Q-Chem

The videos from the Q-Chem workshops last week at the Virtual Winter School on #CompChem are posted! If you missed us, you can watch the talks and work through the exercises here: winterschool.cc/program/day-...

Don't forget, Q-Chem has two VWSCC workshops happening over the next 24 hours: One at 9am CET, and another at 10pm CET! Join whichever fits your timezone best. Register here: winterschool.cc

2026 Nick Besley and Michael Wormit Award nominations are due this week! If you know someone who develops in Q-Chem or works with computational spectroscopy methods, please consider nominating them.

Wormit Award: q-chem.com/about/wormit/
Besley Award: q-chem.com/about/besley/

Don't forget about the 2026 Virtual Winter School in Computational Chemistry (VWSCC) meeting, happening next week! This is a great (free!) opportunity to learn and network, including talks and hands-on workshops! Learn more and register here: winterschool.cc #compchem

Don't forget about the upcoming Q-Chem webinar from Avik Ojha; he will discuss his recent work implementing X-ray spectroscopy features in Q-Chem (including XCIS-CVS, which is now available now in Q-Chem 6.4)! Register here: zoom.us/webinar/regi...

Don't miss next week's webinar from Q-Chem developer Avik Ojha (OSU), who will be talking about his recent CVS-XCIS implementation in Q-Chem for X-ray spectroscopy modeling. Read the abstract and register here: zoom.us/webinar/regi...

Q-Chem is thrilled to be one of the sponsors for the 2026 Virtual Winter School on Computational Chemistry! This year's schedule includes many exciting lectures and hands-on workshops, including a Q-Chem workshop. Learn more and register: winterschool.cc #compchem

Happy New Year! As we enter 2026, we want to celebrate the accomplishments of the Q-Chem community over the past year. Check out our 2025 Year In Review publications list: q-chem.com/news/2025-qc...

Thanks to all of our users and developers for making Q-Chem possible! ✨💫

YouTube video by QChemSoftware Webinar 84: Modern Quantum Chemistry in Q-Chem 6.4

Did you miss the recent Q-Chem 6.4 launch event? Not to worry! Watch this webinar recording from John Herbert to learn about our latest release, including a variety of exciting new features: youtu.be/PXMXKPXd8Ok

Try Q-Chem 6.4: q-chem.com/try/

Q-Chem 6.4 includes Robust SCF: A simple black-box approach for improved convergence! It automatically detects and corrects common SCF convergence issues, including plateauing, oscillation, and unstable solutions. manual.q-chem.com/6.4/sub_scf_...

Try Q-Chem 6.4: q-chem.com/try/

In Q-Chem 6.4: Stochastic RI-CC2 analytical gradients and derivative coupling! Obtain accurate CC2 gradients faster, with O(N4) scaling with basis set size. Check out the recent preprint from developers:
doi.org/10.48550/arX...

Try Q-Chem 6.4: q-chem.com/try/

Q-Chem 6.4 includes new B97-type functionals for TAO-DFT! Read this paper from developers Shaozhi Li and Jeng-Da Chai, where they develop methods that perform well for both single- and multi-reference systems. doi.org/10.1021/acs....

Try Q-Chem 6.4 today: q-chem.com/try/

New in Q-Chem 6.4: Iterative CC-in-DFT embedding! This new approach, developed by Anthuan Ferino Pérez and Thomas Jagau, provides high accuracy for relevant properties at lower cost. Read their paper to learn more: doi.org/10.1021/acs....

Try Q-Chem 6.4: q-chem.com/try/

New in Q-Chem 6.4: Faster coupled cluster calculations! Our new two-step Cholesky decomposition for CC and EOM-CC energy and gradient (developed by Tingting Zhao and Anna Krylov) provides speedup. Learn more about features in our new release: q-chem.com/explore/qc64/

Q-Chem 6.4 is here! Upgrade for new spectroscopy features (such as CVS-XCIS our new-and-improved ΔSCF driver), iterative CC-in-DFT embedding, faster CC calculations, MR-SF-DFT, stochastic RI-CC2, NEO methods, and more: q-chem.com/explore/qc64/

New in Q-Chem 6.4: XCIS-CVS! In a new paper, researchers use XCIS-CVS to accurately calculate core-level spectra for open-shell molecules, including transition metal complexes. doi.org/10.1021/acs....

CVS for ROCIS, CIS, and QROCIS is available in Q-Chem 6.4, coming next week!

New in Q-Chem 6.4: Improved ΔSCF! The input for ΔSCF is now one simple, easy-to-use section, making it easier to run than ever. The new ΔSCF driver (developed by Juanes Arias-Martinez) includes several other useful functionalities.

Q-Chem 6.4 is coming next week. Stay tuned!

Check out this new paper: Authors use Q-Chem's EA-TDDFT and ALMO-EDA-PCM to uncover evidence pointing to the presence of interanionic hydrogen bonding (IAHB) in concentrated phosphoric acid solutions. pubs.acs.org/doi/10.1021/...

Try Q-Chem for free: q-chem.com/try/

Coupled-Cluster in Density Functional Theory Embedding Applied to Static Polarizabilities in Aqueous Environments We present a study of static polarizabilities of organic molecules in aqueous environments using projection-based coupled-cluster in density functional theory quantum embedding. We propose two methods...

Check out this recent paper in JCTC, in which authors pioneer the use of iterative CC-in-DFT embedding in Q-Chem to study static polarizabilities for organic molecules in aqueous environments. doi.org/10.1021/acs....

Try Q-Chem today: q-chem.com/try/

Check out this recent preprint from Q-Chem developers at KU Leuven, who use EA-EOM-RICC2 in Q-Chem to study the reduction of ubiquinone (CoQ), a key step in cellular respiration. doi.org/10.26434/che...

Interested in becoming a Q-Chem developer? Learn more here: www.q-chem.com/about/team/d...

Don't miss tomorrow's webinar from Manisha on coupled cluster triples! If you can't make it at the scheduled time, still be sure to register—the webinar recording will be made available afterwards. zoom.us/webinar/regi...

Join us on 11/19 at 9PM PST for a webinar from Manisha, one of our 2025 Summer at Q-Chem interns! She will discuss her recent work with coupled cluster, including her recent Q-Chem implementations of CCSDt and several EOM-CCSDT variants. Register here: zoom.us/webinar/regi...

In this recent preprint, researchers use Q-Chem to help design and characterize a merocyanine metastable-state photoacid! They use the proposed monomer to build a series of light-responsive polymers. doi.org/10.26434/che...

Try Q-Chem today: q-chem.com/try/

Locating Ab Initio Transition States via Geodesic Construction on Machine-Learned Potential Energy Surfaces Efficient and reliable identification and optimization of transition state structures is a longstanding challenge in computational chemistry. Popular chain-of-states methods require hundreds if not thousands of ab initio calculations to generate initial guesses for local quasi-Newton optimizers, with persistent risk of collapse to an alternative stationary point on the potential energy surface (PES). Here, we show that high-quality guess structures for transition state optimization can be obtained by constructing the geodesic path between reactant and product structures on the PES generated by machine learning potentials (MLPs). We present an algorithm for optimization of such geodesic paths, as well as the associated codebase. We demonstrate effectiveness of this approach using the recent eSEN-sm-cons MLP. On average, the highest-energy point along these MLP geodesics requires 30% fewer quasi-Newton optimization steps to converge to the transition state compared to guesses from the fully ab initio freezing string method. Our approach therefore completely eliminates the need for ab initio calculations for the generation of transition state guesses and considerably speeds up subsequent structural optimization. Geodesic construction on ML PES thus promises to be a useful approach for efficient computational elucidation of complex chemical reaction networks.

Finding transition states is one of the most challenging computational chemistry problems. Can #machinelearning help? In this recent publication, authors use machine-learned potential energy surfaces to find TS structures more quickly and accurately: pubs.acs.org/doi/10.1021/...

In this preprint, Q-Chem developers introduce two implementations of sRI-CC2 for excited-state analytical gradients and derivative couplings. Their partial sRI-CC2 method, available in Q-Chem 6.4, is significantly faster than traditional RI-CC2 approaches! doi.org/10.48550/arX...

In this recent preprint, Q-Chem developers introduce a new method for modeling the XAS of open-shell systems! Their approach, included in the upcoming Q-Chem 6.4 release, yields semi-quantitative K-edge and pre-edge orbital splittings. doi.org/10.26434/che...

Join us for an upcoming Q-Chem webinar on November 19th from Manisha, one of our Summer At Q-Chem interns! She will be discussing her work with coupled cluster methods in Q-Chem. Read the abstract and register here: zoom.us/webinar/regi...

In this preprint, authors examine the discrepancy between experimental and theoretical results based on Marcus theory for C-13-ae, using a new scheme (E-SHAKE) to sample the seam between two diabatic electronic states. arxiv.org/pdf/2510.11810

Try Q-Chem: q-chem.com/try/

Researchers accurately model the UV absorption spectrum of the hydroxyl anion in water. They use Q-Chem's CCSD and EOM-CCSD to run highly-accurate QM simulations on clusters generated via MD: doi.org/10.1016/j.mo...

Try Q-Chem today: q-chem.com/try/

In this recent paper, authors use penalty-constrained geometry optimization and SF-LC-TDDFT in Q-Chem 6.3 to study the fluorescence quenching mechanism of a styrene derivative at a conical intersection: doi.org/10.1021/acso...

Try Q-Chem 6.3 today: q-chem.com/try/