{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T19:06:42Z","timestamp":1791313602594,"version":"4.3.1"},"reference-count":92,"publisher":"American Chemical Society (ACS)","issue":"29","license":[{"start":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T00:00:00Z","timestamp":1784160000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004527","name":"Energimyndigheten","doi-asserted-by":"publisher","award":["P2025-03176"],"award-info":[{"award-number":["P2025-03176"]}],"id":[{"id":"10.13039\/501100004527","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100022724","name":"Stand Up for Energy","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100022724","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004063","name":"Knut och Alice Wallenbergs Stiftelse","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004063","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Swedish National Strategic e-Science program eSSENCE"},{"name":"Batteries Sweden"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,7,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Electrolyte discovery for rechargeable batteries today relies on heuristic trial-and-error or high-throughput screening of existing molecules. Here, we introduce a Generative Solvent Design System (GSDS) that integrates a graph-based deep molecular generator with machine learning (ML) property predictors to design rechargeable battery solvents de novo. We enable this by constructing a battery-specific prior data set (Batt-SLM, 115,756 molecules) and fine-tuning a graph-based molecular generator using physics-informed ML surrogates for redox potential, viscosity, melting point, donor number, and dielectric constant. We validated the performance of GSDS on the rediscovery of both fluorinated and phosphorus-containing compounds not seen during training. This allows us to propose application-specific candidates (top 0.2 \u2030) for alkali metal batteries\u2500fluorinated diluents and nonfluorinated weakly solvating electrolytes\u2500that pass a posterior verification funnel including property evaluation, synthetic accessibility, candidate prioritization, and literature checks. We conclude that GSDS establishes a tractable solvent design layer of a broader electrolyte-design framework and can be expanded toward salt-aware, interface-informed, and mixture-included optimization for next-generation rechargeable batteries.<\/jats:p>","DOI":"10.1021\/acsnano.6c06255","type":"journal-article","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T12:36:27Z","timestamp":1784205387000},"page":"20714-20729","source":"Crossref","is-referenced-by-count":2,"title":["Unlocking the Chemical\nSpace for Rechargeable Batteries\nwith a Generative Solvent Design System"],"prefix":"10.1021","volume":"20","author":[{"given":"Zhan-Yun","family":"Zhang","sequence":"first","affiliation":[{"name":"Uppsala University , , La\u0308gerhyddsva\u0308gen 1 , P.O. Box 538, ,","place":["Uppsala, Sweden, 75121"]},{"name":"Uppsala University , , ,","place":["Uppsala, Sweden, 75121"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roci\u0301o","family":"Mercado","sequence":"additional","affiliation":[{"name":"Chalmers University of Technology & University of Gothenburg , , Chalmersplatsen 1 , ,","place":["Gothenburg, Sweden, 412 96"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-1531-3714","authenticated-orcid":true,"given":"Thanh Trung","family":"Le","sequence":"additional","affiliation":[{"name":"Uppsala University , , La\u0308gerhyddsva\u0308gen 1 , P.O. Box 538, ,","place":["Uppsala, Sweden, 75121"]},{"name":"Uppsala University , , ,","place":["Uppsala, Sweden, 75121"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7167-0840","authenticated-orcid":true,"given":"Chao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Uppsala University , , La\u0308gerhyddsva\u0308gen 1 , P.O. Box 538, ,","place":["Uppsala, Sweden, 75121"]},{"name":"Uppsala University , , ,","place":["Uppsala, Sweden, 75121"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,7,16]]},"reference":[{"key":"2026072810074786300_cit1","doi-asserted-by":"publisher","first-page":"11503","DOI":"10.1021\/cr500003w","article-title":"Electrolytes\nand Interphases in Li-Ion Batteries and Beyond","volume":"114","author":"Xu","year":"2014","journal-title":"Chem. Rev."