Thermal properties of cubic KTa 1 x Nb x O 3 crystals

Cubic potassium tantalite niobate KTa1−xNbxO3 KTN crystals of large size, good quality, and varying Nb concentration have been grown by the Czochralski method and their thermal properties have been systematically studied. The melting point, molar enthalpy of fusion, and molar entropy of fusion of the crystals were determined to be: 1536.9 K, 12 068.521 J mol−1, and 7.85 J K−1 mol−1 for KTa0.67Nb0.33O3; and 1520.61 K, 15 352.511 J mol−1, and 10.098 J K−1 mol−1 for KTa0.67Nb0.33O3, respectively. Based on the data, the Jackson factor was calculated to be 0.994f and 1.214f for KTa0.67Nb0.33O3 and KTa0.63Nb0.37O3, respectively. The thermal expansion coefficients over the temperature range of 298.15−773.15 K are: =4.0268 10−6 /K, 6.4428 10−6 /K, 6.5853 10−6 /K for KTaO3, KTa0.67Nb0.33O3, and KTa0.63Nb0.37O3, respectively. The density follows an almost linear decrease when the temperature increases=from 298.15 to 773.15 K. The measured specific heats at 303.15 K are: 0.375 J g−1 K−1 for KTaO3; 0.421 J g−1 K−1 for KTa0.67Nb0.33O3, and 0.430 J g−1 K−1 for KTa0.63Nb0.37O3 The thermal diffusion coefficients of the crystals were measured over the temperature range from 303.15−563.15 K. The calculated thermal conductivity values of KTaO3, KTa0.67Nb0.33O3, and KTa0.63Nb0.37O3 at 303.15 K are 8.551, 5.592, and 4.489 W m−1 K−1, respectively. The variation of these thermal properties versus Nb concentration is qualitatively analyzed. These results show that crystalline KTN is a promising material for optical applications

Growth and thermal properties of Sr W O 4 single crystal

A strontium tungstate SrWO4 single crystal with dimensions of 25 40 mm2 has been grown by the Czochralski method using an iridium crucible. X-ray powder diffraction results show that as grown the SrWO4 crystal belongs to the tetragonal system in the scheelite structure. The effective segregation coefficients of elemental W and Sr in the crystal growth are measured by x-ray fluorescence, and the respective values are close to 1. The thermal properties of the SrWO4 crystal were systemically studied by measuring the thermal expansion, specific heat, and thermal diffusion coefficient. These results show that the crystal possesses a large anisotropic thermal expansion with thermal-expansion coefficients a=8.61 10−6/K, b=8.74 10−6/K, c=18.78 10−6 /K over the temperature range of 303.15–773.15 K. The measured value of the specific heat is 0.30–0.34 J g−1 K−1 when the temperature is increased from 323.15 to 1073.15 K. The thermal diffusion coefficient was measured over the temperature range of 303.15–543.15 K. The thermal conductivities of the SrWO4 crystal along the 100 and 001 directions are calculated to be 3.1326 W m−1 K−1 and 2.9477 W m−1 K−1, respectively, at 303.15 K. Then the thermal properties of some other Raman crystals were compared with these data, and the thermal focal lengths for these crystals were also estimated

Anisotropic thermal expansion of monoclinic potassium lutetium tungstate single crystals

The anisotropic thermal expansion of a single crystal of KLu WO4 2 KLuW , obtained by the top-seeded solution growth method, has been investigated over a wide temperature range 50– 600 °C . The linear thermal-expansion tensor has been determined and its principal X, Y, and Z axes are in the 705 , 010 , and 107 crystallographic directions, respectively. The principal thermal-expansion coefficients I, II, and III are 12.8 10−6, 7.8 10−6, and 22.2 10−6 K−1, respectively. The principal axis with maximum thermal expansion Z with III=22.2 10−6 is located at 10.37° from the c axis. In comparison with KGd WO4 2 and KYb WO4 2, the thermal-expansion anisotropy of KLuW is weaker and therefore optical-quality crystals are easier to obtain than with KGdW and KYbW from a thermal-expansion standpoint

Thermal and mechanical properties of BaWO4 crystal

A large single crystal of barium tungstate BaWO4 with dimensions of 22- mm diameter 80-mm length was grown by the Czochralski method using an iridium crucible. The melting point, molar enthalpy of fusion, and molar entropy of fusion of the crystal were determined to be 1775.10 K, 96 913.80 J mol−1, and 54.60 J K−1 mol−1, respectively. The average linear thermal-expansion coefficients are a=10.9526 10−6/K, b=10.8069 10−6 /K, and c =35.1063 10−6 /K in the temperature range from 303.15 to 1423.15 K along the three respective crystallographic axes. The density of the crystal follows an almost linear decrease from 6.393 103 to 6.000 103 kg m−3 when the temperature is increased from 303.15 to 1423.15 K. The measured specific heat are 115.56–130.96 J K−1 mol−1 in the temperature range of 323.15–1173.15 K. The thermal diffusion coefficient of the crystal was measured in the temperature range of 297.15–563.15 K. The calculated thermal conductivity is 2.256 W m−1 K−1 along the 001 direction and 2.324 W m−1 K−1 along the 100 direction at 323.15 K. The microhardness of the BaWO4 single crystal in the 001 and 100 planes is 1393 and 1814 MPa under a load of 0.050 kg

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives