Mixed Array Research Articles

A Change Localization Benefit for Mixed Arrays Over Uniform Arrays

A Change Localization Benefit for Mixed Arrays Over Uniform Arrays

Recoverability degradation of adhesion between soft matters under uniaxial cyclic bonding–debonding: Modified cohesive interface model and numerical implementation

The main objective of this work is to propose a partial recoverable cohesive interface model, coupled with a bi-potential contact algorithm, to simulate the phenomenon of adhesion recoverability degradation under cyclic bonding–debonding between hyperelastic bodies. For this end, the proposed adhesion recoverability degradation model is constructed by defining the recovery of interface damage during the rebonding when two bodies come into contact, and a degradation factor related to the number of bonding–debonding cycles is introduced into the fully recoverable adhesion model to reduce energy dissipation after multiple cycles. Recoverability degradation includes adhesive stiffness and strength degradation, which is physically described as parallel, series and mixed arrays of adhesive bonds. Then, a finite element framework coupling the adhesion recoverability degradation model and the bi-potential contact algorithm is proposed, with Mooney–Rivlin hyperelastic material used to describe the soft matters. This framework is implemented in an in-house finite element code, with numerical examples demonstrating the model’s reliability. The proposed approach could be applied to investigate interfacial adhesion effects in fields such as flexible electronics and intelligent robotics.

Investigation of machining performance of waspaloy using copper-graphite composite electrodes in electric discharge machining

Abstract This study endeavoured to investigate the machining of Waspaloy using Electric Discharge Machining (EDM), utilizing copper-graphite composites as the tool material. Given the limited existing research on machining Waspaloy with composite tools, this study aims to address this gap by employing a copper-graphite composite tool. In this work, pure copper electrode and three composite electrodes with varying graphite percentages in copper, viz. copper containing 5%, 10%, and 15% graphite (CuGr-5, CuGr-10, and CuGr-15), are utilized for experimentation. Composite electrodes are fabricated by the stir-casting process. The scanning electron microscope reveals that the graphite specks are homogeneously disseminated over the matrix material. The Taguchi mixed orthogonal array was used for developing experimental runs. By varying the current, polarity, pulse on and off times, tool materials, and gap, machining performance was measured in terms of Material Removal Rate (MRR), Tool Wear Rate (TWR), and Surface Roughness (Ra). It was observed that CuGr-5 provides an enhancement in MRR due to the improved electric conductivity, bridging effect, and increased energy concentration at the spark gap. Diverse characteristics witnessed on the surface morphology include black dots, globules, remelted layers, micro-cracks, and scratches. When machined with a CuGr5 electrode, the surface quality improved owing to the completed flushing and uniform distribution of generated heat as confirmed through worn surface morphology. The parameters were optimized utilizing the PROMETHEE optimization technique; it was found that the CuGr-5 electrode with the assessment value 0.02458 was optimal for machining of Waspaloy.

Shack-Hartmann wavefront sensor based on a two-dimensional mixed aperture diffractive lens array

Shack-Hartmann wavefront sensor based on a two-dimensional mixed aperture diffractive lens array

Label -free measuring biomolecular interactions using plasmonic metasurfaces with dual bands based on surface lattice resonances in the mid-infrared range

Mid-infrared plasmonic metasurfaces are remarkable platforms for chemical-specific detection and dynamic monitoring of biomolecules. This study uses surface-enhanced infrared absorption (SEIRA) spectroscopy by applying plasmonic metasurfaces for label-free and real-time monitoring of biomolecular interactions. SEIRA devices based on geometric combinations of two types of square arrays with different Au microdots require the use of new dual-resonant plasmonic metasurfaces. Resonant matching between the plasmonic and molecular vibrational modes can be realized through the controlled microdot dimensions and periodicity of the array. Plasmonic surface lattice resonances contribute to this optical tuning, enabling simultaneous observations of SEIRA-enhanced methyl and amide bands. The electric fields on mixed arrays were strongly confined to approximately 100 nm, enabling high SEIRA performance and single molecule detection. Moreover, the SEIRA device no longer needed in-plane polarization control of IR light, enhancing sensing detection’s robustness and stability. Finally, the in situ real-time monitoring of biomolecular interactions between protein A and immunoglobulin, which provides remarkable changes in the intensity and vibrational features of SEIRA absorbance, is reported. Dynamic SEIRA measurements using molecular vibrations as self-biomarkers helped in identifying the kinetic parameters required for important affinity metrics of biomolecular interactions.

