Uniform Energy Research Articles

Removal of Herbicide from Aqueous Solution Using Granular Activated Carbon: Equilibrium Data and Process Design

2,4-Dichlorophenoxyacetic acid (2,4-D) herbicide is a widely utilized herbicide known to be moderately toxic, have extensive use, poor biodegradability, and h led to contamination of surface and ground waters. The Granular Activated Carbon (GAC) was characterized by its porosity, surface morphology, and availability of functional groups. Type I isotherm was observed in the GAC, indicating microporosity with specific a surface area of 832.35 m2/g and pore diameter of 0.899 nm. GAC was evaluated for its ability to adsorb herbicide 2,4-D as the model adsorbate and evaluated the effects of initial concentration, contact time, pH, and activated carbon dosage on the adsorption process. According to the results, 94.01 %, 97.17%, 97.76 %, 98.15%, and 98.2 % of the adsorptive removal were achieved at initial concentrations of 10, 20, 30, 40, and 50 mg/l, respectively. Langmuir and Freundlich isotherm models were used to analyze the adsorption isotherm. It was determined that 2,4-D had a maximum monolayer adsorption capacity of 20.28 mg/g for GAC. Freundlich isotherm model predicted uniform binding energy distribution over heterogeneous surface binding sites for the best fit. The Freundlich model was used to design a batch adsorber capable of removing 2,4-D from effluent solutions of different volumes using the required mass of GAC. Resulting of the achieved results, GAC is a highly effective adsorbent for the removal of 2,4-D from aqueous environments.

Laguerre-Gaussian laser filamentation for the control of electric discharges in air.

We study the use of Laguerre-Gaussian (LG) femtosecond laser filament with multi GW peak power to guide electric sparks in the atmosphere. We demonstrate that an LG beam with a vortex phase or with 6 azimuthal phase steps generates a filamentation regime, where a longer and more uniform energy deposition is produced compared to a normal beam with a flat phase. Such filaments can guide electric discharges over much longer distances. This technique could significantly extend the guiding range of laser filaments for lightning control and other long-range atmospheric experiments involving filamentation.

Uniformizing the temperature of turbine blades during the heat treatment process from the perspective of radiation energy distribution

Nickel-based single-crystal turbine blades are critical components of jet engines. Due to element segregation and microstructural defects in as-cast blades, vacuum heat treatment is essential. Controlling the blades’ heat treatment temperature is crucial for improving mechanical performance. However, when treating multiple blades simultaneously, large temperature differences often occur, making it challenging to ensure consistent and uniform temperatures. This paper establishes a numerical algorithm that links blade temperature with radiant energy, optimizing blade arrangement to achieve uniform energy distribution and temperature field homogenization. The improved view factor finite element algorithm is more suitable for blade structures. The Particle Swarm Optimization (PSO) and Coordinate Descent (CD) methods were used to solve the optimization function, aiming to minimize the temperature difference among blades. Finite element simulation was utilized to model the temperature field of the blades during radiative heat transfer from heating elements. The PSO and CD optimization methods were employed to find the local optimal solution that minimizes the view factor variance, reducing it from 2.24 before optimization to about 1. Simultaneously, the optimized maximum average temperature difference of the blades was 71.1 °C, approximately 50 % lower than the 138.8 °C before optimization. By comparing the view factor values with the simulated temperature fields, the strong correlation between the view factor and blade temperature was verified. This paper innovatively proposes a numerical method for optimizing blade arrangement to homogenize the temperature field, effectively enhancing temperature consistency during the heat treatment process.

Non-contact targeted removal of remnant powder particles from additive manufacturing builds with nano-second laser pulsing

