Researches

Rice straw is an inexpensive and easily accessible lignocellulosic resource which in comparison with other lignocellulosic materials has high content of silica. The presence of silica reduces enzymatic hydrolysis yield of straw and consequently, adversely affects ethanol production. In this study, silica removal from rice straw using various chemical substances at different temperatures and time intervals was investigated. Sodium carbonate, sodium hydroxide, sodium chloride, and sodium dodecyl sulfate were used to remove silica from rice straw.

Increasing demand for energy increases the importance of renewable resources to meet this great amount of demands. Among different biofuels, bioethanol has been taking the most attention. Various resources could be used to biologically produce ethanol, but lignocelluloses are of special interest because of having no conflict with food resources. Lignocellulosic materials considered as one of the best renewable resources for biofuel production, are cheap and available in all over the world. These materials are found in cell wall of plants.

In the recent years, because of availability, renewability, low density, high reinforcement properties, and environmental concerns, the use of cellulose nanofibers was increased. Extraction of cellulose nanofibrils (microfibrilated cellulose (MFC)) from plants cell wall has been done by different methods which almost all of these methods include a chemical purification of cellulosic fibers and a mechanical treatment for disintegration of cell wall. In this work, a chemi – mechanical method was developed and used to extract MFCs from rice straw.

Increasing demand for energy in addition to various environmental concerns intensify the significance of using renewable resources for energy production. Among different renewable resources, biomasses, especially lignocellulosic materials, are the most promising alternative for liquid biofuel production. Bioethanol should be considered as the most convenient biofuel to replace fossil fuels. Lignocellulosic materials, mostly include waste materials, are found in the cell wall of plants and composed of three major polymers: cellulose, hemicelluloses, and lignin.

Cellulose nanofibers were isolated from wheat straw by a chemical-mechanical treatment. Initially, wheat straw fibers were subjected to a chemical process to eliminate lignin, hemicelluloses, and pectin. After cutting, wheat straw fibers were soaked in An alkali solution to swell the cell walls to enable chemical molecules to penetrate through the crystalline region of cellulose and dewaxing. Then, hemicellulose and pectin removed from pulp in acid hydrolysis stage.  Soluble lignin removed in alkali treatment and klasson lignin removed in bleaching stage.

In the last century, production of petrochemical-based materials and their usage have caused many adverse effects such as greenhouse effects, environmental pollution, and dangerous diseases such as asthma, lung cancer, etc. On the other hand, wood-based materials have destroyed forests which has intensified these problems. In recent decades, international community concerns have developed a new generation of materials and products. Today, bio-based materials have been replaced by petrochemical-based materials in many applications.

This study reports on the fabrication of a novel single chamber microbial fuel cell (MFC) configuration. The single chamber MFC with annular configuration and spiral anode geometry, is suggested for future large-scale applications. There were two main objectives in this study. First, the stainless steel mesh anode with graphite coated as a porous surface for biofilm growing in annular single chamber MFC configuration were designed and its characteristics were investigated.

Microbial fuel cells are one of the newly emerged technologies in the field of energy recovery and treating wastewaters simultaneously which have attracted interest in recent years. In this study, MFC model based on the direct conduction of electrons in biofilm has been presented and validated by available experimental data from litrature. The presented model is able to predict the measured data with an acceptable accuracy.