摘要：Conductive and transparent dipeptide hydrogels are desirable building blocks to prepare soft electronic devices and wearable biosensors due to their excellent biocompatibility,multi-functionality,and physiochemical properties similar to those of body ***,the preparation of such hydrogels featuring high conductivity and transparency is a huge challenge because of the hydrophobic feature of conductive additives making the doping process *** overcome this issue,hydrophilic conductive polydopamine(PDA)-doped polypyrrole(PPy)nanoparticles are introduced into the dipeptide hydrogel networks to form conductive nanofibrils in situ to achieve a good level of hydrophilic templating of the hydrogel *** tech-nique creates a complete conductive network and allows visible light to pass *** strategy proposed herein not only endows the dipeptide hydrogel with good conductivity and high transparency,but also provides a great potential application of conductive dipeptide hydrogels for body-adhered signal detection,as evidenced by the experimental data.

摘要：With the rapid development of artificial intelligence technology and increasing material data,machine learning-and artificial intelligence-assisted design of high-performance steel materials is becoming a mainstream paradigm in materials *** learning methods,based on an interdisciplinary discipline between computer science,statistics and material science,are good at discovering correlations between numerous data *** with the traditional physical modeling method in material science,the main advantage of machine learning is that it overcomes the complex physical mechanisms of the material itself and provides a new perspective for the research and development of novel *** review starts with data preprocessing and the introduction of different machine learning models,including algorithm selection and model ***,some successful cases of applying machine learning methods in the field of steel research are reviewed based on the main theme of optimizing composition,structure,processing,and *** application of machine learning methods to the performance-oriented inverse design of material composition and detection of steel defects is also ***,the applicability and limitations of machine learning in the material field are summarized,and future directions and prospects are discussed.

摘要：The sieving and enrichment of rare tumor cells from large-volume pleural effusion(PE)samples is a promising technique for cell-based lung tumor diagnosis and drug tests,which features high throughput and recovery,purification,as well as viability rates of rare target cells as the prerequisites for high sensitivity,specificity,and accuracy of tumor cell *** this paper,we propose a three-dimensional(3 D)sieving method for rare tumor cell enrichment,which effectively eliminates the"dead zones"in traditional two-dimensional(2 D)cell filters with a dimension-raising strategy to satisfy the requirements mentioned *** prototype device was combined with a funnel-shaped holder,a flexible micropore membrane in the middle,and a3 D spiral fluid channel covered on the membrane as a three-layer ice-creaming cone composite *** by gravity alone,the device performed as follows:(1)20-fold throughput compared with the 2 D commercial planee hich was up to 20 mL/min for a threefold dilution of whole blood sample;(2)high recovery rates of 84.5%±21%,86%±25%,83%±14%for 100,1000,and 10000 cells/mL,respectively,in 30 mL phosphate buffer saline(PBS)sample,and a 100%positive detection rate in the case of≤5 A549 cells in 1 mL PBS;(3)a typical purification rate of 85.5%±9.1%;and(4)a viability rate of>93%.In the demonstration application,this device effectively enriched rare target cells from large volumes(>25 mL)of clinical pleural *** following results indicated that tumor cells were easy-to-discover in the enriched PE samples,and the proliferation capability of purified cells was(>4.6 times)significantly stronger than that of unprocessed cells in the subsequent 6-day *** above evaluation indicates that the proposed easily reproducible method for the effective execution of rare cell enrichments and assays is expected to become a practical technique for clinical cell-based tumor diagnosis.

摘要：Contextual advertising is a major revenue source for today’s *** extraction is a key step in this kind of advertising,through which appropriate

摘要：太阳能水蒸发对于解决净水危机潜力无限.随着研究的深入,研发高效光热转换材料和合理的材料结构设计均可以提高光热蒸发速率.因此,我们设计合成了一种双层碳基水凝胶复合材料.在一个太阳光照条件下,其最大蒸发速率可达2.19 kg m^(−2)h^(−1),光热转换效率可达93.7%.同时,该复合材料展现了优异的海水淡化性能及良好的稳定性,扩展了实际应用范围.除此之外,其可控规模化及便携性可以自如面对多种复杂的应用环境,成本低廉可以使其大规模应用于经济落后地区,为复合结构水凝胶蒸发器的生产提供了可供参考的设计思路和策略.