Post-production precision cleaning is one critical challenge in Additive Manufacturing (AM) production of high-value, critical parts/builds. A part shedding particle during its operational use could cause severe complications in critical applications such as medical devices and aerospace components. This study presents a non-contact precision particle removal procedure based on a novel Dry Laser Cleaning (DLC) framework. DLC utilizes the thermo-elastic wave generation/propagation and high-frequency surface acceleration fields to dislodge and remove remnant particles due to inertial forces from a well-defined (user-specified) cleaning zone in a non-contact manner, as opposed to cleaning the entire build surface, which could lead to undesirable re-deposition and re-location of particles as well as high cost. The removal of spherical Stainless Steel 316 L (SS316L) micro-particles commonly used in AM from polished, atomically flat Silicon (Si) wafer substrates with uniform high free surface energy using a nano-second laser pulse is experimentally and computationally investigated. In general, a rough surface has a lower average free surface energy; thus, its cleaning, compared to Si wafer, is less challenging. The data with the SS316-Si material pair offers a consistent baseline. In parallel to experiments, a fully-coupled thermo-mechanical finite element study is also conducted for transient surface acceleration simulations to predict the effectiveness of SS316L micro-particle removal from a Si wafer substrate with laser pulsation. It is observed that SS316L micro-particles with a diameter larger than 5.61 μm, 8.43 μm, and 12.24 μm can be removed entirely at 3 mm, 6 mm, and 9 mm distances from its epicenter, respectively. Accordingly, a work-of-adhesion of 990.8 mJ/m2 is selected between the SS316-Si material pair, consistent with the literature. The reported experiments and simulations demonstrate the potential of the proposed rapid precision particle removal procedure for cleaning critical powder-based AM builds, where the targeted removal of particles is essential for the safe and reliable operation of high-value builds and parts.

Calibration and performance evaluation of an N-type HPGe detector for a collimated and focused PGNAA system by experimental and Monte Carlo methods

The MCNP code was utilized to assess the operational status of an N-type high-purity germanium (HPGe) detector and to evaluate its potential for a collimated and focused Prompt Gamma Neutron Activation Analysis (PGNAA) detection system. In order to calibrate the detector, a narrow beam γ collimator was designed to scan the detector in both axial and radial directions. The curvature of the crystal front edge and the non-uniform description of the detector dead layer (DL) were taken into account when adjusting the effective crystal size. A collimated 137Cs γ source was used to assess the detection efficiency in the scanning experiments. Monte Carlo studies were performed using 0.662 MeV γ rays, and separately, a uniform γ-ray energy distribution from 0 to 1.6 MeV. Lastly, the effects of a collimation aperture with different sizes and different incident directions were considered to discuss the relationship between the spatial resolution and suitable measurement scenarios. Therefore, a detailed calibration method for non-uniform dead layers was introduced through a comparison between experiments and Monte Carlo simulations. This work reevaluates the performance of HPGe detectors and provides valuable data support for a detailed system design and γ spectroscopy analysis in future.

Pseudo-static topology optimization using the evolutionary-type method for reinforced concrete shear walls

For improved ductility in seismic-design reinforced concrete shear walls, a methodology referred to as pseudo-static topology optimization is incorporated to guide the design process. This approach involves a stepwise elimination of elements from the initial structural configuration, under specified conditions such as reciprocating loads, displacement constraints and volume limitations. The primary objective of this optimization is to maximize the structural capacity for energy dissipation. This is achieved by creating a sensitivity analysis based on variations in cumulative plastic strain energy resulting from element deletions. The final optimized topologies exhibit bar structures with exceptional capacity for energy dissipation. These optimized configurations evolve with changes in height–width ratios and axial compression ratios, shifting from structures with uniform energy dissipation to those with a two-level distribution. Furthermore, the orientation of the main bars changes from folded bars on both sides to inclined straight bars, depending on the specific conditions.

A comparative approach for estimating microstructural characteristics of BaTi1−xZrxO3 (0.0 ≤ x ≤ 0.3) nanoparticles via X-ray diffraction patterns

Barium titanate materials are currently a special topic for scientific research due to their effective technological applications. The tetragonal BaTi1-xZrxO3 (0.0 ≤ x ≤ 0.3) nanoparticles (NPs) were synthesized using a modified citrate technique. The current work provides a comparative approach for the calculation of crystallite size, stress, strain, and elastic characteristics based on X-ray diffraction (XRD) patterns. Various models have been developed to analyze XRD data; these models differ in their assumptions, mathematical approaches, and the type of information they provide. The Scherrer model ignores lattice micro-structures that develop in nanostructures, such as intrinsic strain. To overcome such drawbacks, three Williamson-Hall models, (the uniform deformation model (UDM)), the uniform stress deformation model (USDM), and the uniform deformation energy density model (UDEDM) have been discussed. According to the USDM model, with increasing Zr ion concentrations, interplanar space increases, causing a drop in Young’s modulus. All the previous approaches take into account the diffraction angle (2θ)-dependent peak broadening, which is thought to represent a combination of size and strain-driven induced broadening.Graphical

