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Info

This page contains an overview of the projects/studies aimed at improving the FF optimization process in general. Specific features and decisions made for each FF optimization cycle should be recorded in FF Force field releases.

Objectives

Team

Main objective: Refine and improve FF optimization process.

Project driver: Lee-Ping Wang David Mobley Michael Shirts

Objectives for 2020:

  • Identify and improve poorly performing parameters in Parsley

  • Perform feasibility study for property calculations in FF optimization and benchmarking

  • Design a systematic procedure for selecting molecules for QM optimization/scanning from potentially available datasets (and possibly in some cases finding unusual chemistries outside datasets we have on hand)

Team members: Hyesu Jang Jeffrey Wagner Simon Boothroyd Jessica Maat (Deactivated)

Current Projects

Driver

Project / Study

Simon Boothroyd

Non-bonded optimization Binary Mixture Data Feasibility Study

Hyesu Jang David Mobley Jessica Maat (Deactivated)

QM dataset selection Parsley minor release(s) Training Dataset Selection

Scientific Questions

  • ForceBalance:

    • Cross-validation: Multiple fitting stages using the same training set and computing parameter uncertainties based on the observed changes?

    • Stochastic gradient optimization techniques? 

  • Have we selected right QM level of theory?

    • Do we have to be consistent across the use cases / types?

    • Can we use it to inform LJ?

      • Can we focus on the subset of molecules with strong steric interactions? Do those inform LJ effectively (more so than full set of molecules?)

    • Can we use ANI / Where can we use ANI?

  • What things should be co-optimized, when, and how much does it help?

    • Co-optimization of torsions and LJ parameters?

  • Should water model be co-optimized with FFs?

  • Does optimization get harder with more parameters?

  • Use of Dimensional reduction (PCA) in optimizations? 

  • Constrained parameterization for coupled FF parameters (for example, angles in benzene etc)?

  • Can Hessians identify soft degrees of freedom that should be driven?

  • How do we derive GBSA parameters?

  • H-bonds in fitting? Two versions -- one with and one without? What is the proper way to use constrained hydrogen bonds in QM fitting?

  • How do alternate RESP models impact accuracy?

  • How much do virtual sites help?

  • How much does polarization help? Which model (Drude, point polarizable, fluc-q) is best, or how do they compare?

  • What data types to get better results?

  • How do we use optimization trajectories to help?

Infrastructure Requirements

Desired features:

  • Cross-validation capability

  • Scaling ForceBalance

  • Internal coordinate Hessian for fitting

Software:

...