Prof. Amir Karton @Lab_initio
iChem Therefore iAm. Founding Director, Institute for Strategic AI (ISA) | Visiting Researcher @MSFTResearch | Professor of Computational & Materials Chemistry theisa.ai NSW, Australia Joined October 2014-
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@Lab_initio @MSFTResearch Finally, a reference dataset large enough to train ML potentials properly. 73k W1-F12 points change what I can model in materials.
“The newly-launched Institute for Strategic AI [UNE] has been using the tech to automate the discovery and testing of potential solvents that can isolate components of the silicon wafers efficiently.”
As Australia’s love for #solar threatens to pile into a serious waste stream, researchers are turning to AI to extract more value from retired #panels.. reneweconomy.com.au/aussie-researc…
The MSR-ACC/TAE25 database of 73,000 W1-F12 CCSD(T)/CBS atomization energies is now published in Scientific Data! A tremendous collaboration with the @MSFTResearch #AI4Science Team! doi.org/10.1038/s41597… doi.org/10.5281/zenodo… #CompChem #DeepLearning #DFT #QuantumChemistry
We're proud to be part of the beta release of @nvidia's ALCHEMI Toolkit. This toolkit is a unified environment for building custom atomistic simulation workflows, built on the same work that powered speedups to Orb-v3, the latest version of our simulation model Orb. Recap from March’s Orb-v3 update: Up to 1.7x faster inference on large systems (up to 100,000 atoms) and up to 33x faster inference on batched small systems with TorchSim support. Our forthcoming OrbMol-v2 model will leverage components from the toolkit including: → PME electrostatics for periodic Coulomb interactions → The MTK integrator for batched constant-pressure molecular dynamics The result: materially lower inference time.
Very proud of my PhD student @HengZ_921 and joint work with @nagyrpeter and @TCPUniLu: delivering unprecedented DFT accuracy for charged environments (e.g., metalloenzymes). Now in Science Advances: science.org/doi/10.1126/sc… @unifrChemistry
The latest release of Skala is out! Accuracy largely improved beyond hybrids at semilocal cost! #compchem
Today we're sharing a major Skala update: new paper and model release. Skala is a deep-learned XC functional for DFT: 2.8 kcal/mol on GMTKN55, wins 32/55 subsets & surpasses SOTA hybrids in accuracy at semi-local cost. Paper: arxiv.org/abs/2506.14665 Code: github.com/microsoft/skala
Skala is now clearly the best DFT functional in the widely accepted community benchmark GMTKN55, and is faster than other high-accuracy functionals. If you're generating DFT data today, go ahead and use it! @MSFTResearch #AI #Science #MachineLearning
Today we're sharing a major Skala update: new paper and model release. Skala is a deep-learned XC functional for DFT: 2.8 kcal/mol on GMTKN55, wins 32/55 subsets & surpasses SOTA hybrids in accuracy at semi-local cost. Paper: arxiv.org/abs/2506.14665 Code: github.com/microsoft/skala
Does AlphaFold’s latent space encode only the native state or something like a distribution over conformations? We begin to answer this question with ConforNets, a mechanism for producing diverse states, or very specific ones, via inference-time adaption of OF3p’s latent space👇
We introduce ConforNets, a mechanism for conformational control in AlphaFold3 models - SoTA at producing diverse conformations on every multistate benchmark (N=104) - Novel capability: transfer state from one protein to another Outperforms BioEmu, ConforMix and AFsample3 🧵1/8
Thanks to Prime Minister @AlboMP for the warm welcome today. We are making our largest investment in Australia to date, committing A$25 billion to expand AI and cloud capacity, strengthen cybersecurity, and help people and organizations across the country build digital skills.
Exciting new update of Skala. This table should speak for itself: Skala is now the leading density functional in main-group chemistry surpassing previous SOTA hybrid functional at a cheaper, semi-local cost. #compchem #ai4science
Today we're sharing a major Skala update: new paper and model release. Skala is a deep-learned XC functional for DFT: 2.8 kcal/mol on GMTKN55, wins 32/55 subsets & surpasses SOTA hybrids in accuracy at semi-local cost. Paper: arxiv.org/abs/2506.14665 Code: github.com/microsoft/skala
I'm thrilled that the new #deeplearning #DFT Skala-1.1 functional is out! arxiv.org/abs/2506.14665 Skala-1.1 breaks the longstanding accuracy-to-cost trade-off of Jacob's Ladder. Amazing collaboration with @paolagorigiorgi and the entire @MSFTResearch AI4Science team! #CompChem
Today we're sharing a major Skala update: new paper and model release. Skala is a deep-learned XC functional for DFT: 2.8 kcal/mol on GMTKN55, wins 32/55 subsets & surpasses SOTA hybrids in accuracy at semi-local cost. Paper: arxiv.org/abs/2506.14665 Code: github.com/microsoft/skala
🎶 If you like it - put a ring on it! 🎵 But... where?? 🤔 Alex's (@awahab_pg) new paper maps the rules of the game for pyrene-based systems! 🥳 From Rings to Properties: Understanding the Effect of Annelation on Pyrene pubs.acs.org/doi/10.1021/ac…
#CompChem + Experiment driving real-world impact! Collaborating with @Joshinano & Nobel Laureate Kostya Novoselov using @NCInews supercomputer, we found calcium ions + graphene oxide can boost atmospheric water harvesting 3×!💧⚙️ tinyurl.com/4eyrsvsd doi.org/10.1073/pnas.2…
PAHAPS estimates PAH isomer energies from XYZ in seconds. Backed by our JCC study of 38k nonplanar PAHs: ΣDihedral (MAD ~3.6 kcal/mol), +HOMA (~2.5), +fitted xTB (~0.8). Open access: onlinelibrary.wiley.com/doi/10.1002/jc… #CompChem #Cheminformatics #PAH @Lab_initio
@Aromaticist Fantastic news! Congratulations @Aromaticist on a well deserved promotion and Happy birthday too! 🎂🎉🎉🎉🎉
The largest snowfall in recorded history really made the @UniNewEngland campus look like Narnia. More photos from the day: labinitio.org/explore/armida… #UNE #Armidale #Snow #Australia
Yesterday's historic snowfall turned the @UniNewEngland campus into a true winter wonderland. Here are some photos from the incredible day: labinitio.org/explore/armida… #UNE #Armidale #Snow #Australia
@ktakeda1 @UniNewEngland @MSFTResearch Thank you @ktakeda1. Working with you and the brilliant team at @MSFTResearch is a highlight of my career. This collaboration makes research so rewarding!
Thrilled to receive the 2025 Research Collaboration Leadership Award from @UniNewEngland A huge thank you to all my incredible #CompChem and experimental collaborators — this award is for you! 🙏 Grateful to #UNE for fostering an environment of high-impact research partnerships
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Angewandte Chemie @angew_chem
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Caroline Lynn Kamerli... @kamerlinlab
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