Talmazan Radu Alexandru

[ChipotLab @ChipotLab]

Rare molecular events can often follow several competing pathways. Our new work introduces an iterative framework that can disentangle these pathways and identifies the dominant transition routes.

https://t.co/5diNjlo7lN

[JCIM & JCTC Journals @JCIM_JCTC]

From Static Pathways to Dynamic Mechanisms: A Committor-Based Data-Driven Approach to Chemical Reactions
https://t.co/VjEfw9JdEx
@RaduTalmazan @ChipotLab
#JCIM Vol66 Issue2 #MachineLearning #DeepLearning

[Nature Computational Science @NatComputSci]

📢Out now! Work from @ChipotLab and colleagues presents a method that learns from atomic motion without the need for handcrafted descriptors, allowing for accurate kinetics and atom-level insights. https://t.co/NxvQ9MSkdh

🔓https://t.co/gry4dgdjzz

[ChipotLab @ChipotLab]

"From Static Pathways to Dynamic Mechanisms: A Committor-Based Data-Driven Approach to Chemical Reactions"
Check out our work using a committor‑based workflow coupled with a high‑level MLIP to reveal dynamic effects in chemical reactions.
https://t.co/9tJA20d9iy
@ACSPublications

[Talmazan Radu Alexandru @RaduTalmazan]

Our new QM/MM MD workflow + ML analysis which reveals reaction coordinates in supramolecular catalysts as sequences of motions has been published in Digital Discovery. Read the full paper here: https://t.co/h7lJ98dmjA

@PodewitzLab

[ChipotLab @ChipotLab]

Did you ever want to try out enhanced sampling with ABF? Have a look at our newest tutorial to get started!
https://t.co/Pr3yanvJsU

@RaduTalmazan, Haohao Fu, Mengchen Zhou, Jérôme Hénin, James C. Gumbart and Christophe Chipot

[Nature Computational Science @NatComputSci]

🚨Our July issue is now live and includes research on adverse drug reactions, multi-fidelity Bayesian optimization, rare event sampling, and much more!
https://t.co/myy3LVRjGO