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To address this, we introduce a fully automated and generally applicable workflow centered on integrated tempering sampling (ITS) within a nanoreactor framework. The protocol integrates ITS (a collective-variable-free enhanced sampling method) at the semiempirical GFN2-xTB level for reaction-space exploration, a hidden Markov model (HMM) for reaction-event identification, and high-level quantum-chemical calculations for mechanistic refinement, enabling autonomous discovery and validation of reaction pathways without any prior mechanistic input. Using formaldehyde\u2013ammonia and HCN\u2013water mixtures as case studies, the method successfully constructs extensive reaction networks. Notably, in the HCN\u2013water system, the generated network includes prebiotically relevant heterocycles and peptide-like species. This approach provides an efficient and broadly applicable route for systematic reaction-network discovery, shifting the paradigm from the hypothesis-driven verification of reaction mechanism to the automated exploration of unknown chemical spaces.<\/jats:p>","DOI":"10.1021\/acs.jctc.6c00571","type":"journal-article","created":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T15:02:13Z","timestamp":1786719733000},"page":"8094-8109","source":"Crossref","is-referenced-by-count":0,"title":["Systematic Construction\nof Chemical Reaction Networks:\nAn Automated Nanoreactor Approach Powered by Integrated Tempering\nSampling"],"prefix":"10.1021","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0220-1670","authenticated-orcid":true,"given":"Jie","family":"Li","sequence":"first","affiliation":[{"name":"South China Normal University , , ,","place":["Guangzhou, P. R. 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