},{"key":"2026072810074786300_cit2","doi-asserted-by":"publisher","first-page":"6783","DOI":"10.1021\/acs.chemrev.9b00531","article-title":"New Concepts\nin Electrolytes","volume":"120","author":"Li","year":"2020","journal-title":"Chem. Rev."},{"key":"2026072810074786300_cit3","doi-asserted-by":"publisher","first-page":"4238","DOI":"10.1039\/D3SC06650A","article-title":"Recent Advances\nin Electrolyte Molecular Design for Alkali Metal Batteries","volume":"15","author":"Ruan","year":"2024","journal-title":"Chem. Sci."},{"key":"2026072810074786300_cit4","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1038\/s41560-019-0336-z","article-title":"Advances and\nIssues in Developing Salt-Concentrated Battery electrolytes","volume":"4","author":"Yamada","year":"2019","journal-title":"Nat. Energy"},{"key":"2026072810074786300_cit5","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.joule.2019.12.007","article-title":"Uncharted\nWaters: Super-Concentrated Electrolytes","volume":"4","author":"Borodin","year":"2020","journal-title":"Joule"},{"key":"2026072810074786300_cit6","doi-asserted-by":"publisher","DOI":"10.1149\/1945-7111\/abd60e","article-title":"Review\u2500Localized High-Concentration\nElectrolytes for Lithium Batteries","volume":"168","author":"Cao","year":"2021","journal-title":"J. Electrochem.\nSoc."},{"key":"2026072810074786300_cit7","doi-asserted-by":"publisher","first-page":"4090","DOI":"10.1002\/anie.202011482","article-title":"Regulating\nInterfacial Chemistry\nin Lithium-Ion Batteries by a Weakly Solvating Electrolyte","volume":"60","author":"Yao","year":"2021","journal-title":"Angew. Chem., Int. Ed."},{"key":"2026072810074786300_cit8","doi-asserted-by":"publisher","first-page":"588","DOI":"10.1016\/j.joule.2021.12.018","article-title":"Liquid Electrolyte: The Nexus of Practical Lithium\nMetal Batteries","volume":"6","author":"Wang","year":"2022","journal-title":"Joule"},{"key":"2026072810074786300_cit9","doi-asserted-by":"publisher","first-page":"5022","DOI":"10.1021\/acsenergylett.5c02764","article-title":"Weakly Solvating\nElectrolyte to Enable Lithium- and Manganese-Rich Cathode-Based Li-Ion\nBatteries","volume":"10","author":"Zhu","year":"2025","journal-title":"ACS Energy Lett."},{"key":"2026072810074786300_cit10","doi-asserted-by":"publisher","first-page":"2713","DOI":"10.1039\/D2CS00873D","article-title":"Emerging Electrolytes\nwith Fluorinated Solvents for Rechargeable\nLithium-Based Batteries","volume":"52","author":"Wang","year":"2023","journal-title":"Chem. Soc. Rev."},{"key":"2026072810074786300_cit11","doi-asserted-by":"publisher","first-page":"4569","DOI":"10.1021\/acs.chemrev.8b00239","article-title":"Boosting Rechargeable Batteries R&D\nby Multiscale Modeling: Myth or Reality?","volume":"119","author":"Franco","year":"2019","journal-title":"Chem.\nRev."},{"key":"2026072810074786300_cit12","doi-asserted-by":"publisher","first-page":"10970","DOI":"10.1021\/acs.chemrev.1c00904","article-title":"Applying Classical,\nAb Initio, and Machine-Learning Molecular Dynamics Simulations to\nthe Liquid Electrolyte for Rechargeable Batteries","volume":"122","author":"Yao","year":"2022","journal-title":"Chem. Rev."},{"key":"2026072810074786300_cit13","doi-asserted-by":"publisher","DOI":"10.1088\/2515-7655\/acfe9b","article-title":"2023\nRoadmap on Molecular Modelling of Electrochemical Energy Materials","volume":"5","author":"Zhang","year":"2023","journal-title":"J. Phys. Energy"},{"key":"2026072810074786300_cit14","doi-asserted-by":"publisher","first-page":"10899","DOI":"10.1021\/acs.chemrev.1c00108","article-title":"Artificial Intelligence\nApplied to Battery Research:\nHype or Reality?","volume":"122","author":"Lombardo","year":"2022","journal-title":"Chem. Rev."