Emerging global trends and development in forensic toxicology: A review.

This study conducts a comprehensive analysis of forensic toxicology research trends, publication patterns, author's contributions, and collaboration. Utilizing the Scopus database, we scrutinized 3259 articles across 348 journals spanning from 1975 to 2023. Analysis employed diverse software tools such as VOSviewer, RStudio, MS Excel, and MS Access to dissect various publication aspects. We observed a notable surge in publications post-2007, indicating heightened research interest. Leading contributors included the United States, Germany, and Italy, with Logan B.K. emerging as the most prolific author. Forensic Science International stood out as the primary journal, publishing 888 articles and accruing significant citations. Keyword co-occurrences such as "forensic toxicology," "forensic science," and "toxicology" underscored core thematic areas in the field. Moreover, extensive research collaboration, especially among Western nations in Europe, was evident. This study underscores the imperative for enhanced collaboration between developing and developed nations to foster further advancements in forensic science. Strengthened partnerships can catalyze innovation, facilitate knowledge dissemination, and address emerging challenges, thereby propelling the field of forensic toxicology toward new frontiers of discovery and application.

Experimental Investigations of Using Aluminum Oxide (Al2O3) and Nano-Graphene Powder in the Electrical Discharge Machining of Titanium Alloy.

In the present study, a comprehensive parametric analysis was carried out using the electrical discharge machining of Ti6Al4V, using pulse-on time, current, and pulse-off time as input factors with output measures of surface roughness and material removal rate. The present study also used two different nanopowders, namely alumina and nano-graphene, to analyze their effect on output measures and surface defects. All the experimental runs were performed using Taguchi's array at three levels. Analysis of variance was employed to study the statistical significance. Empirical relations were generated through Minitab. The regression model term was observed to be significant for both the output responses, which suggested that the generated regressions were adequate. Among the input factors, pulse-off time and current were found to have a vital role in the change in material removal rate, while pulse-on time was observed as a vital input parameter. For surface quality, pulse-on time and pulse-off time were recognized to be influential parameters, while current was observed to be an insignificant factor. Teaching-learning-based optimization was used for the optimization of output responses. The influence of alumina and nano-graphene powder was investigated at optimal process parameters. The machining performance was significantly improved by using both powder-mixed electrical discharge machining as compared to the conventional method. Due to the higher conductivity of nano-graphene powder, it showed a larger improvement as compared to alumina powder. Lastly, scanning electron microscopy was operated to investigate the impact of alumina and graphene powder on surface morphology. The machined surface obtained for the conventional process depicted more surface defects than the powder-mixed process, which is key in aeronautical applications.

Fabrication of Multi-Walled Structure through Parametric Study of Bead Geometries of GMAW-Based WAAM Process of SS309L.

In the present study, an attempt is made to investigate and optimize the bead geometries of bead width (BW) and bead height (BH) of SS-309L using an SS316L substrate by employing a gas metal arc welding (GMAW)-based wire-arc additive manufacturing (WAAM) process. The Box-Behnken design approach was used to conduct the trials of single-layer depositions with input variables of travel speed (TS), voltage (V), and gas mixture ratio (GMR). The developed multi-variable regression models were tested for feasibility using ANOVA and residual plots. The data obtained indicated that V had the most significant impact on BW, followed by TS and GMR. For BH, TS had the most significant impact, followed by GMR and V. The results of single-response optimization using a passing vehicle search (PVS) algorithm showed a maximum BH of 9.48 mm and a minimum BW of 5.90 mm. To tackle the contradictory situation, a multi-objective PVS algorithm was employed, which produced non-dominated solutions. A multi-layered structure was successfully fabricated at the optimal parametric settings of TS at 20 mm/s, of voltage at 22 V, and of GMR at 3. For multi-layer structures, fusion among the layers was observed to be good, and they were found to be free from the disbonding of layers. This revealed the suitability of the PVS algorithm for generating suitable optimal WAAM variables. We consider the current work highly beneficial for users fabricating multi-layer structures.

Implementation of Passing Vehicle Search Algorithm for Optimization of WEDM Process of Nickel-Based Superalloy Waspaloy.

