Search

Solvent extraction of metals from Ti ore was investigated with a view of enhancing extraction yields by changing the concentration of the ligands, the rate of mixing, the pH, and the temperature of the solution. Norwegian Ti ore was leached with 5M HNO3 alongside 10% ascorbic acid to obtain a pregnant solution containing transition metals and some rare earth elements (REEs). Part Two of the study will address the recovery of the REEs in the ore. The elemental analysis of solid and aqueous samples was done by two models of total reflection X-ray fluorescence spectrometers (S2 PICOFOX, Bruker Corporation, Berlin, Germany; and T-STAR, Bruker Corporation, Berlin, Germany). The same analysis was repeated using an inductively coupled plasma-mass spectrometer (Perkin Elmer Sciex ELAN DRC II, Perkin Elmer, Waltham, MA, USA). The extraction process and parameters were examined by ICP-MS. The extraction efficiencies were studied under different conditions through the use of various concentrations of ligands at different pHs, temperatures, and mixing rates of the solution. At pH 1.0, 22.5 °C, and a mixing rate of 1400 rpm, the selectivity of 150 g/L trioctyl methyl ammonium chloride (Aliquat 336) was 99% Ti4+, 94% V4⁺, and 82% Hf4+, while 99% of Co2⁺ was recovered at pH 0.8. The extraction efficiency of triethyl phosphate (10% TEP) was 58% Cu2⁺, 68% Mn2⁺, and 63% V4⁺ at 55 °C, 1400 rpm, and without a pH change. Tributyl phosphate (10% TBP) was able to retrieve 87% Cu2⁺ and 78% Zn2⁺ at pH 1.3, 1400 rpm, and 22.5 °C, and 80% Ti4+ at pH 1.2. A 10% solution of 2,4,6-tris (allyloxy)-1,3,5-triazine (TAOT) demonstrated 61% Mn2⁺ and 56% Hf4+ extraction at pH 1.3, 22.5 °C, and 1400 rpm. Under the same conditions, 10% methyl salicylate (MS) was able to recover 56% Hf4+ at pH 1.3. Using 1400 rpm, di (2-ethylhexyl) phosphoric acid (10% D2EHPA) was found to selectively extract 87% Hf4+ at 22.5 °C without a pH change, and around 99% Co2⁺, Ti4+, and Fe2⁺ at pH 1.3. This study provides valuable insights into optimizing solvent extraction conditions for transition metals' recovery and serves as a precursor to future research on the extraction of REEs from Ti ores. This process is relevant from the environmental and economic perspectives since it provides the best approach to recycling metals to reduce the rate of raw ore mining. [ABSTRACT FROM AUTHOR]

At our Historically-Black University, about 89% of first-year students place into developmental mathematics, negatively impacting retention and degree completion. In 2012, an NSF-funded learning enrichment project began offering the introductory and developmental mathematics courses on-line over the summer to incoming science, technology, engineering and mathematics (STEM) majors at no cost to students. Passing rates for the summer on-line classes were around 80%, and students in the on-line classes scored equivalently on the common departmental final exams as students taking the classes in the traditional format. For students who passed the on-line classes, their performance in the following classes (College Algebra and Trigonometry) at least equaled that of students who progressed to those courses by taking the traditional series of in-person courses. Three years of data show that students who started college with an on-line mathematics course in a summer bridge program had a higher first year GPA, a better first year retention rate and earned significantly more credits in their first year than the overall population of STEM students. While not solely attributable to the on-line classes, these results suggest that offering introductory mathematics courses on-line as part of a freshman bridge program is an effective, scalable intervention to increase the academic success of students who enter college under-prepared in mathematics. The positive results are particularly exciting since the students in our project were 87% minority.

