<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Research on CEAD Lab</title><link>https://ceadpx.github.io/research/</link><description>Recent content in Research on CEAD Lab</description><generator>Hugo</generator><language>en-us</language><atom:link href="https://ceadpx.github.io/research/index.xml" rel="self" type="application/rss+xml"/><item><title>Mechanics and design of field-responsive materials</title><link>https://ceadpx.github.io/research/field-responsive-materials/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://ceadpx.github.io/research/field-responsive-materials/</guid><description>How electric and magnetic fields interact with microstructure, interfaces and geometry, and how those interactions determine actuation, adhesion and degradation in soft composites.</description></item><item><title>Fracture and failure in heterogeneous materials</title><link>https://ceadpx.github.io/research/fracture-and-failure/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://ceadpx.github.io/research/fracture-and-failure/</guid><description>How matrix cracking, interface debonding, particle fracture and contact interactions compete to control strength, toughness, localization and residual load capacity.</description></item><item><title>Reliable scientific AI for mechanics, discovery and design</title><link>https://ceadpx.github.io/research/reliable-scientific-ai/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://ceadpx.github.io/research/reliable-scientific-ai/</guid><description>How residuals, error estimates and targeted high-fidelity solves can determine when a reduced or learned model is accurate enough for inference, optimization or design.</description></item></channel></rss>