Polymer 4D printing: Advanced shape-change and beyond

4D printing is an exciting branch of additive manufacturing. It relies on established 3D printing techniques to fabricate objects in much the same way. However, structures which fall into the 4D printed category have the ability to change with time, hence the “extra dimension.” The common perception of 4D printed objects is that of macroscopic single-material structures limited to point-to-point shape change only, in response to either heat or water. However, in the area of polymer 4D printing, recent advancements challenge this understanding. A host of new polymeric materials have been designed which display a variety of wonderful effects brought about by unconventional stimuli, and advanced additive manufacturing techniques have been developed to accommodate them. As a result, the horizons of polymer 4D printing have been broadened beyond what was initially thought possible. In this review, we showcase the many studies which evolve the very definition of polymer 4D printing, and reveal emerging areas of research integral to its advancement.     

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.     

One-pot,one-step,and selective terpolymerization of ethylene oxide,propylene oxide,and COS to copoly(thioether)s with tunable thermal properties

Facile construction of sulfur-rich polymers using readily available raw chemicals is an area aggressively pursued but challenging. Herein we use common feedstocks of ethylene oxide (EO), propylene oxide (PO), and carbonyl sulfide (COS) to synthesize copoly(thioether)s which are traditionally produced from unpleasant and difficult to store episulfides. In this protocol, the EO/COS coupling selectively generates a pure poly(ethylene sulfide) (PES) with melting temperature (T_m) values up to 172°C and high yields up to 98%. The EO/PO/COS terpolymerization leads to the incorporation of soft poly(propylene sulfide) (PPS) and hard PES segments together, affording a random PES-co-PPS copoly(thioether) with the complete consumption of EO and PO. Additionally, by simply varying the EO/PO feeding ratio, the obtained copoly(thioether)s possess tunable thermal properties, T_m values in the range of 76–144°C, and excellent solubility. These copolymerizations are conducted in one-pot/one-step at industrially favored reaction temperatures of 100–120°C using catalysts of common organic bases, suggesting a facile and practical manner. Especially, the copoly(thioether) exhibits high refractive indices up to 1.68 owing to its high sulfur content, suggesting a broad application prospect in optical materials.     

Calcium-based coordination polymers from a solvothermal synthesis of HKUST-1 in 3D printed autoclaves

A mixed-metal 1D coordination polymer [CaCu(HBTC)₂(H2O)₈]_n (where H₃BTC – benzene-1,3,5-tric arboxylic acid) was obtained in a solvothermal synthesis of a well-known copper-containing metal–organic framework [Cu₃(BTC)₂(H₂O)₃]_n (HKUST-1) in autoclaves 3D-printed from commercial polypropylene. This material was a source of calcium ions, apparently, leaking from a colorant (calcium carbonate) promoted by glacial acetic acid as a modulator used to produce large single crystals of HKUST-1. This finding was confirmed by elemental analysis and a model experiment that resulted in a new calcium-based 1D coordination polymer [Ca(H₂BTC)₂(H₂O)₅]_n under the same solvothermal conditions with no copper or calcium salts put into a 3D-printed autoclave.     

石墨基液流电池复合双极板

液流电池是一种安全性高、使用寿命长、可扩展的大规模储能系统,可以协助电网调峰储能,提高能源利用率,发展前景广阔。双极板是液流电池的重要组成部分。功能上起到了分隔、串联电池、传导电流、为电堆提供结构支撑等作用。从成本构成角度看,双极板的价格占电堆成本的比重也较大。开发高性能、低成本的双极板对加快液流电池的商业化应用具有重要意义,也是目前业界的迫切需求。虽然文献上报道了许多针对液流电池双极板开发的工作,但是目前高性能、低成本的液流电池双极板产品仍无法充分满足市场需求。本文着重介绍了石墨基复合双极板的研究现状,介绍了材料选择、工艺流程对关键性能的影响,对相关工作进行了评述,并为液流电池双极板的开发提出了建议。     

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.     

A post curing strategy toward the feasible covalent adaptable networks in polyacrylate latex films

The implementation of covalent adaptable networks (CANs) in general resin system is becoming attractive. In this work, we propose a simple post-curing strategy based on the core-shell structured acrylate latex for the achievement on both the improved general performance and the CANs characteristics in latex films. The building to the CANs was relied on the introduction of 4,4′-diaminophenyl disulfide as the curing agent, which cured the acetoacetoxy decorated shell polymer through the ketoamine reaction. The metathesis reaction of aromatic disulfides in the crosslinking segments enabled the thermally induced dynamic behavior of the network as revealed in the stress relaxation tests by comparison with other diamine crosslinking agents without the incorporation of disulfide. The synergism of the dynamic crosslinking of the shell polymer and static crosslinking in the core polymer contributed to the improved mechanical strength (15 MPa, strain% = 250%) and the suppressed water adsorption (~1% in 24 h of soaking) of the latex film, which exhibited above 90% of recovery in both strength and strain from a cut-off film damage within 1 h at 80°C. Moreover, the cured latex film could be recycled, and 75% of the mechanical performance was regained after three fragmentation-hot-pressing cycles. These, in addition with the feasible and environmental friendly characteristics, suggest a sustainable paradigm toward the smart thermosetting latex polymers.     

