A single biological neuron can efficiently perform Boolean operations. Artificial neuromorphic systems, on the other hand, typically require several devices to complete a single operation. Here, we show that neuristors that exploit the intrinsic polarity of two-dimensional materials can perform logic operations in a single device. XNOR gates can be made using ambipolar tungsten diselenide (WSe₂), NOR gates using p-type black phosphorus, and OR and AND gates using n-type molybdenum disulfide (MoS₂) of different thicknesses. To illustrate the potential of the neuristors, we fabricate logic half-adder and parity-checker circuits using a WSe₂ neuristor and a MoS₂ neuristor in a two-transistor two-resistor configuration, offering an area saving of 78% compared to circuits based on MoS₂ gates in a traditional design. We also propose a binary neural network that is based on a three-dimensional XNOR array, which simulations show should offer an energy efficiency of 622.35 tera-operations per second per watt and a power consumption of 7.31 mW.

单个生物神经元可以有效地执行布尔运算。另一方面，人工神经形态系统通常需要多个设备来完成单个操作。在这里，我们展示了利用二维材料固有极性的神经元可以在单个器件中执行逻辑运算。XNOR 门可以使用双极性二硒化钨 (WSe ₂ ) 制成，NOR 门使用 p 型黑磷制成，OR 和 AND 门使用不同厚度的 n 型二硫化钼 (MoS ₂ ) 制成。_{为了说明神经元的潜力，我们使用 WSe 2}神经元和 MoS ₂制造逻辑半加器和奇偶校验电路神经电阻器采用双晶体管双电阻器配置，与传统设计中基于 MoS ₂栅极的电路相比，可节省 78% 的面积。我们还提出了一个基于 3D XNOR 阵列的二元神经网络，模拟显示该网络的能效为 622.35 tera-operations per second perwatt，功耗为 7.31 mW。