Francesco Calcagno

QO-BRA: A Quantum Operator-Based Autoencoder for De Novo Molecular Design We introduce a variational quantum autoencoder tailored for de novo molecular design, named QO-BRA (Quantum Operator-Based Real Amplitude autoencoder). QO-BRA leverages quantum circuits for real-ampli...

Thrilled to see this paper out on #JCTC!

pubs.acs.org/doi/10.1021/...

Mol2Raman: a graph neural network model for predicting Raman spectra from SMILES representations Raman spectroscopy is a powerful technique for probing molecular vibrations, yet the computational prediction of Raman spectra remains challenging due to the high cost of quantum chemical methods and ...

Thrilled to share our latest work now published on @digital-discovery.rsc.org ! 🎉

👉 “Mol2Raman: a graph neural network model for predicting Raman spectra from SMILES representations”

pubs.rsc.org/en/content/a...

HPQC - High-Performance and Quantum Computing HPQC - High-Performance and Quantum Computing

Interested in #QuantumComputing and #HPC? Join the second edition of the HPQC Master’s program at the University of Bologna 🇮🇹!

Apply now:
master.unibo.it/hpqc/en

The Quantum Ensemble Variational Optimization Algorithm: Applications to Molecular Inverse Design Designing molecules with optimized properties remains a fundamental challenge due to the intricate relationship between molecular structure and properties. Traditional computational approaches that ad...

Breaking the glass ceiling of molecular design with quantum computers #QC!

Thrilled to share our new preprint on #QEVO!

Read more about QEVO👇
arxiv.org/abs/2508.15896

QOBRA: A Quantum Operator-Based Autoencoder for De Novo Molecular Design We introduce a variational quantum autoencoder tailored for de novo molecular design named QOBRA (Quantum Operator-Based Real-Amplitude autoencoder). QOBRA le circuits for real-amplitude encoding and ...

Protein design with Quantum Machine Learning #QML. Not sci-fi, but reality!

Read more about QOBRA in our latest work 👇
doi.org/10.1101/2025...

Advancing CO2 Conversion with Cu‐LDHs: A Review of Computational and Experimental Studies The combination of computational and experimental approaches provides fundamental insights into the electro- and photocatalytic conversion of CO2 on complex Layered Double Hydroxide-based catalysts, ....

🚀 LDHs for CO2 conversion: our new review is now out!

doi.org/10.1002/tcr....

Is DFT enough? Towards accurate high-throughput computational screening of azobenzenes for molecular solar thermal applications An efficient screening of azobenzene (AB) derivatives for Molecular Solar Thermal (MOST) applications based on ground state properties (energy stored per molecule and Z isomer stability) could be perf...

Is DFT enough? Learn more in our new paper!

doi.org/10.1039/D4ME...

Combined computational-experimental study of Ru(0)-catalyzed Guerbet reaction Calcagno et al. show the reaction performance of a ruthenium catalyst for the production of biofuels from second-generation feedstock. Synergistic experimental and computational investigations provide...

🚀 Excited to share our latest paper in @cp-cellrepphyssci.bsky.social

“Combined computational-experimental study of Ru(0)-catalyzed Guerbet reaction”

Fantastic collab 🇮🇹🇸🇪!

doi.org/10.1016/j.xc...

Modeling solvent effects and convergence of 31P‐NMR shielding calculations with COBRAMM The effect of different solution models in the computation of 31P-NMR shielding values was investigated. This work aimed to show the computational advantage of performing QM/MM optimizations to speed....

Now in #OA on the #JCC! #NMR calculations of 31P shielding using MD and QM/MM

doi.org/10.1002/jcc....