scholarly journals STUDY OF THE SORPTION OF AMMONIUM CATIONS ON A FIBROUS CARBOXYLIC SORBENT

2021 ◽  
Vol 18 (38) ◽  
pp. 224-241
Author(s):  
Yuri Semenovich PEREGUDOV ◽  
Elena Mikhailovna GORBUNOVA ◽  
Behzod Aminovich OBIDOV ◽  
Ksenia Borisovna KIM ◽  
Sabuhi Ilich oglu NIFTALIEV
Keyword(s):  
Neural Networks ◽  
Mineral Fertilizer ◽  
Distribution Coefficients ◽  
Ion Concentration ◽  
Ammonium Ion ◽  
Coefficient Of Determination ◽  
Ammonium Ions ◽  
Sorption Data ◽  
Developed Surface ◽  
Degree Of Recovery

Background: Wastewater from the mineral fertilizer production, agribusiness containing ammonium ions causes significant harm to fish farming; therefore, it must be purified before discharge. Ion-exchange sorption is a promising method for isolating ammonium cations. The object of the study was a chemisorption fiber VION KN-1, which has developed surface and high sorption rate. Purpose: To study the sorption kinetics of ammonium cations from aqueous solutions on VION KN-1; to train an ANN to predict the degree of recovery of ammonium ions from wastewater using Statistica Neural Networks Version 13. Methods: The ammonium ion concentration in the solution was established by direct potentiometry. Sorption isotherms were constructed using the method of variable concentrations. To determine the limiting stage, the obtained kinetic dependencies were represented in the coordinates of the Boyd-Adamson equations for internal/external diffusion. Results and Discussion: During sorption from solutions with different ammonium nitrogen contents, the values of distribution coefficients (Kd) are at the level of 2.3ꞏ103 cm3/g, which significantly exceeds this parameter for granular ionites. Experimental sorption data were verified using Freundlich (R2 = 0.9224) and Langmuir (R2 = 0.9996) isotherms. The maximum degree of recovery (over 96 %) was achieved by passing a solution with a concentration of 11.3 mmol/dm3. Using an array of experimental data, the MLP-3-5-1 neural network was trained. The coefficient of determination R2 = 0.999420 obtained for the training sample characterizes high network performance. Conclusions: The Langmuir equation better describes the process of NH4+ sorption on a fibrous sorbent. It is reasonable to use VION KN-1 at the fine treatment stage. Ammonium ion desorption from the fiber was performed by acid solution. The resulting solutions of ammonium salts can be used as liquid fertilizers. The trained neural networks can be used to predict the degree of recovery of ammonium ions by sorbent VION KN-1.

In-Situ Leaching of South Texas Uranium Ores-Part 2: Oxidative Removal of Adsorbed Ammonium Ions With Sodium Hypochlorite

1983 ◽  
Vol 23 (02) ◽  
pp. 387-396 ◽  
Author(s):  
J.M. Paul ◽  
W.F. Johnson ◽  
A. Fletcher ◽  
P.B. Venuto
Keyword(s):  
Cation Exchange ◽  
Sodium Hypochlorite ◽  
Geographical Area ◽  
Ammonium Bicarbonate ◽  
South Texas ◽  
Ion Concentration ◽  
Ammonium Ion ◽  
Side Reactions ◽  
Ammonium Ions

