Scrap Research Articles

Deep eutectic solvent microemulsions with abundant hydrogen ions in supercritical CO2 for decontamination of radioactive solid waste: Overcoming roadblocks to hydrogen ions deficiency

Deep eutectic solvents (DESs) dispersed in supercritical CO2 (SC-CO2) as microemulsions have shown promise for the removal of radioactive contaminants from solid surfaces. However, the current technology needs urgent improvement in terms of decontamination performance. This study reported a novel strategy to enhance the decontamination ability of DESs-in-CO2 systems by adding hydrogen ion (H+) supplemental reagents. The type and acidity of the added H+ reagents were found to be critical factors in dictating the decontamination performance. For instance, fluorinated carboxylic acids with higher acidity and higher CO2 affinity were more competitive for decontamination compared to other non-fluorinated carboxylic acids. Additionally, when nitric acid was used as the H+ supplemental reagent for microemulsions in SC-CO2, outstanding decontamination results were achieved. It could remove 99 % of UO3 contaminants on the specimen surfaces. The formation of microemulsions was demonstrated by molecular dynamics (MD) simulations. Meanwhile, low-cost nitric acid was more promising for scale-up applications. Remarkably, the versatility of the decontamination technology with the addition of nitric acid was demonstrated by its ability to completely decontaminate multiple radioactive wastes made of various materials, as well as different simulated radionuclides. Decontamination efficiency reached more than 99.0 %. More importantly, the DESs-in-CO2 systems with nitric acid also reduced the radioactivity of real radioactive metal waste to the clearance level with the decontamination efficiency reaching 99.0 %. Overall, this study provided valuable insights into the design of advanced decontamination technologies based on microemulsions of DESs in SC-CO2 and opened new avenues for the sustainable management of radioactive waste.

Analysis of the scrap pre-heating inside an EOF steel refining furnace

In the present work a full-scale mathematical model of the gaseous flow and the thermal exchange of gases with the scrap were proposed in the exhaust system of an Energy Optimizing Furnace (EOF). The analysis of the flow and heat transfer of the gases in the exhaust system is fundamental to predict the thermal use in the pre-heating of the scrap and the best scrap allocation profile in the system to predict the continuity of the current industrial process. The objective of this work is to improve the overall energy efficiency of the EOF process, thereby reducing the direct and indirect emission of gases that contribute to climate change. Industrial tests were carried out to obtain the real values of the variables such as gas and scrap temperature. The results of the variables were used in the mathematical model. The results of the mathematical modelling demonstrated that the heat transfer between the gases and the metal scrap depends mainly on the previous preparation in the scrap yard and on the control of the size and compaction of the scrap. In this work it was possible to predict the variables of gas flow and scrap pre-heating during the steel production process in the EOF using mathematical simulation and validating with the results collected in the industrial furnace.

An Efficient and Accurate Quality Inspection Model for Steel Scraps Based on Dense Small-Target Detection

Scrap steel serves as the primary alternative raw material to iron ore, exerting a significant impact on production costs for steel enterprises. With the annual growth in scrap resources, concerns regarding traditional manual inspection methods, including issues of fairness and safety, gain increasing prominence. Enhancing scrap inspection processes through digital technology is imperative. In response to these concerns, we developed CNIL-Net, a scrap-quality inspection network model based on object detection, and trained and validated it using images obtained during the scrap inspection process. Initially, we deployed a multi-camera integrated system at a steel plant for acquiring scrap images of diverse types, which were subsequently annotated and employed for constructing an enhanced scrap dataset. Then, we enhanced the YOLOv5 model to improve the detection of small-target scraps in inspection scenarios. This was achieved by adding a small-object detection layer (P2) and streamlining the model through the removal of detection layer P5, resulting in the development of a novel three-layer detection network structure termed the Improved Layer (IL) model. A Coordinate Attention mechanism was incorporated into the network to dynamically learn feature weights from various positions, thereby improving the discernment of scrap features. Substituting the traditional non-maximum suppression algorithm (NMS) with Soft-NMS enhanced detection accuracy in dense and overlapping scrap scenarios, thereby mitigating instances of missed detections. Finally, the model underwent training and validation utilizing the augmented dataset of scraps. Throughout this phase, assessments encompassed metrics like mAP, number of network layers, parameters, and inference duration. Experimental findings illustrate that the developed CNIL-Net scrap-quality inspection network model boosted the average precision across all categories from 88.8% to 96.5%. Compared to manual inspection, it demonstrates notable advantages in accuracy and detection speed, rendering it well suited for real-world deployment and addressing issues in scrap inspection like real-time processing and fairness.

