Bayesian optimization for chemical products and functional materials
K Wang, AW Dowling - Current Opinion in Chemical Engineering, 2022 - Elsevier
The design of chemical-based products and functional materials is vital to modern
technologies, yet remains expensive and slow. Artificial intelligence and machine learning …
technologies, yet remains expensive and slow. Artificial intelligence and machine learning …
A perspective on Bayesian methods applied to materials discovery and design
For more than two decades, there has been increasing interest in developing frameworks for
the accelerated discovery and design of novel materials that could enable promising and …
the accelerated discovery and design of novel materials that could enable promising and …
A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys
D Khatamsaz, R Neuberger, AM Roy… - npj Computational …, 2023 - nature.com
The design of materials and identification of optimal processing parameters constitute a
complex and challenging task, necessitating efficient utilization of available data. Bayesian …
complex and challenging task, necessitating efficient utilization of available data. Bayesian …
Adaptive active subspace-based efficient multifidelity materials design
D Khatamsaz, A Molkeri, R Couperthwaite, J James… - Materials & Design, 2021 - Elsevier
Materials design calls for an optimal exploration and exploitation of the process-structure-
property (PSP) relationships to produce materials with targeted properties. Recently, we …
property (PSP) relationships to produce materials with targeted properties. Recently, we …
On the importance of microstructure information in materials design: PSP vs PP
A Molkeri, D Khatamsaz, R Couperthwaite, J James… - Acta Materialia, 2022 - Elsevier
The focus of goal-oriented materials design is to find the necessary chemistry/processing
conditions to achieve the desired properties. In this setting, a material's microstructure is …
conditions to achieve the desired properties. In this setting, a material's microstructure is …
Autonomous materials discovery and manufacturing (AMDM): A review and perspectives
STS Bukkapatnam - IISE Transactions, 2023 - Taylor & Francis
This article presents an overview of the emerging themes in Autonomous Materials
Discovery and Manufacturing (AMDM). This interdisciplinary field is garnering a growing …
Discovery and Manufacturing (AMDM). This interdisciplinary field is garnering a growing …
Estimation of microstructural properties of wormlike micelles via a multi-scale multi-recommendation batch bayesian optimization
Microstructural properties of wormlike micelles (WLMs), which are employed in
characterizing the system to predict rheological properties, have long been obtained via …
characterizing the system to predict rheological properties, have long been obtained via …
Accelerated design of architected materials with multifidelity Bayesian optimization
In this work, we present a multifidelity Bayesian optimization framework for designing
architected materials with optimal energy absorption during compression. Data from both …
architected materials with optimal energy absorption during compression. Data from both …
Machine-Learning-Based phase diagram construction for high-throughput batch experiments
To know phase diagrams is a time saving approach for developing novel materials. To
efficiently construct phase diagrams, a machine learning technique was developed using …
efficiently construct phase diagrams, a machine learning technique was developed using …
Current Status and Future Scope of Phase Diagram Studies
M Enoki, S Minamoto, I Ohnuma, T Abe, H Ohtani - ISIJ International, 2023 - jstage.jst.go.jp
Research on alloy phase diagrams started in the middle of the 19th century and progressed
into the laborious and time-consuming process of constructing phase diagrams through …
into the laborious and time-consuming process of constructing phase diagrams through …