Physical Properties Of Organic Compounds Research Articles

Transformer-Based Representation of Organic Molecules for Potential Modeling of Physicochemical Properties.

In this work, we study the use of three configurations of an autoencoder neural network to process organic substances with the aim of generating meaningful molecular descriptors that can be employed to develop property prediction models. A total of 18,322,500 compounds represented as SMILES strings were used to train the model, demonstrating that a latent space of 24 units is able to adequately reconstruct the data. After AE training, an analysis of the latent space properties in terms of compound similarity was carried out, indicating that this space possesses desired properties for the potential development of models for forecasting physical properties of organic compounds. As a final step, a QSPR model was developed to predict the boiling point of chemical substances based on the AE descriptors. 5276 substances were used for the regression task, and the predictive ability was compared with models available in the literature evaluated on the same database. The final AE model has an overall error of 1.40% (1.39% with augmented SMILES) in the prediction of the boiling temperature, while other models have errors between 2.0 and 3.2%. This shows that the SMILES representation is comparable and even outperforms the state-of-the-art representations widely used in the literature.

Artificial neural network for the prediction of physical properties of organic compounds based on the group contribution method

AbstractIn the development and optimization of chemical processes involving the selection of organic fluids, knowledge of the physical properties of compounds is vital. In many cases, it is complex to find experimental measurements for all substances, so it becomes necessary to have a tool to predict properties based on the characteristics of the molecule. One of the most extensively used methods in the literature is the estimation by contribution of functional groups, where properties are calculated using the constituent elements of the molecule. There are several models published in the literature, but they fail to represent a wide variety of compounds with high accuracy and simultaneously maintain a low computational complexity. The aim of this work is to develop a prediction model for eight thermodynamic properties (melting temperature, boiling temperature, critical pressure, critical temperature, critical volume, enthalpy of vaporization, enthalpy of fusion, and enthalpy of gas formation) based on the group contribution methodology by implementing a multilayer perceptron. Here, 2736 substances were used to train the neural network, whose prediction capacity was compared with other reference models available in the literature. The proposed model presents errors ranging from 1% to 5% for the different properties (except for the melting point), which improves the reference models with errors in the range of 3%–30%. Nevertheless, a difficulty in the prediction of the melting point is detected, which could represent an inherent hindrance to this methodology.

On Computation of Entropy Measures and Their Statistical Analysis for Complex Benzene Systems

Benzene is aromatic organic compound having six membered ring. Molecular studies provide evidence of presence of three alternative double bond providing exceptional stability to the molecule. Being basic unit of organic chemicals, benzene is widely used in pharmaceuticals, rubber, pesticides, dyes, lubricants, explosives and additives. Benzene derivatives are used in production of dyes, deodorants, pesticides, organic solvents, dispersants, plasticizers, and drugs. Keeping in view the extensive applications of benzene derivatives, we made use of QSPR analysis for predicting the multiple chemical and physical properties of organic compounds. By using SPSS software, correlation between newly introduced entropies and the Physico-chemical properties of benzene derivatives is examined. Our acquired consequences demonstrated that two physical properties of chemical structures, ie Boiling Point and enthalpy can be best predicted from the fifth entropy, and the other two properties namely Pie-electron Energy and molecular weight predicted from the neighborhood version of redefined first Zagreb entropy and neighborhood version of redefined second Zagreb entropy, respectively.

Photocatalytic Difluoromethylation Reactions of Aromatic Compounds and Aliphatic Multiple C-C Bonds.

Among the realm of visible light photocatalytic transformations, late-stage difluoromethylation reactions (introduction of difluoromethyl groups in the last stages of synthetic protocols) have played relevant roles as the CF2X group substitutions exert positive impacts on the physical properties of organic compounds including solubility, metabolic stability, and lipophilicity, which are tenets of considerable importance in pharmaceutical, agrochemical, and materials science. Visible-light-photocatalyzed difluoromethylation reactions are shown to be accomplished on (hetero)aromatic and carbon–carbon unsaturated aliphatic substrates under mild and environmentally benign conditions.

