Toward “On‐Demand” Materials Synthesis and Scientific Discovery through Intelligent Robots

How to explore chemical space using algorithms and automation

(2019) Piotr S. Gromski et al.   Nature Reviews Chemistry

The Molecular Industrial Revolution: Automated Synthesis of Small Molecules

(2018) Melanie Trobe et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

A platform for automated nanomole-scale reaction screening and micromole-scale synthesis in flow

(2018) Damith Perera et al.   SCIENCE

Digitization of multistep organic synthesis in reactionware for on-demand pharmaceuticals

(2018) Philip J. Kitson et al.   SCIENCE

Autonomous robotic searching and assembly of two-dimensional crystals to build van der Waals superlattices

(2018) Satoru Masubuchi et al.   Nature Communications

Accelerating the discovery of materials for clean energy in the era of smart automation

(2018) Daniel P. Tabor et al.   Nature Reviews Materials

Efficient Syntheses of Diverse, Medicinally Relevant Targets Planned by Computer and Executed in the Laboratory

(2018) Tomasz Klucznik et al.   Chem

Nanoscale synthesis and affinity ranking

(2018) Nathan J. Gesmundo et al.   NATURE

Planning chemical syntheses with deep neural networks and symbolic AI

(2018) Marwin H. S. Segler et al.   NATURE

Reconfigurable system for automated optimization of diverse chemical reactions

(2018) Anne-Catherine Bédard et al.   SCIENCE

Across-the-World Automated Optimization and Continuous-Flow Synthesis of Pharmaceutical Agents Operating Through a Cloud-Based Server

(2018) Daniel E. Fitzpatrick et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

AIR-Chem: Authentic Intelligent Robotics for Chemistry

(2018) Jiagen Li et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Organic synthesis in a modular robotic system driven by a chemical programming language

(2018) Sebastian Steiner et al.   SCIENCE

Properties and potential optoelectronic applications of lead halide perovskite nanocrystals

(2017) Maksym V. Kovalenko et al.   SCIENCE

Optimizing Chemical Reactions with Deep Reinforcement Learning

(2017) Zhenpeng Zhou et al.   ACS Central Science

Machine-learned and codified synthesis parameters of oxide materials

(2017) Edward Kim et al.   Scientific Data

Towards dial-a-molecule by integrating continuous flow, analytics and self-optimisation

(2016) Victor Sans et al.   CHEMICAL SOCIETY REVIEWS

1,500 scientists lift the lid on reproducibility

(2016) Monya Baker   NATURE

Mastering the game of Go with deep neural networks and tree search

(2016) David Silver et al.   NATURE

On-demand continuous-flow production of pharmaceuticals in a compact, reconfigurable system

(2016) A. Adamo et al.   SCIENCE

Enabling Technologies for the Future of Chemical Synthesis

(2016) Daniel E. Fitzpatrick et al.   ACS Central Science

Organic Synthesis: March of the Machines

(2015) Steven V. Ley et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Reinforcement learning improves behaviour from evaluative feedback

(2015) Michael L. Littman   NATURE

Advances in natural language processing

(2015) J. Hirschberg et al.   SCIENCE

The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies

(2015) Scott Kirklin et al.   npj Computational Materials

A Systems Approach towards an Intelligent and Self-Controlling Platform for Integrated Continuous Reaction Sequences

(2014) Richard J. Ingham et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)

(2013) James E. Saal et al.   JOM

High-Performance Carbon Nanotube Transparent Conductive Films by Scalable Dip Coating

(2012) Francesca Mirri et al.   ACS Nano

Focusing Nanocrystal Size Distributions via Production Control

(2011) Michael D. Clark et al.   NANO LETTERS

SNOBFIT -- Stable Noisy Optimization by Branch and Fit

(2008) Waltraud Huyer et al.   ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE