The underground argon project: procurement and purification of argon for dark matter searches and beyond
Bibliographic record
Abstract
The existence of dark matter in the universe is inferred from abundant astrophysical and cosmological observations. The Global Argon Dark Matter Collaboration (GADMC) aims to perform the searches for dark matter in the form of weakly interacting massive particles (WIMPs), whose collisions with argon nuclei would produce nuclear recoils with tens of keV energy. Argon has been considered an excellent medium for the direct detection of WIMPs as argon-based scintillation detectors can make use of pulse shape discrimination (PSD) to separate WIMP-induced nuclear recoil signals from electron recoil backgrounds with extremely high efficiency. However, argon-based direct dark matter searches must confront the presence of intrinsic 39 Ar as the predominant source of electron recoil backgrounds (it is a beta-emitter with an endpoint energy of 565 keV and half-life of 269 years). Even with PSD, the 39 Ar activity in atmospheric argon (AAr), mainly produced and maintained by cosmic ray-induced nuclear reactions, limits the ultimate size of argon-based detectors and restricts their ability to probe very-low-energy events. The discovery of argon from deep underground wells with significantly less 39 Ar than that in AAr was an important step in the development of direct dark matter detection experiments using argon as the active target. Thanks to pioneering research and successful R&D, in 2012, the first 160 kg batch of underground argon (UAr) was extracted from a CO 2 well in Cortez, Colorado. The DarkSide-50 experiment at the Gran Sasso National Laboratory (LNGS) in Italy, the first liquid argon detector ever operated with a UAr target, demonstrated a ∼ 1,400 suppression of the 39 Ar activity with respect to the atmospheric argon. An even larger suppression is expected for 42 Ar (another intrinsic beta-emitter with the 42 K daughter isotope, also a beta-emitter) as its production is expected mainly in the upper atmosphere. Following the results of DarkSide-50, the GADMC initiated the UAr project for extraction from underground and cryogenic purification of 100 t of argon to be used as a target in the next-generation experiment DarkSide-20k. This paper contains a description of the Urania Plant in Cortez, Colorado, where UAr is extracted; the Aria Plant in Sardinia, Italy, an industrial-scale plant comprising a 350-m state-of-the-art cryogenic isotopic distillation column, designed for further purification of the extracted argon and further reduction of the isotopic abundance of 39 Ar; and DArT, a facility for UAr radiopurity qualification at the Canfranc Underground Laboratory (LSC), Spain. Moreover, the high radiopurity of UAr leads to other possible applications, for instance, for those neutrinoless double-beta decay experiments using argon as shielding material or, more generally, for all those activities on argon-based detectors in high-energy physics or nuclear physics, which will be briefly discussed.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".