226 research outputs found
Ball and stick model of nucleic acid.
No full text<p>Ball and stick model of various types of nucleic acid helical forms, showing base inclination angle axis (solid red line); diameter of groove (dashed blue line).</p
Raman Studies of Ball Mill Synthesized Bulk Cu2ZnSnSe4
No full textKesterite with chemical formula Cu2ZnSnSe4 (CZTSe) has been synthesized by ball milling followed by annealing and hot pressing. Mechanochemical synthesis was carried out in the presence of process control agent namely toluene under two different milling conditions. Structural and phase evolution during different stages of the synthesis was studied with X-ray diffraction (XRD) and Raman spectroscopy. Near resonant Raman spectrum was obtained by making use of laser wavelength of 488 nm to resolve the presence of secondary ZnSe which otherwise is difficult to conclude with XRD alone. Deconvoluted Raman spectrum confirmed the presence of CZTSe along with secondary phases Cu2SnSe3 (CTSe) and ZnSe. This inference was further confirmed by electron probe micro analysis (EPMA) and wavelength dispersive spectroscopy (WDS) studies
Study of thermo-fluidic behavior of micro-droplet in inkjet-based micro manufacturing processes
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Effect of grain size on structural and dielectric properties of barium titanate piezoceramics synthesized by high energy ball milling
No full textCarbonaceous Composite Materials. Materials Research Foundations Ser.
No full text2. Lithium-ion batteries.This book reports current progress in the development, design and utilization of carbonaceous materials in such diverse areas as electronics, medical implants, drug delivery, clean energy, biofuel and pollution control. Keywords: Carbonaceous Materials, Carbons, Graphite, Biochar, Fullerenes, Graphene, Carbon Foam, Carbon Nanotubes, Graphene Oxide, Graphitic Carbon Nitride, Carbon Aerogels, Carbon Matrix Composites, Organic-inorganic Hybrid Materials, Building Materials, Carbon-based Composites, Carbon Matrix Polymer Composites, Conducting Polymers, Clean Energy, Energy Storage, Electrode Mate.Intro; Table of Contents; Preface; 1; Graphene and Graphene/TiO2 Nanocomposites for Renewable Dye Sensitized Solar Cells; 1. Introduction; 2. Historical overview of DSSCs; 2.1 Material Selection for DSSCs; 3. Reduced graphene oxide (rGO); 3.1 Electronic properties of rGO based bilayer systems; 3.2 Thermal conductivity of rGO; 3.3 Optical properties of rGO; 3.4 Electrochemical performance of rGO; 4. TiO2-rGO NC material; 4.1 TiO2-rGO NC material's properties; 4.2 Formation mechanism of TiO2-rGO NC material; 4.4 Preparation of TiO2-rGO NC; 4.4.1 Sol-Gel synthesis.4.4.2 Solution mixing synthesis4.4.3 In-Situ growth synthesis; 5. Conclusion; 6. Acknowledgements; References; 2; Carbon Based Nanomaterials for Energy Storage; 1. Introduction; 2. Carbonaceous nanomaterials; 2.1 Origin; 2.2 Fullerenes; 2.3 Carbon nanotubes; 2.4 Graphene; 2.5 Nitrogen doped carbon nanomaterial; 2.6 Carbon gels; 3. Energy storage system; 3.1 Electrochemical storage system; 3.1.1 Binder free electrodes; 3.1.2 Super capacitors; 3.1.3 Lithium-ion batteries; 3.2 Nanomaterials as electrodes; 3.3 Hydrogen storage system; 3.4 Thermal energy storage; 3.5 Nanomaterials as Fuel cells.3.6 Capture of carbondioxide and methane4. Conclusion and future development; References; 3; Molecular Dynamics Simulation of Capped Single Walled Carbon Nanotubes and their Composites; 1. Introduction; 2. Materials and method; 2.1 CNT; 2.2 Polymer; 2.3 Simulation strategy; 3. Total potential energies and inter-atomic forces; 4. Stiffness of SWCNTs; 4.1 Modeling of SWCNTs; 4.2 Geometry optimization; 4.3 Dynamics; 4.4 Mechanical properties; 5. Results and discussion; 6. Polymer/CNT Composites; 6.1 Molecular model of polymer matrix; 6.2 Elastic moduli of polymer; 6.3 PMMA/CNT composite system.7. ConclusionReferences; 4; Fullerenes and its Composites; 1. Introduction; 2. Fullerenes; 2.1 Types of fullerenes; 2.1.1 Nanotubes; 2.1.2 Mega tubes; 2.1.3 Bucky ball clusters; 2.1.4 Polymers; 2.1.5 Nano onion; 2.1.6 Linked "ball and chain" dimers; 3. Structure of