An Update on Molecularly Imprinted Polymer Design through a Computational Approach to Produce Molecular Recognition Material with Enhanced Analytical Performance

Molecularly imprinted polymer (MIP) computational design is expected to become a routine technique prior to synthesis to produce polymers with high affinity and selectivity towards target molecules. Furthermore, using these simulations reduces the cost of optimizing polymerization composition. There are several computational methods used in MIP fabrication and each requires a comprehensive study in order to select a process with results that are most similar to properties exhibited by polymers synthesized through laboratory experiments. Until now, no review has linked computational strategies with experimental results, which are needed to determine the method that is most appropriate for use in designing MIP with high molecular recognition. This review will present an update of the computational approaches started from 2016 until now on quantum mechanics, molecular mechanics and molecular dynamics that have been widely used. It will also discuss the linear correlation between computational results and the polymer performance tests through laboratory experiments to examine to what extent these methods can be relied upon to obtain polymers with high molecular recognition. Based on the literature search, density functional theory (DFT) with various hybrid functions and basis sets is most often used as a theoretical method to provide a shorter MIP manufacturing process as well as good analytical performance as recognition material.     

Sentinel-2卫星的多光谱轻量级船舶目标检测算法

近年来深度卷积神经网络在可见光船舶检测方面取得了显著的进展，然而，大多数相关研究是通过改进大型的网络结构来提高检测性能，因此加大了对更高计算机性能的需求。此外，可见光图像难以在云、雾、海杂波、黑夜等复杂场景检测到船舶。针对以上问题，提出了一种融合红（red, R）、绿（green, G）、蓝（blue, B）和近红外（NIR）4个波段光谱信息的由粗到精细的轻量型船舶检测算法。与现有的方法中根据光谱特性利用水体检测算法提取水体区域不同之处是该算法是利用改进的水体检测算法来提取船舶候选区域。为获取更准确的候选区域，对船舶、厚云、薄云、平静海面、杂波海面5种场景中4个波段的像素值进行了统计分析，选取近红外大于阈值作为辅助判断，并以其中心点获取候选区域32×32大小的切片，并对切片进行非极大值抑制，由此获得了船舶粗检测结果。随后构建了轻量级LSGFNet网络对船舶候选区域切片进行精细识别。构建的网络融合了1×1卷积提取的波谱特征与3×3的提取几何特征，为防止光谱特征与几何特征的信息在融合时“信息不流通”，在LSGFNet网络中引入了ShuffleNet中的通道打乱机制，并减小了模型结构，与典型的轻量级网络相比具有更好的效果且模型较小。最后，利用Sentinel-2卫星多光谱10 m分辨率数据构建了512×512大小的1 120组数据进行粗检测，以及32×32大小的6 014组数据进行精细网络训练，其中候选区域粗提取的查全率为98.99%，精细识别网络精确度为96.04%，不同场景下的平均精确度为92.98%。实验表明该算法在抑制云层、海浪杂波等干扰的复杂背景下具有较高的检测效率，且训练时间短、计算机性能需求低。     

Buffering effects on the solution behavior and hydrolytic degradation of poly(β-amino ester)s

With a vast, synthetically accessible compositional space and highly tunable hydrolysis rates, poly(β-amino ester)s (PBAEs) are an attractive degradable polymer platform. Leveraging PBAEs in a wide range of applications hinges on the ability to program degradation, which, thus far, has been frustrated by multiple confounding phenomena contributing to the degradation of these charged polyesters. Basic conditions accelerate hydrolysis, yet reduce solubility, limiting water access to amines and esters. Further, the high buffering capacity of PBAEs can render buffers ineffective at controlling solution pH. To unify understanding of PBAE degradation and solution properties, this study examines PBAE hydrolysis as a function of pH and buffer concentration as well as polymer hydrophobicity. At low buffer concentrations, the PBAE amines and the acid produced during hydrolysis control solution pH. Meanwhile, at high buffer concentrations that afford relatively constant pH, hydrolysis rate increases with pH, despite the reduced PBAE solubility. Increasing the hydrophobic content of PBAEs eventually hinders the capacity of the polymer to accept protons from solution, limiting the pH increase and slowing hydrolysis. These studies showcase the role of buffering on the pH-dependent degradation and solution properties of PBAEs, providing guidance for programming degradation in applications ranging from drug delivery to thermosets.