{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T11:42:57Z","timestamp":1773488577131,"version":"3.50.1"},"reference-count":61,"publisher":"American Chemical Society (ACS)","issue":"10","license":[{"start":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T00:00:00Z","timestamp":1600819200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T00:00:00Z","timestamp":1600819200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T00:00:00Z","timestamp":1600819200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"funder":[{"DOI":"10.13039\/100000015","name":"U.S. Department of Energy","doi-asserted-by":"publisher","award":["DE-EE0007888-9.5"],"award-info":[{"award-number":["DE-EE0007888-9.5"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]},{"name":"State of Delaware"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Chem. Inf. Model."],"published-print":{"date-parts":[[2020,10,26]]},"DOI":"10.1021\/acs.jcim.0c00699","type":"journal-article","created":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T20:38:26Z","timestamp":1600893506000},"page":"4673-4683","source":"Crossref","is-referenced-by-count":8,"title":["Thermochemical Data Fusion Using Graph Representation Learning"],"prefix":"10.1021","volume":"60","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6598-3939","authenticated-orcid":true,"given":"Himaghna","family":"Bhattacharjee","sequence":"first","affiliation":[{"name":"Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States"},{"name":"Catalysis Center for Energy Innovation and RAPID Manufacturing Institute, 221 Academy Street, Newark, Delaware 19716, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6795-8403","authenticated-orcid":true,"given":"Dionisios G.","family":"Vlachos","sequence":"additional","affiliation":[{"name":"Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States"},{"name":"Catalysis Center for Energy Innovation and RAPID Manufacturing Institute, 221 Academy Street, Newark, Delaware 19716, United States"}]}],"member":"316","published-online":{"date-parts":[[2020,9,23]]},"reference":[{"key":"ref1\/cit1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRev.140.A1133"},{"key":"ref2\/cit2","doi-asserted-by":"publisher","DOI":"10.1038\/natrevmats.2015.4"},{"key":"ref3\/cit3","doi-asserted-by":"publisher","DOI":"10.1016\/j.susc.2015.03.023"},{"key":"ref4\/cit4","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1006652108"},{"key":"ref5\/cit5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ces.2011.05.050"},{"key":"ref6\/cit6","doi-asserted-by":"publisher","DOI":"10.1038\/nmat1752"},{"key":"ref7\/cit7","doi-asserted-by":"publisher","DOI":"10.1016\/j.electacta.2010.02.056"},{"key":"ref8\/cit8","doi-asserted-by":"publisher","DOI":"10.1063\/1.3672219"},{"key":"ref9\/cit9","doi-asserted-by":"publisher","DOI":"10.1021\/jz101565j"},{"key":"ref10\/cit10","doi-asserted-by":"crossref","unstructured":"Perdew, J. P. Jacob\u2019s Ladder of Density Functional Approximations for the Exchange-Correlation Energy.In AIP Conference Proceedings; AIP Publishing, 2003; Vol. 577, pp 1\u201320.","DOI":"10.1063\/1.1390175"},{"key":"ref11\/cit11","doi-asserted-by":"publisher","DOI":"10.1126\/science.aah5975"},{"key":"ref12\/cit12","doi-asserted-by":"publisher","DOI":"10.1016\/j.susc.2015.03.023"},{"key":"ref13\/cit13","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.85.235149"},{"key":"ref14\/cit14","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bth294"},{"key":"ref15\/cit15","doi-asserted-by":"publisher","DOI":"10.1038\/nbt1203"},{"key":"ref16\/cit16","doi-asserted-by":"publisher","DOI":"10.1021\/ci300547g"},{"key":"ref17\/cit17","doi-asserted-by":"publisher","DOI":"10.1109\/MAES.2005.1396793"},{"key":"ref18\/cit18","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2017.06.044"},{"key":"ref19\/cit19","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcp.2017.05.021"},{"key":"ref20\/cit20","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2882777"},{"key":"ref21\/cit21","doi-asserted-by":"publisher","DOI":"10.1109\/56.802"},{"key":"ref22\/cit22","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2006.877407"},{"key":"ref23\/cit23","doi-asserted-by":"publisher","DOI":"10.1615\/Int.J.UncertaintyQuantification.2014006914"},{"key":"ref24\/cit24","doi-asserted-by":"publisher","DOI":"10.1098\/rspa.2016.0751"},{"key":"ref25\/cit25","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.223"},{