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Storing energy with molecular photoisomers
Some molecular photoisomers can be isomerized to a metastable high-energy state by
exposure to light. These molecules can then be thermally or catalytically converted back to …
exposure to light. These molecules can then be thermally or catalytically converted back to …
Automation and computer-assisted planning for chemical synthesis
The molecules of today—the medicines that cure diseases, the agrochemicals that protect
our crops, the materials that make life convenient—are becoming increasingly sophisticated …
our crops, the materials that make life convenient—are becoming increasingly sophisticated …
The role of machine learning in the understanding and design of materials
Develo** algorithmic approaches for the rational design and discovery of materials can
enable us to systematically find novel materials, which can have huge technological and …
enable us to systematically find novel materials, which can have huge technological and …
Quantum machine learning for chemistry and physics
Machine learning (ML) has emerged as a formidable force for identifying hidden but
pertinent patterns within a given data set with the objective of subsequent generation of …
pertinent patterns within a given data set with the objective of subsequent generation of …
Machine learning accelerates the investigation of targeted MOFs: performance prediction, rational design and intelligent synthesis
Metal-organic frameworks (MOFs) are a new class of nanoporous materials that are widely
used in various emerging fields due to their large specific surface area, high porosity and …
used in various emerging fields due to their large specific surface area, high porosity and …
Merging enzymatic and synthetic chemistry with computational synthesis planning
Synthesis planning programs trained on chemical reaction data can design efficient routes
to new molecules of interest, but are limited in their ability to leverage rare chemical …
to new molecules of interest, but are limited in their ability to leverage rare chemical …
Combining generative artificial intelligence and on-chip synthesis for de novo drug design
Automating the molecular design-make-test-analyze cycle accelerates hit and lead finding
for drug discovery. Using deep learning for molecular design and a microfluidics platform for …
for drug discovery. Using deep learning for molecular design and a microfluidics platform for …
AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application
We present an updated overview of the AiZynthFinder package for retrosynthesis planning.
Since the first version was released in 2020, we have added a substantial number of new …
Since the first version was released in 2020, we have added a substantial number of new …
Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias
Organic synthesis remains a major challenge in drug discovery. Although a plethora of
machine learning models have been proposed as solutions in the literature, they suffer from …
machine learning models have been proposed as solutions in the literature, they suffer from …
PaRoutes: towards a framework for benchmarking retrosynthesis route predictions
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 …