Pyrolyzed carbon materials give fascinating solutions for many problems in the current research world. The locally available organic wastes can be pyrolyzed and tuned for their properties for various applications. Coconut-based materials such as shell and fiber have shown promising results in different technological applications. However, a detailed study of the structural and property evolution of these materials has not been carried out yet. In this work, the evolution of conductivity and piezoresistivity of coconut fiber-derived carbon is studied. Coconut fiber is pyrolyzed at different temperatures 600 degrees C, (CCP600) 800 degrees C (CCP800) and 1000 degrees C (CCP1000) to produce carbon fiber. Electrical conductivity experiments show differences between CCP600, CCP800 and CCP1000, with CCP600 displaying much lower conductivity at approximately (0.7 S/m) compared to CCP800 (1 x 103 S/m) and CCP1000 (1.4 x 103 S/m). Conversely, CCP600 demonstrates impressive piezoresistive characteristics, exhibiting significant resistance changes even under minimal strain. The gauge factor for the coconut fiber-derived carbon was found to be 4.1 for CCP600, 1.0 for CCP800, and 0.3 for CCP1000. Further, the powdered carbon samples show an increase in the gauge factor to a range of 36.8, which makes CCP600 well-suited for sensor applications requiring precise sensing capabilities. The present study suggests that CCP600, with its low cost and ease of fabrication, is a promising material for low-budget sensor applications.

Accurate characterization of agricultural sprays is crucial to predict in-field performance of liquid applied crop protection products. In this paper, we introduce a robust and efficient machine learning (ML) based Digital In-line Holography (DIH) algorithm to accurately characterize the droplet field for a wide range of commonly used agricultural spray nozzles. Compared to non-ML based DIH processing, the ML-based algorithm enhances accuracy, generalizability, and processing speed. The ML-based approach employs two neural networks: a modified U-Net to obtain the 3D droplet field from the numerically reconstructed optical field, followed by a VGG16 classifier to reduce false positives from the U-Net prediction. The modified U-Net is trained using holograms generated using a single spray nozzle (XR11003) at three different spray locations; center, half-span, and the spray edge to create training data with different number densities and droplet size ranges. VGG16 is trained using the minimum intensity projection of the droplet 3D point spread function (PSF). Data augmentation is used to increase the efficiency of classification and make the algorithm generalizable for different measurement settings. The model is validated using National Institute of Standards and Technology (NIST) traceable glass beads and six different agricultural spray nozzles representing various spray characteristics. The principal results demonstrate a high accuracy rate, with over 90% droplet extraction and less than 5% false positives, regardless of droplet number density and size. Compared to traditional spray measurement techniques, the new ML-based DIH methodology offers a significant leap forward in spatial resolution and generalizability. We show that the proposed ML-based algorithm can extract the real cumulative volume distribution of the NIST beads, where the LD system measurements are biased towards droplets moving at slower speeds. Additionally, the ML-based DIH approach enables the estimation of mass and momentum flux at different locations and the calculation of relative velocities of droplet pairs, which are difficult to obtain using conventional spray characterization techniques.

Despite its potential for label-free particle diagnostics, holographic microscopy is limited by specialized processing methods that struggle to generalize across diverse settings. We introduce a deep learning architecture leveraging human perception of longitudinal variation of diffracted patterns of particles, which enables highly generalizable analysis of 3D particle information with orders of magnitude improvement in processing speed. Trained with minimal synthetic and real holograms of simple particles, our method demonstrates exceptional performance across various challenging cases, including high particle concentrations, significant noise, and a wide range of particle sizes, complex shapes, and optical properties, exceeding the diversity of training datasets.

