{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T08:30:11Z","timestamp":1776069011522,"version":"3.50.1"},"reference-count":72,"publisher":"American Chemical Society (ACS)","issue":"1","license":[{"start":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T00:00:00Z","timestamp":1640217600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100020636","name":"Ministerio de Educaci??n y Formaci??n Profesional","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100020636","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002428","name":"Austrian Science Fund","doi-asserted-by":"publisher","award":["SFB F81 TACO"],"award-info":[{"award-number":["SFB F81 TACO"]}],"id":[{"id":"10.13039\/501100002428","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Chem. Inf. Model."],"published-print":{"date-parts":[[2022,1,10]]},"DOI":"10.1021\/acs.jcim.1c01380","type":"journal-article","created":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T20:12:18Z","timestamp":1640290338000},"page":"88-101","source":"Crossref","is-referenced-by-count":53,"title":["A Differentiable Neural-Network Force Field for Ionic Liquids"],"prefix":"10.1021","volume":"62","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9861-8076","authenticated-orcid":true,"given":"Hadri\u00e1n","family":"Montes-Campos","sequence":"first","affiliation":[{"name":"Grupo de Nanomateriais, Fot\u00f3nica e Materia Branda, Departamento de F\u00edsica de Part\u00edculas, Universidade de Santiago de Compostela, Campus Vida s\/n E-15782 Santiago de Compostela, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0971-1098","authenticated-orcid":true,"given":"Jes\u00fas","family":"Carrete","sequence":"additional","affiliation":[{"name":"Institute of Materials Chemistry, TU Wien, 1060 Vienna, Austria"}]},{"given":"Sebastian","family":"Bichelmaier","sequence":"additional","affiliation":[{"name":"Institute of Materials Chemistry, TU Wien, 1060 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0569-0042","authenticated-orcid":true,"given":"Luis M.","family":"Varela","sequence":"additional","affiliation":[{"name":"Grupo de Nanomateriais, Fot\u00f3nica e Materia Branda, Departamento de F\u00edsica de Part\u00edculas, Universidade de Santiago de Compostela, Campus Vida s\/n E-15782 Santiago de Compostela, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9844-9145","authenticated-orcid":true,"given":"Georg K. H.","family":"Madsen","sequence":"additional","affiliation":[{"name":"Institute of Materials Chemistry, TU Wien, 1060 Vienna, Austria"}]}],"member":"316","published-online":{"date-parts":[[2021,12,23]]},"reference":[{"key":"ref1\/cit1","doi-asserted-by":"crossref","DOI":"10.1002\/9783527340033","volume-title":"Fundamentals of Ionic Liquids: From Chemistry to Applications","author":"MacFarlane D.","year":"2017"},{"key":"ref2\/cit2","doi-asserted-by":"publisher","DOI":"10.1039\/b921469k"},{"key":"ref3\/cit3","doi-asserted-by":"crossref","unstructured":"Mallakpour, S.; Dinari, M. In  Green Solvents II: Properties and Applications of Ionic Liquids; Mohammad, A., Inamuddin, D., Eds. Springer Netherlands: Dordrecht, Netherlands, 2012; pp 1\u201332.","DOI":"10.1007\/978-94-007-2891-2_1"},{"key":"ref4\/cit4","doi-asserted-by":"publisher","DOI":"10.1126\/science.1090313"},{"key":"ref5\/cit5","doi-asserted-by":"publisher","DOI":"10.3390\/pr9020337"},{"key":"ref6\/cit6","doi-asserted-by":"publisher","DOI":"10.1039\/c2cc31638b"},{"key":"ref7\/cit7","doi-asserted-by":"publisher","DOI":"10.1039\/C9CS00016J"},{"key":"ref8\/cit8","doi-asserted-by":"publisher","DOI":"10.3390\/molecules25245812"},{"key":"ref9\/cit9","doi-asserted-by":"publisher","DOI":"10.1063\/1.2718531"},{"key":"ref10\/cit10","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jpcc.8b08248"},{"key":"ref11\/cit11","doi-asserted-by":"publisher","DOI":"10.1002\/cphc.200700552"},{"key":"ref12\/cit12","doi-asserted-by":"publisher","DOI":"10.1021\/jp206341z"},{"key":"ref13\/cit13","doi-asserted-by":"publisher","DOI":"10.1021\/acs.langmuir.5b00982"},{"key":"ref14\/cit14","doi-asserted-by":"publisher","DOI":"10.1039\/C8CP01541D"},{"key":"ref15\/cit15","doi-asserted-by":"publisher","