{"id":223719,"date":"2025-10-21T04:23:35","date_gmt":"2025-10-21T09:23:35","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2025\/10\/a-mathematical-rosetta-stone-translates-and-predicts-the-larger-effects-of-molecular-systems"},"modified":"2025-10-21T04:23:35","modified_gmt":"2025-10-21T09:23:35","slug":"a-mathematical-rosetta-stone-translates-and-predicts-the-larger-effects-of-molecular-systems","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2025\/10\/a-mathematical-rosetta-stone-translates-and-predicts-the-larger-effects-of-molecular-systems","title":{"rendered":"A mathematical \u2018Rosetta Stone\u2019 translates and predicts the larger effects of molecular systems"},"content":{"rendered":"

<\/a><\/p>\n

Penn Engineers have developed a mathematical \u201cRosetta Stone\u201d that translates atomic and molecular movements into predictions of larger-scale effects, like proteins unfolding, crystals forming and ice melting, without the need for costly, time-consuming simulations or experiments. That could make it easier to design smarter medicines, semiconductors and more.<\/p>\n

In a recent paper<\/a> in Journal of the Mechanics and Physics of Solids<\/i>, the Penn researchers used their framework, stochastic thermodynamics with internal variables<\/a> (STIV), to solve a 40-year problem in phase-field modeling, a widely used tool for studying the shifting frontier between two states of matter, like the boundary between water and ice or where the folded and unfolded parts of a protein join.<\/p>\n

\u201cPhase-field modeling is about predicting what happens at the thin frontier between phases of matter, whether it\u2019s proteins folding, crystals forming or ice melting,\u201d says Prashant Purohit, Professor in Mechanical Engineering and Applied Mechanics (MEAM) and one of the paper\u2019s co-authors. \u201cSTIV gives us the mathematical machinery to describe how that frontier evolves directly from first principles, without needing to fit data from experiments.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

Penn Engineers have developed a mathematical \u201cRosetta Stone\u201d that translates atomic and molecular movements into predictions of larger-scale effects, like proteins unfolding, crystals forming and ice melting, without the need for costly, time-consuming simulations or experiments. That could make it easier to design smarter medicines, semiconductors and more. In a recent paper in Journal of [\u2026]<\/p>\n","protected":false},"author":427,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,38,2229],"tags":[],"class_list":["post-223719","post","type-post","status-publish","format-standard","hentry","category-biotech-medical","category-engineering","category-mathematics"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/223719","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/427"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=223719"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/223719\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=223719"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=223719"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=223719"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}