Structural Dynamics-Us最新文献

We introduce a computational framework that integrates artificial intelligence (AI), machine learning, and high-performance computing to enable real-time steering of neutron scattering experiments using an edge-to-exascale workflow. Focusing on time-of-flight neutron event data at the Spallation Neutron Source, our approach combines temporal processing of four-dimensional neutron event data with predictive modeling for multidimensional crystallography. At the core of this workflow is the Temporal Fusion Transformer model, which provides voxel-level precision in predicting 3D neutron scattering patterns. The system incorporates edge computing for rapid data preprocessing and exascale computing via the Frontier supercomputer for large-scale AI model training, enabling adaptive, data-driven decisions during experiments. This framework optimizes neutron beam time, improves experimental accuracy, and lays the foundation for automation in neutron scattering. Although real-time experiment steering is still in the proof-of-concept stage, the demonstrated potential of this system offers a substantial reduction in data processing time from hours to minutes via distributed training, and significant improvements in model accuracy, setting the stage for widespread adoption across neutron scattering facilities and more efficient exploration of complex material systems.

We introduce a hardware-software system for rapidly characterizing liquid microjets for x-ray diffraction experiments. An open-source python-based software package allows for programmatic and automated data collection and analysis. We show how jet speed, length, and diameter are influenced by nozzle geometry, gas flow rate, liquid viscosity, and liquid flow rate. We introduce "jet instability" and "jet probability" metrics to help quantify the suitability of a given nozzle for x-ray diffraction experiments. Among our observations were pronounced improvements in jet stability and reliability when using asymmetric needle-tipped nozzles, which allowed for the production of microjects smaller than 250 nm in diameter, traveling faster than 120 m/s.

Proteins, serving as the fundamental architects of biological processes, interact with ligands to perform a myriad of functions essential for life. Designing functional ligand-binding proteins is pivotal for advancing drug development and enhancing therapeutic efficacy. In this study, we introduce ProteinReDiff, an diffusion framework targeting the redesign of ligand-binding proteins. Using equivariant diffusion-based generative models, ProteinReDiff enables the creation of high-affinity ligand-binding proteins without the need for detailed structural information, leveraging instead the potential of initial protein sequences and ligand SMILES strings. Our evaluations across sequence diversity, structural preservation, and ligand binding affinity underscore ProteinReDiff's potential to advance computational drug discovery and protein engineering.

Light-matter interaction at the nanoscale in magnetic alloys and heterostructures is a topic of intense research in view of potential applications in high-density magnetic recording. While the element-specific dynamics of electron spins is directly accessible to resonant x-ray pulses with femtosecond time structure, the possible element-specific atomic motion remains largely unexplored. We use ultrafast electron diffraction (UED) to probe the temporal evolution of lattice Bragg peaks of FePt nanoparticles embedded in a carbon matrix following excitation by an optical femtosecond laser pulse. The diffraction interference between Fe and Pt sublattices enables us to demonstrate that the Fe mean square vibration amplitudes are significantly larger that those of Pt as expected from their different atomic mass. Both are found to increase as energy is transferred from the laser-excited electrons to the lattice. Contrary to this intuitive behavior, we observe a laser-induced lattice expansion that is larger for Pt than for Fe atoms during the first picosecond after laser excitation. This effect points to the strain-wave driven lattice expansion with the longitudinal acoustic Pt motion dominating that of Fe.

We analyze the structures of the low-spin (LS) ground state and the high-spin (HS) lowest excited state of the iron-(II)-tris bipyridine complex ([Fe(bpy)₃]²⁺) using density functional theory PBE methods, modeling the solvent interactions with conductor-like polarizable continuum model. These calculations are globally benchmarked against a wide range of experimental observables that include ultraviolet-visible linear absorption and circular dichroism (CD) spectra and Fe K-edge x-ray absorption near edge spectra (XANES). The calculations confirm the already established D₃ geometry of the LS state, as well as a departure from this geometry for the HS state, with the appearance of inequivalent Fe-N bond elongations. The simulated structures nicely reproduce the above-mentioned experimental observables. We also calculate the vibrational modes of the LS and HS states. For the former, they reproduce well the vibrational frequencies from published infrared and Raman data, while for the latter, they predict very well the low-frequency vibrational coherences, attributed to Fe-N stretch modes, which were reported in ultrafast spectroscopic experiments. We further present calculations of the high-frequency region, which agree with recent ultrafast transient infrared spectroscopy studies. This work offers a common basis to the structural information encoded in the excited state CD and the Fe K XANES of the HS state tying together different structural IR, UV-visible, and x-ray observables.

