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Showing 1–3 of 3 results
Advanced filters: Author: Pengzhan Jin Clear advanced filters

  • Reconfigurable neuromorphic transistors are important for creating compact and efficient neuromorphic computing networks. Here, Li et al. introduce an optoelectronic electrolyte-gated transistor to perform multimodal recognition.

    • Pengzhan Li
    • Mingzhen Zhang
    • Chen Ge
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-11

  • Efficient production of MSC secretome for therapeutic applications remains a challenging task. Here, the authors present an approach whereby an acoustofluidic mechanobiological environment can form reproducible 3D MSC aggregates, allowing for secretome production with high efficiency.

    • Ye He
    • Shujie Yang
    • Tony Jun Huang
    ResearchOpen Access
    Nature Communications
    Volume: 14, P: 1-12

  • Neural networks are known as universal approximators of continuous functions, but they can also approximate any mathematical operator (mapping a function to another function), which is an important capability for complex systems such as robotics control. A new deep neural network called DeepONet can lean various mathematical operators with small generalization error.

    • Lu Lu
    • Pengzhan Jin
    • George Em Karniadakis
    Research
    Nature Machine Intelligence
    Volume: 3, P: 218-229