Hybrid Process Research Articles

Investigation on deformation and strengthening mechanisms of Al-Zn-Mg-Cu alloy under a hybrid process of cryogenic incremental sheet forming and bake-hardening treatment

Incremental sheet forming process is featured with high flexibility and short manufacturing cycle, which has great potential in customized forming of complex components. However, the formability of high-strength aluminum alloy is still needs to be improved. In this paper, an efficient cryogenic incremental sheet forming (CISF) process combined with bake-hardening (BH) treatment is proposed to achieve excellent formability and strength for Al-Zn-Mg-Cu alloy. First, the effect of different cryogenic temperatures on the formability of Al-Zn-Mg-Cu alloy is investigated and the mechanism of plasticity enhancement during cryogenic incremental sheet forming was revealed. The fracture forming limit lines constructed from different components show a significant increase in the formability of as-quenched Al-Zn-Mg-Cu at −170°C. Specially, when forming cone component with variable wall angle at −170℃, the ultimate forming height is increased by 70.4 % compared with 25℃. The microstructure shows that dislocation cross-slip is suppressed at cryogenic temperatures, and the large number of subgrain structure and uniformly distributed dislocations reflect the improved deformation uniformity at cryogenic temperatures. Second, the effect of cryogenic incremental sheet forming on the strength of Al-Zn-Mg-Cu is explored. The vertical forming force can be increased by 37.4 % at −170°C compared to 25°C, and the components have higher post-forming strength. Moreover, the strengthening response of the components after the combination of cryogenic incremental sheet forming and bake-hardening treatments is investigated. The cryogenic specimens exhibited a rapid bake-hardening response compared to the room temperature specimens. The yield strength increased by 15.4 % to 387.2 MPa after 40 mins of bake-hardening treatment at 180°C. It has been shown that precipitation strengthening and dislocation strengthening are the main strengthening mechanisms during cryogenic incremental sheet forming and bake-hardening treatments. This study reveals the dual enhancement effect during the cryogenic incremental sheet forming process, and proposes an efficient approach which combines cryogenic incremental sheet forming with bake-hardening treatment to manufacture high-performance components.

Spectral channels increase of multi-wavelength visible laser enabled by SHG-SFG hybrid processes

Spectral evolution in nonlinear optical processes, such as second harmonic generation (SHG) and sum frequency generation (SFG), plays a crucial role in multi-wavelength generation through nonlinear frequency conversion. In this study, the enhancement of spectral performance in a multi-wavelength visible laser facilitated by SHG-SFG hybrid processes is proposed and demonstrated, for the first time to our knowledge. An output of up to eleven wavelengths can be achieved using a six-wavelength pump. Theoretical analysis suggests that the increase in spectral channel count is attributed to the SHG-SFG hybrid processes. Additionally, each nonlinear process operates independently without competition under small-signal approximation, validated through temperature variations. This research not only elucidates the mechanism of spectral evolution in hybrid nonlinear processes but also presents a viable method for improving the spectral performance of a multi-wavelength visible light source.

Direct synthesis of nickel oxide nanoparticles from pregnant leach solution by using electrodeionization and Fenton processes in the presence of EDTA

This paper presents the results of a novel study on the direct synthesis of nickel oxide nanoparticles from a synthetic pregnant leach solution (PLS) as a middle stage product of hydrometallurgy process of nickel production. To increase the nickel proportion in the initial PLS, electrodeionization was utilized in the presence of EDTA to form an anionic complex ([Ni-EDTA]2−) with Ni2+ cations, allowing their separation from cobalt cations through the EDI process. Subsequently, the Fenton process was applied to synthesize nickel oxide nanoparticles from the complex containing solution. The proposed hybrid process was conducted in two different modes of one-stage and two-stage EDI process followed by the Fenton process. Different analysis methods including AAS, XRD, FE-SEM, and ICP were used for qualitative and quantitative evaluations. The analyses’ results revealed that by implementing one-stage EDI process followed by Fenton process resulted in producing nickel oxide nanoparticles with an average particle size of 45 nm and purity of about 98 %. Also, it was seen that about 81 % of initial nickel content of the initial PLS was recovered as nickel oxide nanoparticles. In the case of two-stage EDI process, 100 % pure nickel oxide nanoparticles with average size of 55 nm and recovery of 65 % was produced. The results showed that the innovative hybrid EDI/Fenton process can be considered as a promising approach for direct synthesis of high purity nickel oxide nanoparticles from PLS. However, it should be noted that there was a trade-off between purity of nickel oxide and nickel recovery from PLS.

