Tim Duignan
@timothyduignan.bsky.social
Researcher at Orbital Materials. Working on molecular simulation with ML for chemical engineering applications.
When generating training data on specific systems the MLIP/NNP community needs to get organized and agree on one particular level of theory, settings and data storage standards as much as possible so we can pool all the data for training foundation/universal models right?
October 20, 2025 at 12:55 PM
When generating training data on specific systems the MLIP/NNP community needs to get organized and agree on one particular level of theory, settings and data storage standards as much as possible so we can pool all the data for training foundation/universal models right?
When agentic AI started popping up I remember thinking, yeah that is the logical next step but we're not there yet. Its a several years away, well I think its here now and it came much faster then I expected. It's still early days but seems it will have a profound impact.
October 10, 2025 at 11:50 AM
When agentic AI started popping up I remember thinking, yeah that is the logical next step but we're not there yet. Its a several years away, well I think its here now and it came much faster then I expected. It's still early days but seems it will have a profound impact.
Couple of very nice new papers on understanding the SEI formation in lithium ion batteries using neural network/machine learning interatomic potentials (NNPs/MLIPs).
October 9, 2025 at 1:00 PM
Couple of very nice new papers on understanding the SEI formation in lithium ion batteries using neural network/machine learning interatomic potentials (NNPs/MLIPs).
Universal machine learning forcefields beating tailor made classical potentials for zeolites quite convincingly. Great to see all these benchmarking papers! Again demonstrates accurate training data + speed should be key focus now.
arxiv.org/abs/2509.07417
arxiv.org/abs/2509.07417
September 18, 2025 at 11:14 AM
Universal machine learning forcefields beating tailor made classical potentials for zeolites quite convincingly. Great to see all these benchmarking papers! Again demonstrates accurate training data + speed should be key focus now.
arxiv.org/abs/2509.07417
arxiv.org/abs/2509.07417
I think neural network potentials are the eventual pathway to a virtual cell. The accuracy/memory are quite close to where you need them. Timescale is the last real hurdle. But we can port decades of great tools from classical FFs, so it’s becoming more of an engineering problem now.
September 9, 2025 at 11:40 AM
I think neural network potentials are the eventual pathway to a virtual cell. The accuracy/memory are quite close to where you need them. Timescale is the last real hurdle. But we can port decades of great tools from classical FFs, so it’s becoming more of an engineering problem now.
arxiv.org/pdf/2508.15614 This is right and it's a big deal. Been waiting my whole career for this point. So many things to simulate!
September 8, 2025 at 11:19 AM
arxiv.org/pdf/2508.15614 This is right and it's a big deal. Been waiting my whole career for this point. So many things to simulate!
Another very interesting benchmarking paper on NNPs. lnkd.in/gWbcTQw8 It seems the models are pretty much there. Very exciting times as these new large datasets continue to be built. Always need more though!
September 2, 2025 at 11:55 AM
Another very interesting benchmarking paper on NNPs. lnkd.in/gWbcTQw8 It seems the models are pretty much there. Very exciting times as these new large datasets continue to be built. Always need more though!
Another remarkable jump in accuracy with these new OrbMol models for simulating chemistry. For example, they now quantitatively reproduce the structure of water. But they should be just as applicable for studying a vast range of different liquids.
August 28, 2025 at 12:18 PM
Another remarkable jump in accuracy with these new OrbMol models for simulating chemistry. For example, they now quantitatively reproduce the structure of water. But they should be just as applicable for studying a vast range of different liquids.
Another nice benchmarking paper highlighting the rapid exciting progress of universal MLIPS/NNPs: www.arxiv.org/abs/2507.11806
July 23, 2025 at 11:57 PM
Another nice benchmarking paper highlighting the rapid exciting progress of universal MLIPS/NNPs: www.arxiv.org/abs/2507.11806
Love this combination of LLMs and NNPs, a powerful pair of tools. www.sciencedirect.com/science/arti... Also wonderful to see people picking up Orb so quickly and getting good results!
June 23, 2025 at 6:36 AM
Love this combination of LLMs and NNPs, a powerful pair of tools. www.sciencedirect.com/science/arti... Also wonderful to see people picking up Orb so quickly and getting good results!
This is excellent! arxiv.org/abs/2506.14492
June 19, 2025 at 12:10 PM
This is excellent! arxiv.org/abs/2506.14492
Reposted by Tim Duignan
🚀 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 ⚛️🔥🧪🧬
June 18, 2025 at 11:24 AM
🚀 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 ⚛️🔥🧪🧬
Reposted by Tim Duignan
So proud of this work with our amazing team 🤩
🚀 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 ⚛️🔥🧪🧬
June 18, 2025 at 12:59 PM
So proud of this work with our amazing team 🤩
So many nice NNP papers coming out now it is impossible to stay on top of them. Four very cool recent ones:
June 18, 2025 at 12:07 PM
So many nice NNP papers coming out now it is impossible to stay on top of them. Four very cool recent ones:
Reposted by Tim Duignan
Interesting work exploring an enzyme reaction with a machine learning potential. Looking forward to much more like this in the next few years.
So Orb has blown me away again. I simulated the carbonic anhydrase enzyme with it: one of the most important and well studied enzymes in biology. (It converts CO2 to bicarbonate and is involved in many diseases and could also be useful for carbon capture.)
March 20, 2025 at 11:56 AM
Interesting work exploring an enzyme reaction with a machine learning potential. Looking forward to much more like this in the next few years.
