Innovations in IN939: From Cast Alloy to Additive Manufacturing

Nickel-based superalloys are the most reliable material choice for the hot sections of turbines. These superalloys are mainly employed in aircraft engines, particularly in the combustor and turbine sections. In this scenario, the growing need for materials that can endure high temperatures while retaining their strength has driven the development of IN939. Although IN939 holds these significant important properties and applications, it has received less attention in recent literature than other superalloys. This review aims to comprehensively analyze the main research on IN939 over the past 50 years. From 1970 to 1980, research primarily focused on the development of IN939 through casting methods. Between 1980 and 1990, the emphasis shifted to studying its oxidation resistance and microstructural stability during service. The period from 1990 to 2000 focused on repairing components after long service time at high temperatures. In recent decades, advances in additive manufacturing techniques have led to growing interest in developing IN939 using methods like laser powder bed fusion (LPBF). Research in the area has demonstrated that the LPBF technique offers a promising approach to manufacturing high-performance IN939 components.

Effect of Recycled High-Density Polyethylene on the Impact Strength of Polybutylene Terephthalate/Polyamide 6

Recycling high-density polyethylene (HDPE) is crucial to addressing plastic waste challenges. This study investigates the mechanical properties of blends composed of HDPE, polybutylene terephthalate (PBT), and polyamide 6 (PA6). Blends with varying HDPE content (0, 70, 80, 90, and 100%) were analyzed using injection molding to determine their impact toughness and structural characteristics. PBT and PA6 (blended in a 50:50 ratio) were combined with HDPE to create composites with enhanced properties. Testing included unnotched impact strength analysis and scanning electron microscopy (SEM). HDPE, a flexible thermoplastic, was paired with PBT and PA6, known for their strength and heat resistance, to produce a blend with superior mechanical performance. Results reveal that incorporating HDPE enhances the impact toughness of the composites compared to the pure PBT/PA6 blend, offering promising potential for many diverse applications in materials engineering in the automotive industry, household products, and protective casings of electronic products.

Porous Cu(Mn)-Doped ZnO-MgO Nanocomposites for Photocatalytic and Antibacterial Applications

Porous Cu(Mn):ZnO-MgO composites synthesized by polymeric sol-gel method were characterized. The crystal structure, morphology, spectral properties, the ability of the photogeneration of chemically active singlet oxygen under external visible irradiation, photocatalytic and antibacterial properties of porous composites were studied. Obtained composites consist of small ZnO and MgO crystals having size less than 20 nm. It was found that Cu²⁺ and Mn²⁺ ions are embedded into the lattices of ZnO and MgO crystals, altering their crystal cell parameters. The band gap values of obtained composites are 3.41 ÷ 3.42 eV which are slightly higher than the band gap of pure ZnO. Prepared materials demonstrate a high ability of photogeneration of chemically active singlet oxygen under blue light (λ = 405 nm) irradiation. It was found that dependencies of the intensity of singlet oxygen photogeneration from the power density of visible irradiation are linear. Photocatalytic decomposition of the diazo dye Chicago Sky Blue in solutions under UV and blue light irradiation proceeds rapidly in the presence of the prepared composites (constants rate of photocatalytic dye decomposition under UV irradiation are 0.024 min⁻¹ and 0.025 min⁻¹ for ZnO-MgO composites doped with Cu and Mn, correspondingly). Porous composites demonstrate superior antibacterial activity against gram-positive bacteria. These materials are promising for practical application in medicine and photocatalytic technologies of air and water cleaning.

Cement-Free Binders in Alumina-Magnesia Refractory Castables—A Review

To solve the problem of the accelerated deterioration of calcium aluminate (CAC)-bonded alumina-magnesia refractory castables during the secondary refining process, the development of cement-free binders has emerged as one significant research field of castables. The hydration behavior, curing mechanism, and properties of the most recent research on cement-free binders are compared in this paper. The problems and the modification of each binder of recent research are summarized. High-temperature performance of the castables bonded by traditional hydraulic cement-free binders (ρ-Al₂O₃ and activated MgO) is outstanding, explosive spalling resistance of the castables bonded by sol binders (silica sol, alumina sol) is good, and the properties of the castables bonded by novel organic hydratable binder (hydratable magnesium citrate) combine the advantages of these two binders above, but the mid-temperature mechanical strength is low. Furthermore, alumina-magnesia castables bonded by organic-composited inorganic cement-free binders are expected to be a future domain.

Efficient Removal of Glyphosate from Aqueous Solution by Cerium Dioxide Loaded Biochar

Glyphosate, which is one of the most widely used organophosphorus herbicides, poses a threat to the surrounding water environment. Traditional adsorbents were depicted to have poor capacities to eliminate it. CeO₂ embraces the potential to adsorb glyphosate efficiently. However, suitable carbonaceous composites were necessary to be employed as its support. In this paper, water hyacinth was used as the precursor to prepare CeO₂-loaded biochar (CeO₂/WHBC), which was employed to remove glyphosate from the aqueous solution via adsorption. The results showed that CeO₂/WHBC-3 illustrated the best adsorption performance for glyphosate with the capacity of 126.3 mg·g, which was prepared with per mmol CeO₂ loaded of 0.2 g WHCB. Static adsorption experiments demonstrated that glyphosate adsorption at different solution pH values followed the Langmuir isotherm model and quasi-second order kinetic model, indicating that the adsorption was monolayer adsorption and that the adsorbent’s surface active sites primarily controlled the rate. Coexisting ion interference experiments showed that common cations (K⁺, Na⁺, Ca²⁺, Mg²⁺) and anions (Cl⁻, NO₃⁻, SO₄²⁻) both promoted glyphosate adsorption on the CeO₂/WHBC-3 surface. Moreover, the prepared sorbent maintained a high adsorption capacity after five adsorption-desorption cycles. Dynamic adsorption experiments showed that the CeO₂/WHBC-3 packed column could efficiently remove glyphosate from aqueous solutions, even at high concentrations and fast flow rates. Zeta potentials and XPS analysis revealed that the adsorption mechanism of CeO₂/WHBC-3 for glyphosate is mainly through electrostatic adsorption and metal complexation.

