Computational and Quantum Chemistry

🔬 PySCF v2.14.0 has been released The new version substantially expands PySCF’s capabilities for many-body electronic structure, multireference calculations, periodic systems, and relativistic methods. Main additions: • Molecular Bethe–Salpeter equation (BSE) calculations, supporting restricted and unrestricted GW references • New G₀W₀, self-consistent GW, and periodic GW developments, with improved CPU and memory efficiency • Spin-restricted and unrestricted k-point RPA, including periodic calculations with smeared occupations • Implementation of the RCCSDT(Q) correction for high-order coupled-cluster calculations • Spin–orbit-coupling Hamiltonian for GCCSD, together with support for complex GCCSD orbitals • Analytic CASCI gradients using UHF, RKS, or UKS orbitals • New MC26 and COF26 on-top functionals • CABS singles correction and new q-vSZP basis-set/ECP variants • Self-consistent dipole corrections for slab and two-dimensional periodic systems • Pipek–Mezey Wannier functions and Wannier interpolation for periodic k-point calculations Other improvements include: • Better Windows compatibility • HOMO–LUMO gap reporting in SCF output • Configurable ωB97X-D4 parameters • Improved numerical stability in periodic RPA • Reduced memory usage in PCM gradients and periodic density fitting • Corrections affecting X2C, meta-GGA derivatives, UKS Hessians, ghost atoms, and Basis Set Exchange loading Upgrade with: pip install --upgrade pyscf 📋 Full release notes: https://github.com/pyscf/pyscf/releases/tag/v2.14.0 📚 Documentation: https://pyscf.org 📦 PyPI package: https://pypi.org/project/pyscf/ #PySCF #QuantumChemistry #ComputationalChemistry

OpenClatura: an open-source structure-to-name tool OpenClatura is a new open-source Python package for generating systematic chemical names from SMILES. Developed by Adrian Mirza, Kevin Maik Jablonka, and Rostislav at LAMA Lab, it aims to provide an open and inspectable alternative to structure-to-name tools such as ChemDraw’s naming functionality. OpenClatura uses a rule-based approach, exposes intermediate naming decisions, and supports optional OPSIN round-trip checks. The project is currently in beta, and feedback is very welcome, especially on: • installation or compatibility issues • difficult or unusual molecules • unexpected names or failed cases • possible applications and integrations Install from PyPI: pip install openclatura Try it from the command line: openclatura name "CC(=O)Nc1ccccc1" GitHub and documentation: https://github.com/lamalab-org/openclatura Issues: https://github.com/lamalab-org/openclatura/issues Even a quick installation check or one difficult test molecule would help.

🚀 CP2K v2026.2 released Main new features: • DFT+U, Löwdin analysis and Harris functional with k-points • k-point symmetry reduction and wavefunction extrapolation • ACE acceleration for HFX/ADMM • Broadened DOS/PDOS with k-point projections • Brownian-chain molecular dynamics for path integrals • Fixed-volume cell optimization • Improved NEB output and CIF/EXTXYZ structure export • CUDA-accelerated Hartree–Fock exchange via libGint • New LibFCI active-space solver • openPMD output support Release notes and downloads: https://github.com/cp2k/cp2k/releases/tag/v2026.2

Springer Nature un-retracts Planck papers, citing “human error” – Retraction Watch https://share.google/LjHEIGydQI3eTYj8e

The third edition of our school "Quantum Chemistry of Excited States (QCES)" in Cluj, Romania (28/09-02/10) is open for registrations. https://Inkd.in/ezEcVNEK This school, run by Valera Veryazov, Giovanni Li Manni, Luca De Vico, Kasia Pernal and Felix Plasser is developed to teach excited-state computations to PhD students covering theoretical and practical aspects featuring extended hands-on sessions.

The third edition of our school "Quantum Chemistry of Excited States (QCES)" in Cluj, Romania (28/09-02/10) is open for registrations. https://Inkd.in/ezEcVNEK This school, run by Valera Veryazov, Giovanni Li Manni, Luca De Vico, Kasia Pernal and myself is developed to teach excited-state computations to PhD students covering theoretical and practical aspects featuring extended hands-on sessions.

