Tetrabutylammonium nitrate è un composto chimico registrato con il numero CAS 1941-27-1, con formula bruta C₁₆H₃₆N·NO₃, e massa molare di 304.47 g/mol.
La molecola contiene 57 atomi collegati da 55 legami chimici. Il nome sistematico IUPAC completo di questo composto è tetrabutylazanium nitrate. Il modello 3D interattivo qui sopra permette di visualizzare la disposizione spaziale degli atomi — puoi ruotarlo con il mouse, zoomare con la rotellina e passare tra le modalità di visualizzazione scheletro / Ball & Stick / Space Fill.
Dal punto di vista delle proprietà chimico-fisiche, superficie polare PSA = 62.9 Ų, 0 donatori e 3 accettori di legami a idrogeno. Questi parametri sono fondamentali per valutare la biodisponibilità e l'interazione con le biomolecole.
Data from PubMed (NIH NLM), OpenAlex (CC0), Semantic Scholar (AI2). AI Summary generated by Semantic Scholar TLDR. Articles marked with require paid access.
📜 Licenza e provenienzaPREDICTED 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)
require paid access.