Single-walled carbon nanotubes (CNTs) may enable the fabrication of integrated circuits smaller than 10 nanometers, but this would require scalable production of dense and electronically pure semiconducting nanotube arrays on wafers. We developed a multiple dispersion and sorting process that resulted in extremely high semiconducting purity and a dimension-limited self-alignment (DLSA) procedure for preparing well-aligned CNT arrays (within alignment of 9 degrees) with a tunable density of 100 to 200 CNTs per micrometer on a 10-centimeter silicon wafer. Top-gate field-effect transistors (FETs) fabricated on the CNT array show better performance than that of commercial silicon metal oxide–semiconductor FETs with similar gate length, in particular an on-state current of 1.3 milliamperes per micrometer and a recorded transconductance of 0.9 millisiemens per micrometer for a power supply of 1 volt, while maintaining a low room-temperature subthreshold swing of <90 millivolts per decade using an ionic-liquid gate. Batch-fabricated top-gate five-stage ring oscillators exhibited a highest maximum oscillating frequency of >8 gigahertz.

Human-Object Interaction (HOI) Detection is an important problem to understand how humans interact with objects. In this paper, we explore Interactiveness Knowledge which indicates whether human and object interact with each other or not. We found that interactiveness knowledge can be learned across HOI datasets, regardless of HOI category settings. Our core idea is to exploit an Interactiveness Network to learn the general interactiveness knowledge from multiple HOI datasets and perform Non-Interaction Suppression before HOI classification in inference. On account of the generalization of interactiveness, interactiveness network is a transferable knowledge learner and can be cooperated with any HOI detection models to achieve desirable results. We extensively evaluate the proposed method on HICO-DET and V-COCO datasets. Our framework outperforms state-of-the-art HOI detection results by a great margin, verifying its efficacy and flexibility. Code is available at https://github.com/DirtyHarryLYL/ Transferable-Interactiveness-Network.

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Zinc dendrite growth is controlled by electrolyte flow at high current densities, effectively extending the cycle life of rechargeable zinc–air batteries.

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