},{"key":"2026072810074786300_cit15","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1002\/batt.202000262","article-title":"Modelling Bulk Electrolytes and Electrolyte\nInterfaces with Atomistic\nMachine Learning","volume":"4","author":"Shao","year":"2021","journal-title":"Batteries Supercaps"},{"key":"2026072810074786300_cit16","doi-asserted-by":"publisher","first-page":"23764","DOI":"10.1021\/jacs.3c08346","article-title":"Data-Driven\nInsight into the Reductive Stability of Ion\u2013Solvent Complexes\nin Lithium Battery Electrolytes","volume":"145","author":"Gao","year":"2023","journal-title":"J. Am. Chem.\nSoc."},{"key":"2026072810074786300_cit17","doi-asserted-by":"publisher","first-page":"1544","DOI":"10.1039\/D5DD00025D","article-title":"Application\nof Pretrained Universal Machine-Learning Interatomic Potential for\nPhysicochemical Simulation of Liquid Electrolytes in Li-Ion Batteries","volume":"4","author":"Ju","year":"2025","journal-title":"Digital Discovery"},{"key":"2026072810074786300_cit18","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1038\/s42256-025-01009-7","article-title":"A Predictive Machine Learning Force-Field\nFramework for Liquid Electrolyte Development","volume":"7","author":"Gong","year":"2025","journal-title":"Nat. Mach. Intell."},{"key":"2026072810074786300_cit19","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-025-67982-0","article-title":"Domain Oriented\nUniversal Machine Learning Potential Enables Fast Exploration of Chemical\nSpace of Battery Electrolytes","volume":"17","author":"Wang","year":"2026","journal-title":"Nat. Commun."},{"key":"2026072810074786300_cit20","doi-asserted-by":"publisher","DOI":"10.1038\/s41524-025-01720-4","article-title":"High-Accuracy\nPhysical Property Prediction\nfor Pure Organics via Molecular Representation Learning: Bridging\nData to Discovery","volume":"11","author":"Ou","year":"2025","journal-title":"npj Comput. Mater."},{"key":"2026072810074786300_cit21","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.jechem.2024.10.021","article-title":"Design Principles\nof Fluoroether Solvents for Lithium Metal Battery Electrolytes Unveiled\nby Extensive Molecular Simulation and Machine Learning","volume":"102","author":"Yuan","year":"2025","journal-title":"J. Energy Chem."},{"key":"2026072810074786300_cit22","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1126\/science.aat2663","article-title":"Inverse Molecular Design using Machine\nLearning: Generative\nModels for Matter Engineering","volume":"361","author":"Sanchez-Lengeling","year":"2018","journal-title":"Science"},{"key":"2026072810074786300_cit23","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1021\/jz502319n","article-title":"Accelerating Electrolyte\nDiscovery for Energy Storage with High-Throughput Screening","volume":"6","author":"Cheng","year":"2015","journal-title":"J. Phys. Chem. Lett."},{"key":"2026072810074786300_cit24","doi-asserted-by":"publisher","DOI":"10.1002\/ange.202416506","article-title":"A Knowledge\u2013Data\nDual-Driven Framework for Predicting the Molecular Properties of Rechargeable\nBattery Electrolytes","volume":"137","author":"Gao","year":"2025","journal-title":"Angew. Chem."},{"key":"2026072810074786300_cit25","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-025-63303-7","article-title":"Active\nLearning Accelerates Electrolyte Solvent Screening for Anode-Free\nLithium Metal Batteries","volume":"16","author":"Ma","year":"2025","journal-title":"Nat. Commun."},{"key":"2026072810074786300_cit26","doi-asserted-by":"publisher","first-page":"9630","DOI":"10.1039\/D5CS00053J","article-title":"Accelerating Battery\nInnovation: AI-Powered Molecular Discovery","volume":"54","author":"Gao","year":"2025","journal-title":"Chem. Soc. Rev."},{"key":"2026072810074786300_cit27","doi-asserted-by":"publisher","DOI":"10.1088\/2632-2153\/abcf91","article-title":"Graph Networks for\nMolecular Design","volume":"2","author":"Mercado","year":"2021","journal-title":"Mach. Learn.: Sci. Technol."