Selective Metal Research Articles

Machine Learning Framework for Selective and Sensitive Metal Ion Sensing with Nitrogen-doped Graphene Quantum Dots Heterostructure

Machine Learning Framework for Selective and Sensitive Metal Ion Sensing with Nitrogen-doped Graphene Quantum Dots Heterostructure

Post-synthetic modification of a MOF via Continuous Flow Methods for Gold E-Waste Recycling.

This study pioneers the use of continuous flow methods to modify the nanoporous metal-organic framework Fe-BTC (MIL-100(Fe)) with redox-active poly-p-phenylenediamine (PpPDA). The Fe-BTC/PpPDA composite, known for its gold extraction capabilities, was synthesized in continuous flow on a 250 g scale. Fe-BTC/PpPDA was then tested in eight industrial leachates (e.g., cyanide, thiourea, aqua regia) exhibiting varying effectiveness, pH, and gold speciation, which led to significant differences in the composite's performance for gold extraction. The composite performed best in solutions containing [AuCl4]- species. Structured into spherical beads using a novel continuous flow microdroplet technique, these adsorbents were tested for gold recovery from real e-waste solutions in a breakthrough epemriment. They achieved a capacity of ~600 mg of gold per gram before breakthrough and ~900 mg per gram at a 60% recovery rate. Selectivity ratios for Au/Ni, Au/Co, and Au/Fe were 972, 262, and 193, respectively. In situ X-ray absorption near edge spectroscopy (XANES) provided evidence of the reduction of Au³⁺ to Au⁰, facilitated by the redox-active oligomers. Outperforming several commercial resins, Fe-BTC/PpPDA shows great promise for scalable, selective metal recovery from waste streams. This study highlights the potential of MOF/polymer composites and continuous flow methods for large-scale production.

Site differentiation strategy for selective strontium uptake and elution within an all-inorganic polyoxoniobate framework

Selective uptake and elution of trace amounts of hazardous radioactive 90Sr from large-scale high-level liquid waste (HLW) is crucial for sustainable development. Here, we propose a site differentiation strategy, based on the presence of distinct selective metal capture sites (concavity site and tweezer site) within the giant polyoxoniobate (PONb) nanoclusters of an all-inorganic PONb framework (FZU-1). Through this strategy, FZU-1 can not only effectively remove 98.9% of Sr²⁺ from simulated nuclear liquid waste, performing best among the reported Sr adsorbents, but also achieve desorption of adsorbed Sr²⁺ ions by selectively loading Na⁺ ions, thus enabling the recycling of FZU-1. Based on the well-defined single-crystal structures and theoretical studies, it can be revealed that the rapid and selective uptake of Sr²⁺ is attributed to the strong binding energy between the Sr²⁺ ions and the concavity sites. The effective elution of Sr²⁺, on the other hand, stems from the preferential binding of Na⁺ ions at the tweezer sites, elevating the cluster’s electrostatic potential and indirectly facilitating the elution of Sr²⁺ ions. The exceptional stability of FZU-1, along with its rapid and selective Sr²⁺ capture and elution capabilities, positions it as a promising candidate for large-scale nuclear waste treatment and groundwater remediation applications.

Intelligent Evaluation and Dynamic Prediction of Oysters Freshness with Electronic Nose Non-Destructive Monitoring and Machine Learning.

Physiological and environmental fluctuations in the oyster cold chain can lead to quality deterioration, highlighting the importance of monitoring and evaluating oyster freshness. In this study, an electronic nose was developed using ten partially selective metal oxide-based gas sensors for rapid freshness assessment. Simultaneous analyses, including GC-MS, TVBN, microorganism, texture, and sensory evaluations, were conducted to assess the quality status of oysters. Real-time electronic nose measurements were taken at various storage temperatures (4 °C, 12 °C, 20 °C, 28 °C) to thoroughly investigate quality changes under different storage conditions. Principal component analysis was utilized to reduce the 10-dimensional vectors to 3-dimensional vectors, enabling the clustering of samples into fresh, sub-fresh, and decayed categories. A GA-BP neural network model based on these three classes achieved a test data accuracy rate exceeding 93%. Expert input was solicited for performance analysis and optimization suggestions enhanced the efficiency and applicability of the established prediction system. The results demonstrate that combining an electronic nose with quality indices is an effective approach for diagnosing oyster spoilage and mitigating quality and safety risks in the oyster industry.

