Information Propagation and Encoding in Solids: A Quantitative Approach Towards Mechanical Intelligence

TL;DR

This paper develops a quantitative framework using information theory to analyze how information propagates through elastic solids, linking mechanical phenomena to information transmission and enabling design of structures for mechanical intelligence.

Contribution

It introduces a novel information-theoretic approach to quantify information transfer in elastic bodies, bridging mechanics and information processing for mechanical intelligence.

Findings

Information transmission can be quantified using information theory in elastic bodies.

Geometry and material architecture influence information propagation and blocking.

Framework enables design of structures with tailored information transmission properties.

Abstract

Engineered systems typically separate mechanical function from information processing, whereas biological systems can exploit physical structure as a medium for information processing and computation. Motivated by this contrast, recent work in mechanics has explored embedding information-processing capabilities directly into mechanical structures. However, quantitative frameworks for evaluating such capabilities remain limited. Here we address a foundational question: how does information propagate through a solid body? Using elastic bodies as a model system, we apply information-theoretic tools to treat an elastic domain as an information encoder and quantify how information transmits from applied loads to discrete sensor locations. We further connect these measures to familiar mechanical phenomena, including Saint-Venant's effect and principal stress lines. Moving toward design, we show how geometry and architected materials can tune transmission, enabling elastic domains to either transmit or block information. Overall, this work advances quantifiable metrics and benchmark tasks for mechanical intelligence, supporting comparable designs of mechanically embodied information processing.