Thank you very much indeed @rociomer.bsky.social and @smnlssn.bsky.social for the opportunity to visit Chalmers, and to speak in this series! #compchem

Rocío Mercado Oropeza@rociomer.bsky.social · 6mo ago

A recording of @vlderinger.bsky.social's excellent talk now available on the Chalmers AI4Science Seminar YouTube Channel, check it out! 🎬 www.youtube.com/watch?v=MWei...

🎓 Applications are open for the IMAT Centre for Doctoral Training at @oxfordchemistry.bsky.social & @oxfordmaterials.bsky.social! Among many exciting topics, have a look at our projects P10 and P13, both combining MLIPs and #compchem with close experimental collaborations: imatcdt.chem.ox.ac.uk

#PsiK2025 selfie! Super to see the community so active & so much exciting #compchem research going on. And of course delighted to be here with members of our group 🙂

🚨 #machinelearning for #compchem goodies from our 🧑‍🚀 team incoming! After years of work it's time to share. Go check arxiv.org/abs/2508.15704 and/or metatensor.org to learn about #metatensor and #metatomic. What they are, what they do, why you should use them for all of your atomistic ML projects 🔍.

🧪🤖 Our first paper on autoplex is published! We describe an automated #compchem framework for building MLIP training datasets, and show a range of application examples. A pleasure to collaborate on this with @molecularxtal.bsky.social & team. Thank you everyone! doi.org/10.1038/s414...

An automated framework for exploring and learning potential-energy surfaces - Nature Communications

Machine learning is revolutionising materials modelling but requires high-quality training data. Here, the authors introduce autoplex, an open framework automating exploration and fitting of potential...

doi.org

📢pls share We are hiring! New opening for a W2 Professor in "experimental inorganic chemistry" @unibonn.bsky.social Deadline Oct. 10 t.co/EqMLA0fCuC

Mechanical properties of graphene oxide from machine-learning-driven simulations – now online in ChemComm (@chemcomm.rsc.org)! In this #compchem study, we explore the links between atomistic structure and mechanical behaviour in GO. Congratulations Zak & Bowen 🙂 Read more: doi.org/10.1039/D5CC...

Excited to share in @nature.com today: Broadband transient full-Stokes luminescence spectroscopy - detecting the most subtle changes in light polarization over time with unprecedented sensitivity. Grateful for the team that made this possible!😊 www.nature.com/articles/s41... #chirality #light

Broadband transient full-Stokes luminescence spectroscopy - Nature

A high-sensitivity, broadband, transient, full-Stokes spectroscopy setup is demonstrated, which can detect quickly varying small signals from chiral emitters.

nature.com

Read more about our MLIP distillation preprint in John’s thread! 🙂 #compchem #chemsky

John Gardner@jla-gardner.bsky.social · last yr.

Excited to share the pre-print we’ve been working on for the last ~4 months: “Distillation of atomistic foundation models across architectures and chemical domains” Deep dive thread below! 🤿🧵

Congratulations to the group‘s MChem students Georgi, Arun, Johana, and Cecilia on completing their projects & theses! They covered a range of topics across #compchem, ML, and materials chemistry applications – well done and thank you everyone 😀

Now published in @chemicalscience.rsc.org and highlighted as a #ChemSciPicks. Great work by @ffmmgg.bsky.social. Collab with @aicooper.bsky.social A Universal Foundation Model for Transfer Learning in Molecular Crystals #compchemsky #chemsky @unisouthampton.bsky.social @liverpooluni.bsky.social

Chemical Science@chemicalscience.rsc.org · last yr.

This week's #ChemSciPicks comes from @graemeday.bsky.social (University of Southampton), @ffmmgg.bsky.social‬, Chengxi Zhao‬, Xenphon Evangelopoulos, and @aicooper.bsky.social‬ (University of Liverpool). Read the full paper here: doi.org/10.1039/D5SC... #ChemSky

🚀 After two+ years of intense research, we’re thrilled to introduce Skala — a scalable deep learning density functional that hits chemical accuracy on atomization energies and matches hybrid-level accuracy on main group chemistry — all at the cost of semi-local DFT ⚛️🔥🧪🧬

🎉 DFT-accurate, with built-in uncertainty quantification, providing chemical shielding anisotropy - ShiftML3.0 has it all! Building on a successful @nccr-marvel.bsky.social-funded collaboration with LRM🧲⚛️, it just landed on the arXiv arxiv.org/html/2506.13... and on pypi pypi.org/project/shif...

Distilling atomistic foundation models! ⚗️🧪🤖 In this #compchem preprint, we describe a general (“architecture-agnostic”) approach to creating fast, application-specific MLIP models via synthetic data – led jointly by @jla-gardner.bsky.social & @dft-dutoit.bsky.social arxiv.org/abs/2506.10956

Distillation of atomistic foundation models across architectures and chemical domains

Machine-learned interatomic potentials have transformed computational research in the physical sciences. Recent atomistic `foundation' models have changed the field yet again: trained on many differen...

arxiv.org

BaZrS3 is an emerging solar-cell material ☀️ In a preprint led by @biancapasca.bsky.social, we describe an ML potential that can tackle the structural complexity of amorphous and polycrystalline BaZrS3. Very happy to see this online! Read more at arxiv.org/abs/2506.01517

Machine-learning-driven modelling of amorphous and polycrystalline BaZrS$_{3}$

The chalcogenide perovskite material BaZrS$_{3}$ is of growing interest for emerging thin-film photovoltaics. Here we show how machine-learning-driven modelling can be used to describe the material's ...

arxiv.org

Alchemy Frontier Fund 2025 now open (aichemy.ac.uk/aichemy-fron...). Apply for 2-year projects of up to £1.25m to advance the frontiers of AI for chemistry. Deadline = Sept 12th 2025. Webinar to launch the fund on June 18th. For information, email: funding@aichemy.ac.uk @ukri.org #EPSRC #AI

It was great to take part in the @cecamevents.bsky.social Flagship Workshop on “Virtual Materials Design” at @kit.edu this week – and to see Litong, Shixuan, Natascia, & @biancapasca.bsky.social present their #compchem research! 😀

📢 Running molecular dynamics with time steps up to 64fs for any atomistic system, from Al(110) to Ala2? Thanks to 🧑‍🚀 Filippo Bigi and Sanggyu Chong, with some help from Agustinus Kristiadis, this is not as crazy as it sounds. Let us briefly introduce FlashMD⚡ arxiv.org/html/2505.19...

