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Machine Learning in Nanoscale Materials Design

Machine Learning in Nanoscale Materials Design

0 - Default Title
Description
Introduction to Nanoengineered Materials.- Molecular Dynamics Simulation: An Overview.- Machine Learning.- Prospects of Machine Learning driven Atomistic Simulations: A Review.- Fracture Response of Graphene: A Data Driven Characterization.- Nanoscale Ballistic Response of Bi-Layer Graphene: ML Driven Approach.- Inter-Atomic Potential Parametrization for Graphene.- High Entropy Alloy: A Data Driven Quasi-Static Characterization.- Etc...
Product details
Number of Pages:
132
Release Date:
2025-10-31
Publication Date:
2025-10-31
Publisher:
Springer
Languages:
Original: English
ISBN10:
9819526590
ISBN13:
9789819526598
GPSR Manufacturer Reference:
Weight:
393 g
Height:
160 cm
Width:
241 cm
Thickness:
13 cm
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