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Selective recovery of pure copper nanopowder from indium-tin-oxide etching wastewater by various wet chemical reduction process: Understanding their chemistry and comparisons of sustainable valorization processes
Sustainable valorization processes for selective recovery of pure copper nanopowder from Indium-Tin-Oxide (ITO) etching wastewater by various wet chemical reduction processes, their chemistry has been investigated and compared. After the indium recovery by solvent extraction from ITO etching wastewater, the same is also an environmental challenge, needs to be treated before disposal. After the indium recovery, ITO etching wastewater contains 6.11 kg/m{sup 3} of copper and 1.35 kg/m{sup 3} of aluminum, pH of the solution is very low converging to 0 and contain a significant amount of chlorine in the media. In this study, pure copper nanopowder was recovered using various reducing reagents by wet chemical reduction and characterized. Different reducing agents like a metallic, an inorganic acid and an organic acid were used to understand reduction behavior of copper in the presence of aluminum in a strong chloride medium of the ITO etching wastewater. The effect of a polymer surfactant Polyvinylpyrrolidone (PVP), which was included to prevent aggregation, to provide dispersion stability and control the size of copper nanopowder was investigated and compared. The developed copper nanopowder recovery techniques are techno-economical feasible processes for commercial production of copper nanopowder in the range of 100–500 nm size from the reported facilities through a one-pot synthesis. By all the process reported pure copper nanopowder can be recovered with>99% efficiency. After the copper recovery, copper concentration in the wastewater reduced to acceptable limit recommended by WHO for wastewater disposal. The process is not only beneficial for recycling of copper, but also helps to address environment challenged posed by ITO etching wastewater. From a complex wastewater, synthesis of pure copper nanopowder using various wet chemical reduction route and their comparison is the novelty of this recovery process. - Highlights: • From the Indium-Tin-Oxide etching wastewater, copper nanopowder was synthesized. • Solution chemistry of ITO etching wastewater is addressed. • A techno-economical feasible, environment friendly and occupational safe process. • Brings back the material to production stream and address the circular economy. • A cradle to cradle technology management lowers the futuristic carbon economy.
Computational framework for modeling membrane processes without process and solution property simplifications
Accurately modeling membrane processes is critical to evaluating novel process configurations, designing scalable membrane systems, informing process cost estimates, and directing future research. Most membrane process models trade accuracy for computational efficiency by employing simplified approximations of the process (i.e. no salt flux, no pressure drop) and solution properties (i.e. ideal solution, and constant density, viscosity, and diffusivity). Our report introduces a detailed one-dimensional finite difference model for evaluating membrane processes that avoids these common simplifications. We apply this model to quantify the error introduced by these simplifications for case studies of reverse osmosis, osmotically assisted reverse osmosis, forward osmosis, and pressure retarded osmosis. While the magnitude of error introduced by these simplifications is reliant on the case study parameters and specifications, we find that existing model formulations can underestimate or overestimate average water flux by nearly 50% for some membrane processes operating under standard conditions. Lastly we investigate the error introduced by simplified inlet-outlet models that do not solve the governing system of differential equations, and we assess the accuracy of novel inlet-outlet formulations that use a log and geometric mean, instead of the typical arithmetic mean, to represent non-linear water flux profiles.
Passivation of In{sub 0.53}Ga{sub 0.47}As/ZrO{sub 2} interfaces by AlN atomic layer deposition process
Reducing defects at III-V/high-k interfaces is essential for optimizing devices built on these materials. Here, the role of an interfacial AlN process at In{sub 0.53}Ga{sub 0.47}As/ZrO{sub 2} interfaces is investigated by hard x-ray photoelectron spectroscopy (HAXPES) and capacitance/voltage (C-V) measurements. C-V measurements show a significant reduction in the density of interface traps with the interfacial AlN process and a capping TiN layer. To elucidate the specific role of the AlN process, blanket films with various deposition processes are compared. The AlN process alone (without subsequent dielectric deposition) reduces InGaAs oxide levels below the HAXPES detection limit, even though the AlN is ultimately found to be oxidized into AlO{sub x} with only trace N incorporation, yet AlN passivation provides a lower D{sub it} (density of interface traps) when compared with an H{sub 2}O-based Al{sub 2}O{sub 3} deposition. The AlN process does not passivate against re-oxidation of the InGaAs during an O{sub 3} based ZrO{sub 2} deposition process, but it does provide passivation against As-As development during subsequent TiN deposition. The role of chemical defects in the C-V characteristics is also discussed.
