52 research outputs found
Biosensors based on conductometric detection
The present paper is a self-review on the development of about 20 conductometric biosensors based on planar electrodes and containing different biological material (enzymes, cells, antibodies), bio-mimics or synthetic membranes, including Imprinting polymers, as a sensitive element. Highly specific, sensitive, simple, fast and cheap determination of different analytes makes them promising for needs of medicine, biotechnology, environmental control, agriculture and food industry. Non-specific interference of back-ground ions may be overcome by the differential mode of measurement, the usage of rather concentrated sample buffer and additional negatively or positively charged membranes, which decrease buffer capacity influence and extend a dynamic range of sensors response. For development of easy-to-use small conductometric immunosensors several approaches seem to be promising: i) the usage of polyaniline as electroconductive label for antibodies detection in competitive electroimmunoassay; ii) the elaboration of multilayer structures with phtalocyanine films; iii) the usage of acrylic copolymeric membranes. The advantages and disadvantages of conductometric biosensors created are discussed. For future commercialisation our effort are aimed to unite a thin-film technology with membranes deposition and to find the ways of membrane stabilisation, including bio-mimics creation, utilisation of bioaffinity polymeric membranes, imprinting polymers etc.ΠΠ³Π»ΡΠ΄ ΠΏΡΠΈΡΠ²ΡΡΠ΅Π½ΠΎ Π°Π½Π°Π»ΡΠ·Ρ Π²Π»Π°ΡΠ½ΠΈΡ
ΡΠΎΠ±ΡΡ Π· ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ Π±Π»ΠΈΠ·ΡΠΊΠΎ 20 ΠΊΠΎΠ½Π΄ΡΠΊΡΠΎΠΌΠ΅ΡΡΠΈΡΠ½ΠΈΡ
Π±ΡΠΎΡΠ΅Π½ΡΠΎΡΡΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΠΏΠ»Π°Π½Π°ΡΠ½ΠΈΡ
Π΅Π»Π΅ΠΊΡΡΠΎΠ΄ΡΠ² ΡΠ° ΡΡΠ·Π½ΠΎΠΌΠ°Π½ΡΡΠ½ΠΎΠ³ΠΎ Π±ΡΠΎΠ»ΠΎΠ³ΡΡΠ½ΠΎΠ³ΠΎ ΠΌΠ°ΡΠ΅ΡΡΠ°Π»Ρ (ΡΠ΅ΡΠΌΠ΅Π½ΡΠΈ, ΠΊΠ»ΡΡΠΈΠ½ΠΈ, Π°Π½ΡΠΈΡΡΠ»Π°), ΡΠΈΠ½ΡΠ΅ΡΠΈΡΠ½ΠΈΡ
ΠΌΠ΅ΠΌΠ±ΡΠ°Π½ ΡΠΊ ΡΡΡΠ»ΠΈΠ²ΠΈΡ
Π΅Π»Π΅ΠΌΠ΅Π½ΡΡΠ². ΠΠΈΡΠΎΠΊΠ° ΡΠ΅Π»Π΅ΠΊΡΠΈΠ²Π½ΡΡΡΡ, ΡΡΡΠ»ΠΈΠ²ΡΡΡΡ, Π½ΠΈΠ·ΡΠΊΠ° ΡΡΠ½Π°, ΠΏΡΠΎΡΡΠΎΡΠ° ΡΠ° Π΅ΠΊΡΠΏΡΠ΅ΡΠ½ΡΡΡΡ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½Π½Ρ ΡΡΠ·Π½ΠΎΠΌΠ°Π½ΡΡΠ½ΠΈΡ