Nickel-based superalloys find their main use in missile engines, atomic devices, investigational aircraft, aerospace engineering, industrial applications, and automotive gas turbines, spacecraft petrochemical tools, steam power, submarines, and broader heating applications. These superalloys impose certain difficulties during the process fabrication owing to their levels of higher hardness. In the current study, the precise machining of Waspaloy was attempted through the wire electrical discharge machining (WEDM) technique. A multi-objective optimization has been performed, and the influence of multi-walled carbon nanotubes (MWCNTs) has been assessed using the passing vehicle search (PVS) algorithm. The effects of machining variables like current, Toff, and Ton were studied using the output measures of material removal rate (MRR), recast layer thickness (RLT), and surface roughness (SR). The Box-Behnken design was applied to generate the experimental matrix. Empirical models were generated which show the interrelationship among the process variables and output measures. The analysis of variance (ANOVA) method was used to check the adequacy, and suitability of the models and to understand the significance of the parameters. The PVS technique was executed for the optimization of MRR, SR, and RLT. Pareto fronts were derived which gives a choice to the user to select any point on the front as per the requirement. To enhance the machining performance, MWCNTs mixed dielectric fluid was utilized, and the effect of these MWCNTs was also analyzed on the surface defects. The use of MWCNTs at 1 g/L enhanced the performance of MRR, SR, and RLT by 65.70%, 50.68%, and 40.96%, respectively. Also, the addition of MWCNTs has shown that the machined surface largely reduces the surface defects.

Experimental Investigations and Effect of Nano-Powder-Mixed EDM Variables on Performance Measures of Nitinol SMA.

In the present study, the effect of alumina (Al2O3) nano-powder was investigated for the electrical discharge machining (EDM) of a Nitinol shape memory alloy (SMA). In addition to the nano-powder concentration, other parameters of pulse-on-time (Ton), pulse-off-time (Toff), and current were selected for the performance measures of the material removal rate (MRR), surface roughness (SR), and tool wear rate (TWR) of Nitinol SMA. The significance of the design variables on all the output measures was analyzed through an analysis of variance (ANOVA). The regression model term has significantly impacted the developed model terms for all the selected measures. In the case of individual variables, Al2O3 powder concentration (PC), Toff, and Ton had significantly impacted MRR, TWR, and SR measures, respectively. The influence of EDM variables were studied through main effect plots. The teaching-learning-based optimization (TLBO) technique was implemented to find an optimal parametric setting for attaining the desired levels of all the performance measures. Pursuant to this, the optimal parametric settings of current at 24 A, PC at 4 g/L, Toff at 10 µs, and Ton of 4 µs have shown optimal input parameters of 43.57 mg/min for MRR, 6.478 mg/min for TWR, and 3.73 µm for SR. These results from the TLBO technique were validated by performing the experiments at the optimal parametric settings of the EDM process. By considering the different user and application requirements, 40 Pareto points with unique solutions were generated. Lastly, scanning electron microscopy (SEM) performed the machined surface analysis. The authors consider this to be very beneficial in the nano-powder-mixed EDM process for appropriate manufacturing operations.

Parametric Optimization and Influence of Near-Dry WEDM Variables on Nitinol Shape Memory Alloy.

Nitinol-shape memory alloys (SMAs) are widely preferred for applications of automobile, biomedical, aerospace, robotics, and other industrial area. Therefore, precise machining of Nitinol SMA plays a vital role in achieving better surface roughness, higher productivity and geometrical accuracy for the manufacturing of devices. Wire electric discharge machining (WEDM) has proven to be an appropriate technique for machining nitinol shape memory alloy (SMA). The present study investigated the influence of near-dry WEDM technique to reduce the environmental impact from wet WEDM. A parametric optimization was carried out with the consideration of design variables of current, pulse-on-time (Ton), and pulse-off-time (Toff) and their effect were studied on output characteristics of material removal rate (MRR), and surface roughness (SR) for near-dry WEDM of nitinol SMA. ANOVA was carried out for MRR, and SR using statistical analysis to investigate the impact of design variables on response measures. ANOVA results depicted the significance of the developed quadratic model for both MRR and SR. Current, and Ton were found to be major contributors on the response value of MRR, and SR, respectively. A teaching-learning-based optimization (TLBO) algorithm was employed to find the optimal combination of process parameters. Single-response optimization has yielded a maximum MRR of 1.114 mm3/s at Ton of 95 µs, Toff of 9 µs, current of 6 A. Least SR was obtained at Ton of 35 µs, Toff of 27 µs, current of 2 A with a predicted value of 2.81 µm. Near-dry WEDM process yielded an 8.94% reduction in MRR in comparison with wet-WEDM, while the performance of SR has been substantially improved by 41.56%. As per the obtained results from SEM micrographs, low viscosity, reduced thermal energy at IEG, and improved flushing of eroded material for air-mist mixture during NDWEDM has provided better surface morphology over the wet-WEDM process in terms of reduction in surface defects and better surface quality of nitinol SMA. Thus, for obtaining the better surface quality with reduced surface defects, near-dry WEDM process is largely suitable.

