Amination of biochar surface from watermelon peel for toxic chromium removal enhancement

Watermelon peel residues were used to produce a new biochar by dehydration method. The new biochar has undergone two methods of chemical modification and the effect of this chemical modification on its ability to adsorb Cr(VI) ions from aqueous solution has been investigated. Three biochars, Melon-B, Melon-BO-NH_2 and Melon-BO-TETA, were made from watermelon peel via dehydration with 50% sulfuric acid to give Melon-B followed by oxidation with ozone and amination using ammonium hydroxide to give Melon-BO-NH_2 or Triethylenetetramine(TETA) to give Melon-BO-TETA. The prepared biochars were characterized by BET, BJH,SEM, FT-IR, TGA, DSC and EDAX analyses. The highest removal percentage of Cr(VI) ions was 69% for Melon-B,98% for Melon-BO-NH_2 and 99% for Melon-BO-TETA biochars of 100 mg·L~(-1) Cr(VI) ions initial concentration and 1.0 g·L~(-1) adsorbents dose. The unmodified biochar(Melon-B) and modified biochars(Melon-BO-NH_2 and Melon-BO-TETA) had maximum adsorption capacities(Qm) of 72.46, 123.46, and 333.33 mg·g~(-1), respectively.The amination of biochar reduced the pore size of modified biochar, whereas the surface area was enhanced.The obtained data of isotherm models were tested using different error function equations. The Freundlich,Tempkin and Langmuir isotherm models were best fitted to the experimental data of Melon-B, Melon-BO-NH_2 and Melon-BO-TETA, respectively. The adsorption rate was primarily controlled by pseudo-second–order rate model. Conclusively, the functional groups interactions are important for adsorption mechanisms and expected to control the adsorption process. The adsorption for the Melon-B, Melon-BO-NH_2 and Melon-BO-TETA could be explained for acid–base interaction and hydrogen bonding interaction.     

Statistical Optimization for Production of Light Olefins in a Fluidized‐Bed Reactor

The methanol‐to‐olefins reaction (MTO) was studied in a small‐scale fluidized‐bed reactor over synthesized silicoaluminophosphate (SAPO‐34) catalysts. Mesoporous nanocrystalline SAPO‐34 molecular sieves were synthesized hydrothermally by ultrasonic and microwave‐assisted aging processes in the presence of hexadecyltrimethylammonium bromide (CTAB) and tetradecyldimethyl(3‐trimethoxysilylpropyl)ammonium chloride (TPOAC) as surfactant agents. The Box‐Behnken experimental design method was applied to determine the optimum operating parameters of this process conducted in the fluidized‐bed reactor. The optimum conditions in terms of reaction temperature, ratio of inlet gas velocity to minimum fluidizing velocity, and MeOH weight fraction were evaluated.     

Calf massager: Intervention for body muscle discomfort during prolonged standing

Many occupations require workers to stand for long periods of time without proper interventions, which causes discomfort in the back and lower limbs. Therefore, this study aims to assess the effectiveness in alleviating body muscle discomfort during prolonged standing through the use of a calf massager. This study was conducted among male workers at a manufacturer with production line workers and the list was obtained from the HR Department and simple random sampling was done by number categorization. A total of 100 respondents (50 respondents for both the control and the experimental groups) participated in this study. The experiment took place in a room with a similar setup for the production line. Each respondent was requested to perform the simulated task for 2 hr. For the experimental group, the calf massager was turned on every 15 min. At every 15‐min interval after turning on the calf massager, respondents from both groups were required to evaluate their discomfort level on a Borg's scale CR‐10 questionnaire. The results showed that the level of body discomfort among respondents in the experimental group reduced (20–30%) compared with that of the control group. Multivariate analysis results revealed that the discomfort rating for the lower back, knees, thighs, calves, and feet was significantly lower (p < .05) among the experimental group compared with the control group. For lower body parts, the lower back region was statistically significant (p < .05) at the 90th, 105th, and 120th min; the thigh region was statistically significant (p < .05) at the 120th min; the knee region was statistically significant (p < .05) at the 105th and 120th min; the calf region was statistically significant (p < .05) at all minute intervals except the 15th and 45th min, while the feet region, was statistically significant at the 105th and 120th min. Therefore, this study indicates that calf massage treatment is capable of reducing body muscle discomfort during prolonged standing and highlights the significance of calf massage.     