DOI":"10.1021\/ja9621760"},{"key":"ref16\/cit16","doi-asserted-by":"publisher","DOI":"10.1021\/ct900009a"},{"key":"ref17\/cit17","doi-asserted-by":"publisher","DOI":"10.1039\/C4CP04512B"},{"key":"ref18\/cit18","doi-asserted-by":"publisher","DOI":"10.1063\/1.4968393"},{"key":"ref19\/cit19","doi-asserted-by":"publisher","DOI":"10.1038\/npjcompumats.2015.11"},{"key":"ref20\/cit20","doi-asserted-by":"publisher","DOI":"10.1002\/qua.24927"},{"key":"ref21\/cit21","doi-asserted-by":"crossref","unstructured":"Batzner, S.; Smidt, T. E.; Sun, L.; Mailoa, J. P.; Kornbluth, M.; Molinari, N.; Kozinsky, B. SE(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials. arXiv:2101.03164 [physics.comp-ph], 2021. Online at https:\/\/arxiv.org\/abs\/2101.03164","DOI":"10.21203\/rs.3.rs-244137\/v1"},{"key":"ref22\/cit22","doi-asserted-by":"publisher","DOI":"10.1002\/qua.24890"},{"key":"ref23\/cit23","doi-asserted-by":"publisher","DOI":"10.1021\/acs.chemrev.0c00868"},{"key":"ref24\/cit24","doi-asserted-by":"publisher","DOI":"10.1088\/2515-7655\/abc7f3"},{"key":"ref25\/cit25","doi-asserted-by":"publisher","DOI":"10.1063\/1.5111045"},{"key":"ref26\/cit26","doi-asserted-by":"publisher","DOI":"10.1063\/1.3553717"},{"key":"ref27\/cit27","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.87.184115"},{"key":"ref28\/cit28","first-page":"1","volume":"18","author":"Baydin A. G.","year":"2018","journal-title":"J. Mach. Learn. Res."},{"key":"ref29\/cit29","doi-asserted-by":"publisher","DOI":"10.1063\/1.5019779"},{"key":"ref30\/cit30","unstructured":"Anderson, B.; Hy, T.S.; Kondor, R. Cormorant: Covariant Molecular Neural Networks. arXiv:1906.04015 [physics.comp-ph], 2019. Online at https:\/\/arxiv.org\/abs\/1906.04015"},{"key":"ref31\/cit31","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.0c00451"},{"key":"ref32\/cit32","doi-asserted-by":"publisher","DOI":"10.1038\/s41524-020-0323-8"},{"key":"ref33\/cit33","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.99.064103"},{"key":"ref34\/cit34","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevMaterials.3.093803"},{"key":"ref35\/cit35","doi-asserted-by":"publisher","DOI":"10.1039\/C6SC05720A"},{"key":"ref36\/cit36","doi-asserted-by":"publisher","DOI":"10.1002\/jcc.20291"},{"key":"ref37\/cit37","doi-asserted-by":"publisher","DOI":"10.1063\/1.4879660"},{"key":"ref38\/cit38","doi-asserted-by":"publisher","DOI":"10.1002\/jcc.21224"},{"key":"ref39\/cit39","doi-asserted-by":"publisher","DOI":"10.1063\/1.470117"},{"key":"ref40\/cit40","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.71.035109"},{"key":"ref41\/cit41","doi-asserted-by":"publisher","DOI":"10.1088\/0953-8984\/22\/25\/253202"},{"key":"ref42\/cit42","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.80.195112"},{"key":"ref43\/cit43","doi-asserted-by":"publisher","DOI":"10.1088\/1361-648X\/aa680e"},{"key":"ref44\/cit44","unstructured":"Bradbury, J.; Frostig, R.; Hawkins, P.; Johnson, M. J.; Leary, C.; Maclaurin, D.; Necula, G.; Paszke, A.; VanderPlas, J.; Wanderman-Milne, S.; Zhang, Q. JAX: composable transformations of Python+NumPy programs. 2018; http:\/\/github.com\/google\/jax, accessed 2021-12-09."},{"key":"ref45\/cit45","doi-asserted-by":"publisher","DOI":"10.3389\/fams.2019.00067"},{"key":"ref46\/cit46","unstructured":"Karingula, S. R.; Ramanan, N.; Tahsambi, R.; Amjadi, M.; Jung, D.; Si, R.; Thimmisetty, C.; Coelho, C. N., Jr. Boosted Embeddings for Time Series Forecasting. arXiv:2104.04781 [cs.LG], 2021. Online at https:\/\/arxiv.org\/abs\/2104.04781"},{"key":"ref47\/cit47","unstructured":"Heek, J.; Levskaya, A.; Oliver, A.; Ritter, M.; Rondepierre, B.; Steiner, A.; van Zee, M. Flax: A neural network library and ecosystem for JAX. 2020; http:\/\/github.com\/google\/flax, accessed on 2021\u201312\u201309."