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy.

Shape memory alloy (SMA), particularly those having a nickel-titanium combination, can memorize and regain original shape after heating. The superior properties of these alloys, such as better corrosion resistance, inherent shape memory effect, better wear resistance, and adequate superelasticity, as well as biocompatibility, make them a preferable alloy to be used in automotive, aerospace, actuators, robotics, medical, and many other engineering fields. Precise machining of such materials requires inputs of intellectual machining approaches, such as wire electrical discharge machining (WEDM). Machining capabilities of the process can further be enhanced by the addition of Al2O3 nanopowder in the dielectric fluid. Selected input machining process parameters include the following: pulse-on time (Ton), pulse-off time (Toff), and Al2O3 nanopowder concentration. Surface roughness (SR), material removal rate (MRR), and recast layer thickness (RLT) were identified as the response variables. In this study, Taguchi's three levels L9 approach was used to conduct experimental trials. The analysis of variance (ANOVA) technique was implemented to reaffirm the significance and adequacy of the regression model. Al2O3 nanopowder was found to have the highest contributing effect of 76.13% contribution, Ton was found to be the highest contributing factor for SR and RLT having 91.88% and 88.3% contribution, respectively. Single-objective optimization analysis generated the lowest MRR value of 0.3228 g/min (at Ton of 90 µs, Toff of 5 µs, and powder concentration of 2 g/L), the lowest SR value of 3.13 µm, and the lowest RLT value of 10.24 (both responses at Ton of 30 µs, Toff of 25 µs, and powder concentration of 2 g/L). A specific multi-objective Teaching-Learning-Based Optimization (TLBO) algorithm was implemented to generate optimal points which highlight the non-dominant feasible solutions. The least error between predicted and actual values suggests the effectiveness of both the regression model and the TLBO algorithms. Confirmatory trials have shown an extremely close relation which shows the suitability of both the regression model and the TLBO algorithm for the machining of the nanopowder-mixed WEDM process for Nitinol SMA. A considerable reduction in surface defects owing to the addition of Al2O3 powder was observed in surface morphology analysis.

Thermal crowning mechanism in gold-silica nanocomposites: plasmonic-photonic pairing in archetypal two-dimensional structures.

A close-packed monolayer of a two-dimensional periodic array of Silica nanospheres (SNs) with gold (Au) crowning, forming a long-ranged archetypal plasmonic-photonic nanocomposite, has been achieved. We investigate the thermal crowning mechanism in such a nanocomposite using electron microscopy and X-ray diffraction techniques. Pre- and post-annealing morphological features reveal gold crowning on top of SNs, at different annealing temperatures for various thicknesses of the sputter-deposited gold. In situ grazing incidence X-ray diffraction was employed to structurally characterize the reconstruction in the Au-layer as a function of the annealing temperature. Finite element methods were used to simulate the interaction between the paired nanocomposites and the incident electromagnetic radiations to elucidate the crowning and nanodrop formation mechanism. This study provides an insight into real-time morphological and structural changes of a dewetting plasmonic film over a photonic basis and explores a robust, reliable, and scalable route to fabricate coupled nanocomposites. Such nanocomposites allow prospective applications in optoelectronics, sensing, catalysis, and surface-enhanced Raman spectroscopy by exploiting the plasmonic-photonic pairing in archetypal two-dimensional structures.

Parametric Optimization and Effect of Nano-Graphene Mixed Dielectric Fluid on Performance of Wire Electrical Discharge Machining Process of Ni55.8Ti Shape Memory Alloy.

