{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T14:57:26Z","timestamp":1790607446079,"version":"4.1.0"},"reference-count":59,"publisher":"American Chemical Society (ACS)","issue":"18","license":[{"start":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T00:00:00Z","timestamp":1789084800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T00:00:00Z","timestamp":1789084800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T00:00:00Z","timestamp":1789084800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"funder":[{"DOI":"10.13039\/501100007128","name":"Natural Science Foundation of Shaanxi Province","doi-asserted-by":"publisher","award":["2024QY-SZX-02"],"award-info":[{"award-number":["2024QY-SZX-02"]}],"id":[{"id":"10.13039\/501100007128","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/na","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["22275145"],"award-info":[{"award-number":["22275145"]}],"id":[{"id":"10.13039\/na","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/na","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["22305189"],"award-info":[{"award-number":["22305189"]}],"id":[{"id":"10.13039\/na","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,9,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Machine learning has introduced a transformative paradigm for the rapid prediction of crystal properties, circumventing the need for explicit knowledge of crystal packing structures. However, when applied to high-density organic systems such as energetic ionic salts, conventional general-purpose molecular descriptors often exhibit limited prediction accuracy, generalization capability, and extrapolation capability. To address this challenge, we propose a physics-inspired multi-body descriptor (PIMBD). By decoupling the modeling of cations and anions and employing the co-evolutionary optimization of multi-body function hyperparameters, PIMBD effectively captures spatial arrangement features of atoms governed by strong Coulombic interactions. We established a benchmark dataset comprising more than 1200 energetic ionic crystals and conducted a systematic comparison of 6 representative descriptor frameworks and 29 machine learning algorithms. The results show that PIMBD achieves high predictive accuracy, with a mean absolute error (MAE) of 0.034 g\/cm3. Meanwhile, it achieves an MAE of 0.0282 g\/cm3 on an independent validation set composed of pentazolate-based ionic salts, shows pronounced advantages in the high-density region, and outperforms other descriptors in terms of generalization robustness and extrapolation capability. Furthermore, atomic-scale interpretability analyses were performed to elucidate the critical structural factors governing crystal density, leading to the distillation of three physically meaningful design principles. This work provides an efficient and interpretable descriptive methodology specifically tailored for ionic salts and may potentially accelerate the rational structure design of high-energy-density materials.<\/jats:p>","DOI":"10.1021\/acs.jcim.6c02052","type":"journal-article","created":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T12:01:30Z","timestamp":1789128090000},"page":"11948-11965","source":"Crossref","is-referenced-by-count":0,"title":["Physics-Inspired\nMulti-Body Descriptors Enable Interpretable\nDensity Prediction of Energetic Ionic Salts"],"prefix":"10.1021","volume":"66","author":[{"given":"Xiaoyan","family":"Wang","sequence":"first","affiliation":[{"name":"Xi\u2019an Modern Chemistry Research Institute , ,","place":["Xi\u2019an, China, 710065"]},{"name":"Xi\u2019an Key Laboratory of Liquid Crystal and Organic Photovoltaic Materials , ,","place":["Xi\u2019an, China, 710065"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7188-791X","authenticated-orcid":true,"given":"Xiaokai","family":"He","sequence":"additional","affiliation":[{"name":"Xi\u2019an Modern Chemistry Research Institute , ,","place":["Xi\u2019an, China, 710065"]},{"name":"Xi\u2019an Key Laboratory of Liquid Crystal and Organic Photovoltaic Materials , ,","place":["Xi\u2019an, China, 710065"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yining","family":"Zhang","sequence":"additional","affiliation":[{"name":"Xi\u2019an Modern Chemistry Research Institute , ,","place":["Xi\u2019an, China, 710065"]},{"name":"Xi\u2019an Key Laboratory of Liquid Crystal and Organic Photovoltaic Materials , ,","place":["Xi\u2019an, China, 710065"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guojin","family":"Li","sequence":"additional","affiliation":[{"name":"Xi\u2019an Modern Chemistry Research Institute , ,","place":["Xi\u2019an, China, 710065"]},{"name":"Xi\u2019an Key Laboratory of Liquid Crystal and Organic Photovoltaic Materials , ,","place":["Xi\u2019an, China, 710065"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9743-3360","authenticated-orcid":true,"given":"Chao","family":"Chen","sequence":"additional","affiliation":[{"name":"Xi\u2019an Modern Chemistry Research Institute , ,","place":["Xi\u2019an, China, 710065"]},{"name":"Xi\u2019an Key Laboratory of Liquid Crystal and Organic Photovoltaic Materials , ,","place":["Xi\u2019an, China, 710065"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4150-1111","authenticated-orcid":true,"given":"Yingzhe","family":"Liu","sequence":"additional","affiliation":[{"name":"Xi\u2019an Modern Chemistry Research Institute , ,","place":["Xi\u2019an, China, 710065"]},{"name":"National Key Laboratory of Energetic Molecules , ,","place":["Xi\u2019an, China, 710065"]},{"name":"State Key Laboratory of Fluorine & Nitrogen Chemicals , ,","place":["Xi\u2019an, China, 710065"]},{"name":"Xi\u2019an Key Laboratory of Liquid Crystal and Organic Photovoltaic Materials , ,","place":["Xi\u2019an, China, 710065"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,9,11]]},"reference":[{"key":"2026092810064180400_cit1","volume-title":"Molecular\nCrystals and Molecules","author":"Kitaigorodskii","year":"1973"},{"issue":"4","key":"2026092810064180400_cit2","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1107\/S2052519213018861","article-title":"Why Don\u2019t\nWe Find More Polymorphs?","volume":"69","author":"Price","year":"2013","journal-title":"Acta Crystallogr.,\nSect. B:Struct. Sci., Cryst. Eng. Mater."},{"issue":"5","key":"2026092810064180400_cit3","doi-asserted-by":"publisher","first-page":"870","DOI":"10.1007\/BF02494628","article-title":"A Quantum-Chemical\nStudy of 1,2,3,4,5,6,7,8-Octaazanaphthalene and itsN-Oxides","volume":"48","author":"Rezchikova","year":"1999","journal-title":"Russ. Chem. Bull."},{"issue":"16","key":"2026092810064180400_cit4","doi-asserted-by":"publisher","first-page":"6578","DOI":"10.1021\/acs.cgd.4c00950","article-title":"A New Answer to an Old Puzzle: A\nRevisited Study of Tetrazino-Tetrazine 1,3,6,8-Tetraoxide (TTTO) Density\nPrediction","volume":"24","author":"Ma","year":"2024","journal-title":"Cryst. Growth Des."},{"issue":"38","key":"2026092810064180400_cit5","doi-asserted-by":"publisher","first-page":"11472","DOI":"10.1002\/anie.201605611","article-title":"Synthesis\nof Tetrazino-Tetrazine 1,3,6,8-Tetraoxide (TTTO)","volume":"55","author":"Klenov","year":"2016","journal-title":"Angew. Chem., Int. Ed."