"key":"ref26\/cit26","doi-asserted-by":"publisher","DOI":"10.1002\/cpa.21588"},{"key":"ref27\/cit27","doi-asserted-by":"publisher","DOI":"10.1063\/1.1630951"},{"key":"ref28\/cit28","doi-asserted-by":"publisher","DOI":"10.1063\/1.3206326"},{"key":"ref29\/cit29","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevMaterials.3.063801"},{"key":"ref30\/cit30","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jctc.9b00986"},{"key":"ref31\/cit31","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jpclett.9b01428"},{"key":"ref32\/cit32","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2017.10.011"},{"key":"ref33\/cit33","first-page":"2053","volume":"3","author":"Gilmer J.","year":"2017","journal-title":"34th International Conference on Machine Learning, ICML 2017"},{"key":"ref34\/cit34","doi-asserted-by":"publisher","DOI":"10.1063\/1.5126701"},{"key":"ref35\/cit35","doi-asserted-by":"publisher","DOI":"10.1063\/1.5020710"},{"key":"ref36\/cit36","doi-asserted-by":"publisher","DOI":"10.1016\/j.commatsci.2016.12.004"},{"key":"ref37\/cit37","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.93.115104"},{"key":"ref38\/cit38","unstructured":"Tian, H.; Rangarajan, S. On Deriving Probabilistic Models for Adsorption Energy on Transition Metals using Multi-level Ab initio and Experimental Data; http:\/\/arxiv.org\/abs\/1901.09253 (accessed May 13, 2020)."},{"key":"ref39\/cit39","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jctc.5b00099"},{"key":"ref40\/cit40","doi-asserted-by":"publisher","DOI":"10.1021\/ct400195d"},{"key":"ref41\/cit41","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.108.058301"},{"key":"ref42\/cit42","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jpclett.5b00831"},{"key":"ref43\/cit43","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2012.2236828"},{"key":"ref44\/cit44","volume-title":"Journal of Chemical Theory and Computation","author":"Cheng L.","year":"2019"},{"key":"ref45\/cit45","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jpca.9b04195"},{"key":"ref46\/cit46","doi-asserted-by":"publisher","DOI":"10.1021\/cr60259a002"},{"key":"ref47\/cit47","doi-asserted-by":"publisher","DOI":"10.1039\/C7RE00210F"},{"key":"ref48\/cit48","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"ref49\/cit49","doi-asserted-by":"publisher","DOI":"10.1038\/sdata.2014.22"},{"key":"ref50\/cit50","doi-asserted-by":"publisher","DOI":"10.1021\/ci300415d"},{"key":"ref51\/cit51","doi-asserted-by":"publisher","DOI":"10.1021\/j100096a001"},{"key":"ref52\/cit52","doi-asserted-by":"publisher","DOI":"10.1021\/ct700248k"},{"key":"ref53\/cit53","doi-asserted-by":"publisher","DOI":"10.1063\/1.481224"},{"key":"ref54\/cit54","volume-title":"Gaussian 09","author":"Frisch M. J.","year":"2009"},{"key":"ref55\/cit55","unstructured":"RDKit: Open-source cheminformatics; http:\/\/www.rdkit.org."},{"key":"ref56\/cit56","unstructured":"Hagberg, A.; Schult, D. A.; Swart, P. J. Exploring Network Structure, Dynamics, and Function Using NetworkX. InProceedings of the 7th Python in Science Conference (SciPy2008); Varoquaux, G., Vaught, T., Millman, J., Eds. Pasadena, CA USA, 2008; pp 11\u201315."},{"issue":"85","key":"ref57\/cit57","first-page":"2825","volume":"12","author":"Pedregosa F.","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref58\/cit58","doi-asserted-by":"publisher","DOI":"10.1109\/MCSE.2007.55"},{"key":"ref59\/cit59","volume-title":"Mwaskom\/Seaborn: V0.8.1","author":"Waskom M.","year":"2017"},{"key":"ref60\/cit60","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.69.066138"},{"key":"ref61\/cit61","unstructured":"Ver Steeg, G. Non-Parametric Entropy Estimation Toolbox (NPEET), 2013."}],"container-title":["Journal of Chemical Information and Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.0c00699","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,14]],"date-time":"2024-08-14T17:09:22Z","timestamp":1723655362000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/doi\/10.1021\/acs.jcim.0c00699"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,23]]},"references-count":61,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2020,10,26]]}},"alternative-id":["10.1021\/acs.jcim.0c00699"],"URL":"https:\/\/doi.org\/10.1021\/acs.jcim.0c00699","relation":{},"ISSN":["1549-9596","1549-960X"],"issn-type":[{"value":"1549-9596","type":"print"},{"value":"1549-960X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,23]]}}}