Application of online near infrared spectroscopy to study the kinetics of anionic polymerization of butadiene

Online Fourier-transform near infrared (FT-NIR) spectroscopy in combination with a fiber optic probe was utilized to study the kinetics of the anionic polymerization of butadiene. The conversion of the butadiene to methylene protons in the polymer was monitored in solution polymerization conditions by monitoring the absorbance at 1632 nm. The off-line gel permeation chromatography, GPC, technique was used to validate the online FT-NIR spectroscopy method. Butadiene polymerization kinetics in cyclohexane initiated with n-butyllithium at different initiator concentrations and temperatures was studied. A phenomenological kinetic expression for the anionic polymerization of butadiene in cyclohexane initiated with n-butyllithium was determined. The predictions of the kinetic expression were in agreement with kinetic data reported in the literature.     

Parameterized approximations for the two-sided assortment optimization

We consider the problem faced by an online service platform that matches suppliers with consumers. Unlike traditional matching models, which treat them as passive participants, we allow both sides of the market to exercise their choices. To model this setting, we introduce a two-sided assortment optimization model wherein each participant's choice is modeled using a multinomial logit choice function, and the platform's objective is to maximize its expected revenue. We first show that the problem is NP-hard even when the number of suppliers is limited to two and provide a mixed-integer linear programming formulation. Next, we discuss two simple greedy heuristics and argue that these can lead to arbitrarily bad solutions. We then develop relaxations that provide upper and lower bounds and investigate the tightness of these relaxations by obtaining parametric approximation guarantees. Finally, we present numerical results on synthetic data demonstrating the practical utility of these relaxations.     

借鉴梅西大学经验开展农科有机化学在线教学

Massey University is a world-leading university in remote-instruction, online and mixed teaching based on the Stream teaching platform. This paper analyzed the advantages of the Stream teaching platform, resource utilization, course format, teaching team cooperation and course evaluation in Massey University. The paper also analyzed the enlightenment of teaching experience of Massey University to undergraduate teaching. During the outbreak of COVID-19 epidemic, drawing on Massey's experience, combined with the rapid development of information technology in China, the teaching team of organic chemistry adopted the multi-teaching strategy of "teacher-centered and student-centered", and the teaching mode of "teacher-led and self-taught by students". The online teaching practice of organic chemistry was carried out in agriculture university. It has been demonstrated that this model can effectively improve teaching effects.     

单离子束技术概述

 对单离子束的发展和应用作了介绍。结合我国首台单离子束装置CAS-LIBB,综合讨论了准直器限流型和静电透镜聚焦型两种典型单离子束的技术结构。限流型结构简单但定位精度有限,聚焦型条件苛刻但可获得亚微米束,是单离子束发展的趋势。评估了前探测、全前置探测和后探测3种单离子束探测方式及其特点,研究了这3种探测方式对辐照离子的计数精度和单离子束品质产生的影响。对CAS-LIBB装置研制了光导型全前置探测器以提高计数精度和束流品质。最后设计了快速荧光在线检测技术方案。     

Investigating undergraduate mathematics learners’ cognitive engagement with recorded lecture videos

The use of recorded lecture videos (RLVs) in mathematics instruction continues to advance. Prior research at the post-secondary level has indicated a tendency for RLV use in mathematics to be negatively correlated with academic performance, although it is unclear whether this is because regular users are generally weaker mathematics students or because RLV use is somehow depressing student learning. Through the lens of cognitive engagement, a quasi-experimental pre- and post-test design study was conducted to investigate the latter possibility.

Cognitive engagement was operationalized using the Revised Two-Factor Study Process Questionnaire (R-SPQ-2F), which measures learning approaches on two major scales: surface and deep. In two mathematics courses at two universities, in Australia and the UK, participants were administered the questionnaire near the course start and finish. Overall findings were similar in both contexts: a reduction in live lecture attendance coupled with a dependence on RLVs was associated with an increase in surface approaches to learning.

This study has important implications for future pedagogical development and adds to the sense of urgency regarding research into best practices using RLVs in mathematics.     

