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The new topological indices (Sh indices) based on the distance sum and connectivity of a molecular graph, previously developed by our team, were extended to predict the two physicochemical properties, including normal boiling point (NBP) and molar refractivity (MR), of a large set of organic compounds consisting of alkanes, alkenes, ethers, amines, alcohols, alkylbenzenes, and alkylhalides. The sets of molecular descriptors were derived directly from the two-dimensional molecular structure of the compounds based on graph theory. Both linear and nonlinear modelings were implemented by using principal component regression (PCR) and principal component -- artificial neural network (PC--ANN) with back-propagation learning algorithm, respectively. Eigenvalue and correlation-ranking procedures were used to rank the principal components and entered them into the models. Principal component analysis of Sh data matrix showed that the respective six and seven PCs could explain 97.49% and 99.22% of variances in the Sh indices. PCR analysis of the NBP and MR data demonstrated that the proposed Sh indices could explain about 97.52% and 99.52% of variations, while the variations explained by the PC--ANN modeling were more than 99.00% and 99.82%, respectively. The predictive ability of the models were evaluated using an external test set for NBP and MR of the molecules with the respective root-mean-square errors lower than 9.69 K and 0.660 [cm.sup.3] [mol.sup.-1] for the linear model and 6.17 K and 0.416 [cm.sup.3] [mol.sup.-1] for the nonlinear model. Key words: topological Sh indices, eigenvalue ranking, correlation ranking, normal boiling point, molar refractivity, principal component analysis, principal component regression (PCR), principal component-artificial neural network (PC-ANN). Les nouveaux indices topologiques (indices Sh) bases sur la somme de la distance et la connectivite d'un graphe moleculaire et developpes anterieurement par notre equipe ont ete etendus afin de pouvoir predire deux proprietes physicochimiques, dont le point d'ebullition normal (PEN) et la refractivite molaire (RM) d'un large ensemble de composes organiques formes d'alcanes, d'alcenes, d'amines, d'alkylbenzenes et d'halogenures d'alkyle. Les ensembles de descripteurs moleculaires ont ete derives directement de la structure moleculaire bidimensionnelle des composes basee sur la theorie des graphes. On a developpe des modeles lineaires et non lineaires en utilisant l'algorithme d'apprentissage en retropropagation respectivement avec une regression du composant principal (RCP) et avec le reseau neural artificiel du composant principal (RNA--CP). On a fait appel aux methodes de la valeur de eigen et du classement des correlations pour classer les composants principaux qui ont ensuite ete introduits dans les modeles. L'analyse du composant principal d'une matrice de donnees Sh a permis de montrer que respectivement six ou sept composants principaux (CP) peuvent expliquer 97,49 % et 99,22 % des variances dans les indices Sh. L'analyse de la RCP des donnees relatives aux PEN et aux RM a permis de demontrer que les indices Sh peuvent expliquer environ 97,52 % et 99,52 % des variations alors que les variations expliquees par me modele RNA-CP expliquent respectivement 99,00 % et 99,82 % des variations. On a evalue l'habilite des modeles a faire des predictions relatives aux PEN et aux RM des molecules en utilisant un ensemble externe et les erreurs quadratiques moyennes respectives etaient inferieures reseau neural artificiel du composant principal (RNA--CP) a 9,69 K et 0,660 [cm.sup.3] [m.sup.-1] pour le modele lineaire et de 6,17 K et 0,416 [cm.sup.3] [m.sup.-1] pour le modele non lineaire. Mots-cles : indices SH topologiques, classement de valeurs de eigen, classement de correlation, point d'ebullition normal (PEN), refractivite moleculaire (RM), analyse du composant principal, regression du composant principal (RCP), reseau neural artificiel du composant principal (RNA-CP). [Traduit par la Redaction], Introduction One of the most fundamental ideas of chemistry is that the physicochemical properties, for instance, normal boiling point and molar refractivity, for chemical and chemical engineering substances are determined [...]

A hexagonal diethynylbenzene macrocycle having exterior octyloxymethyl groups undergoes spontaneous polymerization at room temperature to form hardly soluble materials, in contrast to the corresponding dehydrotetramer and dehydrooctamer, which are stable to show their melting points at higher than 140 degree Celsius.

The paper describes microwave differential thermal analysis, a new technique that combines the advantages of microwave heating with the benefits of differential temperature measurement to give a sensitive means of probing the thermal properties of materials as a function of temperature. Details are given of the theoretical background, equipment, design of sample cells, and different modes of operation. Examples are given for a wide range of thermal transitions including fusions, solid-solid phase transitions, and thermal decompositions. The results are discussed in the context of conventional differential thermal techniques.

The phenomenon of reduction of the carbodiimides by samarium(II) bis(trimethylsilyl)amides is studied. The formation of various oxalamidinates and amidinates through C-C coupling or C-H activation is also discussed.

A study demonstrates the application and importance of the freezing point depression of milk, a commonly used colligative property. The analysis reveals that the effective molar mass of milk depends on the presence of suspended particles.

The crystal structures of the high- and low-temperature (HT and LT) phases of PDTA at 323 K is determined to explore the bistability and phase transition in 1,3,2-dithiazolo[4,5-b]pyrazin-2-yl. The closer inspection of the two structures reveals that in the LT phase, all the molecules are coplanar with the (1,0,0) plane and in the HT form, the mean planes of alternate radicals along [0,0,1] are rotated clockwise and counterclockwise, so that they lie coplanar with the (2,1,0) and (2,-1,0) planes, respectively.

A study is conducted to demonstrate that variable-temperature STM under ultrahigh vacuum (UHV) helps to observe two interconvertible phases of PD in a monolayer of sashlike polymer atomic sash(AS) on a graphite (0001) surface. The monolayer of the sashlike PD atomic sash on graphite (0001) exhibits two interconvertible phases.

The use of sum-frequency generation vibrational spectroscopy to calculate the phase transition temperature of a single planar backed lipid bilayer is described. The results provide proof of the delocalization of domain structures between the two leaflets of the lipid bilayers.

A study reported that the Mno nanoclusters with cluster diameters of 5-10 nm show a ferromagnetic behavior with a phase transition from ferromagnetic to paramagnetic phases at 27K. The results show that for nanoclusters, the surface-to-volume ratio is very large, and surface atoms possess reduced coordination, which may alter spin configurations throughout the nanoclusters.