With advancements in hardware and software, non-destructive radiometric analytical methods have become popular in a wide range of applications. A typical case is the study of the leaching process of metals from mineral ores and mine tailings. The objective of the current study was to develop a radiometric method based on neutron activation analysis (NAA), in particular, delayed gamma neutron activation analysis (DGNAA), to monitor the process of Mn and Zn leaching from Ti ore, Cu mine tailings, and Zn-Pb mine tailings. The DGNAA method was performed using a neutron source: a deuterium-tritium (D-T) neutron generator for Mn and a MARIA research nuclear reactor for Zn. Laboratory-scale Mn leaching from Ti ores, Cu tailings, and Zn-Pb tailings was investigated using delayed gamma-rays of 56Mn (half-life of 2.6 h). The dissolution efficiencies of Mn were found to increase with interaction time and HCl concentration (1 to 5 M) and to vary with the leaching temperature (22.5 to 110 °C). Such results were found to agree with those obtained by total reflection X-ray fluorescence (TXRF) spectrometry for the same samples. 65Zn (half-life of 244 days) was chosen to investigate real-time/online leaching of Zn in Ti ore, Cu tailings, and Zn-Pb tailings. During online monitoring, Zn recovery was also reported to increase with increased leaching time. After approximately 300 min of leaching, 80%, 79%, and 53% recovery of Zn in Zn-Pb tailings, Ti ore, and Cu tailings, respectively, were reported. Theoretically, developed mathematical prediction models for 65Zn radiotracer analysis showed that the spherical diffusion model requires much less time to attain saturation compared to the linear diffusion model. The results of NAA for Zn were compared with those obtained by handheld X-ray fluorescence (handheld-XRF) and TXRF analysis. The analyzed samples encompassed leached Ti ore, Cu tailings, and Zn-Pb tailings which were subjected to different conditions of leaching time, temperature, and HCl concentrations. The XRF analysis confirmed that the leaching efficiencies of Zn rise with the increase in leaching time and HCl concentration and fluctuate with leaching temperature. The developed approach is important and can be applied in laboratories and industrial setups for online monitoring of the recovery of any element whose isotopes can be activated using neutrons. The efficiency of the metal-recovery process has a direct impact on the normal operation and economic advantages of hydrometallurgy. [ABSTRACT FROM AUTHOR]

Computer literacy plays a critical role in today's life sciences research. Without the ability to use computers to efficiently manipulate and analyze large amounts of data resulting from biological experiments and simulations, many of the pressing questions in the life sciences could not be answered. Today's undergraduates, despite the ubiquity of computers in their lives, seem to be largely unfamiliar with how computers are being used to pursue and answer such questions. This article describes an innovative undergraduate-level course, titled Computer Literacy for Life Sciences, that aims to teach students the basics of a computerized scientific research pursuit. The purpose of the course is for students to develop a hands-on working experience in using standard computer software tools as well as computer techniques and methodologies used in life sciences research. This paper provides a detailed description of the didactical tools and assessment methods used in and outside of the classroom as well as a discussion of the lessons learned during the first installment of the course taught at Emory University in fall semester 2009. (Contains 3 tables and 1 figure.)

Abstract Background Independent Component Analysis (ICA) proves to be useful in the analysis of neural activity, as it allows for identification of distinct sources of activity. Applied to measurements registered in a controlled setting and under exposure to an external stimulus, it can facilitate analysis of the impact of the stimulus on those sources. The link between the stimulus and a given source can be verified by a classifier that is able to "predict" the condition a given signal was registered under, solely based on the components. However, the ICA's assumption about statistical independence of sources is often unrealistic and turns out to be insufficient to build an accurate classifier. Therefore, we propose to utilize a novel method, based on hybridization of ICA, multi-objective evolutionary algorithms (MOEA), and rough sets (RS), that attempts to improve the effectiveness of signal decomposition techniques by providing them with "classification-awareness." Results The preliminary results described here are very promising and further investigation of other MOEAs and/or RS-based classification accuracy measures should be pursued. Even a quick visual analysis of those results can provide an interesting insight into the problem of neural activity analysis. Conclusion We present a methodology of classificatory decomposition of signals. One of the main advantages of our approach is the fact that rather than solely relying on often unrealistic assumptions about statistical independence of sources, components are generated in the light of a underlying classification problem itself.