Formation of Hydroxyl Radicals in Advanced Oxidation Processes for the Degradation of Contaminated Organic Matter

Organic compounds in different solutions have caused several pollution problems to the environment and even affected human health. Advanced Oxidation Processes (AOPs) have been effectively used in the decontamination of these types of compounds. Distinct reactive oxygen species (ROS) have been proposed to explain the degradation or mineralization of contaminating organic matter. ROS, such as free radicals (e.g., .OH), superoxide (e.g., .O2 −), and peroxides (e.g., H2O2), are capable of modifying the chemical structure of organic matter and consequently degrade or mineralize it. In this review, the formation of hydroxyl radicals in each AOP, as in a hybrid process, and the methods for quantifying and determining this type of radical are discussed.

Interpretable deep cross networks unveiled common signatures of dysregulated epitranscriptomes across 12 cancer types

Cancer is a complex and multifaceted group of diseases characterized by uncontrolled cell growth that leads to the formation of malignant tumors. Recent studies suggest that N6-methyladenosine (m6A) RNA methylation plays pivotal roles in cancer pathology by influencing various cellular processes. However, the degree to which these mechanisms are shared across different cancer types remains unclear. In this study, we analyzed an expansive array of 167 m6A epitranscriptome profiles covering 12 distinct cancer types and their originating normal tissues. We trained 12 distinct, cancer type-specific interpretable deep cross network models, which successfully distinguish between specific pairs of normal and cancer m6A contexts using integrated information from both the sequences and curated genomic knowledge. Interestingly, cross-cancer type testing indicated the existence of shared genomic patterns across various cancers at the epitranscriptome level. A pan-cancer model was subsequently developed to identify these shared patterns that could not be observed in a single cancer type. Our analysis uncovered, for the first time, a common epitranscriptome signature shared across multiple cancer types, particularly associated with RNA hybridization process and aberrant splicing. This highlights the importance of a comprehensive understanding of the pan-cancer epitranscriptome and holding potential implications in the development of RNA methylation-based therapeutics for various cancers.

Study of Optoelectronic, Magnetic, and Thermoelectric Properties of Sr2XOsO6 (X = Y, Lu, Sc) Double Perovskites for Spintronic and Data Storage Devices

Advancement in electronic device miniaturization coupled with the precise control over their electromagnetic and transport properties, holds great promise for realizing practical quantum computing devices. Double perovskites, known for their stability, non-toxicity, and spin-polarized characteristics, are particularly appealing for spintronics applications. In this communication, we investigate the role of 6d-electrons of Os in regulating the magnetic properties in Sr2XOsO6 (X = Y, Lu, Sc) using theoretical methods with the WIEN2k code. The computed formation energies (-3.04, -2.91, and -2.82 eV) confirm the thermodynamic stability of these compositions. Analysis of the band structures and DOS exhibit ferromagnetic semiconducting character, elucidated through exchange constants and energies. This computation highlights the essential role of basic hybridization processes, crystal field effects, and exchange energy in generating ferromagnetic character driven by electronic spin. The analysis of optical behavior against photon energy (eV) reveals the maximum absorption in the UV region. Furthermore, the calculated values of σ/τ, ke/τ, S, χ, PF, and ZT in the temperature range of 200-800 K highlight the potential of these compounds for thermoelectric applications. This comprehensive analysis underscores the suitability of Sr2XOsO6 (X = Y, Lu, Sc) for advanced electronic and spintronic technologies.

