On the Regularity of the Electron Configuration of Atoms in the Periodic Table

The current periodic table does not necessarily have a clear position for transition elements. Therefore, the purpose of this paper is to use the basic principle discovered by Mendeleev as it is and to create a periodic table with consistency for transition elements. By setting some hypotheses, it was found that transition elements also have regular periodicity, so we succeeded in clarifying the energy level of electrons in each orbit. In addition, by utilizing its periodicity, the electron configuration for each orbit was predicted for unknown elements. In this paper, we did not take the conventional idea of electron orbitals, that is, the idea of forming a hybrid orbital, but assumed a new orbital. Since the state in which electrons fit in orbits and stabilize is defined as an octet, this idea was used as the basic principle in this paper, but the hypothesis that "there are only three orbits in each shell" was established and verified. The calculation of the energy level of the electrons on the orbit became extremely easy, and the order of each orbit could be clarified. It was also found that the three-dimensional structure of the molecule may be visualized by paying attention to the valence electrons of the outermost shell of the element and the octet of the stability condition. Therefore, in this paper, by slightly expanding the structural formula of Kekulé, it became possible to easily determine whether or not the molecule synthesized by the bond between elements is stable. In addition, it has become possible to predict the three-dimensional structure of the molecule as well. Furthermore, not only will it be easier for students studying chemistry to understand complex chemical reactions, but it will also be useful for researchers in the development and research of new drugs.

Development of polymer emulsions stabilized with anionic polyelectrolytes

The colloidal-chemical principles of the formation of reversibly reversible microemulsions based on compositions of anionic polysaccharides, higher fatty acids, and nonionic polyoxyethylated surfactants have been investigated. The structural formula of the interpolymer complex in the “polyelectrolyte - surfactant” system was proposed, and the molar ratios of the components were determined. The effectiveness of the developed polymer emulsions as drilling fluids for the construction of oil wells is shown.

Absorption of SO2 by triethylenetetramine in ether (alcohol)/H2O system

The use of organic solvents to remove SO2 from flue gas has the advantages of low investment cost, convenient operation, high efficiency, and reusability. We prepared three absorbents in this paper, namely tetraethylenetetramine (TETA), triethylenetetramine /triethylene glycol dimethyl ether (TriEDGME), and triethylenetetramine/triethylene glycol dimethyl ether/H2O. The atmospheric bubbling method absorbs SO2. The experimental results show that the three kinds of absorbents formed white precipitates after adsorbing SO2. The infrared spectra analysis and element analysis of the three types of precipitate showed that their chemical structures were basically the same. The structural formula is NH2(CH2)2NH(CH2)2NH3SO3NH2·2H2O; the product was determined to be a shaped crystal structure by XRD and SEM. In addition, the thermal stability analysis of the product revealed that the product sublimed at 123 °C and decomposed at about 185 °C.

Computing Gutman Connection Index of Thorn Graphs

Chemical structural formula can be represented by chemical graphs in which atoms are considered as vertices and bonds between them are considered as edges. A topological index is a real value that is numerically obtained from a chemical graph to predict its various physical and chemical properties. Thorn graphs are obtained by attaching pendant vertices to the different vertices of a graph under certain conditions. In this paper, a numerical relation between the Gutman connection (GC) index of a graph and its thorn graph is established. Moreover, the obtained result is also illustrated by computing the GC index for the particular families of the thorn graphs such as thorn paths, thorn rods, thorn stars, and thorn rings.