Новые возможности количественного хроматографического анализа методом двойного внутреннего стандарта

One of the methods of chromatographic quantitation of analytes in complex matrices with sorption properties is the modified double standard method. It implies introducing the two homologues of target analytes into original samples. This mode provides the high accuracy of determinations despite of any losses of their constituents at all stages of sample preparation. The application of this method is illustrated on the examples of model samples prepared by adding of polar alkanecarboxylic acids to the polar sorbent Silipor 75 (LaChema, Check Republic) followed by their extraction and conversion into derivatives (ethyl esters) for gas chromatographic determination. Relative errors of this mode are (-1) – (-8) %, that is significantly less than those of other possible methods. It is shown this method is applicable at the presence of homologues of analytes in the initial samples, and it can be generalized onto any number of carbon atoms in the molecules of selected standards. The single principal restriction of the double internal standard method remains to be practical availability of the reference samples of homologues. Key words: Quantitative chromatographic analysis, matrix effects, sample preparation, losses of analytes, desorption, extraction, derivatization, double internal standard method. (Russian) DOI: http://dx.doi.org/10.15826/analitika.2014.18.4.014 Igor G. Zenkevich, Konstantin M. Korolev St. Petersburg State University, St. Petersburg, Russian Federation REFERENCES 1. Novak J. Quantitative Analysis by Gas Chromatography . New York: Marcel Dekker Inc., 1975. 130 p. 2. Stolyarov B.V., Savinov I.M., Vitenberg A.G., Kartsova L.A., Zenkevich I.G., Kalmanovskii V.I., Kalambet Yu.A. Prakticheskaia gazovaia i zhidkostnaia khromatografiia [Practical Gas and Liquid Chromatography]. St. Petersburg, Univ. Press, 2002. 610 p. (in Russian). 3. Grob R.L., Barry E.F. Modern Practice of Gas Chromatography . 4 th Edn. New York: John Wiley & Sons, 2004. 1045 p. 4. Zenkevich I.G., Ragozina T.N. [Quantitative gas chromatographic analysis of heterophase systems constituents by double standard addition]. Zhurnal prikladnoi khimii [Rus. J. Appl. Chem.], 1998, vol. 71, no. 5, pp. 763-767. 5. Zenkevich I.G., Ostroukhova O.K. [A comparison of the external standard and standard addition methods for the quantitative chromatographic determination of pesticide concentrations in plant samples]. Zhurnal analiticheskoi khimii [Rus. J. Anal. Chem.], 2006, vol. 61, no. 5, pp. 442-451. 6. Zenkevich I.G., Klimova I.O. [Use of the Standard Addition Method in Quantitative Chromatographic Analysis]. Zhurnal analiticheskoi khimii [Rus. J. Anal. Chem.], 2006, vol. 61, no. 10, pp. 967-972. 7. Zenkevich I.G., Morozova T.E. [Areas of application and characteristics of quantitative chemical analysis by the conse­cutive standard addition method]. Zhurnal analiticheskoi khimii [Rus. J. Anal. Chem.], 2014, vol. 69, no. 4, pp. 327-335. 8. Zenkevich I.G., Morozova T.E. [Features of HPLC-MS determination of monoethanolamine in aqueous solutions by standard addition]. Analitika i Kontrol’ [Analytics and Control], 2012, vol. 16, no. 2, pp. 181-187 (in Russian). 9. Marinichev A.N., Morozova T.E., Zenkevich I.G. [Application of the logistic regression for quantitation by standard addition]. Uspekhi Sovremennogo Estestvoznaniia [Success of modern natural science], 2013, no. 11, pp. 152-157 (in Russian). 10. Morozova T.E., Karakashev G.V., Sorokoumov P.N., Savel’eva E.I., Zenkevich I.G. [Comparison of the precision of calibration and modified standard addition methods on the example of determination of 3-(2,2,2-trimethylhydrazine)propanoic acid in urine at non-linear detection]. Analitika i Kontrol’ [Analytics and Control], 2013, vol. 17, no. 2, pp. 184-189 (in Russian). 11. Zenkevich I.G., Makarov E.D. [Chromatographic quantitation at losses of analyte during sample preparation. Application of the modified method of double internal standard]. J. Chromatogr. A. , 2007, V. 1150, pp. 117-123. doi: 10.1016/j.chroma.2006.08.083 12. Zenkevich I.G., Makarov E.D., Makarova I.Yu. [Quantitative chromatographic analysis at the variation of sample composition during sample preparation. Modification of the double internal standard method]. Zhurnal analiticheskoi khimii. [Rus. J. Anal. Chem.], 2007, vol. 62, no. 8, pp. 748-755. 13. Vigdergauz M.S., Krause I.M. [Development of methods for quantitative interpretation of chromatograms of complex mixtures]. Zhurnal analiticheskoi khimii . [Rus. J. Anal. Chem.], 1986, vol. 41, no. 11, pp. 2064-2074. 14 Zenkevich I.G. [General relations holding in variations of physical properties of organic compounds within homologous series]. Zhurnal organicheskoi khimii . [Rus. J. Org. Chem.], 2006, vol. 42, no. 1, pp. 1-11. 15. Blau K., Halket J.M. Handbook of Derivatives for Chromatography . 2 nd Edn. New York: John Wiley & Sons, 1993. 369 p. 16. The NIST 11 Mass Spectral Library (NIST11/2011/EPA/NIH). Software/Data Version (NIST08); NIST Standard Reference Database, Number 69, August 2011. National Institute of Standards and Techno­logy, Gaithersburg, MD20899. Available at: http://webbook.nist.gov (Accessed August 31, 2014).