摘要：电容式压力传感器是一种将压力转换成电信号的高效可靠的传感器,具有广泛的用途.柔性电容式压力传感器的结构可能会发生较大的变形,大变形下的灵敏度和线性度是柔性压力传感器的主要性能指标,无法用传统小变形理论进行分析。因此,建立能够准确预测外部压力下柔性压力传感器的变形和力-电耦合性能的理论模型对传感器的定量设计至关重要.在本文中,我们提出了一个力-电耦合理论模型,分析了柔性电极在弯曲大变形下的电容变化.该理论被用来预测柔性菱形电容式传感器的变形和电容变化关系,并通过数值模拟和实验进行了验证。该力-电耦合理论可用于对具有对称柔性/弧形电极的悬臂式电容器在对称载荷作用下的力-电性能进行分析和设计,并可退化为文献中的小变形理论.准确的理论分析模型可以促进电容式压力传感器和其他类似结构的研究和设计。

摘要：通过电催化氧化葡萄糖等可再生生物质生产高附加值化学品为实现碳中和目标提供了一条有效途径.目前用于电催化生物质氧化反应的电催化剂主要分为贵金属基催化剂和非贵金属基催化剂.对于贵金属基电催化剂,文献报道了铂基催化剂的氧化态随电势变化,进而调控电催化葡萄糖氧化的活性和选择性.对于非贵金属基催化剂,钴基和镍基氧化物和氢氧化物被广泛应用于电催化生物质氧化反应,但铜基催化剂直到最近才引起关注.最近,金属铜、氧化亚铜和氢氧化铜在内的铜基材料被证实是一类有应用前景的电催化生物质氧化催化剂,但在电化学条件下的真实活性位结构仍难以鉴定.本文针对电催化葡萄糖等生物质平台分子的氧化反应,证明了氧化铜的催化活性相随电压升高从氢氧化铜演变为羟基氧化铜,阐明了结构和反应活性及选择性的构效关系,该工作加深了对铜基催化剂活性位动态重构的理解,有助于电催化生物质转化的催化剂理性设计,促进可再生资源利用和碳中和目标的实现.

摘要：The conventional microwell-based platform for construction of organoid models exhibits limitations in precision oncology applications because of low-speed growth and high variability. Here, we established organoid models on a nested array chip for fast and reproducible drug testing using 50% matrigel. First, we constructed mouse small intestinal and colonic organoid models. Compared with the conventional microwell-based platform, the mouse organoids on the chip showed accelerated growth and improved reproducibility due to the nested design of the chip. The design of the chip provides miniaturized and uniform shaping of the matrigel that allows the organoid to grow in a concentrated and controlled manner. Next, a patient-derived organoid(PDO) model from colorectal cancer tissues was successfully generated and characterized on the chip. Finally, the PDO models on the chip, from three patients, were implemented for high-throughput drug screening using nine treatment regimens. The drug sensitivity testing on the PDO models showed good quality control with a coefficient of variation under 10% and a Z’ factor of more than 0.7. More importantly, the drug responses on the chip recapitulate the heterogeneous response of individual patients, as well as showing a potential correlation with clinical outcomes. Therefore,the organoid model coupled with the nested array chip platform provides a fast and reproducible means for predicting drug responses to accelerate precise oncology.

摘要：CaO–SiO_(2)compounds compromise one of the most common series of oxide particles in liquid steels, which could significantly affect the service performance of the steels as crack initiation sites. However, the structural, electronic, and mechanical properties of the compounds in CaO–SiO_(2)system are still not fully clarified due to the difficulties in the experiments. In this study, a thorough investigation of these properties of CaO–SiO_(2)compound particles in steels was conducted based on first-principles density functional theory. Corresponding phases were determined by thermodynamic calculation, including gamma dicalcium silicate(γ-C2S), alpha-prime(L) dicalcium silicate(αL′-C2S), alpha-prime(H) dicalcium silicate(αH′-C2S), alpha dicalcium silicate(α-C2S), rankinite(C3S2), hatrurite(C3S), wollastonite(CS), and pseudowollastonite(Ps-CS). The results showed that the calculated crystal structures of the eight phases agree well with the experimental results. All the eight phases are stable according to the calculated formation energies, and γ-C2S is the most stable. O atom contributes the most to the reactivity of these phases. The Young’s modulus of the eight phases is in the range of 100.63–132.04 GPa. Poisson’s ratio is in the range of0.249–0.281. This study provided further understanding concerning the CaO–SiO_(2)compound particles in steels and fulfilled the corresponding property database, paving the way for inclusion engineering and design in terms of fracture-resistant steels.

摘要：阳台喷洒羽毛是在中庭火的主要羽毛形式之一，它对为烟控制系统设计的设计者重要的热行为仍然不好现在理解。阳台喷洒羽毛的导致火的气体动力学将被数字方法在这篇论文学习。关于为烟生产率的可得到的计算方法的一些不确定性将被再考。数字结果显示用一个乘火车系数， 0.11 将在描述乘火车行为比 0.16 好，结束效果不应该为不是二维的羽毛(2-D ) 被忽略。合适的实验喷洒羽毛方程将为烟管理系统设计被推荐。