2,2-Bis(4-butoxyphenyl)-1,1,1-trichloroethane

In the structure of the title compound C22H27Cl302, which is the p-butoxyphenyl analogue of the insecticidally active p-methoxyphenyl compound methoxychlor, the dihedral angle between the two phenyl rings is 79.61(11)deg. Present also in the structure is an intramolecular aromatic C-H...Cl interaction [3.361(2)Ang].

Plasma polymerization of 1,1,1-trichloroethane yields a coating with robust antibacterial surface properties

Novel, highly chlorinated surface coatings were produced via a one-step plasma polymerization (pp) of 1,1,1-trichloroethane (TCE), exhibiting excellent antimicrobial properties against the vigorously biofilm-forming bacterium Staphylococcus epidermidis.

Thermodynamic properties of the system toluene — 1, 1, 1-trichloroethane

Data on molar excess enthalpy on mixing at 298.15 K and 308.15 K, vapor-liquid equilibrium, latent heats of vaporization at 91.444 kPa and vapor pressures for the system toluene – 1, 1, 1-trichloroethane are presented. A simple adiabatic calorimeter designed for molar excess enthalpy measurements is described, tested and used. On présente, dans le cas du système toluène – 1, 1, 1-trichloréthane, des résultats relatifs aux grandeurs suivantes: a) enthalpie molaire d'excès à 298.15 K et 308.15 K; b) équilibre liquid-vapeur; c) chaleurs latentes de vaporisation à une pression absolue de 91.444 kP; d) pressions de vapeur. On décrit un calorimètre adiabatique simple, conçu pour mesurer l'enthalpie molaire d'excès, dont on a fait l'essai.

Health assessment document for 1, 1, 1-Trichloroethane (methyl chloroform) : final report.

Mode of access: Internet.

Toxicological profile for 1,1,1-trichloroethane : draft /

"December, 1990,"

Direct observation of extremely low temperature catalytic dehydrochlorination of 1,1,1-trichloroethane over platinum

Fast X-ray photoelectron spectroscopy reveals that the efficient catalytic destruction of 1,1,1-trichloroethane occurs over Pt{111} surfaces at temperatures as low as 150 K. Decomposition occurs via rapid, sequential C-Cl bond scission to form an alkylidyne surface intermediate that in turn dehydrogenates above room temperature. Atomic chlorine liberated during dehydrochlorination undergoes efficient reaction with surface hydrogen, resulting in the evolution of gaseous HCl and small amounts of ethane, presumably via ethylidyne hydrogenation. Irreversible dehydrogenation of residual hydrocarbon fragments results in significant surface coking above 500 K.

Low temperature 1,1,1-trichloroethane dehydrochlorination over Pt catalysts:from model surfaces to the real world

Fast X-ray photoelectron spectroscopy reveals efficient C–Cl activation of 1,1,1-trichloroethane occurs over platinum surfaces at 150 K, and in the presence of hydrogen, sustained ambient temperature dehydrochlorination to HCl and ethane is possible over supported Pt/Al2O3 catalysts.

The effects and extent of 1,1,1-trichloroethane vapor concentration exposure on workers during solvent vapor degreasing

This study attempted to determine if an excessive amount of 1,1,1 - Trichloroethane was released into the air, the acute effects of exposure and the cause(s) of excessive use. The types of degreasing equipments which were tested in this study are straight vapor and the vapor spray machines. The instruments utilized to obtain the data for this study are Gastech Haline Detector, Organic Vapor Monitor Badge and Personal Sampling Pump. Readings were taken on three different tanks. The data accumulated by this study were obtained during actual cleaning operation. During testing, increased exposure was detected due to exceeding the rate of removal, downward drafts were blowing right over the top of a degreaser and, in some cases, poor general ventilation caused solvent vapor to be blown out of the tank and into the workers' breathing zone, affecting excessive vapor drag out and solvent loss. The results show that, since the characteristics of solvent 1,1,1 - Trichloroethane are well suited to vapor degreasing requirements, by using proper procedures and maintenance, 1,1,1 - Trichloroethane emission during vapor degreasing can be controlled at levels well below the industrial hygiene standard established by OSHA for safe and healthful conditions.

Sulfate-enhanced catalytic destruction of 1,1,1-trichlorethane over Pt(111)

The catalytic destruction of 1,1,1-trichloroethane (TCA) over model sulfated Pt(111) surfaces has been investigated by fast X-ray photoelectron spectroscopy and mass spectrometry. TCA adsorbs molecularly over SO4 precovered Pt(111) at 100 K, with a saturation coverage of 0.4 monolayer (ML) comparable to that on the bare surface. Surface crowding perturbs both TCA and SO4 species within the mixed adlayer, evidenced by strong, coverage-dependent C 1s and Cl and S 2p core-level shifts. TCA undergoes complete dechlorination above 170 K, accompanied by C−C bond cleavage to form surface CH3, CO, and Cl moieties. These in turn react between 170 and 350 K to evolve gaseous CO2, C2H6, and H2O. Subsequent CH3 dehydrogenation and combustion occurs between 350 and 450 K, again liberating CO2 and water. Combustion is accompanied by SO4 reduction, with the coincident evolution of gas phase SO2 and CO2 suggesting the formation of a CO−SOx surface complex. Reactively formed HCl desorbs in a single state at 400 K. Only trace (<0.06 ML) residual atomic carbon and chlorine remain on the surface by 500 K.

