Synthesis of microporous hollow spherical polystyrene carbons for the highly efficient CO2 adsorption and selectivity

Atakan Toprak,Baki Hazer 한국공업화학회 2023 Journal of Industrial and Engineering Chemistry Vol.127 No.-

Carbon materials with economic and high adsorption capacity attract much attention to reducing fossilfuel and industrial CO2 emissions. For this purpose, porous hollow spheres with high surface area andmicropore volume, morphologically resembling fullerene or soccer balls, were first produced from thesynthesized polystyrene by hydrothermal and conventional activation. The highest micropore volumeand BET surface area were found in PS-hydroHCl with 0.61 cm3/g and 1481 m2/g, respectively. TheCO2 adsorption capacities of PS-hydroHCl at 0 and 25 C were relatively high and were obtained as6.25 and 3.62 mmol/g, respectively. It was determined that all microporous spheres were influential inthe isosteric heat of adsorption range of 17–26 kJ/mol, that is, typical CO2 physical adsorption. It has beenfound that hydrothermally synthesized PS-hydro and PS-hydroHCl contain higher amounts of oxygenthan PS and PSHCl produced according to the conventional method. In addition, CO2/N2 selectivity at25 C, PS-hydroHCl, was three times more effective than PSHCl. As a result, it can be said that the synthesisof porous hollow microspheres is simple, and the starting material (polystyrene) is cheap and abundant;high CO2 adsorption and effective CO2/N2 selectivity will be promising for industrial applications.

The Effects of Intradetrusor BoNT-A Injections on Vesicoureteral Reflux in Children With Myelodysplasia

Tuncay Toprak,Yavuz Onur Danacioglu,Ayhan Verit 대한배뇨장애요실금학회 2019 International Neurourology Journal Vol.23 No.4

Purpose: We retrospectively evaluated the efficacy of botulinum neurotoxin A (BoNT-A) on vesicoureteral reflux (VUR), continence status, and urodynamic parameters in children with myelodysplasia who were not responsive to standard conservative therapy. Methods: The study included 31 children (13 boys, 18 girls) with a mean age of 9.2±2.3 years (range, 5–14 years) with myelodysplasia, retrospectively. All children were fully compatible with clean intermittent catheterization (CIC) and did not respond to the maximum tolerable anticholinergic dose. All children received an intradetrusor injection of 10 U/kg (maximum, 300 U) of BoNT-A into an infection-free bladder. All patients had VUR (22 unilateral, 9 bilateral) preoperatively. The grade of reflux was mild (grades 1, 2), intermediate (grade 3), and severe (grades 4, 5) in 25, 7, and 8 ureters, respectively. Results: The mean maximum bladder capacity increased from 152.9±76.9 mL to 243.7±103 mL (P<0.001), and the maximum detrusor pressure decreased from 57±29.4 cm H2O to 29.6±13.9 cm H2O (P<0.001). After BoNT-A treatment, 16 refluxing ureters (40%) completely resolved, 17 (42.5%) improved, 5 (12.5%) remained unchanged, and 2 (5%) became worse. Of the 31 children with urinary leakage between CICs, 22 (71%) became completely dry, 6 (19%) improved, and 3 (10%) experienced partial improvement. Conclusions: In children with myelodysplasia, we were able to increase bladder capacity, enhance continence, and prevent VUR by using intradetrusor BoNT-A injections. Although our results are promising, a larger group of long-term prospective studies are warranted to investigate this method of treatment.

A Novel and Integrated Approach to Dyeing Recycled Cotton and Chitosan Yarns Blended Fabrics with Innovative Nanobubble Technology

