Machine intelligence for chemical reaction space
Discovering new reactions, optimizing their performance, and extending the synthetically
accessible chemical space are critical drivers for major technological advances and more …
accessible chemical space are critical drivers for major technological advances and more …
Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
The field of predictive chemistry relates to the development of models able to describe how
molecules interact and react. It encompasses the long-standing task of computer-aided …
molecules interact and react. It encompasses the long-standing task of computer-aided …
AI-driven synthetic route design incorporated with retrosynthesis knowledge
Computer-aided synthesis planning (CASP) aims to assist chemists in performing
retrosynthetic analysis for which they utilize their experiments, intuition, and knowledge …
retrosynthetic analysis for which they utilize their experiments, intuition, and knowledge …
PaRoutes: towards a framework for benchmarking retrosynthesis route predictions
S Genheden, E Bjerrum - Digital Discovery, 2022 - pubs.rsc.org
We introduce a framework for benchmarking multi-step retrosynthesis methods, ie route
predictions, called PaRoutes. The framework consists of two sets of 10 000 synthetic routes …
predictions, called PaRoutes. The framework consists of two sets of 10 000 synthetic routes …
Artificial Intelligence Methods and Models for Retro-Biosynthesis: A Sco** Review
Retrosynthesis aims to efficiently plan the synthesis of desirable chemicals by strategically
breaking down molecules into readily available building block compounds. Having a long …
breaking down molecules into readily available building block compounds. Having a long …
High-throughput virtual screening for organic electronics: a comparative study of alternative strategies
We present a review of the field of high-throughput virtual screening for organic electronics
materials focusing on the sequence of methodological choices that determine each virtual …
materials focusing on the sequence of methodological choices that determine each virtual …
FusionRetro: molecule representation fusion via in-context learning for retrosynthetic planning
Retrosynthetic planning aims to devise a complete multi-step synthetic route from starting
materials to a target molecule. Current strategies use a decoupled approach of single-step …
materials to a target molecule. Current strategies use a decoupled approach of single-step …
De novo creation of a naked eye–detectable fluorescent molecule based on quantum chemical computation and machine learning
Designing fluorescent molecules requires considering multiple interrelated molecular
properties, as opposed to properties that straightforwardly correlated with molecular …
properties, as opposed to properties that straightforwardly correlated with molecular …
Retro-fallback: retrosynthetic planning in an uncertain world
Retrosynthesis is the task of proposing a series of chemical reactions to create a desired
molecule from simpler, buyable molecules. While previous works have proposed algorithms …
molecule from simpler, buyable molecules. While previous works have proposed algorithms …
Machine learning assisted phase and size-controlled synthesis of iron oxide particles
Synthesis of iron oxides with specific phases and particle sizes is a crucial challenge in
various fields, including materials science, energy storage, biomedical applications …
various fields, including materials science, energy storage, biomedical applications …