},{"issue":"4","key":"2026092810064180400_cit6","doi-asserted-by":"publisher","first-page":"463","DOI":"10.1002\/prep.201400259","article-title":"Are DTTO\nand Iso-DTTO Worthwhile\nTargets for Synthesis?","volume":"40","author":"Christe","year":"2015","journal-title":"Propellants, Explos.,\nPyrotech."},{"issue":"1","key":"2026092810064180400_cit10","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-27344-x","article-title":"Applying\nMachine Learning Techniques to Predict the Properties of Energetic\nMaterials","volume":"8","author":"Elton","year":"2018","journal-title":"Sci. Rep."},{"issue":"10","key":"2026092810064180400_cit11","doi-asserted-by":"publisher","first-page":"4457","DOI":"10.1021\/acs.jcim.0c00259","article-title":"Prediction\nof Energetic\nMaterial Properties from Electronic Structure Using 3D Convolutional\nNeural Networks","volume":"60","author":"Casey","year":"2020","journal-title":"J. Chem. Inf. Model."},{"issue":"49","key":"2026092810064180400_cit12","doi-asserted-by":"publisher","first-page":"10330","DOI":"10.1021\/acs.jpca.0c06791","article-title":"Machine Learned Model for Solid Form Volume Estimation Based on Packing-Accessible\nSurface and Molecular Topological Fragments","volume":"124","author":"Bier","year":"2020","journal-title":"J. Phys. Chem. A"},{"issue":"5","key":"2026092810064180400_cit13","doi-asserted-by":"publisher","first-page":"2147","DOI":"10.1021\/acs.jcim.0c01318","article-title":"Predicting Energetics\nMaterials\u2019 Crystalline\nDensity from Chemical Structure by Machine Learning","volume":"61","author":"Nguyen","year":"2021","journal-title":"J. Chem. Inf. Model."},{"key":"2026092810064180400_cit14","doi-asserted-by":"publisher","first-page":"364","DOI":"10.1016\/j.jechem.2021.08.031","article-title":"Accurate\nMachine Learning Models Based on Small Dataset\nof Energetic Materials through Spatial Matrix Featurization Methods","volume":"63","author":"Chen","year":"2021","journal-title":"J. Energy Chem."},{"issue":"6","key":"2026092810064180400_cit15","doi-asserted-by":"publisher","DOI":"10.1002\/adts.202100057","article-title":"Machine Learning Enabled\nQuickly\nPredicting of Detonation Properties of N-Containing Molecules for\nDiscovering New Energetic Materials","volume":"4","author":"Hou","year":"2021","journal-title":"Adv. Theory\nSimul."},{"issue":"38","key":"2026092810064180400_cit16","doi-asserted-by":"publisher","first-page":"21723","DOI":"10.1039\/D1TA04441A","article-title":"Accelerating the Discovery\nof Energetic Melt-Castable Materials by\na High-Throughput Virtual Screening and Experimental Approach","volume":"9","author":"Song","year":"2021","journal-title":"J. Mater. Chem. A"},{"issue":"6","key":"2026092810064180400_cit17","doi-asserted-by":"publisher","first-page":"2582","DOI":"10.1021\/acs.jcim.0c01393","article-title":"Density Prediction\nModels for Energetic Compounds Merely Using Molecular\nTopology","volume":"61","author":"Yang","year":"2021","journal-title":"J. Chem. Inf. Model."},{"key":"2026092810064180400_cit18","doi-asserted-by":"publisher","first-page":"3023","DOI":"10.1039\/d5cp04092b","article-title":"Prediction and Interpretability Analysis\nfor Properties of Energetic Ionic Salts Based on Machine Learning","volume":"28","author":"Feng","year":"2026","journal-title":"Phys. Chem. Chem. Phys."},{"issue":"1","key":"2026092810064180400_cit19","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1021\/accountsmr.4c00230","article-title":"Data-Driven\nCombinatorial Design\nof Highly Energetic Materials","volume":"6","author":"Wen","year":"2025","journal-title":"Acc. Mater. Res."