Memory in a Droplet: Collections of Brain-Inspired Biomolecular Elements

随着人工智能方法变得普遍，需要更多的资源来执行，迫切需要开发替代计算方法。替代计算的一种方法直接从大脑本身获得灵感，通过结合活组织中存在的离子运输和选择性膜屏障来重建传统电路的各个方面。这些方法通过配置内存和处理单元，将内存构建到材料本身的结构中，需要较低的功耗。该项目建立了涂有脂质的液滴网络，作为模型神经元，能够根据它们传递的信号调整它们的特性。这种在模型突触之间调节交换的能力是神经形态结构的关键组成部分，这个项目通过数学预测和实验观察的结合，探索使用相互连接的合成细胞网络中的紧急机制来控制交换。该项目的完成将为能够进行化学计算并能够与传统电子学和生物化学信号接口的动态合成组织提供基础。此外，该项目还为未来的科学家提供跨学科培训，并通过招聘和培训本科生和高中生来促进STEM劳动力的发展。这项研究为基于液滴的神经形态材料提供了一种新的方法，将其扩展到更大的可重构元件的多维网络。对这些神经形态隔间网络的研究表明，内部液滴状态(如电荷积累)如何被用作记忆的一种形式。选择的方法认识到，液滴界面双层可以通过软材料的粘弹性/粘塑性的透镜来观察，从而实现亚稳态行为。通过将电和化学活动结合起来，建立了一种新的多物理模型来模拟胶滴的力学行为。然后这个模型将被用来探索生物膜集合中的复杂电润湿事件，指导生物分子神经形态材料的设计。模型预测将得到实验验证，该模型将逐步扩展，以研究出现在更大的生物分子元素集合中的一致运行的紧急机制。这种脑启发材料的新方法提供了长期的突触可塑性和通过电压信号永久保持膜结构变化的能力。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The development of alternative computing approaches is urgently needed as artificial intelligence methods become prevalent, requiring greater resources for their execution. One approach to alternative computing draws inspiration directly from the brain itself, reconstructing aspects of conventional circuitry through combinations of the ionic transport and selective membranous barriers present in living tissues. These approaches require low power consumption through collocating memory and processing units, building memory into the structure of the material itself. This project builds networks of lipid-coated droplets as model neurons capable of adapting their properties in response to the signals they transmit. This ability to tune the exchange across the model synapses is a crucial component of neuromorphic architectures, and this project explores controlling the exchanges using emergent mechanics in networks of interconnected synthetic cells through a combination of mathematical predictions and experimental observations. Completion of the project will provide a foundation for dynamic synthetic tissues capable of chemical computation and able to interface both with conventional electronics and biochemical signals. In addition, the project provides interdisciplinary training for future scientists and enhances the development of the STEM workforce by recruiting and training undergraduate and high school students. This research provides a new approach to droplet-based neuromorphic materials, expanding them to larger multidimensional networks of reconfigurable elements. Investigating these networks of neuromorphic compartments has demonstrated how the internal droplet states (such as accumulation of charge) may be exploited as a form of memory. The selected approach recognizes that droplet interface bilayers may be viewed through the lens of viscoelasticity/viscoplasticity in soft materials, enabling metastable behaviors. A novel multiphysics model will be created for simulating adhesive droplet mechanics by combining the electrical and chemical activities. This model will then be used to explore complex electrowetting events in collections of biological membranes, guiding the design of biomolecular neuromorphic materials. Model predictions will be validated experimentally, and the model will be gradually expanded to study emergent mechanics present in larger collections of biomolecular elements operating in unison. This new approach to the brain-inspired material provides long term synaptic plasticity and the ability to permanently retain changes in the membranous structure through voltage signals.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.