What is
Chemical Real-Time Predictor?(ChemRTP)

Chemical Real-Time Predictor (ChemRTP) quickly predicts chemical data and information of chemicals you defined.
This would be a complement to other databases that can only provide limited stored data.
ChemRTP based on QSPR provides 28 important chemical data for each chemical in real-time on the web.
Prediction accuracy comes with experimental data, if any.

Types of Compounds Available

  • Predict all pure compounds except radical, salt, mixture, or ion types
  • Types of atoms that can be used for modeling: C, H, N, O, S, F, Cl, Br, I, Si, P, As

Types of Properties Provided

Absolute Entropy of Ideal Gas at 298.15K and 1bar | Acentric Factor | Critical Compressibility Factor | Critical Pressure | Critical Temperature | Critical Volume | Enthalpy of Formation for Ideal Gas at 298.15K | Liquid Molar Volume at 298.15K | Molecular Weight | Net Standard State Enthalpy of Combustion at 298.15K | Normal Boiling Point | Melting Point | Refractive Index | Solubility Parameter at 298.15K | Standard State Absolute Entropy at 298.15K and 1bar | Standard State Enthalpy of Formation at 298.15K and 1bar | Magnetic Susceptibility | Polarizability | Flash Point | Parachor | Lower Flammability Limit Temperature | Lower Flammability Limit Volume Percent | Upper Flammability Limit Temperature | Upper Flammability Limit Volume Percent | Liquid Density at Normal Boiling Point | Heat of Vaporization at 298.15K | Heat of Vaporization

Quality Data Accuracy
through Experimental Data Refining Method

Years of accuracy verification using millions of experimental data points

  • We collected experimental data from every possible source, including technical journals, scientific books, the Internet, and commercial databases.
  • The collected experimental data were inspected and refined to remove the noise and unacceptable errors.
  • Refined experimental data were used to verify the accuracy of the estimated values. Thousands of charts were generated and inspected manually on a daily basis.
  • A systematic process has now been developed based on chemical analysis theories, e.g., similarity analysis, and was then applied for the accuracy verification.

Selected ChemRTP Citation List

PUBLISHER PUBLICATION
NATURE Fractal Based Analysis of the Inflence of Odorants on Heart Activity. Hamidreza Namazi, Vladimir V. Kulish. Scientifi Reports 6, Article number: 38555, DOI:10.1038/srep38555 (2016)
NATURE The Analysis of the Inflence of Odorant’s Complexity on Fractal Dynamics of Human Respiration. Hamidreza Namazi, Amin Akrami,Vladimir V. Kulish. Scientifi Reports 6, Article number: 26948, DOI:10.1038/srep26948 (2016)
American Chemical Society (ACS) Calculation of Average Molecular Parameters, Functional Groups, and a Surrogate Molecule for Heavy Fuel Oils Using 1H and 13C Nuclear Magnetic Resonance Spectroscopy. Abdul Gani Abdul Jameel, Ayman M. Elbaz, Abdul-Hamid Emwas, William L. Roberts, S. Mani Sarathy. Energy Fuels, 2016, 30 (5), pp 3894–3905, DOI: 10.1021/acs.energyfuels.6b00303 (2016)
American Chemical Society (ACS) Comparative Study of the Ignition of 1-Decene, trans-5-Decene, and n-Decane: Constant-Volume Spray and Shock-Tube Experiments. Aniket Tekawade, Tianbo Xie, Matthew A. Oehlschlaeger. Energy Fuels, 2017, 31 (6), pp 6493–6500, DOI: 10.1021/acs.energyfuels.7b00430 (2017)
Springer The CompTox Chemistry Dashboard: a community data resource for environmental chemistry. Antony J. Williams, Christopher M. Grulke, Jeff Edwards, Andrew D. McEachran, Kamel Mansouri, Nancy C. Baker, Grace Patlewicz, Imran Shah, John F. Wambaugh, Richard S. Judson, Ann M. Richard. J Cheminform (2017) 9:61, DOI: 10.1186/s13321-017-0247-6 (2017)
Hindawi Analysis of the Influence of Complexity and Entropy of Odorant on Fractal Dynamics and Entropy of EEG Signal. Hamidreza Namazi, Amin Akrami, Sina Nazeri, Vladimir V. Kulish. BioMed Research International Volume 2016 Article ID 5469587, 5 pages doi:10.1155/2016/5469587 (2016)
Residue2Heat THERMO-PHYSICAL CHARACTERIZATION OF FPBO AND PRELIMINARY SURROGATE DEFINITION. Project title: Renewable residential heating with fast pyrolysis bio-oil. A. Frassoldati, A Cuoci, A. Stagni, T. Faravelli, R. Calabria, P. Massoli. Grant Agreement: 654650. Start of the project: 01.01.2016 (48 months)