Green Urban

Green Urban is a sustainable waste management system offering a shopping section where users can buy daily items focused on pollution prevention and plastic alternatives. Users can sell scrap metal and other recyclable products for a fair price or receive purchase discounts, and they can pre-order pickup dates. Sewage and kitchen waste collection are offered as part of a fully automated subscription plan. To encourage purchases and usage, users earn reward points. The system includes a delivery agent module and a delivery boy module to facilitate the transportation of goods to warehouses and scrapyards, ensuring efficient waste management and recycling processes

Comparative Study of Heat Transfer Simulation and Effects of Different Scrap Steel Preheating Methods

The materials charged into a converter comprise molten iron and scrap steel. Adjusting the ratio by increasing scrap steel and decreasing molten iron is a steelmaking raw material strategy designed specifically for China’s unique circumstances, with the goal of lowering carbon emissions. To maintain the converter tapping temperature, scrap must be preheated to provide additional heat. Current scrap preheating predominantly utilizes horizontal tunnel furnaces, resulting in high energy consumption and low efficiency. To address these issues, a three-stage shaft furnace for scrap preheating was designed, and Fluent software was used to compare and study the preheating efficiency of the new three-stage furnace against the traditional horizontal furnace under various operational conditions. Initially, a three-dimensional transient multi-field coupling model was developed for two scrap preheating scenarios, examining the effects of both furnaces on scrap surface and core temperatures across varying preheating durations and gas velocities. Simulation results indicate that, under identical gas heat consumption conditions, scrap achieves markedly higher final temperatures in the shaft furnace compared to the horizontal furnace, with scrap surface and core temperatures increasing notably with extended preheating times and higher gas velocities, albeit with a gradual decrease in heating rate as the scrap temperature rises. At a gas velocity of 9 m/s and a preheating time of 600 s, the shaft furnace achieves the highest waste heat utilization rate for scrap, with scrap averaging 325 °C higher than in the horizontal furnace, absorbing an additional 202 MJ of heat per ton. In the horizontal preheating furnace, scrap steel exhibits a heat absorption efficiency of 35%, whereas in the vertical furnace, this efficiency increases notably to 63%. In the vertical furnace, the waste heat recovery rate of scrap steel reaches 57%.

Distribution, occurrence, and environmental risks of heavy metals in hazardous waste: A regional study in Beijing, China

Distribution, occurrence, and environmental risks of heavy metals in hazardous waste: A regional study in Beijing, China

Mechanical Properties and Microanalytical Study of Concrete Reinforced with Blended Corn Straw and Scrap Steel Fibers.

Fiber concrete exhibits superior performance in various aspects compared to plain concrete and has been widely researched and applied worldwide. However, many industrially made fibers are expensive, and their cost has to be considered before use; thus, it would be economically valuable to find inexpensive fibers with excellent properties to make fiber concrete. Rural areas have many rich straw resources to be disposed of; at the same time, the rapid development of the automobile industry has introduced a large number of used tires containing steel wire with a very low reuse rate. These two low-cost materials can be processed to make fibers, making the study of mechanical properties regarding their incorporation into concrete practically significant for reducing the cost of fiber concrete. Based on this, a three-factor, three-level orthogonal test was conducted to investigate the effects of different dosages of corn straw fibers and scrap steel fibers, as well as the water-cement ratio, on the mechanical properties of concrete. The optimum level of each factor for blended straw-waste-steel-fiber concrete with different mechanical properties was obtained using the polar and ANOVA methods. It was found that the compressive strength, splitting tensile strength, flexural strength, and impact resistance of the specimens after fiber dosing were better than those of plain concrete specimens with the same water-cement ratio. The maximum improvement was 14.96% in cubic compressive strength, 42.90% in tensile strength, and 16.30% in flexural strength, while the maximum improvement in impact energy consumption at the final crack was 228.03%. Combined with SEM microanalysis, the two fibers formed a stronger whole with the C-S-H gel. When the specimen was subjected to load, the two fibers were able to withstand part of the load, thus enhancing the load-bearing capacity. Finally, the optimal mix ratio of blended straw-scrap-steel-fiber concrete was determined to be 0.8% corn straw fibers by volume, 0.6% scrap steel fibers by volume, and a 0.45 water-cement ratio by combining the weights of the levels of each factor under its four different mechanical properties through hierarchical analysis. This analysis of mechanical properties provides a reference for practical applications in future projects.

