稀土元素的分离技术

对目前稀土元素分离过程中几种常用的分离技术进行了综述，使用得较多的仍然是溶剂萃取法和离子交换法，而且新方法也在不断地出现。     

氰化浸出体系中金的溶剂萃取

本文评述了金的碱性氰化溶液溶剂萃取研究与开发工作的最新进展。包括改性胺，季铵盐，磷氧化物及胍类萃取剂等。     

用边界元法提取VLSI版图电阻

介绍了ＶＬＳＩ版图验证中电阻提取的基本原理和主要方法，给出了一种新颖的基于边界元法的电阻提取算法。该算法采用变节点单元，较好地解决了实际问题中经常出现的角点问题。通过应用该算法对几个实例进行提取，证明使用本文的算法不仅在精度上而且在占用ＣＰＵ时间上都取得了令人满意的效果     

三氯乙烯与糠醛水溶液的液液平衡及萃取模拟计算

本文采用液液平衡釜了糠醛水溶液与三氯乙烯的液液平衡数据，用ＵＮＩＱＵＡＣ方程关联糠醛－水－三氯乙烯体系的液液平衡数据，以ＵＮＩＱＵＡＣ方程的模型，采用液液萃取法模拟计算糖醛和水的分离结果。     

Physicochemical characteristics and leachability of scale and sludge from Bulalo geothermal system, Philippines

Scale and sludge from Bulalo geothermal field, Philippines, have been characterized by whole rock analysis, radioactivity counting, size analysis, light microscopy, scanning electron microscopy, and X-ray diffraction. Their leachability was assessed by regulatory leaching procedures and by sequential extraction. Both scale and sludge consisted mostly of oxides of Si, Al, and Fe with no radionuclides detected. The scale had 10% S content. Sulfides and silicates were important phases in both samples having size ranges from submicron to 2 mm. Geothermal soils at Bulalo have higher than normal soil levels of As, S, Cu, Cr, Zn, and Pb but regulatory leaching tests indicated that these elements are not released. However, the sequential extraction showed that As, Cu, and Zn were leachable under extreme conditions.     

微波萃取在食品化学中的应用

介绍了微波萃取技术在食品化学中的应用。其实质是用微波对萃取溶剂及物料加热，使溶剂的渗透率和扩散率大大提高，因此对食品营养成分或风味物质可以有铲地萃取分离。     

SISAK快速化学分离装置的建立

SISAK(Short-lived Isotopes Studies by the AKUFVE technique)技术是目前使用最广泛的快速化学分离方法之一,主要应用在短寿命核素的分离和鉴别、超重元素的人工合成以及化学性质研究等方面的工作中.本文简单地叙述了SISAK技术的流程、原理和发展现状,介绍了自行建立的国内第一套基于SISAK技术的快速化学分离装置,并通过从裂变产物中分离短寿命核素这一实例验证了SISAK技术在快速化学分离中的优越性.     

溶剂萃取分离锂同位素研究Ⅱ.苏丹Ⅰ-中性配位体协萃体系萃取分离锂同位素效应探讨

文章讨论了苏丹I-中性配位体协萃体系萃取分离锂同位素中螯合剂和协萃剂的结构效应。为了获得高的同位素分离效应,螯合剂必须是弱酸性的(PK_α>11),具有强的分子内氢键及易于形成六元螯合环。协萃剂结构不仅要求无空间位阻,而且具有强的配位基。α随配位基的碱性增大而相应提高。萃取络合物中螯合环的增多亦有利于体系α的提高。此外本文还讨论了一些萃取体系的同位素富集方向和萃锂体系用于分离同位素的前景。     

Two-tier architecture for unconstrained handwritten character recognition

In this paper, we propose an approach that combines the unsupervised and supervised learning techniques for unconstrained handwritten numeral recognition. This approach uses the Kohonen self-organizing neural network for data classification in the first stage and the learning vector quantization (LVQ) model in the second stage to improve classification accuracy. The combined architecture performs better than the Kohonen self-organizing map alone. In the proposed approach, the collection of centroids at different phases of training plays a vital role in the performance of the recognition system. Four experiments have been conducted and experimental results show that the collection of centroids in the middle of the training gives high performance in terms of speed and accuracy. The systems developed also resolve the confusion between handwritten numerals.     

Linear viscoelastic properties of mixtures of 3- and 4-arm polybutadiene stars

The viscoelastic properties of a three-arm and a four-arm star polybutadiene with the same arm molecular weight (M_a) were studied. The zero-shear recoverable compliance (J⁰_e) and plateau modulus (G⁰_N) for these stars are the same. The zero-shear viscosity (η₀) of the three-arm star is 20% lower than that of the four-arm star. Mixtures of the stars had J⁰_e and G⁰_N unchanged. A $\text{50}\text{50}$ mixture of the three- and four-arm star was diluted with a low molecular weight linear polybutadiene. G⁰_N∝ø²; J⁰_e∝ø^?1 and M_e∝ø^?1, as expected for dilution with a θ-solvent.