Selected Mol-Instincts Citation List

PUBLISHER PUBLICATION
NATURE Gold Nanoparticle Monolayers from Sequential Interfacial Ligand Exchange and Migration in a Three-Phase System. Guang Yang, T.Hallinan. Scientifi Reports volume 6, Article number: 35339, DOI:10.1038/srep35339 (2016)
American Chemical Society (ACS) Propylphenol to Phenol and Propylene over Acidic Zeolites: Role of Shape Selectivity and Presence of Steam. Yuhe Liao, Ruyi Zhong, Ekaterina Makshina, Martin d’Halluin, Yannick van Limbergen, Danny Verboekend, and Bert F. Sels. ACS Catal. 2018, 8, 7861-7878, DOI:10.1021/acscatal.8b01564(2018)
American Chemical Society (ACS) Role of Ligand Straining in Complexation of Eu3+–Am3+ Ions by TPEN and PPDEN, Scalar Relativistic DFT Exploration in Conjunction with COSMO-RS. Sk. Musharaf Ali. ACS Omega 2018, 3, 13104-13116, DOI: 10.1021/acsomega.8b00933 (2018)
American Chemical Society (ACS) Extension of the SAFT-VR Mie EoS To Model Homonuclear Rings and Its Parametrization Based on the Principle of Corresponding States. Erich A. Müller, Andrés Mejía. Langmuir, 2017, 33 (42), pp 11518–11529, DOI: 10.1021/acs.langmuir.7b00976 (2017)
American Chemical Society (ACS) Computing the Diamagnetic Susceptibility and Diamagnetic Anisotropy of Membrane Proteins from Structural Subunits. Mahnoush Babaei, Isaac C. Jones, Kaushik Dayal, Meagan S. Mauter. J. Chem. Theory Comput., 2017, 13 (6), pp 2945–2953, DOI: 10.1021/acs.jctc.6b01251 (2017)
ELSEVIER SGC based prediction of the flash point temperature of pure compounds. Tareq A. Albahri, Norah A.M. Esmael. Journal of Loss Prevention in the Process Industries 54, July 2018, Pages 303-311, DOI: 10.1016/j.jlp.2018.05.005 (2018)
ELSEVIER Shape selectivity vapor-phase conversion of lignin-derived 4-ethylphenol to phenol and ethylene over acidic aluminosilicates: Impact of acid properties and pore constraint. Yuhe Liao, Martin d’Halluin, Ekaterina Makshina, Danny Verboekend, Bert F.Sels. Applied Catalysis B: Environmental. 234, 15 October 2018, Pages 117-129, DOI: 10.1016/j.apcatb.2018.04.001 (2018)
ELSEVIER Spontaneous motion of various oil droplets in aqueous solution of trimethyl alkyl ammonium with diffrent carbon chain lengths. Ben Nanzai, Megumi Kato, Manabu Igawa. Colloids and Surfaces A: Physicochemical and Engineering Aspects, Volume 504, 5 September 2016, Pages 154-160, DOI: 10.1016/j.colsurfa.2016.04.063 (2016)
ELSEVIER Electron scattering from C2-C8 symmetric ether molecules. Paresh Modak, Suvam Singh, Jaspreet Kaur, Bobby Antony. International Journal of Mass Spectrometry, 2016, Volume 409, Pages 1-8, DOI: 10.1016/j.ijms.2016.09.002 (2016)
Oxford Academic Plant Cuttings. Nigel Chaffey. Annals of Botany, Volume 121, Issue 6, 11 May 2018, Pages iv–vii, DOI: 10.1093/aob/mcy070 (2018)
Royal Society of Chemistry (RSC) Physical Chemistry of Energy Conversion in Self-propelled Droplets Induced by Dewetting Effect. B. NANZAI, T. BAN. In: Self-organized Motion: Physicochemical Design based on Nonlinear Dynamics, 2018 (2018)
Royal Society of Chemistry (RSC) Nitrile-assistant eutectic electrolytes for cryogenic operation of lithium ion batteries at fast charges and discharges. Yoon-Gyo Cho, Young-Soo Kim, Dong-Gil Sung, Myung-Su Seo, Hyun-Kon Song. Energy Environ. Sci., 2014,7, 1737-1743 DOI: 10.1039/C3EE43029D (2014)
Springer Multi-agent System for Forecasting Based on Modified Algorithms of Swarm Intelligence and Immune Network Modeling. Samigulina G.A., Massimkanova Z.A. In: Agents and Multi-Agent Systems: Technologies and Applications 2018. Jezic G., Chen-Burger YH., Howlett R., Jain L., Vlacic L., Šperka R. (eds) KES-AMSTA-18 2018. Smart Innovation, Systems and Technologies, vol 96. Springer, Cham (2018)
