scholarly journals Ап-конверсия инфракрасного излучения в щелочно-земельных фторидах, активированных Er-=SUP=-3+-=/SUP=-

2020 ◽  
Vol 128 (11) ◽  
pp. 1621
Author(s):  
Е.А. Раджабов ◽  
Р.Ю. Шендрик
Keyword(s):  
Luminescence Spectrum ◽  
Upconversion Luminescence ◽  
Laser Diodes ◽  
Energy Yield

Upconversion processes were studied in MeF2-ErF3 crystals (Me - Ca, Sr, Ba) in the range of ErF3 concentrations from 0.01 to 10 mol% when excited in infrared bands of the Er3 + ion by laser diodes of 808, 978, 1542 nm. Upon excitation of 1542 nm, the 4I11/2-4I15/2 band at 990 nm predominates in the luminescence spectrum of MeF2-Er; the fraction of visible bands is less than 0.1. The energy yield of the upconversion luminescence MeF2-10% ErF3 upon excitation of 1542 nm with a density of about 1 W/cm2 is in the range of 14-26%.

scholarly journals Modulation of upconversion luminescence spectrum of single rare-earth-doped upconversion nanocrystal based on plasmonic nanocavity

2022 ◽  
Vol 71 (2) ◽  
pp. 027801-027801
Author(s):  
Meng Yong-Jun ◽  
◽  
Li Hong ◽  
Tang Jian-Wei ◽  
Chen Xue-Wen
Keyword(s):  
Rare Earth ◽  
Luminescence Spectrum ◽  
Upconversion Luminescence ◽  
Rare Earth Doped

scholarly journals Характеристики апконверсионной люминесценции порошков CaF-=SUB=-2-=/SUB=- : Er при возбуждении лазерным излучением с длиной волны 1.5 μm

2020 ◽  
Vol 128 (2) ◽  
pp. 204
Author(s):  
А.А. Ляпин ◽  
П.А. Рябочкина ◽  
С.В. Гущин ◽  
М.Н. Жарков ◽  
А.С. Ермаков ◽  
...  
Keyword(s):  
Laser Radiation ◽  
Upconversion Luminescence ◽  
Energy Yield ◽  
Yield Values ◽  
Spectral Ranges

The characteristics of upconversion luminescence of CaF2:Er crystalline powders were investigated upon excitation of Er3+ ions to the 4I13/2 level by laser radiation at 1531.8 nm. The energy yield values of upconversion luminescence were determined for the spectral ranges 380–780 and 380–1100 nm. It was found that upconversion luminescence of CaF2:Er powders with concentrations of 0.5, 2, 4, 6, 8, 10, 11, 13, 15, and 17% of Er3+ ions is characterized by correlated color temperatures of about 5100, 2142, 1726, 1738, 1773, 1757, 1762, 1765, 1735, and 1714 K, respectively.

Optimizing genotype-environment-management interactions to ensure silage maize production in the Chinese Maize Belt

2020 ◽  
Vol 80 (2) ◽  
pp. 133-146
Author(s):  
L Zhang ◽  
Z Zhang ◽  
J Cao ◽  
Y Luo ◽  
Z Li
Keyword(s):  
Field Experiments ◽  
Weather Conditions ◽  
Growth Cycle ◽  
High Energy ◽  
Risk Level ◽  
Energy Yield ◽  
Maize Production ◽  
Early Date ◽  
Environment Management ◽  
Silage Maize

Grain maize production exceeds the demand for grain maize in China. Methods for harvesting good-quality silage maize urgently need a theoretical basis and reference data in order to ensure its benefits to farmers. However, research on silage maize is limited, and very few studies have focused on its energetic value and quality. Here, we calibrated the CERES-Maize model for 24 cultivars with 93 field experiments and then performed a long-term (1980-2017) simulation to optimize genotype-environment-management (G-E-M) interactions in the 4 main agroecological zones across China. We found that CERES-Maize could reproduce the growth and development of maize well under various management and weather conditions with a phenology bias of <5 d and biomass relative root mean square error values of <5%. The simulated results showed that sowing long-growth-cycle cultivars approximately 10 d in advance could yield good-quality silage. The optimal sowing dates (from late May to July) and harvest dates (from early October to mid-November) gradually became later from north to south. A high-energy yield was expected when sowing at an early date and/or with late-maturing cultivars. We found that Northeast China and the North China Plain were potential silage maize growing areas, although these areas experienced a medium or even high frost risk. Southwestern maize experienced a low risk level, but the low soil fertility limited the attainable yield. The results of this paper provide information for designing an optimal G×E×M strategy to ensure silage maize production in the Chinese Maize Belt.

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