Fahreddin Sadikoglu

Analysis of quantum-mechanical states of the ring-shaped Mie-type diatomic molecular model via the Fisher's information

Recently, the information theory of quantum-mechanical systems has aroused the interest of many theoretical physicists. This is due to the fact that it provides a deeper insight into the internal structure of the system. Also, it is the strongest support of the modern quantum computation and information, which is a basic theory for numerous technological developments. This study reports the solution of Schrodinger equation with the ring-shaped Mie-type potential. The rotational-vibrational spectroscopic study of some few selected diatomic molecules are given. The probability distribution density of the system which gives the probability density for observing the electron in the state characterized by the quantum numbers (n, l, m) in the ring-shaped Mie-type potential is obtained. Finally, the analysis for this distribution via a complementary information measures of a probability distribution known as the Fishers information have been presented.

Separation of carbon dioxide and nitrogen gases through modified boron nitride nanosheets as a membrane: insights from molecular dynamics simulations

Boron nitride nanosheets (BNNSs) can be a suitable membrane for gas separation with high permeability and selectivity. Molecular dynamics (MD) simulations were performed to investigate the CO2/N2 molecules separation using modified BNNSs. The simulated systems were comprised of modified BNNSs, CO2 and N2 molecules. A series of BNNSs with different pores as the separation membrane of CO2/N2 was designed. The selectivity and permeability of these molecules can be controlled by drilling various pores with different sizes and functionalized factors in the edge of the pores. The permeation mechanisms of the carbon dioxide and nitrogen molecules through the BNNS pores were different. Non-functionalized pores (pores 1 and 2) provided a high permeation rate and moderate selectivity for N2 over CO2 based on a simple size sieving mechanism. Modifying the pores by attaching functional groups to the boron and nitrogen atoms at the edge of the pores (pores 3 and 4) leads to very different outcomes. Using hydroxyl groups and hydrogen atoms leads to a substantial increase in the selectivity for N2 over CO2 and using fluoride atoms actually inverts the selectivity, which is strongly in favour of CO2. When the pore size is further increased, selective separation of molecules does not happen and both molecules propagate through the pores. Due to the interactions between the molecules and membrane pores, the energy barrier for the two molecules in various pores was different. As a consequence, with a low energy barrier more gas molecules permeated the pore. If the energy barrier difference between the two types of molecules is high, a complete separation occurs. The results show that the separation of molecules using the BNNSs was dependent on the pore diameter of the BNNS and the functionalized group used in the edge of the pore. The present study is valuable for designing novel nanostructure membranes for gas separation.

Application of different clustering approaches to hydroclimatological catchment regionalization in mountainous regions, a case study in Utah State

With respect to the different hydrological responses of catchments, even the adjacent ones, in mountainous regions, there are a great number of motivations for classifying them into homogeneous clusters. These motivations include prediction in ungauged basins (PUB), model parameterization, understanding the potential impact of environmental changes, transferring information from gauged catchments to the ungauged ones. The present study investigated the similarity of catchments through the hydro-climatological pure time-series of a 14-year period from 2001 to 2015. Data sets encompass more than 13,000 month-station streamflow, rainfall, and temperature data obtained from 27 catchments in Utah State as one of the eight mountainous states of the USA. The identification, analysis, and interpretation of homogeneous catchments were investigated by applying the four approaches of clustering, K-means, Ward, and SOM (Self-Organized Map) and a newly proposed Wavelet-Entropy-based (WE-SOM) clustering method. By using two clustering evaluation criteria, 3, 5, and 6 clusters were determined as the best numbers of clusters, depending on the method employed, where each cluster represents different hydro-climatological behaviors. Despite the absence of geographic characteristics in input data matrix, the results indicated a regionalization in agreement with topographic characteristics. Considering the dependency of the hydrological behavior of catchments on the physiographic field aspects and characteristics, WE-SOM method demonstrated a more acceptable performance, compared to the other three conventional clustering methods, by providing more clusters. WE-SOM appears to be a promising approach in catchment clustering. It preserves the topological structure of data which can, as a result, be proofed in a greater number of clusters by dividing data into higher numbers of distinct clusters with similar altitudes of catchments in each cluster. The results showed the aptitude of wavelets to quantify the time-based variability of temperature, rainfall and streamflow, in the way contributing to the regionalization of diverse catchments.

Experimental and AI-based numerical modeling of contaminant transport in porous media

This study developed a new hybrid artificial intelligence (AI)-meshless approach for modeling contaminant transport in porous media. The key innovation of the proposed approach is that both black box and physically-based models are combined for modeling contaminant transport. The effectiveness of the approach was evaluated using experimental and real world data. Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were calibrated to predict temporal contaminant concentrations (CCs), and the effect of noisy and de-noised data on the model performance was evaluated. Then, considering the predicted CCs at test points (TPs, in experimental study) and piezometers (in Myandoab plain) as interior conditions, the multiquadric radial basis function (MQ-RBF), as a meshless approach which solves partial differential equation (PDE) of contaminant transport in porous media, was employed to estimate the CC values at any point within the study area where there was no TP or piezometer. Optimal values of the dispersion coefficient in the advection-dispersion PDE and shape coefficient of MQ-RBF were determined using the imperialist competitive algorithm. In temporal contaminant transport modeling, de-noised data enhanced the performance of ANN and ANFIS methods in terms of the determination coefficient, up to 6 and 5%, respectively, in the experimental study and up to 39 and 18%, respectively, in the field study. Results showed that the efficiency of ANFIS-meshless model was more than ANN-meshless model up to 2 and 13% in the experimental and field studies, respectively.