{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T13:08:21Z","timestamp":1790255301319,"version":"4.1.0"},"reference-count":60,"publisher":"American Chemical Society (ACS)","issue":"38","license":[{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"funder":[{"DOI":"10.13039\/501100020959","name":"JST-Mirai Program","doi-asserted-by":"publisher","award":["JP-MJMI25G1"],"award-info":[{"award-number":["JP-MJMI25G1"]}],"id":[{"id":"10.13039\/501100020959","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005946","name":"Hokkaido University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005946","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009024","name":"Exploratory Research for Advanced Technology","doi-asserted-by":"publisher","award":["JPMJER1903"],"award-info":[{"award-number":["JPMJER1903"]}],"id":[{"id":"10.13039\/501100009024","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009023","name":"Precursory Research for Embryonic Science and Technology","doi-asserted-by":"publisher","award":["JPMJPR24T5"],"award-info":[{"award-number":["JPMJPR24T5"]}],"id":[{"id":"10.13039\/501100009023","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["24K01241"],"award-info":[{"award-number":["24K01241"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP23H01762"],"award-info":[{"award-number":["JP23H01762"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008238","name":"Hitachi","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008238","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,9,24]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Conventional catalyst informatics largely relies on composition-based descriptors for catalytic activity prediction. In this study, heterogeneous characterization data are integrated into a multidimensional measurement space and transformed into measurement-derived descriptors for machine-learning analysis. This shift from composition-based to measurement-centered catalyst informatics enables characterization information that is conventionally interpreted individually to be evaluated systematically and quantitatively in combination, providing a framework for describing the activity landscape across catalytic states. Importantly, combining complementary measurement-derived descriptors enables highly accurate prediction of CO2 conversion while revealing complex factors and interactions associated with catalytic activity. Thus, measurement informatics provides a rational framework for extracting interpretable structure\u2013activity relationships from experimental measurement data.<\/jats:p>","DOI":"10.1021\/acs.jpclett.6c02053","type":"journal-article","created":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T08:11:32Z","timestamp":1789459892000},"page":"10942-10951","source":"Crossref","is-referenced-by-count":0,"title":["Learning Interpretable\nActivity Descriptors Directly\nfrom Measurement Features in Heterogeneous Catalysis"],"prefix":"10.1021","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-4918-9187","authenticated-orcid":true,"given":"Yoshiki","family":"Hasukawa","sequence":"first","affiliation":[{"name":"Hokkaido University , , North 10, West 8 , ,","place":["Sapporo, Japan, 060-0810"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0587-3372","authenticated-orcid":true,"given":"Fernando","family":"Garcia-Escobar","sequence":"additional","affiliation":[{"name":"Hokkaido University , , North 10, West 8 , ,","place":["Sapporo, Japan, 060-0810"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9922-8889","authenticated-orcid":true,"given":"Lauren","family":"Takahashi","sequence":"additional","affiliation":[{"name":"Hokkaido University , , North 10, West 8 , ,","place":["Sapporo, Japan, 060-0810"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9328-1694","authenticated-orcid":true,"given":"Keisuke","family":"Takahashi","sequence":"additional","affiliation":[{"name":"Hokkaido University , , North 10, West 8 , ,","place":["Sapporo, Japan, 060-0810"]},{"name":"Hokkaido University , , ,","place":["Sapporo, Japan, 001-0020"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"2026092408420796400_cit1","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.cattod.2012.04.003","article-title":"The past, present and future of heterogeneous\ncatalysis","volume":"189","author":"Fechete","year":"2012","journal-title":"Catal. Today"},{"key":"2026092408420796400_cit2","doi-asserted-by":"publisher","first-page":"100078","DOI":"10.1016\/j.grets.2024.100078","article-title":"Catalysts\ndriving efficiency and innovation in thermal\nreactions: A comprehensive review","volume":"2","author":"Isahak","year":"2024","journal-title":"Green Technol.\nSustainability"},{"key":"2026092408420796400_cit3","doi-asserted-by":"publisher","first-page":"4537","DOI":"10.1002\/cctc.201900971","article-title":"Statistical analysis\nand discovery\nof heterogeneous catalysts based on machine learning from diverse\npublished data","volume":"11","author":"Suzuki","year":"2019","journal-title":"ChemCatChem"},{"key":"2026092408420796400_cit4","doi-asserted-by":"publisher","first-page":"14751","DOI":"10.1021\/acscatal.5c03844","article-title":"Use of Large Language\nModels for Extracting and Analyzing Data from\nHeterogeneous Catalysis Literature","volume":"15","author":"Walls","year":"2025","journal-title":"ACS Catal."},{"key":"2026092408420796400_cit5","doi-asserted-by":"publisher","first-page":"e202216383","DOI":"10.1002\/anie.202216383","article-title":"Data-driven machine\nlearning for understanding surface structures of heterogeneous catalysts","volume":"62","author":"Li","year":"2023","journal-title":"Angew. Chem., Int. Ed."},{"key":"2026092408420796400_cit6","doi-asserted-by":"publisher","first-page":"1616","DOI":"10.1021\/acscatal.4c06717","article-title":"Machine learning potentials\nfor heterogeneous catalysis","volume":"15","author":"Omranpour","year":"2025","journal-title":"ACS Catal."},{"key":"2026092408420796400_cit7","doi-asserted-by":"publisher","first-page":"2222","DOI":"10.1039\/D2CC05938J","article-title":"Catalysts\ninformatics: paradigm shift towards data-driven\ncatalyst design","volume":"59","author":"Takahashi","year":"2023","journal-title":"Chem. Commun."},{"key":"2026092408420796400_cit8","doi-asserted-by":"publisher","first-page":"15735","DOI":"10.1021\/jacs.2c06143","article-title":"Synthesis of heterogeneous catalysts\nin catalyst informatics to bridge experiment and high-throughput calculation","volume":"144","author":"Takahashi","year":"2022","journal-title":"J. Am. Chem. Soc."},{"key":"2026092408420796400_cit9","doi-asserted-by":"publisher","first-page":"20825","DOI":"10.1021\/acscatal.5c06074","article-title":"others Extrapolative-Machine-Learning-Guided\nDiscovery of Multielemental Heterogeneous Catalysts for Low-Temperature\nNO Reduction by H2","volume":"15","author":"Jing","year":"2025","journal-title":"ACS Catal."},{"key":"2026092408420796400_cit10","doi-asserted-by":"publisher","first-page":"8462","DOI":"10.1021\/acs.iecr.1c05079","article-title":"Machine learning-aided\ncatalyst modification in oxidative\ncoupling of methane via manganese promoter","volume":"61","author":"Nishimura","year":"2022","journal-title":"Ind. Eng. Chem. Res."},{"key":"2026092408420796400_cit11","doi-asserted-by":"publisher","first-page":"159942","DOI":"10.1016\/j.apsusc.2024.159942","article-title":"Screening\nof transition metal dual-atom catalysts for hydrogen evolution reaction\nbased on high-throughput calculation and searching surrogate prediction\nmodel using simple features","volume":"659","author":"Wang","year":"2024","journal-title":"Appl. Surf. Sci."},{"key":"2026092408420796400_cit12","doi-asserted-by":"publisher","first-page":"3188","DOI":"10.1021\/acscatal.5c07032","article-title":"Descriptor\nIdentification and Synthesis of Bimetallic\nCatalysts for CO2 Methanation","volume":"16","author":"Hasukawa","year":"2026","journal-title":"ACS\nCatal."