Determining co-combustion characteristics,kinetics and synergy behaviors of raw and torrefied forms of two distinct types of biomass and their blends with lignite

Journal of Thermal Analysis and Calorimetry - In this study, the combustion characteristics and kinetics of various mixtures of both raw and torrefied rose pulp and red pine sawdust with each other...     

A vibrational spectroscopic study of the adsorption of 4,4′-bipyridyl by sepiolite and smectite group clay minerals from Anatolia (Turkey)

The adsorption of 4,4-bipyridyl by natural sepiolite and smectite group clay minerals (bentonite, hectorite and saponite) from Anatolia (Turkey) has been studied using vibrational spectroscopy. Investigation of Fourier-transform infrared and Fourier-transform Raman spectra of adsorbed 4,4-bipyridyl indicate the presence of chemisorbed species. However, any evidence for the generation of anionic species on the surface of the phyllosilicates has not been detected. It is proposed that the adsorbed bipyridyl molecules on sepiolite are centrosymmetric and H-bonded to the surface hydroxyls through both the nitrogen lone pairs as bidentate ligands. The adsorbed bipyridyl molecules on the smectite group clays are coordinated to exchangeable cations both directly and also indirectly through water as monodentate ligands. XRD patterns of the clays studied are also recorded.     

Determination of uranium and thorium in Eskişehir-Beylikahir ore samples by delayed neutron counting technique

The Eskiehir-Beylikahir district has the largest and richest thorium and rare earth elements deposits in Turkey. The uranium and thorium concentrations of samples taken from four different parts of this area have been determined by the delayed neutron counting technique. The results are compared with those of previous analyses by other techniques and found to be in good agreement.     

Solid-state vibrational spectroscopy: Part VI. An infrared and raman spectroscopic study of transition metal(II)4-methylpyridine complexes

Infrared (4000–200 cm^?1) and Raman (3500–300 cm^?1 ) spectra are reported for metal(II) halide and thiocyanate 4-methylpyridine complexes of the following stoichiometries: (MX₂(4-Mepy)₂) {M = Mn, Co, Cu or Zn, X = Cl or Br; M = Mn, Ni or Zn, X = NCS}; (MX₂(4-Mepy)₄) {M = Mn, Fe, Co or Ni, X = Cl or Br; M = Mn, Fe, Co, W or Cu, X = NCS}. For a given series of isomorphous complexes there is a correlation between the sum of the differences between the liquid and ligand values of the ν₁, ν₂, ν₃, ν₄, ν₅, ν₆, ν₇, ν₈, ν₉, ν₁₀, ν₁₂, ν₁₃ and ν₁₄ modes of 4-methylpyridine and the strength of the metal-nitrogen bond. Comparison of the shift values of pyridine and 4-methylpyridine complexes supports the suggestion that, unlike the situation in the pyridine complexes, back-donation from the metal to the ligand is unimportant in the 4-methylpyridine complexes.     

Vibrational spectroscopic studies of three dimensional host lattices formed by pyrazine bridges between tetracyanonickelate layers

Three dimensional host lattices have been developed by forming bridges with bidentate pyrazine molecules between adjacent tetracyanonickelate polymeric layers of Ni(II) or Cd(II). The Fourier-transform IR and Raman spectra (4000-200 cm^–1) of the compounds with the general formula M(pyz)Ni(CN)₄, (where M = Ni or Cd) are reported. These host lattices can include benzene molecules but it is found that aniline molecules cannot be included in these structures. They, however, form complexes with the formula M(an)₂Ni(CN)₄, by replacing pyrazine ligands. A monodentate pyrazine complex of Cd(II) with the formula Cd(pyz)₂Ni(CN)₄ has also been prepared.     

Investigation of metal activation of a partially purified polyphenol oxidase enzyme electrode

Biosensors can be developed using different biological materials and immobilization technologies. Enzymes are generally used in biosensor construction, and some enzymes need metal ions or small organic molecules as a cofactor for their activation. Polyphenol oxidases can be activated by several metal ions such as Cu²⁺, Mg²⁺, Zn²⁺, Mn²⁺, and Ni²⁺. In this study, a new measurement method has been developed that is based on the metal ion activation of the polyphenol oxidase enzyme used in the biosensor preparation, especially to determine the concentration of Mg²⁺ ions. Polyphenol oxidase (PPO) (EC 1.10.3.1) was partially purified from potato (Solanum tuberosum) by using (NH₄)₂SO₄ precipitation, dialysis, and lyophylization processes. As a result of this processes, approximately 30-fold purification was achieved for PPO. For construction of the biosensor, the enzyme was immobilized on the dissolved oxygen probe membrane using gelatin and glutaraldehyde (2.5%). Using the biosensor, we obtained responses for catechol in the absence and presence of Mg²⁺ ions. Differences between the biosensor responses were related to the concentration of Mg²⁺ ions. The biosensor response depends linearly on concentration of Mg²⁺ ions between 0.05 and 7.5?mM. In the optimization studies, phosphate buffer (pH 7.0, 50?mM) and 35°C were determined to be the optimum conditions. This project will be a novel biosensor study and it might bring a new term, ‘activation based biosensor’ into the biosensor area.     

Artificial intelligence–based models for the qualitative and quantitative prediction of a phytochemical compound using HPLC method

Isoquercitrin is a flavonoid chemical compound that can be extracted from different plant species such as Mangifera indica (mango), Rheum nobile , Annona squamosal , Camellia sinensis (tea), and coriander ( Coriandrum sativum L.). It possesses various biological activities such as the prevention of thromboembolism and has anticancer, antiinflammatory, and antifatigue activities. Therefore, there is a critical need to elucidate and predict the qualitative and quantitative properties of this phytochemical compound using the high performance liquid chromatography (HPLC) technique. In this paper, three different nonlinear models including artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and support vector machine (SVM),in addition to a classical linear model [multilinear regression analysis (MLR)], were used for the prediction of the retention time (tR) and peak area (PA) for isoquercitrin using HPLC. The simulation uses concentration of the standard, composition of the mobile phases (MP-A and MP-B), and pH as the corresponding input variables. The performance efficiency of the models was evaluated using relative mean square error (RMSE), mean square error (MSE), determination coefficient (DC), and correlation coefficient (CC). The obtained results demonstrated that all four models are capable of predicting the qualitative and quantitative properties of the bioactive compound. A predictive comparison of the models showed that M3 had the highest prediction accuracy among the three models. Further evaluation of the results showed that ANFIS–M3 outperformed the other models and serves as the best model for the prediction of PA. On the other hand, ANN–M3proved its merit and emerged as the best model for tR simulation. The overall predictive accuracy of the best models showed them to be reliable tools for both qualitative and quantitative determination.