#Postdoc (2Y) in Marseille:
Exciton transport in bioinspired DNA-templated light-harvesting networks. NEGF, exciton-vibration, decoherence; close link to experiments.

Deadline: 23/1
Start: 27/4
More info: fabienne.michelini @ univ-amu.fr

#QuantumTransport #CompChem

Berkeley Lab: Hybrid Simulation Reveals How Electrons Drive Chemical Reactions in Liquids

A team of researchers, including Berkeley Lab Alvarez Fellow Pinchen Xie, has develo - https://www.hpcwire.com/off-the-wire/berkeley-lab-hybrid-simulation-reveals-how-electrons-drive-chemical-reactions-in-liquids/

🚀 *Q-Shape v1.5.0 released*

*Q-Shape* is a browser-based tool for *quantitative coordination geometry analysis* using *Continuous Shape Measures (CShM)*.
No installation. No uploads. Everything runs *locally* in your browser.

*What’s new in v1.5.0*
• *Batch analysis* for multi-structure XYZ/CIF files
• Batch summary table + structure selector
• Batch *PDF* and *CSV* exports
• *Automatic piano-stool (half-sandwich) recognition*
→ realistic CShM values for Cp and arene complexes

🔗 *Web app:*
https://henriquecsj.github.io/q-shape

📦 *Repository:*
https://github.com/HenriqueCSJ/q-shape

📄 *DOI (v1.5.0):*
https://doi.org/10.5281/zenodo.18209621

Feedback and issues are welcome.

🔬 Fun Fact of the Day

Wien’s Displacement Law

λₘₐₓ = b / T

where
b = 2.897 × 10⁻³ m·K

This law explains why heated objects change color as temperature increases — from red-hot to white-hot — as the peak of thermal emission shifts to shorter wavelengths.

Although deceptively simple, this relationship provided crucial empirical evidence leading Max Planck to propose his quantum hypothesis. That step directly triggered the birth of quantum mechanics, which underpins modern computational chemistry methods such as DFT and post–Hartree–Fock theories.

A classic result with far-reaching consequences.

Do you perform biomolecular MD simulations and wish you could achieve DFT-level accuracy for an entire protein or enzyme in explicit solvent, at timescales relevant to biomolecular processes?

I’m very happy to share our new neural network potential, AMPv3-BMS25, designed for efficient ML/MM simulations. The model is trained on the new BMS25 dataset, which features over 1.5 million DFT/MM calculations focused on proteins, small organic molecules, and transition states.
The model runs very efficiently on a single GPU and scales smoothly to systems with tens of thousands of ML atoms and hundreds of thousands of water molecules.

This work pushes the boundaries of computational chemistry and serves as a powerful complement to generative models. We demonstrate its scalability and accuracy across a wide range of benchmarks (>23 μs), including solvation free energies, protein structural features, and free-energy profiles of enzymatically catalyzed reactions. Interestingly, the model can also handle gas-phase structures with high accuracy, despite not being explicitly trained on them.

We have made the code, weights, and training dataset freely available to the community. 🚀

Preprint:
https://chemrxiv.org/engage/chemrxiv/article-details/695c160d098cdc781ff4d62b

Dataset preprint:
https://chemrxiv.org/engage/chemrxiv/article-details/6936ba61a10c9f5ca1e12680

Github:
https://github.com/rinikerlab/amp_bms

Fun Fact of the Day

The computational cost of canonical CCSD(T) formally scales as O(N⁷), yet with modern locality and sparsity exploitation, effective scaling in large insulating systems is often closer to N⁴-N⁵, blurring the once‑clear boundary between “benchmark” and “production” methods.

Fun Fact of the Day
Hydrogen cyanide, although highly polar, can form solid-state cocrystals with nonpolar hydrocarbons such as methane and ethane under Titan-like cryogenic conditions, violating the textbook “like dissolves like” intuition for mixing polar and nonpolar species. Quantum-mechanical calculations confirm that insertion of these small hydrocarbons into the HCN lattice can be energetically favorable, with distinct shifts in Raman-active vibrational modes as a spectroscopic signature.

DOI: 10.1073/pnas.2507522122

Fun Fact of the Day

Even in a perfect electromagnetic vacuum, quantum field theory predicts non‑zero “zero‑point energy,” so the ground state contains incessant fluctuations and virtual particle–antiparticle pairs. These vacuum fluctuations contribute to phenomena like the Casimir effect and set fundamental baselines for excited‑state and response calculations.

❄️ The Virtual Winter School on Computational Chemistry starts in one week! ❄️

💻 The event is fully online and free of charge.
📊 Submit your Single-Figure Presentation (SFP) to earn a participation certificate,
🧪 enjoy workshops led by the Q-Chem and GROMACS teams,
🎓 and attend lectures by leading experts across different areas of computational chemistry.

⏰ SFP submission deadline: *January 21st, 23:59 CET*
🚀 Do not miss this opportunity!

🔗 More information and registration: https://winterschool.cc

🚀 Tomorrow (08:55 CET) the 2026 Virtual Winter School on Computational Chemistry begins!
🧪 Five days of free talks, Single-Figure Presentations, round tables, and workshops by #Q-Chem and #GROMACS.
🏅 SFP submitters and GROMACS workshop participants receive certificates.

#CompChem #VWSCC

https://winterschool.cc/

We’re about to kick off!
In just a few minutes (08:55 CET), Dr. Cate Anstöter officially opens VWSCC 2026 welcoming our first speaker, Dr. Esther Heid, with the talk
“Predictive and Generative Deep Learning Approaches for Chemical Reactions.”
The week starts strong - don’t miss it https://winterschool.cc/program/day-1/welcome-to-vwscc26#/
#CompChem