Paesani Lab

🚨 Our Perspective on single-ion hydration is out today in @JPhysChem #Letters!

👉 doi.org/10.1021/acs.jp…

We bring together what we’ve learned with our #MBpol and #MBnrg #datadriven #manybody potentials, following ions from small water clusters 🫧 to bulk solutions and the air/water interface. 🌊

The common thread is how short-range #machinelearned n-body terms trained on CCSD(T) data work together with the physics of electrostatics, polarization, and dispersion to predict hydration structure, spectra, and thermodynamics 🖥️. All without training our #datadriven #manybody potentials to solution-phase properties! 😎

Interested in performing #datadriven #manybody simulations? Check out #MBX:
✅ mbxsimulations.com
✅ github.com/paesanilab/MBX
✅ groups.google.com/g/mbx-users

Congrats to the team, and a special shout-out to Olivia, who contributed to this work while still in high school and is now an undergrad at @Caltech! 🙌

Big thanks to @NSF for supporting this research and to @ACCESSforCI for providing computational resources! 🙏

@UCSanDiego @UCSDPhySci @UCSDChem @HDSIUCSD @SDSC_UCSD

What an exciting day at the 9th #SoCalTheoChem Symposium at @SDSU! 🎉

So proud of our undergrads and grad students who presented six posters to the SoCal theoretical chemistry community, sharing research spanning ion transport, biomolecular simulations, hydration, vibrational spectroscopy, and faster many-body potentials! 🖥️

Huge thanks to the organizers for bringing everyone together for a great day of #compchem research and lively discussion!

@UCSanDiego @UCSDPhySci @UCSDChemBiochem @HDSIUCSD @SDSC_UCSD

🧩 New building blocks for peptide simulations!

👉 doi.org/10.26434/chemr…

Our latest @ChemRxiv preprint introduces an MB-nrg library of #datadriven #manybody potentials for all 20 standard amino acids, a step toward CCSD(T)-level simulations of peptides!

We combine #machinelearned n-body terms trained on DLPNO-CCSD(T) fragment data with physics-based electrostatics, polarization, and dispersion. These reusable building blocks let us assemble potentials for complete dipeptides without using whole-dipeptide energies for training. 😎

This is the first iteration of the potentials. We’ll keep improving and expanding them as we develop larger training sets of n-body interactions, including additional nonbonded and higher-body terms. 🏄‍♀️

Great work by Xinmao, Ethan, and Jiwon! 🙌

Interested in performing #datadriven #manybody simulations? Check out #MBX: ✅ mbxsimulations.com ✅ github.com/paesanilab/MBX ✅groups.google.com/g/mbx-users

Big thanks to @AFOSR for supporting the development of these MB-nrg potentials for amino acids and to @NSF for supporting their implementation in #MBX!

We are also grateful to #HPCMP and @ACCESSforCI for providing computational resources! 🙏

@UCSanDiego @UCSDPhySci @UCSDChem @HDSIUCSD @SDSC_UCSD

Today was Richa’s last day in the group. We knew it was coming, but saying goodbye still isn’t easy! 🥹

Richa, thank you for all the wonderful science, for mentoring our undergrads, and for being so generous with your time and ideas. So much to celebrate and so many good memories over these past five years! 🫶

We’re going to miss you! Good luck with your postdoc at @Columbia! We’re excited to see what you do next! Stay in touch and come back to visit! ❤️

#OnceAPirateAlwaysAPirate 🏴‍☠️

@UCSanDiego @UCSDPhySci @UCSDChem @HDSIUCSD @SDSC_UCSD @RichaRashm

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Our undergrads did it again! 🤯

Today, four more of our fantastic students shared their summer research on testing and improving machine-learned molecular models 💻, ion hydration 🌊, and how antifreeze proteins interact with ice. 🧊

Seven presentations over two Fridays and so much to be proud of! 🙌

A huge thank you to @NSF for supporting our undergraduate summer research program! 🙏

@UCSanDiego @UCSDPhySci @UCSDChem @HDSIUCSD @SDSC_UCSD