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X-ray free-electron lasers (XFELs) produce X-ray pulses with high brilliance and short pulse duration. These properties enable structural investigations of biomolecular nanocrystals, and they allow resolving the dynamics of biomolecules down to the femtosecond timescale. Liquid jets are widely used to deliver samples into the XFEL beam. The impact of the X-ray pulse leads to vaporization and explosion of the liquid jet, while the expanding gas triggers the formation of shock wave trains traveling along the jet, which may affect biomolecular samples before they have been probed. Here, we used molecular dynamics simulations to reveal the structural dynamics of shock waves after an X-ray impact. Analysis of the density in the jet revealed shock waves that form close to the explosion center, travel along the jet with supersonic velocities and decay exponentially with an attenuation length proportional to the jet diameter. A trailing shock wave formed after the first shock wave, similar to the shock wave trains in experiments. Although using purely classical models in the simulations, the resulting explosion geometry and shock wave dynamics closely resemble experimental findings, and they highlight the importance of atomistic details for modeling shock wave attenuation., Comment: 16 pages, 11 figures

Small-angle X-ray or neutron scattering (SAXS/SANS/SAS) is widely used to obtain structural information on biomolecules or soft-matter complexes in solution. Deriving a molecular interpretation of the scattering signals requires methods for predicting SAS patterns from a given atomistic structural model. Such SAS predictions are non-trivial because the patterns are influenced by the hydration layer of the solute, the excluded solvent, and by thermal fluctuations. Many computationally efficient methods use simplified, implicit models for the hydration layer and excluded solvent, leading to some uncertainties and to free parameters that require fitting against experimental data. SAS predictions based on explicit-solvent molecular dynamics (MD) simulations overcome such limitations at the price of an increased computational cost. To rationalize the need for explicit-solvent methods, we first review the approximations underlying implicit-solvent methods. Next, we describe the theory behind explicit-solvent SAS predictions that are easily accessible via the WAXSiS web server. We present the workflow for computing SAS pattern from a given molecular dynamics trajectory with a freely available via a modified version of the GROMACS simulations software, coined GROMACS-SWAXS, which implements the WAXSiS method. Practical considerations for running routine explicit-solvent SAS predictions are discussed.