},{"key":"2026092408420796400_cit13","doi-asserted-by":"publisher","first-page":"1544","DOI":"10.1021\/acsami.5c20537","article-title":"Automated\nFeature Engineering and Model Aggregation for Data-Driven Oxidative\nCoupling of Methane Catalyst Design","volume":"18","author":"Garcia-Escobar","year":"2025","journal-title":"ACS Appl.\nMater. Interfaces"},{"key":"2026092408420796400_cit14","doi-asserted-by":"publisher","first-page":"11749","DOI":"10.1021\/acscatal.3c06293","article-title":"From characterization to discovery: artificial intelligence,\nmachine learning and high-throughput experiments for heterogeneous\ncatalyst design","volume":"14","author":"Benavides-Hernandez","year":"2024","journal-title":"ACS Catal."},{"key":"2026092408420796400_cit15","doi-asserted-by":"publisher","first-page":"8594","DOI":"10.1021\/acs.chemrev.1c00905","article-title":"Designing\nsites in heterogeneous catalysis: are we reaching selectivities competitive\nwith those of homogeneous catalysts?","volume":"122","author":"Zaera","year":"2022","journal-title":"Chem.\nRev."},{"key":"2026092408420796400_cit16","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1021\/acs.chemrev.3c00402","article-title":"Crystal-phase engineering in heterogeneous catalysis","volume":"124","author":"Zhao","year":"2024","journal-title":"Chem. Rev."},{"key":"2026092408420796400_cit17","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1038\/s41570-021-00340-y","article-title":"The concept of active site in heterogeneous\ncatalysis","volume":"6","author":"Vogt","year":"2022","journal-title":"Nat. Rev. Chem."},{"key":"2026092408420796400_cit18","doi-asserted-by":"publisher","first-page":"17648","DOI":"10.1039\/D1RA02327F","article-title":"Role of oxide support\nin Ni based catalysts for CO\n2 methanation","volume":"11","author":"Lee","year":"2021","journal-title":"RSC Adv."},{"key":"2026092408420796400_cit19","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1080\/08940886.2022.2078580","article-title":"Operando X-ray Photoelectron Spectroscopy\nfor High-Pressure\nCatalysis Research Using the POLARIS Endstation","volume":"35","author":"Degerman","year":"2022","journal-title":"Synchrotron Radiat. News"},{"key":"2026092408420796400_cit20","doi-asserted-by":"publisher","first-page":"13374","DOI":"10.1021\/acs.chemrev.3c00352","article-title":"Operando electron\nmicroscopy of catalysts: the missing cornerstone in heterogeneous\ncatalysis research?","volume":"123","author":"Chee","year":"2023","journal-title":"Chem. Rev."},{"key":"2026092408420796400_cit21","doi-asserted-by":"publisher","first-page":"101980","DOI":"10.1016\/j.jcou.2022.101980","article-title":"Monitoring\nby in situ NAP-XPS of active sites for CO2 methanation\non a Ni\/CeO2 catalyst","volume":"60","author":"Lopez-Rodriguez","year":"2022","journal-title":"J. CO2 Util."},{"key":"2026092408420796400_cit22","doi-asserted-by":"publisher","first-page":"4615","DOI":"10.1039\/c0cs00064g","article-title":"Infrared\nand Raman imaging of heterogeneous catalysts","volume":"39","author":"Stavitski","year":"2010","journal-title":"Chem. Soc. Rev."},{"key":"2026092408420796400_cit23","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1038\/s41524-023-00984-y","article-title":"Adaptively driven X-ray diffraction guided by machine learning for\nautonomous phase identification","volume":"9","author":"Szymanski","year":"2023","journal-title":"npj Comput.\nMater."},{"key":"2026092408420796400_cit24","doi-asserted-by":"publisher","first-page":"180053","DOI":"10.1038\/sdata.2018.53","article-title":"An open experimental\ndatabase for exploring inorganic materials","volume":"5","author":"Zakutayev","year":"2018","journal-title":"Sci. Data"},{"key":"2026092408420796400_cit25","doi-asserted-by":"publisher","first-page":"5576","DOI":"10.1039\/D3CY00587A","article-title":"Indirect design of\nOCM catalysts\nthrough machine learning of catalyst surface oxygen species","volume":"13","author":"Nishino","year":"2023","journal-title":"Catal. Sci. Technol."