Influence of Process Parameters on Synthesis of Biochar by Pyrolysis of Biomass: An Alternative Source of Energy

Organic matter derived from plants and animals are known as biomass. It has a great potential to be used as an alternate source of energy by employing thermochemical conversion techniques. Among the available techniques, pyrolysis is considered to be the most efficient technique used for the conversion of biomass-based waste into value-added solid, liquid and gaseous products through heating in an oxygen-limited environment. Biochar (solid fuel) is a carbonaceous material and has multiple applications in various fields such as soil health, climate stability, water resource, energy efficiency and conservation. The yield of biochar depends on organic constituents of biomass and the pyrolytic process parameters such as temperature, time, heating rate, purging gas, particle size, catalyst, flow rate, pressure and types of pyrolysis reactors. Suitable conditions for biochar production were observed to be slow pyrolysis, low carrier gas flow rate, acid-catalysed biomass or biomass mixed with some inorganic salts, low heating rate, large particle size, high pressure, longer residence time, low temperature, feedstocks with high lignin content and pyrolysis reactors with lower bed height. Thermal conversion of biomass could be a possible sustainable alternative to provide economically viable, clean and eco-friendly solid fuel

A hybrid flux balance analysis and machine learning pipeline elucidates the metabolic response of cyanobacteria to different growth conditions

Machine learning has recently emerged as a promising tool for inferring multi-omic relationships in biological systems. At the same time, genome-scale metabolic models (GSMMs) can be integrated with such multi-omic data to refine phenotypic predictions. In this work, we use a multi-omic machine learning pipeline to analyze a GSMM of Synechococcus sp. PCC 7002, a cyanobacterium with large potential to produce renewable biofuels. We use regularized flux balance analysis to observe flux response between conditions across photosynthesis and energy metabolism. We then incorporate principal-component analysis, k-means clustering, and LASSO regularization to reduce dimensionality and extract key cross-omic features. Our results suggest that combining metabolic modeling with machine learning elucidates mechanisms used by cyanobacteria to cope with fluctuations in light intensity and salinity that cannot be detected using transcriptomics alone. Furthermore, GSMMs introduce critical mechanistic details that improve the performance of omic-based machine learning methods

Fiber-optic Pressure Sensor For Time-of-flight Measurements In A Shock Wave

Fiber-optic sensors are widely employed to detect pressures and temperatures precisely. In particular, MEMS-based Ber-optic sensors are immune to electromagnetic interference but may have limitations at high temperatures as encountered in combustors. To ensure high-temperature survivability, such sensors may be bondedanodically. This project explains the development of a Ber-optic pressure sensor utilizing intensity based principle whereby a fused silica optical window was glued to the tungsten carbide enclosure. The development was estimated to determine high pressures of up to at least 3.5 MPa (507 psi). The sensor is designed to capture the pressure pulse and the time-of-flight (TOF) of a propagating detonation wave for implementation shock tubes. Time-of- flight is critically important in detonation studies as it relates directly to the detonation wave velocity. Generally, the TOF is obtained by discrete sensors separated by a distance of at least a few cm. Thus, the propagation velocity, is strictly the average over that distance, thereby introducing a certain uncertainty. In order to obtain a point measurement, the separation distance between the sensors should be kept as short as possible. Advances in MEMS and electro-optics have made it possible to devise such an integrated TOF sensor together with high-speed data acquisition

Hybrid technologies for remediation of recalcitrant industrial wastewater

In metal machining processes, the regulation of heat generation and lubrication at the contact point are achieved by application of a fluid referred to as metalworking fluid (MWF). This has the combined features of the cooling properties of water and lubricity of oil. MWFs inevitably become operationally exhausted with age and intensive use, which leads to compromised properties, thereby necessitating their safe disposal. Disposal of this waste through a biological route is an increasingly attractive option, since it is effective with relatively low energy demands when compared to current physical and chemical options. However, biological treatment is challenging since MWF are chemically complex, including the addition of toxic biocides which are added specifically to retard microbial deterioration whilst the fluids are operational. This makes bacterial treatment exceptionally challenging and has stimulated the search and need to assess technologies which complement biological treatment. In this study the remediation, specifically of the recalcitrant component of a semi-synthetic MWF, employing a novel hybrid treatment approach consisting of both bacteriological and chemical treatment, was investigated. Three chemical pre-treatment methods (Fenton’s oxidation, nano-zerovalent iron (nZVI) oxidation and ozonation) of the recalcitrant components followed by bacterial degradation were examined. The synergistic interaction of Fenton’s-biological oxidation and nZVI-biodegradation led to an overall COD reduction of 92% and 95.5% respectively, whereas pre-treatment with ozone reduced the total pollution load by 70% after a post-biological step. An enhancement in biodegradability was observed after each of the chemical treatments, thus facilitating the overall treatment process. The findings from this study established that the use of non-pathogenic microorganisms to remediate organic materials present in MWF wastewater is a favourable alternative to energy demanding physical and chemical treatment options. However, optimal performance of this biological process may require chemical enhancement, particularly for those components that are resistant to biological transformation

Successful <i style="">in situ</i> oil bioremediation programmes — Key parameters

495-501Naturally occurring microbial consortia have been utilized in a variety of bioremediation processes. One important characteristic of bioremediation is that it is carried out in non-sterile open environments, which contain a host of microorganisms. Successful in situ bioremediation strategy should be tailored in such a manner that due consideration be given to the various environmental constraints (salinity, nutrient availability, anaerobic degradation, bioavailability considerations) that affect a particular location

Identification, characterization, and lipid profiling of microalgae Scenedesmus sp. NC1, isolated from coal mine effluent with potential for biofuel production

An autoflocculating microalgal strain was isolated from coal mine effluent wastewater which was named as Scenedesmus sp. NC1 after morphological and molecularly characterization. Further analysis of internal transcribed spacer 2 (ITS2) and compensatory base changes (CBCs) showed it does not belong to the clade comprising Scenedesmus sensu stricto. In stationary phase of growth, Scenedesmus sp. NC1 exhibited excellent autoflocculation efficiency (> 88 %) within 150 min of setting. Temperature, pH, and inorganic metals exhibited minor influence on the autoflocculation activity of Scenedesmus sp. NC1. The fatty acid profiling of Scenedesmus sp.NC1 showed that palmitic acid (C16:0), oleic acid (C18:1), and stearic acid (18:0) accounted for more than 68 % of total fatty acids. Moreover, Scenedesmus sp. NC1 demonstrated significant bioflocculation potential over non-flocculating freshwater microalgae, Chlorella sp. NCQ and Micractinium sp. NCS2. Hence, Scenedesmus sp. NC1 could be effective for economical harvesting of other non-flocculating microalgae for productions of biodiesel and other metabolites