Deep Learning Based Process Analytics Model for Predicting Type 2 Diabetes Mellitus

Process analytics is one of the popular research domains that advanced in the recent years. Process analytics encompasses identification, monitoring, and improvement of the processes through knowledge extraction from historical data. The evolution of Artificial Intelligence (AI)-enabled Electronic Health Records (EHRs) revolutionized the medical practice. Type 2 Diabetes Mellitus (T2DM) is a syndrome characterized by the lack of insulin secretion. If not diagnosed and managed at early stages, it may produce severe outcomes and at times, death too. Chronic Kidney Disease (CKD) and Coronary Heart Disease (CHD) are the most common, long-term and life-threatening diseases caused by T2DM. Therefore, it becomes inevitable to predict the risks of CKD and CHD in T2DM patients. The current research article presents automated Deep Learning (DL)-based Deep Neural Network (DNN) with Adagrad Optimization Algorithm i.e., DNN-AGOA model to predict CKD and CHD risks in T2DM patients. The paper proposes a risk prediction model for T2DM patients who may develop CKD or CHD. This model helps in alarming both T2DM patients and clinicians in advance. At first, the proposed DNN-AGOA model performs data preprocessing to improve the quality of data and make it compatible for further processing. Besides, a Deep Neural Network (DNN) is employed for feature extraction, after which sigmoid function is used for classification. Further, Adagrad optimizer is applied to improve the performance of DNN model. For experimental validation, benchmark medical datasets were used and the results were validated under several dimensions. The proposed model achieved a maximum precision of 93.99%, recall of 94.63%, specificity of 73.34%, accuracy of 92.58%, and F-score of 94.22%. The results attained through experimentation established that the proposed DNN-AGOA model has good prediction capability over other methods.     

Fabrication of core–shell nanocomposites with enhanced photocatalytic efficacy

The current study establishes the unprecedented involvement in the evolution and production of novel core–shell nanocomposites composed of nanosized titanium dioxide and aniline‐o‐phenylenediamine copolymer. TiO₂@copoly(aniline and o‐phenylenediamine) (TiO₂@PANI‐o‐PDA) core–shell nanocomposites were chemically synthesized in a molar ratio of 5:1 of the particular monomers and several weights of nano‐TiO₂ via oxidative copolymerization. The construction of the TiO₂@PANI‐o‐PDA core–shell nanocomposites was ascertained from Fourier transform IR spectroscopy, UV–visible spectroscopy and XRD. A reasonable thermal behavior for the original copolymer and the TiO₂@PANI‐o‐PDA core–shell nanocomposites was investigated. The bare PANI‐o‐PDA copolymer was thermally less stable than the TiO₂@PANI‐o‐PDA nanocomposites. The core–shell feature of the nanocomposites was found to have core and shell sizes of 17 nm and 19–26 nm, respectively. In addition, it was found that the addition of a high ratio of TiO₂ nanoparticles increases the electrical conductivity and consequently lowers the electrical resistivity of the TiO₂@PANI‐o‐PDA core–shell nanocomposites. The hybrid photocatalysts exhibit a dramatic photocatalytic efficacy of methylene blue degradation under solar light irradiation. A plausible interpretation of the photocatalytic degradation results of methylene blue is also demonstrated. Our setup introduces a facile, inexpensive, unique and efficient technique for developing new core–shell nanomaterials with various required functionalities and colloidal stabilities. © 2018 Society of Chemical Industry