Next-generation experimentation with self-driving laboratories

F Häse, LM Roch, A Aspuru-Guzik - Trends in Chemistry, 2019 - cell.com
The ever-growing demand for advanced functional materials requires disruption of
conventional approaches to experimentation and acceleration of the discovery process …

Self-driving laboratories: A paradigm shift in nanomedicine development

RJ Hickman, P Bannigan, Z Bao, A Aspuru-Guzik… - Matter, 2023 - cell.com
Nanomedicines have transformed promising therapeutic agents into clinically approved
medicines with optimal safety and efficacy profiles. This is exemplified by the mRNA …

[HTML][HTML] Gryffin: An algorithm for Bayesian optimization of categorical variables informed by expert knowledge

F Häse, M Aldeghi, RJ Hickman, LM Roch… - Applied Physics …, 2021 - pubs.aip.org
Designing functional molecules and advanced materials requires complex design choices:
tuning continuous process parameters such as temperatures or flow rates, while …

ChemOS: An orchestration software to democratize autonomous discovery

LM Roch, F Häse, A Aspuru-Guzik - 2020 - books.rsc.org
The key economic and societal challenges of the 21st century, including clean energy,
global health and sustainability, 1 require the scientific discovery process to be streamlined …

Golem: an algorithm for robust experiment and process optimization

M Aldeghi, F Häse, RJ Hickman, I Tamblyn… - Chemical …, 2021 - pubs.rsc.org
Numerous challenges in science and engineering can be framed as optimization tasks,
including the maximization of reaction yields, the optimization of molecular and materials …

Data infrastructure elements in support of accelerated materials innovation: ELA, PyMKS, and MATIN

SR Kalidindi, A Khosravani, B Yucel, A Shanker… - Integrating Materials and …, 2019 - Springer
Materials data management, analytics, and e-collaborations have been identified as three of
the main technological gaps currently hindering the realization of the accelerated …

[PDF][PDF] Gryffin: An algorithm for Bayesian optimization for categorical variables informed by physical intuition with applications to chemistry

F Häse, LM Roch, A Aspuru-Guzik - arXiv preprint arXiv …, 2020 - researchgate.net
Designing functional molecules and advanced materials requires complex interdependent
design choices: tuning continuous process parameters such as temperatures or flow rates …

Molecular De Novo Design Through Deep Generative Models

O Engkvist, J Arús-Pous, EJ Bjerrum, H Chen - 2020 - books.rsc.org
Machine learning (ML) and artificial intelligence (AI) have had a renaissance during the last
few years and have become a hot topic not only in drug discovery but in the whole of society …

ChemOS: An Orchestration Software to Democratize Autonomous Discovery

A ASPURU-GUZIK - Artificial Intelligence in Drug Discovery, 2020 - books.google.com
The key economic and societal challenges of the 21st century, including clean energy,
global health and sustainability, 1 require the scientific discovery process to be streamlined …

[PDF][PDF] Surya R. Kalidindi, Ali Khosravani, Berkay Yucel, Apaar Shanker &

AL Blekh - researchgate.net
Materials data management, analytics, and e-collaborations have been identified as three of
the main technological gaps currently hindering the realization of the accelerated …