Mechanism and Modelling Group UNSW

Using #compchem to predict molecular properties, reaction mechanisms etc. @UNSW. Led by Junming Ho, account run by group.

[The Journal of Physical Chemistry @JPhysChem]

Computational chemists at UNSW showed that basis set superposition errors (BSSE) mask the benefits of charge embedding in many body expansions. When BSSE is removed, charge embedding significantly accelerates convergence. @MechModelUNSW @UNSWScience
https://t.co/FvJybhOlFD

[Mechanism and Modelling Group UNSW @MechModelUNSW]

2) Our latest paper in J Chem Ed investigates how accurate are acid base approximations taught in undergraduate chemistry courses.

https://t.co/TRxcuhDPIj

#compchem #ozchem

[Mechanism and Modelling Group UNSW @MechModelUNSW]

Check out these two new papers from our group!

1) Efficient generation of CCSD(T)/CBS quality geometries and harmonic frequencies confirm that small basis DFT calculation for reaction thermochemistry is pretty accurate.

https://t.co/Wm7EKCXdb3

[The Journal of Physical Chemistry @JPhysChem]

Reliable Prediction of C–F bond dissociation energies in PFAS. Researchers @MechModelUNSW find significant errors in popular DFT methods with the degree of fluorination and the size of the molecule.
https://t.co/ZBfrIyW3TJ

[Mechanism and Modelling Group UNSW @MechModelUNSW]

So give us a follow and explore the many ways we use comp chem here in Sydney. Also, occasional photos of our fish tanks

[Mechanism and Modelling Group UNSW @MechModelUNSW]

Finally joining #compchem twitter, here's an thread with all the exciting things happening in the MMG!

[Mechanism and Modelling Group UNSW @MechModelUNSW]

Mack also published a paper comparing docking and molecular dynamics based MM-GBSA approach for the prediction of ligand binding affinities for a carbonic anhydrase zinc metalloenzyme

https://t.co/ZU5Yrg7abu