OPTIMIZING THE GEOMETRICAL PARAMETERS OF 3D PRINTED NEGATIVE STIFFNESS METAMATERIAL USING TAGUCHI METHOD

The field of negative stiffness metamaterials (NSM) is a rapidly developing area within the realm of mechanical metamaterials. This work presents a novel negative stiffness metamaterial based on a bistable structure that consists of a straight beam with an elastic element shaped like a ring. Further, this work presents the findings of a Taguchi-based experiment aimed at optimizing geometrical parameters in negative stiffness metamaterial. The Taguchi method, known for its efficiency in experimental design and analysis, was employed to systematically study the effects of various factors on snapping force for a novel structure exhibiting negative stiffness. The experiment utilized L18 mixed level orthogonal array. All the test samples were fabricated using additive manufacturing technique. Signal-to-noise ratio analysis and analysis of variance were two statistical approaches that were used to comprehensively evaluate the acquired data. The results of this study provide valuable insights into the optimal geometrical configuration for maximizing snapping force of negative stiffness metamaterial.

Boosting Urea-Assisted Natural Seawater Electrolysis in 3D Leaf-Like Metal-Organic Framework Nanosheet Arrays Using Metal Node Engineering.

Metal node engineering, which can optimize the electronic structure and modulate the composition of poor electrically conductive metal-organic frameworks, is of great interest for electrochemical natural seawater splitting. However, the mechanism underlying the influence of mixed-metal nodes on electrocatalytic activities is still ambiguous. Herein, a strategic design is comprehensively demonstrated in which mixed Ni and Co metal redox-active centers are uniformly distributed within NH2-Fe-MIL-101 to obtain a synergistic effect for the overall enhancement of electrocatalytic activities. Three-dimensional mixed metallic MOF nanosheet arrays, consisting of three different metal nodes, were in situ grown on Ni foam as a highly active and stable bifunctional catalyst for urea-assisted natural seawater splitting. A well-defined NH2-NiCoFe-MIL-101 reaches 1.5 A cm-2 at 360 mV for the oxygen evolution reaction (OER) and 0.6 A cm-2 at 295 mV for the hydrogen evolution reaction (HER) in freshwater, substantially higher than its bimetallic and monometallic counterparts. Moreover, the bifunctional NH2-NiCoFe-MIL-101 electrode exhibits eminent catalytic activity and stability in natural seawater-based electrolytes. Impressively, the two-electrode urea-assisted alkaline natural seawater electrolysis cell based on NH2-NiCoFe-MIL-101 needs only 1.56 mV to yield 100 mA cm-2, much lower than 1.78 V for alkaline natural seawater electrolysis cells and exhibits superior long-term stability at a current density of 80 mA cm-2 for 80 h.

Multi-functional Inconel 625 micro-machining and process optimization using ANFIS

The primary objective of this study is to develop an adaptive neuro-fuzzy inference-based system (ANFIS) that assesses the ideal parameters and impact of the micro-electro-discharge machining (Micro-EDM) technique on surface roughness (SR). In this work multi-functional Inconel alloy specimens were machined using micro-elector-discharge machining (Micro-EDM) with zinc-coated copper electrodes in a graphite nano abrasive submersion medium. An ANFIS and Taguchi design of experiments (DOE) was employed to evaluate the Micro-EDM method. The study utilized Taguchi's L9 mixed orthogonal arrays (OA) to consider three process variables, namely open voltage (V), capacitance (C), and powder concentration (CP). ANOVA analysis was conducted to identify important process variables and evaluate their influence on surface properties. The experimental results showed that all approaches were effective in representing the process. Based on the results of the response surface methodology (RSM) and ANFIS predictions, the correlation coefficients (R2) of the experimental roughness were 0.995649 and the root mean square error (RMSE) value was 1.01226e-06, respectively. The results obtained indicate a strong alignment between the predicted and experimental values, effectively fulfilling the proposed objective. These findings hold significant potential for practical applications in the Micro-EDM industry, particularly in the machining of Inconel alloy.

Amorphous/Crystalline Phases Mixed Nanosheets Array Rich in Oxygen Vacancies Boost Oxygen Evolution Reaction of Spinel Oxides in Alkaline Media.

