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Volker Deringer @vlderinger.bsky.social · Aug 28

Congratulations Kim!! 🙂

Volker Deringer @vlderinger.bsky.social · Aug 28

#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 🙂

A selfie of Volker and team members in front of the conference venue on Wednesday evening

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Reposted by Volker Deringer

COSMO Lab @labcosmo.bsky.social · Aug 22

🚨 #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 🔍.

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Volker Deringer @vlderinger.bsky.social · Aug 21

🧪🤖 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

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Reposted by Volker Deringer

Connie Lu @cluchem.bsky.social · Aug 19

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

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Volker Deringer @vlderinger.bsky.social · Jun 27

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...

The table-of-contents image for the paper mentioned in the post – showing an atomistic structural model of graphene oxide on the left, and stress–strain plots on the right

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Reposted by Volker Deringer

Sascha Feldmann @feldmannlab.bsky.social · Jun 26

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.

www.nature.com

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Volker Deringer @vlderinger.bsky.social · Jun 23

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

John Gardner @jla-gardner.bsky.social · Jun 23

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! 🤿🧵

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Volker Deringer @vlderinger.bsky.social · Jun 19

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 😀

A photo of Georgi, Arun, Johana, and Cecilia, taken outdoors on a sunny day

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Reposted by Volker Deringer

Graeme Day @graemeday.bsky.social · Jun 18

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 · Jun 18

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

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Reposted by Volker Deringer

Jan Hermann @jan.hermann.name · Jun 18

🚀 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 ⚛️🔥🧪🧬

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Reposted by Volker Deringer

COSMO Lab @labcosmo.bsky.social · Jun 17

🎉 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...

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Volker Deringer @vlderinger.bsky.social · Jun 17

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

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Volker Deringer @vlderinger.bsky.social · Jun 11

It is very fast! (In particular for those cases where we need hundreds of thousands of atoms and more – "realistic" polycrystalline samples are one example)

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Volker Deringer @vlderinger.bsky.social · Jun 11

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

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Reposted by Volker Deringer

Andy Cooper @aicooper.bsky.social · Jun 10

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: [email protected] @ukri.org #EPSRC #AI

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Volker Deringer @vlderinger.bsky.social · Jun 4

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! 😀

A photo of Volker, Litong, Shixuan, Natascia, and Bianca outside a building at KIT where the workshop was held

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Reposted by Volker Deringer

COSMO Lab @labcosmo.bsky.social · May 27

📢 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...

Scheme of the GNN architecture of the FlashMD method.

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Reposted by Volker Deringer

Aron ⇋ e⁻ @aronwalsh.github.io · May 13

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...

www.nature.com

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Volker Deringer @vlderinger.bsky.social · May 5

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...

A photo of Vancouver on a sunny day, showing a waterfront and high-rise buildings in the background

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Volker Deringer @vlderinger.bsky.social · Apr 25

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 · Apr 22

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

John Gardner @jla-gardner.bsky.social · Dec 9

🚨 Introducing graph-pes: a unified framework for building, training and using graph-based machine-learned models of potential energy surfaces! 🚨

#compchem #ML #ChemSky #CompChemSky

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Reposted by Volker Deringer

Sascha Feldmann @feldmannlab.bsky.social · Apr 22

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

Feldmann Lab at EPFL is hiring at PhD and Postdoc Level in Spectroscopy and Nanomaterials

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Volker Deringer @vlderinger.bsky.social · Apr 2

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 · Apr 1

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

arXiv bot (cond-mat) @krxiv-cond-mat.bsky.social · Apr 1

The structure and topology of an amorphous metal-organic framework
https://arxiv.org/pdf/2503.24367
Thomas C. Nicholas, Daniel F. Thomas du Toit, Louise A. M. Rosset, Davide M. Proserpio, Andrew L. Goodwin, Volker L. Deringer.

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Reposted by Volker Deringer

Sascha Feldmann @feldmannlab.bsky.social · Apr 1

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

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Volker Deringer @vlderinger.bsky.social · Mar 11

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...

www.nature.com

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