ΡΠ΅ΡΠΎΠ²ΠΈΠ½ ΡΠΎΠ±Π»ΡΡΡ Π±ΡΠΎΡΠ΅Π½ΡΠΎΡΠΈ Π½Π΅ΠΎΠ±Ρ
ΡΠ΄Π½ΠΈΠΌΠΈ Π΄Π»Ρ ΠΏΠΎΡΡΠ΅Π± ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΠΈ, Π±ΡΠΎΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΡΡ, Π΅ΠΊΠΎΠ»ΠΎΠ³ΠΈ, ΡΡΠ»ΡΡΡΠΊΠΎΠ³ΠΎ Π³ΠΎΡΠΏΠΎΠ΄Π°ΡΡΡΠ²Π° ΡΠ° Ρ
Π°ΡΡΠΎΠ²ΠΎΡ ΠΏΡΠΎΠΌΠΈΡΠ»ΠΎΠ²ΠΎΡΡΡ. ΠΡΠΈ Π°Π½Π°Π»ΡΠ·Ρ ΡΠ΅Π°Π»ΡΠ½ΠΈΡ
Π·ΡΠ°Π·ΠΊΡΠ² Π½Π΅ΡΠΏΠ΅ΡΠΈΡΡΡΠ½ΠΈΠΉ Π²ΠΏΠ»ΠΈΠ² ΡΠΎΠ½ΠΎΠ²ΠΈΡ
Π΅Π»Π΅ΠΊΡΡΠΎΠ»ΡΡΡΠ² ΠΌΠΎΠΆΠ½Π° ΡΡΡΡΡΠ²ΠΎ Π·ΠΌΠ΅Π½ΡΠΈΡΠΈ Π·Π°Π²Π΄ΡΠΊΠΈ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ Π΄ΠΈΡΠ΅ΡΠ΅Π½ΡΡΠΉΠ½ΠΎΠ³ΠΎ ΡΠ΅ΠΆΠΈΠΌΡ Π²ΠΈΠΌΡΡΡΠ²Π°Π½Ρ, Π±ΡΠ»ΡΡ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠΎΠ²Π°Π½ΠΈΡ
Π±ΡΡΠ΅ΡΠ½ΠΈΡ
ΡΠΎΠ·ΡΠΈΠ½ΡΠ², Π° ΡΠ°ΠΊΠΎΠΆ Π΄ΠΎΠ΄Π°ΡΠΊΠΎΠ²ΠΈΡ
Π½Π΅Π³Π°ΡΠΈΠ²Π½ΠΎ ΡΠΈ ΠΏΠΎΠ·ΠΈΡΠΈΠ²Π½ΠΎ Π·Π°ΡΡΠ΄ΠΆΠ΅Π½ΠΈΡ
ΠΌΠ΅ΠΌΠ±ΡΠ°Π½, ΡΠΊΡ Π·Π°ΠΏΠΎΠ±ΡΠ³Π°ΡΡΡ Π²ΠΏΠ»ΠΈΠ²ΠΎΠ²Ρ Π±ΡΡΠ΅ΡΠ½ΠΎΡ ΡΠΌΠ½ΠΎΡΡΡ ΡΠ° ΡΠΎΠ½Π½ΠΎΡ ΡΠΈΠ»ΠΈ ΡΠΎΠ·ΡΠΈΠ½ΡΠ² Ρ ΡΠΎΠ·ΡΠΈΡΡΡΡΡ Π΄ΠΈΠ½Π°ΠΌΡΡΠ½ΠΈΠΉ Π΄ΡΠ°ΠΏΠ°Π·ΠΎΠ½ ΡΠΎΠ±ΠΎΡΠΈ ΡΠ΅Π½ΡΠΎΡΡΠ². ΠΠ»Ρ ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ ΠΌΡΠ½ΡΠ°ΡΡΡΠ½ΠΈΡ
ΡΠΌΡΠ½ΠΎΡΠ΅Π½ΡΠΎΡΡΠ² Π±ΡΠ»ΠΎ Π·Π°ΠΏΡΠΎΠΏΠΎΠ½ΠΎΠ²Π°Π½ΠΎ ΡΠ°ΠΊΡ ΠΏΡΠ΄Ρ
ΠΎΠ΄ΠΈ: Π°) Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ ΠΏΠΎΠ»ΡΠ°Π½ΡΠ»ΡΠ½Ρ ΡΠΊ Π΅Π»Π΅ΠΊΡΡΠΎΠΏΡΠΎΠ²ΡΠ΄Π½ΠΎΡ ΠΌΡΡΠΊΠΈ ΠΏΡΠΈ Π²ΠΈΠ· Π½Π°ΡΠ΅ ΠΏΠ½Ρ Π°Π½ΡΠΈΡΡΠ» Ρ ΠΊΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½ΠΎΠΌΡ ΡΠΌΡΠ½ΠΎΠ°Π½Π°Π»ΡΠ·Ρ: Π±) ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ Π±Π°Π³Π°ΡΠΎΡΠ°ΡΠΎΠ²ΠΈΡ
ΡΡΡΡΠΊΡΡΡ Π· ΠΏΠ»ΡΠ²ΠΊΠ°ΠΌΠΈ ΡΡΠ°Π»ΠΎΡΡΠ°Π½ΡΠ½Ρ; Π²) Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ Π°ΠΊΡΠΈΠ»ΠΎΠ²ΠΈΡ
ΡΠΎΠΏΠΎΠ»ΡΠΌΠ΅ΡΠ½ΠΈΡ
ΠΌΠ΅ΠΌΠ±ΡΠ°Π½. ΠΠ±Π³ΠΎΠ²ΠΎΡΠ΅Π½ΠΎ ΠΏΠ΅ΡΠ΅Π²Π°Π³ΠΈ ΡΠ° Π½Π΅Π΄ΠΎΠ»ΡΠΊΠΈ ΡΠΎΠ·ΡΠΎΠ±Π»Π΅Π½ΠΈΡ
ΠΊΠΎΠ½Π΄ΡΠΊΡΠΎΠΌΠ΅ΡΡΠΈΡΠ½ΠΈΡ
Π±ΡΠΎΡΠ΅Π½ΡΠΎΡΡΠ². ΠΠΎΠ΄Π°Π»ΡΡΠ° ΠΊΠΎΠΌΠ΅ΡΡΡΠ°Π»ΡΠ·Π°ΡΡΡ ΡΠ°ΠΊΠΈΡ
ΠΏΡΠΈΠ»Π°Π΄ΡΠ² ΠΏΠΎΠ²'ΡΠ·Π°Π½Π° Π· ΠΏΠΎΡΡΠΊΠΎΠΌ ΡΠ»ΡΡ
ΡΠ² ΡΡΠ°Π±ΡΠ»ΡΠ·Π°ΡΡΡ ΡΡΡΠ»ΠΈΠ²ΠΈΡ
ΠΌΠ΅ΠΌΠ±ΡΠ°Π½ ΡΠ° ΡΡΠΌΡΡΠ΅Π½Π½Ρ ΡΠΎΠ½ΠΊΠΎΠΏΠ»ΡΠ²ΠΊΠΎΠ²ΠΈΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΡΠΉ Π· Π½Π°Π½Π΅ΡΠ΅Π½Π½ΡΠΌ ΠΌΠ΅ΠΌΠ±ΡΠ°Π½ Ρ ΡΠ΄ΠΈΠ½ΠΎΠΌΡ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΡΡΠ½ΠΎΠΌΡ ΡΠΈΠΊΠ»Ρ.ΠΠ±Π·ΠΎΡ ΠΏΠΎΡΠ²ΡΡΠ΅Π½ Π°Π½Π°Π»ΠΈΠ·Ρ ΡΠΎΠ±ΡΡΠ²Π΅Π½Π½ΡΡ