Flexible photodetector for broadband detection using wurtzite phase CuFeS2 nanoparticles

In the realm of electronic devices, a rising demand for flexible and enhanced performance has emerged. Current research predominately centres on optoelectronics and sensors within the flexible devices’ domain. A flexible photodetector, utilizing CuFeS2 (CFS), is crafted on a cellulose paper substrate. Employing the hand printing method, a thin film of CFS on a graphene-based transporting layer is fabricated. The wurtzite phase of the material synthesized using microwave−assisted method is confirmed by X−ray diffraction (XRD) and Raman spectroscopy, with compositional details provided by energy dispersive X−ray analysis. Comprehensive XRD based calculations of size, stress, strain and energy density are conducted using three different models - Uniform Deformation Model, Uniform Stress Deformation Model and Uniform Deformation Energy Density Model. The average particle size, strain and stress from the three different models is found to be 9⋅73 nm, 1⋅35 × 10−3, 55⋅05 MPa along with calculated energy density value of 78⋅421 kJ m−3, respectively. Band gap calculations utilizing diffuse reflectance yielded an optical bandgap of 1⋅23 eV for the CFS thin film. The fabricated photodetector is studied for different illumination wavelengths, 450 nm, 520 nm, 570 nm, 620 nm and 940 nm, to determined device parameters. The optimum rise time, decay time, responsivity, and specific detectivity for wavelength of 520 nm are 6⋅43 s, 7⋅01 s, 0⋅0319 mA W−1 and 1⋅173 × 1010 Jones. The photoresponse of the fabricated device bended to 2⋅5− and 5−mm radii is studied to recognize suppleness. The photoresponse showed the photocurrent decreases with increase of bending. The observed traits under bending switched to initial on flattening the thin film.

A prolegomenon to Design Input Energy Spectra for the Himalayan region

Energy-based design is becoming progressively significant as a new age of earthquake-resistant design unfolds. Thitherto, very little is known about energy-based design in India despite the fact that the Himalayan region is one of the most seismically active regions in the world. Therefore, the current work provides a preliminary analysis of the elastic input energy and equivalent velocity (Vea) spectra for the active regions in the Himalayas. In this regard, the ground motions of Himalayan databases are blended with NGA WEST2 to estimate the Vea spectra, an inertia-independent representation of the input energy spectra. Incipiently, an Artificial Neural Network-based ground motion model (GMM) is developed for Vea spectra based on the predictor variables as magnitude, distance, hypocentral depth and site conditions. Consequently, a Probabilistic Seismic Hazard analysis is performed to obtain the uniform hazard energy spectra for a 2475-year return period. In addition, a Design Input Energy Spectra is proposed for the active regions in the Indian Himalayas. In addition, the relationship between the Vea and pseudo-spectral velocity (PSV) is analyzed to develop a Vea-informed GMM for PSV. Furthermore, the PSA estimated from the Vea-PSV model is compared with the design spectra recommended by the Indian Standard Code of Practice (IS1893-1:2016).

Gram-scale microwave-assisted synthesis of high-quality CsPbBr3 nanocrystals for optoelectronic applications

