A semiclassical model of the immediate temperature distribution surrounding the track of heavy ions with therapeutic energies
Bibliographic record
Abstract
Abstract Objective. Spikes of high temperature and pressure are created in the vicinity of heavy ions, especially at the Bragg peak. The expected subsequent thermoacoustic effects are however not well understood. In particular, the distribution of the densely packed primary interactions has not been considered in molecular dynamics (MDs) simulations or shock wave solutions. In this work, we derive a dedicated model to describe the primary interactions and their radial distribution, applicable to the modeling of acoustic and thermodynamic effects at the nanoscale. Approach. Starting from first principles, we assemble a semiclassical model of the energy loss of the primary heavy ions, consistent with the expected linear energy transfer and parametrized with the distance from the track. Based on the interaction energies, we then disentangle the primary energy depositions, i.e. the primary excitations and binding energies of the secondary electrons. Thereby we obtain the radial distribution of the primary interactions, independent of empirical parameters. Our theoretical description is kept general, however, numerical results are presented for protons stopped in water. Validity and uncertainties of our model are analyzed in detail. Main results. Following from the sought radial energy distribution, we find that the primary interactions are the dominant energy depositions below a radius of 1 nm. This can give rise to thermal spikes as high as 103 K even for low-Z projectiles, such as protons stopped in water. The presented model is valid down to primary proton energies of approximately 0.5 MeV. Significance. Our results can be used to revise the thermodynamic modeling at the nanoscale and investigate their potential involvement in the intriguing biological response to novel modalities such as FLASH or spatially fractionated radiotherapies. Also, our findings can be integrated into microscale track structure Monte Carlo codes, or ab initio MD simulations, for more accurate modeling in the nanometer domain.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".