},{"key":"2026092810064180400_cit20","doi-asserted-by":"crossref","unstructured":"Chen, C.; Ma, Y.; He, X.; Zhang, Z.; Liu, Y.\n          Multi-Body Approximation\nFeaturization to Broaden\nMachine Learning Application Range for Crystal Density Modelling\n          ChemRxiv\n          2026, 10.26434\/chemrxiv.10002100\/v1.","DOI":"10.26434\/chemrxiv.10002100\/v1"},{"issue":"42","key":"2026092810064180400_cit21","doi-asserted-by":"publisher","first-page":"10874","DOI":"10.1021\/jp073117j","article-title":"Accurate\nPredictions of Crystal Densities\nUsing Quantum Mechanical Molecular Volumes","volume":"111","author":"Rice","year":"2007","journal-title":"J. Phys. Chem. A"},{"issue":"19","key":"2026092810064180400_cit22","doi-asserted-by":"publisher","first-page":"2095","DOI":"10.1080\/00268970903156306","article-title":"An Electrostatic\nInteraction Correction for Improved Crystal Density Prediction","volume":"107","author":"Politzer","year":"2009","journal-title":"Mol. Phys."},{"issue":"10","key":"2026092810064180400_cit23","doi-asserted-by":"publisher","first-page":"1391","DOI":"10.1080\/00268971003702221","article-title":"An Electrostatic\nCorrection for Improved Crystal Density Predictions of Energetic Ionic\nCompounds","volume":"108","author":"Politzer","year":"2010","journal-title":"Mol. Phys."},{"issue":"11","key":"2026092810064180400_cit24","doi-asserted-by":"publisher","first-page":"1680","DOI":"10.1002\/prep.202000076","article-title":"Assessment of Recent\nResearches for Reliable Prediction\nof Density of Organic Compounds as Well as Ionic Liquids and Salts\nContaining Energetic Groups at Room Temperature","volume":"45","author":"Keshavarz","year":"2020","journal-title":"Propellants, Explos., Pyrotech."},{"key":"2026092810064180400_cit25","doi-asserted-by":"crossref","unstructured":"Barnes, B. C.\n           In  Deep Learning for\nEnergetic Material Detonation Performance, AIP Conference\nProceedings; AIP Publishing, 2024; p 070002.","DOI":"10.1063\/12.0001089"},{"issue":"35","key":"2026092810064180400_cit26","doi-asserted-by":"publisher","first-page":"17963","DOI":"10.1039\/C5TA05291B","article-title":"A High Density Pyrazolo-Triazine\nExplosive (PTX)","volume":"3","author":"Schulze","year":"2015","journal-title":"J. Mater. Chem. A"},{"key":"2026092810064180400_cit27","article-title":"Detonation\nPerformance and Sensitivity: A Quest for Balance","volume-title":"Advances in quantum chemistry","author":"Politzer","year":"2014"},{"issue":"38","key":"2026092810064180400_cit28","doi-asserted-by":"publisher","first-page":"20418","DOI":"10.1039\/c2jm33646d","article-title":"Pushing the\nLimits of Energetic Materials \u2013 the Synthesis and Characterization\nof Dihydroxylammonium 5,5\u2032-Bistetrazole-1,1\u2032-Diolate","volume":"22","author":"Fischer","year":"2012","journal-title":"J. Mater. Chem."},{"issue":"6323","key":"2026092810064180400_cit29","doi-asserted-by":"publisher","first-page":"374","DOI":"10.1126\/science.aah3840","article-title":"Synthesis and Characterization\nof the Pentazolate Anion Cyclo -N5 \u0305\nin (N5)6 (H3 O)3 (NH4)4 Cl","volume":"355","author":"Zhang","year":"2017","journal-title":"Science"},{"issue":"3","key":"2026092810064180400_cit30","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1021\/acs.cgd.4c01266","article-title":"Structure Design and\nProperty Prediction of Energetic Pentazolate Salt: An Overview","volume":"25","author":"Cao","year":"2025","journal-title":"Cryst. Growth Des."