ΡΠ°Π±ΠΎΡ ΠΏΠΎ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ΅ ΠΎΠΊΠΎΠ»ΠΎ 20 ΠΊΠΎΠ½Π΄ΡΠΊΡΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π±ΠΈΠΎΡΠ΅Π½ΡΠΎΡΠΎΠ² Π½Π°. ΠΎΡΠ½ΠΎΠ²Π΅ ΠΏΠ»Π°Π½Π°ΡΠ½ΡΡ
ΡΠ»Π΅ΠΊΡΡΠΎΠ΄ΠΎΠ² ΠΈ ΡΠ°Π·Π»ΠΈΡΠ½ΠΎΠ³ΠΎ Π±ΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Π°, (ΡΠ΅ΡΠΌΠ΅Π½ΡΡ, ΠΊΠ»Π΅ΡΠΊΠΈ, Π°Π½ΡΠΈΡΠ΅Π»Π°) ΠΈ ΡΠΈΠ½ΡΠ΅ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΠΌΠ±ΡΠ°Π½ ΠΎ ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΡΠ»Π΅ΠΌΠ΅Π½ΡΠΎΠ². ΠΡΡΠΎΠΊΠ°Ρ ΡΠ΅Π»Π΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ, ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΡ, Π΄Π΅ΡΠ΅Π²ΠΈΠ·Π½Π°, ΠΏΡΠΎΡΡΠΎΡΠ° ΠΈ Π±ΡΡΡΡΠΎΡΠ° ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
Π²Π΅ΡΠ΅ΡΡΠ² Π΄Π΅Π»Π°ΡΡ Π±ΠΈΠΎΡΠ΅Π½ΡΠΎΡΡ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΡΠΌΠΈ Π² ΠΌΠ΅Π΄ΠΈΡΠΈΠ½Π΅, Π±ΠΈΠΎΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΡΠΊΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΡΠ΅Π»ΡΡΠΊΠΎΠΌ Ρ
ΠΎΠ·ΡΠΉΡΡΠ²Π΅ ΠΈ ΠΏΠΈΡΠ΅Π²ΠΎΠΉ ΠΏΡΠΎΠΌΡΡΠ»Π΅Π½Π½ΠΎΡΡΠΈ. ΠΡΠΈ Π°Π½Π°Π»ΠΈΠ·Π΅ ΡΠ΅Π°Π»ΡΠ½ΡΡ
ΠΎΠ±ΡΠ°Π·ΡΠΎΠ² Π½Π΅ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠΎΠ½ΠΎΠ²ΡΡ
ΡΠ»Π΅ΠΊΡΡΠΎΠ»ΠΈΡΠΎΠ² ΠΌΠΎΠΆΠ½ΠΎ ΡΡΡΡΠ°Π½ΠΈΡΡ Π±Π»Π°Π³ΠΎΠ΄Π°ΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π΄ΠΈΡΡΠ΅ΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠ΅ΠΆΠΈΠΌΠ° ΠΈΠ·ΠΌΠ΅ΡΠ΅Π½ΠΈΠΉ, Π±ΠΎΠ»Π΅Π΅ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π±ΡΡΠ΅ΡΠ½ΡΡ
ΡΠ°ΡΡΠ²ΠΎΡΠΎΠ², Π° ΡΠ°ΠΊΠΆΠ΅ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΎΡΡΠΈΡΠ°ΡΠ΅Π»ΡΠ½ΠΎ ΠΈΠ»ΠΈ ΠΏΠΎΠ»ΠΎΠΆΠΈΡΠ΅Π»ΡΠ½ΠΎ Π·Π°ΡΡΠΆΠ΅Π½Π½ΡΡ
ΠΌΠ΅ΠΌΠ±ΡΠ°Π½, ΡΠΌΠ΅Π½ΡΡΠ°ΡΡΠΈΡ
Π²Π»ΠΈΡΠ½ΠΈΠ΅ Π±ΡΡΠ΅ΡΠ½ΠΎΠΉ Π΅ΠΌΠΊΠΎΡΡΠΈ ΠΈ ΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΈΠ»Ρ ΡΠ°ΡΡΠ²ΠΎΡΠΎΠ² ΠΈ ΡΠ°ΡΡΠΈΡΡΡΡΠΈΡ
Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΈΠΉ Π΄ΠΈΠ°ΠΏΠ°Π·ΠΎΠ½ ΡΠ°Π±ΠΎΡΡ ΡΠ΅Π½ΡΠΎΡΠΎΠ². ΠΠ»Ρ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΠΌΠΈΠ½ΠΈΠ°ΡΡΡΠ½ΡΡ
