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We simulated Coulomb explosion dynamics due to fast ionization induced by high-intensity x-rays in six proteins that share similar atomic content and shape. We followed and projected the trajectory of the fragments onto a virtual detector, providing a unique explosion footprint. After collecting 500 explosion footprints for each protein, we utilized principal component analysis and 𝑡-distributed stochastic neighbor embedding to classify these. Results show that the classification algorithms were able to separate proteins on the basis of explosion footprints from structurally similar proteins into distinct groups. The explosion footprints, therefore, provide a unique identifier for each protein. We envision that method could be used concurrently with single-particle coherent imaging experiments to provide additional information on shape, mass, or conformation.

We describe a method to compute photon–matter interaction and atomic dynamics with x-ray lasers using a hybrid code based on classical molecular dynamics and collisional-radiative calculations. The forces between the atoms are dynamically determined based on changes to their electronic occupations and the formation of a free electron cloud created from the irradiation of photons in the x-ray spectrum. The rapid transition from neutral solid matter to dense plasma phase allows the use of screened potentials, reducing the number of non-bonded interactions. In combination with parallelization through domain decomposition, the hybrid code handles large-scale molecular dynamics and ionization. This method is applicable for large enough samples (solids, liquids, proteins, viruses, atomic clusters, and crystals) that, when exposed to an x-ray laser pulse, turn into a plasma in the first few femtoseconds of the interaction. We present four examples demonstrating the applicability of the method. We investigate the non-thermal heating and scattering of bulk water and damage-induced dynamics of a protein crystal using an x-ray pump–probe scheme. In both cases, we compare to the experimental data. For single particle imaging, we simulate the ultrafast dynamics of a methane cluster exposed to a femtosecond x-ray laser. In the context of coherent diffractive imaging, we study the fragmentation as given by an x-ray pump–probe setup to understand the evolution of radiation damage in the time range of hundreds of femtoseconds.

Water and ice are routinely studied with X-rays to reveal their diverse structures and anomalous properties. We employ a hybrid collisional-radiative/molecular-dynamics method to explore how femtosecond X-ray pulses interact with hexagonal ice. We find that ice makes a phase transition into a crystalline plasma where its initial structure is maintained up to tens of femtoseconds. The ultrafast melting process occurs anisotropically, where different geometric configurations of the structure melt on different time scales. The transient state and anisotropic melting of crystals can be captured by X-ray diffraction, which impacts any study of crystalline structures probed by femtosecond X-ray lasers.

- Single particle imaging using X-ray lasers is a technique aiming to capture atomic resolution structures of biomolecules in their native state. Knowing the particle's orientation during exposure is crucial for method enhancement. It has been shown that the trajectories of sulfur atoms in a Coulomb exploding lysozyme are reproducible, providing orientation information. This study explores if sulfur atom depth influences explosion trajectory. Employing a hybrid collisional-radiative/molecular dynamics model, we analyze the X-ray laser-induced dynamics of a single sulfur ion at varying depths in water. Our findings indicate that the ion spread-depth relationship depends on pulse parameters. At a photon energy of 2 keV, high-charge states are obtained, resulting in an increase of the spread with depth. However, at 8 keV photon energy, where lower charge states are obtained, the spread is essentially independent with depth. Finally, lower ion mass results in less reproducible trajectories, opening a promising route for determining protein orientation through the introduction of heavy atoms.

Saturable absorption is a nonlinear effect where a material's ability to absorb light is frustrated due to a high influx of photons and the creation of electron vacancies. Experimentally induced saturable absorption in copper revealed a reduction in the temporal duration of transmitted x-ray laser pulses, but a detailed account of changes in opacity and emergence of resonances is still missing. In this computational work, we employ nonlocal thermodynamic equilibrium plasma simulations to study the interaction of femtosecond x rays and copper. Following the onset of frustrated absorption, we find that a K–M resonant transition occurring at highly charged states turns copper opaque again. The changes in absorption generate a transient transparent window responsible for the shortened transmission signal. We also propose using fluorescence induced by the incident beam as an alternative source to achieve shorter x-ray pulses. Intense femtosecond x rays are valuable to probe the structure and dynamics of biological samples or to reach extreme states of matter. Shortened pulses could be relevant for emerging imaging techniques.