Fully inorganic halide perovskite nanocrystals (NCs) are promising candidates for optoelectronic applications due to their beneficial properties such as their amenability to solution processing, high absorption coefficients, and high quantum yields. Various methods have been developed to prepare perovskite CsPbX3 (X = Cl, Br, and I) NCs; however, large-scale synthesis with high-quality CsPbX3 NCs remains challenging. In the study, we report an advanced method for the gram-scale synthesis of all-inorganic perovskite NCs via specially designed microwave-assisted synthesis, which offers uniform reaction energy transfer, excellent reproducibility, and flexible parameter tuning. The composition, size and uniformity of the CsPbBr3 NCs have been optimized by controlling the surfactant ratio, precursor ratio, and reaction time. This systematic optimization leads to the production of gram-scale (> 0.165 g per a 100 ml reaction mixture for a single synthesis cycle) high-quality, phase-pure CsPbBr3 NCs with a uniform size of ∼ 10 nm. These optimized NCs exhibit a sharp photoluminescence peak centered at 515 nm with a photoluminescence quantum yield of 94 % and produce excellent radioluminescence under X-ray irradiation. To test the feasibility of these NCs for use in real optoelectronic devices, a photodetector consisting of CsPbBr3 NCs and monolayer MoS2 was fabricated, demonstrating enhanced photosensitivity and a faster response time compared with a pure MoS2-based photodetector. The proposed gram-scale microwave-assisted synthesis method thus has the potential to promote the commercialization of metal halide perovskite NCs through cost-effective mass production for use in many optoelectronic applications.

Rapid Fabrication of Yttrium Aluminum Garnet Microhole Array Based on Femtosecond Bessel Beam

High-aspect-ratio microholes, the fundamental building blocks for microfluidics, optical waveguides, and other devices, find wide applications in aerospace, biomedical, and photonics fields. Yttrium aluminum garnet (YAG) crystals are commonly used in optical devices due to their low stress, hardness, and excellent chemical stability. Therefore, finding efficient fabrication methods to produce high-quality microholes within YAG crystals is crucial. The Bessel beam, characterized by a uniform energy distribution along its axis and an ultra-long depth of focus, is highly suitable for creating high-aspect-ratio structures. In this study, an axicon lens was used to shape the spatial profile of a femtosecond laser into a Bessel beam. Experimental verification showed a significant improvement in the high aspect ratio of the microholes produced in YAG crystals using the femtosecond Bessel beam. This study investigated the effects of the power and defocus parameters of single-pulse Bessel beams on microhole morphology and size, and microhole units with a maximum aspect ratio of more than 384:1 were obtained. Based on these findings, single-pulse femtosecond Bessel processing parameters were optimized, and an array of 181 × 181 microholes in a 400 μm thick YAG crystal was created in approximately 13.5 min. The microhole array had a periodicity of 5 μm and a unit aspect ratio of 315:1, with near-circular top and subface apertures and high repeatability.

Light-Triggered Inflation of Microdroplets.

Driven systems composed largely of droplets and fuel make up a significant portion of microbiological function. At the micrometer scale, fully synthetic systems that perform an array of tasks within a uniform bulk are much more rare. In this work, we introduce an innovative design for solid-in-oil composite microdroplets. These microdroplets are engineered to nucleate an internal phase, undergo inflation, and eventually burst, all powered by a steady and uniform energy input. We show that by altering the background input, volumetric change and burst time can be tuned. When the inflated droplets release the inner contents, colloidal particles are shown to transiently attract to the release point. Lastly, we show that the system has the ability to perform multiple inflation-burst cycles. We anticipate that our conceptual design of internally powered microdroplets will catalyze further research into autonomous systems capable of intricate communication as well as inspire the development of advanced, responsive materials.

Dedicated microwave extraction allows uniform energy distribution to efficiently solubilize Ascophyllum nodosum

Considering the current transition to biobased carbon sources and the search for viable extraction procedures, the microwave-assisted solubilization of seaweed biomass was explored. Hereto, the brown North Sea native species Ascophyllum nodosum was processed using water as green extraction solvent. Response surface methodology was used to determine the best solubilization conditions towards maximizing the solubilization efficiency and minimizing the applied energy per mass of solubilized seaweed by varying (i) temperature, (ii) time and (iii) solid to liquid ratio (S/L). It was found that a temperature of 120 °C, a processing time of 15 min and a 1.03 w:v S/L are most suitable to achieve the pre-set criteria. Concurrently, mass balances were developed with respect to total lipid, polysaccharide, protein, mineral and heavy metal contents. Moreover, zeta potential measurements were performed to link the obtained values and the antimicrobial characteristics of the extracts. Finally, antimicrobial tests on S. aureus and E. coli were conducted and with results indicating up to 97 % inhibition of bacterial growth after 8 h, antimicrobial characteristics were indeed observed.

