University of Houston

About: University of Houston is a education organization based out in Houston, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 23074 authors who have published 53903 publications receiving 1641968 citations.

Studies on Thermoelectric Properties of n‐type Polycrystalline SnSe1‐xSx by Iodine Doping

Abstract: Iodine-doped n-type SnSe polycrystalline by melting and hot pressing is prepared. The prepared material is anisotropic with a peak ZT of ≈0.8 at about 773 K measured along the hot pressing direction. This is the first report on thermoelectric properties of n-type Sn chalcogenide alloys. With increasing content of iodine, the carrier concentration changed from 2.3 × 1017 cm−3 (p-type) to 5.0 × 1015 cm−3 (n-type) then to 2.0 × 1017 cm−3 (n-type). The decent ZT is mainly attributed to the intrinsically low thermal conductivity due to the high anharmonicity of the chemical bonds like those in p-type SnSe. By alloying with 10 at% SnS, even lower thermal conductivity and an enhanced Seebeck coefficient were achieved, leading to an increased ZT of ≈1.0 at about 773 K measured also along the hot pressing direction.

Pharmacological characterization of a neuronal receptor for 5-hydroxytryptamine in guinea pig ileum with properties similar to the 5-hydroxytryptamine receptor.

Abstract: Experiments were undertaken to characterize pharmacologically a neuronal receptor to 5-HT in guinea pig ileum. Segments of longitudinal muscle myenteric plexus preparations were treated with phenoxybenzamine and exposed to submaximal electrical field stimulation to evoke the cholinergically mediated "twitch" response. The ability of 5-HT to enhance the submaximal twitch response was investigated. Results using several antagonists (metergoline, spiperone, cyanopindolol, N-acetyl-5-hydroxytryptophyl-5-hydroxytryptophan amide, N-hexanoyl-5-hydroxytryptophyl-5-hydroxytryptophan amide, ICS 205-930, GR 38032F, MDL 72222 and cocaine) indicate that 5-HT (3 X 10(-10) to 1 x 10(-7) M) agonizes a novel 5-HT receptor site distinct from the 5-HT1, 5-HT2, 5-HT3 and 5-HT1P subtypes as well as the M receptor. The receptor site is located neuronally and is characterized positively by a low affinity for ICS 205-930 (pA2 = 6.5 vs. 5-HT) and by the following order of agonist potency: 5-HT greater than 5-methoxytryptamine greater than BRL 24924 greater than alpha-methyl-5-hydroxytryptamine greater than zacopride = cisapride = 5-carboxamidotryptamine. Agonist-independent pA2 estimates for ICS 205-930 (6.3-6.6) suggest a single site of agonism. 2-Methyl-5-hydroxytryptamine and 5-hydroxyindalpine were inactive at 1 x 10(-5) M either as agonists or antagonists. Thus, the receptor site exhibits a pharmacological profile similar to that characterizing the recently described 5-HT4 [corrected] receptor. Unlike Gaddum's M receptor, which equates with the 5-HT3 [corrected] receptor, the putative 5-HT4 [corrected] receptor site exhibits a higher sensitivity to agonism by 5-HT and is resistant to antagonism by cocaine.

The Law of Higher Education

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Predicting the Band Gaps of Inorganic Solids by Machine Learning.

Abstract: A machine-learning model is developed that can accurately predict the band gap of inorganic solids based only on composition. This method uses support vector classification to first separate metals from nonmetals, followed by quantitatively predicting the band gap of the nonmetals using support vector regression. The superb accuracy of the regression model is obtained by using a training set composed entirely of experimentally measured band gaps and utilizing only compositional descriptors. In fact, because of the unique training set of experimental data, the machine learning predicted band gaps are significantly closer to the experimentally reported values than DFT (PBE-level) calculated band gaps. Not only does this resulting tool provide the ability to accurately predict the band gap for any composition but also the versatility and speed of the prediction based only on composition will make this a great resource to screen inorganic phase space and direct the development of functional inorganic materials.