Applying design of experiments to evaluate economic feasibility of rare-earth element recovery

Deng, Sidi; Pérez-Cardona, Jesús R.; Huang, Aihua; Yih, Yuehwern; Thompson, Vicki S.; Reed, David W.; Jin, Hongyue; Sutherland, John W.

doi:10.1016/j.procir.2020.02.005

Cited by 12 publications

(9 citation statements)

References 17 publications

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“…DOE is a statistical methodology that is employed in order to find relationships among variables that affect certain processes [38]. In other words, DOE makes it possible to see how a simultaneous change in more than one variable will affect the output variable.…”

Section: Design Of Experimentsmentioning

confidence: 99%

GASVeM: A New Machine Learning Methodology for Multi-SNP Analysis of GWAS Data Based on Genetic Algorithms and Support Vector Machines

Díaz¹,

Lasheras

Moratalla-Navarro

et al. 2021

Mathematics

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Genome-wide association studies (GWAS) are observational studies of a large set of genetic variants in an individual’s sample in order to find if any of these variants are linked to a particular trait. In the last two decades, GWAS have contributed to several new discoveries in the field of genetics. This research presents a novel methodology to which GWAS can be applied to. It is mainly based on two machine learning methodologies, genetic algorithms and support vector machines. The database employed for the study consisted of information about 370,750 single-nucleotide polymorphisms belonging to 1076 cases of colorectal cancer and 973 controls. Ten pathways with different degrees of relationship with the trait under study were tested. The results obtained showed how the proposed methodology is able to detect relevant pathways for a certain trait: in this case, colorectal cancer.

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Section: Design Of Experimentsmentioning

confidence: 99%

GASVeM: A New Machine Learning Methodology for Multi-SNP Analysis of GWAS Data Based on Genetic Algorithms and Support Vector Machines

Díaz¹,

Lasheras

Moratalla-Navarro

et al. 2021

Mathematics

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“…The overall efficiency of REE-bioleaching can be greatly influenced by a variety of process variables, most importantly the pulp density 23,24 . To test how these variables affect the REE-bioleaching improvement conferred by genetic engineering, we compared REE-bioleaching efficiency of the Δ pstS and Δ pstS , P 112 : mgdh at 1 and 10% pulp density of REE-containing mineral.…”

Section: Resultsmentioning

confidence: 99%

“…batch processing; and glucose concentration 23 . However, all of these factors also influence the process economics 24 .…”

Section: Introductionmentioning

confidence: 99%

High Efficiency Rare Earth Element Biomining with Systems Biology Guided Engineering ofGluconobacter oxydans

Schmitz

Pian

Marecos

et al. 2023

Preprint

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The global demand for critical rare earth elements (REE) is rising with the increase in demand for sustainable energy technologies like wind turbines, electric vehicles, and high efficiency lighting. Current processes for producing REE require high energy inputs and can produce disproportionate amounts of hazardous waste. Biological methods for REE production are a promising solution to this problem. In earlier work we identified the most important genetic mechanisms contributing to the REE-bioleaching capability of Gluconobacter oxydans B58. Here we have targeted two of these mechanisms to generate a high-efficiency bio-mining strain of G. oxydans. Disruption of the phosphate-specific transport system through a clean deletion of pstS constitutively turns on the phosphate starvation response, yielding a much more acidic biolixiviant, and increasing bioleaching by up to 30%. Coupling knockout of pstS with the over-expression of the mgdh membrane-bound glucose dehydrogenase gene, results in up to 73% improvement of REE-bioleaching.

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“…The current review also highlights the abundance of REM wealth in the industrial waste whence, relevant data like REM content on individual industrial waste, the volume of waste being generated, and the fate of generated waste are hardly available which is the rudimentary stage for the policy or process development. Though some of the researchers report plausible economic feasibility, an equally opposite conclusion also hinders industrial recovery interest (Innocenzi et al 2016b ; Joseph et al 2019 ; Deng et al 2020 ; Ilankoon et al 2022 ). Through, dedicated research and precise data on the context of industrial-scale REM recovery and economic impact can address the concern.…”

Section: Significance and Novelty Of Review Over Rem Valorization Fro...mentioning

confidence: 99%

Challenges and opportunities for sustainable valorization of rare earth metals from anthropogenic waste

Swain

2023

Rev Environ Sci Biotechnol

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Applying design of experiments to evaluate economic feasibility of rare-earth element recovery

Cited by 12 publications

References 17 publications

GASVeM: A New Machine Learning Methodology for Multi-SNP Analysis of GWAS Data Based on Genetic Algorithms and Support Vector Machines

GASVeM: A New Machine Learning Methodology for Multi-SNP Analysis of GWAS Data Based on Genetic Algorithms and Support Vector Machines

High Efficiency Rare Earth Element Biomining with Systems Biology Guided Engineering ofGluconobacter oxydans

Challenges and opportunities for sustainable valorization of rare earth metals from anthropogenic waste

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