Liquid–paper interactions during liquid drop impact and recoil on paper surfaces

The spreading and recoiling of water drops on several flat and macroscopically smooth model surfaces and on sized paper surfaces were studied over a range of drop impaction velocities using a high-speed CCD camera. The water drop spreading and recoiling results on several model hydrophobic and hydrophilic surfaces were found to be in agreement with observations reported in the literature. The maximum drop spreading diameter for those model surfaces at impact was found to be dependent upon the initial drop kinetic energy and the degree of hydrophobicity/hydrophilicity of the surface. The extent of the maximum drop recoiling was found to be much weaker for hydrophilic substrates than for hydrophobic substrates. Sized papers, however, showed an interesting switch of behaviour in the process of water drop impaction. They behave like a hydrophobic substrate when a water drop impacts on it, but like a hydrophilic substrate when water drop recoils. Although the contact angle between water and hydrophilic or hydrophobic non-porous surfaces changes from advancing to receding as reported in literature, the change of contact angle during water impact on paper surface is unique in that the level of sizing was found to have a smaller than expected influence on the degree of recoil. Atomic force microscopy (AFM) was used to probe fibres on a sized filter paper surface under water. The AFM data showed that water interacted strongly with the fibre even though the paper was heavily sized. Implications of this phenomenon were discussed in the context of inkjet print quality and of the surface conditions of sized papers. Results of this study are very useful in the understanding of inkjet ink droplet impaction on paper surfaces which sets the initial condition for ink penetration into paper after impaction.     

喷墨打印系统多光谱特征化正向模型的建立

随着光谱技术的发展,打印系统的光谱特征化模型成为研究热点。基于光谱匹配的特征化模型通过直接预测设备基色的光谱反射比数据,可以有效的减少同色异谱现象的发生,为实现高保真印刷提供条件。主要基于Yule-Nielsen修正的Neugebauer光谱模型,开展了关于12色打印系统光谱特征化模型如何提高模型精度的研究。首先通过对颜色测量仪器及测量条件、喷墨打印机打印系统进行稳定性及精确度验证,为后续样本设计和测量提供可行性依据。然后,建立该研究设备适用的正向YNSN模型。依据CIELAB颜色空间中明度值L*均匀分布的原则,设计并输出了1 331个测试样本,抽取部分样本做训练样本,对所建立的光谱的特征化正向模型进行验证。结果表明,基于光谱的特征化模型预测精度较高,具有明显的优势。经验证,通过引入Yule-Nielsen修正参数n值,可进一步改善光谱预测精度。     

Roughness influence on the sheet resistance of the PEDOT:PSS printed on paper

The use of paper as a platform to manufacture organic electronic devices, electronic paper, has expanding potential for many applications because of several properties offered. In this work, we show a study of PEDOT:PSS printed by inkjet on bond paper, vegetal paper and sheets of PET. The relation between the surface density of the deposited material, morphology and resistivity was investigated for samples printed with a commercial Hewlett-Packard(HP)^® printer and Microsoft Word^® software. The amount of material deposited, i.e. surface density, was controlled using the print number in the same position and changing the gray scale used in the image formation. Changing the surface density of printed PEDOT:PSS, it is possible to produce a continuous film permeating the papers fibers. Sheet resistances obtained, when 7.0 mg cm⁻² of PEDOT:PSS were deposited on the surfaces, were: (a) 413.2 kΩ/Sq for bond paper, (b) 5.6 kΩ/Sq for vegetable paper and (c) 2.3 kΩ/Sq for PET. The exponential dependence of sheet resistance with the surface density of printed material allows us to evaluate the strong influence of substrate roughness on PEDOT:PSS conductivity and to predict, for each one, conditions to minimize it.     

