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Decision trees within a molecular memristor

机译:分子忆内体内的决策树

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Profuse dendritic-synaptic interconnections among neurons in the neocortex embed intricate logic structures enabling sophisticated decision-making that vastly outperforms any artificial electronic analogues(1-3). The physical complexity is far beyond existing circuit fabrication technologies: moreover, the network in a brain is dynamically reconfigurable, which provides flexibility and adaptability to changing environments(4-6). In contrast, state-of-the-art semiconductor logic circuits are based on threshold switches that are hard-wired to perform predefined logic functions. To advance the performance of logic circuits, we are re-imagining fundamental electronic circuit elements by expressing complex logic in nanometre-scale material properties. Here we use voltage-driven conditional logic interconnectivity among five distinct molecular redox states of a metal-organic complex to embed a 'thicket' of decision trees (composed of multiple if-then-else conditional statements) having 71 nodes within a single memristor. The resultant current-voltage characteristic of this molecular memristor (a 'memory resistor', a globally passive resistive-switch circuit element that axiomatically complements the set of capacitor, inductor and resistor) exhibits eight recurrent and history-dependent non-volatile switching transitions between two conductance levels in a single sweep cycle. The identity of each molecular redox state was determined with in situ Raman spectroscopy and confirmed by quantum chemical calculations, revealing the electron transport mechanism. Using simple circuits of only these elements, we experimentally demonstrate dynamically reconfigurable, commutative and non-commutative stateful logic in multivariable decision trees that execute in a single time step and can, for example, be applied as local intelligence in edge computing(7-9).Multiple redox transitions in a molecular memristor can be harnessed as 'decision trees' to undertake complex and reconfigurable logic operations in a single time step.
机译:Neocortex嵌入式复杂逻辑结构中神经元中的神经元中的突触互连互联,从而实现了复杂的决策,从而大大优于任何人工电子类似物(1-3)。物理复杂性远远超出现有的电路制造技术:此外,大脑中的网络是动态可重新配置的,这为改变环境提供了灵活性和适应性(4-6)。相反,最先进的半导体逻辑电路基于阈值开关,其硬连接以执行预定义的逻辑功能。为了推进逻辑电路的性能,我们通过在纳米级材料特性中表达复杂的逻辑来重新想象基本的电子电路元件。这里,我们在金属有机综合体的五个不同分子氧化还原态之间使用电压驱动的条件逻辑互连,以嵌入决策树的“丛林”(由多个if-wear-wess条件语句组成),其中包括单个存储器内的71个节点。该分子膜的所得电流 - 电压特性(“存储器电阻”,一个公正地补充电容器,电感器和电阻集的全局无源电阻开关电路元件)在单个扫描周期中的两个电导水平。用原位拉曼光谱法测定每个分子氧化还原状态的同一性,并通过量子化学计算证实,揭示了电子传输机制。使用仅这些元素的简单电路,我们通过在单个时间步骤中执行在多变量决策树中进行动态可重新配置,交换和非换向状态逻辑,并且可以例如在边缘计算中应用为本地智能(7-9 )。可以利用分子忆内转换的多种氧化还原转换作为“决策树”,以在单个时间步骤中进行复杂和可重构的逻辑操作。

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  • 来源
    《Nature 》 |2021年第7874期| 51-56| 共6页
  • 作者单位

    Natl Univ Singapore Dept Phys Singapore Singapore|Natl Univ Singapore NUSNNI NanoCore Singapore Singapore|Natl Univ Singapore NUS Grad Sch Integrat Sci & Engn Singapore Singapore;

    Indian Assoc Cultivat Sci IACS Sch Chem Sci Kolkata India;

    Natl Univ Singapore Dept Phys Singapore Singapore|On Deck San Francisco CA USA;

    Indian Assoc Cultivat Sci IACS Sch Chem Sci Kolkata India;

    Hewlett Packard Enterprise AI Res Lab Ft Collins CO USA;

    Natl Univ Singapore Dept Phys Singapore Singapore|Natl Univ Singapore NUSNNI NanoCore Singapore Singapore|Natl Univ Singapore NUS Grad Sch Integrat Sci & Engn Singapore Singapore;

    Univ Limerick Bernal Inst Dept Phys Limerick Ireland;

    Natl Univ Singapore Dept Phys Singapore Singapore|Natl Univ Singapore NUSNNI NanoCore Singapore Singapore|Natl Univ Singapore NUS Grad Sch Integrat Sci & Engn Singapore Singapore|Natl Univ Singapore Dept Elect & Comp Engn Singapore Singapore|Univ Oklahoma Ctr Quantum Res & Technol Norman OK 73019 USA;

    Indian Assoc Cultivat Sci IACS Sch Chem Sci Kolkata India;

    Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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