Recyclability study for the next generation of cobalt-free lithium-ion battery systems with C-LNMO, Si/C- LRLO and TiNbO-LNMO active materials via hydrometallurgical route

The scarcity and uncertain supply of cobalt poses significant challenges for the lithium-ion battery industry. To address this issue, alternative chemistries excluding cobalt have been developed. Despite solving supply issues, these developments raise concerns about recyclability and their impact on current recycling trends.This study presents a recycling strategy and evaluates its performance for next-generation cobalt-free lithium-ion batteries. It focuses on three prototypes that use innovative cathode materials (titanium niobium oxide, carbon, and silicon/carbon) and electrolyte systems (ionic liquid and gelified). The proposed recycling process includes pyrolysis, mechanical separation, neutral and acid leaching, cementation, and neutralisation for selective metal separation.The results indicate that gelified electrolytes exhibit greater thermal stability than their liquid counterparts, indicating an effect on the degradation temperature and gas emissions, which are crucial for metal recovery. This study highlights the reduced toxicity of ionic liquid electrolytes and emphasises the need for strict pyrolysis gas handling due to hazardous emissions. High recovery rates (65–90 %) were achieved for nickel, manganese, lithium, and anode components.With potential for process optimisation to improve the quality of products, this study shows that cobalt-free battery systems can be integrated into existing recycling frameworks with adjustments, supporting progress towards sustainable battery practices.

Insights into the Effect of Crystal Facets and Sulfur Defects on the Product Selectivity of Various CdS Configurations for CO2 Photoreduction: A DFT Study

CO2 photoreduction into valuable hydrocarbons, such as CO, CH4, and C2H4, delivers a promising approach to address both environmental and energy challenges. Transition metal chalcogenides, particularly cadmium sulfide (CdS), have emerged as prominent candidates due to their tunable electronic properties and availability. This study delves into a comprehensive investigation of how CdS crystalline facets and sulfur-deficient surfaces modulate the product selectivity. Through employing density functional theory (DFT), we unravel the catalytic performance of various CdS crystal orientations and sulfur vacancy configurations. The results have shown that different CdS facets exhibit unique electronic characteristics and surface energetics, which influence the adsorption dynamics and reaction pathways. The introduction of sulfur vacancies further modulates the nature of active sites, leading to substantial shifts in product selectivity. A detailed investigation on the reaction mechanisms unveils that specific facets preferentially facilitate the formation of CO, while others are more conducive to the generation of hydrocarbons such as CH4 and C2H4, due to the variations in activation barriers and intermediate stabilities. These findings underscore the importance of crystal facet engineering and defect manipulation in tailoring catalyst performance thus providing valuable insights for the rational design of efficient and selective CO2 reduction metal catalysts.

A generalized machine learning framework to estimate fatigue life across materials with minimal data

In this research, a generalized machine learning (ML) framework is proposed to estimate the fatigue life of epoxy polymers and additively manufactured AlSi10Mg alloy materials, leveraging their failure surface void characteristics. An extreme gradient boosting algorithm-based ML framework encompassing Synthetic Minority Over-sampling TEchnique (SMOTE), categorical data encoding, and external loop cross-validation is developed to evaluate the fatigue life across materials. The influence of different training strategies based on materials, input features, encoding method, and data standardization on the model performance is explored. Additionally, the importance of anti-data-leakage and anti-overfitting measures over the ML model performance is addressed. The result shows that the data-leakage-free, external loop cross-validated model can estimate the fatigue life of selective epoxy polymers and metal alloys with an average R2 of 0.71 ± 0.06 using a mere 12 to 27 experimental data points per material category. Whereas the model trained with data-leakage and overfitting results in high R2 of 0.9.