Hierarchical V2O3 spiny hollow nanosphere for efficient adsorption of precious metal ions in complicated matrices

Treatment of precious metals in electronic waste has attracted tremendous attention and is essential for both environmental protection and resource sustainable development. In this study, a novel adsorbent for precious metal ions, V2O3 spiny hollow nanospheres (p-V2O3 SHN), was synthesized through a one-step hydrothermal-assisted methodology for the adsorption of Au(III), Ag(I), Pd(II), and Pt(IV) from the leaching solution of electronic waste. The results reveal that the p-V2O3 SHN hierarchy was successfully constructed with a hollow structure and dense spiny morphology. The prepared p-V2O3 SHN can effectively remove precious metal ions such as Au(III), Ag(I), Pd(II), and Pt(IV), with the selective capture order being Au(III) > Ag(I) > Pt(IV) > Pd(II) > other metal ions. This superior adsorption capability can be attributed to the multi-diffusible, intermingled composition, and numerous active sites decorating the p-V2O3 SHN hierarchy, facilitating the uptake of Au(III), Ag(I), Pd(II), and Pt(IV) ions from electronic waste. The Langmuir model provided a better fit for the uptake process, revealing maximum uptake capacities of 833.33 mg/g for Au(III), 370.37 mg/g for Ag(I), 77.51 mg/g for Pd(II), and 42.01 mg/g for Pt(IV) on p-V2O3 SHN. Remarkably, p-V2O3 SHN exhibited a robust affinity for the adsorbate due to the presence of surface defects and reduction. The new p-V2O3 SHN also demonstrated good reusability for three sorption cycles, highlighting its potential for electronic waste treatment. Due to its facile synthesis and excellent efficiency, hierarchical p-V2O3 SHN presents itself as a promising candidate for the selective uptake of Au(III), Ag(I), Pt(IV), and Pd(II) from electronic waste.

Preparation and Optimization of Polyaniline/ Titanium Dioxide/ Carboxymethyl Cellulose Powder for Effective Nickel Adsorption

Hexanoic acid-doped polyaniline (PAni) is a great potential candidate to replace conventional adsorbent towards the removal of heavy metal waste from electroplating industry, especially nickel (Ni). In this study, different weight % (wt %) of titanium dioxide (TiO2) and carboxymethyl cellulose (CMC) are added to form PAni composites with enhanced Ni removal efficiency. All the synthesized samples were examined with FTIR, UV-Vis, conductivity measurement, XRD, TGA, and FESEM to confirm their chemical structures, oxidation states, electrical conductivity, crystallinity and incorporation of metal oxide, thermal stability, and surface morphology, respectively. Among the different samples, PAni / TiO2 20 % exhibited the highest Ni removal efficiency of 37.5 %. Upon further addition of CMC, PAni / TiO2 / CMC 5 % showed the highest Ni removal efficiency of 89.08 %. Optimization of the experimental parameters were conducted and a maximum Ni removal efficiency of 97.88 % was achieved at pH 10, 30 min contact time at a temperature of 30 °C, and with an adsorbent dosage of 0.01 g. This study shows that the composite of PAni / TiO2 / CMC 5 % shows good potential to be applied as adsorbent of the removal of Ni ions.

Improving urban waste management: A comprehensive study on household waste generation and spatial patterns in the Grand Guayaquil Metropolitan Area.

