Picosecond infrared laser driven sample delivery for simultaneous liquid-phase and gas-phase electron diffraction studies
Bibliographic record
Abstract
Here, we report on a new approach based on laser driven molecular beams that provides simultaneously nanoscale liquid droplets and gas-phase sample delivery for femtosecond electron diffraction studies. The method relies on Picosecond InfraRed Laser (PIRL) excitation of vibrational modes to strongly drive phase transitions under energy confinement by a mechanism referred to as Desorption by Impulsive Vibrational Excitation (DIVE). This approach is demonstrated using glycerol as the medium with selective excitation of the OH stretch region for energy deposition. The resulting plume was imaged with both an ultrafast electron gun and a pulsed bright-field optical microscope to characterize the sample source simultaneously under the same conditions with time synchronization equivalent to sub-micrometer spatial resolution in imaging the plume dynamics. The ablation front gives the expected isolated gas phase, whereas the trailing edge of the plume is found to consist of nanoscale liquid droplets to thin films depending on the excitation conditions. Thus, it is possible by adjusting the timing to go continuously from probing gas phase to solution phase dynamics in a single experiment with 100% hit rates and very low sample consumption (<100 nl per diffraction image). This approach will be particularly interesting for biomolecules that are susceptible to denaturation in turbulent flow, whereas PIRL-DIVE has been shown to inject molecules as large as proteins into the gas phase fully intact. This method opens the door as a general approach to atomically resolving solution phase chemistry as well as conformational dynamics of large molecular systems and allow separation of the solvent coordinate on the dynamics of interest.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".