Effect of monomer hydrophilicity on ARGET–ATRP kinetics in aqueous mini-emulsion polymerization

Activators regenerated by electron transfer (ARGET) atom transfer radical polymerization (ATRP)-based aqueous miniemulsion polymerization where the polymerization takes place in the stabilized monomer droplets is described. In this work, we compared styrene, n-butyl methacrylate (nBMA) and tert-butyl methacrylate (tBMA) and investigated the influence of their hydrophobicity on dispersity, molecular weight and particle stability based their partition coefficients (logP) (2.67, 2.23, and 1.86, respectively). Tetrabutylammonium bromide (TBAB) was used as a phase transfer agent for the controlled delivery of Cu²⁺-Br/tris(2-pyridylmethyl)amine (TPMA), a hydrophilic catalyst, into monomer droplets of varying hydrophobicity. The resulting dispersity and particle stability of each polymer is a function of its logP value, with the most hydrophobic monomer (styrene) displaying the narrowest dispersity and most control (Đ < 1.3), and the most hydrophilic polymer poly(tert-butyl methacrylate) (PtBMA) having reduced emulsion stability, determined by the observation of aggregate formation. Selected polymerization parameters, including effects of total ascorbic acid feed concentration and the monomer concentration and their effects on dispersity are reported. The controlled polymerizations of hydrophilic monomers using ARGET-ATRP in miniemulsion conditions and understanding the effect of monomer hydrophilicity on the emulsion stability will broaden the use of ARGET-ATRP in emulsion polymerization for the synthesis of polymer-grafted nanoparticles with hydrophilic corona.     

Pattern transition and regulation in a subthalamopallidal network under electromagnetic effect

Although the significant roles of magnetic induction and electromagnetic radiation in the neural system have been widely studied, their influence on Parkinson's disease (PD) has yet to be well explored. By virtue of the magnetic flux variable, this paper studies the transition of firing patterns induced by magnetic induction and the regulation effect of external magnetic radiation on the firing activities of the subthalamopallidal network in basal ganglia. We find: (i) The network reproduces five typical waveforms corresponding to the severity of symptoms: weak cluster, episodic, continuous cluster, episodic, and continuous wave. (ii) Magnetic induction is a double-edged sword for the treatment of PD. Although the increase of magnetic coefficient may lead the physiological firing activity to transfer to pathological firing activity, it also can regulate the pathological intensity firing activity with excessive β-band power transferring to the physiological firing pattern with weak β-band power. (iii) External magnetic radiation could inhibit continuous tremulous firing and β-band power of subthalamic nucleus (STN), which means the severity of symptoms weakened. Especially, the bi-parameter plane of the regulation region shows that a short pulse period of magnetic radiation and a medium level of pulse percentage can well regulate pathological oscillation. This work helps to understand the firing activity of the subthalamopallidal network under electromagnetic effect. It may also provide insights into the mechanisms behind the electromagnetic therapy of PD-related firing activity.     

High-efficient surface tailoring via reverse atom transfer radical polymerization and reversible addition-fragmentation chain-transfer polymerization in an aqueous system initiated by a monocenter redox pair

The commonly used multi-center initiation methods always lead to the formation of quantities of homopolymer in the surface tailoring based on reverse atom transfer radical polymerization (ATRP) and reversible addition-fragmentation chain-transfer (RAFT) polymerization. In this study, a monocenter redox pair constructed of silica bearing tert-butyl hydroperoxide groups and ascorbic acid (SiO₂-TBHP/AsAc) was applied to substitute the commonly used initiation method of R-supported RAFT grafting polymerization. All the propagating radicals were restricted on the surface of solid particles during the whole procedure theoretically, resulting in a higher grafting efficiency of 95.1% combined with the “controllable” feature at 10 h. This redox pair was also used to initiate the reverse ATRP in miniemulsion successfully with a grafting efficiency of 86.3% at 10 h. The grafting efficiency obtained under this monocenter initiation method was significantly higher than that of the frequently reported surface modification by reverse ATRP and RAFT polymerization. In addition, the high-efficient surface tailoring was traced and confirmed by nuclear magnetic resonance, Fourier transform infrared, X-ray photoelectron spectroscopy, thermogravimetric analysis, transmission electron microscopy, and other analysis tests. The advantage of this monocenter redox pair will open a new avenue for the potential “high-efficient” surface tailoring of various materials.     

