02.12.2021NANO COLLOQUIA S3 Avinash Vikatakavi
Date and Time: December 2, 2021 - 15.00 ONLINE
25.11.2021Producing electricity from heat losses: engineered in Pisa the first device capable of achieving it in a controlled manner
It is now possible to create a new generation of “smart” thermoelectric systems to generate clea...
23.11.2021il progetto RIMMEL @ MECSPE - Bologna 2021
Si svolgerà martedì 23 novembre, dalle 16.45 alle 17.45 (Sala Concerto c/o Centro Servizi – Bolo...
19.11.2021Graphene as a solid lubricant becomes super-slippery
Cnr Nano researchers in collaboration with Sussex University and Rice University studied the frictio...
17.11.2021International Workshop on Advanced Materials-to-Device Solutions for Synaptic Electronics
CNR Nano and ICN2 organized the
03.11.2021The RIMMEL Project @ l'Europa è qui 2021 – VOTE THE VIDEO ONLINE
The RIMMEL project enters the “Europe is here ...
11.10.2021Quantum computers become an experimental physics laboratory
A quantum computer is a machine designed to do calculations. Now a group of physicists from CnrNano,...
05.10.20212021 Nobel Prize for the discoveries on TRPV1 and PIEZO receptors
The seminal discoveries by this year’s Nobel Laureates have explained how heat, cold and touch can...
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Date and Time: Thursday 17 January 2019 - 11:00 Venue: NEST Seminar Room, Third Floor, Physics Building, FIM Department Speaker: Paolo A. Erdman (SNS, NEST, NANO-CNR) Title: Optimal probabilistic work extraction beyond the free energy difference Abstract:We experimentally realize protocols that allow to extract work beyond the free energy difference from a single electron transistor at the single thermodynamic trajectory level. With two carefully designed out-of-equilibrium driving cycles featuring kicks of the control parameter, we demonstrate work extraction up to large fractions of kBT or with probabilities greater than 1/2, despite zero free energy difference over the cycle. Our results are explained in the framework of nonequilibrium fluctuation relations. We thus show that irreversibility can be used as a resource for optimal work extraction even in the absence of feedback, unlike in a traditional Maxwell’s Demon. For information, please contact: Fabio Taddei (9038) - fabio.taddei@nano.cnr.it Stefan Heun (9472) - stefan.heun@nano.cnr.it