Formation of iron aluminide coatings on plain carbon steel by TIG process

Micro end-milling is widely used in many industries to produce micro products with complex 3D shapes. The accurate modeling and prediction of surface roughness are important for evaluating the productivity of the machine tools and the surface quality of the machined parts. This paper presents an accurate surface roughness model based on the kinematics of cutting process and tool geometry by considering the effects of tool run-out and minimum chip thickness. The proposed surface roughness model is validated by micro end-milling experiments with the miniaturized machine tool. The results show that the proposed surface roughness model can accurately predict both the trends and magnitude of the surface roughness in micro end-milling.     

Effect of substitution by Ni in MgAl2O4 spinel for biogas dry reforming

Mesoporous nanocrystalline Mg_1-xNi_xAl₂O₄ (x = 0.10, 0.13, 0.17 and 0.20) with large surface area were synthesized via a simple one-step sol-gel method using nonprecious metals. The prepared Mg_1-xNi_xAl₂O₄ catalysts exhibit good catalytic performance towards methane and carbon dioxide dry reforming reaction. The catalysts were evaluated by various techniques, including XRD, BET, TPR, TPO, EPR, Chemisorption, SEM and TEM. All the Ni incorporated MgAl₂O₄ samples possessed high BET area (296–305 m² g^?1) and pore volume (0.47–0.56 cm³ g^?1) with small pore size (6.4–7.4 nm) in meso region after calcination at 700 °C. The TPR results suggested strong interaction effect in NiMg and the reducibility property of the catalysts improved with the increase of nickel doping. Mg_0.8Ni_0.2Al₂O₄ exhibited the highest activity for biogas dry reforming with 72.6% CH₄ and 80.7% CO₂ conversion at 700 °C. Electron paramagnetic resonance (EPR) results indicated that the incorporation of Ni in MgAl₂O₄ spinel lattice led to the lattice distortion and formed oxygen vacancies which are a benefit for the dry reforming reaction.     

Poly(itaconic acid)-assisted ultrafiltration of heavy metal ions’ removal from wastewater

The complexation–ultrafiltration technique has been introduced as a capable system to remove heavy metals ions from wastewater. This method needs a water-soluble polymer; therefore, in this paper we synthesized super water-soluble poly(itaconic acid) (PITA) and employed it in polymer-assisted ultrafiltration process to remove Pb(II) ions from synthetic wastewater solutions. The itaconic acid can be produced from different agricultural products and is a green and eco-friendly material. Factors influencing the removal of the metals ions including poly(itaconic acid) concentration, pH and permeate flux were investigated. The results showed that the maximum percentage of metal ion removal was obtained in the basic pH (pH > 7). The flux test was performed by 200 mg/L of poly(itaconic acid) and after 60 min, the flux of membrane was 33.4 L/m²h. The simultaneously selective removal ability of the poly(itaconic acid) for adsorption of different metal ions (Pb²⁺, Sn²⁺, Cu²⁺, Zn²⁺, and Cd²⁺) was also studied. The trend of rejection was Pb²⁺ > Cu²⁺ > Sn²⁺ > Zn²⁺ > Cd²⁺. The highest rejection of Pb(II) ions was achieved as 86%. Generally, the results of this research demonstrated that poly(itaconic acid) (with two carboxyl groups on its repeating unit) is more effective in removing heavy metals ions from wastewater in comparison with customary polymers.

     

Magnetic nanobiosorbent (MG‐Chi/Fe3O4) for dispersive solid‐phase extraction of Cu(II), Pb(II), and Cd(II) followed by flame atomic absorption spectrometry determination

