Merge branch 'master' into gpu-constraints

Author: ejmeitz

NEWS.md

@@ -1,5 +1,26 @@
 # Molly.jl release notes
 
+## v0.22.3 - Jul 2025
+
+### Bug fixes
+- A bug when calculating the potential energy of a system using Measurements.jl is fixed.
+
+## v0.22.2 - Jun 2025
+
+### New features
+- `write_structure` is added to allow a system to be written to a file.
+- `TrajectoryWriter` now writes out better PDB files. `StructureWriter` is now an alias for `TrajectoryWriter` with the PDB format and will be removed in a future breaking release. It is recommended to replace instances of `StructureWriter` with `TrajectoryWriter`.
+- The `excluded_res` and `write_boundary` keyword arguments can now be given to `TrajectoryWriter`. The `atom_inds` keyword argument can now be given to `StructureWriter`.
+- `AtomData`can now store `chain_id` and `hetero_atom`, allowing better file writing.
+- The Urey-Bradley potential is added as `UreyBradley`.
+- The mixing functions `waldman_hagler_σ_mixing`, `waldman_hagler_ϵ_mixing` and `fender_halsey_ϵ_mixing` are added.
+- Additional keyword arguments can now be provided to the `System` constructor taking in an AtomsBase system.
+
+### Bug fixes
+- A bug when initialising forces in `LangevinSplitting` is fixed.
+- A bug when converting from an AtomsBase system without velocities is fixed.
+- A bug when setting up a system with infinite boundaries from a file is fixed.
+
 ## v0.22.1 - Mar 2025
 
 ### New features

Project.toml

@@ -1,7 +1,7 @@
 name = "Molly"
 uuid = "aa0f7f06-fcc0-5ec4-a7f3-a573f33f9c4c"
 authors = ["Joe G Greener <jgreener@hotmail.co.uk>"]
-version = "0.22.1"
+version = "0.22.3"
 
 [deps]
 Atomix = "a9b6321e-bd34-4604-b9c9-b65b8de01458"
@@ -62,7 +62,7 @@ Distances = "0.10"
 Distributions = "0.23, 0.24, 0.25"
 Enzyme = "0.13.20"
 EzXML = "1"
-GLMakie = "0.8, 0.9, 0.10, 0.11"
+GLMakie = "0.8, 0.9, 0.10, 0.11, 0.12, 0.13"
 GPUArrays = "11"
 Graphs = "1.8"
 KernelAbstractions = "0.9"

docs/src/differentiable.md

@@ -428,7 +428,7 @@ The [code is available](https://github.com/greener-group/GB99dms).
 
 ## Reversible simulation
 
-Molly.jl was also used to code [reversible simulation](https://arxiv.org/abs/2412.04374), an extension of differentiable simulation with RAD where the gradients are calculated explicitly.
+Molly.jl was also used to code [reversible simulation](https://doi.org/10.1073/pnas.2426058122), an extension of differentiable simulation with RAD where the gradients are calculated explicitly.
 This means the memory cost is constant in step number.
 
 ## Molecular loss functions

docs/src/documentation.md

@@ -137,6 +137,11 @@ visualize(sys.loggers.coords, boundary, "sim_lj.mp4")
 ```
 ![LJ simulation](images/sim_lj.gif)
 
+A Molly [`System`](@ref) can also be constructed from an AtomsBase.jl system. For example:
+```julia
+System(ab_sys; force_units=u"kJ/Å", energy_units=u"kJ")
+```
+
 ## GPU acceleration
 
 To run simulations on the GPU you will need to have a GPU available and then load the appropriate package:
@@ -577,6 +582,7 @@ The available specific interactions are:
 - [`FENEBond`](@ref) - 2 atoms
 - [`HarmonicAngle`](@ref) - 3 atoms
 - [`CosineAngle`](@ref) - 3 atoms
+- [`UreyBradley`](@ref) - 3 atoms
 - [`PeriodicTorsion`](@ref) - 4 atoms
 - [`RBTorsion`](@ref) - 4 atoms
 
@@ -1097,6 +1103,7 @@ The available loggers are:
 - [`GeneralObservableLogger`](@ref)
 - [`TemperatureLogger`](@ref)
 - [`CoordinatesLogger`](@ref)
+- [`DisplacementLogger`](@ref)
 - [`VelocitiesLogger`](@ref)
 - [`TotalEnergyLogger`](@ref)
 - [`KineticEnergyLogger`](@ref)

docs/src/examples.md

@@ -439,9 +439,9 @@ save("polymer_angle.png", f)
 ```
 ![Polymer angles](images/polymer_angle.png)
 
-## Machine learning potentials
+## ACE potentials
 
-There is [an example](https://acesuit.github.io/ACEpotentials.jl/dev/tutorials/molly) of using ACE potentials in Molly.
+There is [an example](https://acesuit.github.io/ACEmd.jl/stable/molly) of using ACE potentials in Molly via [ACEmd.jl](https://github.com/ACEsuit/ACEmd.jl).
 
 ## Python ASE calculator
 

docs/src/exercises.md

@@ -1,5 +1,5 @@
 # Molly exercises
 
-A notebook with exercises covering various parts of Molly is available [here](https://github.com/noeblassel/SINEQSummerSchool2023/blob/main/notebooks/molly_average.ipynb), with answers available [here](https://github.com/noeblassel/SINEQSummerSchool2023/blob/main/notebooks/molly_average_answers.ipynb).
+A notebook with exercises covering various parts of Molly is available [here](https://github.com/JuliaMolSim/Molly.jl/tree/master/exercises).
 
 Another notebook with exercises on computing transport coefficients with Molly is available [here](https://github.com/noeblassel/SINEQSummerSchool2023/blob/main/notebooks/shear_viscosity.ipynb).

docs/src/publications.md

@@ -9,7 +9,8 @@ A paper involving more contributors with further details on the software will be
 Other papers that use, contribute to or are compatible with Molly are listed below:
 
 - Martínez L. CellListMap.jl: Efficient and customizable cell list implementation for calculation of pairwise particle properties within a cutoff, [Comput Phys Commun](https://doi.org/10.1016/j.cpc.2022.108452) 279, 108452 (2022)
-- Blassel N and Stoltz G. Fixing the flux: A dual approach to computing transport coefficients, [arXiv](https://arxiv.org/abs/2305.08224) (2023)
 - Witt WC et al. ACEpotentials.jl: A Julia implementation of the atomic cluster expansion, [J Chem Phys](https://doi.org/10.1063/5.0158783) 159, 164101 (2023)
-- Greener JG. Reversible molecular simulation for training classical and machine learning force field, [arXiv](https://arxiv.org/abs/2412.04374) (2024)
+- Blassel N and Stoltz G. Fixing the Flux: A Dual Approach to Computing Transport Coefficients, [Journal of Statistical Physics](https://doi.org/10.1007/s10955-024-03230-x) 191, 17 (2024)
 - Spacek R, Monmarché P and Stoltz G. Transient Subtraction: A Control Variate Method for Computing Transport Coefficients, [Journal of Statistical Physics](https://doi.org/10.1007/s10955-025-03424-x) 192, 53 (2025)
+- Wu X, Shang X. Stochastic Norton Dynamics: An Alternative Approach for the Computation of Transport Coefficients in Dissipative Particle Dynamics, [arXiv](https://arxiv.org/abs/2504.14479) (2025)
+- Greener JG. Reversible molecular simulation for training classical and machine learning force field, [Proceedings of the National Academy of Sciences](https://doi.org/10.1073/pnas.2426058122) 122(22), e2426058122 (2025)