Joining of the functionally gradient friction material to the backing plate for wind turbines using sinter-brazing technique

This study explores the sinter brazing of friction materials to the backing plate, aiming to enhance the bonding strength of the wind turbine mechanical braking system. Sinter brazing, a hybrid process of integrating sintering and brazing in a single heat cycle to offer a robust method for joining friction materials to backing plates under high temperatures. The microstructure establishes the evidence of strong metallurgical bond between the friction material and the backing plate. An average hardness of 133.2HV was obtained at the interface and the shear strength obtained was 74.3 N/mm2.

Ammonia recovery from real biogas slurry in the up-scaled Donnan Dialysis-Osmotic Distillation membrane-based system: Performance and potentials

Recovering ammonia from wastewater is crucial for building a circular economy and achieving carbon neutrality. Some innovative ammonia recovery technologies have shown great potential yet lacking theoretical guidance for up-scaling from laboratory to practical applications. Based on our previously-proposed Donnan dialysis-osmotic distillation (DD-OD) hybrid process for selective ammonia recovery at nearly zero energy input, two challenges as modelling/prediction and product application were solved in this study. Under the guide of the tailor-made mass transfer model, a reasonable design of the reactor and operating parameters was fixed, whose performance in recovering ammonia from real biogas slurry and the feasibility of the recovered product as irrigation water was then investigated. The up-scaled DD-OD reactor achieved efficient and stable ammonia removal and recovery (∼75 % and ∼ 65 %, respectively) and excellent impurity retention efficiency (∼95 %) in 360 h continuous run. Impurities deposited on the cation-exchange membrane did not affect ammonium transfer and were effectively removed by water washing, and no fouling was found for the hydrophobic membrane, highlighting its long-term capability for ammonia recovery. Moreover, the cost-effectiveness of the process was analyzed, which could be greatly improved given the future improved membrane materials. A proper dilution of the recovered product for irrigating cabbage and radish promoted plant growth, recycled product containing a moderate ammonia concentration (136 mg/L) was highlighted and well-rounded, multi-element nutrient profile was recommended. The above results provide theoretical guidance for the scaling-up of ammonia recovery module and a reference basis for the application of recycled products in agricultural irrigation.

Green Approaches to Extractive Metallurgy: A Novel Synthesis of Sustainable Practices

The realm of extractive metallurgy, a cornerstone for diverse industrial applications, has traditionally grappled with environmental challenges stemming from conventional extraction methods. This thorough literature review delves into the realm of innovative green approaches within extractive metallurgy, with the overarching goal of synthesizing sustainable practices. The introduction casts a spotlight on the environmental quandaries associated with traditional metallurgical practices, underscoring the imperative for ecologically friendly alternatives. The research methodology meticulously entails a comprehensive review of peer-reviewed literature, applying stringent criteria to handpick studies that delve into sustainable metallurgical practices. The results and discussion section intricately categorizes and dissects an array of green approaches in metal extraction, including bioleaching, ionic liquids, supercritical fluid extraction, green hydrometallurgy, electrochemical methods, and hybrid processes, providing nuanced insights into their efficacy and sustainability. Through the lens of case studies, the study sheds light on recent strides made by industries that have wholeheartedly embraced these sustainable practices, with a keen focus on unraveling their consequential environmental and economic impacts. Moreover, the study conscientiously addresses the challenges encountered in the adoption of green metallurgy and adeptly identifies latent opportunities for further development in this transformative field. The findings resonate with a resounding call for the widespread adoption of sustainable practices within extractive metallurgy, emphasizing their profound implications for both industrial application and the trajectory of future research endeavors. This expanded exploration underscores the pivotal role of environmentally conscious approaches in reshaping the landscape of extractive metallurgy, paving the way for a more sustainable and responsible future.

Toxicological assessment of reactive blue 19 dye aqueous solutions under UV-LED light

