Conxita Lao-Luque

The selectivity of the colorimetric method for Co(II) determination using the nitroso-R-salt (NRS) in samples with complex matrices has been improved. Interferences caused by Cu(II), Fe(II), Fe(III), Mn(II), Al(III) and Ni(II) ions, which were present in the bioleach ate of lithium-ion batteries, have been solved through the sequential addition of masking agents: acetate, fluoride, ethylenediaminetetraacetic acid (EDTA), and strong acids (H₂SO₄). The absorbance of the NRS-Co(II) complex was typically measured at 525 nm, but it was also studied at 550 nm due to minimal interferences observed at 550 nm. The sequence of the masking agent’s addition showed a significant influence on the interference effect. The optimal sequence was sample, acetate–acetic acid buffer solution with dissolved fluoride, NRS, EDTA and H₂SO₄. The proposed method demonstrated robust performance at 550 nm, with a relative standard deviation (RSD) around 2%, and good accuracy (RV% around 100%). The limit of detection (LoD) was 0.1 mg L⁻¹ and the limit of quantification (LoQ) was 0.3 mg L⁻¹. The linear range extended up to 15 mg L⁻¹ (R² = 0.998). Real samples analyzed using the optimized method showed no significant differences when compared to results from atomic absorption spectroscopy, confirming its reliability.

The selectivity of the colorimetric method for Co(II) determination using the nitroso-R-salt (NRS) in samples with complex matrix had been improved. Interferences caused by Cu(II), Fe(II), Fe(III), Mn(II), Al(III) and Ni(II) ions, which were present in the bioleachate of lithium-ion batteries, have been solved through the sequential addition of masking agents: acetate, fluoride, ethylenediaminetetraacetic acid (EDTA), and strong acids (H2SO4). The absorbance of the NRS-Co(II) complex was typically measured at 525 nm but it was also studied at 550 nm due to minimal interferences observed at 550 nm. The sequence of the masking agent’s addition showed a significant influence on the interferences effect. The optimal sequence was sample, acetate-acetic acid buffer solution with dissolved fluoride, NRS, EDTA and H2SO4. The proposed method demonstrated robust performance at 550 nm, with a relative standard deviation (RSD) around 2%, accuracy (RV% around 100%). The limit of detection (LoD) was 0.1 mg L-1 and the limit of quantification (LoQ) was 0.3 mg L-1. The linear range extended up to 15 mg L-1 (R2= 0.998). Real samples analyzed using the optimized method showed no significant differences when compared to results from atomic absorption spectroscopy, confirming its reliability.

The rising demand for lithium-ion batteries (LIBs), driven by the growing consumption of electronic devices and the expansion of electric vehicles, is leading to a concerning depletion of primary metal resources and a significant accumulation of electronic waste. This urgent challenge highlights the need for sustainable recovery methods to extract valuable metals from spent LIBs, aligning with circular economy principles. In this study, the preparation of spent batteries for the bioleaching process was achieved with minimal manipulation. This included a preliminary discharge to ensure safety in subsequent processes and a brief crushing to facilitate the access of leaching agents to valuable metals. Unlike most studies that grind batteries to obtain powders between 70 and 200 microns, our approach works with particles sized around 5 mm. Additionally, our preparation process avoids any thermal or chemical treatments. This straightforward pre-treatment process marks a significant advancement by reducing the complexity and cost of processing. A systematic study was conducted on various fractions of the large particle sizes, using Fe (III) produced through bio-oxidation by A. ferrooxidans and biogenically obtained H2SO4 from A. thiooxidans. The highest metal extraction rates were achieved using the unsorted fraction, directly obtained from the black mass after the grinding process, without additional particle separation. When treated with bio-oxidized Fe (III), this fraction achieved a 95% recovery of Cu, Ni, and Al within 20 min, and over 90% recovery of Co, Mn, and Li within approximately 30 min. These recovery rates are attributed to the combined reducing power of Al and Cu already present in the black mass and the Fe (II) generated during the oxidation reactions of metallic Cu and Al. These elements actively facilitate the reduction of transition metal oxides into their more soluble, lower-valence states, enhancing the overall metal solubilization process. The extraction was carried out at room temperature in an acidic medium with a pH no lower than 1.5. These results demonstrate significant potential for efficient metal recovery from spent batteries with minimal pre-treatment, minimizing environmental impact. Additionally, the simplified residue preparation process can be easily integrated into existing waste management facilities without the need for additional equipment.

