Analytical #Raman intensities are one of the notable new features of #ORCA 6.1 (MPI Kofo & FACCTs). Check the implementation paper by Frank Neese and Petra Pikulová.
doi.org/10.1063/5.03...
Manual on Raman simulations:
www.faccts.de/docs/orca/6....
#Spectroscopy #CompChem #QuantumChem
If you want to combine ORCA+Python seamlessly, the OPI (ORCA Python Interface) is the way to go.
The paper is out and is free of access for 6 months - it was accepted as the Editor's choice in JCCT.
The interface is open-source and ready to get new contributions. 🐍
FACCTs at the Analytica, Munich. Hall A3, Booth 503-1.
Visit our team at the Analytica in Munich to learn more about our latest software solutions. We’re looking forward to connecting and exchanging with you.
Hall A3,
Booth 503-1
#FACCTs #analytica2026 #CompChem #QuantumChem #Workflows #Automation #AI #AnalyticChem #ORCA #WEASEL #TOUCAN
FACCTs at the Analytica 2026
On March 24, #analytica 2026 kicks off in Munich — and we’re excited to be part of it.
Experience #WEASEL, #ORCA, and more live and discover how our solutions elevate your processes to a new level of efficiency.
We look forward to seeing you there
#FACCTs #QuantumChem #Workflows #AnalyticalChem
It's really good Geoff! 🧡
With our latest #WEASEL release, it is time to introduce another workflow: the fully automated calculation of rotational barriers for arbitrary molecules, enabling the reliable identification and classification of #atropisomers.
www.faccts.de/weasel/
#FACCTs #Workflows #QuantumChem #CompChem #CADD
Redoxpotentials with ORCA and OPI
Check out the new Jupyter notebook on the calculation of redox potentials with #ORCA and #OPI by #FACCTs Computational Scientist Hagen Neugebauer:
www.faccts.de/docs/opi/nig...
OPI Docs: www.faccts.de/docs/opi/docs/
OPI GitHub: github.com/faccts/opi
#ORCAqc #ORCAPI #CompChem #Python #ChemSky
From the FACCTs side, we will keep pushing and giving our best contribution to the project. Take a look at www.faccts.de for tutorials and the download area if you are curious why so many people are using it 😉.
I can tell from the inside, that is entirely due to the great and inspiring leadership of Prof. Frank Neese, and the excitement and engagement of the team - people really like whay they are doing here!
ORCA has now 100k registered users! We are very proud to be part of the project, and all the impact it has across chemistry/physics/molecular sciences. It's really an enormous privilege to be able to help so many people execute their best ideas through our tools/theories/algorithms 🙏.
Use Fukui functions to estimate molecular reactivity and pinpoint reactive sites. With #WEASEL, you can visualize them and get all associated indices easily using just one command!
Learn more about WEASEL www.faccts.de/weasel
#FACCTs #CompChem #QuantumChem #Fukui #Reactivity #WorkflowAutomation
IM-CCS with WEASEL
Efficiency, robustness, adaptability. Three aspects that characterize our #WEASEL workflows!
One of WEASELs workflows is IM-CCS prediction which reliably predicts #IMCCS with a MARD of 1.7% (2.9 Å) for a set of 48 molecules.
Check out WEASEL at www.faccts.de/weasel.
#FACCTs #ChemSky #CompChem
Most people know us for our contributions to ORCA — but have you heard of WEASEL?
WEASEL is our smart workflow driver that delivers efficient workflows for complex quantum chemical processes.
Learn more about WEASEL at www.faccts.de/weasel
youtu.be/stYgkMZwi5s
#WEASEL #FACCTs #CompChem #ChemSky
The paper touches on how those impact on large datasets for later training. I am glad the effort was worth it. Honestly both were a lot of work and didn't come without sweat and tears 😅.
OBS.: DEFGRID3 is definitely recommended for benchmark data, that's why we made it!
3/3
We have first have developed the new ML-optimized grids for numerical integration in ORCA 5, which have smaller error even with less points.
Then derivied and implemented a fully translation-invariant COSX gradient for ORCA 6, which reduces numerical noise.
2/3
Running bad DFT calculations very fast is easy, and it's also useless. That's why we put a lot of effort in the last few years in making ORCA faster, while at the same time *increasing* the accuracy.
1/3
arxiv.org/abs/2510.197...
It's 10-23 day! So we decided to make a new release:
- AutoOptimize Tool 🎉
- New charts and spectra
- Easier geometry constraints, including for ORCA input
- Plenty of bug fixes and tweaks
discuss.avogadro.cc/t/avogadro-1...
😂
FACCTs at the STC 2025
We are visiting STC in Berlin! Come and join us at our poster presentation—we look forward to many exciting discussions with you! Also check out all the new ORCA features and the new ORCA Python interface, OPI!
#FACCTs #ORCAqc #STC2025 #CompChem #TheoChem
FACCTs at the SMASH 2025
Visit Anneke Dittmer, Bernardo de Souza, and Christoph Riplinger at the SMASH in beautiful Porto! Get the latest information about our quantum chemical NMR toolkit. We look forward to seeing you there!
#FACCTs #ORCAqc #SMASH2025 #CompChem #TheoChem #NMR
PS3: The original post has only limited context (which is OK), so my comment here is not about that one in particular, just in general since so much is happening, and you did ask for it 😆.
PS2: The accuracy I refer to is for MLIP. New functionals like the Skala do improve over wB97M-V - but that's still regular DFT, just a better functional!
They have accelerated what people have been doing by hand for years and it's a perfectly reasonable approach to finding the XC func., IMHO.
PS.: Not even the authors made such big claims, they did a really nice job there and reported as it is. I hope we can test all this and put it to use for the benefit of us all.
Yes, I don't even know why we are discussing this in 2025, as if any of these models they could extrapolate far from the training. This is good old magical thinking, certainly not mathematical one.
5. Overarching claims, IMHO, actually do not help the field, because people might loose trust once it fails. And it will fail, as everything does, so there's no need for that.
We don't need to revolutionize the world every other week. Continuous progress is fine too 😀.
4. It does not mean they are no useful, it is actually amazing that this was achieved! These method will probably become part of our toolkit to solve problems, and they can help a lot. Specially for things like geometry optimization and MD, could be really something.
3. As we know from other models, the gains get smaller with the size of the system. So even to get to the "next level" wB97M-V quality, one probably needs orders of magnitude more parameters and training size, which would be quite challenging. CC seems far off in the horizon.
2. Even if it could perfectly extrapolate to the entire chemical space, the current quality is of good non-hybrid DFT like r2SCAN-3c. It does not "solve the problem", as we know non-hybrid DFT does not unfortunately.
I don't know exactly what Prof. Reiher meant with this to be honest. But in general, I keep my take on it:
1. All current AI/ML are interpolation methods. Which means that, by construction, they are bound to the training space, or "points between points" in the dataset, maybe a bit further.
QBIC VII in Berlin sponsored by FACCTs
Great to see many of our collaborators and friends from the ORCA community including Michael Römelt, Dimitrios Pantazis, @podewitzlab.bsky.social, @letigonzalez.bsky.social, @kulikgroup.bsky.social, and many more at the QBIC VII in Berlin, Germany!
#QBICVII #CompChemSky #ChemSky #ORCAqc #ORCA
