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Volume 20 Issue 1, January 2025

Memristors for on-chip intelligence

The image on the cover shows the optoelectronic memristor cells to be fully integrated as a 128 × 8 multi-mode array for in-sensor computing applications.

See Heyi Huang et al.

Image: Heyi Huang, Tsinghua University. Cover design: Vanitha Selvarajan

Editorial

  • Nanotechnology fosters energy-efficient devices that significantly boost on-chip performance for faster, more powerful AI, while also supporting dense integration of sensing and computing, reducing power consumption for advanced on-chip intelligence.

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Comment

  • The lack of standardization in the protocols used to assess the physicochemical properties of the battery electrode surface layer has led to data dispersion and biased interpretation in the literature. Here I propose guidelines for investigating it properly — or at least to allow a fair comparison between literature data.

    • Claire Villevieille
    Comment
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News & Views

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Research Briefings

  • Reducing the duration of current pulses used to perform magnetization switching via spin–orbit torques in ferromagnetic and ferrimagnetic samples from microseconds to picoseconds leads to a continuous decrease in the energy consumption. These findings show that speed and efficiency of switching can be combined in various magnetic materials with different properties.

    Research Briefing
  • From a single library of siloxane-based lipidoids, siloxane-incorporated lipid nanoparticles (SiLNPs) involving minor alterations in lipid chemistry yield tissue-specific mRNA delivery to the liver, lung, or spleen. Upon enhanced intracellular delivery, these SiLNPs show clinical promise for protein replacement therapies, regenerative medicine, and CRISPR–Cas-based gene editing applications.

    Research Briefing
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