},{"key":"2026092408420796400_cit26","doi-asserted-by":"publisher","first-page":"10192","DOI":"10.1021\/acscatal.9b03599","article-title":"\u201cInverting\u201d X-ray absorption spectra\nof catalysts by machine learning in search for activity descriptors","volume":"9","author":"Timoshenko","year":"2019","journal-title":"ACS Catal."},{"key":"2026092408420796400_cit27","doi-asserted-by":"publisher","first-page":"e202401213","DOI":"10.1002\/cctc.202401213","article-title":"Low temperature Sabatier\nCO2 methanation","volume":"16","author":"Molinet-Chinaglia","year":"2024","journal-title":"ChemCatChem"},{"key":"2026092408420796400_cit28","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.cattod.2020.02.017","article-title":"Recent trend in thermal\ncatalytic low temperature CO2 methanation:\nA critical review","volume":"368","author":"Lee","year":"2021","journal-title":"Catal. Today"},{"key":"2026092408420796400_cit29","doi-asserted-by":"publisher","first-page":"114926","DOI":"10.1016\/j.rser.2024.114926","article-title":"Comprehensive\nreview of nickel-based catalysts advancements for CO2 methanation","volume":"207","author":"Medina","year":"2025","journal-title":"Renewable Sustainable Energy Rev."},{"key":"2026092408420796400_cit30","doi-asserted-by":"publisher","first-page":"e190","DOI":"10.1002\/cnl2.190","article-title":"Progress and Future Challenges in\nDesigning High-Performance Ni\/CeO2 Catalysts for CO2 Methanation: A Critical Review","volume":"4","author":"Liu","year":"2025","journal-title":"Carbon\nNeutralization"},{"key":"2026092408420796400_cit31","doi-asserted-by":"publisher","first-page":"5241","DOI":"10.1021\/acs.energyfuels.0c04238","article-title":"What are the best active\nsites for CO2 methanation over Ni\/CeO2?","volume":"35","author":"Tada","year":"2021","journal-title":"Energy Fuels"},{"key":"2026092408420796400_cit32","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.jcou.2020.01.016","article-title":"The distributions\nof alkaline earth metal oxides and their promotional effects on Ni\/CeO2 for CO2 methanation","volume":"38","author":"Liu","year":"2020","journal-title":"J.\nCO2 Util."},{"key":"2026092408420796400_cit33","doi-asserted-by":"publisher","first-page":"119562","DOI":"10.1016\/j.apcatb.2020.119562","article-title":"Highly selective and stable nickel\ncatalysts supported on ceria promoted with Sm2O3, Pr2O3 and MgO for the CO2 methanation\nreaction","volume":"282","author":"Siakavelas","year":"2021","journal-title":"Appl. Catal., B"},{"key":"2026092408420796400_cit34","doi-asserted-by":"publisher","first-page":"104317","DOI":"10.1016\/j.jtice.2022.104317","article-title":"Nanostructured ceria-zirconia\nsupported\nNi catalysts for high performance CO2 methanation: phase\nand morphology effect on activity","volume":"134","author":"Ullah","year":"2022","journal-title":"J. Taiwan\nInst. Chem. Eng."},{"key":"2026092408420796400_cit35","doi-asserted-by":"publisher","first-page":"10587","DOI":"10.1021\/acscatal.2c02535","article-title":"Frustrated\nLewis pairs boosting low-temperature CO2 methanation performance\nover Ni\/CeO2 nanocatalysts","volume":"12","author":"Xie","year":"2022","journal-title":"ACS Catal."},{"key":"2026092408420796400_cit36","doi-asserted-by":"publisher","first-page":"11096","DOI":"10.1039\/D4NR01409J","article-title":"Lattice capacity-dependent\nactivity\nfor CO2 methanation: crafting Ni\/CeO2 catalysts\nwith outstanding performance at low temperatures","volume":"16","author":"Liu","year":"2024","journal-title":"Nanoscale"},{"key":"2026092408420796400_cit37","doi-asserted-by":"publisher","first-page":"125029","DOI":"10.1016\/j.apcatb.2025.125029","article-title":"Understanding\ndefect generation on CeO2 and its utilization for enhanced\nmetal-support interactions in Ni\/CeO2 catalysts for improved\nCO2 methanation performance","volume":"366","author":"Chen","year":"2025","journal-title":"Appl.