Calculating physical properties of organic compounds for environmental modeling from molecular structure

Mathematical models for predicting the transport and fate of pollutants in the environment require reactivity parameter values - that is the value of the physical and chemical constants that govern reactivity. Although empirical structure-activity relationships have been developed that allow estimation of some constants, such relationships are generally valid only within limited families of chemicals. The computer program, SPARC, uses computational algorithms based on fundamental chemical structure theory to estimate a large number of chemical reactivity parameters and physical properties for a wide range of organic molecules strictly from molecular structure. Resonance models were developed and calibrated using measured light absorption spectra, whereas electrostatic interaction models were developed using measured ionization pK(a)s in water. Solvation models (i.e., dispersion, induction, H-bonding, etc.) have been developed using various measured physical properties data. At the present time, SPARC's physical property models can predict vapor pressure and heat of vaporization (as a function of temperature), boiling point (as a function of pressure), diffusion coefficient (as a function of pressure and temperature), activity coefficient, solubility, partition coefficient and chromatographic retention time as a function of solvent and temperature. This prediction capability crosses chemical family boundaries to cover a broad range of organic compounds.

General relations holding in variation of physical properties of organic compounds within homologous series

The patterns of variation of different parameters (A) of organic compounds within a homologous series (such as boiling point under atmospheric pressure, critical temperature, critical pressure, refractive index, relative density, viscosity, surface tension, saturated vapor pressure, dielectric constant, first adiabatic ionization energies, etc.) are identical, and they can be described in terms of a single linear recurrent equation, A(n+1)=aA(n)+b. This equation relates a property of any member of a homologous series to the corresponding parameters of preceding homologs. The largest deviations from the proposed relation were revealed only in some homologous series for a few (1 or 2) simplest representatives which are characterized by deviations of all parameters.

Prediction of the Solubility, Activity Coefficient and Liquid/Liquid Partition Coefficient of Organic Compounds

AbstractSolvation models, based on fundamental chemical structure theory, were developed in the SPARC mechanistic tool box to predict a large array of physical properties of organic compounds in water and in non‐aqueous solvents strictly from molecular structure. The SPARC self‐interaction solvation models that describe the intermolecular interaction between like molecules (solute‐solute or solvent‐solvent) were extended to quantify solute‐solvent interaction energy in order to estimate the activity coefficient in almost any solvent. Solvation models that include dispersion, induction, dipole‐dipole and hydrogen bonding interactions are used to describe the intermolecular interaction upon placing an organic solute molecule in any single or mixed solvent system. In addition to estimation of the activity coefficient for 2674 organic compounds, these solvation models were validated on solubility and liquid/liquid distribution coefficient in more than 163 solvents including water. The RMS deviations of the calculated versus observed activity coefficients, solubilities and liquid/liquid distribution coefficients were 0.272 log mole fraction, 0.487 log mole fraction and 0.44 log units, respectively.