Abstract The dye-contaminated industrial effluent causes serious health issues when it gets mixed with underground water without primary treatment. The current project was designed to treat reactive blue-19 dye aqueous solutions in the presence of hydrogen peroxide (H2O2) and titanium dioxide (TiO2) under UV-LED light. The characterization of the photocatalyst was carried out via X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM) for structure, purity, and surface study. The effect of various factors such as pH, TiO2 dose, UV-LED light exposure time, H2O2, and dye concentration, on the degradation rate and cytotoxicity reduction was evaluated and optimized through the Response Surface Methodology (RSM). The maximum degradation of dye solution and chemical oxygen demand (COD) reduction was achieved at 98.81 and 86.22 %, respectively for 50 ppm solution, using UV-LED/H2O2(3 %)/TiO2(6 g/L) hybrid process. The toxicity evaluation through the Allium cepa test demonstrated a 62.40, 65.2, and 56.97 % increase in root length (RL), root count (RC), and mitotic index (MI), respectively, following treatment with the UV-LED/H₂O₂/TiO₂ combined process for 150 min. The hemolytic and brine shrimp tests revealed a reduction in toxicity up to 92.18 and 84.08 %, respectively, after applying the same treatment. Additionally, the Ames test indicated up to 80.94 % reduction in mutagenicity for TA98 and an 84.04 % reduction for TA100 strain when dye samples were treated with UV-LED light in the presence of H₂O₂ and TiO₂ for 150 min. The findings suggested that UV-LED light in conjunction with H2O2 and TiO2 can be a useful tool for the degradation and detoxification of toxic pollutants found in textile wastewater.

Hybrid Bee Colony Algorithm with Whale Algorithm

In this research paper, two hybrid algorithms of Meta-Heuristic algorithms, both of which are inspired by nature, are presented: the Bee- settlement Amendment algorithm (BCO) and the Whale Amendment Algorithm (WOA). The Bee settlement Amendment algorithm is an amendment algorithm founded on swarm intelligence modeling attitude. It is one of the techniques of synthetic information that focuses on studying the grouping conduct of decentralized systems, which are represented by groups of modest elements that react locally simultaneously and with the surrounding perimeter. One of the methods that distinguishes it is the method of exploration. As for the Whale Amendment Algorithm, whom represents the friendly conduct of the hump-back whale. It is based on the fancy net fishing design. One of the advantages of this algorithm depends on the poise between screening and utilization and avoidance of falling into local solutions. A hybridization process was carried out between the two algorithms, and the new algorithm was named (ABCWOA), and the whole algorithm was used to 16 rising -measurement Amendment assignment with diverse frequencies between (100, 200, 500, and 1000). The outcomes of the proposition algorithm showed access to optimality solutions by achieving the minimum value (f_min). For most assignment, the outcomes of this algorithm were disparity with the search algorithms.

In-situ generation of bifunctional reagents via Al/C microelectrolysis for efficient coagulation–Fenton oxidation treatment of leachate MBR effluent

Coagulation–Fenton oxidation stands as a prevalent method for organic pollutant removal from MBR effluent in landfill leachate. However, its dependence on intricate coagulant preparation and hazardous H2O2 handling presents challenges in logistics. Herein, a novel Al0/C–N, Cl composite was developed via high-energy ball milling and high-temperature sintering, which facilitates in situ generation of H2O2 and aluminum salt coagulant upon stirring in oxygen-containing aqueous solutions. Under conditions of 2 g/L Al0/C–N, Cl and initial pH 9, H2O2 production achieved 459 mg/L within 1 h, yielding an Al3+/H2O2 bifunctional reagent. Subsequent coagulation in MBR effluent and Fenton oxidation achieved removal efficiencies of 85.5 %, 76.4 %, and 99.3 % for UV254, total organic carbon, and chromaticity, respectively. The efficient degradation of refractory fulvic-like substances was obtained from this novel “coagulation–Fenton” hybrid process without additional coagulants and H2O2. These results illustrated that the hybrid process is a promising and efficient technology for the advanced treatment of landfill leachate.

A scenario-based decision framework for the order promising process in hybrid MTS/MTO production systems considering product substitution

ABSTRACT Considering the increasing competition among manufacturers and the diversification of customer orders, it is important to use the optimal production system. Hybrid manufacturing systems have proven to be a viable solution to achieve a satisfactory level of customization while maintaining adequate production volumes. This article determines the optimal strategy for decision makers in order to choose the appropriate method of supplying customers’ orders. In this article, a hybrid MTS-MTO production system has been studied in two different scenarios. For this purpose, a mixed-integer linear bi-objective model with product substitution and replaceable materials has been developed and solved by a Lagrangian Relaxation algorithm. The findings of this study reveal that enabling product substitution by manufacturers leads to an increase in the number of accepted orders, along with resulting in a higher average level of customer dissatisfaction. The system prioritizes the fulfillment of orders from permissive customers. Also, with the increase of uncertainty in each of the supplying methods, manufacturers are using other sources to supply raw materials to satisfy the accepted orders.