},{"key":"2026072810074786300_cit28","doi-asserted-by":"publisher","first-page":"1382","DOI":"10.1021\/acs.jctc.4c01570","article-title":"PiNN: Equivariant Neural Network Suite for Modeling Electrochemical\nSystems","volume":"21","author":"Li","year":"2025","journal-title":"J. Chem. Theory Comput."},{"key":"2026072810074786300_cit29","doi-asserted-by":"publisher","first-page":"1184","DOI":"10.1021\/acs.jcim.9b00994","article-title":"PiNN: A Python\nLibrary for Building Atomic Neural Networks of Molecules and Materials","volume":"60","author":"Shao","year":"2020","journal-title":"J. Chem. Inf. Model."},{"key":"2026072810074786300_cit30","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1016\/j.commatsci.2015.02.050","article-title":"The Electrolyte Genome Project: A Big Data Approach\nin Battery Materials Discovery","volume":"103","author":"Qu","year":"2015","journal-title":"Comput. Mater.\nSci."},{"key":"2026072810074786300_cit31","doi-asserted-by":"publisher","first-page":"1862","DOI":"10.1039\/D3DD00153A","article-title":"A Database of Molecular\nProperties Integrated in the Materials Project","volume":"2","author":"Spotte-Smith","year":"2023","journal-title":"Digital Discovery"},{"key":"2026072810074786300_cit32","doi-asserted-by":"publisher","first-page":"D1516","DOI":"10.1093\/nar\/gkae1059","article-title":"PubChem 2025 Update","volume":"53","author":"Kim","year":"2025","journal-title":"Nucleic Acids Res."},{"key":"2026072810074786300_cit33","doi-asserted-by":"publisher","first-page":"A2365","DOI":"10.1149\/2.1351810jes","article-title":"Exploring Classes of Co-Solvents for Fast-Charging Lithium-Ion Cells","volume":"165","author":"Hall","year":"2018","journal-title":"J. Electrochem. Soc."},{"key":"2026072810074786300_cit34","doi-asserted-by":"publisher","DOI":"10.1002\/anie.202411437","article-title":"Machine Learning Assisted Prediction\nof Donor Numbers: Guiding Rational Fabrication of Polymer Electrolytes\nfor Lithium-Ion Batteries","volume":"64","author":"Gao","year":"2025","journal-title":"Angew. Chem., Int.\nEd."},{"key":"2026072810074786300_cit35","doi-asserted-by":"crossref","DOI":"10.1039\/9781837671311","volume-title":"Electrolytes, Interfaces\nand Interphases: Fundamentals and Applications in Batteries","author":"Xu","year":"2023"},{"key":"2026072810074786300_cit36","doi-asserted-by":"publisher","first-page":"18703","DOI":"10.1021\/jacs.1c09006","article-title":"Steric Effect\nTuned Ion Solvation Enabling Stable Cycling of High-Voltage\nLithium Metal Battery","volume":"143","author":"Chen","year":"2021","journal-title":"J. Am. Chem. Soc."},{"key":"2026072810074786300_cit37","doi-asserted-by":"publisher","first-page":"1723","DOI":"10.1021\/acsenergylett.3c00004","article-title":"Design of Localized High-Concentration\nElectrolytes via Donor Number","volume":"8","author":"Chen","year":"2023","journal-title":"ACS Energy Lett."},{"key":"2026072810074786300_cit38","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1038\/s41586-022-05627-8","article-title":"Electrolyte Design\nfor Li-Ion Batteries under Extreme Operating Conditions","volume":"614","author":"Xu","year":"2023","journal-title":"Nature"},{"key":"2026072810074786300_cit39","doi-asserted-by":"publisher","DOI":"10.1186\/1758-2946-1-8","article-title":"Estimation of Synthetic Accessibility\nScore of Drug-Like\nMolecules based on Molecular Complexity and Fragment Contributions","volume":"1","author":"Ertl","year":"2009","journal-title":"J. Cheminform."},{"key":"2026072810074786300_cit40","doi-asserted-by":"publisher","DOI":"10.1002\/batt.202100373","article-title":"Fluorine-Free\nElectrolytes for Lithium and Sodium Batteries","volume":"5","author":"Herna\u0301ndez","year":"2022","journal-title":"Batteries Supercaps"},{"key":"2026072810074786300_cit41","doi-asserted-by":"publisher","DOI":"10.1002\/anie.202115884","article-title":"Integrated\nRing-Chain Design of a New Fluorinated Ether Solvent for High-Voltage\nLithium-Metal Batteries","volume":"61","author":"Zhou","year":"2022","journal-title":"Angew. Chem., Int.\nEd."