[Demo] Active Matter as Information Engines
Updated: 14 hours ago
Authors: SciViD Editorial (demonstration item)
*Affiliation: SciViD, 4101 Brisbane, Queensland, Australia
DEMONSTRATION ITEM · PRELIMINARY · NOT PEER REVIEWED · REVIEW AND PERSPECTIVE
Type: Review / perspective · Collection: Micro- and Nanotechnology
Interactive lab: https://information-horizon-lab.gainscholar.workers.dev
Corresponding author: editor@scivid.net
Abstract
An information engine converts information about a system into work or directed motion, subject to thermodynamic bounds such as the Landauer limit of k_BT ln 2 (about 2.9 × 10⁻²¹ J per bit at 300 K) and the generalized second law for feedback control. Experimental realizations have so far relied mainly on colloidal particles in optical or electrical traps, where measurement and feedback are performed by external instruments. This review asks whether catalytic micro- and nanomotors, self-propelled particles that convert chemical energy into motion, can serve as materials-based platforms for information processing in which part of the sensing, memory and response is embedded in the material itself. The article is organized in four parts. The first summarizes the materials, catalytic reactions and operating media of catalytic motors. The second examines autonomous motion and environmental response, including chemotaxis-like behavior, as candidate forms of sensing and stored state. The third discusses external fields (magnetic, optical, acoustic and electric) as platforms for controlled measurement-and-feedback experiments. The fourth outlines a theoretical framework that connects active-matter stochastic thermodynamics with information-theoretic descriptions of feedback. A central caution runs throughout: the motion of a catalytic motor is driven far from equilibrium by fuel consumption, so its directed motion does not by itself demonstrate information-to-work conversion. The article distinguishes established results, interpretations and open hypotheses, and identifies the measurements that would be needed to quantify information flow in such systems.
Article information
IDENTIFIER: SciViD-DEMO-03. This is a demonstration identifier outside the SciViD preprint sequence; it is not a DOI.
VERSION HISTORY: version 1, posted Oct 24, 2026. REVIEW STATUS: preliminary; not peer reviewed. License: CC BY 4.0
AI USE: Literature organization, figure preparation and drafting were assisted by AI tools; all statements and citations were checked by the SciViD editorial team against the original sources.
NOT FOR CITATION: this demonstration item illustrates the SciViD format and is not a research record.
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