Inherent porosity of Zeolitic Imidazolate Framework-62 melt leading to formation of the porous melt-quenched glass

Porous glasses produced through melt-quenching of some selective metal organic frameworks like Zeolitic Imidazolate Framework-62 (ZIF-62) and ZIF-4 belong to the advanced functional materials because of their inherent porosity, ease of processing, high gas adsorption capacity and gas separation selectivity. We have delineated thermal induced modifications in the porosity features (pore size, size-distribution and pore density) of crystalline ZIF-62 from room temperature (RT) to its melt-state (> melting point, Tm) followed by its quenching, back to RT, carrying out the depth sensitive positron annihilation lifetime spectroscopy (PALS) measurements in-situ at varying temperatures (RT−Tm). On heating under vacuum, the pores' size as well as size-distribution of crystalline ZIF-62 increases up to ∼473 K as a consequence of removal of entrapped solvent molecules and nonuniform thermal expansion. At higher temperatures (∼473 −573 K), a reduction in pores’ size and size-distribution is observed due to the loss of long range ordering and volume collapse. On melting, ZIF-62 turns into a porous liquid having ∼1.4 times larger pores compared to its crystalline form. The quenching of this porous melt is fully irreversible, and results in the formation of a porous glass having the pores larger than its crystalline counterpart. The in-situ PALS investigation provides the first experimental evidence of inherent porosity in ZIF-62 melt existing at high temperature that has been predicted before through molecular dynamics simulation of the ZIFs-based melts.

Robust superhydrophobic copper oxide layer with high-low staggered structure on polymers for strong anti-icing and all-day de-icing

Recently, superhydrophobic materials with photothermal and electrothermal conversion functions have received much attention in solving icing problems. However, the currently emerging methods still suffer from the complexity of the preparation method, poor hydrophobicity, or poor abrasion resistance. Herein, a robust copper oxide layer with a high-low staggered structure was prepared on the polymer surface by laser-induced selective metallization (LISM), which can be used for anti-icing and all-day (daytime and night) de-icing. The high-low staggered structure of the superhydrophobic copper oxide surface gives the surface excellent hydrophobicity, light trapping capability, and high electrical resistance, resulting in the surface with superior delayed icing, photothermal de-icing, and electrothermal de-icing capabilities. The copper oxide layer has a water contact angle (CA) of up to 161.3° and a surface delayed icing time of 1374 s, which is 8.23 times longer than the conventional copper layer prepared by LISM. In addition, the surface temperatures of the copper oxide layer are 67.6 °C and 57.3 °C, respectively, under 1.0 sun irradiation or at 5 V applied voltage. Under these conditions, the copper oxide surface’s photothermal and electrothermal de-icing times are 159 and 186 s. In addition, the high-low staggered structure of the prepared superhydrophobic copper oxide surface makes the surface less susceptible to abrasion, resulting in excellent mechanical robustness of the copper oxide layer surface. The proposed method is suitable for low-cost large-scale manufacturing, which guides the preparation of copper oxide superhydrophobic materials for anti-icing and all-day de-icing, and has good application prospects.

High-Entropy Effect Breaking the Oxo Wall for Selective High-Valent Metal–Oxo Species Generation

High-Entropy Effect Breaking the Oxo Wall for Selective High-Valent Metal–Oxo Species Generation

Cohesive energy discrepancy drives the fabrication of multimetallic atomically dispersed materials for hydrogen evolution reaction

Atomically dispersed single atom (SA) and atomic cluster (AC) metallic materials attract tremendous attentions in various fields. Expanding monometallic SA and AC to multimetallic SA/AC composites opens vast scientific and technological potentials yet exponentially increasing the synthesis difficulty. Here, we present a general energy-selective-clustering methodology to build the largest reported library of carbon supported bi-/multi-metallic SA/AC materials. The discrepancy in cohesive energy results into selective metal clustering thereby driving the symbiosis of multimetallic SA or/and AC. The library includes 23 bimetallic SA/AC composites, and expanded compositional space of 17 trimetallic, quinary-metallic, septenary-metallic SA/AC composites. We chose bimetallic M1SAM2AC to demonstrate the electrocatalysis utility. Unique decoupled active sites and inter-site synergy lead to 8/47 mV overpotential at 10 mA cm−2 for alkaline/acidic hydrogen evolution and over 1000 h durability in water electrolyzer. Moreover, delicate modulations towards composition and configuration yield high-performance catalysts for multiple electrocatalysis systems. Our work broadens the family of atomically dispersed materials from monometallic to multimetallic and provides a platform to explore the complex composition induced unconventional effects.