Tuba Toprak‑Cavdur 한국섬유공학회 2023 Fibers and polymers Vol.24 No.11

In order to reduce the environmental impacts caused by the increasing consumption to meet the textile needs of the world growing population, sustainable production in textiles has to be taken very seriously. Recycling and innovative technologies are some of the key factors for sustainable textile production. Cotton and chitosan are widely used biomaterials in textiles. Additionally, using nanobubbles is an innovative water technology that has an increasing usage potential in different areas recently. Herein, the dyeing behavior and environmental effects of recycled cotton and chitosan yarns blends in different proportions were investigated in the presence of nanobubble technology. Increasing amount of chitosan in the blend increased the band intensities in FTIR. When the chitosan ratio in the mixture was increased to 25% (in 1% o.w.f. dyeing), the color strength increased by 70%. In other words, the use of chitosan in the mixture could have provided similar color strengths with less dye consumption. Moreover, the negative effect of nanobubbles on color strength could have been compensated by the use of chitosan. The transmittance of dyeing baths containing nanobubbles was lower than those without nanobubbles because of its removing effect of unfixed/hydrolyzed dye molecules from fibers. The chemical oxygen demand of dyeing baths also improved by about 15% with nanobubbles. The summary of the study was that environment-friendly processes could be designed by dyeing blended yarns consisting of superior biopolymer chitosan and recycled cotton obtained by reusing the natural resource with nanobubbles.

Adding connective tissue manipulation to physiotherapy for chronic low back pain improves pain, mobility, and well-being : a randomized controlled trial

Seyda Toprak Celenay,Derya Ozer Kaya,Sevtap Gunay Ucurum 한국운동재활학회 2019 JER Vol.15 No.2

Dyeing Behavior of Enzyme and Chitosan-Modified Polyester and Estimation of Colorimetry Parameters Using Random Forests

Tuba Toprak‑Cavdur,Pervin Anis,Merve Bakir,Aslı Sebatli‑Saglam,Fatih Cavdur 한국섬유공학회 2023 Fibers and polymers Vol.24 No.1

Dyeing of the crystalline structure necessitates a process with a disperse dye either at high temperatures or with a carrier dueto its compact and non-ionic structure of polyester. In this study, in order to eliminate these limitations and develop moreenvironmentally friendly dyeing processes, the dyeability of polyester under different conditions with reactive, direct, andacid dyes after surface modifications with enzyme and chitosan was investigated. In addition to the corresponding physicalexperiments, CIELAB and color strength values were also estimated using random forests. The results of the physical experimentsshowed that the surface modifications conducted with enzyme and chitosan significantly increased the color depthsobtained in dyeing for reactive, direct, and acid dyes, especially at pH 4.5. This was explained by the potentially protonatedamine groups in acidic medium of chitosan could have attracted large amounts of anionic dye molecules with physical forces. The highest color depths were obtained from acid dyeing. Washing fastness of the pre-treated and dyed fabrics (except theacid-dyed fabrics) decreased with the shift of the bath pH values to the acidic region. In the next phase of the study, weimplemented random forests to estimate CIELAB and color strength values. We considered different random forest designsand trained each design ten times to observe the performance of the corresponding topology. The results of the computationalexperiments showed that the estimation performance of the random forests is quite satisfactory (with R-values greater than99%) and random forests could be used to estimate CIELAB and color strength values successfully.

Neuro-fuzzy modelling methods for relative density prediction of stainless steel 316L metal parts produced by additive manufacturing technique

Can Barış Toprak,C.U. Dogruer 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.1

Two machine learning (ML) methods, adaptive neuro fuzzy inference system (ANFIS) and artificial neural networks (ANN) have been implemented to predict the relative density (RD) of stainless steel 316L parts which are produced in additive manufacturing (AM) machines. The objective of this paper was to create ML models adapted for AM technique to verify the generalized model that predicts RD with the least error. Some important process parameters in AM such as scanning speed, laser power, hatch distance and layer thickness were picked as input and RD was set as output. Effects of the input parameters on RD were discussed and they were represented in the form of surface plots. It has been found that ANN method‘s convergence rate was better than that of ANFIS method, which confirms that usage of neural networks is a better choice than the usage of fuzzy reasoning in modelling AM technique.

A Critical Review of Machine Learning Methods Used in Metal Powder Bed Fusion Process to Predict Part Properties

Can Barıs Toprak,Can Ulas Dogruer 한국정밀공학회 2024 International Journal of Precision Engineering and Vol.25 No.2

Metal Powder Bed Fusion (M-PBF) technique is one of the popular branches of Additive Manufacturing (AM). One of the biggest challenges in M-PBF is understanding relationship between processing parameters and produced part’s mechanical properties. In this review paper, recent M-PBF and Machine Learning (ML) studies are comparatively investigated to guide the scientific community in selecting right ML algorithm to predict and optimize the mechanical properties of the parts produced by M-PBF technique. In this context, theoretical background of M-PBF techniques are discussed in terms of processing parameters and mechanical properties. Constraints on M-PBF processes are examined and possible solutions are studied. ML theory is briefly reviewed and various ML algorithms are investigated regarding their applicability and validity for M-PBF processes. Popular Design of Experiments (DOE) methods are reported. Future trends and suggestions on M-PBF techniques are discussed.