The ePIC (electron-Proton/Ion Collider) experiment is a future facility at the Electron-Ion Collider (EIC) complex, located at the Brookhaven National Laboratory, USA. It will use 70% longitudinally polarized beam of electrons, protons, and light ions to study their collisions to understand the properties of the quarks, gluons, and the strong force responsible for the formation of the nucleus. The layout of the central detector of the ePIC experiment is not symmetric along the beams axis consisting of barrel, forward, and backward detectors to achieve a wide pseudorapidity ( |n| < 3.5) coverage. There are further far-forward and far-backward tracking detectors to measure the luminosity and reconstruct the particles and fragments for the study of the exclusive deep-inelastic scattering (DIS) processes. The experiment has a challenging environment due to the presence of the background radiations (synchrotron radiation, beam-gas interactions, minimum-bias events, etc.) which will produce additional background hits on the tracker. The synchrotron radiation is suppressed to some extent by coating the beampipe with a 5 mu m gold layer. The experiment uses state-of-the-art bent wafer-scale silicon monolithic active pixel sensors (MAPS) with a 5 mu s acquisition window, micro-pattern gas detector (MPGD) with a good time resolution ( 20-30 ns ), and time-of-flight detectors based on AC-LGAD sensors (time resolution 30 ps ). The timing information of each detector will play a crucial role in track finding and rejecting the background hits utilizing the 4-dimensional tracking (space, time) to ensure the excellent performance of the experiment. The article presents the expected tracking performance of the ePIC detector using the modular ePIC software stack for simulation, reconstruction, and analysis. The Geant4 toolkit is employed for full detector simulations, alongside DD4hep (Detector Description for High Energy Physics) for geometry definition and exchange. The reconstruction incorporates the JANA2 framework, in addition to the tracking and vertexing algorithms inherited from A Common Tracking Software (ACTS).

ZnO and Mn-doped Zn 0.92 Y 0.08-x Mn x O (x = 0, 0.01, 0.02, 0.04, 0.06) nanoparticles were synthesized hydrothermally and thoroughly characterized structurally, morphologically, and optically. X-ray diffraction (XRD) confirmed their crystalline wurtzite structure, with dopant concentration affecting lattice parameters, causing expansion or contraction. X-ray photoelectron spectroscopy (XPS) confirmed Mn and Y integration into the ZnO matrix. Scanning electron microscopy (SEM) showed morphological shifts from rods to flowers with increased Mn doping concentration. UV -visible absorption revealed optical band changes due to doping. Fourier transform infrared spectroscopy (FTIR) identified Zn -O, Y -O, and Mn -O bonds. Photoluminescence (PL) indicated intensity shifts with doping, suggesting dopant influence on defect -related emissions. Doped ZnO nanoparticles displayed superior hydrogen gas sensing, especially x = 0.04 at 250 degrees C, attributed to smaller size and structural changes.

Understanding the onset of clustering is an essential consideration in many engineering and natural systems. High operating costs and sophisticated methods associated with the existing spatial measurement techniques in clustering analysis call upon the use of low-dimensional measurements. In this experimental study, we study the 1D temporal droplet diameter data in a polydisperse droplet field with a background turbulence, to directly demonstrate a viable relationship between inertial clustering and the droplet arrival pattern. Upon the onset of clustering, a substantial increase is observed in the occurrence of ordinal patterns containing monotonically increasing sub-patterns, where smaller droplets are followed by bigger droplets, and a clear bifurcation in the occurrence of these patterns with downstream location is observed. These trends are understood in terms of droplet settling velocity. The mean flow dominated background turbulence enhances the settling velocity of clustered droplets, which induces a size–velocity correlation of the droplets and, as a result, increases the occurrence of ordinal patterns containing monotonically increasing sub-patterns. This study shows the potential of using low-dimensional measurements for the qualitative understanding of complex flows in different natural and engineering systems.

To investigate the characteristics of particle generation and dispersion during dental procedure using digital inline holography (DIH) Particles at two locations, near-field and far-field, which represent the field closer to the procedure location and within 0.5 m from the procedure location respectively, are studied using two different DIH systems. The effect of three parameters namely rotational speed, coolant flow rate, and bur angle on particle generation and dispersion are evaluated by using 10 different operating conditions. The particle characteristics at different operating conditions are estimated from the holograms using machine learning–based analysis. The particle concentration decreased by at least two orders of magnitude between the near-field and far-field locations across the 10 different operating conditions, indicating significant dispersion of the particles. High rotational speed is found to produce a larger number of smaller particles, while lower rotational speeds generate larger particles. Coolant flow rate is found to have a greater impact on particle transport to the far-field location. Irregular shape dental particles account for 29