Sorbent selection for the recovery of gallium and indium from aqueous solutions: a sustainable approach to the recovery of strategic metals from LED lamps.

Gallium and indium, metals present in light-emitting diode (LED) lighting technology, can be effectively recovered from aqueous solutions by sorption. For this purpose, carbonaceous materials, such as activated carbon, or low-cost biosorbents as beer bagasse, spent coffee grounds or peanut shells, and a low-cost zeolite as chabazite, were characterized by BET, FTIR, XRD, and SEM analysis prior use. Protonated chabazite, with high surface area (505m2/g) and a Si/Al molar ratio of 3.4, showed high sorption capacities for gallium (56mg/g) and indium (92mg/g), which is 10 to 30 times higher than those of our carbonaceous materials (T = 298K, pH < 3, dosage = 1g/L). Sorption experiments with both metals in solution showed a competitive effect between gallium and indium for the sorption sites of the chabazite, showing more affinity toward gallium than indium. Ga3+sorbed/In3+sorbed molar ratio above 2 was achieved for the same initial concentration of both metals, increasing to almost 3 when the initial gallium concentration increased, which was appropriate since gallium concentration tends to be higher in LED chips. However, the sorption capacity for both metals was always around 0.35mmol Ga + In/g. The selectivity of the chabazite was conditioned by different behavior of both metals in aqueous solution at the sorption pH (below 3.5) being the predominant species in solution Ga(OH)2+ for gallium and In3+ for indium. Sorption with protonated chabazite can be used in the treatment of spent LEDs leachate for the dual purpose of water purification and selective metal separation.

Bioinspired, Carbohydrate-Containing Polymers Efficiently and Reversibly Sequester Heavy Metals.

Water scarcity and heavy metal pollution are significant challenges in today's industrialized world. Conventional heavy metal remediation methods are often inefficient and energy-intensive, and produce chemical sludge. To address these issues, we developed a bioinspired, carbohydrate-containing polymer system for efficient and selective heavy metal removal. Using ring opening metathesis polymerization, we synthesized polymers bearing amphiphilic glucuronate side chains capable of selectively binding heavy metal cations in mixed media. In samples containing high concentrations of heavy metals (>550 ppb), these polymers rapidly form a filterable precipitate upon metal capture, reducing the concentration of cation to <1.5 ppb within 3 min, as measured by inductively coupled plasma mass spectrometry. This system effectively removes cadmium ions from highly contaminated solutions to levels below the Agency for Toxic Substances and Disease Registry limit for Cd2+ in drinking water and selectively removes both Cd2+ and Pb2+ from lake water spiked with trace amounts of metal. Acidification triggers protonation of the glucuronate groups, releasing the heavy metals and resolubilizing the polymer. This capture-and-release process can be repeated over multiple cycles without loss of binding capacity. As such, this study introduces a novel class of recyclable materials with pH-responsive properties, offering potential for applications in water remediation and beyond.

Regulation of surface oxygen vacancy of Cu-CeO2/TiO2 heterostructures via fast Joule heating method for enhanced CO2 electrochemical reduction

Strict control of carbon emissions is crucial for expediting the achievement of carbon neutrality. However, the current CO2RR electrocatalytic exhibits numerous shortcomings that impede the enhancement of catalytic activity. Issues such as lengthy catalyst preparation times, and high levels of precious metal content. Additionally, the aggregation of ultrafine nanoparticles contributes to a rapid deterioration in catalytic performance. Herein, a Joule-heating method is efficiently utilized to synthesize heterostructures nano-catalysts for CO2 electroreduction on carbon cloth substrates. This method takes advantage of the thermoelectric coupling of the carbon cloth to achieve carbothermal reduction, while also regulating phase composition and introduction of oxygen vacancies. The Cu-CeO2/TiO2/CC catalyst synthesized in this method showed a current density in CO2 of −32 mA·cm−2 at −1.0 V (vs. RHE). Notably, this catalyst demonstrated high CO selectivity and Faraday efficiency (FECO) of up to 82.5 % at a low potential of −0.3 V (vs. RHE). Optimal electrochemical performance is achieved at a power of 40 W. The ultra-fast temperature change process prevented the agglomeration of catalyst particles and facilitated the construction of a stable heterogeneous interface with a high oxygen vacancy concentration. In conclusion, this study presents a promising approach, particularly for the rapid preparation of low-cost, highly selective non-precious metal electrocatalysts.

