Tetrabutylammonium nitrate ist eine chemische Verbindung, registriert unter der Nummer CAS 1941-27-1, mit der Summenformel C₁₆H₃₆N·NO₃, und einer Molmasse von 304.47 g/mol.
Das Molekül enthält 57 Atome, verbunden durch 55 chemische Bindungen. Der vollständige systematische IUPAC-Name dieser Verbindung lautet tetrabutylazanium nitrate. Das interaktive 3D-Modell oben zeigt die räumliche Anordnung der Atome — Sie können es mit der Maus drehen, mit dem Scrollrad zoomen und zwischen den Darstellungsmodi Skelett / Ball & Stick / Space Fill wechseln.
Hinsichtlich der physikalisch-chemischen Eigenschaften polare Oberfläche PSA = 62.9 Ų, 0 Donatoren und 3 Wasserstoffbrücken-Akzeptoren. Diese Parameter sind entscheidend für die Beurteilung der Bioverfügbarkeit und der Wechselwirkung mit Biomolekülen.
Data from PubMed (NIH NLM), OpenAlex (CC0), Semantic Scholar (AI2). AI Summary generated by Semantic Scholar TLDR. Articles marked with require paid access.
📜 Lizenz und ProvenienzPREDICTED MODEL · NOT VERIFIEDMolGod_License_1
PREDICTED MODEL — NOT VERIFIED computed by MolGod Scientific · experimental feature (beta) · may contain errors ILLUSTRATIVE FRAGMENT ARRANGEMENT — relative positions are not structural data
No source 3-D conformer was available to MolGod for this substance. MolGod Scientific computed this geometry from the structural formula with RDKit 2026.03.6 (ETKDGv3 conformer generation, MMFF94 force-field optimisation; lowest-energy converged conformer of a fixed-seed set). It is not a measured structure, it does not come from PubChem, and it has not been compared with experimental data. It shows one possible conformation.
This substance consists of 2 separate components (for example ions). Each component was computed separately; they are arranged radially around a layout anchor for visualisation only (at least 3.0 Å apart). Their relative positions are not a crystal structure, coordination geometry, ionic contacts or any experimentally determined arrangement.
Methods and references
RDKit: Open-source cheminformatics, version 2026.03.6. Zenodo. doi:10.5281/zenodo.22140358 (all versions: doi:10.5281/zenodo.591637)
Riniker S, Landrum GA. Better Informed Distance Geometry: Using What We Know To Improve Conformation Generation. J. Chem. Inf. Model. 2015, 55, 2562-2574. doi:10.1021/acs.jcim.5b00654
Wang S, Witek J, Landrum GA, Riniker S. Improving Conformer Generation for Small Rings and Macrocycles Based on Distance Geometry and Experimental Torsional-Angle Preferences. J. Chem. Inf. Model. 2020, 60, 2044-2058. doi:10.1021/acs.jcim.0c00025
Halgren TA. Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. J. Comput. Chem. 1996, 17, 490-519. doi:10.1002/(SICI)1096-987X(199604)17:5/6<490::AID-JCC1>3.0.CO;2-P
Tosco P, Stiefl N, Landrum G. Bringing the MMFF force field to the RDKit: implementation and validation. J. Cheminform. 2014, 6, 37. doi:10.1186/s13321-014-0037-3
Heller SR, McNaught A, Pletnev I, Stein S, Tchekhovskoi D. InChI, the IUPAC International Chemical Identifier. J. Cheminform. 2015, 7, 23. doi:10.1186/s13321-015-0068-4
Bolton EE, Kim S, Bryant SH. PubChem3D: Conformer generation. J. Cheminform. 2011, 3, 4. doi:10.1186/1758-2946-3-4 (cited for contrast: no source 3-D conformer was available to MolGod for this record)
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