Abstract This paper reports a laboratory study of the oxidative destruction by sodium hypochlorite (NaOCl) of ammonium ions adsorbed on relatively reduced south Texas uranium ore. Included are an assessment of reaction stoichiometry, determination of some major reaction pathways and side reactions, and identification of several pathways and side reactions, and identification of several intermediates. Adsorbed ammonium ions were completely removed by 0.5 % NaOCl, with the concentration of NH3 in the effluent falling to a very low value after 10 to 15 PV NaOCl oxidant. A small fraction (5 to 10%) of NaOCl was utilized in reacting with NH3. After the NH3 was nearly depleted, mono-, di-, and trichloramines, the expected intermediates in NaOCl oxidation of NH3, were observed. Chloramine decomposition studies showed that all three decomposed completely within 12 days. Since the ore was relatively highly reducing, the major pan of the NaOCl was, not unexpectedly, consumed in side reactions. Substantial quantities of sulfate, reflecting oxidation of sulfide minerals such as pyrite, were formed, large amounts of uranium were leached out, and substantial amounts of calcium and magnesium ions were also produced during the presaturation with NH4HCO3 preceding the oxidation stage. Introduction A leachate that has sometimes been used for in-situ leaching of uranium ores is a solution of ammonium bicarbonate (NH4HCO3) containing an oxidant-usually hydrogen peroxide (H2O2) or oxygen (O2). The ammonium ion (NH4+) introduced into the ore body upon injection of this leachate is exchanged for cations such as calcium (Ca+2 ) and sodium (Na+), which are associated with mineral species in the formation possessing available cation exchange sites. As the indigenous groundwaters reinvade the leached zone, the adsorption process is reversed with NH4+ ions being displaced from process is reversed with NH4+ ions being displaced from the cation exchange sites and returned to the ground-waters. In general, this latter process maintains the ammonia (NH3 (or NH4+ ion) concentration well above the baseline (pre-mining) value in groundwater for extended periods of time in waters produced from wells in or near the mined zone following cessation of leachate injection. Prior to abandonment of an in-situ leach-mining site by the operator, satisfactory restoration of groundwater quality must be demonstrated. Requirements for this demonstration vary with the geographical area. A summary of applicable regulations has been provided by Kasper et al. A review of the state of restoration demonstrations to Sept. 1979 has been given by Tiepel. Most of the in-situ leach operations in south Texas have been conducted in aquifers containing indigenous waters with TDS contents in the 700- to 3,000-ppm range. Ca+ 2, magnesium (Mg+2), and bicarbonate ion (HCO3 ) concentrations are high in these slightly alkaline waters. These equilibrium water compositions indicate that an appreciable fraction of the interlayer ion exchange sites of the smectite clays in the formation are occupied by Ca+2 or Mg+2 ions. SPEJ P. 387

scholarly journals Response surface methodology (RSM) and its application for optimization of ammonium ions removal from aqueous solutions by pumice as a natural and low cost adsorbent

2016 ◽  
Vol 42 (2) ◽  
pp. 33-43 ◽  
Author(s):  
Masoud Moradi ◽  
Mehdi Fazlzadehdavil ◽  
Meghdad Pirsaheb ◽  
Yadollah Mansouri ◽  
Touba Khosravi ◽  
...  
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Contact Time ◽  
Fourier Transforms ◽  
Low Cost ◽  
Chemical Properties ◽  
Ion Concentration ◽  
Ammonium Ion ◽  
Ammonium Ions ◽  
Mixing Rate

Abstract This research was conducted to study the adsorption of ammonium ions onto pumice as a natural and low-cost adsorbent. The physico-chemical properties of the pumice granular were characterized by X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). Modeling and optimization of a NH4+ sorption process was accomplished by varying four independent parameters (pumice dosage, initial ammonium ion concentration, mixing rate and contact time) using a central composite design (CCD) under response surface methodology (RSM). The optimum conditions for maximum removal of NH4+ (70.3%) were found to be 100 g, 20 mg/l, 300 rpm and 180 min, for pumice dosage, initial NH4+ ion concentration, mixing rate and contact time. It was found that the NH4+ adsorption on the pumice granular was dependent on adsorbent dosage and initial ammonium ion concentration. NH4+ was increased due to decrease the initial concentration of NH4 and increase the contact time, mixing rate and amount of adsorbent.

Water uptake and trans-potential in sunflower roots as influenced by ammonium ions

1980 ◽  
Vol 94 (1) ◽  
pp. 145-150 ◽  
Author(s):  
S. M. Ragab
Keyword(s):  
Water Uptake ◽  
Water Movement ◽  
External Medium ◽  
Xylem Sap ◽  
Ion Concentration ◽  
Ammonium Ion ◽  
Ammonium Ions ◽  
Root Cells ◽  
Uptake Inhibition ◽  
Root Potential

SummaryThe effect of ammonium ions on artificially imposed water flux and trans-root potential difference was studied in excised sunflower roots. Water movement through the root system decreased and the potential of the xylem sap became less negative with respect to the external medium as the ammonium ion concentration in the external medium increased. It is suggested that ammonium ions appeared to inhibit water uptake either wholly or partially through a general or specific blockage of root metabolism which reflected on the permeability of water through root membranes. The reduction in the trans-root potential was due to the effect of ammonium ions on the original trans-root potential of epidermal root cells. This may indicate that the site of water uptake inhibition lies within the root epidermis.