fullerene; 3.1 Bucky ball structure; 3.2 Cylindrical structure; 4. Synthesis; 4.1 Arc discharge vaporization of graphite; 4.2 Low -- pressure Benzene/Oxygen diffusion flame method; 4.3 Combustion process; 4.4 Laser ablation; 4.5 Chemical vapor deposition (CVD); 4.6 Chemical synthesis of fullerene; 5. Properties.5.1 Physical properties5.2 Size; 5.3 Solubility; 5.4 Chemical properties; 5.5 Optical properties; 5.6 Mechanical properties; 5.7 Vibrational properties; 5.8 Electrical properties; 5.9 Magnetic properties; 5.10 Lubricating properties; 6. Composites of fullerenes; 7. Applications; 7.1 Fullerenes as wires; 7.2 Medicinal applications; 7.3 Fullerenes in organo photovoltaics; 7.4 Fullerenes as hydrogen gas storage; 7.5 Fullerenes as sensors; Conclusion; References; 5; Graphene Oxide Composites and their Potential Applications; 1. Supercapacitors or electrochemical capacitors.1 online resource (344 pages)
Temperature Distribution Prediction in Laser Powder Bed Fusion using Transferable and Scalable Graph Neural Networks
No full textThis study presents novel predictive models using Graph Neural Networks (GNNs) for simulating thermal dynamics in Laser Powder Bed Fusion (L-PBF) processes. By developing and validating Single-Laser GNN (SL-GNN) and Multi-Laser GNN (ML-GNN) surrogates, the research introduces a scalable data-driven approach that learns fundamental physics from small-scale Finite Element Analysis (FEA) simulations and applies them to larger domains. Achieving a Mean Absolute Percentage Error (MAPE) of 3.77% with the baseline SL-GNN model, GNNs effectively learn from high-resolution simulations and generalize well across larger geometries. The proposed models capture the complexity of the heat transfer process in L-PBF while significantly reducing computational costs. For example, a thermomechanical simulation for a 2 mm x 2 mm domain typically requires about 4 hours, whereas the SL-GNN model can predict thermal distributions almost instantly. Calibrating models to larger domains enhances predictive performance, with significant drops in MAPE for 3 mm x 3 mm and 4 mm x 4 mm domains, highlighting the scalability and efficiency of this approach. Additionally, models show a decreasing trend in Root Mean Square Error (RMSE) when tuned to larger domains, suggesting potential for becoming geometry-agnostic. The interaction of multiple lasers complicates heat transfer, necessitating larger model architectures and advanced feature engineering. Using hyperparameters from Gaussian process-based Bayesian optimization, the best ML-GNN model demonstrates a 46.4% improvement in MAPE over the baseline ML-GNN model. In summary, this approach enables more efficient and flexible predictive modeling in L-PBF additive manufacturing
Motor Current Signature Analysis for Bearing Fault Detection in Mechanical Systems
No full textAbstractBearings are one of the critical components in rotating machinery. The need of an easy and effective fault diagnosis technique has led to the increasing use of motor current signature analysis (MCSA). Bearing faults in the mechanical system run by an induction motor causes change in its stator current spectrum. The faults in the bearings cause variations of load irregularities in the magnetic field which in turn change the mutual and self inductance causing side bands across the line frequency. The objective of this paper is to detect bearing faults (outer race fault) in a mechanical system using motor current signature. Fast Fourier Transform (FFT) is initially employed for a first comparison between a healthy and a defective bearing. Six wavelets are considered out of which three are real valued and remaining three are complex valued. Base wavelet has been selected on the basis of wavelet selection criteria - Maximum Relative wavelet energy. Then, 2D wavelet scalogram has been used for the detection and occurrence of outer race faults of various sizes in ball bearings of mechanical systems using motor current signatures of induction motor
Structural and magnetic properties of high energy Ball milled Co2FeAl0.5Si0.5 Heusler alloy
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