Total and Local Quadratic Indices of the Molecular Pseudograph's Atom Adjacency Matrix: Applications to the Prediction of Physical Properties of Organic Compounds

A novel topological approach for obtaining a family of new molecular descriptors is proposed. In this connection, a vector space E (molecular vector space), whose elements are organic molecules, is defined as a “direct sum” of different ℜi spaces. In this way we can represent molecules having a total of i atoms as elements (vectors) of the vector spaces ℜi (i=1, 2, 3,..., n; where n is number of atoms in the molecule). In these spaces the components of the vectors are atomic properties that characterize each kind of atom in particular. The total quadratic indices are based on the calculation of mathematical quadratic forms. These forms are functions of the k-th power of the molecular pseudograph’s atom adjacency matrix (M). For simplicity, canonical bases are selected as the quadratic forms’ bases. These indices were generalized to “higher analogues” as number sequences. In addition, this paper also introduces a local approach (local invariant) for molecular quadratic indices. This approach is based mainly on the use of a local matrix [Mk(G, FR)]. This local matrix is obtained from the k-th power (Mk(G)) of the atom adjacency matrix M. Mk(G, FR) includes the elements of the fragment of interest and those that are connected with it, through paths of length k. Finally, total (and local) quadratic indices have been used in QSPR studies of four series of organic compounds. The quantitative models found are significant from a statistical point of view and permit a clear interpretation of the studied properties in terms of the structural features of molecules. External prediction series and cross-validation procedures (leave-one-out and leave-group-out) assessed model predictability. The reported method has shown similar results, compared with other topological approaches. The results obtained were the following: a) Seven physical properties of 74 normal and branched alkanes (boiling points, molar volumes, molar refractions, heats of vaporization, critical temperatures, critical pressures and surface tensions) were well modeled (R>0.98, q2>0.95) by the total quadratic indices. The overall MAE of 5-fold cross-validation were of 2.11 oC, 0.53 cm3, 0.032 cm3, 0.32 KJ/mol, 5.34 oC, 0.64 atm, 0.23 dyn/cm for each property, respectively; b) boiling points of 58 alkyl alcohols also were well described by the present approach; in this sense, two QSPR models were obtained; the first one was developed using the complete set of 58 alcohols [R=0.9938, q2=0.986, s=4.006oC, overall MAE of 5-fold cross-validation=3.824 oC] and the second one was developed using 29 compounds as a training set [R=0.9979, q2=0.992, s=2.97 oC, overall MAE of 5-fold cross-validation=2.580 oC] and 29 compounds as a test set [R=0.9938, s=3.17 oC]; c) good relationships were obtained for the boiling points property (using 80 and 26 cycloalkanes in the training and test sets, respectively) using 2 and 5 total quadratic indices: [Training set: R=0.9823 (q2=0.961 and overall MAE of 5-fold cross-validation=6.429 oC) and R=0.9927 (q2=0.977 and overall MAE of 5-fold cross-validation=4.801 oC); Test set: R=0.9726 and R=0.9927] and d) the linear model developed to describe the boiling points of 70 organic compounds containing aromatic rings has shown good statistical features, with a squared correlation coefficient (R2) of 0.981 (s=7.61 oC). Internal validation procedures (q2=0.9763 and overall MAE of 5-fold cross-validation=7.34 oC) allowed the predictability and robustness of the model found to be assessed. The predictive performance of the obtained QSPR model also was tested on an extra set of 20 aromatic organic compounds (R=0.9930 and s=7.8280 oC). The results obtained are valid to establish that these new indices fulfill some of the ideal requirements proposed by Randić for a new molecular descriptor.