scholarly journals Use of natural bentonite clays in pond fish farming to create optimal concentrations of ammonium ions

2021 ◽  
Vol 262 ◽  
pp. 02021
Author(s):  
Timur Tlupov ◽  
Karina Bambetova ◽  
Kamaludin Magomedov ◽  
Ruslan Kumykov ◽  
Nikolay Khalko
Keyword(s):  
Sorption Capacity ◽  
Natural Waters ◽  
Bentonite Clay ◽  
Fish Farming ◽  
Ion Concentration ◽  
Ammonium Ion ◽  
Labor Costs ◽  
Ammonium Ions ◽  
Maximum Sorption Capacity ◽  
Bentonite Clays

The composition and some sorption properties of bentonite clays, the efficiency of natural waters treatment in pond fish farming from excess ammonium ions using the natural bentonite clay from the Gerpegezhskoye deposit have been studied. The maximum sorption capacity of bentonite clay of this material has been determined. It is found out that when a smaller amount of the sample is added to each liter of the standard solution (0.1 and 0.01 g), higher values of the sorption capacity are identified. To achieve the optimal degree of cleaning of ponds from excess ammonium ions and expediency in terms of reducing the material and labor costs to a minimum, the optimal amount of bentonite was calculated, the use of which would be sufficient to maintain the ammonium ion concentration. The conditions were chosen so that to ensure a decrease in the ammonium nitrogen concentration from 2-3 maximum allowable concentration (MAC) (5-7.5 mg/l) to 0.2-0.8 mg/l. It is shown that the sorption capacity is realized more efficiently when the bentonite weigh decreases to 0.01 g/L, provided that the ammonium ion content in the aqueous medium exceeds the MAC by 2-3 times.

scholarly journals Dynamics of mineral nitrogen compounds in the waters of the Dniester River

2021 ◽  
Author(s):  
Petru Ciorba ◽  
◽  
Elena Zubcov ◽  
Nina Bagrin ◽  
Liliana Teodorof ◽  
...  
Keyword(s):  
Total Nitrogen ◽  
Water Samples ◽  
Seasonal Dynamics ◽  
Organic Nitrogen ◽  
Mineral Nitrogen ◽  
Ion Concentration ◽  
Ammonium Ion ◽  
Nitrogen Compounds ◽  
Ammonium Ions ◽  
Nitrate Ions

This article presents the results of studying the content of mineral (ammonium ions, nitrites and nitrates) and organic nitrogen compounds in water samples collected from the Dniester river in 2020. In the study are examines the seasonal dynamics of the forms of mineral nitrogen, total nitrogen and the correlation between organic and mineral nitrogen. Limits of ammonium ion concentration in the Dniester river varied between 0.002 mg N/l and 0.93 mg N/l, nitrite ions 0.002 mg N/l and 0.05 mg N/l, nitrate ions 0.002 mg N/l - 1.36 mg N/l.

Prediction Models for Truck Accidents at Freeway Ramps in Washington State Using Regression and Artificial Intelligence Techniques

1998 ◽  
Vol 1635 (1) ◽  
pp. 30-36 ◽  
Author(s):  
Wael H. Awad ◽  
Bruce N. Janson
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Linear Regression ◽  
Prediction Models ◽  
Washington State ◽  
Training Data ◽  
Coefficient Of Determination ◽  
Training Process ◽  
Truck Accidents ◽  
High Level

Three different modeling approaches were applied to explain truck accidents at interchanges in Washington State during a 27-month period. Three models were developed for each ramp type including linear regression, neural networks, and a hybrid system using fuzzy logic and neural networks. The study showed that linear regression was able to predict accident frequencies that fell within one standard deviation from the overall mean of the dependent variable. However, the coefficient of determination was very low in all cases. The other two artificial intelligence (AI) approaches showed a high level of performance in identifying different patterns of accidents in the training data and presented a better fit when compared to the regression model. However, the ability of these AI models to predict test data that were not included in the training process showed unsatisfactory results.

scholarly journals Molecular recognition of organic ammonium ions in solution using synthetic receptors

