Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Wilberforce Road, Cambridge, CB3 0WA, UK.
ICTP - International Centre for Theoretical Physics, Strada Costiera, 11, 34151, Trieste, Italy.
Sci Rep. 2023 Mar 18;13(1):4517. doi: 10.1038/s41598-023-31583-y.
We study the heat transfer between two nanoparticles held at different temperatures that interact through nonreciprocal forces, by combining molecular dynamics simulations with stochastic thermodynamics. Our simulations reveal that it is possible to construct nano refrigerators that generate a net heat transfer from a cold to a hot reservoir at the expense of power exerted by the nonreciprocal forces. Applying concepts from stochastic thermodynamics to a minimal underdamped Langevin model, we derive exact analytical expressions predictions for the fluctuations of work, heat, and efficiency, which reproduce thermodynamic quantities extracted from the molecular dynamics simulations. The theory only involves a single unknown parameter, namely an effective friction coefficient, which we estimate fitting the results of the molecular dynamics simulation to our theoretical predictions. Using this framework, we also establish design principles which identify the minimal amount of entropy production that is needed to achieve a certain amount of uncertainty in the power fluctuations of our nano refrigerator. Taken together, our results shed light on how the direction and fluctuations of heat flows in natural and artificial nano machines can be accurately quantified and controlled by using nonreciprocal forces.
我们通过将分子动力学模拟与随机热力学相结合，研究了通过非互易力相互作用的两种处于不同温度的纳米粒子之间的传热。我们的模拟表明，有可能构建纳米致冷机，以非互易力为代价，从冷储库向热储库产生净热传递。我们将随机热力学的概念应用于一个最小的欠阻尼朗之万模型，推导出了功、热和效率波动的精确解析表达式预测，这些预测再现了从分子动力学模拟中提取的热力学量。该理论仅涉及一个未知参数，即有效摩擦系数，我们通过将分子动力学模拟的结果拟合到我们的理论预测来估计该参数。利用这个框架，我们还确定了设计原则，这些原则确定了在我们的纳米致冷机的功率波动中实现一定不确定性所需的最小熵产生量。总之，我们的研究结果阐明了如何通过使用非互易力来准确地量化和控制自然和人工纳米机器中的热流方向和波动。
