{"id":660,"date":"2025-09-21T11:33:49","date_gmt":"2025-09-21T17:33:49","guid":{"rendered":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/?p=660"},"modified":"2025-09-21T11:33:49","modified_gmt":"2025-09-21T17:33:49","slug":"entropic-path-sampling","status":"publish","type":"post","link":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/2025\/09\/21\/entropic-path-sampling\/","title":{"rendered":"Entropic Path Sampling"},"content":{"rendered":"<p data-start=\"0\" data-end=\"1045\">Entropic path sampling (EPS) was developed by our group as a trajectory-based protocol to quantify how configurational entropy varies along a reaction path, especially after the transition state, by harvesting ensembles of snapshots from quasiclassical direct-dynamics trajectories, slicing them into structural windows (e.g., by forming-bond length), and computing entropy with an internal-coordinate, histogram-based estimator using the mutual-information spanning tree. The resulting \u2212T\u0394S profile reveals \u201centropic traps\u201d and allows one to distinguish long-lived dynamic intermediates from rigorously defined entropic intermediates (free-energy minima that arise from entropy rather than potential-energy wells). EPS has been benchmarked on cyclopentadiene dimerization, where it captures subtle (\u22643 kcal\u00b7mol\u207b\u00b9) entropic features that normal-mode (harmonic) analysis misses or reverses in sign, demonstrating the value of trajectory ensembles and anharmonic entropy estimates for post-TS bifurcations and selectivity analysis.<\/p>\n<p data-start=\"1047\" data-end=\"1652\">An accelerated variant, BGAN-EPS, uses a bidirectional generative adversarial network to augment configuration distributions so that converged entropic profiles can be recovered from only a few hundred trajectories (e.g., ~124 versus a 2,480-trajectory reference), enabling routine application to complex systems. Beyond speedups, BGAN-EPS also uncovered a \u201chidden entropic intermediate\u201d, a dynamically trapped species at a local entropic maximum without a corresponding free-energy minimum, highlighting how entropy can mediate outcomes on otherwise downhill surfaces.<\/p>\n<p><strong>The software code<\/strong>:<\/p>\n<p>https:\/\/github.com\/rshin1209\/bgan_eps\/<\/p>\n<p>https:\/\/github.com\/ZJYgrp\/Entropic_Path_Sampling<\/p>\n<p><strong>Publications<\/strong>:<\/p>\n<p>https:\/\/pubs.acs.org\/doi\/abs\/10.1021\/acs.jpcb.3c01202<\/p>\n<p>https:\/\/pubs.acs.org\/doi\/10.1021\/acs.jpclett.1c03116<\/p>\n<p>https:\/\/pubs.acs.org\/doi\/10.1021\/acs.jctc.4c01138?ref=recommended<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Entropic path sampling (EPS) was developed by our group as a trajectory-based protocol to quantify how configurational entropy varies along a reaction path, especially after the transition state, by harvesting ensembles of snapshots from quasiclassical direct-dynamics trajectories, slicing them into structural windows (e.g., by forming-bond length), and computing entropy with an internal-coordinate, histogram-based estimator using&#8230;<\/p>\n","protected":false},"author":253,"featured_media":661,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[9],"tags":[],"class_list":["post-660","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-software"],"acf":[],"_links":{"self":[{"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/posts\/660","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/users\/253"}],"replies":[{"embeddable":true,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/comments?post=660"}],"version-history":[{"count":1,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/posts\/660\/revisions"}],"predecessor-version":[{"id":662,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/posts\/660\/revisions\/662"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/media\/661"}],"wp:attachment":[{"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/media?parent=660"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/categories?post=660"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/tags?post=660"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}