Lukas Sigmund
@lukasmsigmund.bsky.social
📤 67
📥 152
📝 3
PostDoc @ AstraZeneca | Computational Chemistry and Machine Learning
Now published in
@angewandtechemie.bsky.social
: Our hybrid QM/ML model for the prediction of the outcome of the aromatic thianthrenation reaction – with
@peonor.bsky.social
,
@valencekjell.com
, and many great colleagues from
@astra-zeneca.bsky.social
.
onlinelibrary.wiley.com/doi/10.1002/...
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Predicting Reaction Feasibility and Selectivity of Aromatic C─H Thianthrenation with a QM–ML Hybrid Approach
This paper presents the open-source machine learning model PATTCH, which predicts the reaction feasibility and site-selectivity of aromatic C─H thianthrenation reactions. The model was built using bo....
https://onlinelibrary.wiley.com/doi/10.1002/anie.202510533
15 days ago
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The thianthrenation reaction of aromatic C-H bonds now has its predictive ML model for assessing both reaction feasibility and selectivity. Many thanks to the amazing team,
@peonor.bsky.social
,
@valencekjell.com
, and my colleagues at
@astra-zeneca.bsky.social
.
chemrxiv.org/engage/chemr...
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Predicting Reaction Feasibility and Selectivity of Aromatic C–H Thianthrenation with a QM-ML Hybrid Approach
The direct thianthrenation of aromatic C–H bonds is a valuable late-stage functionalization strategy that can assist, for example, the development of new drugs. We herein present a predictive computat...
https://chemrxiv.org/engage/chemrxiv/article-details/6823546950018ac7c5f0504d
5 months ago
0
4
3
Now out in
@chemicalscience.rsc.org
: our review on regio- and site-selectivity prediction of organic reactions. Great collaboration with my colleagues at AstraZeneca and my academic mentor
@valencekjell.com
.
doi.org/10.1039/D5SC00541H
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Computational tools for the prediction of site- and regioselectivity of organic reactions
The regio- and site-selectivity of organic reactions is one of the most important aspects when it comes to synthesis planning. Due to that, massive research efforts were invested into computational mo...
https://doi.org/10.1039/D5SC00541H
7 months ago
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