This study tackles the growing global concern about municipal waste management, particularly in cities like the Grand Guayaquil Metropolitan Area (GGA). Through realistic field studies on in situ household waste generation and geographic information system (GIS) tools, this work offers a framework to predict the quantities and types of recyclable household waste for any metropolitan area in Latin America. Over 4 weeks, students collected, sorted and weighed recyclable waste types, including plastic, paper, metal, glass and fabric, from 776 sampled household of the GGA. ArcGIS survey tool identified household locations and allowed to survey different socio-demographic features. With the help of ArcGIS interpolation method, the total household waste generation for GGA was predicted, and the classification of the different types of recyclable waste was also spatially distributed for the study area. The report identified notable trends in plastic waste, specifically polyethylene terephthalate waste's steady prevalence and 42% growth rate, emphasizing the importance of enhanced recycling techniques. Spatial density maps showed a heterogeneous waste distribution across the GGA, emphasizing locations with higher waste output. This study demonstrates that improving recyclable waste collection can be accomplished with a moderately cheap expenditure by collaborating with academia to overcome knowledge gaps. This strategy provides opportunities to mitigate the environmental impacts of poor waste management.

Engineering Single‐Atom Catalysts on Conjugated Porphyrin Polymer Photocatalysts via E‐Waste for Sustainable Photocatalysis

AbstractThis study presents a surface engineering strategy utilizing electronic waste (e‐waste) to incorporate single‐atom catalysts on conjugated polymers. Employing a conjugated porphyrin polymeric photocatalyst, gold single‐atom‐site catalysts are successfully introduced using the acidic metal leachates from e‐waste, where metal speciation and composition are regulated during the metal loading processes. The resulting photocatalyst with gold single atoms demonstrates a remarkable hydrogen peroxide (H2O2) selectivity of up to 97.56%, yielding a pure H2O2 solution at 73.3 µm h−1 under white LED illumination. The produced H2O2 is activated to •OH radicals on the same polymer with mixed gold and iron atoms, enabling a photo‐Fenton reaction and the complete degradation of toxic microcystin‐LR within 10 min under visible light. This study highlights the universal applicability of the metal mining strategy in various photoreactions. It is believed that this discovery pioneers sustainable photocatalysis, allowing the tuning of reactivity and selectivity on photocatalytic surfaces using metal waste.

Effect of Residual Elements during the Hot‐Working Process of Steel Production: A Critical Review

Demand for steel scrap as feedstock for steelmaking increases, allowing the production of steel with lower energy costs and reduced CO2 emissions. In general, steel scrap may contain high levels of undesirable residual elements, which may contribute to processing challenges such as surface hot‐shortness, bulk hot‐shortness, hot‐brittleness, and higher rolling loads during the hot‐working process of steel production. The effect of different residual elements during the hot‐deformation process is a broad topic and involves the understanding of both individual and combined behavior of residual elements for different thermal and mechanical conditions that arise. In this article, the behavior of various residual elements is critically reviewed, individually and synergistically at high temperatures during the hot‐working process (i.e., reheat furnace stage, descaling stage, and deformation stage) of steel production, with a focus on (surface) hot‐shortness, delayed recrystallization, and higher rolling loads caused by the residual elements. Herein, it is aimed to help the steel community to identify challenges and opportunities in efficiently utilizing steel scrap.

Data-driven robust optimization for a sustainable steel supply chain network design: Toward the circular economy

Steel is the indispensable cornerstone of modern life and its remarkable strength and adaptability render it a fundamental pillar of worldwide advancement and economic growth. However, the steel sector faces significant challenges, including the need to incorporate sustainable practices and circular economy principles, especially enhancing occupational safety, optimizing water and energy resource utilization, and effectively utilizing by-products within the steel supply chains. This paper addresses these gaps by presenting a bi-objective data-driven optimization model formulated to design a sustainable forward-reverse steel supply chain network. Sustainable development is studied by examining total cost, occupational safety, and environmental impacts of water and energy consumption and transportation system, concurrently. Incorporating circular economy principles, the collection of steel scrap under take-back policies and utilizing steel slag, a by-product of steel production, is considered. To address uncertainties, a data-driven robust optimization method is employed which harnesses historical data to construct a dynamic uncertainty set using support vector clustering. The model is applied to a real case study in the Iranian steel sector. Results demonstrate the effectiveness and robustness of the proposed method, showing that, on average, a 5 % increase in costs correlates with a 7 % improvement in environmental impacts.