人工智能在锂离子电池研发中的应用

锂离子电池已成为解决现代社会储能问题的最佳解决方案之一。然而,电池材料和器件开发都是复杂的多变量问题,传统的依赖研究人员进行实验的试错法在电池性能提升方面遇到了瓶颈。人工智能（AI）具有强大的高速、海量数据处理能力,是上述突破研究瓶颈的最具潜力的技术。其中,机器学习 (ML) 算法在评估多维数据变量和集合之间的组合关联方面的独特优势有望帮助研究人员发现不同因素之间的相互作用规律并阐明材料合成和设备制造的机制。本综述总结了锂离子电池传统研究方法遇到的各种挑战,并详细介绍了人工智能在电池材料研究、电池器件设计与制造、材料与器件表征、电池循环寿命与安全性评估等方面的应用。最重要的是,我们介绍了AI和ML在电池研究中面临的挑战,并讨论了它们应用的缺点和前景。我们相信,未来实验科学家、数学建模专家和AI专家之间更紧密的合作将极大地促进AI和ML方法用以解决传统方法难以克服的电池和材料问题。     

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.     

电喷印刷柔性传感器

柔性传感器因其在弯折、扭曲、拉伸等大变形条件下具有稳定的传感性能,所以在软体机器人、可穿戴电子和生物医疗等领域具有潜在的应用前景,受到了国内外研究者的广泛关注。与传统光刻技术相比,印刷技术制造作为增材制造,具有绿色、低成本和可大面积制造的优势,被广泛应用于柔性电子器件制备。其中,电流体动力喷墨打印(电喷印)技术因其具有多种功能材料的兼容性,被认为最有可能替代传统的光刻技术,实现柔性传感器高分辨率和跨规模制造。近年来,电喷印技术在微型化柔性传感器制造领域显示出广泛的应用潜力。本综述重点介绍了电喷印刷柔性传感器的工艺、材料和应用的最新研究进展。首先,详细介绍了电流体动力喷墨打印技术的工作原理,总结了用于电喷印的各种功能性墨水材料,然后,介绍了电喷印刷中墨水和柔性基底间表界面调控的问题。随后,综述了电喷印方法在柔性压力传感器、柔性气体传感器和柔性电化学传感器等柔性传感器制造的应用进展。最后,总结讨论了下一代电喷印刷技术在柔性传感器领域的机遇与挑战。     

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.     

Chitosan and Whey Protein Bio-Inks for 3D and 4D Printing Applications with Particular Focus on Food Industry

The application of chitosan (CS) and whey protein (WP) alone or in combination in 3D/4D printing has been well considered in previous studies. Although several excellent reviews on additive manufacturing discussed the properties and biomedical applications of CS and WP, there is a lack of a systemic review about CS and WP bio-inks for 3D/4D printing applications. Easily modified bio-ink with optimal printability is a key for additive manufacturing. CS, WP, and WP–CS complex hydrogel possess great potential in making bio-ink that can be broadly used for future 3D/4D printing, because CS is a functional polysaccharide with good biodegradability, biocompatibility, non-immunogenicity, and non-carcinogenicity, while CS–WP complex hydrogel has better printability and drug-delivery effectivity than WP hydrogel. The review summarizes the current advances of bio-ink preparation employing CS and/or WP to satisfy the requirements of 3D/4D printing and post-treatment of materials. The applications of CS/WP bio-ink mainly focus on 3D food printing with a few applications in cosmetics. The review also highlights the trends of CS/WP bio-inks as potential candidates in 4D printing. Some promising strategies for developing novel bio-inks based on CS and/or WP are introduced, aiming to provide new insights into the value-added development and commercial CS and WP utilization.     

微流控纸芯片的加工及其分析应用的实验设计*

设计了一个使用喷墨打印法加工微流控纸芯片的实验,在经烷基烯酮二聚体(AKD)的正己烷溶液浸泡过的滤纸上,以三乙醇胺溶液为打印墨水,用喷墨打印机打印出设计好的芯片图案。滤纸加热后,打印区域呈现亲水性,非打印区域为疏水性,从而制备出纸芯片,用该纸芯片通过数字比色法实现了亚硝酸根离子的定量测定。该实验不使用昂贵仪器设备,易普及。通过实验,促使学生了解微流控芯片这一前沿科学技术,锻炼学生细致、灵巧的动手能力,激发学生科技创新活力。