Adaptive Event-Triggered Control for Multi-Quadrotor Systems under Aperiodically Intermittent Communications

A novel adaptive event-triggered control strategy is proposed for multi-quadrotor systems under intermittent communications, addressing the leader-follower consensus-seeking problem where the leader has an unknown bounded input. Firstly, an activation time ratio condition is proposed, eliminating the reliance on the maximum time interval of intermittent communication. Secondly, a compensation term related to the leader’s unknown bounded input is designed in the controller to compensate for the error caused by intermittent communication in each period. Meanwhile, a prediction method is developed to eliminate the dependence on continuous information of neighboring quadrotors. Zeno behavior is strictly excluded, and communication among quadrotors is efficiently reduced with the designed event-triggering condition. Finally, numerical simulations verify the effectiveness and superiority of the proposed control strategy.

The Effect of Polyethylene Glycol on Cobalt Oxide Nanoparticles Prepared Using Sonochemical Synthesis

In this work, Cobalt oxide nanoparticles (Co₃O₄·NPs) were synthesized via a simple sonochemical reaction by using polyethylene glycol (PEG) as a surfactant. Structural, morphological and spectroscopic analysis of obtained powder (Co₃O₄·NPs) was investigated by X-ray diffraction, FTIR spectroscopy and scanning electron microscope (SEM). The nanocrystalline nature of the sample was confirmed by XRD, which exhibits the cubic face-centered normal spinel structure of (Co₃O₄·NPs) and the space group of Fd-3m with the average crystallite size around 15 nm. FTIR spectrum shows two strong absorption bands of (Co⁺²–O) and (Co⁺³–O) which confirm the spinel structure of Co₃O₄·NPs. Moreover, SEM micrographs showed that the agglomeration of the nanoparticles was reduced by the addition of (PEG) surfactant and UV-Vis was used to study the synthesized material’s optical properties. The Co₃O₄ band gap ranged around 2.2 and 3.5 eV.

Intelligent Rehabilitation and Engineering: Empowering the People with Disabilities

4DoF Rat-SLAM with Memristive Spiking Neural Networks for UAVs Navigation System

Unmanned Aerial Vehicles (UAVs) are versatile platforms with potential applications in precision agriculture, disaster management, and more. A core need across these applications is a navigation system that accurately estimates location based on environmental perception. Commercial UAVs use multiple onboard sensors whose fused data improves localization accuracy. The bioinspired Rat-Simultaneous Localization and Mapping (Rat-SLAM) system, is a promising alternative to be explored to tackle the localization and mapping problem of UAVs. Its cognitive capabilities, semi-metric map construction, and loop closure make it attractive for localization in complex environments. This work presents an improved Rat-SLAM algorithm for UAVs, focusing on three innovations. First, Spiking Neural Networks (SNNs) are incorporated into Rat-SLAM’s core modules to emulate biological processing with greater efficiency. Second, Neuromorphic Computing models the neurons of the SNNs, assessing the feasibility of implementing SNNs on specialized hardware to reduce software processing, a key advantage for UAVs with limited onboard resources. Third, SNNs are developed based on the Memristive Leaky Integrate-and-Fire model, integrating memristors into artificial neurons to leverage their low power and memory properties. Our approach was evaluated through trajectory simulations using the Hector Quadrotor UAV in the Gazebo environment within the Robot Operating System, yielding valuable insights and guiding future research directions.

Digital Twin and Artificial Intelligence in Machining: A Bibliometric Analysis

The past decade has witnessed an exodus toward smart and lean manufacturing methods. The trend includes integrating intelligent methods into sustainable manufacturing systems purposely to improve the machining efficiency, reduce waste and also optimize productivity. Manufacturing systems have seen transformations from conventional methods, leaning towards smart manufacturing in line with the industrial revolution 4.0. Since the manufacturing process encompasses a wide range of human development capacity, it is essential to analyze its developmental trends, thereby preparing us for future uncertainties. In this work, we have used a Bibliometric analysis technique to study the developmental trends relating to machining, digital twins and artificial intelligence techniques. The review comprises the current activities in relation to the development to this area. The article comprises a Bibliometric analysis of 464 articles that were acquired from the Web of Science database, with a search period until November 2024. The method of obtaining the data includes retrieval from the database, qualitative analysis and interpreting the data via visual representation. The raw data obtained were redrawn using the origin software, and their visual interpretations were represented using the VOSviewer software (VOSviewer_1.6.19). The results obtained indicate that the number of publications related to the searched keywords has remarkably increased since the year 2018, achieving a record maximum of over 80 articles in 2024. This is indicative of its increasing popularity. The analysis of the articles was conducted based on the author countries, journal types, journal names, institutions, article types, major and micro research areas. The findings from the analysis are meant to provide a bibliometric explanation of the developmental trends in machining systems towards achieving the IR 4.0 goals. Additionally, the results would be helpful to researchers and industrialists that intend to achieve optimum and sustainable machining using digital twin technologies.