Computing with Liquid-State Nanomechanical Oscillator Networks

我们的研究计划探索使用纳米级机械元件来取代电子晶体管，作为先进计算设备的基本构件。众所周知，由于制造过程中的基本物理限制，减小电子晶体管的尺寸以创建更好的计算应用变得越来越困难和昂贵。取而代之的是，我们从异常强大和节能的计算系统(如人脑)中寻找灵感，提出一种基于复杂网络中相互连接的机械单元的计算机。之所以选择机械单元，是因为它们可以小尺寸制造，具有独特的性能(高速、低能耗、非线性行为)。这些单元被组织成一个网络，就像大脑中的神经元一样，因为这种类型的组织可以产生更有趣的计算设备，具有生物有机体的典型特征(大规模并行性、健壮性和适应性)。特别是，我们建议新颖地使用非常小的振荡液态金属液滴(直径降至100纳米)作为我们的演示装置的机械单元。这些纳米液滴的制备相当简单，而且是液体，具有非常有趣的特性，适合我们的目的。数以千计的水滴将在网络中组装，以研究计算能力的出现。预计这些复杂的机制在检测声音或图像中的模式等困难和重要问题上的表现将远远好于标准电子计算机。*他说，我们的多学科研究具有重要的科学意义，因为它引入了一种新工具-液态金属纳米液滴，来探索非常小规模的流体运动；因为它创造了可能是有史以来由机械元件制造的最复杂的计算机器，其尺寸和能效比微电子电路的机器更好；还因为它加深了我们对复杂系统中计算能力的出现的理解，这是计算机科学和神经科学中的一个核心重要主题。我们的研究在技术上也很重要，因为它可能会导致微型、节能和强大的计算设备，这些设备可以在运行中重新配置，以快速解决具有挑战性的问题。这些设备在能源资源有限的应用中尤其有用，例如移动电话或分布式传感器网络。

Our research program explores the use of nanoscale mechanical elements to replace electronic transistors as the elemental building block of advanced computing devices. It is well-known that it is increasingly difficult and expensive to reduce the dimensions of electronic transistors to create better computing applications, due to fundamental physical limitations in their fabrication process. Instead, we look for inspiration in extraordinarily powerful and energy-efficient computing systems such as the human brain, to propose a computing machine based on mechanical units interconnected in a complex network. Mechanical units are chosen because they can be fabricated at small dimensions with unique capabilities (high speed, low energy consumption, non-linear behavior). These units are organized in a network, like neurons in the brain, because this type of organization can lead to much more interesting computing devices with characteristics typical of living organisms (massive parallelism, robustness, adaptability). We suggest, in particular, the novel use of very small oscillating droplets of liquid metal (diameters down to 100 nm) as the mechanical units for our demonstrators. These nano-droplets are reasonably simple to fabricate and, being liquid, have very interesting properties for our purpose. Thousands of droplets will be assembled in networks to study the emergence of computing capabilities. It is expected that these complex mechanisms will perform far better than standard electronic computers on difficult and important problems, such as the detection of patterns in sounds or in images.***     Our multi-disciplinary research is important scientifically because it introduces a new tool, liquid metal nano-droplets, to explore the motion of fluids at very small scales; because it creates what is probably the most sophisticated computing machine ever fabricated from mechanical elements, with dimensions and power-efficiency better than those of microelectronic circuits; and because it deepens our understanding of the emergence of computing capabilities in complex systems, a theme of central importance in computer science and neuroscience. Our research is also important technologically, as it may lead to miniature, energy-efficient and robust computing devices which can be reconfigured on the fly to rapidly solve challenging problems. These devices would be especially useful in applications with limited energy resources, such as mobile phones or distributed sensor networks.