ΠΈΠΌΠΌΡΠ½ΠΎΡΠ΅Π½ΡΠΎΡΠΎΠ² ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Ρ ΡΠ»Π΅Π΄ΡΡΡΠΈΠ΅ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ: Π°) ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΠΎΠ»ΠΈΠ°Π½ΠΈΠ»ΠΈΠ½Π° ΠΊΠ°ΠΊ ΡΠ»Π΅ΠΊΡΡΠΎΠΏΡΠΎΠ²ΠΎΠ΄ΡΡΠ΅ΠΉ ΠΌΠ΅ΡΠΊΠΈ ΠΏΡΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠΈ Π°Π½ΡΠΈΡΠ΅Π» Π² ΠΊΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½ΠΎΠΌ ΠΈΠΌΠΌΡΠ½ΠΎΠ°Π½Π°Π»ΠΈΠ·Π΅; Π±) ΡΠΎΠ·Π΄Π°Π½ΠΈΠ΅ ΠΌΠ½ΠΎΠ³ΠΎΡΠ»ΠΎΠΉΠ½ΡΡ
ΡΡΡΡΠΊΡΡΡ Ρ ΠΏΠ»Π΅Π½ΠΊΠ°ΠΌΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΡΡΠ°Π»ΠΎΡΠΈΠ°Π½ΠΈΠ½Π°; Π²) ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π°ΠΊΡΠΈΠ»ΠΎΠ²ΡΡ
ΡΠΎ ΠΏΠΎΠ»ΠΈΠΌΠ΅ΡΠ½ΡΡ
ΠΌΠ΅ΠΌΠ±ΡΠ°Π½. ΠΠ±ΡΡΠΆΠ΄Π΅Π½Ρ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π° ΠΈ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΊΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΡΡ
ΠΊΠΎΠ½Π΄ΡΠΊΡΠΎΠΌΠ΅ΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π±ΠΈΠΎΡΠ΅Π½ΡΠΎΡΠΎΠ². ΠΠ°Π»ΡΠ½Π΅ΠΉΡΠ°Ρ ΠΊΠΎΠΌΠΌΠ΅ΡΡΠΈΠ°Π»ΠΈΠ·Π°ΡΠΈΡ, ΡΠ°ΠΊΠΈΡ
ΠΏΡΠΈΠ±ΠΎΡΠΎΠ² ΡΠ²ΡΠ·Π°Π½Π° Ρ ΠΏΠΎΠΈΡΠΊΠΎΠΌ ΠΏΡΡΠ΅ΠΉ ΡΡΠ°Π±ΠΈΠ»ΠΈΠ·Π°ΡΠΈΠΈ ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΌΠ΅ΠΌΠ±ΡΠ°Π½ ΠΈ ΡΠΎΠ²ΠΌΠ΅ΡΠ΅Π½ΠΈΡ, ΡΠΎΠ½ΠΊΠΎΠΏΠ»Π΅Π½ΠΎΡΠ½ΠΎΠΉ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ Ρ Π½Π°Π½Π΅ΡΠ΅Π½ΠΈΠ΅ΠΌ ΠΌΠ΅ΠΌΠ±ΡΠ°Π½ Π² Π΅Π΄ΠΈΠ½ΠΎΠΌ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΌ ΡΠΈΠΊΠ»Π΅
TomograPy: A Fast, Instrument-Independent, Solar Tomography Software
Solar tomography has progressed rapidly in recent years thanks to the
development of robust algorithms and the availability of more powerful
computers. It can today provide crucial insights in solving issues related to
the line-of-sight integration present in the data of solar imagers and
coronagraphs. However, there remain challenges such as the increase of the
available volume of data, the handling of the temporal evolution of the
observed structures, and the heterogeneity of the data in multi-spacecraft
studies.
We present a generic software package that can perform fast tomographic
inversions that scales linearly with the number of measurements, linearly with
the length of the reconstruction cube (and not the number of voxels) and