},{"key":"2026092810064180400_cit31","doi-asserted-by":"publisher","DOI":"10.1016\/j.molstruc.2025.142109","article-title":"The Effective Combination\nof Tetrazoles, 1,2,4-Triazole and Dinitromethyl: A Sensible Strategy\nfor Energy and Stability Balance","volume":"1336","author":"Wang","year":"2025","journal-title":"J. Mol. Struct."},{"issue":"22","key":"2026092810064180400_cit32","doi-asserted-by":"publisher","first-page":"3833","DOI":"10.1039\/D5CE00194C","article-title":"Hybrid Computational Approaches for\nAccurate Crystalline Density Prediction of Cyclo -Pentazolate\nSalts","volume":"27","author":"Chen","year":"2025","journal-title":"CrystEngComm"},{"issue":"1","key":"2026092810064180400_cit33","doi-asserted-by":"publisher","DOI":"10.1038\/s41524-018-0082-y","article-title":"Effect of Ionic Composition\non Thermal Properties of Energetic Ionic Liquids","volume":"4","author":"Park","year":"2018","journal-title":"npj Comput. Mater."},{"issue":"35","key":"2026092810064180400_cit34","doi-asserted-by":"publisher","first-page":"8991","DOI":"10.1021\/acs.jpcb.5c04300","article-title":"Accelerating\nEnergetic Ionic Liquid Discovery: A Synergistic Fusion Strategy for\nProperty Prediction","volume":"129","author":"Pan","year":"2025","journal-title":"J. Phys. Chem. B"},{"issue":"1A","key":"2026092810064180400_cit35","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRev.137.A152","article-title":"Stability of Crystal Lattices","volume":"137","author":"Wallace","year":"1965","journal-title":"Phys. Rev."},{"issue":"40","key":"2026092810064180400_cit36","doi-asserted-by":"publisher","first-page":"5310","DOI":"10.1002\/anie.200301739","article-title":"Quantifying\nIntermolecular Interactions: Guidelines for the Molecular Recognition\nToolbox","volume":"43","author":"Hunter","year":"2004","journal-title":"Angew. Chem., Int. Ed."},{"issue":"5-6","key":"2026092810064180400_cit37","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."},{"issue":"3","key":"2026092810064180400_cit38","doi-asserted-by":"publisher","first-page":"1652","DOI":"10.1021\/acs.jctc.8b01176","article-title":"GFN2-xTB\u2500An\nAccurate and Broadly\nParametrized Self-Consistent Tight-Binding Quantum Chemical Method\nwith Multipole Electrostatics and Density-Dependent Dispersion Contributions","volume":"15","author":"Bannwarth","year":"2019","journal-title":"J. Chem. Theory Comput."},{"issue":"4","key":"2026092810064180400_cit39","doi-asserted-by":"publisher","DOI":"10.1063\/5.0260616","article-title":"Harnessing Machine\nLearning Enabled Quickly Predicting Density of CHON Molecules for\nDiscovering New Energetic Materials","volume":"15","author":"Zong","year":"2025","journal-title":"AIP Adv."},{"key":"2026092810064180400_cit40","doi-asserted-by":"crossref","unstructured":"Beste, A.; Barnes, B. C. In  Prediction\nof Thermal\nDecomposition Temperatures Using Statistical Methods, AIP\nConference Proceedings; AIP Publishing, 2020; p 050004.","DOI":"10.1063\/12.0000811"},{"issue":"4","key":"2026092810064180400_cit41","doi-asserted-by":"publisher","DOI":"10.1002\/prep.202200236","article-title":"Predicting\nEnthalpy of Formation of Energetic Compounds by Machine Learning:\nComparison of Featurization Methods and Algorithms","volume":"48","author":"Tian","year":"2023","journal-title":"Propellants, Explos., Pyrotech."},{"issue":"4","key":"2026092810064180400_cit42","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1016\/j.fpc.2023.04.002","article-title":"Searching for the Analogues of 1,1-Dinitro-2,2-Diamino\nEthylene (FOX-7) by High-Throughput Computation and Machine Learning","volume":"3","author":"Qian","year":"2023","journal-title":"FirePhysChem"},{"issue":"4","key":"2026092810064180400_cit43","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.enmf.2023.05.002","article-title":"Identifying the Determining Factors\nof Detonation Properties\nfor Linear Nitroaliphatics with High-Throughput Computation and Machine\nLearning","volume":"5","author":"Qian","year":"2024","journal-title":"Energy Mater. Front."