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Ganna (Anya) Gryn’ova 🇺🇦

@grynova.bsky.social

Associate Professor of Computational Chemistry, University of Birmingham https://www.grynova-ccc.org/ views my own

123 Posts2494 Follower516 Folgt
Cristina Trujillo@trujillo-group.bsky.social · 6mo ago

PhD opening in Trujillo Group @manchester.ac.uk Fully funded EPSRC DTP on automated mechanistic studies in catalysis! Collab Dr Alegre-Requena (Zaragoza). July/Oct 2026 start. Details/apply: www.findaphd.com/phds/project... #phd #catalysis #compchem #ml

EPSRC DTP - Automated mechanistic studies in catalysis with quantum chemistry and machine learning at The University of Manchester on FindAPhD.com

PhD Project - EPSRC DTP - Automated mechanistic studies in catalysis with quantum chemistry and machine learning at The University of Manchester, listed on FindAPhD.com

findaphd.com

The Matter Lab@thematterlab.bsky.social · 7mo ago

Our perspective, Connecting the concepts of quantum state tomography and molecular representations for machine learning", is now published in Digital Discovery🎉 Here, we explore how ideas from quantum state tomography can inform representation learning in molecular ML 🔗 doi.org/10.1039/D5DD... [1/5]

The Matter Lab@thematterlab.bsky.social · 12mo ago

🎉Excited to share our new perspective: “Connecting the concepts of quantum state tomography and molecular representations for machine learning” — now on ChemRxiv! Link: doi.org/10.26434/che... [1/5]

Ganna (Anya) Gryn’ova 🇺🇦@grynova.bsky.social · 7mo ago

Excited to share ReSolved - a #GNN for predicting #redox potentials of organic molecules in diverse #solvents, by @chemwedding.bsky.social pubs.acs.org/doi/10.1021/...

Multi-Solvent Graph Neural Network for Reduction Potential Prediction Across the Chemical Space

Reduction potentials of redox-active molecules and materials are essential descriptors of their performance as catalysts, antioxidants, electrode materials, etc. For a given species, its practical applications often span a range of solvent environments, which profoundly impact its redox properties. In this work, we present a message passing graph neural network architecture with a Set Transformer readout trained on ca. 20,000 reduction potentials of chemically diverse closed- and open-shell organic redox-active molecules (the “ReSolved” data set), computed using a rigorously benchmarked density functional theory procedure. The predictor model affords high accuracy with mean absolute errors of ca. 0.2 eV and is uniquely able to generalize to previously unseen solvents. We couple this architecture with an evolutionary algorithm to inverse-design synthetically accessible candidate molecules with target reduction potentials for several battery-related practical applications.

pubs.acs.org

Ganna (Anya) Gryn’ova 🇺🇦@grynova.bsky.social · 7mo ago

DeCOFpose is an automatic #fragmentation tool for covalent organic #frameworks - whether you want to analyse, fragment, or reconstruct them! Great work with @chemwedding.bsky.social and @michelle-ernst.bsky.social pubs.rsc.org/en/content/a...

Fragment to framework: automatic fragmentation of covalent organic frameworks into building blocks for band gap analysis

Understanding structure–property relationships in ordered functional materials is essential for their rational design and optimisation. Fragment-based approaches relating materials’ properties to thos...

pubs.rsc.org

Johannes Margraf@jtmargraf.bsky.social · 7mo ago

📢 We're hiring a PhD student in ML for Materials Chemistry at Uni Bayreuth! Apply if you're into atomistic simulations and the intersections between physics, chemistry and ML. We offer a great environment in one of the nicest towns in Germany. Apply here: bit.ly/4aPBgE9. #compchem #chemsky

Job advertisement of the University of Bayreuth  - Chair of Physical Chemistry V: Theory and Machine Learning

Fixed-Term Research Associate (m/f/d, E13 TV-L, 67%) in the field of Machine Learning for Materials Chemistry

uni-bayreuth.de