The rising demand for lithium-ion batteries (LIBs), driven by the growing consumption of electronic devices and the expansion of electric vehicles, is leading to a concerning depletion of primary metal resources and a significant accumulation of electronic waste. This urgent challenge highlights the need for sustainable recovery methods to extract valuable metals from spent LIBs, aligning with circular economy principles. In this study, the preparation of spent batteries for the bioleaching process was achieved with minimal manipulation. This included a preliminary discharge to ensure safety in subsequent processes and a brief crushing to facilitate the access of leaching agents to valuable metals. Unlike most studies that grind batteries to obtain powders between 70 and 200 microns, our approach works with particles sized around 5mm. Additionally, our preparation process avoids any thermal or chemical treatments. This straightforward pre-treatment process marks a significant advancement by reducing the complexity and cost of processing. A systematic study was conducted on various fractions of the large particle sizes, using Fe (III) produced through biooxidation by A. ferrooxidans and biogenically obtained H2SO4 from A. thiooxidans. The highest metal extraction rates were achieved using the unsorted fraction, directly obtained from the black mass after the grinding process, without additional particle separation. When treated with bio-oxidized Fe (III), this fraction achieved a 95% recovery of Cu, Ni, and Al within 20 minutes, and over 90% recovery of Co, Mn, and Li within approximately 30 minutes. These recovery rates are attributed to the combined reducing power of Al and Cu already present in the black mass and the Fe(II) generated during the oxidation reactions of metallic Cu and Al. These elements actively facilitate the reduction of transition metal oxides into their more soluble, lower-valence states, enhancing the overall metal solubilization process. The extraction was carried out at room temperature in an acidic medium with a pH no lower than 1.5. These results demonstrate significant potential for efficient metal recovery from spent batteries with minimal pretreatment, minimizing environmental impact. Additionally, the simplified residue preparation process can be easily integrated into existing waste management facilities without the need for additional equipment.

In this study, a modular, multi-step, photometric microflow injection analysis (micro-FIA) system for the automatic determination of Cu(II) in a bioreactor was developed. The system incorporates diverse 3D-printed modules, including a platform formed by a mixer module to mix Cu(II) with hydroxylamine, which reduces Cu(II) to Cu(I) linked to a diluter module via a Tesla valve, a chelation mixer module, a disperser module, and a detector module provided by an LED light source at λ = 455 nm and a light dependence resistor (LDR) as a light intensity detector. The system measures the color intensity resulting from the chelation between Cu(I) and neocuproine. The micro-FIA system demonstrated good capability for automatic and continuous Cu(II) determination, in a wide range of Cu concentrations, from 34 to 2000 mg L⁻¹. The device exhibits a good repeatability (coefficient of variation below 2% across the measured concentration range), good reproducibility, and has an accuracy of around 100% between 600 and 1900 mg L⁻¹. Real samples were analyzed using both the micro-FIA system and an atomic absorption spectroscopy method, revealing no statistically significant differences. Additionally, a Tesla valve located before the detector substituted a 3-way solenoid valve, eliminating the need for moving parts.

In this study, a modular multi-step photometric microflow injection analysis (micro-FIA) system for the automatic determination of Cu(II) in a bioreactor has been developed. The system incorporates diverse 3D-printed modules, including a platform formed by a mixer module to mix Cu(II) with hydroxylamine which reduces Cu(II) to Cu(I) linked to a diluter module via a Tesla valve, a chelation mixer module, a disperser module, and a detector module provided by a LED light source at λ= 455 nm and a light dependence resistor (LDR) as a light intensity detector. The system measures the color intensity resulting from the chelation between Cu(I) and neocuproine. The micro-FIA system has demonstrated good capability for automatic and continuous Cu(II) determination, in a wide range of Cu concentrations from 34 to 2000 mg L-1. The device exhibits a good repeatability (coefficient of variation below 2% across the concentration range), good reproducibility, and has an accuracy of around 100% between 600 to 1900 mg·L-1. Real samples were analyzed using both the micro-FIA system and an atomic absorption spectroscopy method, revealing no statistically significant differences. Additionally, a Tesla valve located before the detector substituted a 3-way solenoid valve, eliminating the need for moving parts.

A modular microflow injection analysis (microFIA) system for the determination of Fe(III) in a bioleaching reactor has been designed, developed and validated. The different modules of the analyzer (mixer, diluter, disperser and detector) were 3D-printed. Fe(III) quantification is due by measuring the color intensity of the chelate formed between Fe(III) and salicylic acid at 525 nm. The device has been designed to dilute, disperse and detect high Fe(III) concentrations in the form of an inexpensive multi-step photometric flow cell that uses an light-emitting diode (LED) as a light source and an light-dependent resistor (LDR) as a light intensity detector. This microFIA system has been shown to be suitable for automatic and continuous determination of Fe(III) in the operation of a bioreactor for the oxidation of Fe(II). The device has a good repeatability (less than 5% of coefficient of variation in the whole range of concentrations) and accuracy of around 100%. The analyzer features an exceptional wide linear range, between 25 and 6000 mg·L⁻¹. The device was successfully applied to the determination of Fe(III) in real samples. The obtained results proved that the method is applicable for accurate, precise, rapid, and low-cost colorimetric analysis and didn’t show significant differences with a conventional UV–Vis method. Graphical Abstract