Springer Electron-Transfer Secondary Reaction Matrices for MALDI MS Analysis of Bacteriochlorophyll a in Rhodobacter sphaeroides and Its Zinc and Copper Analogue Pigments. Calvano CD, Ventura G, Trotta M, Bianco G, Cataldi TR, Palmisano F. J Am Soc Mass Spectrom. 2017 Jan, 28(1), 125-135. DOI: 10.1007/s13361-016-1514-x (2017)
Springer A modified scaled variable reduced coordinate (SVRC)-quantitative structure property relationship (QSPR) model for predicting liquid viscosity of pure organic compounds. Seongmin Lee, Kiho Park, Yunkyung Kwon, Dae Ryook Yang. Korean Journal of Chemical Engineering, 2017, 34, 2715-2724, DOI: 10.1007/s11814-017-0173-3 (2017)
Springer Many InChIs and quite some feat. Wendy A. Warr.Journal of Computer-Aided Molecular Design, 2015, Volume 29, Issue 8, pp 681–694, DOI: 10.1007/s10822-015-9854-3 (2015)
Taylor & Francis Microbial growth yield estimates from thermodynamics and its importance for degradation of pesticides and formation of biogenic non-extractable residues. A. L. Brock, M. Kästner, S. Trapp. SAR and QSAR in Environmental Research, Volume 28, 2017, DOI: 10.1080/1062936X.2017.1365762 (2017)
NCBI Diversity and Applications of Endophytic Actinobacteria of Plants in Special and Other Ecological Niches. Singh R and Dubey AK. Front. Microbiol. 9:1767. doi: 10.3389/fmicb.2018.01767 (2018)
IUCr The solid-state conformation of the topical antifungal agent O-naphthalen-2-yl N-methyl-N(3-methylphenyl)carbamothioate. Douglas M. Ho and Michael J. Zdilla. Acta Cryst. (2018). C74, 1495–1501 DOI: 10.1107/S2053229618013591(2018)
Qazaq university Construction of an optimal immune network model based on the modified swarm algorithm. G. A. Samigulina, Zh. A. Massimkanova. KazNU Bulletin. Mathematics, Mechanics, Computer Science Series, N.2(98), Aug 2018, Pages 77-87, DOI: 10.26577/jmmcs-2018-2-402 (2018)
TEDE Uma perspectiva da modelagem QSPR para triagem/desenho de catalisadores para a síntese de carbonatos oleoquímicos. Santos, Victor Hugo Jacks Mendes dos. PUCRS(Pontníficia Universidade Católica do Rio Grande do Sul), Available Online at: http://tede2.pucrs.br/tede2/handle/tede/8260 (2018)
TAUJA DETERMINACIÓN DE ESBO EN SIMULANTES. Moreno-Infantes, Rosa L.. UJA(Universidad de Jaén), Available Online at: https://hdl.handle.net/10953.1/8417 (2018)
NKU Aspartamın yapay reseptörlere dayalı moleküler baskılı polimerleri ve moleküler modellenmesi. Sevindik, Yunus. Namık Kemal University Institutional Repository, Available Online at: http://hdl.handle.net/20.500.11776/2622 (2018)
J-STAGE A Quantitative Structure-Property Relationship Model for Predicting the Critical Pressures of Organic Compounds Containing Oxygen, Sulfur, and Nitrogen. Ji Ye Oh, Kiho Park, Yangsoo Kim, Tae-Yun Park, Dae Ryook Yang. Journal of Chemical Engineering of Japan, Vol. 50, No. 6, pp. 1–11, 2017, DOI:10.1252/jcej.16we367 (2017)
ΣΥΝΔΕΣΜΟΣ ΕΛΛΗΝΙΚΩΝ ΑΚΑΔΗΜΑΪΚΩΝ ΒΙΒΛΙΟΘΗΚΩΝ Εργαστηριακές ασκήσεις κλινικής χημείας. Karkalousos, P., Zoi, G., Kroupis, C., Papaioannou, A., Plageras, P., Spyropoulos, V., Tsotsou, G., Fountzoula, C. 2015. [ebook] Athens:Hellenic Academic Libraries Link. Available Online at: http://hdl.handle.net/11419/5382
ProQuest The development of guidance for solving polymer-penetrant diffusion problems in marine hardware. Rice, Matthew Aaron. Master Thesis. University of Rhode Island, ProQuest Dissertations Publishing, 2015.
Wiley A New Kaempferol-based Ru(II) Coordination Complex, Ru(kaem)Cl(DMSO)3: Structure and Absorption–Emission Spectroscopy Study. Mingwei Shao, Jongback Gang, Sanghyo Kim, Minyoung Yoon. Bull. Korean Chem. Soc., 2016, 37: 1625–1631. DOI: 10.1002/bkcs.10916 (2016)