},{"issue":"4","key":"2026092810064180400_cit44","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1016\/j.enmf.2023.09.004","article-title":"Machine\nLearning-Assisted Quantitative\nPrediction of Thermal Decomposition Temperatures of Energetic Materials\nand Their Thermal Stability Analysis","volume":"5","author":"Zhang","year":"2024","journal-title":"Energy\nMater. Front."},{"key":"2026092810064180400_cit45","doi-asserted-by":"crossref","unstructured":"Zhou, G.; Gao, Z.; Ding, Q.; Zheng, H.; Xu, H.; Wei, Z.; Zhang, L.; Ke, G.\n          Uni-Mol: A Universal\n3D Molecular Representation Learning Framework\n          ChemRxiv\n          2023\n          10.26434\/chemrxiv-2022-jjm0j-v4.","DOI":"10.26434\/chemrxiv-2022-jjm0j-v4"},{"issue":"12","key":"2026092810064180400_cit46","doi-asserted-by":"publisher","first-page":"2326","DOI":"10.1021\/acs.jpclett.5b00831","article-title":"Machine Learning Predictions of Molecular\nProperties: Accurate Many-Body Potentials and Nonlocality in Chemical\nSpace","volume":"6","author":"Hansen","year":"2015","journal-title":"J. Phys. Chem. Lett."},{"issue":"5","key":"2026092810064180400_cit47","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevLett.108.058301","article-title":"Fast and\nAccurate Modeling of Molecular Atomization Energies with Machine Learning","volume":"108","author":"Rupp","year":"2012","journal-title":"Phys. Rev. Lett."},{"key":"2026092810064180400_cit48","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2020.118874","article-title":"A Novel Stacked Generalization\nEnsemble-Based Hybrid\nLGBM-XGB-MLP Model for Short-Term Load Forecasting","volume":"214","author":"Massaoudi","year":"2021","journal-title":"Energy"},{"issue":"3","key":"2026092810064180400_cit49","doi-asserted-by":"publisher","first-page":"736","DOI":"10.1016\/j.ijforecast.2015.11.017","article-title":"Nonlinear\nForecasting\nwith Many Predictors Using Kernel Ridge Regression","volume":"32","author":"Exterkate","year":"2016","journal-title":"Int. J. Forecast."},{"issue":"253","key":"2026092810064180400_cit50","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1080\/01621459.1951.10500769","article-title":"The Kolmogorov-Smirnov\nTest for Goodness of Fit","volume":"46","author":"Massey","year":"1951","journal-title":"J. Am. Stat. Assoc."},{"issue":"1","key":"2026092810064180400_cit51","doi-asserted-by":"publisher","DOI":"10.1038\/s43586-022-00184-w","article-title":"Principal Component Analysis","volume":"2","author":"Greenacre","year":"2022","journal-title":"Nat. Rev. Methods Primers"},{"issue":"86","key":"2026092810064180400_cit52","first-page":"2579","article-title":"Visualizing Data Using T-SNE","volume":"9","author":"van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"issue":"17","key":"2026092810064180400_cit53","doi-asserted-by":"publisher","first-page":"8406","DOI":"10.1021\/acs.jctc.5c00865","article-title":"Machine Learning\nDensities,\nDetonation Velocities, and Formation Enthalpies of Energetic Materials\nUsing Quantum Chemistry Descriptors","volume":"21","author":"Kimber","year":"2025","journal-title":"J. Chem.\nTheory Comput."},{"issue":"5","key":"2026092810064180400_cit54","doi-asserted-by":"publisher","first-page":"2690","DOI":"10.1021\/acs.cgd.0c01574","article-title":"Nonmetallic\nPentazole Salts Based on Furazan or 4-Nitropyrazole\nfor Enhancing Density and Stability","volume":"21","author":"Hu","year":"2021","journal-title":"Cryst.