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Ben Blaiszik

@benblaiszik.bsky.social

3.4K followers 2.6K following 510 posts

Group Leader - AI and data infrastructure for science at UChicago/Argonne/Globus - UofIllinois alum. materials, chemistry, physics. Opinions are my own.🤖🔬

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Ben Blaiszik @benblaiszik.bsky.social · Nov 22

Quick introduction. 👋

Here are some things I do:

🤖 Use AI/ML to supercharge science - from analysis to prediction, to automation

🔨 Build data infra so researchers can do more science with less overhead

🌟 Contribute to open code, data, and science

🤝 Build communities for modern research.

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Ben Blaiszik @benblaiszik.bsky.social · 1d

This paper won Best Paper Award at EScience 2025, congrats to the entire team team: Marcus Schwarting, @WardLT2, @NCHudson95, Xiaoli Yan, me, Santanu Chaudhuri, Eliu Huerta, @ianfoster
@argonne, @UChicago, @thisisUIC

Ben Blaiszik @benblaiszik.bsky.social · 1d

Applied to MOF discovery, this queue prioritization:
🔶 Doubled discovery of high-performing candidates
🔷 Required <1% extra compute for the RL loop
🔶 Discovered more stable, varied materials

📘 Read the full paper: arxiv.org/pdf/2509.25538

Ben Blaiszik @benblaiszik.bsky.social · 1d

Generative AI is changing how we discover materials, but without direction, it can quickly lose its way. Marcus Schwarting led an effort to show that using active learning as a guide helps to prioritize the best candidates in scientific discovery workflows for MOFs.

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Ben Blaiszik @benblaiszik.bsky.social · 6d

Are you looking for ~120~ examples of how LLMs can be used to advance research in materials science & chemistry with open code? We've made a quick search interface for you to explore projects from the recent hackathon.

See the projects here and come join our community: llmhackathon.github.io

Ben Blaiszik @benblaiszik.bsky.social · 14d

Thanks to support from NIST and James Warren for making the MDF vision of vast troves of open data to fuel discovery possible.

We can't wait to see what you build and discover!

Access Details: github.com/facebookrese...

github.com

Ben Blaiszik @benblaiszik.bsky.social · 14d

Eagle provides researchers access to high-volume data pioneered by @ianfoster42.bsky.social, Rachana Ananthakrishnan, Kyle Chard, Michael Papka, Rick Stevens, and others. @globusorg.bsky.social provides platform capabilities (auth, data transfer, automation, and compute) to over 600k researchers.

Globus

Research data management simplified.

Globus.org

Ben Blaiszik @benblaiszik.bsky.social · 14d

For this first release, the data are quite raw, and as-created by the Meta team. There's an opportunity for the community to build tools that simplify access to these data, allow data query and browsing, create databases of calculated properties and descriptors, and much more.

Ben Blaiszik @benblaiszik.bsky.social · 14d

The Materials Data Facility is proud to make these data available via the Eagle cluster at ALCF through a high-performance Globus endpoint. Given the dataset's scale, we're first releasing data for a 4M random OMol25 split, with the multi-petabyte dataset following based on community engagement.

Ben Blaiszik @benblaiszik.bsky.social · 14d

This dataset includes DFT outputs, electronic densities, wavefunctions, and molecular orbital information for over 4M high-accuracy calculations. We see this as an opportunity to develop higher quality partial charges, partial spins, and advanced electronic features to unlock next generation models.

Ben Blaiszik @benblaiszik.bsky.social · 14d

Data to train next-generation AI models. Data to push the boundaries of what's computationally possible in molecular chemistry and lead the world in AI for science. Data that captures the full complexity of chemical systems, from small organic molecules to massive biomolecular complexes.

Ben Blaiszik @benblaiszik.bsky.social · 14d

We envision a future where researchers can rapidly design molecules and peptides to treat diseases, discover catalysts to revolutionize synthesis and manufacturing, identify the next electrolyte to store and transport energy to protect the grid, and more. But breakthrough discoveries require data.

Ben Blaiszik @benblaiszik.bsky.social · 14d

🔥 Today we announce the Meta OMol25 Electronic Structures Dataset - 500 TB of molecular data in collaboration with the AI at Meta team.

Access Details: github.com/facebookrese...

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Ben Blaiszik @benblaiszik.bsky.social · 22d

Going to be honest. Apple’s Liquid Glass and ios26 styling feels cheap and cluttered. Also why would I want to see so much visually distorted content (under glass)?

Some interesting concepts, but needs a lot of work.

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Ben Blaiszik @benblaiszik.bsky.social · 27d

Thanks Kyle! More soon…

Ben Blaiszik @benblaiszik.bsky.social · 28d

Ah, you're right. Folders are premium. 🥲

Ben Blaiszik @benblaiszik.bsky.social · 28d

Bookmarks on X are premium tier - which is wild.

Ben Blaiszik @benblaiszik.bsky.social · 28d

Still time to join (event is tomorrow):

Ben Blaiszik @benblaiszik.bsky.social · 28d

Due to overwhelming demand, we are also looking for qualified judges to help if you have an hour or two in the next week and some expertise in materials/chemistry, LLMs, or even with business or previous pitch competitions.

Sign up here: forms.gle/MJNsK5Dvbmvc...

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Ben Blaiszik @benblaiszik.bsky.social · 28d

Over 1100 people around the world, virtual and in-person, decided to take a chance together, to imagine, and build - seeking ways to speed discovery and understanding in materials and chemistry with AI.

We'll share our findings soon, but from what I've heard already prepare to be amazed.

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Ben Blaiszik @benblaiszik.bsky.social · 29d

Thanks looks cool. :)

Ben Blaiszik @benblaiszik.bsky.social · 29d

Agreed.

Ben Blaiszik @benblaiszik.bsky.social · 29d

My feed has gotten stale. Who is posting top tier science content?

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Ben Blaiszik @benblaiszik.bsky.social · 29d

And they’re free too. :)

Ben Blaiszik @benblaiszik.bsky.social · 29d

Read the entire paper and learn about more of our findings here by the amazing team at @argonne @argonne_lcf @UChicago @globus @ianfoster @ENERGY @labsglobus

Read the paper: arxiv.org/abs/2508.18489

Ben Blaiszik @benblaiszik.bsky.social · 29d

We also learned that MCP can bridge LLMs and existing scientific infrastructure and we showed that it can work today in chemistry, materials, bioinformatics, and HPC ops

…but challenges remain particularly in: auth, evaluation, and long-running workflows.

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