Simple Neural Network Models for Prediction of Physical Properties of Organic Compounds

Quantitative structure-performance-based neural network models for estimating physical properties of organic compounds are proposed. Several configurations of neural networks with various molecular descriptors as inputs have been tested. The molecular descriptors studied are UNIFAC group surface area and group volume parameters, molecular weight and normal boiling point. The advantage of choosing these parameters is that they can be easily obtained for a given compound, irrespective of the functional groups it may contain. Physical properties estimated include critical temperature, pressure, volume and normal boiling point. Neural network models were found to give reasonable estimates for various classes of organic compounds, often even without recourse to experimentally measured values of any property as an input.

Prediction of Physical Properties of Organic Compounds Using Artificial Neural Networks within the Substructure Approach

Prediction of Physical Properties of Organic Compounds Using Artificial Neural Networks within the Substructure Approach

Estimating thermodynamic properties of organic compounds using a solvation model

A model is proposed for the quantitative description of physical properties of organic compounds along the vapor–liquid saturation curve. This model uses solvation theory to describe the vapor–liquid transition, and the linear solvation energy relationship (LSER) concept to represent molecular energies and changes in the Gibbs free energy during the solvation process. The model has accurate predictive ability, rendering good quantitative estimates of the normal boiling temperatures and of the critical temperature and pressure of non-polar and of polar organic compounds, as confirmed for numerous compounds of diverse structures and degrees of polarity.

Advanced Organic Chemistry. Part A: Structure and Mechanisms. Fourth Edition. by Francis A. Carey

first_page settings Order Article Reprints Font Type: Arial Georgia Verdana Font Size: Aa Aa Aa Line Spacing:    Column Width:    Background: Open AccessNew Book Received Advanced Organic Chemistry. Part A: Structure and Mechanisms. Fourth Edition. by Francis A. Carey by Shu-Kun Lin MDPI, Saengergasse 25, CH-4054 Basel, Switzerland Molecules 2000, 5(12), 1528-1529; https://doi.org/10.3390/51201528 Received: 22 December 2000 / Published: 31 December 2000 Download Download PDF Download PDF with Cover Download XML Download Epub Versions Notes Since its original appearance in 1977, Advanced Organic Chemistry has found wide use as a text providing broad coverage of the structure, reactivity and synthesis of organic compounds. The Fourth Edition provides updated material but continues the essential elements of the previous edition. The material in Part A is organized on the basis of fundamental structural topics such as structure, stereochemistry, conformation and aromaticity and basic mechanistic types, including nucleophilic substitution, addition reactions, carbonyl chemistry, aromatic substitution and free radical reactions.The material in Part B is organized on the basis of reaction type with emphasis on reactions of importance in laboratory synthesis. As in the earlier editions, the text contains extensive references to both the primary and review literature and provides examples of data and reactions that illustrate and document the generalizations. While the text assumes completion of an introductory course in organic chemistry, it reviews the fundamental concepts for each topic that is discussed.The Fourth Edition updates certain topics that have advanced rapidly in the decade since the Third Edition was published, including computational chemistry, structural manifestations of aromaticity, enantioselective reactions and lanthanide catalysis.The two parts stand alone, although there is considerable cross-referencing. Part A emphasizes quantitative and qualitative description of structural effects on reactivity and mechanism. Part B emphasizes the most general and useful synthetic reactions. The focus is on the core of organic chemistry, but the information provided forms the foundation for future study and research in medicinal and pharmaceutical chemistry, biological chemistry and physical properties of organic compounds. *Editor's Note: The brief summary and the contents of the books are reported as provided by the author or the publishers. Authors and publishers are encouraged to send review copies of their recent books of potential interest to readers of Molecules to the Editor-in-Chief (Dr. Shu-Kun Lin, MDPI, Saengergasse 25, CH-4054 Basel, Switzerland. Tel. +41 79 322 3379, Fax +41 61 302 8918, E-mail: [email protected]). Some books will be offered to the scholarly community for the purpose of preparing full-length reviews. © 2000 by MDPI (http://www.mdpi.org). Share and Cite MDPI and ACS Style Lin, S.-K. Advanced Organic Chemistry. Part A: Structure and Mechanisms. Fourth Edition. by Francis A. Carey. Molecules 2000, 5, 1528-1529. https://doi.org/10.3390/51201528 AMA Style Lin S-K. Advanced Organic Chemistry. Part A: Structure and Mechanisms. Fourth Edition. by Francis A. Carey. Molecules. 2000; 5(12):1528-1529. https://doi.org/10.3390/51201528 Chicago/Turabian Style Lin, Shu-Kun. 2000. "Advanced Organic Chemistry. Part A: Structure and Mechanisms. Fourth Edition. by Francis A. Carey" Molecules 5, no. 12: 1528-1529. https://doi.org/10.3390/51201528 Find Other Styles Article Metrics No No Article Access Statistics For more information on the journal statistics, click here. Multiple requests from the same IP address are counted as one view.