Design consideration and modelling studies of ultrasound and ultraviolet combined approach for shelf-life enhancement of pine apple juice

Although both ultraviolet (UV) radiation and ultrasound (US) treatment have their capabilities in microbial inactivation, applying any one method alone may require a high dose for complete inactivation, which may affect the sensory and nutritional properties of pineapple juice. Hence, this study was intended to analyse and optimise the effect of combined US and UV treatments on microbial inactivation without affecting the selected quality parameters of pineapple juice. US treatment (33 kHz) was done at three different time intervals, viz. 10 min, 20 min and 30 min., after which, juice samples were subjected to UV treatment for 10 min at three UV dosage levels, viz. 1 J/cm², 1.3 J/cm², and 1.6 J/cm². The samples were evaluated for total colour difference, pH, total soluble solids (TSS), titrable acidity (TA), and ascorbic acid content; total bacterial count and total yeast count; and the standardization of process parameters was done using Response Surface Methodology and Artificial Neural Network. The results showed that the individual, as well as combined treatments, did not significantly impact the physicochemical properties while retaining the quality characteristics. It was observed that combined treatment resulted in 5 log cycle reduction in bacterial and yeast populations while the individual treatment failed. From the optimization studies, it was found that combined US and UV treatments with 22.95 min and1.577 J/cm² ensured a microbiologically safe product while retaining organoleptic quality close to that of fresh juice.     

Visible light-driven acridone catalysis for atom transfer radical polymerization

Acridone as a new kind of visible light photocatalyst has been developed to catalyze metal free atom transfer radical polymerization (ATRP). The photocatalyst possess low excited state potential as can undergo an oxidative quenching pathway to initiate ATRP of vinyl monomers. Kinetic study and light on/off reaction demonstrate the “living”/controlled nature of the polymerization by light. Block copolymers can be achieved by using PMMA as macroinitiator to reinitiate polymerization of other vinyl monomers, which shows highly preserved Br chain-end functionality in the synthesized polymers. Moreover, the polymerization can be conducted under air atmosphere as most photocatalysts need anaerobic condition, which may give inspiration of further application of this kind of photocatalyst.     

On the Fundamental Polymer Chemistry of Inverse Vulcanization for Statistical and Segmented Copolymers from Elemental Sulfur

In this concept review, the fundamental and polymerization chemistry of inverse vulcanization for the preparation of statistical and segmented sulfur copolymers, which have been actively developed and advanced in various applications over the past decade is discussed. This concept review delves into a discussion of step-growth polymerization constructs to describe the inverse vulcanization process and discuss prepolymer approaches for the synthesis of segmented sulfur polyurethanes. Furthermore, this concept review discusses the advantages of inverse vulcanization in conjunction with dynamic covalent polymerization and post-polymerization modifications to prepare segmented block copolymers with enhanced thermomechanical and flame retardant properties of these materials.     

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。     

Hyperparameter on-line learning of stochastic resonance based threshold networks

Aiming at training the feed-forward threshold neural network consisting of nondifferentiable activation functions, the approach of noise injection forms a stochastic resonance based threshold network that can be optimized by various gradient-based optimizers. The introduction of injected noise extends the noise level into the parameter space of the designed threshold network, but leads to a highly non-convex optimization landscape of the loss function. Thus, the hyperparameter on-line learning procedure with respective to network weights and noise levels becomes of challenge. It is shown that the Adam optimizer, as an adaptive variant of stochastic gradient descent, manifests its superior learning ability in training the stochastic resonance based threshold network effectively. Experimental results demonstrate the significant improvement of performance of the designed threshold network trained by the Adam optimizer for function approximation and image classification.     

基于流量测点的热网变动阻力系数优化辨识

随着供热计量系统的普及，系统可以根据负荷的变化进行调整，管网的阻力系数随即发生变化。对变动阻力系数进行优化辨识是了解供热管网实时运行状况的有效手段。提出一种基于流量监测数据的供热管网变动阻力系数优化辨识方法，并利用遗传算法进行求解。对洛阳市某小区供暖季管网实际运行数据进行验证，辨识结果的相对误差在5%以内。结果表明：该方法可以在只有流量观测数据时得到精度较高的供热管网变动阻力系数，为供热系统的运行调节提供指导。     

RNAGCN: RNA tertiary structure assessment with a graph convolutional network

RNAs play crucial and versatile roles in cellular biochemical reactions. Since experimental approaches of determining their three-dimensional (3D) structures are costly and less efficient, it is greatly advantageous to develop computational methods to predict RNA 3D structures. For these methods, designing a model or scoring function for structure quality assessment is an essential step but this step poses challenges. In this study, we designed and trained a deep learning model to tackle this problem. The model was based on a graph convolutional network (GCN) and named RNAGCN. The model provided a natural way of representing RNA structures, avoided complex algorithms to preserve atomic rotational equivalence, and was capable of extracting features automatically out of structural patterns. Testing results on two datasets convincingly demonstrated that RNAGCN performs similarly to or better than four leading scoring functions. Our approach provides an alternative way of RNA tertiary structure assessment and may facilitate RNA structure predictions. RNAGCN can be downloaded from https://gitee.com/dcw-RNAGCN/rnagcn.