Metal bioleaching from printed circuit boards by bio-Fenton process: Optimization and prediction by response surface methodology and artificial intelligence models.

Recycling printed circuit boards (PCBs) in the e-waste stream is essential for ecological protection and metal recycling for a circular economy. Efficient metal recovery from PCBs is highly dependent on the determination of the optimum combination of inputs in the recycling process. In this study, optimization and predictive modelling of the bio-Fenton process were performed employing the response surface methodology (RSM) and the artificial intelligence (AI) models for efficient enzymatic metal bioleaching from discarded cellphone PCBs. The Box-Behnken design (BBD) of RSM was chosen as the design matrix. Further, two AI models, i.e., support vector machine (SVM) and artificial neural network (ANN) were employed to predict complex metal bioleaching process. Experiments were performed based on variations of four input process parameters, namely, glucose oxidase (GOx) content (100-1000 U/L), Fe2+ content (10-50 mM), PCB pulp density (1-10 g/L), and shaking speed (150-450 rpm). Results revealed that the maximum simultaneous enzymatic metal extraction of 100% Cu, 70% Ni, 40% Pb, and 100% Zn was attained at the optimized conditions: GOx content: 300 U/L, Fe2+ content: 10 mM, pulp density: 1 g/L, and shaking speed: 335 rpm. A comparative analysis of the AI models suggested that the ANN-based model predicting more accurate results than the SVM-based model with coefficient of determination values > 0.99 for all the targeted metals. The FTIR analysis confirmed the partial disintegration of PCB polymeric base by OH radicals (OH•), which helped in liberating and exposing the embedded metals to the bio-Fenton solution. Further, the oxidation of metals by ferric ions produced from GOx-mediated oxidation of ferrous ions ensued efficient enzymatic metal bioleaching. Selective metal recovery of >99% was obtained by the chemical precipitation of bioleachate.

Fungal biotechnology for urban mining of metals from waste printed circuit boards: A review.

Rapid surge in electronic waste (e-waste) and its unscientific handling has an adverse impact on humans and the environment. Waste printed circuit board (WPCB), an integrated component of e-waste, has a high metallic content that includes both toxic and precious metals. Therefore, metal recovery is essential not just to avoid environmental degradation but also for economic growth. The current literature analysis focuses on one such eco-friendly approach, known as fungal biotechnology, for extracting metals from WPCBs. Among diverse bioleaching agents, fungi have shown promising metal extraction efficiency (Al: 65-96%; Co: 45-90%; Cu: 34-100%; Ni: 8-95%; Mn: 70-95%; Pb: 27-95%; Zn: 54-99%) and the ability to work in a wide pH range. However, in terms of metal recovery from WPCBs, fungal bioleaching has been less explored. This review, thus, assesses the fungal biotechnology for metal extraction from WPCBs and discusses the associated mechanism and kinetics involved. Different process parameters affecting the fungal bioleaching have also been discussed briefly. The review highlights that, while this process has enough potential, some associated drawbacks hinder its practical applicability on an industrial scale. Lastly, some suggestions for scaling up and reducing the cost of the process have been made, which need to be addressed.

Exploring barriers to payer utilization of genetic counselors.

Access to genetic counselors' services is neither universal nor automatic, due in part to the gatekeeper role of healthcare payers--the companies and agencies that purchase healthcare services on patients' behalf and control the bulk of healthcare spending. This pilot study surveyed and analyzed the relative importance of barriers to expanded payer coverage of genetic counselors' services. Surveys were mailed to 263 medical directors and quality assurance directors at health insurance carriers throughout the United States. Respondents provided demographic information and indicated the importance of nine possible barriers, plus an optional write-in "other." Twenty-two surveys were analyzed. "Evidence that use of genetic counselors improves health outcomes" led the list of factors having a significant/very significant influence on coverage policy. Sixteen respondents (73 %) rated this factor "4" or "5" on a Likert scale; it also received the most #1 rankings and the highest score using a weighted-mean analysis. Provider practice guidelines, CMS/Medicare regulations, and genetic counselor licensure-all of which are outside of payers' direct control-also ranked highly. The research demonstrates that although the potential barriers to expanded reimbursement for genetic counselors are numerous and complex, some are more consistently identified as important and therefore more deserving of legislative and advocacy resources to effect change. Future research should endeavor to increase survey response and include providers as well as payers.