A Gliclazide Complex based on Palladium towards Alzheimer’s Disease: Promising Protective Activity against Aβ-induced Toxicity in C. Elegans

A new palladium coordination compound based on gliclazide with the chemical formula [Pd(glz)2] (where glz = gliclazide) has been synthesized and characterised. The structural characterization reveals that this material consists...

Burn XL Keto Customer Shoking & WARNING Reviews : Is It Legit? v1

The Keto Burn XL diet pill is one of the latest weight loss supplements available in today’s market. It has some chemical formula, but there are natural procedures involved with this product as well.

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The Keto Burn XL diet pill is one of the latest weight loss supplements available in today’s market. It has some chemical formula, but there are natural procedures involved with this product as well.

Nanostructured LaFeO3 /Si Thin Films Grown by Pulsed Laser Deposition

The orthorhombic LaFeO3 thin films grown by pulsed laser deposition on silicon showed nano-structuration of their surface and preferential crystallographic exposed facets, depending on the deposition temperature. The LaFeO3 film deposited at 850°C has two types of grain termination, flat or tip-like, corresponding to two different growth directions, respectively [110] and [200]. Due to the shape of the termination, the same {110} facets are exposed. The LaFeO3 is iron deficient and consequently contains oxygen vacancies, the exact chemical formula being LaFe0.82O3-delta.

Existence of solutions for a class of nonlinear boundary value problems on the hexasilinane graph

Chemical graph theory is a field of mathematics that studies ramifications of chemical network interactions. Using the concept of star graphs, several investigators have looked into the solutions to certain boundary value problems. Their choice to utilize star graphs was based on including a common point connected to other nodes. Our aim is to expand the range of the method by incorporating the graph of hexasilinane compound, which has a chemical formula $\mathrm{H}_{12} \mathrm{Si}_{6}$ H 12 Si 6 . In this paper, we examine the existence of solutions to fractional boundary value problems on such graphs, where the fractional derivative is in the Caputo sense. Finally, we include an example to support our significant findings.

Calcium substituted with magnesium, silver and zinc in hydroxyapatite: a review

Hydroxyapatite with the chemical formula Ca10(-PO4)6(OH)2 is an important bioceramic well known for its high osteoconductive properties, non-toxic nature, high bioactivity and good biocompatibility. Moreover, it is known to mimic natural bone. Inspite of the above mentioned advantages, it has certain disadvantages such as having poor mechanical properties, being brittle, not showing an inhibitory effect on microbes and taking a long time to resorb in the body. These disadvantages can be covered up by the addition of dopants which include cations, anions and polymers. These are sufficiently known to improve the properties of hydroxyapatite. This review focuses on the substitution of hydroxyapatite with silver, zinc, magnesium ions and alloys to show the changes in the morphology and biocompatible properties of hydroxyapatite after substitution of the ions in the matrix.

Structural and chemical characterization of dienerite, Ni3As, and its revalidation as a mineral species

ABSTRACT Dienerite, ideally Ni3As, was discovered in 1919 near Radstadt (Salzburg, Austria) and its description and chemical characterization date back to the 1920s. The paucity of reliable experimental data, as well as the absence of any other documented occurrences of such a mineral in over 80 years, led to the supposition of a typographic error in the transcription of the original chemical analysis, suggesting the mineral might in fact be nickelskutterudite [(Ni,Co,Fe)As3]. As a consequence, the mineral was discredited and deleted in the post-2006 IMA list of valid mineral species. Nonetheless, several minerals having a metal/As ratio close to 3:1 and a description fitting that of dienerite were reported after its discreditation. Here we report the discovery of minute inclusions in a sample of josephinite from Josephine Creek (Oregon, USA) exhibiting high optical and electron reflectance. Structural and chemical investigations unequivocally showed that a mineral having cubic structure [a = 9.6206(9) Å, sp. gr. I3d; R1 = 0.0353] and ideal chemical formula Ni3As does exist, suggesting that dienerite could in fact be a valid species. The proposal to revalidate dienerite has been approved by the Commission on New Minerals, Nomenclature and Classification (IMA-Proposal 19-E). The neotype is deposited in the mineralogical collections of the Natural History Museum, University of Florence, Italy, under catalogue number 3364/I.

MATHEMATICAL MODELING OF THE CRYSTAL STRUCTURE OF PEROVSKITE-LIKE MATERIALS

The paper presents the calculation of the metric parameters of crystalline compounds according to a given chemical formula and a space symmetry group. The structures of perovskite and double perovskite are considered.

Deep Learning Approach for Prediction of Critical Temperature of Superconductor Materials Described by Chemical Formulas

This paper proposes a novel neural network architecture and its ensembles to predict the critical superconductivity temperature of materials based on their chemical formula. The research describes the methods and processes of extracting data from the chemical formula and preparing these extracted data for use in neural network training using TensorFlow. In our approach, recurrent neural networks are used including long short-term memory layers and neural networks based on one-dimensional convolution layers for data analysis. The proposed model is an ensemble of pre-trained neural network architectures for the prediction of the critical temperature of superconductors based on their chemical formula. The architecture of seven pre-trained neural networks is based on the long short-term memory layers and convolution layers. In the final ensemble, six neural networks are used: one network based on LSTM and four based on convolutional neural networks, and one embedding ensemble of convolution neural networks. LSTM neural network and convolution neural network were trained in 300 epochs. Ensembles of models were trained in 20 epochs. All neural networks are trained in two stages. At both stages, the optimizer Adam was used. In the first stage, training was carried out by the function of losses Mean Absolute Error (MAE) with the value of optimizer learning rate equal to 0.001. In the second stage, the previously trained model was trained by the function of losses Mean Squared Error (MSE) with a learning rate equal to 0.0001. The final ensemble is trained with a learning rate equal to 0.00001. The final ensemble model has the following accuracy values: MAE is 4.068, MSE is 67.272, and the coefficient of determination (R2) is 0.923. The final model can predict the critical temperature for the chemistry formula with an accuracy of 4.068°.

Chemical Formulas and Nomenclature

Chemical Formula and Nomenclature explains the rules for writing chemical formulas and naming compounds. The concept of oxidation number and how to determine it within a molecule or a polyatomic ion is described. Rules for writing and naming ionic and molecular compounds are discussed.