THERMAL STIFFNESS – A KEY ACCURACY INDICATOR OF MACHINE TOOLS

Static and dynamic stiffness [N/m] determine the ability of solids to resist constant and variable loads. Both elastic characteristics of a machine tool effect their quality assessment. Thermal stiffness (comprising heat stiffness and temperature stiffness) [W/µm] is a key accuracy indicator of the machine tool's ability to resist temperature influences. The proposed method creates the thermo-physical structure of a machine tool, based on a set of homogeneous heat-active elements and quasi-thermostable links. Quasi-thermostable links retain constant properties when the thermal state of the heat-active elements changes within a given range, building and determining their spatial and temporal relative position. The structural formula is given: < S-thermal link > -<F-function of the thermal behavior of a heat-active element > - <S-thermal link>. When exposed to heat, heat-active elements change their temperature and thermoelastic properties change their temperature and thermoelastic properties with stress, strain, distortion. Thermal behavior F-functions characterize these changes over time. Thermal energy causes a heat exchange in the machine tool and leads to temperature differences, thermoelastic stresses and geometrical deformations. The material used in machine tools enables the thermal conduction, convection and radiation due to its dimensions, volume and surface area, thermal conductivity. Elasticity effects base on thermal linear expansion coefficient, modulus of elasticity, thermal energy storage due to its heat capacity. The analysis of the structural formula defines and describes generalized thermal stiffness indicators of a machine tool as a reaction to thermal effects when the heat sources are constantly active and when the heat source is absent, but only the ambient temperature changes. This paper presents relationships between the thermal stiffness and the thermo-physical property indicators of the machine tool. Examples of thermal stiffness are described for several machine tool types.

Local Cuban bentonite clay: composition, structure and textural characterization

The Cuban bentonite clays have a specific surface area of 79.9098 m2.g-1, a pore volume of about 0.077612 cm3.g-1 and both isotherms exhibited a hysteresis loop of IV type. X-ray diffractogram of raw bentonite shows that the main mineralogical component is montmorillonite (> 90%). The mineral object study presents the first endothermic peak, characteristic of montmorillonite, in 48.11 ºC and others less accentuated (80.81, 94.01, 119.81 ºC) characteristic of calcium montmorillonite, that corresponds to the loss of water, and can be extended up to 250 ºC. The FTIR spectra showed the existence of Si-OH, Al-Al-OH, Al-Fe-OH, Al-Mg-OH and Si-O-Si functional groups in all clay samples, confirmed the presence of hydrated aluminosilicate in the clay, bands between 1120 and 461 cm-1 correspond to phyllosilicate structures and OH stretching vibrations were observed. The pH at the point of zero charge (pHPZC) obtained has a value of 8.1, which allows montmorillonite to be classified as basic. The structural formula for one-layer unit of montmorillonite was determined as (Na3.99Al0.01)(Al1.11Fe3+0.49Mg0.18Ti0.07)(Ca0.24Na0.15K0.01)O10(OH)2, indicate the location of the different cations in metal oxide octahedrons or tetrahedrons, respectively. From the results obtained by different methods and the analysis of the calculated structural formula, it can be concluded that the bentonite under study is a calcium montmorillonite, with a low specific surface area and little porosity.

Alluaudite-Group Phosphate and Arsenate Minerals

ABSTRACT A systematic study of alluaudite, hagendorfite, and varulite was done using single-crystal X-ray diffraction, powder diffraction, and electron probe microanalysis of samples from 12 separate localities. The crystal structures of the representative alluaudite and hagendorfite samples were refined to R1 indices of 3.7 and 1.8%, respectively, using a Siemens P4 automated four-circle diffractometer equipped with a graphite monochromator and MoKα X-radiation. These samples and several others were analyzed with an electron microprobe to study variations in chemical composition. For the single-crystal analyses, the resulting unit formulae are (Na0.11□0.89)(Na0.59Mn0.27Ca0.14)Mn1.00(Fe3+1.64Al0.24Mg0.13)(PO4)3 for alluaudite, (Na0.79□0.21)(Na0.81Mn2+0.19)(Mn0.70Fe2+0.30)(Fe2+1.72Mg0.27Al0.01)(PO4)3 for hagendorfite, and (Na0.84□0.16)(Na0.71Ca0.23□0.06)Mn1.00(Fe3+0.89Fe2+0.68Mn0.42Mg0.01)(PO4)3 for varulite. Originally, a nomenclature scheme was proposed for the alluaudite-group minerals that was based on sequentially distributing the cations in the cell according to increasing polyhedron size, matching that size with increasing ionic radii of the cations. For alluaudite, the structural formula was written as X(2)4X(1)4M(1)4M(2)8(PO4)12, with the sites ordered in decreasing size of the discrete polyhedra. Later, the formula [A(2)A(2)'A(2)”2][A(1)A(1)'A(1)”2]M(1)M(2)2(PO4)3 was proposed, which takes into account the distinct crystallographic sites in the channels of the structure. More recently there has been a revision to the nomenclature of the group. The simplified structural formula for the alluaudite-type is now A(2)'A(1)M(1)M(2)2(TO4)3; the new nomenclature scheme has been adopted by the Commission on New Minerals, Nomenclature and Classification of the International Mineralogical Association (IMA-CNMNC), based on the contents of the M(1) and M(2) octahedral sites, and the results are reviewed here. Compounds belonging to the alluaudite structural family have been the focus of synthetic mineral studies for decades owing to the open-framework architecture and their unique physical properties. Improvements in synthesis methods have allowed researchers to substitute a wide range of elements into the alluaudite structure.

