MUSEUM AND SCHOOL GEOLOGY PROMOTION AMONG PUPILS IN HIGHER CLASSES

Results of the 5-year geological experimental course at school are considered. Sources and qualification of workers from Geological Department at National Science Nature Museum of National Academy of Sciences were used for teaching. The museum space was used as a place for direct understanding and study of an examined geological sample. The course included theory, laboratory and field practice, academic competition and quizzes The dynamics of knowledge changes for learners was established. Some of them chose geology as their future scientific direction after the course. Problems of teaching were noticed to be connected with the lack of motivation among students. The tendency was observed both in obtaining of profound knowledge and in learning of geology in general. The key method of the problem’s solution is achieving of ultimate dynamic in lessons It can be realized by 1) active using of laboratory possibilities at museums and academic institutions; 2) work with rock templates\minerals collections; 3) field or rocks expeditions; 4) organizations of competitions; 5) contact with parents of learners. The obtained statistical and methodical material can become a basis for next similar experiments at schools.

A simple single-stage extraction method for Mo separation from geological samples for isotopic analysis by MC-ICP-MS

Simple, fast and efficient column separation of Mo from geological sample matrices using the TRU resin.

Characterizing Complex Mineral Structures in Thin Sections of Geological Samples with a Scanning Hall Effect Microscope

We improved a magnetic scanning microscope for measuring the magnetic properties of minerals in thin sections of geological samples at submillimeter scales. The microscope is comprised of a 200 µm diameter Hall sensor that is located at a distance of 142 µm from the sample; an electromagnet capable of applying up to 500 mT DC magnetic fields to the sample over a 40 mm diameter region; a second Hall sensor arranged in a gradiometric configuration to cancel the background signal applied by the electromagnet and reduce the overall noise in the system; a custom-designed electronics system to bias the sensors and allow adjustments to the background signal cancelation; and a scanning XY stage with micrometer resolution. Our system achieves a spatial resolution of 200 µm with a noise at 6.0 Hz of 300 nTrms/(Hz)1/2 in an unshielded environment. The magnetic moment sensitivity is 1.3 × 10−11 Am2. We successfully measured the representative magnetization of a geological sample using an alternative model that takes the sample geometry into account and identified different micrometric characteristics in the sample slice.

Characterizing Complex Mineral Structures in Thin Section of Geological Sample with a Scanning Hall Effect Microscope

We improved a magnetic scanning microscope for measuring the magnetic properties of minerals in thin sections of geological samples at submillimeter scales. The microscope is comprised of a 200 µm diameter Hall sensor that is 142 µm from the sample; an electromagnet capable of applying to the sample up to 500 mT dc magnetic fields over a 40 mm diameter region; a second Hall sensor arranged in a gradiometric configuration to cancel the background signal applied by the electromagnet and reduce overall noise in the system; a custom-designed electronics to bias the sensors and provide adjustment for background signal cancelation; and a scanning XY stage with micrometer resolution. Our system achieves a spatial resolution of  220 µm with noise at 6.0 Hz of »300 nTrms/(Hz)1/2 in an unshielded environment. The magnetic moment sensitivity is 1.3 × 10−11 Am2.1/2 We successfully measured the representative magnetization of a geological sample using an alternative model that takes into account the sample geometry and identified different micrometric characteristics in the sample slice.

Sample Classification Algorithm Based on Spectral Similarity Calculation

According to the field geological sample classification, a spectral similarity the cluster analysis algorithm (SSCA) has been put forward. This algorithm expands and improves the spectra sort encoding algorithm on the spectral sorting and similarity computation, and adds similarity clustering analysis method. Testing on 100 field geological samples using SSCA algorithm, we get the results showing that this algorithm can make further classification for field geological samples to some extent.

Geological Sample Preparation Evaluations By EBSD Pattern Quality

Extended abstract of a paper presented at Microscopy and Microanalysis 2011 in Nashville, Tennessee, USA, August 7–August 11, 2011.