Machine learning in aerodynamic shape optimization
Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …
optimization (ASO), thanks to the availability of aerodynamic data and continued …
Emerging materials intelligence ecosystems propelled by machine learning
The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its
successes and promises, several AI ecosystems are blossoming, many of them within the …
successes and promises, several AI ecosystems are blossoming, many of them within the …
Autonomous experimentation systems for materials development: A community perspective
Solutions to many of the world's problems depend upon materials research and
development. However, advanced materials can take decades to discover and decades …
development. However, advanced materials can take decades to discover and decades …
On-the-fly closed-loop materials discovery via Bayesian active learning
Active learning—the field of machine learning (ML) dedicated to optimal experiment design—
has played a part in science as far back as the 18th century when Laplace used it to guide …
has played a part in science as far back as the 18th century when Laplace used it to guide …
Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation
The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …
traditional research paradigms in the era of artificial intelligence and automation. An …
Polymer informatics: Current status and critical next steps
Artificial intelligence (AI) based approaches are beginning to impact several domains of
human life, science and technology. Polymer informatics is one such domain where AI and …
human life, science and technology. Polymer informatics is one such domain where AI and …
A machine learning Automated Recommendation Tool for synthetic biology
T Radivojević, Z Costello, K Workman… - Nature …, 2020 - nature.com
Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules
such as renewable biofuels or anticancer drugs. However, traditional synthetic biology …
such as renewable biofuels or anticancer drugs. However, traditional synthetic biology …
Nucleation and growth in solution synthesis of nanostructures–from fundamentals to advanced applications
Nucleation and growth are two important and entwined processes in materials synthesis and
engineering. While understanding of the fundamental mechanisms of the processes remain …
engineering. While understanding of the fundamental mechanisms of the processes remain …
The case for data science in experimental chemistry: examples and recommendations
The physical sciences community is increasingly taking advantage of the possibilities
offered by modern data science to solve problems in experimental chemistry and potentially …
offered by modern data science to solve problems in experimental chemistry and potentially …
Gaussian processes for autonomous data acquisition at large-scale synchrotron and neutron facilities
The execution and analysis of complex experiments are challenged by the vast
dimensionality of the underlying parameter spaces. Although an increase in data-acquisition …
dimensionality of the underlying parameter spaces. Although an increase in data-acquisition …