Thermodynamic properties of the systems benzene-chloroethanes

This paper presents the experimental data on vapor-liquid equilibrium and heats of mixing of mixtures of benzene with 1, e-dichloroethane, 1, l, 1 -trichloroethane, and lt1,2,2-tetrachloroethane.A literature survey revealed that the heats of mixing of benzene-l,2-dichloroethane have been studied and Table I shows the extent of study on this system.

Développement de modèles prédictifs de la toxicocinétique de substances organiques

Les modèles pharmacocinétiques à base physiologique (PBPK) permettent de simuler la dose interne de substances chimiques sur la base de paramètres spécifiques à l’espèce et à la substance. Les modèles de relation quantitative structure-propriété (QSPR) existants permettent d’estimer les paramètres spécifiques au produit (coefficients de partage (PC) et constantes de métabolisme) mais leur domaine d’application est limité par leur manque de considération de la variabilité de leurs paramètres d’entrée ainsi que par leur domaine d’application restreint (c. à d., substances contenant CH3, CH2, CH, C, C=C, H, Cl, F, Br, cycle benzénique et H sur le cycle benzénique). L’objectif de cette étude est de développer de nouvelles connaissances et des outils afin d’élargir le domaine d’application des modèles QSPR-PBPK pour prédire la toxicocinétique de substances organiques inhalées chez l’humain. D’abord, un algorithme mécaniste unifié a été développé à partir de modèles existants pour prédire les PC de 142 médicaments et polluants environnementaux aux niveaux macro (tissu et sang) et micro (cellule et fluides biologiques) à partir de la composition du tissu et du sang et de propriétés physicochimiques. L’algorithme résultant a été appliqué pour prédire les PC tissu:sang, tissu:plasma et tissu:air du muscle (n = 174), du foie (n = 139) et du tissu adipeux (n = 141) du rat pour des médicaments acides, basiques et neutres ainsi que pour des cétones, esters d’acétate, éthers, alcools, hydrocarbures aliphatiques et aromatiques. Un modèle de relation quantitative propriété-propriété (QPPR) a été développé pour la clairance intrinsèque (CLint) in vivo (calculée comme le ratio du Vmax (μmol/h/kg poids de rat) sur le Km (μM)), de substrats du CYP2E1 (n = 26) en fonction du PC n octanol:eau, du PC sang:eau et du potentiel d’ionisation). Les prédictions du QPPR, représentées par les limites inférieures et supérieures de l’intervalle de confiance à 95% à la moyenne, furent ensuite intégrées dans un modèle PBPK humain. Subséquemment, l’algorithme de PC et le QPPR pour la CLint furent intégrés avec des modèles QSPR pour les PC hémoglobine:eau et huile:air pour simuler la pharmacocinétique et la dosimétrie cellulaire d’inhalation de composés organiques volatiles (COV) (benzène, 1,2-dichloroéthane, dichlorométhane, m-xylène, toluène, styrène, 1,1,1 trichloroéthane et 1,2,4 trimethylbenzène) avec un modèle PBPK chez le rat. Finalement, la variabilité de paramètres de composition des tissus et du sang de l’algorithme pour les PC tissu:air chez le rat et sang:air chez l’humain a été caractérisée par des simulations Monte Carlo par chaîne de Markov (MCMC). Les distributions résultantes ont été utilisées pour conduire des simulations Monte Carlo pour prédire des PC tissu:sang et sang:air. Les distributions de PC, avec celles des paramètres physiologiques et du contenu en cytochrome P450 CYP2E1, ont été incorporées dans un modèle PBPK pour caractériser la variabilité de la toxicocinétique sanguine de quatre COV (benzène, chloroforme, styrène et trichloroéthylène) par simulation Monte Carlo. Globalement, les approches quantitatives mises en œuvre pour les PC et la CLint dans cette étude ont permis l’utilisation de descripteurs moléculaires génériques plutôt que de fragments moléculaires spécifiques pour prédire la pharmacocinétique de substances organiques chez l’humain. La présente étude a, pour la première fois, caractérisé la variabilité des paramètres biologiques des algorithmes de PC pour étendre l’aptitude des modèles PBPK à prédire les distributions, pour la population, de doses internes de substances organiques avant de faire des tests chez l’animal ou l’humain.

Measurement of fats, oil and grease by spectro-photometry and its application on different sites at São Paulo State, Brazil

This investigation was carried out within the Parana sedimentary basin, Brazil, involved the sampling of effluents and groundwater from monitoring stations situated at different sites at São Paulo State, and was realized with the purpose of evaluating the presence of fats, oil and grease (FOG) in different matrices. Several tests were realized with very distinct materials (cooking oil, butter, margarine, pig fat, vacuum pump oil) in order to properly calibrate the spectrophotometric system. Each matrix was dissolved with 1,1,1-trichloroethane and from the stock solutions it was prepared working standards from different dilutions. The data obtained were plotted on absorbance vs. concentration graph that yielded a successful calibration curve when a mineral oil for vacuum pump was utilized in the experiments at a wavelength corresponding to 410 mn. The results obtained for the analyzed samples were compared with the limiting value established by the São Paulo State legislation on the prevention and pollution control of the environment that was established in 8(th) September 1976 by Rule No. 8468.

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^