On the Topological Sub-Structural Molecular Design (TOSS-MODE) in QSPR/QSAR and Drug Design Research

A recently introduced graph-theoretical approach to the study of structure-property-activity relationships is presented. The theoretical approach and the computational strategy for the use of the TOSS-MODE approach are given with details. Several QSPR and QSAR applications are reviewed including the study of physical properties of organic compounds, diamagnetic susceptibilities, and biological properties. The applications of the TOSS-MODE approach to discrimination of active/inactive compounds, the virtual screening of compounds with a desired property from databases of chemical structures, identification of active/inactive fragments and its relationships with 2D/3D pharmacophores, and to the design of novel compounds with desired biological activities are also reviewed.

UPPER III: Unified physical property estimation relationships. Application to non‐hydrogen bonding aromatic compounds

The UPPER scheme uses four additive and two nonadditive parameters and several well‐known equations to calculate 21 physical properties of organic compounds strictly from molecular structure. The scheme allows reasonable estimations of melting and boiling points, aqueous and octanol solubilities, air–octanol, air–water, and octanol–water partition coefficients, vapor pressure, and other properties. In this report non‐hydrogen bonding aromatic compounds are used to evaluate a portion of the UPPER scheme.

Neural Network-Graph Theory Approach to the Prediction of the Physical Properties of Organic Compounds

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTNeural Network-Graph Theory Approach to the Prediction of the Physical Properties of Organic CompoundsAndrei A. Gakh, Elena G. Gakh, Bobby G. Sumpter, and Donald W. NoidCite this: J. Chem. Inf. Comput. Sci. 1994, 34, 4, 832–839Publication Date (Print):July 1, 1994Publication History Published online1 May 2002Published inissue 1 July 1994https://doi.org/10.1021/ci00020a017RIGHTS & PERMISSIONSArticle Views493Altmetric-Citations55LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (780 KB) Get e-Alerts

Estimation of Properties of Acyclic Organic Compounds Using Conjugation Operators

The ABC approach to the estimation of thermodynamic and physical properties of organic compounds is based on the contributions of Atoms and Bonds in the properties of Conjugate forms of a molecular structure. The method has successfully been applied to the estimation of properties of acyclic hydrocarbons. The approach is extended to the estimation of thermodynamic and physical properties of acyclic organic compounds which may contain nitrogen, oxygen, or sulfur. The estimated properties are standard enthalpy of formation, normal boiling point, standard enthalpy of vaporization, critical pressure, critical temperature, and critical volume. The ABC technique is more accurate than a typical group-contribution approach

Purification and Physical Properties of Organic Compounds. XII. The Lower Aliphatic Bromides1

Purification and Physical Properties of Organic Compounds. XII. The Lower Aliphatic Bromides¹

Purification and Physical Properties of Organic Compounds. X. The Freezing Point Diagram for the System Acetanilide—Propionanilide1

Purification and Physical Properties of Organic Compounds. X. The Freezing Point Diagram for the System Acetanilide—Propionanilide¹

Purification and Physical Properties of Organic Compounds. IX. Some Binary Freezing Point Diagrams and a Study of Their Ideality

Purification and Physical Properties of Organic Compounds. IX. Some Binary Freezing Point Diagrams and a Study of Their Ideality