The first release of our text-to-crystal model, Chemeleon, is out in @natcomms.nature.com 🌈 Paper: www.nature.com/articles/s41... Code: github.com/hspark1212/c... You can sample an inorganic structure in minutes on a laptop thanks to @hspark1212.bsky.social - #CompChem that gives me goosebumps!

Exploration of crystal chemical space using text-guided generative artificial intelligence - Nature Communications

The vastness of chemical space makes discovering new materials challenging. Here, authors propose a generative AI model enabling crystal structures generation from textual descriptions, accelerating m...

nature.com

In Vancouver for a major conference on ceramic & glass technology! Looking forward to presenting some of our recent #compchem work, and to discussing what ML interatomic potentials can do in this exciting area 🙂 ceramics.org/event/16th-p...

graph-pes is John‘s open-source, all-round software package for fitting & fine-tuning graph-based ML interatomic potentials – do try it out, follow him for updates, and share! #chemsky #compchem 🧪

John Gardner@jla-gardner.bsky.social · last yr.

I've been working hard behind the scenes, and am excited to announce that graph-pes version 0.1.0 is now out!

𝐖𝐄 𝐀𝐑𝐄 #𝐇𝐈𝐑𝐈𝐍𝐆 on the 𝐏𝐇𝐃 & 𝐏𝐎𝐒𝐓𝐃𝐎𝐂 level! If you are interested in #spectroscopy & #materials science for spin-/optoelectronics, please consider joining our team. Details on the positions and how to apply: www.feldmannlab.com/open-positions Sharing with your network is greatly appreciated!🙏:) #EPFL

Great to see this preprint online – a data-driven study of an amorphous metal–organic framework, led by @tcnicholas.bsky.social – thanks to Tom and everyone 🙂 Comments very welcome! arxiv.org/abs/2503.24367

Thomas Nicholas@tcnicholas.bsky.social · last yr.

Very pleased to share our latest #compchem preprint, bringing together amorphous MOFs, ML potentials, and topology analysis.

Proud to see @Kinga' Master’s project published: 𝐀𝐧 𝐞𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭𝐚𝐥 𝐝𝐚𝐭𝐚 𝐥𝐢𝐛𝐫𝐚𝐫𝐲 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐟𝐮𝐥𝐥 𝐂𝐬𝐏𝐛(𝐂𝐥𝐱𝐁𝐫𝟏−𝐱)𝟑 𝐜𝐨𝐦𝐩𝐨𝐬𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐬𝐞𝐫𝐢𝐞𝐬, open-access!⁣⁣ Great #collaboration with co-supervisor & friend @vlderinger.bsky.social, and thanks to @chemcomm.rsc.org for the invitation! pubs.rsc.org/en/content/a...

An experimental data library for the full CsPb(ClxBr1−x)3 compositional series

A complete series of CsPb(ClxBr1−x)3 mixed-halide perovskites with x = 0–1 in small steps is reported, and their structural and optical properties characterised. A comparison of synthetic approaches s...

pubs.rsc.org

Amorphous silicon has a seemingly random structure – and yet there is more to it, as Louise demonstrates using #compchem & ML approaches. A great collaboration with @dadrabold.bsky.social! Read more in @naturecomms.bsky.social, openly available here: www.nature.com/articles/s41...

Signatures of paracrystallinity in amorphous silicon from machine-learning-driven molecular dynamics - Nature Communications

Conflicting theories exist on the structure of amorphous silicon. Here the authors use machine-learning-driven molecular dynamics to show that amorphous Si can accommodate a degree of local paracrysta...

nature.com

Exciting news for #chemsky - you can now follow all of your favourite @rsc.org journals on Bluesky! 🥳🧪⚗ go.bsky.app/QAaTTZ3

Happy to finally share our review on the broad (and quickly progressing!) field of chiral solution processable semiconductors! #ChemSky ⚗️🧪 www.nature.com/articles/s41...

Chiral light–matter interactions in solution-processable semiconductors - Nature Reviews Chemistry

Endowing chirality onto solution-processable semiconductors unlocks new bounds for their spin and optoelectronic properties. This Review discusses the synthesis, properties, characterization methods, ...

nature.com

📢 Highlighted on #PhysRevMaterials (not yet on 🦋), a little, insightful gem by 🧑‍🚀 Wei Bin, Raymond, Fede & Kevin, relevant for all of you #machinelearning electronic structure properties. Band alignment matters, but it shouldn't, so here's how to deal with it with a self-aligning loss! A short 🧵...

🤖 Interested in automated DFT or ab initio calculations for crystals or molecules? atomate2 could be your package! doi.org/10.26434/che... #compchem

Atomate2: Modular workflows for materials science

High-throughput density functional theory (DFT) calculations have become a vital element of computational materials science, enabling materials screening, property database generation, and training of...

doi.org

In Cambridge today for a workshop on ML interatomic potentials! Photo with @jla-gardner.bsky.social, Natascia, @biancapasca.bsky.social, & Litong 🙂 #compchem