scholarly journals Use of Ligand-based Iron Complexes for Phenol Degradation by Fenton Modified Process

2017 ◽  
Vol 57 (2) ◽  
Author(s):  
Iván A. Reyes ◽  
Francisco Patiño ◽  
Mizraím U. Flores ◽  
Jayanthi Narayanan ◽  
Hilda Calderón ◽  
...  
Keyword(s):  
Fenton Reaction ◽  
Phenol Degradation ◽  
Iron Complexes ◽  
Phenol Oxidation ◽  
Considerable Influence ◽  
Normal Probability Plot ◽  
Independent Variables ◽  
Probability Plot ◽  
Normal Probability ◽  
Two Factors

The efficiency of phenol degradation by the iron complexes ([Fe(TBMA)Cl<sub>3</sub>∙3H<sub>2</sub>O] and [Fe(terpy)Cl<sub>2</sub>]) is compared with that of the Fenton reaction. The results show that although the Fenton reaction efficiently oxidizes phenol at low pH’s, the Fenton modified reagents (iron complexes/H<sub>2</sub>O<sub>2</sub>) effectively oxidize phenol at neutral pH. Besides, the factorial designing study is performed by considering three independent variables: (i) [Fe] (<em>A</em>), (ii) pH (<em>B</em>), and (iii) [H<sub>2</sub>O<sub>2</sub>] (<em>C</em>). For the Fenton reaction, the normal probability plot reveals that two factors, such as concentration of Fe<sup>2+</sup> and interaction{[H<sub>2</sub>O<sub>2</sub>]∙pH} have considerable influence on the phenol oxidation; in the normal probability plot of the complexes, factors C (concentration of H<sub>2</sub>O<sub>2</sub>) and AC {[Fe]∙[H<sub>2</sub>O<sub>2</sub>]} have an effect on the oxidation of the phenol by [Fe(terpy)Cl<sub>2</sub>]/H<sub>2</sub>O<sub>2</sub>, while for [Fe(TBMA)Cl<sub>3</sub>∙3H<sub>2</sub>O], factors B and AC significantly influence the degradation. Of both iron complexes, [Fe(TBMA)Cl<sub>3</sub>∙3H<sub>2</sub>O]/H<sub>2</sub>O<sub>2</sub> is an excellent oxidant, showing a good response at pH 7.0.

Application of normal probability plot analysis to lutetium orthoborate factors and parameters

1971 ◽  
Vol 4 (4) ◽  
pp. 284-290 ◽  
Author(s):  
S. C. Abrahams ◽  
J. L. Bernstein ◽  
E. T. Keve
Keyword(s):  
Standard Deviation ◽  
Least Squares ◽  
Thermal Vibration ◽  
Normal Probability Plot ◽  
Lattice Constants ◽  
Probability Plot ◽  
Plot Analysis ◽  
Structure Factors ◽  
Normal Probability ◽  
Vibration Parameters

The methods of normal probability plot analysis have been applied to two nearly complete sets of structure factors (F meas) and the corresponding objectively assigned standard deviations (σF meas) obtained by diffractometer measurement with two different crystals of lutetium orthoborate. The least-squares derived positional and thermal vibration parameters are shown to be too small by a factor of 1.8, and the σF meas to be overestimated by a factor of 1.55. The two sets of F meas are found to contain a small but parallel bias. The lattice constants of rhombohedral calcite-type LuBO3 are measured as a H = 4.91538±0.00002 Å and cH = 16.21200±0.00003 Å at 298°K, with six formulas in the unit cell, space group R\overline 3c. The Lu–O distance in this six-coordinated Lu compound is 2.240±0.002 Å (corrected standard deviation). The B–O distance in the BO3 triangular groups is 1.370±0.005 Å. The characteristic Θ temperature is estimated as 446±19°K.

scholarly journals PENGARUH MODAL SENDIRI DAN MODAL PINJAMAN TERHADAP SISA HASIL USAHA (SHU) PADA KOPERASI UNIT DESA (KUD) BINA SEJAHTERA RENGAT BARAT KABUPATEN INDRAGIRI HULU

2019 ◽  
Vol 10 (3) ◽  
pp. 360-373
Author(s):  
Suharmiyati Suharmiyati
Keyword(s):  
Normal Probability Plot ◽  
Probability Plot ◽  
Normal Probability