Trace amounts of Cu (II), Pb (II), and Cd (II) in a wastewater sample were preconcentrated with a novel cross‐linked magnetic chitosan modified with a new synthesised methionine‐glutaraldehyde Schiff''s base (MG‐Chi/Fe₃O₄) as a dispersive solid‐phase extraction (DSPE) adsorbent. The adsorbed metal ions were then eluted with a specific volume of suitable solution and determined by flame atomic absorption spectrometry (FAAS). Various parameters affecting the extraction efficiency of the metal ions were investigated and optimised, including pH, amount of adsorbent, extraction time, type and volume rate of eluent, elution time, sample volume, and effect of interfering ions. The adsorption kinetics are more consistent with the pseudo‐second order model. The results were statistically interpreted and the analytical performance of the proposed method was found to have preconcentration factors of 55, 60, and 50 μg L⁻¹ for Cu(II), Pb(II), and Cd(II), respectively, limits of detection were 0.22, 0.24, and 0.10 μg L⁻¹ for Cu(II), Pb(II), and Cd(II), respectively, with a relative standard deviation (1.5%‐2.8 %), and the liner range was 5–1000 for Cu(II) and Pb(II) and 2.5–1000 for Cd(II). It was concluded that this method was suitable for successful simultaneous determination of Cu(II), Pb(II), and Cd(II) in industrial wastewater samples.     

Structure of the Flight Muscle Thick Filament from the Bumble Bee,Bombus ignitus,at 6 Å Resolution

Four insect orders have flight muscles that are both asynchronous and indirect; they are asynchronous in that the wingbeat frequency is decoupled from the frequency of nervous stimulation and indirect in that the muscles attach to the thoracic exoskeleton instead of directly to the wing. Flight muscle thick filaments from two orders, Hemiptera and Diptera, have been imaged at a subnanometer resolution, both of which revealed a myosin tail arrangement referred to as “curved molecular crystalline layers”. Here, we report a thick filament structure from the indirect flight muscles of a third insect order, Hymenoptera, the Asian bumble bee Bombus ignitus. The myosin tails are in general agreement with previous determinations from Lethocerus indicus and Drosophila melanogaster. The Skip 2 region has the same unusual structure as found in Lethocerus indicus thick filaments, an α-helix discontinuity is also seen at Skip 4, but the orientation of the Skip 1 region on the surface of the backbone is less angled with respect to the filament axis than in the other two species. The heads are disordered as in Drosophila, but we observe no non-myosin proteins on the backbone surface that might prohibit the ordering of myosin heads onto the thick filament backbone. There are strong structural similarities among the three species in their non-myosin proteins within the backbone that suggest how one previously unassigned density in Lethocerus might be assigned. Overall, the structure conforms to the previously observed pattern of high similarity in the myosin tail arrangement, but differences in the non-myosin proteins.     

Effect of coagulation treatment on antifouling properties of PVC nanocomposite membrane in a submerged membrane system for water treatment

A submerged membrane system was used in this work to investigate the effect of the polyaluminum chloride (PAC) coagulant on the antifouling performance of the polyvinyl chloride/alumina (PVC/Al₂O₃) nanocomposite membrane. The prepared nanocomposite membranes were characterized with field emission scanning electron microscopy (FE-SEM), atomic force microscopy, contact angle, porosity measurement, and pure water flux. The results revealed that the membrane containing Al₂O₃ nanoparticles (the mass ratio of PVC to Al₂O₃ was 98.5/1.5) had a higher hydrophilicity, porosity, and pure water flux than other membranes. The FE-SEM images showed that when Al₂O₃ nanoparticles were present in the PVC membrane, large pores and macrovoids formed on the surface and cross-section of the membrane. The fouling behavior of membranes was investigated through the filtration of humic acid (HA) solution with and without the PAC coagulant. Without PAC addition, the PVC/Al₂O₃ membrane significantly decreased the irreversible fouling ratio from 60.7% to 19.4% and showed a high HA removal efficiency of approximately 90.5%. The Hermia model confirmed that the cake formation mechanism best described the experimental data for the neat PVC and nanocomposite membranes with the presence and absence of the PAC coagulant. This confirms that the PAC coagulant can significantly mitigate fouling and improve HA removal in the submerged membrane system.     