\nGrowth Des."},{"issue":"16","key":"2026092810064180400_cit55","doi-asserted-by":"publisher","first-page":"2877","DOI":"10.1002\/asia.201900776","article-title":"Syntheses of Energetic Cyclo -Pentazolate Salts","volume":"14","author":"Tian","year":"2019","journal-title":"Chem. -\nAsian J."},{"issue":"1","key":"2026092810064180400_cit56","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1021\/acs.cgd.0c01458","article-title":"New Insight into the Aromaticity of Cyclo -N5\u2013 by Constructing 3D Arrays in Crystal\nStructures","volume":"21","author":"Xia","year":"2021","journal-title":"Cryst. Growth Des."},{"issue":"8","key":"2026092810064180400_cit57","doi-asserted-by":"publisher","first-page":"924","DOI":"10.1002\/asia.201800187","article-title":"Stabilization of the Pentazolate\nAnion in Three Anhydrous and Metal-Free Energetic Salts","volume":"13","author":"Xu","year":"2018","journal-title":"Chem. - Asian J."},{"issue":"20","key":"2026092810064180400_cit58","doi-asserted-by":"publisher","first-page":"12468","DOI":"10.1039\/C9TA01077G","article-title":"A Series of\nEnergetic Cyclo -Pentazolate Salts: Rapid Synthesis,\nCharacterization, and Promising Performance","volume":"7","author":"Xu","year":"2019","journal-title":"J. Mater. Chem. A"},{"issue":"1","key":"2026092810064180400_cit59","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1021\/acsaem.0c02052","article-title":"Investigating\nthe Stabilizing Forces of Pentazolate\nSalts","volume":"4","author":"Yang","year":"2021","journal-title":"ACS Appl. Energy Mater."},{"issue":"48","key":"2026092810064180400_cit60","doi-asserted-by":"publisher","first-page":"16488","DOI":"10.1021\/jacs.8b05106","article-title":"Synthesis and Characterization\nof Cyclo -Pentazolate Salts of NH4+, NH3 OH+, N2 H5+, C(NH2)3+, and N(CH3)4+","volume":"140","author":"Yang","year":"2018","journal-title":"J. Am. Chem.\nSoc."},{"issue":"2","key":"2026092810064180400_cit61","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.enmf.2022.05.002","article-title":"A Hybrid of Tetrazolium and Pentazolate:\nAn Energetic Salt with Ultrahigh Nitrogen Content and Energy","volume":"4","author":"Yu","year":"2023","journal-title":"Energy Mater. Front."},{"key":"2026092810064180400_cit62","doi-asserted-by":"publisher","DOI":"10.34133\/energymatadv.0196","article-title":"Precise N-Oxidation\nof Triazolotetrazine Facilitates Fused High-Energy-Density\nCompounds","volume":"7","author":"Zhang","year":"2026","journal-title":"Energy Mater. Adv."}],"container-title":["Journal of Chemical Information\nand Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.6c02052","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/jcisd8\/article-pdf\/66\/18\/11948\/68481247\/acs.jcim.6c02052.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pubs.acs.org\/jcisd8\/article-pdf\/66\/18\/11948\/68481247\/acs.jcim.6c02052.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T14:14:14Z","timestamp":1790604854000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/jcisd8\/article\/66\/18\/11948\/5428223\/Physics-Inspired-Multi-Body-Descriptors-Enable"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,11]]},"references-count":59,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2026,9,11]]},"published-print":{"date-parts":[[2026,9,28]]}},"URL":"https:\/\/doi.org\/10.1021\/acs.jcim.6c02052","relation":{},"ISSN":["1549-9596","1549-960X"],"issn-type":[{"value":"1549-9596","type":"print"},{"value":"1549-960X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,11]]}}}