As promising oxygen evolution reaction (OER) catalysts, spinel-type oxides face the bottleneck of weak adsorption for oxygen-containing intermediates, so it is challenging to make a further breakthrough in remarkably lowering the OER overpotential. In this study, a novel strategy is proposed to substantially enhance the OER activity of spinel oxides based on amorphous/crystalline phases mixed spinel FeNi2O4 nanosheets array, enriched with oxygen vacancies, in situ grown on a nickel foam (NF). This unique architecture is achieved through a one-step millisecond laser direct writing method. The presence of amorphous phases with abundant oxygen vacancies significantly enhances the adsorption of oxygen-containing intermediates and changes the rate-determining step from OH*→O* to O*→OOH*, which greatly reduces the thermodynamic energy barrier. Moreover, the crystalline phase interweaving with amorphous domains serves as a conductive shortcut to facilitate rapid electron transfer from active sites in the amorphous domain to NF, guaranteeing fast OER kinetics. Such an anodic electrode exhibits a nearly ten fold enhancement in OER intrinsic activity compared to the pristine counterpart. Remarkably, it demonstrates record-low overpotentials of 246 and 315 mV at 50 and 500 mA cm-2 in 1 m KOH with superior long-term stability, outperforming other NiFe-based spinel oxides catalysts.

Performance analysis of ECMM using saw, critic and ANN methods

Electrochemical micromachining (ECMM) finds application in various industries especially in surface finishing process in aerospace industries. In this research the workpiece made from aluminum scrap metal matrix reinforced with alumina is subjected to wear, surface profile and machinability studies. To analysis the ECMM performance simple additive weighting (SAW) CRiteria Importance Through Intercriteria Correlation (CRITIC) and Artificial Neural Network (ANN) was used. The wear studies show that at high loads the height wear loss is less and frictional force is more. The L18 mixed orthogonal array experiments was conducted and analysis of experiments shows that the most crucial parameter values for high MRR and low OC are 28g/lit NaNO3+0.05M HNO3, 10 V, and 80% duty cycle. The weight values of the performance metrics obtained using SAW method are 0.549 and 0.45. The optimal output performance predicted by ANN is MRR of 0.520 ?m/sec and OC of 23.8 ?m.

Probing the 186Os/188Os Precision Barrier: New Recommended Values for the DROsS Reference Material and an Assessment of Mixed 1011 and 1012 Ω Amplifier Arrays

We present high precision negative ion thermal ionisation mass spectrometry (N‐TIMS) Os isotope measurement results for the DROsS isotope reference material (iCRM), to investigate the limits on the precision of TIMS‐based 186Os/188Os results. We used analytical conditions previously highlighted to optimise precision, present a new flexible data processing protocol, and measured 184Os intensities on a Faraday Cup equipped with an amplifier using a 1012 Ω resistor. Despite a measurement procedure that minimised uncertainty contributions from counting statistics and Johnson‐Nyquist noise, the intermediate measurement precision of our approach does not significantly improve on previous high precision Os isotope measurements, with the exception of 184Os/188Os. This is probably due to uncertainties in measured amplifier gain factors, which are greater when using mixed arrays of 1011 and 1012 Ω resistors than when using 1011 Ω resistors alone, though Faraday Cup deterioration could also contribute. We propose that multi‐dynamic Os isotope measurements could largely eliminate both of these uncertainties. Our 184Os/188Os measurement results are the most precise yet, yielding 184Os/188Os = 0.0013036 ± 0.0000007 (2s, n = 38). Additionally, we average our data with published data to recommend the following isotope ratios for DROsS: 186Os/188Os = 0.1199319 ± 0.0000024, 187Os/188Os = 0.1609227 ± 0.0000022, 189Os/188Os = 1.219709 ± 0.000010, 190Os/188Os = 1.983793 ± 0.000011.

Assessment of three mixed arrays dataset for subsurface cavities detection using resistivity tomography as inferred from numerical modelling

The present study deals with the evaluation of a three-mixed array dataset for the detection of subsurface cavities using conceptual air-filled cavity model sets at different depths. Cavity models were simulated using the forward modelling technique to generate synthetic apparent resistivity data for three common individual arrays. These arrays are dipole–dipole (DD), pole–dipole (PD), and Wenner–Schlumberger (WS). The synthetically apparent resistivity data obtained from two different individual arrays were merged to form a high-resolution single model. Consequently, three possible mixed arrays datasets can be obtained: the dipole–dipole-Wenner–Schlumberger (DD+WS), pole–dipole, and Wenner–Schlumberger (PD+WS), and dipole–dipole and pole–dipole (DD+PD). The synthetically apparent resistivity data for both the individual and mixed arrays were inverted using Res2dinv software based on the robust constrain inversion technique to obtain a 2D resistivity model section. The inverted resistivity sections were evaluated in terms of their recovering ability of the model’s parameters (e.g. resistivity, and geometry). The results show that the individual arrays can resolve the location and dimensions of the cavity within reasonable accuracy only at a depth not exceeding 6 m below the surface. On the other hand, a significant resolution enhancement in model resistivity with increasing depth was observed when the mixed arrays were used. The (DD+WS) mixed arrays dataset brings up better model resistivity and shows closer parameters to the true actual model among the other mixed arrays. So it is strongly recommended for cavity detection studies.