Unraveling the origin of the wild pig (Sus scrofa Linnaeus, 1758) from the northwest Patagonian region: evidence of hybridization processes and a possible pure wild boar population in a protected area

Unraveling the origin of the wild pig (Sus scrofa Linnaeus, 1758) from the northwest Patagonian region: evidence of hybridization processes and a possible pure wild boar population in a protected area

Electro-coagulation pretreatment for improving nanofiltration membrane performance during reclamation of microplastic-contaminated secondary effluent: unexpectedly enhanced membrane fouling and mechanism analysis by MD-DFT simulation

The residue of microplastic in secondary effluent was inevitable with continuous aggravation on nanofiltration membrane fouling. Thus, this study aimed to further evaluate the applicability of electro-coagulation as pretreatment for improving the performance of a nanofiltration-oriented hybrid process during the reclamation of microplastic-contaminated secondary effluent. The electro-coagulation parameters were skillfully optimized and designed for following dynamic nanofiltration experiments. The potential influence of coagulants in different forms as well as their combined effects of microplastics on membrane fouling behaviors and pollutant rejection efficiency was distinguished. Specifically, terminal membrane permeability was reduced by 19% after 0.05 A electro-coagulation, while 0.2 A electro-coagulation almost eliminated the negative effects of microplastics. Mass transfer model analysis excluded the dominance of organic accumulation in the concentration polarization layer on membrane fouling development. Molecular dynamic (MD) simulation and egg-box model demonstrated that humic-Fe network possessed stronger bridging effects and greater porosity. This structure favored the co-deposition of other unlinked bacteria metabolites, which secretion was also facilitated by microplastics as immobilized carriers, on membrane surface. Additionally, density functional theory (DFT) calculation further confirmed that the greater demand for dehydration energy for ferric ions (1124 kcal/mol) inspired the formation of stronger humic-Fe complexes. Besides, residual microplastics in electro-coagulation effluent had different impacts on membrane rejection towards organic and inorganic pollutants, and it depended on the influenced cake-enhanced concentration polarization (CECP) by microplastic affinity with different pollutants.

Variogram models reconstruction for damaged ERT profiles

Reconstructing signals which are embedding spatial patterns such as Electrical resistivity tomography, is a process that should require to reconstruct first the spatial correlation of the damaged signals. This paper proposes an approach that implements an Unstationary Kriging (UNK) to reconstruct the experimental variogram of a damaged synthetic pseudo section within a set of pseudo sections coming from the same survey. We used and compared 02 other simple methods which are Linear Regression (LR) and Ordinary Kriging (OK), to test the hypothesis we formulate to link the experimental variograms coming from the same ERT survey. We implemented the UNK using Discrete Fourier Transforms (DFT) for trend modeling. After an implementation of the hybrid process (UNK) on 02 sets of data which are synthetics, we observed that the LR and the UNK methods present an interest. They both reconstruct signals with a +90% rate of accuracy, but when there is no structure or spatial correlation within the data, the LR is unstable. DFT was also tested alone for reconstruction but was mainly used in this study to help in computing the trends for each set of variographic signals. In the end, we conclude on an evidence that is: the proposed hybrid process is a promising way to reconstruct variographic signals, since we can improve it after more time invested to dig deep into the modeling of each of his components.

Tough Cortical Bone-Inspired Tubular Architected Cement-Based Material with Disorder.