Time-resolved x-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data.

The structure and spin of photoexcited Fe²⁺(phen)₃ in water are examined by x-ray scattering and x-ray emission spectroscopy with 100 ps time resolution. Excitation of the low-spin (LS) ground state (GS) to the charge transfer state ¹MLCT^* leads to the formation of a high-spin (HS) state that returns to the GS in 725 ps. Density functional theory (DFT) predicts a Fe-N bond elongation in HS by 0.19 Å in agreement with the scattering data. The angle between the ligands increases by 5.4° in HS, which allows the solvent to get 0.33 Å closer to Fe in spite of the expansion of the molecule. The rise in solvent temperature from the return of photoproducts to the GS is dominated by the formation dynamics of HS, ¹MLCT^* → HS, which is followed by a smaller rise from the HS → GS transition. The latter agrees with the 0.61 eV energy gap E(HS)-E(LS) calculated by DFT. However, the temperature rise from the ¹MLCT → HS transition is greater than expected, by a factor of 2.1, which is explained by the re-excitation of nascent HS^* by the 1.2 ps pump pulse. This hypothesis is supported by optical spectroscopy measurements showing that the 1.2 ps long pump pulse activates the HS^* → ⁵MLCT^* channel, which is followed by the ultrafast return to HS^* via intersystem crossing. Finally, the spins of the photoproducts are monitored by the K_β emission and the spectra confirm that the spins of LS and HS states are 0 and 2, respectively.

Time-resolved soft-x-ray-diffraction experiments give access to microscopic processes in a broad range of solid-state materials by probing ultrafast dynamics of ordering phenomena. While laboratory-based high-harmonic generation (HHG) light sources provide the required photon energies, their limited photon flux is distributed over a wide spectral range, rendering typical monochromatic diffraction schemes challenging. Here, we present a scheme for energy-dispersive soft-x-ray diffraction with femtosecond temporal resolution and photon energies across the water window from 200 to 600 eV. The experiment utilizes the broadband nature of the HHG emission to efficiently probe large slices in reciprocal space. As a proof-of-concept, we study the laser-induced structural dynamics of a Mo/Si superlattice in an ultrafast, non-resonant soft-x-ray diffraction experiment. We extract the underlying strain dynamics from the measured shift of its first order superlattice Bragg peak in reciprocal space at photon energies around 500 eV via soft-x-ray scattering simulations.

Most x-ray sources are inherently polychromatic. Polychromatic ("pink") x-rays provide an efficient way to conduct diffraction experiments as many more photons can be used and large regions of reciprocal space can be probed without sample rotation during exposure-ideal conditions for time-resolved applications. Analysis of such data is complicated, however, causing most x-ray facilities to discard >99% of x-ray photons to obtain monochromatic data. Key challenges in analyzing polychromatic diffraction data include lattice searching, indexing and wavelength assignment, correction of measured intensities for wavelength-dependent effects, and deconvolution of harmonics. We recently described an algorithm, Careless, that can perform harmonic deconvolution and correct measured intensities for variation in wavelength when presented with integrated diffraction intensities and assigned wavelengths. Here, we present Laue-DIALS, an open-source software pipeline that indexes and integrates polychromatic diffraction data. Laue-DIALS is based on the dxtbx toolbox, which supports the DIALS software commonly used to process monochromatic data. As such, Laue-DIALS provides many of the same advantages: an open-source, modular, and extensible architecture, providing a robust basis for future development. We present benchmark results showing that Laue-DIALS, together with Careless, provides a suitable approach to the analysis of polychromatic diffraction data, including for time-resolved applications.

The application of dynamic strain holds the potential to manipulate topological invariants in topological quantum materials. This study investigates dynamic structural deformation and strain modulation in the Weyl semimetal WTe₂, focusing on the microscopic regions with static strain defects. The interplay of static strain fields, at local line defects, with dynamic strain induced from photo-excited coherent acoustic phonons results in the formation of local standing waves at the defect sites. The dynamic structural distortion is precisely determined utilizing ultrafast electron microscopy with nanometer spatial and gigahertz temporal resolutions. Numerical simulations are employed to interpret the experimental results and explain the mechanism for how the local strain fields are transiently modulated through light-matter interaction. This research provides the experimental foundation for investigating predicted phenomena such as the mixed axial-torsional anomaly, acoustogalvanic effect, and axial magnetoelectric effects in Weyl semimetals, and paves the road to manipulate quantum invariants through transient strain fields in quantum materials.