Basic oxygen furnace slags (BOS) are by-products of basic oxygen steel production. Whereas the solubility of some elements from these slags has been well investigated, information about the mineralogy and related leaching, i.e., availability of the environmentally relevant elements chromium (Cr), molybdenum (Mo), and vanadium (V), is still lacking. The aim of this study was to investigate these issues with a modified, four-fraction-based, sequential extraction procedure (F1-F4), combined with X-ray diffraction, of two BOS. Extractants with increasing strength were used (F1 demineralized water, F2 CHCOOH + HCl, F3 NaEDTA + NHOH·HCl, and F4 HF + HNO + HO), and after each fraction, X-ray diffraction was performed. The recovery of Cr was moderate (66.5%) for one BOS, but significantly better (100.2%) for the other one. High recoveries were achieved for the other elements (Mo, 100.8-107.9% and V, 112.6-87.0%), indicating that the sequential extraction procedure was reliable when adapted to BOS. The results showed that Cr and Mo primarily occurred in F4, representing rather immobile elements under natural conditions, which were strongly bound into/onto Fe minerals (srebrodolskite, magnetite, hematite, or wustite). In contrast, V was more mobile with proportional higher findings in F2 and F3, and the X-ray diffraction results reveal that V was not solely bound into Ca minerals (larnite, hatrurite, kirschsteinite, and calcite), but also bound to Fe minerals. The results indicated that the total amount of recovery was a poor indicator of the availability of elements and did not correspond to the leaching of elements from BOS.
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http://dx.doi.org/10.1007/s11356-018-2361-z | DOI Listing |
Sci Rep
January 2025
D. Y. Patil Agriculture and Technical University, Talsande, Maharashtra, India.
Indian agriculture is vital sector in the country's economy, providing employment and sustenance to millions of farmers. However, Plant diseases are a serious risk to crop yields and farmers' livelihoods. Traditional plant disease diagnosis methods rely heavily on human expertise, which can lead to inaccuracies due to the invisible nature of early disease symptoms and the labor-intensive process, making them inefficient for large-scale agricultural management.
View Article and Find Full Text PDFNat Commun
January 2025
Van 't Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands.
As a result of the current high throughput of the fast fashion collections and the concomitant decrease in product lifetime, we are facing enormous amounts of textile waste. Since textiles are often a blend of multiple fibers (predominantly cotton and polyester) and contain various different components, proper waste management and recycling are challenging. Here, we describe a high-yield process for the sequential chemical recycling of cotton and polyester from mixed waste textiles.
View Article and Find Full Text PDFBioresour Technol
January 2025
CRETUS, Department of Chemical Engineering, Universidade de Santiago de Compostela 15782 Santiago de Compostela, Spain.
This work investigates the optimization of medium-chain carboxylate (MCC) production through xylan mixed-culture monofermentation. The pH screening in batch assays showed that the hydrolysis stage and selectivity towards MCC precursors were optimised at pH 6. Subsequently, a continuous stirred tank reactor (CSTR) and a Sequential Batch Reactor (SBR) were operated at different Hydraulic Retention Times (HRT), revealing that the SBR at HRT 2 days yielded the highest caproic acid since lactic acid availability and chain elongation process were balanced.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
January 2025
Great Ormond Street Institute of Child Health, University College London, London, UK.
Introduction: Unsupervised feature learning methods inspired by natural language processing (NLP) models are capable of constructing patient-specific features from longitudinal Electronic Health Records (EHR).
Design: We applied document embedding algorithms to real-world paediatric intensive care (PICU) EHR data to extract patient-specific features from 1853 patients' PICU journeys using 647 unique lab tests and medication events. We evaluated the clinical utility of the patient features via a K-means clustering analysis.
BMC Med Educ
January 2025
University of Illinois Chicago, College of Medicine, Associate Professor of Medicine, Chicago, IL, US.
Implicit biases involve associations outside conscious awareness that lead to a negative evaluation of a person based on individual characteristics. Early evaluation of implicit bias in medical training can prevent long-term adverse health outcomes related to racial bias. However, to our knowledge, no present studies examine the sequential assessment of implicit bias through the different stages of medical training.
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