Modeling Dimensionless Longitudinal Dispersion Coefficient in Natural Streams using Artificial Intelligence Methods

Z. Fuat Toprak,Nizamettin Hamidi,Ozgur Kisi,Resit Gerger 대한토목학회 2014 KSCE JOURNAL OF CIVIL ENGINEERING Vol.18 No.2

Learning the Longitudinal Dispersion (LD) mechanism in natural channel is vitally important to be able to control water pollutionand to prevent different stratification in flow that crucial for water resources conservation for both human and aquatic life. Manyrelated studies can be found in the existing literature. However, almost all studies aim to investigate the mechanism of the LD innatural channels or to model dimensional LD coefficient. The main goal of this work is to develop three models based on differentartificial neural network techniques to predict dimensionless (not dimensional) LD coefficients in natural channels. Another goal ofthis study is to present a large and critical assessment on the existing studies made on both dimensional and dimensionless LD. Thedata sets obtained from the literature concerning more than 30 rivers at different times in the United States of America, include thedepth, the width, and the mean cross-sectional velocity of the flow, shear velocity, and dimensionless longitudinal dispersioncoefficient. The results have been compared with the data at hand, a fuzzy based model, and seven conventional equations proposedin literature by using statistical magnitudes, error modes, and contour map method. It is observed that the feed forward neuralnetwork yields the best reliable results.

Female Breast Cancer Mortality Rates in Turkey

Dogan, Nurhan,Toprak, Dilek Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.18

The main objective of this study was to analyze the mortality trends of female breast cancer in Turkey between the years 1987-2008. The rates per 100,000 age-standardized to the European standard population were assessed and time trends presented using joinpoint regression analysis. Average annual percent change (AAPC), anual percent change (APC) and 95% confidence interval (CI) was calculated. Nearly 23,000 breast cancer deaths occurred in Turkey during the period 1987-2008, with the average annual age-standardized mortality rate (ASR) being 11.9 per 100,000 women. In the last five years, significant increases were observed in all age groups, but there was no significant change over the age of 65. In this period, the biggest significant increase was in the 45-54 age group (AAPC=4.3, 95%CI=2.6 to 6.0).

Hydrogen sorption characteristics of Zonguldak region coal activated by physical and chemical methods

Turkan Kopac,Atakan Toprak 한국화학공학회 2009 Korean Journal of Chemical Engineering Vol.26 No.6

Hydrogen sorption characteristics of activated carbons (ACs) produced by physical and chemical activations from two coal mines (Kilimli and Armutcuk) in the Zonguldak region, Turkey were investigated by a volumetric technique at 77 K. H2 adsorption isotherms were obtained on the samples exposed to pyrolytic thermal treatments in a temperature range of 600-900℃ under N2 flow and chemical activation using different chemical agents such as KOH, NH4Cl, ZnCl2 from the two mines. Experimental hydrogen adsorption isotherm data at 77 K were used for the evaluation of the adsorption isotherm constants of the Brunauer-Emmett-Teller (BET) and the Langmuir models, and also the amount of hydrogen adsorbed on the various samples was evaluated by using the adsorption isotherm data. Higher hydrogen adsorption capacity values were obtained for all the heat and the chemically treated activated carbon samples from the Kilimli coal samples than Armutcuk. The amount of H2 adsorbed on the original Kilimli coal samples was 0.020 wt%, and it was increased to 0.89 wt% on the samples pyrolyzed at 800℃. The highest value of hydrogen adsorption obtained was 1.2 wt% for the samples treated with KOH+NH4Cl mixture at 750℃ followed by oxidation with ZnCl2. It was shown that chemical activations were much more effective than physical activations in increasing the surface area, pore volume and the hydrogen sorption capacities of the samples.