},{"key":"2026072810074786300_cit42","doi-asserted-by":"publisher","first-page":"3900","DOI":"10.1021\/acsenergylett.5c01943","article-title":"Non-fluorinated Asymmetric\nEther\nElectrolytes with Controlled Solvation Structure for High-Voltage\nLithium Metal Batteries","volume":"10","author":"Pompizii","year":"2025","journal-title":"ACS Energy Lett."},{"key":"2026072810074786300_cit43","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1038\/s42256-025-01173-w","article-title":"A Unified Predictive and Generative\nSolution for Liquid Electrolyte Formulation","volume":"8","author":"Yang","year":"2026","journal-title":"Nat. Mach. Intell."},{"key":"2026072810074786300_cit44","doi-asserted-by":"publisher","first-page":"8223","DOI":"10.1039\/D4TA07449A","article-title":"Enabling Rational Electrolyte Design for Lithium Batteries\nthrough\nPrecise Descriptors: Progress and Future Perspectives","volume":"13","author":"Cui","year":"2025","journal-title":"J. Mater. Chem. A"},{"key":"2026072810074786300_cit45","doi-asserted-by":"publisher","first-page":"1155","DOI":"10.1038\/s41560-025-01842-5","article-title":"Unified Affinity\nParadigm for the Rational Design of High-Efficiency Lithium Metal\nElectrolytes","volume":"10","author":"Li","year":"2025","journal-title":"Nat. Energy"},{"key":"2026072810074786300_cit46","doi-asserted-by":"publisher","first-page":"1250","DOI":"10.1021\/acscentsci.9b00406","article-title":"Ion Transport and\nthe True Transference Number in Nonaqueous\nPolyelectrolyte Solutions for Lithium Ion Batteries","volume":"5","author":"Fong","year":"2019","journal-title":"ACS Cent. Sci."},{"key":"2026072810074786300_cit47","doi-asserted-by":"publisher","first-page":"7583","DOI":"10.1021\/jacs.2c02389","article-title":"Transference\nNumber\nin Polymer Electrolytes: Mind the Reference-Frame Gap","volume":"144","author":"Shao","year":"2022","journal-title":"J. Am. Chem. Soc."},{"key":"2026072810074786300_cit48","doi-asserted-by":"publisher","DOI":"10.1002\/adma.202509760","article-title":"A Non-Concentrated Gradient-Solvation Electrolyte Enables\na High-Voltage Lithium Metal Battery with 447.6 Wh\/kg","volume":"37","author":"Wang","year":"2025","journal-title":"Adv. Mater."},{"key":"2026072810074786300_cit49","doi-asserted-by":"publisher","first-page":"8634","DOI":"10.1021\/jacs.5c20477","article-title":"Combating Phase Segregation\nin Earth-Abundant Pyrite Cathodes for\nHigh-Energy-Density Lithium\u2013Metal Batteries","volume":"148","author":"Liu","year":"2026","journal-title":"J. Am. Chem. Soc."},{"key":"2026072810074786300_cit50","doi-asserted-by":"publisher","DOI":"10.1002\/anie.202505212","article-title":"Data\u2013Knowledge-Dual-Driven\nElectrolyte Design for Fast-Charging Lithium Ion Batteries","volume":"64","author":"Yang","year":"2025","journal-title":"Angew. Chem., Int. Ed."},{"key":"2026072810074786300_cit51","doi-asserted-by":"publisher","DOI":"10.1016\/j.xcrp.2020.100264","article-title":"Autonomous\nDiscovery of Battery Electrolytes with Robotic Experimentation and\nMachine Learning","volume":"1","author":"Dave","year":"2020","journal-title":"Cell Rep. Phys. Sci."},{"key":"2026072810074786300_cit52","doi-asserted-by":"publisher","first-page":"102129","DOI":"10.1016\/j.matt.2025.102129","article-title":"A Data-Driven\nPlatform for Automated Characterization of Polymer Electrolytes","volume":"8","author":"Stolberg","year":"2025","journal-title":"Matter"},{"key":"2026072810074786300_cit53","doi-asserted-by":"publisher","DOI":"10.1063\/5.0160937","article-title":"A Cloud Platform\nfor Sharing and Automated Analysis of Raw Data from High Throughput\nPolymer MD Simulations","volume":"1","author":"Xie","year":"2023","journal-title":"APL Mach. Learn."},{"key":"2026072810074786300_cit54","doi-asserted-by":"publisher","first-page":"1522","DOI":"10.1038\/s41563-025-02272-0","article-title":"Accelerated Data-Driven Materials Science with the Materials Project","volume":"24","author":"Horton","year":"2025","journal-title":"Nat. Mater."