📢 Ireland – PhD Position in Quantum Chemistry at Trinity College Dublin 🏛 University: Trinity College Dublin 🌍 Country: Ireland 🎓 Fields: Chemistry, Chemical Engineering, Quantum Chemistry, Computational Science, Materials Science Are you passionate about advancing sustainable chemistry and eager to harness the power of quantum simulations and machine learning for real-world impact? If you aspire to contribute to greener chemical processes and develop next-generation catalysts, a fully funded PhD position at Trinity College Dublin could be your ideal next step. The focus of this PhD project is “Data-enhanced Quantum Chemistry for Predictive Catalyst Design.” Catalysts are the backbone of modern chemical manufacturing, enabling efficient production of countless materials and fuels. However, the majority of industrial catalysts rely on precious metals like platinum and rhodium—elements that are not only scarce and expensive but also pose significant environmental challenges due to their extraction and processing. 🔗 Find out more and Apply Now: ⚠️ Android users: If it doesn't open, use "Open in browser" https://phdfinder.com/2026/06/29/ireland-phd-position-in-quantum-chemistry-at-trinity-college-dublin/ ━━━━━━━━━━

MSSC2026 - Ab initio Modelling in Solid State Chemistry London (UK), September 14-18, 2026   Directors: S. Casassa - A. Erba - N.M. Harrison - G. Mallia https://www.imperial.ac.uk/mssc/mssc2026/ The Department of Chemistry and the Thomas Young Centre at Imperial College London and the Theoretical Chemistry Group of the University of Torino, in collaboration with the Computational Materials Science Group of the Science and Technology Facilities Council (STFC), are organising the MSSC2026 Summer School on "Ab initio Modelling in Solid State Chemistry". The School is designed for Master and Ph.D. students, as well as for post-docs and researchers who have an interest in getting or strengthening a background in Computational Solid State Chemistry, Physics, Materials Science, Surface- and Nano-Science. The week-long School consists of morning lectures and afternoon hands-on tutorial sessions, where the formal framework and functionalities of the CRYSTAL electronic structure package will be explored (https://www.crystal.unito.it/features.html).    While we strongly encourage in-person participation, we also offer the possibility to attend remotely through streaming of morning lectures and afternoon hands-on tutorials.   Participants will have the opportunity to present their research at a poster session. Topics covered in the School include: basics of solid-state physics, density-functional theory, electronic structure of materials; use of local basis sets; spin-orbit coupling and magnetism; elasticity; lattice dynamics, vibrational spectroscopy (IR and Raman) and thermodynamics; transport properties; electron density analysis; parallel computing and response properties.   You can register at: https://www.imperial.ac.uk/mssc/mssc2026/registration/ Friday 24 July - Deadline for payment of early bird fees. See the website for further details: https://www.imperial.ac.uk/mssc/mssc2026/

Generative AI and Structure-Based Workflow for the De Novo Design and Optimization of DprE1 Inhibitor Candidates Decaprenylphosphoryl-β-D-ribose 2′-epimerase 1 (DprE1) is a key target for tuberculosis drug discovery. We developed a hybrid generative AI and structure-based workflow to optimize DprE1 inhibitors from TCA1. After nine optimization cycles, the best candidates showed improved predicted drug-like properties, binding affinity, and complex stability. GTD_9.7 and GTD_9.4 emerged as the most promising molecules, highlighting the potential of generative AI to accelerate anti-tuberculosis drug discovery. https://chemrxiv.org/doi/full/10.26434/chemrxiv.15004861/v2

Why did this journal retract two 1940s papers by Max Planck? - Ars Technica https://share.google/U78PrjBxBZX4Vi4DM

🚀 OMNI-P2x is now out in Nature Communications Very interesting development for anyone working with excited states, photochemistry, UV/Vis spectra, and nonadiabatic dynamics. OMNI-P2x is a universal neural network potential for ground and excited electronic states in small-molecule chemical space. The idea is very attractive: approaching TD-DFT-level excited-state predictions at much lower computational cost, while still allowing fine-tuning for specific systems. 🔬 Why it matters OMNI-P2x can be used for excited-state simulations, UV/Vis spectroscopy, photodynamics, and the rational design of visible-light-absorbing azobenzene systems. 🧪 Particularly relevant for • Ground- and excited-state simulations • UV/Vis spectrum prediction • Photodynamics applications • Nonadiabatic molecular dynamics workflows • Machine-learning potentials for excited states • Downstream fine-tuning for specific molecular systems A nice aspect is that the authors are not selling it as magic. The applicability domain is still limited and there is room for improvement, but OMNI-P2x looks like a meaningful step toward making excited-state calculations more accessible and scalable. 🌐 Try OMNI-P2x online https://aitomistic.xyz 💻 Run locally / integrate into workflows https://github.com/dralgroup/mlatom 📘 Tutorial https://aitomistic.com/mlatom/tutorial_omnip2x.html 📄 Paper Martyka, M.; Tong, X.-Y.; Jankowska, J.; Dral, P. O. et al. OMNI-P2x universal neural network potential for excited-state simulations. Nature Communications 2026, 17, 4949. https://doi.org/10.1038/s41467-026-71380-5 🔬 Follow-up Chem. Sci. work https://doi.org/10.1039/D5SC09557C #QuantumChemistry #ComputationalChemistry #MachineLearning #MLPotentials #OMNIP2x #MLatom #ExcitedStates #TDDFT #Photochemistry #Photodynamics #NonadiabaticDynamics #UVVis #Azobenzene #MolecularSimulation #ScientificComputing