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Abstract Owing to the increasing global demand for carbon resources, pressure on finite materials, including petroleum and inorganic resources, is expected to increase in the future. Efficient utilization of waste resources has become crucial for sustainable resource acquisition for creating the next generation of industries. Rice husks, which are abundant worldwide as agricultural waste, are a rich carbon source with a high silica content and have the potential to be an effective raw material for energy‐related and environmental purification materials such as battery, catalyst, and adsorbent. Converting these into valuable resources often requires separation and carbonization; however, these processes incur significant energy losses, which may offset the benefits of using biomass resources in the process steps. This review summarizes and discusses the high value of RHs, which are abundant as agricultural waste. Technologies for separating and converting RHs into valuable resources by hydrothermal carbonization are summarized based on the energy efficiency of the process.

Currently, there have been issues concerning the depletion and scarcity of mineral resources. This is mostly due to the excavation of high grade minerals having already occurred years and years ago, hence forcing the mining industry to opt for the production and optimization of lower grade minerals. This however brings about a plethora of problems, many of which economic, stemming from the purification of those low grade minerals in various stages required for mineral processing. In order to reduce costs and aid in the optimization of the mining stream, this study, introduces an automatic mineral identification system which combines the predictive abilities of deep learning with the excellent resolution of hyperspectral imaging, for pre-stage of mineral processing. These technologies were used to identify and classify high grade arsenic (As) bearing minerals from their low grade mineral counterparts non-destructively. Most of this ability to perform such tasks comes from the highly versatile machine learning model which employs deep learning as a means to classify minerals for mineral processing. Experimental results supported this statement as the model was able to achieve an over 90% accuracy in the prediction of As-bearing minerals, hence, one could conclude that this system has the potential to be employed in the mining industry as it achieves modern day system requirements such as high accuracy, speed, economic, userfriendly and automatic mineral identification.

Abstract SCS pincer ligands 1–4 were synthesised, and their ability to extract Pd(II) from HCl and HNO3 media was studied. The Pd(II) extraction properties of 1–4 were compared with those of commercial extractants (DOS and LIX®84-I) in kerosene. 1 and 2 showed superior Pd(II) extractability (E% = 99.9) relative to DOS and LIX®84-I from 0.1–8.0 M HCl and to DOS from 0.1–8.0 M HNO3 and mixed HCl + HNO3 media. The Pd(II) extraction rate, acid durability, the most suitable organic/aqueous (O/A) phase ratio, and Pd(II) loading capacity of extractants 1, 2, and DOS were evaluated. 1 and 2 exhibited a greater Pd(II) extraction rate and Pd(II) loading capacity than DOS. 1 was very stable in acid media (HCl and HCl + HNO3), whereas 2 and DOS deteriorated in HCl + HNO3. Selective extraction of Pd(II) by 1 and 2 was achieved from a mixed solution containing Pd, Pt, Rh, rare metals, and base metal ions that simulated the leach liquors of automotive catalysts. The back extraction of Pd(II) and reusability of extractants 1 and 2 were studied. The Pd(II) extraction mechanism of 1–4 was investigated using FT-IR, UV-visible, and NMR spectroscopy.

The flotation tailings obtained from Bor Copper Mine contain pyrite (FeS2) and chalcopyrite (CuFeS2), these sulfide minerals are known to promote acid mine drainage (AMD) which poses a serious threat to the environment and human health. This study focuses on the treatment of mine tailings to convert the AMD supporting minerals to more stable forms, while simultaneously valorizing the mine tailings. A combination of hydrometallurgical processes of high-pressure oxidative leaching (HPOL), solvent extraction (SX), and electrowinning (EW) were utilized to recover copper from mine tailings which contain about 0.3% Cu content. The HPOL process yielded a high copper leaching rate of 94.4% when water was used as a leaching medium. The copper leaching kinetics were promoted by the generation of sulfuric acid due to pyrite oxidation. It was also confirmed that a low iron concentration (1.4 g/L) and a high copper concentration (44.8 g/L) obtained in the stripped solution resulted in an improved copper electrodeposition current efficiency during copper electrowinning. Moreover, pyrite, which is primarily in the mine tailings, was converted into hematite after HPOL. A stability evaluation of the solid residue confirmed almost no elution of metal ions, confirming the reduced environmental loading of mine tailings through re-processing.

This paper deals with the recovery of gold from waste printed circuit boards (WPCBs) ash by high-pressure oxidative leaching (HPOL) pre-treatment and iodide leaching followed by reduction precipitation. Base metals present in WPCB ash were removed via HPOL using a diluted sulfuric acid solution at elevated temperatures. Effects of potassium iodide concentration, hydrogen peroxide concentration, sulfuric acid concentration, leaching temperature, and leaching time on gold extraction from pure gold chips with KI–H2O2–H2SO4 were investigated. The applicability of the optimized iodide leaching process for the extraction of gold from the leach residue obtained after HPOL were examined at different pulp densities ranging from 50 g/t to 200 g/t. Results show that the removal efficiency was 99% for Cu, 95.7% for Zn, 91% for Ni, 87.3% for Al, 82% for Co, and 70% for Fe under defined conditions. Under the optimal conditions, the percentage of gold extraction from the gold chips and the residue of WPCBs was 99% and 95%, respectively. About 99% of the gold was selectively precipitated from the pregnant leach solution by sequential precipitation with sodium hydroxide and L-ascorbic acid. Finally, more than 93% of gold recovery was achieved from WPCB ash by overall combined processes.