RESUMEN
Miniaturization of batteries lags behind the success of modern electronic devices. Neither the device volume nor the energy density of microbatteries meets the requirement of microscale electronic devices. The main limitation for pushing the energy density of microbatteries arises from the low mass loading of active materials. However, merely pushing the mass loading through increased electrode thickness is accompanied by the long charge transfer pathway and inferior mechanical properties for long-term operation. Here, a new spiral microelectrode upon stress-actuation accomplishes high mass loading but short charge transfer pathways. At a small footprint area of around 1 mm2 , a 21-fold increase of the mass loading is achieved while featuring fast charge transfer at the nanoscale. The spiral microelectrode delivers a maximum area capacity of 1053 µAh cm-2 with a retention of 67% over 50 cycles. Moreover, the energy density of the cylinder microbattery using the spiral microelectrode as the anode reaches 12.6 mWh cm-3 at an ultrasmall volume of 3 mm3 . In terms of the device volume and energy density, the cylinder microbattery outperforms most of the current microbattery technologies, and hence provides a new strategy to develop high-performance microbatteries that can be integrated with miniaturized electronic devices.
RESUMEN
Mechanical strain formed at the interfaces of thin films has been widely applied to self-assemble 3D microarchitectures. Among them, rolled-up microtubes possess a unique 3D geometry beneficial for working as photonic, electromagnetic, energy storage, and sensing devices. However, the yield and quality of microtubular architectures are often limited by the wet-release of lithographically patterned stacks of thin-film structures. To address the drawbacks of conventionally used wet-etching methods in self-assembly techniques, here a dry-release approach is developed to roll-up both metallic and dielectric, as well as metallic/dielectric hybrid thin films for the fabrication of electronic and optical devices. A silicon thin film sacrificial layer on insulator is etched by dry fluorine chemistry, triggering self-assembly of prestrained nanomembranes in a well-controlled wafer scale fashion. More than 6000 integrated microcapacitors as well as hundreds of active microtubular optical cavities are obtained in a simultaneous self-assembly process. The fabrication of wafer-scale self-assembled microdevices results in high yield, reproducibility, uniformity, and performance, which promise broad applications in microelectronics, photonics, and opto-electronics.
RESUMEN
The MPI Bioinformatics Toolkit (https://toolkit.tuebingen.mpg.de) provides interactive access to a wide range of the best-performing bioinformatics tools and databases, including the state-of-the-art protein sequence comparison methods HHblits and HHpred. The Toolkit currently includes 35 external and in-house tools, covering functionalities such as sequence similarity searching, prediction of sequence features, and sequence classification. Due to this breadth of functionality, the tight interconnection of its constituent tools, and its ease of use, the Toolkit has become an important resource for biomedical research and for teaching protein sequence analysis to students in the life sciences. In this article, we provide detailed information on utilizing the three most widely accessed tools within the Toolkit: HHpred for the detection of homologs, HHpred in conjunction with MODELLER for structure prediction and homology modeling, and CLANS for the visualization of relationships in large sequence datasets. © 2020 The Authors. Basic Protocol 1: Sequence similarity searching using HHpred Alternate Protocol: Pairwise sequence comparison using HHpred Support Protocol: Building a custom multiple sequence alignment using PSI-BLAST and forwarding it as input to HHpred Basic Protocol 2: Calculation of homology models using HHpred and MODELLER Basic Protocol 3: Cluster analysis using CLANS.
Asunto(s)
Biología Computacional , Análisis de Secuencia de Proteína , Programas Informáticos , Conformación Proteica , Alineación de Secuencia , Análisis de Secuencia de Proteína/métodos , Interfaz Usuario-ComputadorRESUMEN
Self-assembly of two-dimensional patterned nanomembranes into three-dimensional micro-architectures has been considered a powerful approach for parallel and scalable manufacturing of the next generation of micro-electronic devices. However, the formation pathway towards the final geometry into which two-dimensional nanomembranes can transform depends on many available degrees of freedom and is plagued by structural inaccuracies. Especially for high-aspect-ratio nanomembranes, the potential energy landscape gives way to a manifold of complex pathways towards misassembly. Therefore, the self-assembly yield and device quality remain low and cannot compete with state-of-the art technologies. Here we present an alternative approach for the assembly of high-aspect-ratio nanomembranes into microelectronic devices with unprecedented control by remotely programming their assembly behavior under the influence of external magnetic fields. This form of magnetic Origami creates micro energy storage devices with excellent performance and high yield unleashing the full potential of magnetic field assisted assembly for on-chip manufacturing processes.
RESUMEN
The MPI Bioinformatics Toolkit (https://toolkit.tuebingen.mpg.de) is a free, one-stop web service for protein bioinformatic analysis. It currently offers 34 interconnected external and in-house tools, whose functionality covers sequence similarity searching, alignment construction, detection of sequence features, structure prediction, and sequence classification. This breadth has made the Toolkit an important resource for experimental biology and for teaching bioinformatic inquiry. Recently, we replaced the first version of the Toolkit, which was released in 2005 and had served around 2.5 million queries, with an entirely new version, focusing on improved features for the comprehensive analysis of proteins, as well as on promoting teaching. For instance, our popular remote homology detection server, HHpred, now allows pairwise comparison of two sequences or alignments and offers additional profile HMMs for several model organisms and domain databases. Here, we introduce the new version of our Toolkit and its application to the analysis of proteins.