High‐throughput experimentation and computational freeway lanes for accelerated battery electrolyte and interface development research
The timely arrival of novel materials plays a key role in bringing advances to society, as the
pace at which major technological breakthroughs take place is usually dictated by the …
pace at which major technological breakthroughs take place is usually dictated by the …
Uncertainty quantification and propagation in computational materials science and simulation-assisted materials design
P Honarmandi, R Arróyave - Integrating Materials and Manufacturing …, 2020 - Springer
Significant advances in theory, simulation tools, advanced computing infrastructure, and
experimental frameworks have enabled the field of materials science to become …
experimental frameworks have enabled the field of materials science to become …
Towards stacking fault energy engineering in FCC high entropy alloys
Abstract Stacking Fault Energy (SFE) is an intrinsic alloy property that governs much of the
plastic deformation mechanisms observed in fcc alloys. While SFE has been recognized for …
plastic deformation mechanisms observed in fcc alloys. While SFE has been recognized for …
Artificial intelligence for science in quantum, atomistic, and continuum systems
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …
Bayesian optimization objective-based experimental design
M Imani, SF Ghoreishi - 2020 American control conference …, 2020 - ieeexplore.ieee.org
Design has become a salient part of most of the scientific and engineering tasks, embracing
a wide range of domains including real experimental settings (eg, material discovery or drug …
a wide range of domains including real experimental settings (eg, material discovery or drug …
Determining multi‐component phase diagrams with desired characteristics using active learning
Herein, we demonstrate how to predict and experimentally validate phase diagrams for multi‐
component systems from a high‐dimensional virtual space of all possible phase diagrams …
component systems from a high‐dimensional virtual space of all possible phase diagrams …
Accelerated materials design using batch Bayesian optimization: A case study for solving the inverse problem from materials microstructure to process specification
Microstructure-based process design is one of the main ingredients for materials design,
under the integrated computational materials engineering paradigm, which relies on …
under the integrated computational materials engineering paradigm, which relies on …
A deep neural network regressor for phase constitution estimation in the high entropy alloy system Al-Co-Cr-Fe-Mn-Nb-Ni
Abstract High Entropy Alloys (HEAs) are composed of more than one principal element and
constitute a major paradigm in metals research. The HEA space is vast and an exhaustive …
constitute a major paradigm in metals research. The HEA space is vast and an exhaustive …
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 …
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 …