Simulative design and process optimization of the two-stage stretch-blow molding process
The total production costs of PET bottles are significantly affected by the costs of raw material. Approximately 70 % of the total costs are spent for the raw material. Therefore, stretch-blow molding industry intends to reduce the total production costs by an optimized material efficiency. However, there is often a trade-off between an optimized material efficiency and required product properties. Due to a multitude of complex boundary conditions, the design process of new stretch-blow molded products is still a challenging task and is often based on empirical knowledge. Application of current CAE-tools supports the design process by reducing development time and costs. This paper describes an approach to determine optimized preform geometry and corresponding process parameters iteratively. The wall thickness distribution and the local stretch ratios of the blown bottle are calculated in a three-dimensional process simulation. Thereby, the wall thickness distribution is correlated with an objective function and preform geometry as well as process parameters are varied by an optimization algorithm. Taking into account the correlation between material usage, process history and resulting product properties, integrative coupled simulation steps, e.g. structural analyses or barrier simulations, are performed. The approach is applied on a 0.5 liter PET bottle of Krones AG, Neutraubling, Germany. The investigations point out that the design process can be supported by applying this simulative optimization approach. In an optimization study the total bottle weight is reduced from 18.5 g to 15.5 g. The validation of the computed results is in progress.
A novel process for production of spherical PBT powders and their processing behavior during laser beam melting
Additive manufacturing processes like laser beam melting of polymers are established for production of prototypes and individualized parts. The transfer to other areas of application and to serial production is currently hindered by the limited availability of polymer powders with good processability. Within this contribution a novel process route for the production of spherical polymer micron-sized particles of good flowability has been established and applied to produce polybutylene terephthalate (PBT) powders. Moreover, the applicability of the PBT powders in selective laser beam melting and the dependencies of process parameters on device properties will be outlined. First, polymer micro particles are produced by a novel wet grinding method. To improve the flowability the produced particles the particle shape is optimized by rounding in a heated downer reactor. A further improvement of flowability of the cohesive spherical PBT particles is realized by dry coating. An improvement of flowability by a factor of about 5 is achieved by subsequent rounding of the comminution product and dry-coating as proven by tensile strength measurements of the powders. The produced PBT powders were characterized with respect to their processability. Therefore thermal, rheological, optical and bulk properties were analyzed. Based on these investigations a range of processing parameters was derived. Parameter studies on thin layers, produced in a selective laser melting system, were conducted. Hence appropriate parameters for processing the PBT powders by laser beam melting, like building chamber temperature, scan speed and laser power have been identified.
Effect of HEH[EHP] impurities on the ALSEP solvent extraction process
In solvent extraction processes, organic phase impurities can negatively impact separation factors, hydrolytic performance, and overall system robustness. The resulting inconsistent performance can affect the process-level viability of a separation concept, and thus knowledge of the impurities present, their effects on the process, and how to remove them are vital. Deleterious impurities may be introduced into a system from reagent synthesis, or result from degradation via radiolysis and hydrolysis during use. In this work, the acidic extractant, 2-ethylhexylphosphonic acid mono-2-ethylhexyl ester (HEH[EHP])—proposed for application in extractive processes aimed at separating trivalent minor actinides from lanthanides and other fission products—is characterized with respect to its common impurities and their impact on Am(III) stripping in the Actinide Lanthanide SEParation (ALSEP) system. Furthermore, to control impurities in HEH[EHP], existing purification technologies commonly applied for the acidic organophosphorus reagent were assessed and a new chromatographic purification method specific to HEH[EHP] is presented.
