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Meeting 2018 TMS Annual Meeting & Exhibition
Symposium Computational Materials Discovery and Optimization
Presentation Title Design Concepts of Optimized MRI Magnet by COMSOL Multiphysics Simulation
Author(s) Akash Oraon, Sudipto Ghosh, Shampa Aich, Gautam Sinha
On-Site Speaker (Planned) Akash Oraon
Abstract Scope The emphasis of this work is on the optimal design of Magnetic Resonance Imaging (MRI) magnets modified with asymmetric electromagnetic coils and iron shell. The optimum geometrical arrangement of asymmetrical electromagnets in MRI is obtained by COMSOL Multiphysics using a gradient-based optimization solver. The work aims at achieving the required field homogeneity with a shorter magnet having a minimum amount of ampere turns which reduce the current density. The optimized design converged solution gives the total inductance of the set of coils, total conductor length, force and maximum field on each coil. The optimization solver also calculates the allowable geometrical tolerance to achieve the field uniformity. The optimization technique is flexible and can be used for various geometries. The symmetric coils provide field uniformity 1.5 T within a sphere of 50 cm diameter at the central zone of the geometry.
Proceedings Inclusion? Planned: Supplemental Proceedings volume

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A Combined Experimental-computational Approach to Determining Nanoscale Structures
A Materials-informatics Approach for Finding New Hard-magnetic Phases
Computational Design of Fatigue-resistant NiTi-based Shape Memory Alloys
Computational Screening of Novel Two-dimensional Topological Insulators and Layer-dependent properties
Data-driven Discovery of Photocathodes for CO2 Reduction
Design Concepts of Optimized MRI Magnet by COMSOL Multiphysics Simulation
Determination of Thermal Transport in Solids and Liquids by Non-equilibrium Molecular Dynamics Simulations
Dual Band Metamaterial Perfect Absorber Based on Mie Resonances
Economic Analysis of National Needs for Technology Infrastructure to Support the Materials Genome Initiative
Fabricating Optimized Crystallographic Textures through Heterogeneous Templated Grain Growth
First-principles Calculations on the Multiferroic Properties of Two-dimensional Oxides
First Principle Prediction of Magnetic Topological Phase in Thin Films of Bi2XY4 (X = Mn, Cr; Y = Se, Te)
High-throughput Investigation of the Electronic Properties of 2D and Bulk Materials in the MaterialsWeb Database
Holistic Computational Structure Screening of More than 12 000 Candidates for Solid Lithium-ion Conductor Materials
Improving the Ductility of Boron Carbide from Computational Design
Learning Grain Boundary Properties from Macroscopic and Microscopic Structural Descriptors
Light-metal Complex Hydrides: Computational Structure Prediction and Interaction with Functionalized Nanoporous Hosts
Machine Learning for Materials
Machine Learning for Prediction of Electronic Structures of Multi-component Alloys
Minimal Addition of Cerium for Stability of Critical Phases in Hard Magnetic AlNiCo Alloys: Combined Machine Learning and CALPHAD
Predicting Ferroelectric Properties from Microstructures with Deep Learning
Quantum-accurate Force Fields from Machine Learning of Large Materials Data
Reentrant Melting of Sodium, Magnesium and Aluminum and Possible Universal Trend
Search for Rare-Earth Free Permanent Magnets in Fe and Co Based Compounds by Adaptive Genetic Algorithm
Software Tools for High-throughput Materials Data Generation and Data Mining
Structure-property Linkages for Porous Membranes Using the Materials Knowledge Systems Framework
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The Use of Cluster Expansions to Predict the Structure and Properties of Catalysts

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