Francesco Calcagno
@fcalcagno.bsky.social
📤 14
📥 28
📝 8
PostDoc at the University of Bologna 🇮🇹🇪🇺
#CompChem
#QuantumComputing
#AI
and much more!
pinned post!
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
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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...
https://arxiv.org/abs/2508.15896
4 months ago
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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...
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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 ...
https://pubs.rsc.org/en/content/articlelanding/2025/dd/d5dd00210a
5 days ago
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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
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HPQC - High-Performance and Quantum Computing
HPQC - High-Performance and Quantum Computing
https://master.unibo.it/hpqc/en
3 months ago
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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
loading . . .
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...
https://arxiv.org/abs/2508.15896
4 months ago
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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...
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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 ...
https://doi.org/10.1101/2025.07.15.665010
4 months ago
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🚀 LDHs for CO2 conversion: our new review is now out!
doi.org/10.1002/tcr....
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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, ....
https://doi.org/10.1002/tcr.202500014
8 months ago
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Is DFT enough? Learn more in our new paper!
doi.org/10.1039/D4ME...
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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...
https://doi.org/10.1039/D4ME00183D
10 months ago
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🚀 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...
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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...
https://www.cell.com/cell-reports-physical-science/fulltext/S2666-3864%2824%2900605-2
10 months ago
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Now in
#OA
on the
#JCC
!
#NMR
calculations of 31P shielding using MD and QM/MM
doi.org/10.1002/jcc....
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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....
https://doi.org/10.1002/jcc.27338
10 months ago
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