Über die Adsorption in Lösungen

Comparative adsorptive performance of adsorbents developed from sugar industrial wastes for the removal of melanoidin pigment from molasses distillery spent wash

Adsorption is one of the most successful physicochemical approaches for removing heavy metal contaminants from polluted water. The use of residual biomass for the production of adsorbents has attracted a lot of attention due to its cheap price and environmentally friendly approach. The transformation of Sargassum—an invasive brown macroalga—into activated carbon (AC) via phosphoric acid thermochemical activation was explored in an effort to increase the value of Sargassum seaweed biomass. Several techniques (nitrogen adsorption, pHPZC, Boehm titration, FTIR and XPS) were used to characterize the physicochemical properties of the activated carbons. The SAC600 3/1 was predominantly microporous and mesoporous (39.6% and 60.4%, respectively) and revealed a high specific surface area (1695 m2·g−1). To serve as a comparison element, a commercial reference activated carbon with a large specific surface area (1900 m2·g−1) was also investigated. The influence of several parameters on the adsorption capacity of AC was studied: solution pH, solution temperature, contact time and Cr(VI) concentration. The best adsorption capacities were found at very acid (pH 2) solution pH and at lower temperatures. The adsorption kinetics of SAC600 3/1 fitted well a pseudo-second-order type 1 model and the adsorption isotherm was better described by a Jovanovic-Freundlich isotherm model. Molecular dynamics (MD) simulations confirmed the experimental results and determined that hydroxyl and carboxylate groups are the most influential functional groups in the adsorption process of chromium anions. MD simulations also showed that the addition of MgCl2 to the activated carbon surface before adsorption experiments, slightly increases the adsorption of HCrO4− and CrO42− anions. Finally, this theoretical study was experimentally validated obtaining an increase of 5.6% in chromium uptake.

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Adsorption of Hexavalent Chromium Using Activated Carbon Produced from Sargassum ssp.: Comparison between Lab Experiments and Molecular Dynamics Simulations

With the rapid population growth, the annual plastic waste generation is increasing. There is a dire need for reusing plastic waste. If plastic waste is not recycled it ends up in landfills; ocean garbage patches or is incinerated; which causes different environmental problems, and if pollution from incineration plants is controlled then the plant becomes so expensive that not all countries can afford it. The addition of plastic waste to the flexible pavement has become an attractive option because this improves flexible pavement performance and eliminates the environmental problem. Huge work is done on waste addition in the bituminous mix but this review paper focuses on research done on utilizing plastic wastes as a modifier in a bituminous mix of flexible pavement. 

A mini-review on the use of plastic waste as a modifier of the bituminous mix for flexible pavement

Insights into mass transfer mechanism and micro-interaction of melanoidin adsorption on polyethyleneimine-functionalised pomelo-peel-derived aerogel

Overwhelming increase in plastic waste since recent years became series ecological issue for both developed and developing countries. Compromising the large plastic waste potential in Ethiopia and poor pavement performance in the roads due to severe weather and high traffic loads, it is viewed to use this in-hand resource as asphalt modifier to urge sustainability, enhance the stability of asphalt mix and reduce the amount of bitumen used. The study aimed at investigating the effect of using waste LDPE plastic as a modifier of virgin bitumen. This study also tries to amplify the advantage of using wet blending method over dry. Four modified bitumen mixes prepared with 4, 6, 8 and 10% waste LDPE plastic content by the weight of optimum bitumen content (OBC) at different mixing temperatures (160, 170, and 180 °C) and different mixing times (1, 1.5 and 2 hours) to evaluate penetration point, softening point and ductility. 170 °C mixing temperature and 1.5 hour mixing time results, homogeneous mix between bitumen and waste LDPE plastic materials compared to other mixing temperatures and mixing times. Marshall Test Method was used to determine the optimum bitumen content and to evaluate the marshal properties of the plastic modified asphalt mix. The OBC of non-modified marshal sample was found to be 5.16% by weight of the total aggregate while the optimum waste LDPE modified bitumen content was found to be 6.5% by weight of the OBC. Asphalt mix modified with 6.5% of waste LDPE plastic content has 33.67% higher stability value compared to the non-modified asphalt mix.

Investigation and optimization of waste LDPE plastic as a modifier of asphalt mix for highway asphalt: Case of Ethiopian roads

Spent kaolin filter cake as an effective adsorbent for the removal of Hexavalent Chromium [Cr (VI)] from aqueous solution: Comparative study of wastewater treatment methods

Economical Adsorbent Developed from Sugarcane Bagasse for Zinc (II) Removal from Wastewater

This research work primarily focused on the automatic relation extraction between entities for Amharic text using supervised machine learning approach.The Walta Information Centre online archive resources were used to create the studys own corpus, which consisted of 2000 sentences and a reasonable quantity of 30,466 words or tokens. The proposed solution has four processes namely preprocessing, Text labeling, feature extraction and feature selection and Recognition. The tokenization and POS are used as preprocessing. After the text is tokenized and giving POS for each of tokens the next step is text labeling system. For text labeling mechanism BIO scheme is used. The tag features are selected for building the model. The Tag feature consists of name entity type and relation type. The name entity type features are represented by Location (LOC), Organization (ORG) and Person (PER) and the relation type features are identified every word which existed between two entities for instance between location-location relation type or location-organization relation type and all the corresponding entities that are appeared it. Vectorizations are done using DictVectorizer and word2features. Support vector machines and conditional random field machine learning are used to for recognizing the entity relation between Amharic texts. SVM with SGD achieved the weighted precision of 49%, recall 10% and f1-score 13% are scored. SVM with Multinomial Naive Bayes Classifier Algorithm achieve precision of 61%, recall 41% and f1-score 48%.SVM with Passive Aggressive classifier achieved weighted average precision of 55%, recall 19% and f1-score 27%. CRF algorithm achieved precision of 87%, recall 87% and f1-score 86%. The CRF model outperform compared with other SVM algorithms.

Melkamu Birlie Genet

Papers

Comparative adsorptive performance of adsorbents developed from sugar industrial wastes for the removal of melanoidin pigment from molasses distillery spent wash

Investigation and optimization of waste LDPE plastic as a modifier of asphalt mix for highway asphalt: Case of Ethiopian roads

Spent kaolin filter cake as an effective adsorbent for the removal of Hexavalent Chromium [Cr (VI)] from aqueous solution: Comparative study of wastewater treatment methods

Economical Adsorbent Developed from Sugarcane Bagasse for Zinc (II) Removal from Wastewater

Automatic relation extraction between entities for amharic text