2010 ◽  
Vol 6 ◽  
Author(s):  
Andreas Späth ◽  
Burkhard König
Keyword(s):  
Molecular Recognition ◽  
Hydrophobic Interactions ◽  
Covalent Bond ◽  
Ammonium Ion ◽  
Synthetic Receptors ◽  
Ammonium Ions ◽  
Wide Range ◽  
Covalent Bond Formation ◽  
Reversible Covalent ◽  
Ion Receptors

Ammonium ions are ubiquitous in chemistry and molecular biology. Considerable efforts have been undertaken to develop synthetic receptors for their selective molecular recognition. The type of host compounds for organic ammonium ion binding span a wide range from crown ethers to calixarenes to metal complexes. Typical intermolecular interactions are hydrogen bonds, electrostatic and cation–π interactions, hydrophobic interactions or reversible covalent bond formation. In this review we discuss the different classes of synthetic receptors for organic ammonium ion recognition and illustrate the scope and limitations of each class with selected examples from the recent literature. The molecular recognition of ammonium ions in amino acids is included and the enantioselective binding of chiral ammonium ions by synthetic receptors is also covered. In our conclusion we compare the strengths and weaknesses of the different types of ammonium ion receptors which may help to select the best approach for specific applications.

scholarly journals SATELLITE-DERIVED BATHYMETRY USING CONVOLUTIONAL NEURAL NETWORKS AND MULTISPECTRAL SENTINEL-2 IMAGES

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 201-207
Author(s):  
Y. A. Lumban-Gaol ◽  
K. A. Ohori ◽  
R. Y. Peters
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Window Size ◽  
Short Wave ◽  
Training Data ◽  
Coefficient Of Determination ◽  
Linear Transform ◽  
Band Combinations ◽  
Sentinel 2

Abstract. Satellite-Derived Bathymetry (SDB) has been used in many applications related to coastal management. SDB can efficiently fill data gaps obtained from traditional measurements with echo sounding. However, it still requires numerous training data, which is not available in many areas. Furthermore, the accuracy problem still arises considering the linear model could not address the non-relationship between reflectance and depth due to bottom variations and noise. Convolutional Neural Networks (CNN) offers the ability to capture the connection between neighbouring pixels and the non-linear relationship. These CNN characteristics make it compelling to be used for shallow water depth extraction. We investigate the accuracy of different architectures using different window sizes and band combinations. We use Sentinel-2 Level 2A images to provide reflectance values, and Lidar and Multi Beam Echo Sounder (MBES) datasets are used as depth references to train and test the model. A set of Sentinel-2 and in-situ depth subimage pairs are extracted to perform CNN training. The model is compared to the linear transform and applied to two other study areas. Resulting accuracy ranges from 1.3 m to 1.94 m, and the coefficient of determination reaches 0.94. The SDB model generated using a window size of 9x9 indicates compatibility with the reference depths, especially at areas deeper than 15 m. The addition of both short wave infrared bands to the four visible bands in training improves the overall accuracy of SDB. The implementation of the pre-trained model to other study areas provides similar results depending on the water conditions.

Orally Ingested Microencapsulated Urease and an Adsorbent, Zirconium Phosphate, to Remove Urea in Kidney Failure

1987 ◽  
Vol 10 (4) ◽  
pp. 269-274 ◽  
Author(s):  
E.A. Wolfe ◽  
T.M.S. Chang
Keyword(s):  
Renal Function ◽  
Zirconium Phosphate ◽  
Intestinal Tract ◽  
Ammonium Ion ◽  
Ammonium Ions ◽  
Dialysis Therapy ◽  
Dialysis Treatment ◽  
In Series ◽  
Removal System

Dialysis is the conventional treatment for chronic renal failure. It is cumbersome, expensive and time-consuming and thus alternate treatments have long been sought. A compact system consisting of haemoperfusion in series with ultrafiltration can nearly replace dialysis. A urea removal system is the only step required to complete this approach. The potential of combining a microencapsulated enzyme, urease, with an ammonium ion adsorbent, zirconium phosphate, to remove urea was examined in vitro. Urease converts urea to ammonium ions which are then adsorbed on-to zirconium phosphate. This combination would be most effective in the intestinal tract. The capacity of zirconium phosphate is probably not enough to effect the removal of enough urea to completely replace dialysis in patients with no renal function. However, this system could potentially 1) delay the onset of dialysis therapy in patients who still have some renal function, either alone or in combination with haemoperfusion-ultrafiltration, or 2) reduce dialysis treatment times.

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