Schorlomite: a discussion of the crystal chemistry, formula, and inter-species boundaries

Examination of schorlomite from ijolite at Magnet Cove (USA) and silicocarbonatite at Afrikanda (Russia), using electron-microprobe and hydrogen analyses, X-ray diffraction and Mössbauer spectroscopy, shows the complexity of substitution mechanisms operating in Ti-rich garnets. These substitutions involve incorporation of Na in the eightfold-coordinated X site, Fe²⁺ and Mg in the octahedrally coordinated Y site, and Fe³⁺, Al and Fe²⁺ in the tetrahedrally coordinated Z site. Substitutions Ti⁴⁺Fe³⁺Fe³⁺_–1Si_–1 and Ti⁴⁺Al³⁺Fe³⁺_–1Si_–1 are of major significance to the crystal chemistry of schorlomite, whereas Fe²⁺ enters the Z site in relatively minor quantities (<3% Fe). There is no evidence (either structural or indirect, such as discrepancies between the measured and calculated Fe²⁺ contents) for the presence of ^[6]Ti³⁺ or ^[4]Ti⁴⁺ in schorlomite. The simplified general formula of schorlomite can be written as Ca₃Ti⁴⁺₂[Si_3-x(Fe³⁺,Al,Fe²⁺)_xO₁₂], keeping in mind that the notion of end-member composition is inapplicable to this mineral. In the published analyses of schorlomite with low to moderate Zr contents, x ranges from 0.6 to 1.0, i.e. Ti⁴⁺ in the Y site is <2 and accompanied by appreciable amounts of lower-charged cations (in particular, Fe³⁺, Fe²⁺ and Mg). For classification purposes, the mole percentage of schorlomite can be determined as the amount of ^[6]Ti⁴⁺, balanced by substitutions in the Z site, relative to the total occupancy in the Y site: (^[6]Ti⁴⁺–^[6]Fe²⁺–^[6]Mg²⁺– ^[8]Na⁺)/2. In addition to the predominant schorlomite component, the crystals examined in this work contain significant (>15 mol.%) proportions of andradite (Ca₃Fe³⁺₂Si₃O₁₂), morimotoite (Ca₃Fe²⁺TiSi₃O₁₂), and Ca₃MgTiSi₃O₁₂. The importance of accurate quantitative determination and assignment of Fe, Ti and other cations to the crystallographic sites for petrogenetic studies is discussed.

Principles of tabling

The mechanism of concentration on the shaking table is discussed and a fresh attempt is made to obtain the theoretical model describing the velocity of a fluid in depth and time when in contact with a symmetrically reciprocating surface.The significance of the many design and operational variables and their interrelationships are examined. The various areas where the shaking table plays its role are then considered.The relevant features of micropanner, superpanner and the subsequent macropanner and pulsepanner are also treated since they all, like the shaking table, have the differential motion in common.     

X-ray transient sources

The galactic distribution and physical nature of X-ray transient sources is investigated. Two types of transients are considered. The observational data on 41 X-ray transient sources are given, and the average parameters of hard and soft X-ray transients are estimated.     

Power spectrum of brightness temperature fluctuations derived from solar eclipse observations at 2.8 GHz

In this paper we report on the MEM power spectrum analysis of brightness temperature fluctuations observed at 2.8 GHz during the total solar eclipse of 16 February 1980. The observed periodicities range from 3.5 min to 64 min. These periodicities may arise due to spatial and/or temporal variations in the solar radio emission. The observed periodicities imply presence of scale sizes ranging from 70,000 to 600,000 km assuming that the brightness fluctuations arise because of spatial variation only. On the other hand, if these fluctuations are due to temporal variation, the observed periodicities correspond well to predicted modes of solar global oscillations.     

Testing for Trends in Data Unevenly Distributed in Time

Summary  The question discussed in this study is how to calculate linear trends in data that are not distributed evenly in time. This is examined with time series of ten climate elements at a single station, stratified according to a classification based on daily circulation patterns. Trends are calculated in three different ways: (i) from seasonal means, which is a common approach, (ii) from means of individual events, the event being defined as a sequence of days classified as one particular type, preceded and succeeded by another type, and (iii) from individual daily values. The most common method of estimating trend significance, i.e. the t-test of the Pearson correlation coefficient, has been shown to be applicable to seasonal and event-mean trends for all variables. For daily trends, the Monte Carlo test should be used instead. The daily, event-mean and seasonal trends differ from each other considerably for many combinations of climate variable and circulation type. The reason for this difference is identified. Received December 3, 1998 Revised June 21, 1999