Methodology for shielding design and evaluation for container scanners.

There has been an increase in the use of high energy photon beam for container scanners in many countries for multi purposes such as detecting high atomic number materials which might be nuclear materials, drugs, high explosive materials and other contrabands etc. High energy photon beams generally 6 and 9 MV can be used for scanning such materials. However, it is important to ensure that radiation level beyond the container scanner installation is within the permissible dose limit specified by the national competent authority for the protection of public and radiation workers. In this paper, challenges in the biological shielding during the installation of high energy X-ray system for scanning vehicles containing suspected materials are discussed. The purpose of the present study is to develop a methodology for shielding design and evaluation for container scanner installations. The basic concept pertaining to shielding evaluation of radiotherapy installations provided in National Council on Radiation Protection and Measurements (NCRP)/International Atomic Energy Agency (IAEA) reports are referred, and appropriately used to calculate optimized shielding thicknesses requirements for container scanner installation. Workload is estimated based on number of containers scanned, machine ON time and dose rate at 1m. The shielding evaluation includes use of beam stopper in the primary beam, scattering by heterogeneous metallic scrap materials or any other suspected materials contained in the vehicle and their impact on the thickness of shielding walls. A model lay out plan to be used for installation of container scanner is developed. A methodology for shielding evaluation for various protective walls and ceiling of this model is also discussed. The study provides basic requirement for designing a structural room for installing 9MV container scanner from radiological safety view point.

Effectiveness of Activated Carbon from Jackfruit Skin for The Heavy Metal Lead (Pb) Adsorption Using The Langmuir and Freundlich Equations

<p><span lang="EN-US"><strong>ABSTRACT. </strong>Activated carbon is a commonly used medium for adsorption to combat environmental pollution in both water and air. It is produced from plant or plantation waste containing carbon. Jackfruit skin, often considered as plantation waste, contains lignocellulosic compounds and has the potential to be used as active carbon. Activated carbon from jackfruit skin has a good absorption capacity and can absorb heavy metal waste such as lead (Pb). A recent study aimed to evaluate the absorption effectiveness of active carbon from jackfruit skin. The process involved making activated carbon using the pyrolysis method, and then analyzing its lead absorption capacity in lead nitrate solution by varying the weight of the activated carbon (10g, 15g, 20g, 25g, 30g) and the adsorption time in minutes (40, 60, 80, 100, 120). The levels of absorbed lead on activated carbon were tested using Atomic Absorption Spectrophotometry (AAS) at a wavelength of 283.3 nm. The research findings indicate that the </span><span lang="EN">effectiveness of activated carbon absorption reaches 99%</span><span lang="EN-US">, and the appropriate equation model for the adsorption process is the Freundlich isotherm, indicating a multilayer adsorption process.</span></p><p><strong><span lang="EN-US">Keywords:</span></strong></p><p><span lang="EN-US">Adsorption Isotherm, Activated Carbon Jackfruit Skin, Lead (Pb)</span></p>

Efficient separation of cathode materials from aluminum foil by novel low-melting mixture solvent based on choline chloride-xylitol system

Lithium-ion batteries (LIBs) are important energy devices with significant growth and expansion that result in large amounts of metal waste. However, the separation of the cathode materials from aluminum (Al) foil during the recycling of spent LIBs is still challenging due to their strong bonding by polyvinylidene fluoride (PVDF). Herein, a novel low-melting mixture solvent (LoMMS) based on the choline chloride-xylitol system with ow-toxicity, cost-effectiveness, and environmental friendliness was developed for separating the cathode materials from Al foil in LIBs. Under the optimal treatment conditions of a molar ratio of choline chloride to xylitol of 2:1, a reaction temperature of 140 °C, a reaction time of 20 min, and solid-liquid ratio of 16 g/L separation efficiency cathode material reached a maximum of 94.92 %. The mechanistic analysis revealed that the high separation efficiency can be attributed to strong hydrogen bonding provided by choline chloride and xylitol in LoMMS, disrupted PVDF molecular bonding and resulted in deactivation and successful separation of cathode material particles from the aluminum foil. Additionally, scanning electron microscopy examination revealed no changes in the morphologies of the cathode materials, useful for their restoration and reutilization. Overall, the proposed LoMMS method with low-cost and eco-friendly aspects has great potential for recycling spent LIB cathode materials.

