Bernardo de Souza

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

YouTube video by FACCTs WEASEL

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

How Accurate Are DFT Forces? Unexpectedly Large Uncertainties in Molecular Datasets Training of general-purpose machine learning interatomic potentials (MLIPs) relies on large datasets with properties usually computed with density functional theory (DFT). A pre-requisite for accurate...

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

GitHub - faccts/opi: ORCA Python Interface ORCA Python Interface. Contribute to faccts/opi development by creating an account on GitHub.

Create input and parse output of ORCA with the new ORCA Python Interface (OPI), an open source project supported by FACCTs. Check it out and become part of the OPI community!

GitHub: github.com/faccts/opi
Docs: www.faccts.de/docs/opi/1.0...

#ORCAqc #Python #FACCTs #CompChem #QuantumChem

A Two-Level Preconditioner for the CASSCF Linear-Response Equations We present an efficient two-level strategy to accelerate the solution of the CASSCF linear-response eigenvalue problem using a customized Davidson algorithm. By identifying a subset of important response-vector components─the so-called P space─we compute and diagonalize full Hessian and metric matrix elements while treating the remaining Q-space components with a diagonal approximation. This approach decouples the orbital and configuration responses, enabling independent preconditioning of each component. Computational cost is further reduced through the resolution-of-the-identity approximation. We demonstrate significant performance gains across a diverse set of molecules, achieving speedups of up to 2.05 compared to the standard diagonal preconditioning. The largest efficiency gains are observed for MCTDA calculations involving many excited states and relatively small response-vector lengths. The two-level strategy is available in ORCA 6.1 and paves the way for extensions to dynamic polarizabilities, which require solving large-scale linear equations, as well as to time-dependent density functional theory and CI singles.

Hot off the press: “A Two-Level Preconditioner for the CASSCF Linear-Response Equations” by our scientific advisor Benjamin Helmich-Paris (@orca-qc-official.bsky.social). Its already part of ORCA 6.1, check it out!

doi.org/10.1021/acs....

#ORCA #ORCAqc #CompChem #QuantumChem #TheoChem #CASSCF

Pericyclic Umpolung in a Catalytic Asymmetric Diels–Alder Reaction of Tropone with Enol Ethers One remarkable feature of catalysis in chemical synthesis is its capacity to override substrate-imposed reactivity and selectivity. The inversion of normal reaction patterns, commonly known as Umpolun...

Check out the recent paper by List, Neese et al. that ones more demonstrates the synergy of experiment and quantum chemistry powered by ORCA (DFT, GOAT, ...) @faccts.de @orca-qc-official.bsky.social

doi.org/10.1021/jacs...

ORCA: www.faccts.de/orca/

#ORCAqc #ORCA #Catalysis #CompChem #QuantumChem