In this study, a two-step stir casting technique was employed to fabricate composites using scrap aluminium cans (SAC) as matrix and a unique blend of Granite Particles (GP) and boron carbide (B4C) as reinforcements. Mono and hybrid composites were developed to evaluate the effects of the GP-B4C on the microstructure, mechanical properties, wear characteristics, and fracture behaviour of the composites. The microstructural characterization of the composites revealed that the incorporation of reinforcement into the aluminium matrix led to a refined grain structure with distinct interfaces. Both mono and hybrid composites exhibited improved hardness, with the hybrid composite showing a significant increase of 15.74 % in macro hardness and 16.33 % in microhardness compared to the base material. The mono composite demonstrates the highest ultimate tensile strength of 218 MPa, followed by the hybrid composite with a strength of 192 MPa. The improved mechanical properties of the mono composite are attributed to the reduction in grain size and the enhanced interfacial bonding between the reinforcement and the matrix. Although the hybrid composite exhibited more porosities, it shows the maximum ultimate compressive strength of 1124 MPa. The tensile fractured surfaces displayed dimples, cleavage facets, transgranular cracks, and river line markings. The wear loss of the mono composite decreased by 11.2 %, while that of the hybrid composite decreased by an impressive 28 % compared to their parent base matrix. The worn surface exhibits a combination of abrasive, adhesive, and delamination wear mechanisms.

Experimental and numerical studies are performed on the non-premixed n-dodecane spray cool flames in a counterflow burner. A novel phenomenon of repetitive autoignition-extinction instability of near-limit non-premixed spray cool flames is observed and examined. The spray cool flame is established by a polydisperse n-dodecane fuel spray generated from a twin-fluid atomizer, ranging from sub-micron sizes up to 400 μm with Sauter mean diameter of 109 μm. Digital Inline Holography is used to measure spray size distribution and quantify the fuel fraction in spray and gas phases at experimental conditions. The chemiluminescence of the excited formaldehyde molecule in spray cool flame is recorded by an Intensified-CCD (ICCD) camera to examine the repetitive cycles of autoignition and extinction, and to measure the spray cool flame stabilization time in each cycle. The repetitive autoignition and extinction cycles are found to be mostly caused by the competition between chemical heat release from low-temperature fuel oxidation, and heat loss in fuel spray vaporization in a counterflow, where the dynamics of large droplets in polydisperse spray play an important role. It is also found that with the increase of the oxygen mole fraction or the oxidizer temperature, the spray cool flame stabilization time increases and the cycles of autoignition and extinction become less frequent. A one-dimensional two-phase monodisperse spray combustion model with detailed chemistry is applied to reveal the spray cool flame structure and dynamics. It is shown that spray sizes determine the spray cool flame structure, where small droplets pose minimal impacts like gaseous flame while large droplets penetrating the flame front have double-edged effects on spray cool flames, leading to autoignition-extinction events. The experiments and simulations provide insights of this novel phenomenon of repetitive autoignition-extinction instability of near-limit non-premixed spray cool flames.

Natural processes, ranging from blood transport to planetary formation, are strongly influenced by particle collisions induced by background turbulence. While inertial clustering and particle pair relative velocity are recognized as the main collision enhancement factors, their physical coupling is poorly understood. In this experimental study, we measure clustering and relative velocity in a polydisperse droplet field with background air turbulence, to directly demonstrate the physical coupling between these collision enhancement factors. This coupling is shown to cause an inverse relation between clustering and relative velocity in the mean-flow–dominated turbulent flow we study, thus suppressing the intuitive effect of an increase in droplet collision rate with background air turbulence. Turbulence modulation due to clustering, and the resultant reduction of caustic droplet pairs with large relative velocities, are found to be the key physical mechanisms, and should be a consideration in droplet collision rate estimates in warm rain initiation.

Polymer pyrolysis has emerged as a versatile method to synthesize graphenoid (graphene like) materials with varying thickness and properties. The morphology of the thin film, especially the thickness, greatly affects the graphitizability and the properties of the graphenoid material. Using in situ current annealing inside a transmission electron microscope (TEM), the thickness-dependent structural evolution of the polymer film with a special focus on thickness effects is followed. At high temperatures, thin samples form large graphene layers oriented parallel to the substrate, whereas in thick samples multi-walled cage-like structures are formed. Moleclar Dynamics (MD) simulations reveal a film thickness of 40 angstrom below which, the carbonized layers align parallel to the surface. For thicker samples, the orientation of the layers becomes increasingly misoriented starting from the surface to the center. This structural change can be attributed to the formation of bonded multi-layers from the initially unsaturated activated edges. The resulting cage-like structures are stable even during simulated annealing at temperatures as high as 3500 K. An atomistic understanding of the formation of these structures is presented. The results clearly indicate the critical effect of thickness on the graphitizability of polymers and provide a new understanding of the structural evolution during pyrolysis.

