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.     

4D Printing of Shape Memory Materials for Textiles: Mechanism,Mathematical Modeling,and Challenges

Shape memory materials (SMMs) in 3D printing (3DP) technology garnered much attention due to their ability to respond to external stimuli, which direct this technology toward an emerging area of research, “4D printing (4DP) technology.” In contrast to classical 3D printed objects, the fourth dimension, time, allows printed objects to undergo significant changes in shape, size, or color when subjected to external stimuli. Highly precise and calibrated 4D materials, which can perform together to achieve robust 4D objects, are in great demand in various fields such as military applications, space suits, robotic systems, apparel, healthcare, sports, etc. This review, for the first time, to the best of the authors’ knowledge, focuses on recent advances in SMMs (e.g., polymers, metals, etc.) based wearable smart textiles and fashion goods. This review integrates the basic overview of 3DP technology, fabrication methods, the transition of 3DP to 4DP, the chemistry behind the fundamental working principles of 4D printed objects, materials selection for smart textiles and fashion goods. The central part summarizes the effect of major external stimuli on 4D textile materials followed by the major applications. Lastly, prospects and challenges are discussed, so that future researchers can continue the progress of this technology.     

基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高.     

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.     

小型核桃脱壳分选一体机的设计

核桃不仅营养价值极高,而且核桃壳的药用价值也非常高,国内小企业和家庭在核桃硬壳脱壳加工环节,一般采用人工破壳取仁的方式,这种方式劳动强度大,人工成本高且不卫生;针对这个问题设计了一款小型的硬壳脱壳,壳仁分离分选的机器来提高生产效率,减少成本,提高收入。     

紫色球杆菌视紫红质光谱特性的机器学习研究

近年来，机器学习等人工智能技术被应用于蛋白质工程，其在蛋白质结构、功能预测、催化活性等研究中具有独特优势。在未知蛋白质结构的情况下，将蛋白质序列和功能特性与机器学习相结合，基于序列-活性关系（innovative sequence-activity relationship，ISAR）算法，将蛋白质氨基酸序列数字化，用快速傅里叶变换（fast four transform，FFT）进行预处理，再进行偏最小二乘回归建模，可在数据集较少情况下拟合得到最佳模型。通过机器学习对紫色球杆菌视紫红质（gloeobacter violaceus rhodopsin，GR）的突变体蛋白质氨基酸序列与光谱最大吸收波长进行建模，获得了最佳模型。用最佳索引LEVM760106建模得到的确定系数R² 为0.944，均方误差E为11.64。用小波变换进行的预处理，其R² 虽也约为0.944，但E大于11.64，不及FFT进行的预处理。方法较好地解决了蛋白质序列与功能特性之间的数学建模问题，在蛋白质工程中可为预测更优的突变体提供支持。     

变频调速技术在定量包装机中的应用

介绍一种基于变频调速控制的全自动定量包装机，结构简单，组态灵活，性价比高，可广泛应用于食品饲料等行业，现场运行实践证明其通用性好，准确度和可靠性高、速度快、稳定性好。并论述变频器控制系统的设计及使用中的注意问题。     

焊膏印刷工艺参数的选择与优化

表面贴装工艺流程的关键工序之一就是焊膏印刷,其工艺控制的好坏直接影响着装配的线路板的质量。通过对印刷工艺参数的分析,利用试验设计的方法来找出关键工艺参数,并加以优化设定,从而为控制工序参数奠定基础。     

提高焊膏印刷质量的工艺改进

焊膏印刷作为SMT工艺的第一步，其质量好坏对SMT工艺有着重要影响。文章通过对焊膏成分、特性的分析，讨论了印刷中各种工艺参数的正确选择；对焊膏印刷中容易出现的质量问题进行了详细分析，指出了产生问题的原因，提出了改进措施。