--------------------------------------------------------------------------------- Daniel Manzano Quantum Thermodynamics and Quantum Computation Group University of Granada Facultad de Ciencias, Av. Fuentenueva s/n Granada 18071, Spain Phone: +34 958241000 Ext: 20569 https://ic1.ugr.es/members/dmanzano/

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From: Raúl Rica Subject: Seminario NanoTLab: "Brownian Information Engines: The Essentials for Best Performance" (Rafna Rafeek) Date: 19. March 2025 at 10:56:28 CET To: noticias@listas.ugr.es

Seminario impartido por Rafna Rafeek (Department of Chemistry, Indian Institute of Technology Tirupati, Yerpedu 517619, Andhra Pradesh, India)

Fecha y hora: Martes 25 de marzo, 12:10 Lugar: Aula A04 (ubicada en Aulario A de la Faculta de Ciencias)

Título: Brownian Information Engines: The Essentials for Best Performance

Resumen:

This study explores how information can be used to extract energy from a system, inspired by the concept of Maxwell’s demon. Information engines, which convert information into useful work, have attracted interest due to their similarities with biological processes. Traditional engines operate by measuring a particle’s position and adjusting its environment accordingly. However, the impact of different external conditions on these engines is not fully understood.

The first part of the study examines an advanced information engine that incorporates additional energy sources beyond thermal fluctuations. The efficiency of this engine depends on the interaction between different time scales governing the system. Under optimal conditions, it can extract significantly more work than traditional setups. However, as certain parameters change, the additional energy gain diminishes, eventually resembling conventional systems.

The second part investigates how different force fields influence energy extraction. It finds that certain shapes allow for more efficient energy conversion. In particular, some force field configurations can transition between working as an engine and as a cooling mechanism, depending on external conditions. Finally, the study shows that using more complex force fields can further improve energy extraction, making these engines more effective.

References [1] Sagawa, T.; Ueda, M. Generalized Jarzynski Equality under Nonequilibrium Feedback Control. Phys. Rev. Lett. 2010, 104, 090602. [2] Parrondo, J. M.; Horowitz, J. M.; Sagawa, T. Thermodynamics of information. Nat. Phys. 2015, 11, 131. [3] Paneru, G.; Lee, D. Y.; Tlusty, T.; Pak, H. K. Lossless Brownian Information engine. Phys. Rev. Lett. 2018, 120, 020601. [4] Ali, S. Y.; Rafeek, R.; Mondal, D. Geometric Brownian information engine: Upper bound of the achievable work under feedback control. J. Chem. Phys. 2022, 156, 014902. [5] Rafeek, R.; Ali, S. Y.; Mondal, D. Geometric Brownian information engine: Essentials for the best performance. Phys. Rev. E 2023, 107, 044122. [6] Rafeek, R.; Mondal, D. Active Brownian information engine: Self-propulsion induced colossal performance. J. Chem. Phys. 2024, 161, 124116. [7] Rafeek, R.; Mondal, D. Achievable Information-Energy Exchange in a Brownian Information Engine through Potential Profiling. J. Phys. Chem. B Manusript Accepted.

Gracias, un saludo

Raúl

-- Raúl A. Rica Alarcón Nanoparticles Trapping Laboratory Department of Applied Physics School of Sciences Universidad de Granada Avda. Fuentenueva s/n 18071, Granada, Spain +34 958240015 (Office) +34 958241000 Ext. 20631 (Lab) nanotlab@ugr.es mailto:nanotlab@ugr.es

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