The joining of heat-treated alloys(AA6061-T6) by the Welding process often results in a deterioration of mechanical properties because of the coarsening and dissolution of the strengthening precipitates (Mg2Si, Al3FeSi, Al12FeSi) at the weld nugget. However, it scares the applications of AA6061-T6 alloy. To enhance mechanical properties of Friction stir welded(FSWed) AA6061-T6 alloy and to minimize the loss of T6 condition, butt joints (FSW-SiC, FSW- B4C, FSW- TiB2, and FSW- Al2O3) were fabricated with the addition of more complex reinforcement particles( SiC, B4C, TiB2and Al2O3).In this work, the microstructure, tensile strength, surface properties such as hardness, and wear resistance of reinforced FSWed AA6061-T6 alloy joints were investigated. In contrast, the base metal and the welded joint prepared without reinforcement material were utilized as a reference to control the process. The grain refinement, which had been the reason for improved mechanical properties, was enhanced with reinforced particles in the weld region. Due to the high density of homogeneous dispersion of more complex reinforcement particles and considerably increased grain refinement throughout the welded joints, all the reinforced welded joints improved over the unreinforced joint in yield strength, hardness, and wear resistance. The addition of SiC, B4C, TiB2, and Al2O3 particles increases the hardness and wear resistance by14.5%,26.2%,8.9%, and 19.3%. At the same time, it did not influence much on the tensile properties compared to the unreinforced welded joint. Due to the extremely high hardness value and homogeneous dispersion of B4C particles in the FSW- B4C joint showed the highest percentage of hardness enhancement. Furthermore, the distribution of reinforcement particles improved the wear resistance of reinforced FSWed joints regardless of particle type compare to the base plate and unreinforced joint.

The air insulated high current medium energy 200 kV Ion Accelerator, with the terminal voltage in the range of 30-200 kV has been successfully operational at Ion Beam Centre, KU, Kurukshetra, India. A unique and imperative feature of this High Voltage Engineering Europa machine is the availability of only a single charge state, switching magnet with five exit ports and large area implantation using (-hollow cathode ion source). Ar+, B+, N+, Au+, H+, Ag+, Ni+ etc are the typically implanted ions. At present, only one beam line having beam rastering system is working specifically for material science research. The accelerator is consistently being used for conducting experiments using a wide variety of ion and target combination for research in diverse disciplines like materials science, atomic physics etc.. Ion beam sputter erosion experiments have been conducted successfully using different ion beams with varying current and energy. With the continued interest of researchers in this field, our accelerator's use and research output is likely to many-fold in the near future.

Control over the dimensions of nanoscale patterns on macroscopic areas of solid surfaces by varying ion beam parameters has been useful in electronic, optic and optoelectronic applications. This work presents a comparative study on projectile's (Ar and Kr) mass-dependent growth of ripples as a function of the incidence angle. Oblique implantation produces ripples between 50 degrees-70 degrees with highest ordering at similar to 60 degrees. Heavy mass implantation (Kr+) produces higher amplitude of ripples with shorter wavelength as compared to lighter Ar+ ion, and vice versa. Compositional study shows that the broader near surface damage for Ar+ under higher penetration range produces longer ripple wavelength as compared to Kr+.

Energy loss per unit length ( - dE/dx) of Li, C and O ions in self-supporting Ag foils is measured by adopting the transmission technique. These measured values are compared with the prediction of the most commonly used theoretical/semiempirical formulations, viz., Benton and Henke, Northcliffe-Schilling, Hubert et al., Diwan et al., ICRU report 73, Paul and Schinner (MSTAR V3.12 code), Grande and Schwietz (CasP 5.2 code), and Ziegler et al. (SRIM-2013.00 code). This comparison aims to check the accuracy of the considered formulations.

Polysilicon recombination junctions whose n‐type bottom layers double as a passivating contact to the silicon surface are investigated. Such recombination junctions are a key element in the interconnection of tandem devices with a silicon bottom cell, and they could be used to simplify the processing sequence of single‐junction cells with interdigitated back contacts (IBCs). Polysilicon tunneling junctions require high processing temperatures to crystallize the layers; however, this also facilitates interdiffusion of dopants, whereas tunnelling relies on degenerate doping concentrations in the constituent layers and sharp interfaces between them. Using secondary‐ion mass spectrometry (SIMS) in dynamic mode, it is found that dopants diffuse readily across the interface, thus compromising the junction. The undesired diffusion is suppressed by modifying the interface with C, O, or a combination of these. Moreover, it is found that the modification does not interfere with diffusion of H, an essential element to passivate defects at the surface of the silicon wafer. Thus, implied open‐circuit voltages (iV oc) of up to 740 mV are demonstrated for contact resistivities less than 40 mΩ cm2.