},{"key":"2026072810074786300_cit55","doi-asserted-by":"publisher","DOI":"10.1038\/s41524-018-0064-0","article-title":"Review on\nModeling of the Anode Solid Electrolyte Interphase (SEI) for Lithium-Ion\nBatteries","volume":"4","author":"Wang","year":"2018","journal-title":"npj Comput. Mater."},{"key":"2026072810074786300_cit56","doi-asserted-by":"publisher","first-page":"446","DOI":"10.1016\/j.ensm.2019.06.011","article-title":"A Perspective on Inverse\nDesign of\nBattery Interphases using Multi-Scale Modelling, Experiments and Generative\nDeep Learning","volume":"21","author":"Bhowmik","year":"2019","journal-title":"Energy Storage Mater."},{"key":"2026072810074786300_cit57","doi-asserted-by":"publisher","DOI":"10.1002\/anie.202503105","article-title":"Uni-Electrolyte:\nAn Artificial Intelligence Platform for Designing Electrolyte Molecules\nfor Rechargeable Batteries","volume":"64","author":"Chen","year":"2025","journal-title":"Angew. Chem., Int.\nEd."},{"key":"2026072810074786300_cit58","doi-asserted-by":"publisher","first-page":"6507","DOI":"10.1039\/D3TA06274K","article-title":"Inverse Design\nof Porous\nMaterials: A Diffusion Model Approach","volume":"12","author":"Park","year":"2024","journal-title":"J. Mater.\nChem. A"},{"key":"2026072810074786300_cit59","doi-asserted-by":"publisher","first-page":"624","DOI":"10.1038\/s41586-025-08628-5","article-title":"A Generative Model for\nInorganic Materials Design","volume":"639","author":"Zeni","year":"2025","journal-title":"Nature"},{"key":"2026072810074786300_cit60","unstructured":"Miller, B. K.; Chen, R. T. Q.; Sriram, A.; Wood, B. M.\n          FlowMM: Generating\nMaterials with Riemannian Flow Matching. In  Proceedings of the 41st International Conference on Machine Learning, 2024."},{"key":"2026072810074786300_cit61","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2415655121","article-title":"Generative AI for Computational Chemistry:\nA Roadmap to Predicting\nEmergent Phenomena","volume":"122","author":"Tiwary","year":"2025","journal-title":"Proc. Natl. Acad. Sci. U.S.A."},{"key":"2026072810074786300_cit62","doi-asserted-by":"publisher","first-page":"1828","DOI":"10.1039\/C7GC00252A","article-title":"Guidelines\nto Design Organic Electrolytes\nfor Lithium-Ion Batteries: Environmental Impact, Physicochemical and\nElectrochemical Properties","volume":"19","author":"Flamme","year":"2017","journal-title":"Green Chem."},{"key":"2026072810074786300_cit63","first-page":"177","article-title":"Handbook\nof Organic Solvent Properties","volume":"2","author":"Smallwood","year":"1997","journal-title":"Int. J. Adhes.\nAdhes."},{"key":"2026072810074786300_cit64","doi-asserted-by":"publisher","DOI":"10.1002\/adfm.202212342","article-title":"A Thermodynamic\nCycle-based Electrochemical\nWindows Database of 308 Electrolyte Solvents for Rechargeable Batteries","volume":"33","author":"Wang","year":"2023","journal-title":"Adv. Funct. Mater."},{"key":"2026072810074786300_cit65","doi-asserted-by":"publisher","first-page":"2913","DOI":"10.1039\/D1MH00748C","article-title":"Non-Flammable\nLiquid Electrolytes for Safe Batteries","volume":"8","author":"Gond","year":"2021","journal-title":"Mater.\nHoriz."},{"key":"2026072810074786300_cit66","doi-asserted-by":"publisher","first-page":"1115","DOI":"10.1126\/science.132.3434.1115","article-title":"A Computer Program\nfor Classifying Plants: The Computer\nis Programmed to Simulate the Taxonomic Process of Comparing Each\nCase with Every Other Case","volume":"132","author":"Rogers","year":"1960","journal-title":"Science"},{"key":"2026072810074786300_cit67","doi-asserted-by":"publisher","first-page":"2881","DOI":"10.1162\/neco_a_01434","article-title":"Parametric\nUMAP Embeddings for Representation\nand Semisupervised Learning","volume":"33","author":"Sainburg","year":"2021","journal-title":"Neural Comput."},{"key":"2026072810074786300_cit68","doi-asserted-by":"publisher","first-page":"2562","DOI":"10.1021\/acs.jcim.5b00654","article-title":"Better Informed Distance Geometry:\nUsing What We Know\nto Improve Conformation Generation","volume":"55","author":"Riniker","year":"2015","journal-title":"J. Chem.