Related papers: Learning the best thermoelectric nanoscale heat en…
The optimization of the conversion of thermal energy into work and the minimization of dissipation for nano- and mesoscopic systems is a complex challenge because of the important role fluctuations play on the dynamics of small systems. We…
The transition to 4th generation district heating creates a growing need for scalable, automated design tools that accurately capture the spatial and temporal details of heating network operation. This paper presents an automated design…
Heat engines extract work by running cyclically between two heat reservoirs. When the two reservoirs are thermal and at different temperatures, the maximum efficiency of the engine is given by the Carnot limit. Here we consider a quantum…
Information can improve heat engine performance, but the underlying principles are still not so clear. Here we introduce a Carnot information machine (CIE) and obtain a quantitative relationship between the engine performance and…
Understanding energy transport at the nanoscale is an open and fundamental challenge in the molecular sciences with direct implications for the design of new electronics, computing devices, and materials. While nanoscale energy transport…
We study the optimal performance of Carnot-like heat engines working in low dissipation regime using the product of the efficiency and the power output, also known as the efficient power, as our objective function. Efficient power function…
Heat engines that convert thermal energy into work are a cornerstone of classical thermodynamics and remain an active area of contemporary research. Notable examples include microscopic heat engines, trade-off relations between power and…
Optimizing the operation of heating, ventilation, and air-conditioning (HVAC) systems is a challenging task, requiring the modeling of complex nonlinear relationships among HVAC load, indoor temperatures, and outdoor environments. This…
Reinforcement Learning offers a framework to learn to choose actions in order to achieve some goal. However, at the nano-scale, thermal fluctuations hamper the learning process. We analyze this regime using the general framework of Markov…
We investigate the dynamics and thermodynamics of a framework composed of interacting units in which parameters (temperatures and energies) assume distinct values due to the contact with distinct (cold and hot) thermal reservoirs. The…
We theoretically investigate strategies for harnessing quantum interference to optimize the figure of merit $ZT$, power output, and thermodynamic efficiency in multi-quantum-dot Aharonov-Bohm (AB) thermoelectric heat engines. Using the…
We analyze the power output of a quantum dot machine coupled to two electronic reservoirs via thermoelectric contacts, and to two thermal reservoirs - one hot and one cold. This machine is a nanoscale analogue of a conventional thermocouple…
Trajectory optimization in multi-vehicle scenarios faces challenges due to its non-linear, non-convex properties and sensitivity to initial values, making interactions between vehicles difficult to control. In this paper, inspired by…
We investigate the performance of a microscopic quantum heat engine consisting of V- or Lambda-type emitters interacting collectively or independently when being in contact with environmental thermal reservoirs. Though the efficiency of a…
We propose and theoretically investigate a nanomechanical heat engine. We show how a levitated nanoparticle in a harmonic optical trap inside an optical cavity can be used to realize a Stirling cycle in the underdamped regime. The…
According to Thermodynamics, the efficiency of a heat engine is upper bounded by Carnot efficiency. For macroscopic systems, the Carnot efficiency is, however, achieved only for quasi static processes. And, considerable attention has been…
Navigating the intricacies of thermal management at the quantum scale is a challenge in the pursuit of advanced nanoscale technologies. To this extent, theoretical frameworks introducing minimal models mirroring the functionality of…
We consider the optimization of a finite-time Carnot engine characterized by small dissipations. We bound the power with a simple inequality and show that the optimal strategy is to perform small cycles around a given working point, which…
We derive a bound on the efficiency of thermal engines that can be sharper than Carnot's limit. It is a function of statistical correlations between the engine internal state and Hamiltonian, can be saturated even in finite-time cycles, and…
This study explores strategies to improve engine efficiency through innovative materials, design concepts, and alternative energy sources. It highlights the use of nanomaterials and surface engineering to create hydrophobic or other types…