Westinghouse modular grinding process - improvement for follow on processes
In nuclear power plants (NPP) ion exchange (IX) resins are used in several systems for water treatment. The resins can be in bead or powdered form. For waste treatment of spent IX resins, two methods are basically used: Direct immobilization (e.g. with cement, bitumen, polymer or High Integrity Container (HIC)); Thermal treatment (e.g. drying, oxidation or pyrolysis). Bead resins have some properties (e.g. particle size and density) that can have negative impacts on following waste treatment processes. Negative impacts could be: Floatation of bead resins in cementation process; Sedimentation in pipeline during transportation; Poor compaction properties for Hot Resin Supercompaction (HRSC). Reducing the particle size of the bead resins can have beneficial effects enhancing further treatment processes and overcoming prior mentioned effects. Westinghouse Electric Company has developed a modular grinding process to crush/grind the bead resins. This modular process is designed for flexible use and enables a selective adjustment of particle size to tailor the grinding system to the customer needs. The system can be equipped with a crusher integrated in the process tank and if necessary a colloid mill. The crusher reduces the bead resins particle size and converts the bead resins to a pump able suspension with lower sedimentation properties. With the colloid mill the resins can be ground to a powder. Compared to existing grinding systems this equipment is designed to minimize radiation exposure of the worker during operation and maintenance. Using the crushed and/or ground bead resins has several beneficial effects like facilitating cementation process and recipe development, enhancing oxidation of resins, improving the Hot Resin Supercompaction volume reduction performance. (authors)
Effect of fiber reinforcement on the process parameters of injection molding manufacturing process
Use of fillers with the resin is common in injection molding manufacturing technique to enhance the stiffness and strength of the manufactured components. However, the addition of fillers changes the rheological and mechanical properties of the material, required adjustments in the process parameters used for the manufacturing. The present study aims to investigate this impact of fillers on the process parameters of the injection molding manufacturing process. Neat Acrylonitrile Butadiene Styrene (ABS) and ABS reinforced with short glass fibers are used as the materials to perform the comprehensive numerical analysis including complete process sequence, namely filling, packing, cooling and warpage. Parametric studies are conducted to optimize the manufacturing process for minimal warpage (or shrinkage) in the produced part. The selected process parameters for the parametric study include cooling time, packing pressure, and mold temperature, all of which directly impact the quality of the manufactured parts. The optimal values obtained for these parameters are compared to examine the effect fiber reinforcement has on the manufacturing process.
Permanganate Oxidation of Defense Waste Processing Facility (DWPF) Recycle Collection Tank (RCT) Simulants – Protocol Runs for Nominal and Chemical Process Cell (CPC) Foamover Conditions
Savannah River National Laboratory (SRNL) has completed a work scope in support of the Savannah River Remediation (SRR) Nitric-Glycolic flowsheet. Glycolic acid will replace formic acid as a reducing agent in the pre-processing of High-Level Waste sludge performed at the Defense Waste Processing Facility (DWPF). Glycolic acid will perform the same function as formic acid, namely reduction of mercury and adjustment of feed rheology and melter oxidation/reduction potential, while significantly reducing the potential for hydrogen generation in DWPF processing. Development testing has demonstrated glycolic acid virtually eliminates hydrogen production in the pre-processing steps. The Nitric-Glycolic flowsheet significantly improves DWPF’s ability to address one of the Savannah River Site’s key challenges - the incorporation of effluent received from the Salt Waste Processing Facility (SWPF). SWPF will deliver significant effluent volume to DWPF, resulting in a concurrent increase in DWPF effluent returned to the Concentration, Storage and Transfer Facilities (CSTF). This work scope demonstrates that glycolate can be destroyed under the Nitric-Glycolic flowsheet prior to returning the DWPF recycle stream to CSTF. To avoid potential flammability issues due to thermolysis of glycolate in CSTF, SRR tasked SRNL to quantify and mitigate glycolate returns via DWPF’s recycle stream. The development of a strategy for glycolic mitigation was initiated with a system’s engineering workshop. Various chemical and/or physical solutions for how and where to destroy glycolate were considered – consistent with DWPF’s operational capabilities and process requirements. The workshop identified chemical oxidation of glycolate within the DWPF Recycle Collection Tank (RCT) as the most promising option. (The RCT collects offgas condensate from pre-processing, vitrification, and other unit operations performed in DWPF and is the singular return vessel delivering recycle effluent back to CSTF.) A series of down-select experimental tests were performed that showed sodium permanganate was the most effective oxidant. This work was performed to identify an appropriate operational protocol for DWPF implementation. Building upon the downselect experiments, the work targeted an improved description of suitable RCT conditions prior to the strike (pH, etc.), permanganate addition rate, and destruction reaction kinetics. Data collected were also used to determine the best expression of reaction stoichiometry and the effective minimum permanganate addition required.
Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)
This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.
Actinide-rich and Actinide-poor r -process-enhanced Metal-poor Stars Do Not Require Separate r -process Progenitors
The astrophysical production site of the heaviest elements in the universe remains a mystery. Incorporating heavy-element signatures of metal-poor, $r$-process-enhanced stars into theoretical studies of $r$-process production can offer crucial constraints on the origin of heavy elements. In this study, we introduce and apply the "actinide-dilution with matching" model to a variety of stellar groups, ranging from actinide-deficient to actinide-enhanced, to empirically characterize r-process ejecta mass as a function of electron fraction. We find that actinide-boost stars do not indicate the need for a unique and separate $r$-process progenitor. Rather, small variations of neutron richness within the same type of $r$-process event can account for all observed levels of actinide enhancements. The very low-$Y_e$ , fission-cycling ejecta of an $r$-process event need only constitute 10%–30% of the total ejecta mass to accommodate most actinide abundances of metal-poor stars. We find that our empirical $Y_e$ distributions of ejecta are similar to those inferred from studies of GW170817 mass ejecta ratios, which is consistent with neutron-star mergers being a source of the heavy elements in metal-poor, $r$-process-enhanced stars.
Study on a regeneration process of LiCl-KCl eutectic based waste salt generated from the pyrochemical process
A regeneration process of LiCl-KCl eutectic waste salt generated from the pyrochemical process of spent nuclear fuel has been studied. This regeneration process is composed of a chemical conversion process and a vacuum distillation process. Through the regeneration process, a high efficiency of renewable salt recovery can be obtained from the waste salt and rare earth nuclides in the waste salt can be separated as oxide or phosphate forms. Thus, the regeneration process can contribute greatly to a reduction of the waste volume and a creation of durable final waste forms. (authors)
Techno-economic analysis of biomass value-added processing informed by pilot scale de-ashing of paper sludge feedstock
Paper sludge biomass represents an underutilized feedstock rich in pulped and processed cellulose which is currently a waste stream with significant disposal cost to industry for landfilling services. Effective fractionation of the cellulose from paper sludge presents an opportunity to yield cellulose as feedstock for value-added processes. A novel approach to cellulose fractionation is the sidehill screening system, herein studied at the pilot-plant scale. Composition analysis determined ash removal and carbohydrate retention of both sidehill and high-performance benchtop screening systems. Sidehill screening resulted in greater carbohydrates retention relative to benchtop screening (90% vs 66%) and similar ash removal (95% vs 98%). Techno-economic analysis for production of sugar syrup yielded a minimum selling price of $331/metric ton of sugar syrup including disposal savings, significantly less than a commercial sugar syrup without fractionation. Furthermore, sensitivity analysis showed that screening conditions played a significant role in economic feasibility for cellulosic yield and downstream processes.