Conflict-Aware Safe Reinforcement Learning: A Meta-Cognitive Learning Framework

In this paper,a data-driven conflict-aware safe reinforcement learning(CAS-RL)algorithm is presented for control of autonomous systems.Existing safe RL results with predefined performance functions and safe sets can only provide safety and performance guarantees for a single environment or circumstance.By contrast,the presented CAS-RL algorithm provides safety and performance guarantees across a variety of circumstances that the system might encounter.This is achieved by utilizing a bilevel learning control architecture:A higher metacognitive layer leverages a data-driven receding-horizon attentional controller(RHAC)to adapt relative attention to different system’s safety and performance requirements,and,a lower-layer RL controller designs control actuation signals for the system.The presented RHAC makes its meta decisions based on the reaction curve of the lower-layer RL controller using a metamodel or knowledge.More specifically,it leverages a prediction meta-model(PMM)which spans the space of all future meta trajectories using a given finite number of past meta trajectories.RHAC will adapt the system’s aspiration towards performance metrics(e.g.,performance weights)as well as safety boundaries to resolve conflicts that arise as mission scenarios develop.This will guarantee safety and feasibility(i.e.,performance boundness)of the lower-layer RL-based control solution.It is shown that the interplay between the RHAC and the lower-layer RL controller is a bilevel optimization problem for which the leader(RHAC)operates at a lower rate than the follower(RL-based controller)and its solution guarantees feasibility and safety of the control solution.The effectiveness of the proposed framework is verified through a simulation example.     

Finite-Time Distributed Identification for Nonlinear Interconnected Systems

In this paper, a novel finite-time distributed identification method is introduced for nonlinear interconnected systems. A distributed concurrent learning-based discontinuous gradient descent update law is presented to learn uncertain interconnected subsystems’ dynamics. The concurrent learning approach continually minimizes the identification error for a batch of previously recorded data collected from each subsystem as well as its neighboring subsystems. The state information of neighboring in...     

Improvement of light olefins production over the Co-Ni-Mn nano-catalyst: modeling and optimization of process by RSM

The co-precipitated Co-Ni-Mn nano-catalysts were evaluated for carbon monoxide hydrogenation. The influence of Al₂O₃, SiO₂, Zeolite, Active carbon, MgO supports and then the effect of best chosen support loading on the catalytic behavior and structure of ternary Co-Ni-Mn nano-catalysts were studied. The Co-Ni-Mn/20 wt%SiO₂ sample has shown highest selectivity toward light olefins production. Furthermore the influence of process conditions was investigated. Evaluation tests were performed under process conditions of P = 1–10 bar, T = 523-623 K, and H₂/CO = 0.67–3. The Response Surface Methodology (RSM) method was used for modeling and optimization process and the best conditions for catalyst evaluation were determined (T = 598.16 K, P = 1 atm and H₂/CO = 2.19). Under these conditions the highest selectivity of light olefins, higher CO conversion % and lower selectivity toward methane were achieved. Catalysts characteristics were investigated using XRD, BET, TEM, TGA, DSC, SEM, XPS, and TPR techniques. © 2021 Society of Chemical Industry (SCI).     

Physicochemical modification of hydroxylated polymers to develop thermosensitive double network hydrogels

Due to the unique biophysicochemical characteristics of synthesized superhydrophilic poly[N-[tris(hydroxymethyl)methyl] acrylamide] (PTHMMA) and poly(vinyl alcohol) (PVA), in this study, we investigated the preparation of physically and chemically crosslinked thermosensitive double network (DN) hydrogels with superior mechanical properties. The effect of the combination of PTHMMA with PVA was further explored experimentally and theoretically. Moreover, adjusting the lower critical solution temperature (LCST) of PTHMMA/PVA DN hydrogels in the phosphate buffer was achieved by chemical alteration and crosslinking of water-soluble polymers. Changing the composition and the extent of ether/acetal linkages altered the LCST based on hydrophilic/hydrophobic composition, which decreased the complexity of adjusting hydrogels' temperature sensitivity. PTHMMA-comprising hydrogels were found to have non-Fickian and super case ΙΙ transport characters. Moreover, the construction of shrunken PVA at high temperature was tailored by introducing PTHMMA into the network to permit a relaxed drug release of indomethacin (IND) at 37°C and pH 7.4. Finally, the tensile strength, the equilibrium water content, thermo-sensitivity, and cell viability behaviors suggest that these materials can be tailored for potential applications as biomaterials.