\nCatal., B"},{"key":"2026092408420796400_cit38","doi-asserted-by":"publisher","first-page":"120401","DOI":"10.1016\/j.apcatb.2021.120401","article-title":"Deciphering\nthe role of Ni particle size and nickel-ceria\ninterfacial perimeter in the low-temperature CO2 methanation\nreaction over remarkably active Ni\/CeO2 nanorods","volume":"297","author":"Varvoutis","year":"2021","journal-title":"Appl. Catal., B"},{"key":"2026092408420796400_cit39","unstructured":"Rohatgi, A.\n          \n          WebPlotDigitizer, ver. 5; automeris.io, 2024."},{"key":"2026092408420796400_cit40","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1038\/s41586-020-2649-2","article-title":"Array programming with\nNumPy","volume":"585","author":"Harris","year":"2020","journal-title":"Nature"},{"key":"2026092408420796400_cit41","unstructured":"pandas Development Team.\n          \n          pandas-dev\/pandas:\nPandas, 2020.10.5281\/zenodo.3509134."},{"key":"2026092408420796400_cit42","doi-asserted-by":"crossref","unstructured":"McKinney, W.\n          \n          Data Structures\nfor Statistical Computing in Python. In  Proceedings\nof the 9th Python in Science Conference; SciPy Proceedings, 2010; pp 56\u201361.10.25080\/Majora-92bf1922-00a.","DOI":"10.25080\/Majora-92bf1922-00a"},{"key":"2026092408420796400_cit43","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1109\/MCSE.2007.55","article-title":"Matplotlib:\nA 2D graphics environment","volume":"9","author":"Hunter","year":"2007","journal-title":"Comput. Sci. Eng."},{"key":"2026092408420796400_cit44","first-page":"2825","article-title":"Scikit-learn: Machine\nlearning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"2026092408420796400_cit45","doi-asserted-by":"publisher","first-page":"16108","DOI":"10.1016\/j.ijhydene.2017.05.154","article-title":"Methanation\nof carbon dioxide over\nNi\/CeO2 catalysts: Effects of support CeO2 structure","volume":"42","author":"Zhou","year":"2017","journal-title":"Int. J. Hydrogen Energy"},{"key":"2026092408420796400_cit46","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.cattod.2018.04.067","article-title":"Morphology dependence\nof catalytic properties of Ni\/CeO2 for CO2 methanation:\nA kinetic and mechanism study","volume":"347","author":"Bian","year":"2020","journal-title":"Catal. Today"},{"key":"2026092408420796400_cit47","doi-asserted-by":"publisher","first-page":"8684","DOI":"10.1039\/C8RA10348H","article-title":"Preparation\nof Ni based mesoporous Al2O3 catalyst with enhanced\nCO2 methanation performance","volume":"9","author":"Lin","year":"2019","journal-title":"RSC\nAdv."},{"key":"2026092408420796400_cit48","doi-asserted-by":"publisher","first-page":"8340","DOI":"10.1021\/acs.energyfuels.2c01421","article-title":"Oxygen vacancies-mediated\nCO2 methanation over Ni\/CeO2\u2013ZrO2 solid solutions assembled on clay minerals","volume":"36","author":"Chen","year":"2022","journal-title":"Energy Fuels"},{"key":"2026092408420796400_cit49","doi-asserted-by":"publisher","first-page":"137051","DOI":"10.1016\/j.fuel.2025.137051","article-title":"Oxygen vacancy regulation\nin CO2 methanation catalysis: Mechanistic insights and\nresearch advances","volume":"406","author":"Sheng","year":"2026","journal-title":"Fuel"},{"key":"2026092408420796400_cit50","doi-asserted-by":"publisher","first-page":"119561","DOI":"10.1016\/j.apcatb.2020.119561","article-title":"Vacancy\nengineering of the nickel-based catalysts for enhanced CO2 methanation","volume":"282","author":"Zhu","year":"2021","journal-title":"Appl. Catal., B"},{"key":"2026092408420796400_cit51","doi-asserted-by":"publisher","first-page":"6089","DOI":"10.1016\/j.ijhydene.2021.11.214","article-title":"Why Ni\/CeO2 is more active than Ni\/SiO2 for\nCO2 methanation? Identifying effect of Ni particle size\nand oxygen vacancy","volume":"47","author":"Liu","year":"2022","journal-title":"Int. J. Hydrogen Energy"},{"key":"2026092408420796400_cit52","doi-asserted-by":"publisher","first-page":"6753","DOI":"10.1021\/acssuschemeng.0c01148","article-title":"Three-dimensional networked\nNi-phyllosilicate catalyst for CO2 methanation: achieving\nhigh dispersion and enhanced stability\nat high Ni loadings","volume":"8","author":"Dong","year":"2020","journal-title":"ACS Sustainable Chem. Eng."