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Releases: deepmodeling/DMFF

v1.0.0 Released

09 Nov 14:32
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DMFF v1.0.0 Released!

New features:

  • Implemented QEQ electrostatic potential under constant charge and constant potential modes.
  • Refactored the API layer, enhancing frontend robustness.
  • Support calculating electrostatic potential in non-periodic systems for point charge, BCC charge, QEQ model, and multipole model.
  • Added dmff.api.DMFFTopology class for storing topological information.
  • Added dmff.api.ParamSet class, supporting Pytree data structures for improved management of force field parameters.
  • Improved computation efficiency of PME kernel on GPU.
  • Implemented backend/save_dmff2tf.py, which stores DMFF potential as a TensorFlow module for use in C/C++ API calls.
  • Developed an OpenMM plugin, enabling the use of DMFF potential within OpenMM.

v0.2.0 Released

02 Dec 14:41
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DMFF v0.2.0 Released!

New features:

  • Support statistical property optimization using differentiable MBAR estimator
  • Support NBFix in Lennard-Jones potential
  • Support assigning parameters based on SMIRKS-pattern
  • Support bond charge correction (BCC) and virtual site
  • Support building neighborlist with freud package

v0.1.1 Released

17 Jun 13:34
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DMFF v0.1.1 Released!

  • Fix bugs in parsing multiple force field files
  • Fix bugs in LJ force
  • Refine examples and installation code

v0.1.0 Released!

14 Jun 10:07
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DMFF v0.1.0 released!

  • Support differentiable calculation of classical, multiple polarizable and subgragh neural network force fields
  • Refined documents and examples
  • CI/CD workflows