Predictive chemistry often struggles with scarce data. Surrogate models can help, but should we use their predicted QM descriptors or hidden embeddings? Chen & Stuyver show that hidden spaces usually win—faster, more robust, and data-efficient. pubs.rsc.org/en/content/a...

New paper from our group out in JCTC! We introduce CYCLO70 — a benchmarking set of 70 challenging cycloaddition reactions (Diels–Alder, dipolar, sigmatropic).
👉 doi.org/10.1021/acs.... (1/6)

Harnessing Surrogate Models for Data-efficient Predictive Chemistry: Descriptors vs. Learned Hidden Representations | ChemRxiv - doi.org/10.26434/che...

New preprint -- CYCLO70: A New Challenging Pericyclic Benchmarking Set for Kinetics and Thermochemistry Evaluation t.co/O6309jKaJq (1/5)

New preprint from our group: Screening Diels-Alder reaction space to identify candidate reactions for self-healing polymer applications (1/5)

chemrxiv.org/engage/chemr...

What can be learned from the electrostatic environments within nitrogenase enzymes?

Authors: Thijs Stuyver, Olena Protsenko, Davide Avagliano, Thomas Ward
DOI: 10.26434/chemrxiv-2025-dndx6

Happy to see this nice collaboration with @moranlabchem.bsky.social out in @ChemistryEur -- Abiotic Ribonucleoside Formation in Aqueous Microdroplets: Mechanistic Exploration, Acidity, and Electric Field Effects. @javialra97.bsky.social chemistry-europe.onlinelibrary.wiley.com/doi/full/10....

Now out in JCTC: Improving the Reliability of, and Confidence in, DFT Functional Benchmarking through Active Learning @javialra97.bsky.social pubs.acs.org/doi/full/10....

One more week to apply!

We’re reopening applications! A 5-year position as Data Steward/Research Engineer for the chemistry departments of
@psl-univ.bsky.social is available.

💼 New deadline: February 7th.
📄 More info & application details below.
🔁 Reposts appreciated! 🙌

What better first post than to share our last two preprints! 🚀

In one, we study how electric fields modulate chemical reactivity, and in the second, we explore a data-efficient strategy for the assembly of more representative benchmarking datasets for DFT validation.

@thijsstuyver.bsky.social

Abiotic ribonucleoside formation in aqueous microdroplets: mechanistic exploration, acidity, and electric field effects

Authors: Maciej Piejko, Javier Emilio Alfonso Ramos, Joseph Moran, Thijs Stuyver
DOI: 10.26434/chemrxiv-2024-m39s3

Improving the reliability of, and confidence in, DFT functional benchmarking through active learning

Authors: Javier E. Alfonso-Ramos, Carlo Adamo, Éric Brémond, Thijs Stuyver
DOI: 10.26434/chemrxiv-2024-98nc1