Tujuan penelitian ini adalah untuk mengetahui Modal Sendiri dan Modal Pinjaman secara simultan berpengaruh signifikan terhadap Sisa Hasil usaha (SHU), untuk mengetahui Modal Sendirisecara parsial berpengaruh signifikan terhadap Sisa Hasil usaha (SHU), untuk mengetahui Modal Pinjaman secara parsial berpengaruh signifikan terhadap Sisa Hasil usaha (SHU), di Koperasi Unit Desa Bina Sejahtera Rengat Kabupaten Indragiri Hulu. Dalam penelitian ini pola pikir yang digunakan pola pikir induktif. Analisis data menggunakan metode kuantitatif yaitu dengan asumsi klasik ,regresi linear berganda, koefisien korelasi dan determiniasi, uji F, dan uji t. Teknik pengumpulan data menggunakan interview dan studi pustaka. Berdasarkan hasil penelitian dan pembahasan maka dapat diambil kesimpulan yaitu : Dari perhitungan kuantitatif yang diperoleh dengan menggunakan rumus persamaan regresi linear berganda Y = a + b1X1 + b2X2  diperoleh Y =  21,458 + 0,32 X1 – 0,01 X2, yakni nilai koefisien konstanta (a) sebesar 21,458 hal ini berarti apabila nilai Modal Sendiri dan Modal Pinjaman sama dengan nol atau tetap, maka tingkat atau besarnya Sisa Hasil usaha (SHU) sebesar 21,458. Koefisien korelasi linear berganda (R) yaitu 0,872, artinya hubungan yang  korelasi sangat kuat sekali antara Modal Sendiri dan Modal Pinjaman terhadap Sisa hasil Usaha (SHU) sebesar 0,872. Koefisien determinasi (R2) sebesar 0,761, artinya Sisa Hasil Usaha (SHU) dapat dijelaskan oleh variasi perubahan variabel independen Modal Sendiri dan Modal Pinjaman sebesar 76,1%, sedangkan sisanya 23,9% dijelaskan oleh variabel lain di luar penelitian. Berdasarkan hasil uji F diperoleh nilai Fhitung adalah 7,953 dengan tingkat signifikan  0,028. Sedangkan Ftabel pada taraf kepercayaan 95% (0,05) adalah 5,79. Pada kedua perhitungan Fhitung ˃Ftabel yaitu 7,953 ˃ 5,79. Hal ini berarti Ho ditolak dan Ha diterima, artinya secara simultan Modal Sendiri dan Modal Pinjamanberpengaruh signifikan terhadap Sisa Hasil Usaha (SHU). Berdasarkan hasil uji t diperoleh nilai thitung X1 ˃ ttabel = 2,635 < 2,44691 sehingga Ho ditolak dan Ha diterima, yang berarti variabel independen Modal Sendirisecara parsial berpengaruh signifikan terhadap Sisa Hasil Usaha (SHU). Selanjutnya nilai thitung X2 > ttabel = -1,288 > -2,44691 sehingga Ho ditolak dan Ha diterima, yang berarti variabel independen Modal Pinjaman secara parsial berpengaruh signifikan terhadap variabel Sisa Hasil Usaha (SHU). Berdasarkan hasil Uji Klasik diperoleh nilai Uji Multikolinieritas bahwa nilai tolerance dari kedua variabel independen lebih dari 0,1 yaitu VIF kurang dari 10 yaitu 1,328, maka dapat disimpulkan bahwa dalam model regresi tidak terjadi masalah multikolinieritas. Selanjutnya uji heteroskedastisitas diketahui bahwa titik-titik menyebar dengan pola yang tidak jelas diatas dan dibawah angka 0 pada sumbu Sisa Hasil Usaha (SHU) maka pada hasil ini tidak terjadi masalah heteroskedastisitas. Dan yang terakhir uji normalitas pada tampilan grafik histogram, didapatkan garis kurva normal, berarti data yang diteliti diatas berdistribusi normal. Demikian juga dari normal probability plot, menunjukan berdistribusi normal karena garis (titik-titik) mengikuti garis diagonal

Quantile Analysis: A Method for Characterizing Data Distributions

1988 ◽  
Vol 42 (8) ◽  
pp. 1512-1520 ◽  
Author(s):  
Robert A. Lodder ◽  
Gary M. Hieftje
Keyword(s):  
Probability Density ◽  
Statistical Methods ◽  
Probability Density Functions ◽  
Density Functions ◽  
Single Test ◽  
Test Statistic ◽  
Data Set ◽  
Normal Probability Plot ◽  
Probability Plot ◽  
Normal Probability

Analyzing distributions of data represents a common problem in chemistry. Quantile-quantile (QQ) plots provide a useful way to attack this problem. These graphs are often used in the form of the normal probability plot, to determine whether the residuals from a fitting process are randomly distributed and therefore whether an assumed model fits the data at hand. By comparing the integrals of two probability density functions in a single plot, QQ plotting methods are able to capture the location, scale, and skew of a data set. This procedure provides more information to the analyst than do classical statistical methods that rely on a single test statistic for distribution comparisons.

Isomorphism in monomeric 1:3 complexes of silver(I) salts with tri-p-tolylphosphine

2009 ◽  
Vol 65 (6) ◽  
pp. 699-706 ◽  
Author(s):  
Bernard Omondi ◽  
Gertruida J. S. Venter ◽  
Andreas Roodt ◽  
Reinout Meijboom
Keyword(s):  
Orthorhombic Space Group ◽  
Normal Probability Plot ◽  
Space Group ◽  
Probability Plot ◽  
Plot Analysis ◽  
Normal Probability

Reaction of silver(I) salts with three equivalents of tri-p-tolylphosphine in CH3CN resulted in a series of isomorphous complexes [AgX{P(4-MeC6H4)3}3] (X = Br, SCN, ClO4). These complexes all crystallize in the orthorhombic space group Pna21. The complexes with X = Br, SCN are distorted tetrahedral around the silver(I) atom, whereas the ClO4 − complex is distorted trigonal planar around the silver. The new complexes are compared with each other using r.m.s. overlay calculations as well as half-normal probability plot analysis and with the previously reported isomorphous chloride, bromide as well as the non-isomorphous iodide complexes.

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