So Orb has blown me away again. I simulated the carbonic anhydrase enzyme with it: one of the most important and well studied enzymes in biology. (It converts CO2 to bicarbonate and is involved in many diseases and could also be useful for carbon capture.)
March 19, 2025 at 10:29 AM
So Orb has blown me away again. I simulated the carbonic anhydrase enzyme with it: one of the most important and well studied enzymes in biology. (It converts CO2 to bicarbonate and is involved in many diseases and could also be useful for carbon capture.)
Running out of memory used to be a common headache when running molecular simulations with neural network potentials. Not any more. Here Orb is simulating over half a million atoms on a single GPU (H200). This is a fully solvated COVID spike protein.
Models here: github.com/orbital-mate...
Models here: github.com/orbital-mate...
February 25, 2025 at 12:02 PM
Running out of memory used to be a common headache when running molecular simulations with neural network potentials. Not any more. Here Orb is simulating over half a million atoms on a single GPU (H200). This is a fully solvated COVID spike protein.
Models here: github.com/orbital-mate...
Models here: github.com/orbital-mate...
Uranium is one of the hardest elements to simulate due to the large number of electrons, so I thought I would try it with Orb and remarkably it seems to behaves well even getting the melting point roughly correct. I think looking at this systematically for many metals would be a great project.
February 13, 2025 at 11:33 AM
Uranium is one of the hardest elements to simulate due to the large number of electrons, so I thought I would try it with Orb and remarkably it seems to behaves well even getting the melting point roughly correct. I think looking at this systematically for many metals would be a great project.
Had a lot of fun outlining how I think AI accelerated simulation with tools like Orb are going to be profoundly useful for Chemical Engineering in this article for The Chemical Engineer:
www.thechemicalengineer.com/features/vie...
www.thechemicalengineer.com/features/vie...
February 12, 2025 at 12:05 PM
Had a lot of fun outlining how I think AI accelerated simulation with tools like Orb are going to be profoundly useful for Chemical Engineering in this article for The Chemical Engineer:
www.thechemicalengineer.com/features/vie...
www.thechemicalengineer.com/features/vie...
Here's a fun one you can't do in the lab: diamond melting at thousands of degrees simulated with Orb. Simulate anything you want with it here: colab.research.google.com/github/timdu...
February 10, 2025 at 12:44 PM
Here's a fun one you can't do in the lab: diamond melting at thousands of degrees simulated with Orb. Simulate anything you want with it here: colab.research.google.com/github/timdu...
Very cool.
Interesting #preprint arxiv.org/html/2502.02... showing that even with a last-gen #machinelearning potential the liquid-liquid transition in hydrogen is supercritical, exactly as found by @chengbingqing.bsky.social & Guglielmo Mazzola 5 years ago - see www.nature.com/articles/s41.... 🧑🦳 but 🥇!
Evidence for supercritical behaviour of high-pressure liquid hydrogen - Nature
Simulations using machine-learning-based interatomic potentials in dense hydrogen overcome system size and timescale limitations, providing evidence of a supercritical behaviour of high-pressure liqui...
www.nature.com
February 9, 2025 at 1:37 AM
Very cool.
Really enjoyed this discussion on all the ways AI tools like Orb can be used to accelerate the incredibly important task of accelerating materials science and biology. www.cognitiverevolution.ai/material-pro...
Material Progress: Developing AI's Scientific Intuition, with Orbital Materials' Jonathan & Tim
Jonathan Godwin, founder and CEO of Orbital Materials, alongside researcher Tim Duignan, discuss the transformative potential of AI in material science on the Cognitive Revolution podcast.
Watch Epi...
www.cognitiverevolution.ai
January 26, 2025 at 12:24 PM
Really enjoyed this discussion on all the ways AI tools like Orb can be used to accelerate the incredibly important task of accelerating materials science and biology. www.cognitiverevolution.ai/material-pro...
You can now run these yourself with this google colab:
shorturl.at/cFMA7
The same script should work on the gpu on newer Macs too.
All you need is a .xyz file of your atom types and positions and you can simulate your own systems.
shorturl.at/cFMA7
The same script should work on the gpu on newer Macs too.
All you need is a .xyz file of your atom types and positions and you can simulate your own systems.
January 19, 2025 at 12:11 PM
You can now run these yourself with this google colab:
shorturl.at/cFMA7
The same script should work on the gpu on newer Macs too.
All you need is a .xyz file of your atom types and positions and you can simulate your own systems.
shorturl.at/cFMA7
The same script should work on the gpu on newer Macs too.
All you need is a .xyz file of your atom types and positions and you can simulate your own systems.
Reposted by Tim Duignan
Interested in building the future of open source ligand- and structure-based ML models for ADMET prediction?
The ARPA-H funded OMSF (@omsf.bsky.social) OpenADMET project is hiring multiple positions to build ML models of ADMET properties and drive informative data collection!
openadmet.org/jobs/
The ARPA-H funded OMSF (@omsf.bsky.social) OpenADMET project is hiring multiple positions to build ML models of ADMET properties and drive informative data collection!
openadmet.org/jobs/
OpenADMET Jobs
Seeking talented scientists for the OpenADMET Consortium
openadmet.org
January 8, 2025 at 3:41 PM
Interested in building the future of open source ligand- and structure-based ML models for ADMET prediction?
The ARPA-H funded OMSF (@omsf.bsky.social) OpenADMET project is hiring multiple positions to build ML models of ADMET properties and drive informative data collection!
openadmet.org/jobs/
The ARPA-H funded OMSF (@omsf.bsky.social) OpenADMET project is hiring multiple positions to build ML models of ADMET properties and drive informative data collection!
openadmet.org/jobs/