Structure Drawing at the Heart of Teaching Chemistry

Chemistry is all about structures. There are myriads of structural representations that are required for the students to become familiar with when learning chemistry. Structural formula, skeletal formula, Lewis and resonance structures, three-dimensional representations are just a few examples of the drawing styles that should be readily interpreted by a chemistry student. In order to gain the necessary knowledge to understand and manipulate chemical structures, students must extensively solve problems with structural illustrations and practice drawing chemical structures themselves. Here we present Zosimos, an online chemistry educational tool with comprehensive structure-drawing capabilities that allows chemistry teachers to create real chemistry quizzes, share them with their students and get immediate feedback on their learning progress. 5th grade students at Kantonsschule Zug have been learning chemistry with Zosimos since September 2019 and this article also shares insights on how to implement this learning tool in a real classroom setting.

A study of continuous vector representations for theorem proving

Applying machine learning to mathematical terms and formulas requires a suitable representation of formulas that is adequate for AI methods. In this paper, we develop an encoding that allows for logical properties to be preserved and is additionally reversible. This means that the tree shape of a formula including all symbols can be reconstructed from the dense vector representation. We do that by training two decoders: one that extracts the top symbol of the tree and one that extracts embedding vectors of subtrees. The syntactic and semantic logical properties that we aim to preserve include both structural formula properties, applicability of natural deduction steps and even more complex operations like unifiability. We propose datasets that can be used to train these syntactic and semantic properties. We evaluate the viability of the developed encoding across the proposed datasets as well as for the practical theorem proving problem of premise selection in the Mizar corpus.

On the structural formula of smectites: a review and new data on the influence of exchangeable cations

The understanding of the structural formula of smectite minerals is basic to predicting their physicochemical properties, which depend on the location of the cation substitutions within their 2:1 layer. This implies knowing the correct distribution and structural positions of the cations, which allows assigning the source of the layer charge of the tetrahedral or octahedral sheet, determining the total number of octahedral cations and, consequently, knowing the type of smectite. However, sometimes the structural formula obtained is not accurate. A key reason for the complexity of obtaining the correct structural formula is the presence of different exchangeable cations, especially Mg. Most smectites, to some extent, contain Mg2+ that can be on both octahedral and interlayer positions. This indeterminacy can lead to errors when constructing the structural formula. To estimate the correct position of the Mg2+ ions, that is their distribution over the octahedral and interlayer positions, it is necessary to substitute the interlayer Mg2+ and work with samples saturated with a known cation (homoionic samples). Seven smectites of the dioctahedral and trioctahedral types were homoionized with Ca2+, substituting the natural exchangeable cations. Several differences were found between the formulae obtained for the natural and Ca2+ homoionic samples. Both layer and interlayer charges increased, and the calculated numbers of octahedral cations in the homoionic samples were closer to four and six in the dioctahedral and trioctahedral smectites, respectively, with respect to the values calculated in the non-homoionic samples. This change was not limited to the octahedral sheet and interlayer, because the tetrahedral content also changed. For both dioctahedral and trioctahedral samples, the structural formulae improved considerably after homoionization of the samples, although higher accuracy was obtained the more magnesic and trioctahedral the smectites were. Additionally, the changes in the structural formulae sometimes resulted in changing the classification of the smectite.