A quantum-dot heat engine operating close to the thermodynamic efficiency limits

Cyclical heat engines are a paradigm of classical thermodynamics, but are impractical for miniaturization because they rely on moving parts. A more recent concept is particle-exchange (PE) heat engines, which uses energy filtering to control a thermally driven particle flow between two heat reservoirs. As they do not require moving parts and can be realized in solid-state materials, they are suitable for low-power applications and miniaturization. It was predicted that PE engines could reach the same thermodynamically ideal efficiency limits as those accessible to cyclical engines, but this prediction has not been verified experimentally. Here, we demonstrate a PE heat engine based on a quantum dot (QD) embedded into a semiconductor nanowire. We directly measure the engine's steady-state electric power output and combine it with the calculated electronic heat flow to determine the electronic efficiency $\eta$. We find that at the maximum power conditions, $\eta$ is in agreement with the Curzon-Ahlborn efficiency and that the overall maximum $\eta$ is in excess of 70$\%$ of the Carnot efficiency while maintaining a finite power output. Our results demonstrate that thermoelectric power conversion can, in principle, be achieved close to the thermodynamic limits, with direct relevance for future hot-carrier photovoltaics, on-chip coolers or energy harvesters for quantum technologies

Field Test of a Remote Multi-Path CLaDS Methane Sensor

Existing technologies for quantifying methane emissions are often limited to single point sensors, making large area environmental observations challenging. We demonstrate the operation of a remote, multi-path system using Chirped Laser Dispersion Spectroscopy (CLaDS) for quantification of atmospheric methane concentrations over extended areas, a technology that shows potential for monitoring emissions from wetlands

Stabilizing intransitive loops: self‐organized spatial structure and disjoint time frames in the coffee agroecosystem

It is familiar knowledge that population dynamics occur in both time and space. In this work, we incorporate three distinct but related theoretical schemata to qualitatively interrogate the complicated structure of part of a real agroecosystem. The three schemata are first, local dynamics translated into intransitive oscillators through spatial movement, second, stabilizing the system through spatial pattern, and third, formation of a self‐organized spatial pattern. The real system is the well‐studied autonomous pest control in the coffee agroecosystem, in which five insect species (one of which is a pest) are involved in creating a complex community structure that keeps the pest under control (the five species are an ant, Azteca sericeasur, a phorid fly parasitoid, Pseudacteon sp., a hymenopteran parasitoid, Coccophagus sp., a beetle predator, Azya orbigera, and the pest itself, the green coffee scale, Coccus viridis). We use the qualitative framing of the three theoretical schemata to develop a cellular automata model that casts the basic predator/prey (natural enemy/pest) system as an intransitive oscillator, and then explore the interaction of the two basic predator/prey systems as coupled oscillators within this model framework. We note that Gause’s principle of competitive exclusion is not violated with this basic framing (i.e., the two control agents cannot coexist theoretically), but that with a change in the spatial structure of the background habitat, coexistence can be maintained through the tradeoff between regional dispersal and local consumption. Finally, we explore how the other oscillator in the system (the ant and its phorid parasitoid) can act as a pilot system, creating the spatial structure in which the other two oscillators operate, but only in the context of disjoint time frames (between the two control agents and the pilot subsystem).Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146945/1/ecs22489.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146945/2/ecs22489_am.pd

Memristors for the Curious Outsiders

We present both an overview and a perspective of recent experimental advances and proposed new approaches to performing computation using memristors. A memristor is a 2-terminal passive component with a dynamic resistance depending on an internal parameter. We provide an brief historical introduction, as well as an overview over the physical mechanism that lead to memristive behavior. This review is meant to guide nonpractitioners in the field of memristive circuits and their connection to machine learning and neural computation.Comment: Perpective paper for MDPI Technologies; 43 page

MULTI‐PHYSICAL MODELLING AND PROTOTYPING OF AN ENERGY HARVESTING SYSTEM INTEGRATED IN A RAILWAY PNEUMATIC SUSPENSION

The aim of this PhD thesis is the investigation of an energy harvesting system to be integrated in a railway pneumatic spring to recovery otherwise wasted energy source from suspension vibration. Exploiting the piezoelectric effect to convert the mechanical energy into an electrical one, the final scope consists on the use of this system to power supply one or more sensors that can give useful information for the monitoring and the diagnostics of vehicle or its subsystems. Starting from the analysis of the energy sources, a multi‐physical approach to the study of an energy harvesting system is proposed to take into account all physics involved in the phenomenon, to make the most of the otherwise wasted energy and to develop a suitable and affordable tool for the design. The project of the energy harvesting device embedded in a railway pneumatic spring has been carried out by means of using a finite element technique and multi‐physics modelling activity. The possibility to combine two energy extraction processes was investigated with the purpose of making the most of the characteristics of the system and maximize the energy recovering. Exploiting commercial piezoelectric transducers, an experimental activity was conducted in two steps. A first mock‐up was built and tested on a shaker to develop the device and to tune the numerical model against experimental evidence. In the second step a fullscale prototype of an air spring for metro application with the EH system was realized. In order to test the full‐scale component, the design of a new test bench was carried out. Finally, the Air spring integrated with the EH device was tested and models validated

Data-based design of high-performance motion controllers

This paper presents a data-based design of a linear feedback controller which realizes desired closed-loop sensitivity and complementary sensitivity transfer functions. These transfer functions are specified via a single model-based performance cost. The data-based equivalent of this cost is derived, and its utility for the feedback design is demonstrated. A designer can prescribe the controller structure and complexity. Experimental results obtained in a direct-drive robot motion control problem confirm the effectiveness of the design