CAVITATION EROSION BEHAVIOR OF WC–Co COATINGS ON TURBINE STEEL DEPOSITED BY COLD SPRAY

A renowned hard coating material (WC–Co) has the potential to overcome cavitation erosion (CE) in hydromachinery components. Hydro turbines that employ silt-filled water for electricity generation create a lot of metal waste due to erosion and cavitation caused by the particles. There is an urgent need for repair of hydropower components that have undergone damage due to cavitation. In this investigation, tungsten carbide composite coatings were produced on 13Cr4Ni (CA6NM) stainless steel substrates using the cold spray method. In order to create high-quality coatings, nitrogen was used as the propellant gas. The coating microstructures were characterized by EDS, SEM XRD, and microhardness tests. Cold-sprayed WC–Co-based coatings were exposed to enhance the cavitation erosion resistance of CA6NM steel. Cold spray coating prepared with WC-12/17Co powder has shown excellent wear-resistant properties due to higher hardness and lower porosity.

Insights into alkali and acid-activated volcanic ash-based materials: A review

This review provides a comprehensive study of the fundamentals of the alkaline and acid activation of volcanic ashes (VA), for mainstreaming their use as a conventional feedstock for developing geopolymers and their applications. The low reactivity in an alkaline environment is driven by the low content of the amorphous phase and the low solubility of iron, calcium and magnesium at pH > 12. Nevertheless, techniques such as mechanochemical activation has significantly improved the reactivity and the properties of the resulting products. In the acid phosphate medium, the high solubility of iron, calcium and magnesium ensures good reactivity and a high reaction rate at room temperature. As a result, the engineering properties of acid-phosphate-activated volcanic ash are superior to those of alkali-activated volcanic ash. The resulting materials have great potential for use as binders in concrete design, for the stabilization of compressed earth bricks and for the rapid repair of deteriorated concrete structures. However, significant research is required to fully understand their durability performances, life cycle and techno-economic viability for large-scale utilisation. Further, the limited availability of phosphate resources makes acid activation not a viable route to activate volcanic ash for building purposes. The acid-activated volcanic ash has potential in waste management applications such as nuclear waste or heavy metal encapsulation. Finally, volcanic ash emerges as a promising raw material for developing sustainable building materials through alkali and acid activation. This holds as its exploitation is non-disruptive, and processing requires less energy compared to calcined clay or fly ash.

CLRiuS: Contrastive Learning for intrinsically unordered Steel Scrap

There has been remarkable progress in the field of Deep Learning and Computer Vision, but there is a lack of freely available labeled data, especially when it comes to data for specific industrial applications. However, large volumes of structured, semi-structured and unstructured data are generated in industrial environments, from which meaningful representations can be learned. The effort required for manual labeling is extremely high and can often only be carried out by domain experts. Self-supervised methods have proven their effectiveness in recent years in a wide variety of areas such as natural language processing or computer vision. In contrast to supervised methods, self-supervised techniques are rarely used in real industrial applications. In this paper, we present a self-supervised contrastive learning approach that outperforms existing supervised approaches on the used scrap dataset. We use different types of augmentations to extract the fine-grained structures that are typical for this type of images of intrinsically unordered items. This extracts a wider range of features and encodes more aspects of the input image. This approach makes it possible to learn characteristics from images that are common for applications in the industry, such as quality control. In addition, we show that this self-supervised learning approach can be successfully applied to scene-like images for classification.

Effect of carbon concentration on melting behavior of steel scraps in hot metal baths

Effect of carbon concentration on melting behavior of steel scraps in hot metal baths