\nInf. Model."},{"key":"2026072810074786300_cit69","unstructured":"Landrum, G.\n          \n          RDKit: Open-Source Cheminformatics\nSoftware 2016\n          2016; Vol. 149, p 650."},{"key":"2026072810074786300_cit70","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1002\/(SICI)1096-987X(199604)17:5\/6<490::AID-JCC1>3.0.CO;2-P","article-title":"Merck Molecular\nForce Field. I. Basis, Form, Scope, Parameterization, and Performance\nof MMFF94","volume":"17","author":"Halgren","year":"1996","journal-title":"J. Comput. Chem."},{"key":"2026072810074786300_cit71","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1002\/(SICI)1096-987X(199604)17:5\/6<520::AID-JCC2>3.0.CO;2-W","article-title":"Merck Molecular\nForce Field. II. MMFF94 Van Der Waals and Electrostatic Parameters\nfor Intermolecular Interactions","volume":"17","author":"Halgren","year":"1996","journal-title":"J. Comput.\nChem."},{"key":"2026072810074786300_cit72","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1002\/(SICI)1096-987X(199604)17:5\/6<553::AID-JCC3>3.0.CO;2-T","article-title":"Merck Molecular\nForce Field. III. Molecular Geometries and Vibrational Frequencies\nfor MMFF94","volume":"17","author":"Halgren","year":"1996","journal-title":"J. Comput. Chem."},{"key":"2026072810074786300_cit73","doi-asserted-by":"publisher","first-page":"17598","DOI":"10.1021\/jacs.4c07099","article-title":"MACE-OFF:\nShort-Range Transferable Machine Learning\nForce Fields for Organic Molecules","volume":"147","author":"Kova\u0301cs","year":"2025","journal-title":"J. Am. Chem.\nSoc."},{"key":"2026072810074786300_cit74","doi-asserted-by":"publisher","DOI":"10.1088\/1361-648X\/aa680e","article-title":"The Atomic Simulation\nEnvironment\u2500A Python Library for Working with Atoms","volume":"29","author":"Larsen","year":"2017","journal-title":"J. Phys.: Condens. Matter"},{"key":"2026072810074786300_cit75","doi-asserted-by":"publisher","first-page":"9904","DOI":"10.1039\/c3cp54374a","article-title":"\u03c9B97X-V: A\n10-parameter, Range-Separated\nHybrid, Generalized Gradient Approximation Density Functional with\nNonlocal Correlation, Designed by A Survival-of-the-Fittest Strategy","volume":"16","author":"Mardirossian","year":"2014","journal-title":"Phys. Chem. Chem. Phys."},{"key":"2026072810074786300_cit76","doi-asserted-by":"publisher","DOI":"10.1063\/1.3484283","article-title":"Property-Optimized Gaussian Basis Sets for Molecular\nResponse Calculations","volume":"133","author":"Rappoport","year":"2010","journal-title":"J. Chem. Phys."},{"key":"2026072810074786300_cit77","doi-asserted-by":"publisher","first-page":"6378","DOI":"10.1021\/jp810292n","article-title":"Universal Solvation Model Based on\nSolute Electron Density and on A Continuum Model of the Solvent Defined\nby the Bulk Dielectric Constant and Atomic Surface Tensions","volume":"113","author":"Marenich","year":"2009","journal-title":"J. Phys. Chem. B"},{"key":"2026072810074786300_cit78","doi-asserted-by":"publisher","DOI":"10.1063\/5.0004608","article-title":"The ORCA Quantum\nChemistry Program Package","volume":"152","author":"Neese","year":"2020","journal-title":"J. Chem. Phys."},{"key":"2026072810074786300_cit79","doi-asserted-by":"publisher","first-page":"2012","DOI":"10.1021\/acs.jcim.0c00083","article-title":"A New Machine-Learning Tool for Fast Estimation of\nLiquid Viscosity. Application to Cosmetic Oils","volume":"60","author":"Goussard","year":"2020","journal-title":"J. Chem. Inf. Model."},{"key":"2026072810074786300_cit80","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-024-00820-5","article-title":"Advancing Material Property Prediction: Using Physics-Informed\nMachine Learning Models for Viscosity","volume":"16","author":"Chew","year":"2024","journal-title":"J. Cheminf."},{"key":"2026072810074786300_cit81","doi-asserted-by":"publisher","DOI":"10.1016\/j.molliq.2020.114506","article-title":"Calculation of Donor Numbers: Computational\nEstimates\nfor the Lewis Basicity of Solvents","volume":"322","author":"Miranda-Quintana","year":"2021","journal-title":"J. Mol.