},{"key":"ref48\/cit48","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jctc.8b01092"},{"key":"ref49\/cit49","unstructured":"Ramachandran, P.; Zoph, B.; Le, Q. V. Searching for Activation Functions. arXiv:1710.05941 [cs.NE], 2017. Online at https:\/\/arxiv.org\/abs\/1710.05941"},{"key":"ref50\/cit50","doi-asserted-by":"publisher","DOI":"10.1002\/jcc.24764"},{"key":"ref51\/cit51","unstructured":"Ba, J. L.; Kiros, J. R.; Hinton, G. E. Layer Normalization. arXiv:1607.06450 [stat.ML]. Online at https:\/\/arxiv.org\/abs\/1607.06450"},{"key":"ref52\/cit52","doi-asserted-by":"crossref","DOI":"10.1201\/9780429501906","volume-title":"Calculus On Manifolds: A Modern Approach To Classical Theorems Of Advanced Calculus","author":"Spivak M.","year":"2018"},{"key":"ref53\/cit53","doi-asserted-by":"publisher","DOI":"10.1007\/s40745-020-00253-5"},{"key":"ref54\/cit54","unstructured":"Kingma, D. P.; Ba, J. Adam: A method for stochastic optimization. 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, May 7\u20139, 2015, Conference Track Proceedings; 2015."},{"key":"ref55\/cit55","unstructured":"Smith, L. N. A Disciplined Approach to Neural Network Hyper-parameters: Part 1\u2013Learning Rate, Batch Size, Momentum, and Weight Decay. arXiv:1803.09820 [cs.LG], 2018. Online at https:\/\/arxiv.org\/abs\/1803.09820"},{"key":"ref56\/cit56","unstructured":"Larsen, A. H. Localized Atomic Orbital Basis Sets in the Projector Augmented Wave Method. M.Sc. Thesis, Center for Atomic-scale Materials Design, Department of Physics, Technical University of Denmark, 2008."},{"key":"ref57\/cit57","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2979706"},{"key":"ref58\/cit58","unstructured":"Klambauer, G.; Unterthiner, T.; Mayr, A.; Hochreiter, S. Self-Normalizing Neural Networks. In  Advances in Neural Information Processing Systems 30, NIPS 2017, Long Beach, CA, 2017."},{"key":"ref59\/cit59","unstructured":"Fort, S.; Hu, H.; Lakshminarayanan, B. Deep Ensembles: A Loss Landscape Perspective. arXiv:1912.02757 [stat.ML], 2020. Online at https:\/\/arxiv.org\/abs\/1912.02757"},{"key":"ref60\/cit60","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"ref61\/cit61","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.92.045131"},{"key":"ref62\/cit62","doi-asserted-by":"publisher","DOI":"10.1063\/1.5128375"},{"key":"ref63\/cit63","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-20427-2"},{"key":"ref64\/cit64","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevB.95.104105"},{"key":"ref65\/cit65","doi-asserted-by":"publisher","DOI":"10.1021\/j100161a070"},{"key":"ref66\/cit66","doi-asserted-by":"publisher","DOI":"10.1088\/0953-8984\/21\/42\/424120"},{"key":"ref67\/cit67","doi-asserted-by":"publisher","DOI":"10.1063\/5.0067565"},{"key":"ref68\/cit68","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemphys.2016.03.020"},{"key":"ref69\/cit69","unstructured":"Filippov, A. Self-Diffusion and Microstructure of Some Ionic Liquids in Bulk and in Confinement. Ph.D. Thesis, Lule\u00e4 University of Technology: Lule\u00e4, Sweden, 2016."},{"key":"ref70\/cit70","unstructured":"Schoenholz, S. S.; Cubuk, E. D. JAX, M.D.: A Framework for Differentiable Physics. arXiv 1912.04232, 2020. Online at https:\/\/arxiv.org\/abs\/1912.04232"},{"key":"ref71\/cit71","unstructured":"Zaheer, M.; Kottur, S.; Ravanbakhsh, S.; Poczos, B.; Salakhutdinov, R. R.; Smola, A. J. Deep Sets. Advances in Neural Information Processing Systems. Long Beach, CA, 2017."},{"key":"ref72\/cit72","unstructured":"Wagstaff, E.; Fuchs, F.; Engelcke, M.; Posner, I.; Osborne, M. A. On the Limitations of Representing Functions on Sets. Proceedings of the 36th International Conference on Machine Learning. Long Beach, CA, 2019; pp 6487\u20136494."}],"container-title":["Journal of Chemical Information and Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.1c01380","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.1c01380","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,27]],"date-time":"2023-04-27T20:28:14Z","timestamp":1682627294000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/doi\/10.1021\/acs.jcim.1c01380"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,23]]},"references-count":72,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,1,10]]}},"alternative-id":["10.1021\/acs.jcim.1c01380"],"URL":"https:\/\/doi.org\/10.1021\/acs.jcim.1c01380","relation":{},"ISSN":["1549-9596","1549-960X"],"issn-type":[{"value":"1549-9596","type":"print"},{"value":"1549-960X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,23]]}}}