An elliptical compressible liquid inclusion in an infinite nonlinearly coupled thermoelectric matrix

We study the plane strain problem associated with an elliptical thermoelectrically insulated and compressible liquid inclusion embedded in an infinite homogeneous and isotropic nonlinearly coupled thermoelectric matrix under uniform remote electric current density and energy flux. With the aid of conformal mapping and analytic continuation, an exact closed-form solution to the problem is derived. In particular, an elementary expression for the internal uniform hydrostatic tension within the compressible liquid inclusion is obtained. Our result shows that the internal uniform hydrostatic tension is unaffected by the remote energy flux and is proportional to the square of the two components of the remote electric current density vector. Also presented is the hoop stress distribution along the elliptical interface on the matrix side.

An Intelligent Energy-Efficient Data Routing Scheme for Wireless Sensor Networks Utilizing Mobile Sink

Data collection and energy consumption are critical concerns in Wireless sensor networks (WSNs). To address these issues, both clustering and routing algorithms are utilized. Therefore, this paper proposes an intelligent energy-efficient data routing scheme for WSNs utilizing a mobile sink (MS) to save energy and prolong network lifetime. The proposed scheme operates in two major modes: configure and operational modes. During the configure mode, a novel clustering mechanism is applied once, and a prescheduling cluster head (CH) selection is introduced to ensure uniform energy expenditure among sensor nodes (SNs). The scheduling technique selects successive CHs for each cluster throughout the WSNs’ lifetime rounds, managed at the base station (BS) to minimize SN energy consumption. In the operational mode, two main objectives are achieved: sensing and gathering data by each CH with minimal message overhead, and establishing an optimal path for the MS using the genetic algorithm. Finally, the MS uploads the gathered data to the BS. Extensive simulations are conducted to verify the efficiency of the proposed scheme in terms of stability period, network lifetime, average energy consumption, data transmission latency, message overhead, and throughput. The results demonstrate that the proposed scheme outperforms the most recent state-of-the-art methods significantly. The results are substantiated through statistical validation via hypothesis testing utilizing ANOVA, as well as post hoc analysis.

Data aggregation algorithm for wireless sensor networks with different initial energy of nodes.

Data aggregation plays a critical role in sensor networks for efficient data collection. However, the assumption of uniform initial energy levels among sensors in existing algorithms is unrealistic in practical production applications. This discrepancy in initial energy levels significantly impacts data aggregation in sensor networks. To address this issue, we propose Data Aggregation with Different Initial Energy (DADIE), a novel algorithm that aims to enhance energy-saving, privacy-preserving efficiency, and reduce node death rates in sensor networks with varying initial energy nodes. DADIE considers the transmission distance between nodes and their initial energy levels when forming the network topology, while also limiting the number of child nodes. Furthermore, DADIE reconstructs the aggregation tree before each round of data transmission. This allows nodes closer to the receiving end with higher initial energy to undertake more data aggregation and transmission tasks while limiting energy consumption. As a result, DADIE effectively reduces the node death rate and improves the efficiency of data transmission throughout the network. To enhance network security, DADIE establishes secure transmission channels between transmission nodes prior to data transmission, and it employs slice-and-mix technology within the network. Our experimental simulations demonstrate that the proposed DADIE algorithm effectively resolves the data aggregation challenges in sensor networks with varying initial energy nodes. It achieves 5-20% lower communication overhead and energy consumption, 10-20% higher security, and 10-30% lower node mortality than existing algorithms.

Effect of auxiliary laser irradiation on characteristics and properties of micro-arc oxidation coating on Ti6Al4V alloy

In this study, auxiliary laser irradiation was introduced into MAO processing (L-MAO), and its influence on the microstructure and properties of MAO coating was investigated. The results show that laser irradiation causes a reduction in the breakdown and working voltage of MAO processing while the number and brightness of discharge channels increase. Generating more discharge channels promotes a uniform energy distribution on each discharge channel and avoids the formation of high-intensity discharges. Therefore, after introducing laser irradiation, the obtained coating improves in terms of homogeneity, density, thickness, and bonding strength. Compared with MAO processing, the thickness of coating prepared by L-MAO processing increases by 33.8%, while the porosity decreases from 11.94% to 9.77%. The compositions and phase of coating are also impacted after introducing laser irradiation. More electrolyte ions (SiO32−) enter the coating under laser irradiation, raising the Si content from 18.804 to 21.309 at. %. Besides, more rutile TiO2 phases are detected in L-MAO coating. Based on the above microstructural improvements by laser irradiation, the wear and corrosion resistance of the resultant coating are enhanced correspondingly relative to the MAO processing without laser irradiation.