Emulsion liquid membrane technique for optimal separation of Ni (II) and Sm (III) using response surface methodology and Box–Behnken experimental setup

ABSTRACT This study evaluated the reliability of the emulsified liquid membrane (ELM) extraction technique for recovering and separating metals, focusing on Nickel (Ni(II)) and Samarium (Sm(III)), both used in electrochemical devices. Key contributions include determining optimal conditions for creating a stable water-in-oil (W/O) emulsion. The optimal conditions were found to be a 5-minute emulsification time, 4 wt.% Span 80 surfactant concentration, a 1.6 volume ratio of the internal phase to the organic phase, 1 M H2SO4 concentration for the internal phase, a 40/160 volume ratio of the emulsion to the external phase, and kerosene as the diluent. Factors affecting the separation of Ni(II) and Sm(III) included the concentrations of the internal aqueous phase, surfactant, and extractant. Under these conditions, an equimolar mixture of Ni(II) and Sm(III) was extracted within 15 min. The study emphasized the importance of phase volume ratio and surfactant concentration for emulsion stability and extraction efficiency. The response surface method (RSM) and Box–Behnken design were used to optimize influential factors, with a modified quadratic model predicting extraction yields of 83.81% for Sm(III) and 15% for Ni(II). The study demonstrates that effective separation of Ni(II) and Sm(III) ions is achievable using this technique, providing valuable insights into efficient and selective metal ion extraction, contributing to the broader field of metal recovery and recycling technologies.

Printable, stretchable metal-vapor-desorption layers for high-fidelity patterning in soft, freeform electronics

High-fidelity patterning of thin metal films on arbitrary soft substrates promises integrated circuits and devices that can significantly augment the morphological functionalities of freeform electronics. However, existing patterning methods that decisively rely on prefabricated rigid masks are severely incompatible with myriad surfaces. Here, we report printable, stretchable metal-vapor-desorption layers (s-MVDLs) that can enable high-fidelity patterning of thin metal films on freeform polymeric surfaces. The printed rubbery matrix with highly mobile chains effectively repels various metal vapors from the surface and inhibits their condensation, thereby allowing selective metal deposition. The s-MVDLs are printed by direct ink writing techniques, enabling customizable and scalable thin metal patterns ranging from the micrometer to millimeter scale with high fidelity. Furthermore, the superior stretchability and mechanical robustness of the s-MVDLs allow highly compliant deformation along the substrates, enabling the construction of unconventional circuits and devices on multi-curvature, non-developable, and stretchable surfaces.

Exploring the electronic influence on coordination complexes formed from appended pyrrolidine azothioformamide ligands and copper(I) salts

Redox-active arylazothioformamide (ATF) ligands have seen attention through their unique coordination complexes formed with salts of late transition metals and their known ability to oxidatively dissolve zerovalent metals. When mixed with Cu(I) salts, ATF ligands form both 2:1 and 2:2 coordination complexes remaining neutral without undergoing any redox event. Herein, a series of para-substituted pyrrolidine-ATFs were synthesized, incorporating both electron-donating groups (i.e., -OMe and -Me) as well as electron-withdrawing groups (i.e., -CF3, and -CN). These ligands were then mixed with Cu(I) salts, including CuBr, CuI, and [(CH3CN)4Cu](BF4) to form coordination complexes. The resulting complexes underwent thorough characterization, with several producing X-ray quality crystals for detailed structural analysis. Both strong and weak intermolecular interactions were found through Hirshfeld surface analysis and the redox activity of the complexes was probed using cyclic voltammetry in the voltage range of -1.8 to 1.8 V. Through a UV–Vis titration study, the binding interactions between the ligand host and Cu(I) metal salt guest molecules were determined and ranged from 4,000 – 100,000 M-1. Computational modeling was employed to calculate the change in Gibbs free energy (ΔG) for the formation of the complexes, revealing the optimal orientations between the ligand and the metal. These studies have confirmed that para-substituted pyrrolidine-ATFs containing electron-donating groups exhibit a higher binding affinity towards Cu(I) metal salts compared to those with electron-withdrawing groups. With a thorough understanding of ATF-metal coordination, further ligand design can lead to exciting new catalysts and/or selective metal dissolution agents.