\nLiq."},{"key":"2026072810074786300_cit82","doi-asserted-by":"publisher","DOI":"10.1063\/5.0267184","article-title":"Mitigation of the Confinement-Induced\nDielectric Constant\nReduction via Binary Mixing Strategy for Energy Storage Applications","volume":"162","author":"He","year":"2025","journal-title":"J. Chem. Phys."},{"key":"2026072810074786300_cit83","unstructured":"Marenich, A. V.; Kelly, C. P.; Thompson, J. D.; Hawkins, G. D.; Chambers, C. C.; Giesen, D. J.; Winget, P.; Cramer, C. J.; Truhlar, D. G.\n          Minnesota Solvation\nDatabase (MNSOL) Version 2012, 2020."},{"key":"2026072810074786300_cit84","unstructured":"Kingma, D. P.; Ba, J.\n          Adam: A Method for Stochastic Optimization, 2017."},{"key":"2026072810074786300_cit85","doi-asserted-by":"publisher","DOI":"10.1088\/0957-4484\/26\/35\/354003","article-title":"Towards High\nThroughput Screening of Electrochemical Stability of Battery Electrolytes","volume":"26","author":"Borodin","year":"2015","journal-title":"Nanotechnology"},{"key":"2026072810074786300_cit86","doi-asserted-by":"crossref","unstructured":"Chen, T.; Guestrin, C.; et al.\n          XGBoost:\nA Scalable Tree Boosting System. In  Proceedings\nof the 22nd acm sigkdd international conference on knowledge discovery\nand data mining2016; pp 785\u2013794.","DOI":"10.1145\/2939672.2939785"},{"key":"2026072810074786300_cit87","doi-asserted-by":"publisher","first-page":"661","DOI":"10.1016\/0013-4686(76)85034-7","article-title":"Empirical\nParameters for Donor and Acceptor Properties of Solvents","volume":"21","author":"Gutmann","year":"1976","journal-title":"Electrochim. Acta"},{"key":"2026072810074786300_cit88","doi-asserted-by":"publisher","first-page":"2696","DOI":"10.1021\/acs.jpclett.6b01127","article-title":"Computing the Kirkwood\ng-Factor by\nCombining Constant Maxwell Electric Field and Electric Displacement\nSimulations: Application to the Dielectric Constant of Liquid Water","volume":"7","author":"Zhang","year":"2016","journal-title":"J. Phys. Chem. Lett."},{"key":"2026072810074786300_cit89","volume-title":"Nonaqueous Electrochemistry","author":"Aurbach","year":"1999"},{"key":"2026072810074786300_cit90","unstructured":"Kraft, D.\n          \n          A Software Package\nfor Sequential Quadratic Programming\n          Forschungsbericht-\nDeutsche Forschungs- und Versuchsanstalt fur Luft- und Raumfahrt\n          1988."},{"key":"2026072810074786300_cit91","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1038\/s41592-019-0686-2","article-title":"SciPy\n1.0: Fundamental Algorithms for Scientific\nComputing in Python","volume":"17","author":"Virtanen","year":"2020","journal-title":"Nat. Methods"},{"key":"2026072810074786300_cit92","first-page":"2751","article-title":"A View of\nMargin Losses as Regularizers of Probability\nEstimates","volume":"16","author":"Masnadi-Shirazi","year":"2015","journal-title":"J. Mach. Learn. Res."}],"container-title":["ACS Nano"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acsnano.6c06255","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/ancac3\/article-pdf\/20\/29\/20714\/65978948\/acsnano.6c06255.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pubs.acs.org\/ancac3\/article-pdf\/20\/29\/20714\/65978948\/acsnano.6c06255.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T14:40:02Z","timestamp":1785249602000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/ancac3\/article\/20\/29\/20714\/5212134\/Unlocking-the-Chemical-Space-for-Rechargeable"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,16]]},"references-count":92,"journal-issue":{"issue":"29","published-online":{"date-parts":[[2026,7,16]]},"published-print":{"date-parts":[[2026,7,28]]}},"URL":"https:\/\/doi.org\/10.1021\/acsnano.6c06255","relation":{"has-preprint":[{"id-type":"doi","id":"10.26434\/chemrxiv.15001594\/v1","asserted-by":"object"}]},"ISSN":["1936-0851","1936-086X"],"issn-type":[{"value":"1936-0851","type":"print"},{"value":"1936-086X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,16]]}}}