Ionic Hydrogels with Biomimetic 4D‐Printed Mechanical Gradients: Models for Soft‐Bodied Aquatic Organisms

Direct‐ink writing (DIW), a rapidly growing and advancing form of additive manufacturing, provides capacities for on‐demand tailoring of materials to meet specific requirements for final designs. The penultimate challenge faced with the increasing demand of customization is to extend beyond modification of shape to create 4D structures, dynamic 3D structures that can respond to stimuli in the local environment. Patterning material gradients is foundational for assembly of 4D structures, however, there remains a general need for useful materials chemistries to generate gray scale gradients via DIW. Here, presented is a simple materials assembly paradigm using DIW to pattern ionotropic gradients in hydrogels. Using structures that architecturally mimic sea‐jelly organisms, the capabilities of spatial patterning are highlighted as exemplified by selectively programming the valency of the ion‐binding agents. Spatial gradients, when combined with geometry, allow for programming the flexibility and movement of iron oxide nanoparticle–loaded ionotropic hydrogels to generate 4D‐printed structures that actuate in the presence of local magnetic fields. This work highlights approaches to 4D design complexity that exploits 3D‐printed gray‐scale/gradient mechanics.     

选择射频电感

额定电流.直流电阻.Q值以及自谐振频率都是重要因素 在手机、RFID,测试设备、GPS、雷达、Wi-Fi以及卫星无线电等应用的高频模拟电路和信号处理中,电感是最重要的元件之一.通常,它可以承担的几项主要功能包括电路调谐、阻抗匹配,高通和低通滤波器,还可以用作RF扼流圈.     

Strain Anisotropies and Self‐Limiting Capacities in Single‐Crystalline 3D Silicon Microstructures: Models for High Energy Density Lithium‐Ion Battery Anodes

This study examines the crystallographic anisotropy of strain evolution in model, single‐crystalline silicon anode microstructures on electrochemical intercalation of lithium atoms. The 3D hierarchically patterned single‐ crystalline silicon microstructures used as model anodes were prepared using combined methods of photolithography and anisotropic dry and wet chemical etching. Silicon anodes, which possesses theoretically ten times the energy density by weight compared to conventional carbon anodes, reveal highly anisotropic but more importantly, variably recoverable crystallographic strains during cycling. Model strain‐limiting silicon anode architectures that mitigate these impacts are highlighted. By selecting a specific design for the silicon anode microstructure, and exploiting the crystallographic anisotropy of strain evolution upon lithium intercalation to control the direction of volumetric expansion, the volume available for expansion and thus the charging capacity of these structures can be broadly varied. We highlight exemplary design rules for this self‐strain‐limited charging in which an anode can be variably optimized between capacity and stability. Strain‐limited capacities ranging from 677 mAhg^?1 to 2833 mAhg^?1 were achieved by constraining the area available for volumetric expansion via the design rules of the microstructures.     

Enhanced DNA Sequencing Performance Through Edge‐Hydrogenation of Graphene Electrodes

The use of graphene electrodes with hydrogenated edges for solid‐state nanopore‐based DNA sequencing is proposed, and molecular dynamics simulations in conjunction with electronic transport calculations are performed to explore the potential merits of this idea. The results of the investigation show that, compared to the unhydrogenated system, edge‐hydrogenated graphene electrodes facilitate the temporary formation of H‐bonds with suitable atomic sites in the translocating DNA molecule. As a consequence, the average conductivity is drastically raised by about 3 orders of magnitude while exhibiting significantly reduced statistical variance. Furthermore, the effect of the distance between opposing electrodes is investigated and two regimes identified: for narrow electrode separation, the mere hindrance due to the presence of protruding hydrogen atoms in the nanopore is deemed more important, while for wider electrode separation, the formation of H‐bonds becomes the dominant effect. Based on these findings, it is concluded that hydrogenation of graphene electrode edges represents a promising approach to reduce the translocation speed of DNA through the nanopore and substantially improve the accuracy of the measurement process for whole‐genome sequencing.     

简化混合处理器应用开发 FPGA分担DSP功能降低构建成本

随着大规模现场可编程逻辑阵列(FPGA)的成本降低,加上面向软件的FPGA设计工具的发展,使得FPGA器件获得更多的使用,既能处理过去DSP处理器领域的功能,同时大大降低了专用ASIC方案的风险和前期成本.     

Self‐Assembly of Nanoparticle‐Spiked Pillar Arrays for Plasmonic Biosensing

Plasmonic biosensors have demonstrated superior performance in detecting various biomolecules with high sensitivity through simple assays. Scaled‐up, reproducible chip production with a high density of hotspots in a large area has been technically challenging, limiting the commercialization and clinical translation of these biosensors. A new fabrication method for 3D plasmonic nanostructures with a high density, large volume of hotspots and therefore inherently improved detection capabilities is developed. Specifically, Au nanoparticle‐spiked Au nanopillar arrays are prepared by utilizing enhanced surface diffusion of adsorbed Au atoms on a slippery Au nanopillar arrays through a simple vacuum process. This process enables the direct formation of a high density of spherical Au nanoparticles on the 1 nm‐thick dielectric coated Au nanopillar arrays without high‐temperature annealing, which results in multiple plasmonic coupling, and thereby large effective volume of hotspots in 3D spaces. The plasmonic nanostructures show signal enhancements over 8.3 × 10⁸‐fold for surface‐enhanced Raman spectroscopy and over 2.7 × 10²‐fold for plasmon‐enhanced fluorescence. The 3D plasmonic chip is used to detect avian influenza‐associated antibodies at 100 times higher sensitivity compared with unstructured Au substrates for plasmon‐enhanced fluorescence detection. Such a simple and scalable fabrication of highly sensitive 3D plasmonic nanostructures provides new opportunities to broaden plasmon‐enhanced sensing applications.     

Expert system applications in software engineering

This paper presents an overview of research in expert systems and artificial intelligence as they relate to software engineering. The paper begins with a review of current thinking regarding the software process. This is followed by a discussion of artificial intelligence (AI) and the paradigms it uses. Six current projects are described: three are concerned with programming in the large and three with programming in the small. These six projects provide a representative sample of the AI research now underway in the software engineering domain. The paper concludes with some observations regarding when and how the concepts represented by these projects will be available for application to operational projects.     

Quantitative read-across for predicting the acute fish toxicity of organic compounds

Read-across enables the interpolation of a property for a target chemical from respective experimental data of sufficiently similar compounds. Employing a set of 692 organic compounds with experimental values for the 96 h fish toxicity toward the fathead minnow in terms of LC(50) (lethal concentration 50%) values, a read-across method has been developed that is based on atom-centered fragments (ACFs) for evaluating chemical similarity. Prediction of log LC(50) proceeds through reading across the toxicity enhancement over predicted narcosis-level toxicity in terms of the respective logarithmic ratio, log T(e), and adding the respective baseline narcosis LC(50) estimated from log K(ow) (octanol/water partition coefficient). Depending on the minimum similarity imposed on a compound to serve as read-across basis for the target chemical, three different standard settings have been introduced, allowing one to perform screening-level estimations as well as predictions with intermediate and good confidence. The respective squared correlation coefficients (r(2)) are 0.73, 0.78, and 0.87, with root-mean square errors (rms) of 0.73, 0.60, and 0.39 log units, respectively. As a general trend, increasing the ACF minimum similarity increases the prediction quality at the cost of decreasing the application range. The method has the potential to assist in the predictive evaluation of fish toxicity for regulatory purposes such as under the REACH legislation.