linearly with the number of cores and can use data from different sources and
with a variety of physical models: TomograPy
(http://nbarbey.github.com/TomograPy/), an open-source software freely
available on the Python Package Index. For performance, TomograPy uses a
parallelized-projection algorithm. It relies on the World Coordinate System
standard to manage various data sources. A variety of inversion algorithms are
provided to perform the tomographic-map estimation. A test suite is provided
along with the code to ensure software quality. Since it makes use of the
Siddon algorithm it is restricted to rectangular parallelepiped voxels but the
spherical geometry of the corona can be handled through proper use of priors.
We describe the main features of the code and show three practical examples
of multi-spacecraft tomographic inversions using STEREO/EUVI and STEREO/COR1
data. Static and smoothly varying temporal evolution models are presented.Comment: 21 pages, 6 figures, 5 table
Primary CR energy spectrum and mass composition by the data of Tunka-133 array
The Cherenkov light array for the registration of extensive air showers (EAS) Tunka-133 collected data during 5 winter seasons from 2009 to 2014. The differential energy spectrum of all particles and the dependence of the average maximum depth on the energy in the range of 6 β
1015β1018βeV measured for 1540 hours of observation are presented
Pioneering space based detector for study of cosmic rays beyond GZK Limit
Space-based detectors for study of extreme energy cosmic rays (EECR) are being prepared as promising new direction of EECR study. Pioneering space device β tracking ultraviolet set up (TUS) is at the last stage of its construction and testing. TUS detector description is presented
Pioneering space based detector for study of cosmic rays beyond GZK Limit
Space-based detectors for study of extreme energy cosmic rays (EECR) are being prepared as promising new direction of EECR study. Pioneering space device β tracking ultraviolet set up (TUS) is at the last stage of its construction and testing. TUS detector description is presented
- β¦