We demonstrate that x-ray fluorescence emission, which cannot maintain a stationary interference pattern, can be used to obtain images of structures by recording photon-photon correlations in the manner of the stellar intensity interferometry of Hanbury Brown and Twiss. This is achieved utilizing femtosecondduration pulses of a hard x-ray free-electron laser to generate the emission in exposures comparable to the coherence time of the fluorescence. Iterative phasing of the photon correlation map generated a model-free real-space image of the structure of the emitters. Since fluorescence can dominate coherent scattering, this may enable imaging uncrystallised macromolecules.

A nanopore is a tool in single-molecule sensing biotechnology that offers label-free identification with high throughput. Nanopores have been successfully applied to sequence DNA and show potential in the study of proteins. Nevertheless, the task remains challenging due to the large variability in size, charges, and folds of proteins. Miniproteins have a small number of residues, limited secondary structure, and stable tertiary structure, which can offer a systematic way to reduce complexity. In this computational work, we theoretically evaluated sensing two miniproteins found in the human body using a silicon nitride nanopore. We employed molecular dynamics methods to compute occupied-pore ionic current magnitudes and electronic structure calculations to obtain interaction strengths between pore wall and miniprotein. From the interaction strength, we derived dwell times using a mix of combinatorics and numerical solutions. This latter approach circumvents typical computational demands needed to simulate translocation events using molecular dynamics. We focused on two miniproteins potentially difficult to distinguish owing to their isotropic geometry, similar number of residues, and overall comparable structure. We found that the occupied-pore current magnitudes not to vary significantly, but their dwell times differ by 1 order of magnitude. Together, these results suggest a successful identification protocol for similar miniproteins.

Water and ice are routinely studied with X-rays to reveal their diverse structures and anomalous properties. We employ a hybrid collisional-radiative/molecular dynamics method to explore how femtosecond X-ray pulses interact with hexagonal ice. We find that ice makes a phase transition into a crystalline plasma where its initial structure is maintained up to tens of femtoseconds. The ultrafast melting process occurs anisotropically, where different geometric configurations of the structure melt on different time scales. The transient state and anisotropic melting of crystals can be captured by X-ray diffraction, which impacts any study of crystalline structures probed by femtosecond X-ray lasers.

We have developed a hybrid Monte Carlo and classical molecular dynamics code to follow the ultrafast atomic dynamics in biological macromolecules induced by a femtosecond X-ray laser. Our model for fragmentation shows good qualitative agreement with ab-initio simulations of small molecules, while being computationally faster.  We applied the code for macromolecules and simulated the Coulomb explosion dynamics due to the fast ionization in six proteins with different physical properties. The trajectories of the ions are followed and projected onto a detector, where the particular pattern depends on the protein, providing a unique footprint. We utilize algorithms such as principal component analysis  and t-distributed stochastic neighbor embedding to classify the fragmentation pattern. The results show that the classification algorithms are able to separate the explosion patterns into distinct groups. We envision that this method could be used to provide additional class information, like particle mass or shape, in structural determination experiments using X-ray lasers.

Radiation damage is a topic since the dawn of X-ray crystallography, and has gained new importance in the era of X-ray free-electron lasers (XFELs), due to their unprecedented brilliance and pulse duration. One of the driving questions has been how short the XFEL pulse has to be for the structural information to be ”damage free”. Here we compare data from Serial Femtosecond Crystallography (SFX) experiments conducted with a 3 fs and a 10 fs X-ray pulse. We conclude that even if the estimated displacement of atoms in the sample is an order of magnitude larger in the case of the 10 fs experiment, the displacement is still too small to affect the experimental data at a resolution relevant for structural determination.