In the current scenario of manufacturing competitiveness, it is a requirement that new technologies are implemented in order to overcome the challenges of achieving component accuracy, high quality, acceptable surface finish, an increase in the production rate, and enhanced product life with a reduced environmental impact. Along with these conventional challenges, the machining of newly developed smart materials, such as shape memory alloys, also require inputs of intelligent machining strategies. Wire electrical discharge machining (WEDM) is one of the non-traditional machining methods which is independent of the mechanical properties of the work sample and is best suited for machining nitinol shape memory alloys. Nano powder-mixed dielectric fluid for the WEDM process is one of the ways of improving the process capabilities. In the current study, Taguchi's L16 orthogonal array was implemented to perform the experiments. Current, pulse-on time, pulse-off time, and nano-graphene powder concentration were selected as input process parameters, with material removal rate (MRR) and surface roughness (SR) as output machining characteristics for investigations. The heat transfer search (HTS) algorithm was implemented for obtaining optimal combinations of input parameters for MRR and SR. Single objective optimization showed a maximum MRR of 1.55 mm3/s, and minimum SR of 2.68 µm. The Pareto curve was generated which gives the optimal non-dominant solutions.

Intranasal solid lipid nanoparticles for management of pain: A full factorial design approach, characterization & Gamma Scintigraphy.

Pain is a noxious stimulus caused due to tissue damage and varies from mild to severe. Nalbuphine (NLB) is an approved, inexpensive, non-controlled, opioid agonist/antagonist analgesic used worldwide in various clinical settings for pain management. The current study aims to formulate NLB loaded solid lipid nanoparticles (SLNs) using solvent injection technology. The morphological and chemical structure of the developed SLNs were characterized using Field Emission Scanning Electron Microscopy (FESEM), Transmission Electron Microscopy (TEM) and Fourier Transformation Infrared Spectroscopy (FTIR). The results revealed from the point prediction confirmation in design expert software was the formulation of NLB-SLNs with an average particle size of (170.07 ± 25.1 nm), encapsulation efficiency (93.6 ± 1.5%) & loading capacity of 26.67%. The in-vitro permeation of developed NLB-SLNs was observed to be 94.18% at 8 h when compared with NLB solution whose maximum permeation was seen within 3 h of application. Efficacy of the formulation was also evaluated using eddy's hot plate method, where the onset of action started within 10 min of administration, and the maximum effect was observed at 1 h. The NLB-SLNs was screened for cytotoxicity in human embryonic kidney cells (HEK-293), and the dosage was considered safe when administered intranasally in animal since no detectable effect to the brain was observed. Biodistribution and gamma scintigraphy study of NLB-SLNs showed the prepared formulation reaching the target site, i.e. brain and was retained. Conclusively, the prepared NLB-SLNs formulation was safe and effective in producing an analgesic effect in vivo.

Effective light polarization insensitive and omnidirectional properties of Si nanowire arrays developed on different crystallographic planes.

In this paper, fabrication of vertical Si nanowire arrays (SiNWAs) by a facile metal assisted chemical etching approach on different crystallographic planes of Si has been reported. A very low specular reflectance (R spec ) of 0.04% and 0.03% has been achieved in the whole visible range for SiNWAs grown on Si(100) and Si(111) oriented substrates, respectively. High broadband enhancement has been detected for vertical SiNWAs due to multiple scattering paths inside the nanowire arrays. On the other hand, inclined nanowires showed a fascinating behavior at the longer wavelength regime, where light gets the longer path to reflect back-forth and ease to reflect back outward at normal incidence. Moreover, for [100] SiNWAs, transverse electric field component demonstrates the strong polarization insensitive properties at the expense of transverse magnetic field component with a minimum reflectance of <2% up to 1200 nm. The [100] SiNWAs demonstrates extraordinary omnidirectional properties at θ B ≥ 58°. Theoretical validation of COMSOL with an effective medium approach reveal the effective dipole coupling and the presence of strong absorption modes for vertical SiNWs at a typical wavelength regime. The highly bound states of the particle tunneling through classical forbidden region shows a strong dependence on the gradient in the refractive index (mi ) from 1 to 3.4. The high order scattering effect is observed at ∼520 cm-1 in a disordered optical medium. This novel finding of light localization properties for SiNWAs with different orientation gives a new route to support various photonic applications.