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Generative AI-enabled microstructure design of porous thermal interface materials with desired effective thermal conductivity
The conventional approach to achieve desired effective thermal conductivity (ETC) of porous thermal interface materials (TIM) is...
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Accelerating material design with the generative toolkit for scientific discovery
With the growing availability of data within various scientific domains, generative models hold enormous potential to accelerate scientific...
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Multi-objective Optimization-Oriented Generative Adversarial Design for Multi-principal Element Alloys
The discovery of novel alloys, such as multi-principal element alloys (MPEAs)—inclusive of the so-called high-entropy alloys—remains essential for...
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AI powered, automated discovery of polymer membranes for carbon capture
The generation of molecules with artificial intelligence (AI) or, more specifically, machine learning (ML), is poised to revolutionize materials...
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AI-enabled Lorentz microscopy for quantitative imaging of nanoscale magnetic spin textures
The manipulation and control of nanoscale magnetic spin textures are of rising interest as they are potential foundational units in next-generation...
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Molecular identification with atomic force microscopy and conditional generative adversarial networks
Frequency modulation (FM) atomic force microscopy (AFM) with metal tips functionalized with a CO molecule at the tip apex (referred as...
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Influence of tensile properties on hole expansion ratio investigated using a generative adversarial imputation network with explainable artificial intelligence
Hole expansion ratio is widely used to estimate the stretch flangeability of sheet metals which is a critical property of formability and to evaluate...
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Material Discovery
While the previous chapter focussed on the development of ML modelsModels for property, this chapter discusses how those surrogate modelsModels can...
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Deep learning-based multimodal analysis for transition-metal dichalcogenides
AbstractIn this study, we present a novel approach to enable high-throughput characterization of transition-metal dichalcogenides (TMDs) across...
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Defect identification in simulated Bragg coherent diffraction imaging by automated AI
AbstractX-ray Bragg coherent diffraction imaging is a powerful technique for operando and in situ materials characterization and provides a unique...
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Recent progress of artificial intelligence for liquid-vapor phase change heat transfer
Artificial intelligence (AI) is shifting the paradigm of two-phase heat transfer research. Recent innovations in AI and machine learning uniquely...
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Artificial intelligence and machine learning in the design and additive manufacturing of responsive composites
In recent years, the development of artificial intelligence (AI) and machine learning (ML) techniques has revolutionized composite design....
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Drawbacks of Artificial Intelligence and Their Potential Solutions in the Healthcare Sector
Artificial intelligence (AI) has the potential to make substantial progress toward the goal of making healthcare more personalized, predictive,...
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AlphaMat: a material informatics hub connecting data, features, models and applications
The development of modern civil industry, energy and information technology is inseparable from the rapid explorations of new materials. However,...
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Pores for thought: generative adversarial networks for stochastic reconstruction of 3D multi-phase electrode microstructures with periodic boundaries
The generation of multiphase porous electrode microstructures is a critical step in the optimisation of electrochemical energy storage devices. This...
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Artificial optical microfingerprints for advanced anti-counterfeiting
Artificial optical microfingerprints, known as physically unclonable functions (PUFs) offer a groundbreaking approach for anticounterfeiting....
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Accelerating materials discovery using artificial intelligence, high performance computing and robotics
New tools enable new ways of working, and materials science is no exception. In materials discovery, traditional manual, serial, and human-intensive...
