SearcharxivSearch

arXiv · 2504.10311

Performance of a Brownian information engine through potential profiling: Optimum output requisites, Heating-to-Refrigeration transition and their Re-entrance

Abstract

Brownian Information engine (BIE) harnesses the energy from a fluctuating environment by utilizing the associated information change in the presence of a single heat bath. The engine operates in a space-dependent confining potential and requires an appropriate feedback control mechanism. In general, the feedback controller has three different steps: measurement, feedback, and relaxation. The feedback step is related to a sudden change in the potential energy that is essential for a nonzero work output. BIE utilises the amount of information (surprise) acquired during the measurement step for the energy output. However, due to the relaxation process, a certain amount of acquired information is lost or becomes unavailable. So, controlling information loss during relaxation is crucial for the overall efficiency of the engine. The net (available) information, therefore, can be monitored by tuning the feedback controller and the shape of the confining potential. In this paper, we explore the effect of the shape modulation of the confining potential, which may have multiple stable valleys and unstable hills, on the net available information and, hence, the performance of a BIE that operates under an asymmetric feedback protocol. We examine the optimal performance requirements of the BIE and the amount of maximum work output under different potential profiling. For monostable trapping, a concave shape in confining potential results in a higher work output than a convex one. We also find that hills and valleys in the confining potential may lead to multiple good operating conditions. An appropriate shape modulation can create a heater-refrigerator transition and their reentrance due to non-trivial changes in information loss during the relaxation process.

Explore related subjects

Keep this discovery

BibTeXRIS

Rafna Rafeek, Debasish Mondal. 2025-04-14. Performance of a Brownian information engine through potential profiling: Optimum output requisites, Heating-to-Refrigeration transition and their Re-entrance. https://arxiv.org/abs/2504.10311

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Slow Dynamics and the Geometry of Jammed Packings

Saddle points in the energy landscape of granular packings dominate the discrete steepest descent dynamics and ultimately determine the path that an out of mechanical equilibrium packing will follow and the resulting stable minimum that it will find. The saddle points that ultimately determine the resulting minima tend to be low-index saddle points. For models with an analytic energy landscape, such as the $p$-spin model, the steepest descent minimization path is affected by higher-index saddle points, which pull the system towards saddle points of decreasing index before arriving at the minima. Here, we examine the steepest descent minimization path of granular packings and compare them to the $p$-spin model. We show that the granular packing steepest descent minimization paths act like their smooth energy landscape counterparts and get attracted by saddle points. The index versus time curves for all models follow a shifted, stretched exponential. We further show that the shape parameter for the granular packings is unchanged when the energy landscape is modified to become analytic (Gaussian potential in a harmonic well) or non-local (Mari-Krzakala-Kurchan). The $p$-spin, on the other hand, has a significantly larger shape parameter. The reason is not due to the dimensionality, packing fraction, nonanalyticity, or the locality of the Hamiltonian of the models. The exact reason for the discrepancy in the shape parameter is \st{still} an unsolved mystery.

cond-mat.soft

A Phase-Field Study of Desiccation Crack Pattern Maturation under Drying-Wetting Cycles

The characteristic intersection angle of the desiccation crack relaxes from near \ang{90} toward \ang{120} under repeated drying--wetting cycles. However, the theoretical understanding of this relaxation is insufficient, especially the modeling of the drying--wetting cycles. Here we introduce a phase-field model of desiccation fracture, extending the model proposed in previous studies by adding crack healing and a scar effect left by past cracks. By repeating drying--wetting cycles in a finite element simulation, we find that the angle distribution develops a growing peak near \ang{120} as the cycle number increases, consistent with experiments. The standard deviation of the intersection angle from \ang{120} relaxes exponentially with a characteristic time of about 2.85 cycles. These results are consistent with experiments, except that the characteristic time is slightly smaller than the experimental value. Crack energy dominates the total energy and also relaxes exponentially with nearly the same characteristic cycle as the angle relaxation. This decay is driven mainly by a shortening of the effective crack length rather than a change in effective fracture toughness.

cond-mat.soft

Kinetics of ferritin crystal formation and melting in acoustically levitated droplets

Understanding protein crystallization pathways is essential for controlling crystallization in structural biology, materials science, and pharmaceutical applications. Classical nucleation theory does not fully capture crystallization processes for several proteins, including ferritin. Here, we combine acoustic levitation with small- and wide-angle X-ray scattering (SAXS and WAXS) to monitor ferritin crystallization in evaporating aqueous polyethylene glycol (PEG) solutions. Acoustic levitation rapidly drives the droplets through a broad range of protein and polymer concentrations, enabling time-resolved measurements of crystallization during evaporation. The scattering data show that ferritin crystals form during evaporation and subsequently lose their crystalline order upon further dehydration. Varying the PEG molecular weight switches between distinct crystallization pathways: one dominated by attractive protein-protein interactions and another dominated by repulsive interactions and excluded-volume effects. Furthermore, we find that lower molecular weight PEG (1000 g/mol) suppresses the dehydration-induced loss of crystalline order observed for higher molecular weight PEG (6000 g/mol), providing a simple strategy for improving protein crystal stability.

cond-mat.soft