Investigation of Chemical and Microbial Leaching of Iron ore in Sulphuric acid

Investigations on the chemical and microbial leaching of a Nigerian Iron-ore in sulphuric acid have been carried out. The influence of physico-chemical parameters such as acid concentration, temperature, particle size and stirring speed on the chemical dissolution of the ore was investigated. The dissolution rates are significantly influenced by the temperature and acid concentration while the increase of percentage dissolved with stirring speed and particle size was very moderate. The rate of the reaction based on reaction-controlled process was found to conform with the shrinking core model: 1-(1-\u3b1)1/3sup> = kt. With 12M H2sub>SO4sub> and at a temperature of 800C with a stirring speed of 360rpm and particle size 0.04-0.05mm, about 76.80% of iron-ore was dissolved within 120min. The activation energy of 38.29kJ/mole was calculated for the process. The reaction is first order with respect to H+ ion concentration. An attempt to dissolve the ore via microbial action of thiobacillus ferroxidans was not successful. This has been attributed probably to very low sulphur content of the mineral

Mother Tongue and Learning Environment as Students’ Predictors of Academic Achievement in Reading Comprehension

The study examined mother tongue and learning environment as students’ predictors of academic achievement in reading comprehension. This study adopted an ex-post facto design. The population consists of all senior secondary school students in Ijebu-North and Ijebu-Ode Local Government Area of Ogun State. A multi-stage random sampling technique was employed in selecting the sample. Four (4) senior secondary schools were randomly selected from each of the Local Government Area, making a total number of eight (8) senior secondary schools. Stratified random sampling technique was adopted in selecting 50 students from each of the selected senior secondary schools, 25 students each represent the gender totaling 400 students selected for this study. The instruments used for this study were two instruments, a questionnaire and an achievement test on reading comprehension. Kurder-Richardson 21 formula was used to obtain the inter-item reliability coefficient of 0.72 and items on achievement test on reading comprehension was extracted from a past questions of Ogun state unified examinations on English Language. The data analysis involved multiple regressions Analysis. The results were tested at 0.05 level of significance. Based on the findings, it was deduced that there is no significant composite influence of mother tongue and learning environment on students’ achievement in English Language. There is no significant relative influence of mother tongue on students’ achievement in reading comprehension. Part of the recommendations made was that teachers should be encouraged in using mother tongues in teaching. Teachers should cultivate a positive perception towards the use of English in school

Flexible operation of coal fired power plant integrated with post combustion CO2 capture using model predictive control

The growing demand for CO2 capture from coal-fired power plant (CFPP) has increased the need to improve the dynamic operability of the integrated power generation-CO2 capture plant. Nevertheless, high-level operation of the entire system is difficult to achieve due to the strong interactions between the CFPP and post combustion CO2 capture (PCC) unit. In addition, the control tasks of power generation and CO2 removal are in conflict, since the operation of both processes requires consuming large amount of steam. For these reasons, this paper develops a model for the integrated CFPP-PCC process and analyzes the dynamic relationships for the key variables within the integrated system. Based on the investigation, a centralized model predictive controller is developed to unify the power generation and PCC processes together, involving the key variables of the two systems and the interactions between them. Three operating modes are then studied for the predictive control system with different focuses on the overall system operation; power generation demand tracking and satisfying the CO2 capture requirement. The predictive controller can achieve a flexible operation of the integrated CFPP- PCC system and fully exert its functions in power generation and CO2 reduction

Nonlinear dynamic analysis and control design of a solvent-based post-combustion CO2 capture process

A flexible operation of the solvent-based post-combustion CO2capture (PCC) process is of great importance to make the technology widely used in the power industry. However, in case of a wide range of operation, the presence of process nonlinearity may degrade the performance of the pre-designed linear controller. This paper gives a comprehensive analysis of the dynamic behavior and nonlinearity distribution of the PCC process. Three cases are taken into account during the investigation: 1) capture rate change; 2) flue gas flowrate change; and 3) re-boiler temperature change. The investigations show that the CO2capture process does have strong nonlinearity; however, by selecting a suitable control target and operating range, a single linear controller is possible to control the capture system within this range. Based on the analysis results, a linear model predictive controller is designed for the CO2capture process. Simulations of the designed controller on an MEA based PCC plant demonstrate the effectiveness of the proposed control approach

Humoral immunological kinetics of severe acute respiratory syndrome coronavirus 2 infection and diagnostic performance of serological assays for coronavirus disease 2019: an analysis of global reports