Design of a Multisensory Device for Tomato Volatile Compound Detection Based on a Mixed Metal Oxide-Electrochemical Sensor Array and Optical Reader.

Insufficient control of tomato ripening before harvesting and infection by fungal pests produce large economic losses in world tomato production. Aroma is an indicative parameter of the state of maturity and quality of the tomato. This study aimed to design an electronic system (TOMATO-NOSE) consisting of an array of 12 electrochemical sensors, commercial metal oxide semiconductor sensors, an optical camera for a lateral flow reader, and a smartphone application for device control and data storage. The system was used with tomatoes in different states of ripeness and health, as well as tomatoes infected with Botrytis cinerea. The results obtained through principal component analysis of the olfactory pattern of tomatoes and the reader images show that TOMATO-NOSE is a good tool for the farmer to control tomato ripeness before harvesting and for the early detection of Botrytis cinerea.

Simulation on modified multi-surface levitation structure of superconducting magnetic bearing for flywheel energy storage system by H-formulation and Taguchi method

Improving the performance of superconducting magnetic bearing (SMB) is very essential problem to heighten the energy storage capacity of flywheel energy storage devices which are built of components such as superconductor bulks, permanent magnets, flywheel, cooling system and so on. In this paper, three surfaces levitation-superconducting magnetic bearing (TSL-SMB) was simulated in two-dimensional axisymmetric system using H-formulation and Taguchi method. The system was worked by field cooling (FC) method. Taguchi-based L32(21×49) mixed orthogonal array was used to formulate the simulation plans for TSL-SMB, and effects of geometric parameters on levitation force in TSL-SMB was considered using Analysis of Variance (ANOVA). In the optimized TSL-SMB structure, there was no good difference whether the effect of concentric ring PMs with opposite polarization was included or not. Therefore, four surfaces levitation-superconducting magnetic bearing (FSL-SMB) as advanced multi-surface levitation system was presented to improve the performance of SMB. The simulation results in the FSL-SMB system showed that the gap between the stator and the rotor and levitation force per permanent magnet volume might be increased more than those of TSL-SMB system in the condition of same load capacity, this will contribute to improve the load capacity of SMB.

Two Decades of Arrayed Imaging Reflectometry for Sensitive, High-Throughput Biosensing.

Arrayed imaging reflectometry (AIR), first introduced in 2004, is a thin-film interference sensor technique that optimizes optical properties (angle of incidence, polarization, substrate refractive index, and thickness) to create a condition of total destructive interference at the surface of a silicon substrate. The advantages of AIR are its sensitivity, dynamic range, multiplex capability, and high-throughput compatibility. AIR has been used for the detection of antibodies against coronaviruses, influenza viruses, Staphylococcus aureus, and human autoantigens. It has also shown utility in detection of cytokines, with sensitivity comparable to bead-based and ELISA assays. Not limited to antibodies or antigens, mixed aptamer and protein arrays as well as glycan arrays have been employed in AIR for differentiating influenza strains. Mixed arrays using direct and competitive inhibition assays have enabled simultaneous measurement of cytokines and small molecules. Finally, AIR has also been used to measure affinity constants, kinetic and at equilibrium. In this review, we give an overview of AIR biosensing technologies and present the latest AIR advances.

Experimentation on HCHCr steel using vegetable oil as dielectric in EDM

With simplicity and accuracy, conductive hard materials may be machined using the non-traditional material removal technique known as electrical discharge machining (EDM). In the present research endeavour, the influence of using vegetable oil (fresh vegetable oil (FVO), Used Vegetable Oil (UVO) and Mixed Vegetable Oil (MVO)) as an eco-friendly dielectric fluid during die sinking EDM of HCHCr steel has been investigated. Effects of several input variables, including current, pulse width, gap voltage, duty cycle, and using copper and copper chromium electrodes have been examined by employing the Taguchi L18 mixed orthogonal array (OA) technique, to assess the response in terms of Material Removal Rate (MRR), Tool Wear Rate (TWR), and Surface Roughness (SR).

