Effect of environmental conditions on the spectroscopic signature of DNT in sand
Bibliographic record
Abstract
Landmines have been a part of war technology for many years. As a result of the continued and indiscriminate use in approximately 90 countries landmines pose a severe and ever growing problem and a daily risk. Raman Spectroscopy is capable of providing rich information about the molecular structure of the sample and pinpoint detection of many chemicals, both of organic and inorganic nature. The presence of landmines in soils can be detected by Raman Spectroscopy sensing in a Point Detection modality, using characteristic vibrational signals of each explosive present in landmines. Detection of 2,4-DNT in sand and studies on how the vibrational signatures of 2,4-DNT is modified by interacting with soil particles and environmental conditions is reported. Raman Microspectrometers equipped with 514 nm and 785 nm laser excitation lines were used. The work focused in how the spectroscopic signatures of DNT in contact with Ottawa Sand are affected by the presence of humidity, pH, temperature, UV light and reaction times. Samples of mixtures of sand/2,4-DNT were analyzed by Raman Spectroscopy at 10, 50 and 100% water content and temperatures in range of 40-80 °C. Mixtures were also analyzed at different pH: 4, 7 and 10 and under ultraviolet light at 254 nm. Raman spectra were taken as a function of time in an interval from 24 to 336 hours (two weeks). Characteristic signals of 2,4-DNT were analyzed in different ranges 100-3800 cm-1, 600-1200 cm-1, 300-1700 cm-1 and 2800-3500 cm-1. The effect of these variables was measured during 45 consecutive days. It was confirmed that the decrease of characteristic vibrational signatures of 2,4-DNT can be attributed to increase of the degradation of 2,4-DNT by the simulated environmental conditions. Spectroscopic characterization of degradation products, both in contact with sand as well as airborne is under way. These results will make possible the development of highly sensitive sensors for detection of explosives materials and correlated with their degradation products in landmines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".