Cortical bone is a tough biological material composed of tube-like osteons embedded in the organic matrix surrounded by weak interfaces known as cement lines. The cement lines provide a microstructurally preferable crack path, hence triggering in-plane crack deflection around osteons due to cement line-crack interaction. Inspired by this toughening mechanism and facilitated by a hybrid (3D-printing/casting) process, the study engineers architected tubular cement-based materials with the stepwise cracking toughening mechanism, that enables a non-brittle fracture. Using experimental and theoretical approaches, the study demonstrates the competition between tube size and shape on stress intensity factor from which engineering stepwise cracking can emerge. Two competing mechanisms, both positively and negatively affected by the growing tube size, arise to significantly enhance the overall fracture toughness by up to 5.6-fold compared to the monolithic brittle counterpart without sacrificing the specific strength. This is enabled by crack-tube interaction and engineering the tube size, shape, and orientation, which promotes rising resistance-curves (R-curve). "Disorder" curves and statistical mechanics parameters are proposed for the first time to quantitatively characterize the degree of disorder for describing the representation of the architected arrangement of materials in lieu of otherwise inadequate "periodicity" classification and misperceiveddisorder parameters (perturbation and Voronoi tessellation methods).

Ecomuseums in the Mediterranean Area and the Promotion of Sustainable Food Systems

In recent years, the growing interest in food as a central component of heritage preservation has been paired with a reflection on the sustainability of food systems. At the same time, place-based food governance has undergone processes of hybridization, opening up to a wider range of stakeholders. We argue that ecomuseums can positively contribute to the promotion of sustainable food systems that can preserve cultural heritage without undermining the development of healthy food systems. To discuss this hypothesis, we conducted an exploratory study to assess the current diffusion and food-related practices of ecomuseums in the Mediterranean area. Integrating the information of existing databases with online research of new institutions, we mapped a large sample of ecomuseums and carried out a Web Content Analysis. The main results of the research are a geolocalized map of Mediterranean ecomuseums and their activities and an index assessing their capacity to engage users on relevant topics through their webpages. The results highlight the existence of an unbalanced distribution of experiences, and the potential for growth, especially in the east and south of the Mediterranean countries.

Getting Down to Business: Governing the Hybridization of UK Charities

AbstractCharity organizations are important to solving complex social and environmental issues that are beyond the reach of government and commercial organizations. However, these organizations are under increasing pressure for survival due to a sharp decrease in their traditional sources of funding. This study examines how leaders of charity organizations can improve the financial security and impact of their organization by adopting commercial structures into their organization, and therefore undergoing a process of hybridization. We conducted a multiple comparative case study of 18 UK charities comparing how they engaged with emerging social finance funding opportunities that required them to adopt commercial structures which lay outside their dominant logic of action. We identified several aspects that influenced the likelihood of a charity organization to engage with this opportunity and, therefore, strategically hybridize. These included whether a charity executive had sufficient socialization in both the social and commercial logics to view social finance as a strategic opportunity and whether the organization could alter the role expectations of trustees with a commercial background to enable them to actively use both logics rather than compartmentalizing them in their decision‐making. Our findings have important implications for research streams on hybridization and hybrid governance.

Modeling and validation of purification of pharmaceutical compounds via hybrid processing of vacuum membrane distillation

This study provides an in-depth examination of forecasting the concentration of pharmaceutical compounds utilizing the input features (coordinates) r and z through a range of machine learning models. Purification of pharmaceuticals via vacuum membrane distillation process was carried out and the model was developed for prediction of separation efficiency based on hybrid approach. Dataset was collected from mass transfer analysis of process to obtain concentration distribution in the feed side of membrane distillation and used it for machine learning models. The dataset has undergone preprocessing, which includes outlier detection using the Isolation Forest algorithm. Three regression models were used including polynomial regression (PR), k-nearest neighbors (KNN), and Tweedie regression (TWR). These models were further enhanced using the Bagging ensemble technique to improve prediction accuracy and reduce variance. Hyper-parameter optimization was conducted using the Multi-Verse Optimizer algorithm, which draws inspiration from cosmological concepts. The Bagging-KNN model had the highest predictive accuracy (R2 = 0.99923) on the test set, indicating exceptional precision. The Bagging-PR model displayed satisfactory performance, with a slightly reduced level of accuracy. In contrast, the Bagging-TWR model showcased the least accuracy among the three models. This research illustrates the effectiveness of incorporating bagging and advanced optimization methods for precise and dependable predictive modeling in complex datasets.