As the coronavirus disease 2019 (COVID-19) pandemic continues to rise and second waves are reported in some countries, serological test kits and strips are being considered to scale up an adequate laboratory response. This study provides an update on the kinetics of humoral immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and performance characteristics of serological protocols (lateral flow assay [LFA], chemiluminescence immunoassay [CLIA] and ELISA) used for evaluations of recent and past SARS-CoV-2 infection. A thorough and comprehensive review of suitable and eligible full-text articles was performed on PubMed, Scopus, Web of Science, Wordometer and medRxiv from 10 January to 16 July 2020. These articles were searched using the Medical Subject Headings terms 'COVID-19', 'Serological assay', 'Laboratory Diagnosis', 'Performance characteristics', 'POCT', 'LFA', 'CLIA', 'ELISA' and 'SARS-CoV-2'. Data from original research articles on SARS-CoV-2 antibody detection >= second day postinfection were included in this study. In total, there were 7938 published articles on humoral immune response and laboratory diagnosis of COVID-19. Of these, 74 were included in this study. The detection, peak and decline period of blood anti-SARS-CoV-2 IgM, IgG and total antibodies for point-of-care testing (POCT), ELISA and CLIA vary widely. The most promising of these assays for POCT detected anti-SARS-CoV-2 at day 3 postinfection and peaked on the 15th day; ELISA products detected anti-SARS-CoV-2 IgM and IgG at days 2 and 6 then peaked on the eighth day; and the most promising CLIA product detected anti-SARS-CoV-2 at day 1 and peaked on the 30th day. The most promising LFA, ELISA and CLIA that had the best performance characteristics were those targeting total SARS-CoV-2 antibodies followed by those targeting anti-SARS-CoV-2 IgG then IgM. Essentially, the CLIA-based SARS-CoV-2 tests had the best performance characteristics, followed by ELISA then POCT. Given the varied performance characteristics of all the serological assays, there is a need to continuously improve their detection thresholds, as well as to monitor and re-evaluate their performances to assure their significance and applicability for COVID-19 clinical and epidemiological purposes

Study of post-combustion Carbon Dioxide capture for coal-fired plant through modelling and simulation

Fossil-fuel power plants are the largest single source of carbon dioxide (CO2) emissions. Post-combustion capture through monoethanolamine-based absorption is viewed as the most mature technology proposed for mitigating CO2 emissions from such power plants. Despite its advantages, several design and operational challenges arise in the application of this technology. The amount of flue gas to process is much greater than current applications. As a consequence, there will be a large thermal energy requirement for solvent regeneration. There are also concerns about how post-combustion CO2 capture would affect the flexibility and operability of coal-fired power plants. Though expensive pilot plant studies exist worldwide, they are still on a much smaller scale than what would be required commercially. This thesis provides useful insights for the design and operation of pilot and commercial plants through modelling and simulation. Cont/d

Dynamic modelling of CO2 absorption for post combustion capture in coal-fired power plants

Power generation from fossil fuel-fired power plants is the largest single source of CO2 emissions. Post combustion capture via chemical absorption is viewed as the most mature CO2 capture technique. This paper presents a study of the post combustion CO2 capture with monoethanolamine (MEA) based on dynamic modelling of the process. The aims of the project were to compare two different approaches (the equilibrium-based approach versus the rate-based approach) in modelling the absorber dynamically and to understand the dynamic behaviour of the absorber during part load operation and with disturbances from the stripper. A powerful modelling and simulation tool gPROMS was chosen to implement the proposed work. The study indicates that the rate-based model gives a better prediction of the chemical absorption process than the equilibrium-based model. The dynamic simulation of the absorber indicates normal absorber column operation could be maintained during part load operation by maintaining the ratio of the flow rates of the lean solvent and flue gas to the absorber. Disturbances in the CO2 loading of the lean solvent to the absorber significantly affect absorber performance. Further work will extend the dynamic modelling to the stripper for whole plant analysis

Dynamic modeling and simulation of CO2 chemical absorption process for coal- fired power plants

Post combustion capture via chemical absorption is viewed as the most mature CO capture technique. The effects of the addition of CO chemical absorption process on power plant performance have been studied using various steady-state models. However, there are several gaps in the understanding of the impact of post combustion capture on the operability of the power plant. These questions could be addressed by studying the dynamic behavior of such plants. In this study, dynamic models of the CO chemical absorption process were developed and validated. Dynamic analyses of the process reveal that absorber performance is sensitive to L/G ratio and that changes in reboiler duty significantly affect the regenerator performance. © 2009 Elsevier B.V. All rights reserve

Demonstrating full-scale post-combustion CO2 capture for coal-fired power plants through dynamic modelling and simulation

This study aims to provide insights into the design and operation of full-scale post-combustion CO2 capture for a 500MWe sub-critical power plant through dynamic modelling and simulation. The development and validation of the dynamic models of the power plant and CO2 capture plant are described. In addition, the scale-up of the CO2 capture plant from pilot plant scale (where it was validated) to full scale is discussed. Subsequently the manner in which the two plant models were linked is discussed. A floating IP/LP crossover pressure configuration is used. A throttling valve is included between the LP turbine and draw-off point to prevent pressures at the crossover from dropping below required levels in the reboiler for solvent regeneration. The flue gas from the power plant is treated before it is sent to the CO2 capture plant. Four case studies are considered. The first investigates the effect of increasing solvent concentration on the performance of the power plant with the capture plant. The second investigates which absorber packing height offers a good balance between capital and operating costs. The two dynamic case studies show that the CO2 capture plant has a slower response than the power plant. They also reveal an interaction of CO2 capture level and power plant output control loops making it difficult to achieve steady power output levels quickly