/m3～9 143 kJ/m3范围内变化。实验结果表明：较高的气化温度有利于氢的产生；但气化温度过高会使气体热值下降；与常规的空气气化相比，水蒸气的加入使生物质气化产气率显著提高，但水蒸气加入量过多使气化温度下降，产气率和产气热值降低；生物质颗粒粒度的大小对产气组分的分布和产气率均有影响，较小颗粒的生物质会产生较多的CH4、CO和较少的CO2。     

LaNi4.7Al0.3单颗粒微电极电化学行为的研究

报道了一种单颗粒微电极制备新方法, 并研究了LaNi4.7Al0.3球形单颗粒微电极的电化学行为.     

纳米氧化铝负载双硫腙分离富集-原子吸收法测定地质样品中的金、铂、钯的研究

金、铂、钯在地质样品中的含量甚微,国内外常采用ICP-AES,ICP-MS和ETAAS直接测定。FAAS法由于仪器便宜、操作方便,也广泛应用于预富集后的痕量贵金属的分析。目前,在测定贵金属的分析方法中,常采用固相萃取法富集分离样品,主要的固相萃取剂有:无机吸附剂,交联树脂[1],螯合树脂[     

手性二胺修饰的Ru/γ-Al2O3催化剂催化芳香酮不对称加氢

研究了用手性修饰剂(1S,2S)-(-)-1,2-二苯基乙二胺修饰的负载型钌催化剂(Ru/γ-Al2O3)催化芳香酮的不对称加氢反应,在KOH的异丙醇溶液中,10～20℃,pH2=5 MPa条件下,芳香酮及其衍生物加氢产物的ee值达79.5%～85.0%,2-乙酰基噻吩加氢产物的ee值可达86.2%.此催化剂制备简单,容易与产物分离,重复使用4次,对映选择性基本保持不变.     

纳米Re2O7的萃取法制备及光催化特性研究

本工作从N235-正庚烷萃取体系中，以饱和萃取法制得前体物和纳米粉体Re₂O₇，平均粒径30 nm。以此纳米粉为光催化剂，研究了光降解甲基橙染料的最佳条件，并在相同条件下，与非纳米Re₂O₇及工业常用的纳米TiO₂进行比较，光降解甲基橙能力大小为：纳米Re₂O₇ > 锐钛矿型纳米TiO₂ > 非纳米Re₂O₇。     

Synthesis of Tetrahydrofuran and Tetrahydropyran Derivatives Catalyzed by Tungstophosphoric Acid in Ionic Liquid

Synthesis of tetrahydrofuran and tetrahydropyran derivatives catalyzed by tungstophosphoric acid （H3PW12040） were conveniently performed with high yield from the corresponding unsaturated alcohols in ionic liquid. Sufuric acid （H2SO4）, trifluoromathanesulfonic acid （TfOH） and p-toluenesulfonic acid （TsOH） were also explored for preparing these products in ionic liquid. The catalysts and ionic liquid can be easily recovered and reused.     

贵金属对钴基催化剂上肉桂醛选择加氢反应的影响

 研究了贵金属改性的Co／γ－Al2O3催化剂上的肉桂醛选择加氢反应．结果表明，通过Pt，Pd和Ru贵金属改性，提高了催化剂的活性，但只有Pt改性的催化剂具有较高的选择性．w（Pt）＜0．5％时，催化剂的活性随着Pt含量的增加呈直线升高，当w（Pt）＝0．5％时，催化剂活性可提高近5倍，但催化剂的选择性变化很小．XRD结果表明，催化剂经还原后，γ－Al2O3上的钴主要为α－Co0．TPR结果表明，Pt的加入提高了Co3O4的还原性能，且Pt含量越高，Co3O4的还原温度越低．XPS结果表明，Pt改性的催化剂样品，其Co3O4大部分被还原为Co0．由于Pt与Co具有协同效应，故Pt改性的Co／γ－Al2O3催化剂既具有较高的活性，又具有很高的选择性．     

Evaluating and clustering retrosynthesis pathways with learned strategy

With recent advances in the computer-aided synthesis planning (CASP) powered by data science and machine learning, modern CASP programs can rapidly identify thousands of potential pathways for a given target molecule. However, the lack of a holistic pathway evaluation mechanism makes it challenging to systematically prioritize strategic pathways except for using some simple heuristics. Herein, we introduce a data-driven approach to evaluate the relative strategic levels of retrosynthesis pathways using a dynamic tree-structured long short-term memory (tree-LSTM) model. We first curated a retrosynthesis pathway database, containing 238k patent-extracted pathways along with ∼55 M artificial pathways generated from an open-source CASP program, ASKCOS. The tree-LSTM model was trained to differentiate patent-extracted and artificial pathways with the same target molecule in order to learn the strategic relationship among single-step reactions within the patent-extracted pathways. The model achieved a top-1 ranking accuracy of 79.1% to recognize patent-extracted pathways. In addition, the trained tree-LSTM model learned to encode pathway-level information into a representative latent vector, which can facilitate clustering similar pathways to help illustrate strategically diverse pathways generated from CASP programs.

Tree-structured long short-term memory neural model learns to understand the retrosynthesis design strategies from patent-extracted retrosynthetic pathway data.