Contrasting metal bioaccumulation in marine benthic invertebrate groups in polluted harbor sediments

This study examined the sediment metal fractions and availability to infer bioaccumulation in marine harbor benthic organisms. Total metals were analyzed using atomic absorption spectrometry and inductively coupled plasma-optical emission spectrometry for chemical fractions and organisms. The results showed similar metal concentrations and distribution driven by rivers and harbor pollution. We found significant differences in metal accumulation in marine benthic groups, highest in scavenger species. Their metal concentrations in decreasing order were 1.97–4568, 0.10–1260, 1.64–159, and 0.105–112 μg g−1 dw for hermit crabs, forams, bivalves, and polychaetes. Moreover, certain organisms, such as tusk shells, sea pens, bivalves, forams, and isopods, may exhibit selective metal accumulation. Biota-sediment accumulation factors (>1) were highest for essential metals like Cu, Zn, and Mn, while toxic metals like As, Cr, Co, and Ni increased. This concurrent assessment provides more comprehensive data for metal bioaccumulation in marine benthic ecosystems.

Molecular Origins of Near-Infrared Luminescence in Molybdenum and Tungsten Oxyhalide Perovskites.

Materials with near-infrared (near-IR) luminescence are desirable for applications in communications and sensing, as well as biomedical diagnostics and imaging. The most used inorganic near-IR emitters rely on precise doping of host crystal structures with select rare-earth or transition metal ions. Recently, another class of materials with intrinsic near-IR emission has been reported. The compositions of these materials were initially described as vacancy-ordered halide double perovskites Cs2MoCl6 and Cs2WCl6, but further investigation by some of us on the compound reported as Cs2WCl6 revealed an oxyhalide instead, with a composition Cs2WO x Cl6-x , where 1 < x < 2. Here we demonstrate that the Mo compounds similarly possess the composition Cs2MoO x Cl6-x or Cs2MoO x Br6-x where 1 < x < 2. Preparing the pure halide appears harder for Mo than for W, and we have not succeeded in doing so. The distinctly different composition requires the coordination environment and oxidation state for the Mo and W centers to be reconsidered from what was assumed for the pure halides. In this work, we examine the mechanism for near-IR emission in these materials given their true structures and compositions. We demonstrate that the luminescence is due to the specific d-orbital splitting caused by the presence of oxygen in the distorted [MOX5]2- octahedra (X is Cl or Br). The fine structure in the emission spectra at low temperatures has been resolved and is attributed to vibronic coupling to the Mo-O and W-O bond stretches. Understanding the true structure and composition of these interesting materials, besides explaining the near-IR luminescence, suggests how this desirable emission can be realized and manipulated.

Selective Lithium Recovery from Spent Lithium Manganate Batteries Using Oxidative Stabilization Technique.

Using oxidizing compounds to handle the recycling of discarded lithium batteries has advanced significantly in recent years. One of the most prominent methods is the sintered electrode powder treatment using pre-used additives, with an aqueous solution of the oxidizing agent fueling highly selective lithium extraction and transition metals retention in the refractory material. Herein, phosphoric acid (H3PO4) was used as the exchanger and hydrogen ions provider, the oxidant (K2S2O8) activity was driven by heating, the raw material structure was deformed and adjusted by the oxidizing drive, and lithium was exhausted, while manganese was converted into manganese(III) phosphate hydrate and manganese dioxide insoluble material. The optimized conditions resulted in a lithium leaching rate of 94.16 % and a separation factor of 95.74 %, while the corresponding manganese leaching rate was limited to less than 5 %. The X-ray diffraction, X-ray spectroscopy, scanning electron microscopy, and inductively coupled plasma mass spectrometry measurements were used to investigate the influence of oxidation driving force and lithium leaching. Finally, the lithium leach solution was continuously stirred with sodium carbonate in boiling water to obtain the precipitate, which was separated and washed several times to obtain high-purity lithium carbonate.