Puiseux asymptotic expansions for convection-dominated transport problems in thin graph-like networks: Strong boundary interactions

This article completes the study of the influence of the intensity parameter α in the boundary condition ε ∂ ν ε u ε − u ε V ε → · ν ε = ε α φ ε given on the boundary of a thin three-dimensional graph-like network consisting of thin cylinders that are interconnected by small domains (nodes) with diameters of order O ( ε ). Inside of the thin network a time-dependent convection-diffusion equation with high Péclet number of order O ( ε − 1 ) is considered. The novelty of this article is the case of α < 1, which indicates a strong intensity of physical processes on the boundary, described by the inhomogeneity φ ε (the cases α = 1 and α > 1 were previously studied by the same authors). A complete Puiseux asymptotic expansion is constructed for the solution u ε as ε → 0, i.e., when the diffusion coefficients are eliminated and the thin network shrinks into a graph. Furthermore, the corresponding uniform pointwise and energy estimates are proved, which provide an approximation of the solution with a given accuracy in terms of the parameter ε.

Preparation and Performance Study of Titanium‐Based Nanocomposites in Selective Laser Melting: Microstructure Regulation and Optimization of Mechanical Properties

This study focuses on exploring the application of selective laser melting (SLM) technology in the preparation of titanium‐based nanocomposite materials. By introducing 0.5 wt% graphene oxide (GO) and 7.0% nanomolybdenum (Mo) powder, an attempt is made to improve the microstructure and mechanical properties of titanium alloy materials. The experimental results indicate that the microstructure of the titanium‐based nanocomposite material undergoes significant crystal refinement and phase transition behavior, suggesting a positive role of introducing nanoreinforcing phases in crystal structure regulation. Simultaneously, the introduction of GO significantly improves the thermal conductivity of the material, contributing to more uniform energy transfer and temperature distribution, thereby optimizing the process control of laser melting. In terms of mechanical performance, through microhardness and tensile performance tests, the microhardness of TC4–0.5GO–7Mo increases by ≈30.8% compared with pure TC4. This strengthening effect is primarily attributed to the uniform distribution of GO and Mo powder in the matrix, effectively hindering lattice slip and dislocation movement, enhancing the hardness and tensile properties of the material. Through a comprehensive analysis of microstructure and mechanical properties, not only the mapping relationship between the microstructure and mechanical properties of titanium‐based nanocomposite materials is clarified but also the strengthening mechanism is revealed.

X-ray diffraction analysis of orthorhombic SnSe nanoparticles by Williamson–Hall, Halder–Wagner and Size–Strain plot methods

SnSe nanoparticles were synthesized using the sonochemical exfoliation technique, employing SnSe single crystals. Various analysis, including Energy Dispersive Analysis of X-rays-Elemental mapping, X-ray Diffraction (XRD), High-Resolution Transmission Electron Microscopy, Ultra-Violet Diffused Reflectance Spectroscopy-Photoluminescence measurements, Raman spectroscopy, and X-ray Photoelectron Spectroscopy, were conducted to determine the chemical composition, crystalline phase, morphological characteristics, optical properties, vibrational modes, and oxidation states of the synthesized nanoparticles. The XRD peak broadening analysis, specifically employing Williamson–Hall (W-H), Size–Strain Plot (SSP), and Halder–Wagner Method (H-W), was employed to examine particle size and intrinsic strain. Additionally, three models within the W-H method, namely the uniform deformation model (UDM), uniform stress deformation model (USDM), and uniform deformation energy density model (UDEDM), were used to investigate physical and microstructural parameters such as strain, stress, and energy density. A comprehensive comparison of the average particle size results obtained from Williamson–Hall, Size–Strain, and Halder–Wagner Methods, along with results from HR-TEM and Particle Size Analysis, was carried out. The comprehensive comparison of results from different techniques adds credibility to the reported findings.