},{"key":"2026092408420796400_cit53","doi-asserted-by":"publisher","first-page":"5095","DOI":"10.1039\/C5CY01361E","article-title":"Ammonia-assisted synthesis towards\na phyllosilicate-derived highly-dispersed and long-lived Ni\/SiO2 catalyst","volume":"5","author":"Yang","year":"2015","journal-title":"Catal. Sci. Technol."},{"key":"2026092408420796400_cit54","doi-asserted-by":"publisher","first-page":"14727","DOI":"10.1021\/acs.iecr.4c01708","article-title":"Interpretable\nmachine learning for accelerating reverse design and\noptimizing CO2 methanation catalysts with high activity\nat low temperatures","volume":"63","author":"Yang","year":"2024","journal-title":"Ind. Eng. Chem. Res."},{"key":"2026092408420796400_cit55","doi-asserted-by":"publisher","first-page":"23149","DOI":"10.1038\/s41598-024-73848-0","article-title":"Insight and\ncomprehensive study of Ni-based catalysts supported on various metal\noxides for CO2 methanation","volume":"14","author":"Kuhaudomlap","year":"2024","journal-title":"Sci.\nRep."},{"key":"2026092408420796400_cit56","doi-asserted-by":"publisher","first-page":"119922","DOI":"10.1016\/j.apcatb.2021.119922","article-title":"Decoupling\nthe effect of Ni particle\nsize and surface oxygen deficiencies in CO2 methanation\nover ceria supported Ni","volume":"286","author":"Hao","year":"2021","journal-title":"Appl. Catal., B"},{"key":"2026092408420796400_cit57","doi-asserted-by":"publisher","first-page":"20289","DOI":"10.1021\/jacs.3c04284","article-title":"Structure\nsensitivity of CO2 hydrogenation\non Ni revisited","volume":"145","author":"Simons","year":"2023","journal-title":"J. Am. Chem. Soc."},{"key":"2026092408420796400_cit58","doi-asserted-by":"publisher","first-page":"15451","DOI":"10.1021\/acscatal.2c04437","article-title":"Unveiling the key factors\nin determining\nthe activity and selectivity of CO2 hydrogenation over\nNi\/CeO2 catalysts","volume":"12","author":"Zheng","year":"2022","journal-title":"ACS Catal."},{"key":"2026092408420796400_cit59","doi-asserted-by":"publisher","first-page":"139708","DOI":"10.1016\/j.energy.2025.139708","article-title":"Machine learning-guided\nCO2 methanation: From catalyst design optimization to techno-economic\nand life cycle assessment analyses","volume":"342","author":"Golvirdizadeh","year":"2026","journal-title":"Energy"},{"key":"2026092408420796400_cit60","doi-asserted-by":"publisher","first-page":"118064","DOI":"10.1016\/j.jece.2025.118064","article-title":"Machine learning optimization of catalytic CO2 hydrogenation to dimethyl ether for clean fuel production","volume":"13","author":"Ghafarian Nia","year":"2025","journal-title":"J. Environ. Chem. Eng."}],"container-title":["The Journal of Physical\nChemistry Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jpclett.6c02053","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/jpclcd\/article-pdf\/17\/38\/10942\/68507290\/acs.jpclett.6c02053.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pubs.acs.org\/jpclcd\/article-pdf\/17\/38\/10942\/68507290\/acs.jpclett.6c02053.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T12:53:32Z","timestamp":1790254412000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/jpclcd\/article\/17\/38\/10942\/5429762\/Learning-Interpretable-Activity-Descriptors"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,15]]},"references-count":60,"journal-issue":{"issue":"38","published-online":{"date-parts":[[2026,9,15]]},"published-print":{"date-parts":[[2026,9,24]]}},"URL":"https:\/\/doi.org\/10.1021\/acs.jpclett.6c02053","relation":{},"ISSN":["1948-7185"],"issn-type":[{"value":"1948-7185","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,15]]}}}