{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T07:04:40Z","timestamp":1780038280428,"version":"3.53.1"},"reference-count":60,"publisher":"IOP Publishing","issue":"2","license":[{"start":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T00:00:00Z","timestamp":1780012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T00:00:00Z","timestamp":1780012800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["J. Phys. Mater."],"published-print":{"date-parts":[[2026,6,1]]},"abstract":"Abstract<\/jats:title>\n \n The current structure-centric paradigm in artificial intelligence-driven materials discovery, despite delivering thousands of candidate structures, is stalling at a critical barrier: the synthesisability gap. We argue that closing this gap demands a pivot to a synthesis-first paradigm in which executable synthesis protocols, not just atomic configurations, are treated as primary design variables. We outline a roadmap built on three pillars: (i) representing synthesis procedures as machine-readable protocols, (ii) deploying generative and inverse-design models to propose actionable reaction pathways and recipes, and (iii) integrating closed-loop optimisation to refine protocols against experimental realities and sustainability constraints. Framed in terms of the causal backbone\n \n \n \n <\/jats:tex-math>\n \n \n P<\/mml:mi>\n \n \u2192<\/mml:mo>\n \n X<\/mml:mi>\n \n \u2192<\/mml:mo>\n \n y<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n from protocol\n \n \n \n <\/jats:tex-math>\n \n \n P<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n to structure\n \n \n \n <\/jats:tex-math>\n \n \n X<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n and properties\n \n \n \n <\/jats:tex-math>\n \n \n y<\/mml:mi>\n <\/mml:mrow>\n <\/mml:math>\n <\/jats:inline-formula>\n , this perspective sets out methodological building blocks, standards needs and self-driving laboratory integration strategies to accelerate reproducible, data-first materials discovery.\n <\/jats:p>","DOI":"10.1088\/2515-7639\/ae6e72","type":"journal-article","created":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T22:51:37Z","timestamp":1778885497000},"page":"021003","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Beyond structure: revolutionising materials discovery via AI-driven synthesis protocol-property relationships"],"prefix":"10.1088","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0275-4079","authenticated-orcid":true,"given":"Guillaume","family":"Lambard","sequence":"first","affiliation":[{"name":"Data-driven materials design group"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,5,29]]},"reference":[{"key":"jpmaterae6e72bib1","article-title":"Materials genome initiative for global competitiveness","author":"National Science and Technology Council","year":"2011","type":"other"},{"key":"jpmaterae6e72bib2","doi-asserted-by":"publisher","DOI":"10.1063\/1.4812323","type":"journal-article","article-title":"Commentary: the materials project: a materials genome approach to accelerating materials innovation","volume":"1","author":"Jain","year":"2013","journal-title":"APL Mater."},{"key":"jpmaterae6e72bib3","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1016\/j.commatsci.2012.02.005","type":"journal-article","article-title":"Aflow: an automatic framework for high-throughput materials discovery","volume":"58","author":"Curtarolo","year":"2012","journal-title":"Comput. 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