A generalization of group divisible t $t$‐designs

AbstractCameron defined the concept of generalized ‐designs, which generalized ‐designs, resolvable designs and orthogonal arrays. This paper introduces a new class of combinatorial designs which simultaneously provide a generalization of both generalized ‐designs and group divisible ‐designs. In certain cases, we derive necessary conditions for the existence of generalized group divisible ‐designs, and then point out close connections with various well‐known classes of designs, including mixed orthogonal arrays, factorizations of the complete multipartite graphs, large sets of group divisible designs, and group divisible designs with (orthogonal) resolvability. Moreover, we investigate constructions for generalized group divisible ‐designs and almost completely determine their existence for and small block sizes.

Hamming distances of tight orthogonal arrays

Orthogonal arrays (OAs) are widely applied in the statistical design of experiments. The Hamming distances of OAs play an increasingly important role in various areas; however, it is difficult to use Hamming distances, especially for tight and mixed orthogonal arrays (MOAs). For example, two OAs with the same parameters may have distinct Hamming distances due to their different structures and constructions. In addition, studies on Hamming distances of tight OAs are scant, with the exception of a study indicating that a tight symmetrical OA of strength 2 has a constant Hamming distance. In this article, we calculate Hamming distances for high-strength OAs, including all tight symmetrical OAs of strength 3, 4, and 5. Interestingly, the Hamming distances do not depend on the constructions or structures of the arrays. Additionally, we study the Hamming distances of several classes of MOAs of strength 2 and 3, some of which are not related to the structures of the arrays.

Ecological Assessment of the Native Flora of Matta Kharari Village, Swat, Khyber Pakhtunkhwa, Pakistan

Plant species composition, diversity and distribution is a hierarchical expression of vegetation determined by different environmental factors. A study was conducted to document the floristic composition and biological spectrum of plant species of the Matta-Kharari region, Swat. The region has not been ecologically explored yet. We used quantitative ecological techniques for sampling plant species. Sixty-seven quadrats of 1x1 m2 for herbs, 5x5 m2 for shrubs and 10x10 m2 size for trees were established. Plant species data were analyzed using multivariate statistical techniques. We evaluated 76 plant species belonging to 42 families. Asteraceae and Rosaceae were the leading families with 8 species each, followed by Ranunculaceae, Lamiaceae and Moraceae with 4 species each. Among life form classes i.e., geophytes were dominant (13 species, 17.10 %), followed by therophytes (12 species, 15.87 %), nanophanerophytes (11 species, 14.47 %), and chamaephytes (10 species, 13.58 %). Moreover, Mesophylls (36.84 %) were the dominant leaf spectra class followed by nanophyll (30.26 %), microphyll (27.63 %), and megaphyll (2.63 %). The two-way cluster analysis classified the vegetation into three clusters. The detrended correspondence analysis shows the distribution of plants in a mixed array because the locations explored are characterized by similar climatic factors and vegetation. We elucidate that the variation in climatic factors and topography brings variation in vegetation. Understanding these responses at the life form and leaf spectra level will provide a better understanding and knowledge that how plant species and their communities or associations respond to changes in climate in the future. The current study could be utilized as a baseline for large-scale studies in the future.

Optimization of process parameters on wire cut electrical discharge machining and surface integrity studies of AA6070/MgO composites

There are a variety of uses for metal matrix composites (MMC), including the aerospace and automotive industries. Because of their benefits including light weight and inexpensive cost, they are popular. Wire cut electric discharge machining (WEDM) stands out as a great option for creating complex or complicated shapes out of composite materials, especially when compared to other common non-traditional machining processes. An AA6070 metal matrix composite containing 5% and 10% MgO weight fraction (wt) was made using the stir casting method in this work. Various process factors, such as wire tension (WT), dielectric pressure (Pd), gap voltage (Vg) and peak current (IP) are taken into account when the AMMC specimen is machined utilising WEDM. Slot machining rate (MR) and surface roughness (Ra) can be measured and assessed using L18 mixed Orthogonal Array (OA) investigations. Experiments are examined using TOPSIS and ANOVA methodologies for order preference based on similarity to the ideal results (ANOVA). Analysis has shown that the best mixture of processing factors for improved MR and Ra: wt = 5%, vg = 50 V, WT = 13 g, Ip = 9 A, and Pd = 15 bar. Machining Rate and Ra have ideal process parameters of 1.5 mm/min and 3.648 m. ANOVA shows that MR and Ra are significantly influenced by peak current.