Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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This study presents a Python-based tool for extracting molecular reaction pathways from kinetic simulation trajectory files. Compared to traditional depth first search (DFS) and breadth first search (BFS) algorithms, a more efficient chain analysis algorithm is introduced. The tool utilizes a full-time domain response analysis approach, enabling the identification of reactions across nonadjacent frames, thereby enhancing the comprehensiveness of the analysis. The responses are stored in a directed graph structure, and full integration of parallel computing significantly improves processing efficiency. The tool supports molecular dynamics, ab initio molecular dynamics, and coarse-grained simulations. As an open-source Python project, it offers both portability and wide applicability. The reaction processes in a propyne-ethylene blending system and the cross-linking reaction in an epoxy resin coarse-grained system are demonstrated, highlighting the tool's potential for analyzing various molecular systems.
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Source |
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http://dx.doi.org/10.1021/acs.jcim.5c01229 | DOI Listing |