Heterogeneous recurrence monitoring and control of nonlinear stochastic processes
Recurrence is one of the most common phenomena in natural and engineering systems. Process monitoring of dynamic transitions in nonlinear and nonstationary systems is more concerned with aperiodic recurrences and recurrence variations. However, little has been done to investigate the heterogeneous recurrence variations and link with the objectives of process monitoring and anomaly detection. Notably, nonlinear recurrence methodologies are based on homogeneous recurrences, which treat all recurrence states in the same way as black dots, and non-recurrence is white in recurrence plots. Heterogeneous recurrences are more concerned about the variations of recurrence states in terms of state properties (e.g., values and relative locations) and the evolving dynamics (e.g., sequential state transitions). This paper presents a novel approach of heterogeneous recurrence analysis that utilizes a new fractal representation to delineate heterogeneous recurrence states in multiple scales, including the recurrences of both single states and multi-state sequences. Further, we developed a new set of heterogeneous recurrence quantifiers that are extracted from fractal representation in the transformed space. To that end, we integrated multivariate statistical control charts with heterogeneous recurrence analysis to simultaneously monitor two or more related quantifiers. Experimental results on nonlinear stochastic processes show that the proposed approach not only captures heterogeneous recurrence patterns in the fractal representation but also effectively monitors the changes in the dynamics of a complex system.
Process Scale-Up of an Energy-Efficient Membrane Solvent Extraction Process for Rare Earth Recycling from Electronic Wastes
This study reports the process scale-up and long-term performance of an energy-efficient and cost-effective membrane solvent extraction (MSX) process for separation and recovery of high purity rare earth oxides (REOs) from scrap permanent magnets (SPMs). Here, the rare earth elements (REEs), including dysprosium, neodymium, and praseodymium, are recovered from SPMs using a neutral extractant, tetraoctyl diglycolamide (TODGA) embedded in a microporous polypropylene hollow fiber membrane module. The MSX process performance is demonstrated with bench scale module with membrane surface area of 1.4 m 2 to industrial scale modules with membrane surface area of up to 20 m2 to enable the processing of up to 1 ton month –1 of SPMs. The purity and the yield of the recovered REOs are >99.5 wt% and >95%, respectively. The average extraction rate of REOs is >10 g m –2 hr –1 . A skid of MSX system is assembled with a membrane area of 40 m 2 . The MSX skid successfully recovers REOs with a capacity of 300 kg REOs/month. Finally, it is determined that the organic phase containing the extractant maintains its performance up to 250 h. The results suggest that the MSX process is an economically viable and environmentally friendly process for separation and recovery of REOs from electronic wastes.
Multimodal Analysis of Spatially Heterogeneous Microstructural Refinement and Softening Mechanisms in Three-Pass Friction Stir Processed Al4Si Alloy
Multiple thermally and thermomechanically induced microstructural refinement mechanisms can be activated in metallic alloys when subjected to solid phase processing methods such as friction stir processing (FSP). In this work, we provide detailed descriptions of the relationship between region-specific microstructural refinement mechanisms and the variation in microhardness, through a systematic and multimodal microstructural characterization of an FSP-processed 75% cold-rolled Al-4 at.% Si model binary alloy. Spatially resolved high-energy synchrotron X-ray diffraction, electron backscattered diffraction, and scanning transmission electron microscopy were used to understand the spatially heterogeneous microstructural evolution due to FSP. Results provide insights into how mechanisms such as static recovery, static recrystallization, dynamic recovery and recrystallization, geometric and continuous dynamic recrystallization, and particle-stimulated static or dynamic grain nucleation may occur heterogeneously in the microstructure as a function of the distance from the stir zone in processed alloys, directly influencing the degree of softening. The systematic analysis of microstructures and hardness in the FSP-processed model binary alloy given in this work highlights the rich microstructural domains that can be uniquely harnessed through solid phase processing of metallic alloys.
Accelerated simulation of stochastic particle removal processes in particle-resolved aerosol models
Stochastic particle-resolved methods have proven useful for simulating multi-dimensional systems such as composition-resolved aerosol size distributions. While particle-resolved methods have substantial benefits for highly detailed simulations, these techniques suffer from high computational cost, motivating efforts to improve their algorithmic efficiency. Here we formulate an algorithm for accelerating particle removal processes by aggregating particles of similar size into bins. We present the Binned Algorithm for particle removal processes and analyze its performance with application to the atmospherically relevant process of aerosol dry deposition. We show that the Binned Algorithm can dramatically improve the efficiency of particle removals, particularly for low removal rates, and that computational cost is reduced without introducing additional error. In simulations of aerosol particle removal by dry deposition in atmospherically relevant conditions, we demonstrate about 50-times increase in algorithm efficiency.