Nanosized cation exchanger for the electrophoretic separation and preconcentration of catecholamines and amino acids

The first example of application of nanosized polystyrene-based cation exchanger (NSCE) with sulfo groups as a dynamic coating of capillary walls was demonstrated. The conditions of dynamic coating formation were optimized and ensured the long-term stability of the coating. Capillary-to-capillary and day-to-day repeatabilities were 4% and 3%, correspondingly. The NSCE coating stability at various pH and influence of pH on the EOF mobility were investigated. The developed NSCE-modified coated capillaries provided improved resolution (R_s = 0.9–3.2 for catecholamines and R_s = 1.7–2.8 for amino acids) and efficiencies (330–520 ×10³ t.p./m) of basic analytes, which are 1.5 times higher compared to untreated capillary. The optimized conditions were as follows: 50 mM phosphate buffer solution at pH 2.2 with 5 μM NSCE. The effect of the NSCE concentration in BGE on the electrophoretic mobilities of the analytes was investigated. The various online concentration techniques were tested in order to decrease the LODs. The simultaneous application of NSCE capillaries and field-amplified sample stacking provided the lowest LODs of catecholamines and amino acids and allowed to determine these analytes in human urine.     

Artificial intelligence-based microfluidic platforms for the sensitive detection of environmental pollutants: Recent advances and prospects

Environmental pollution and its drastic effects on human and animal health have urged governments to implement strict policies to minimize damage. The first step in applying such policies is to find reliable methods to detect pollution in various media, including water, food, soil, and air. In this regard, various approaches such as spectrophotometric, chromatographic, and electrochemical techniques have been proposed. To overcome the limitations associated with conventional analytical methods, microfluidic devices have emerged as sensitive technologies capable of generating high content information during the past few years. The passage of contaminant samples through the microfluidic channels provides essential details about the whole environment after detection by the detector. In the meantime, artificial intelligence is an ideal means to identify, classify, characterize, and even predict the data obtained from microfluidic systems. The development of microfluidic devices with integrated machine learning and artificial intelligence is promising for the development of next-generation monitoring systems. Combination of the two systems ensures time efficient setups with easy operation. This review article is dedicated to the recent developments in microfluidic chips coupled with artificial intelligence technology for the evolution of more convenient pollution monitoring systems.     

Azimuthal Dipolar Rotor Arrays on Surfaces

A set of dipolar molecular rotor compounds was designed, synthesized and adsorbed as self-assembled 2D arrays on Ag(111) surfaces. The title molecules are constructed from three building blocks: (a) 4,8,12-trioxatriangulene (TOTA) platforms that are known to physisorb on metal surfaces such as Au(111) and Ag(111), (b) phenyl groups attached to the central carbon atom that function as pivot joints to reduce the barrier to rotation, (c) pyridine and pyridazine units as small dipolar units on top. Theoretical calculations and scanning tunneling microscopy (STM) investigations hint at the fact that the dipoles of neighboring rotors interact through space through pairs of energetically favorable head-to-tail arrangements.     

在线固相萃取-高效液相色谱法测定水体中的多环芳烃

建立了在线固相萃取-液相色谱测定水体残留的多环芳烃的方法,用于测定自来水中的20种多环芳烃( PAHs)。直接进样1 mL经过过滤的水体样品,其中的被测组分富集在SPE柱( Acclaim PA II,50 mm×4.6 mm,3μm)上,在线完成净化和萃取富集;再通过阀切换将它们转移至分析流路,在Hypersil Green PAH色谱柱(150 mm ×3 mm,3μm)上分离检测。在线固相萃取流路以水和乙腈为流动相,0.4和0.6 mL/min流速梯度富集/萃取和洗脱;分析流路亦以水和乙腈为流动相,0.8 mL/min流速梯度洗脱,采用紫外254 nm检测无荧光效应的苊烯和弱荧光效应的萘,其它的多环芳烃化合物则于不同的荧光检测通道里,在其对应的最大激发/发射波长下灵敏测定。整个分析流程32 min即可完成。20种PAHs的保留时间的相对标准偏差均小于0.2％,色谱峰面积的相对标准偏差均小于1.3％(n=7);在3个浓度数量级范围内峰面积与进样质量浓度的线性相关系数均大于0.9910,0.05μg/L的自来水加标样品的回收率为57％~140％,5μg/L的自来水加标样品的回收率为85％~116％;多数有荧光响应的PAHs的方法检出限均小于0.02μg/L (S/N=3)。