Krasnoshteinite, Al8[B2O4(OH)2](OH)16Cl4⋅7H2O, a New Microporous Mineral with a Novel Type of Borate Polyanion
Bibliographic record
Abstract
A new mineral, krasnoshteinite (Al8[B2O4(OH)2](OH)16Cl4⋅7H2O), was found in the Verkhnekamskoe potassium salt deposit, Perm Krai, Western Urals, Russia. It occurs as transparent colourless tabular to lamellar crystals embedded up to 0.06 x 0.25 x 0.3 mm in halite-carnallite rock and is associated with dritsite, dolomite, magnesite, quartz, baryte, kaolinite, potassic feldspar, congolite, members of the goyazite–woodhouseite series, fluorite, hematite, and anatase. Dmeas = 2.11 (1) and Dcalc = 2.115 g/cm3. Krasnoshteinite is optically biaxial (+), α = 1.563 (2), β = 1.565 (2), γ = 1.574 (2), and 2Vmeas = 50 (10)°. The chemical composition (wt.%; by combination of electron microprobe and ICP-MS; H2O calculated from structure data) is: B2O3 8.15, Al2O3 46.27, SiO2 0.06, Cl 15.48, H2Ocalc. 33.74, –O=Cl –3.50, totalling 100.20. The empirical formula calculated based on O + Cl = 33 apfu is (Al7.87Si0.01)Σ7.88[B2.03O4(OH)2][(OH)15.74(H2O)0.26]Σ16[(Cl3.79(OH)0.21]Σ4⋅7H2O. The mineral is monoclinic, P21, a = 8.73980 (19), b = 14.4129 (3), c = 11.3060 (3) Å, β = 106.665 (2)°, V = 1364.35 (5) Å3, and Z = 2. The crystal structure of krasnoshteinite (solved using single-crystal data, R1 = 0.0557) is unique. It is based upon corrugated layers of Al-centered octahedra connected via common vertices. BO3 triangles and BO2(OH)2 tetrahedra share a common vertex, forming insular [B2O4(OH)2]4− groups (this is a novel borate polyanion) which are connected with Al-centered octahedra via common vertices to form the aluminoborate pseudo-framework. The structure is microporous, zeolite-like, with a three-dimensional system of wide channels containing Cl- anions and weakly bonded H2O molecules. The mineral is named in honour of the Russian mining engineer and scientist Arkadiy Evgenievich Krasnoshtein (1937–2009). The differences in crystal chemistry and properties between high-temperature and low-temperature natural Al borates are discussed.
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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 | 0.000 |
| 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".