| 1. |
- Davies, Stuart J., et al.
(författare)
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ForestGEO: Understanding forest diversity and dynamics through a global observatory network
- 2021
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Ingår i: Biological Conservation. - : Elsevier BV. - 0006-3207. ; 253
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Tidskriftsartikel (refereegranskat)abstract
- ForestGEO is a network of scientists and long-term forest dynamics plots (FDPs) spanning the Earth's major forest types. ForestGEO's mission is to advance understanding of the diversity and dynamics of forests and to strengthen global capacity for forest science research. ForestGEO is unique among forest plot networks in its large-scale plot dimensions, censusing of all stems ≥1 cm in diameter, inclusion of tropical, temperate and boreal forests, and investigation of additional biotic (e.g., arthropods) and abiotic (e.g., soils) drivers, which together provide a holistic view of forest functioning. The 71 FDPs in 27 countries include approximately 7.33 million living trees and about 12,000 species, representing 20% of the world's known tree diversity. With >1300 published papers, ForestGEO researchers have made significant contributions in two fundamental areas: species coexistence and diversity, and ecosystem functioning. Specifically, defining the major biotic and abiotic controls on the distribution and coexistence of species and functional types and on variation in species' demography has led to improved understanding of how the multiple dimensions of forest diversity are structured across space and time and how this diversity relates to the processes controlling the role of forests in the Earth system. Nevertheless, knowledge gaps remain that impede our ability to predict how forest diversity and function will respond to climate change and other stressors. Meeting these global research challenges requires major advances in standardizing taxonomy of tropical species, resolving the main drivers of forest dynamics, and integrating plot-based ground and remote sensing observations to scale up estimates of forest diversity and function, coupled with improved predictive models. However, they cannot be met without greater financial commitment to sustain the long-term research of ForestGEO and other forest plot networks, greatly expanded scientific capacity across the world's forested nations, and increased collaboration and integration among research networks and disciplines addressing forest science.
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| 2. |
- Wang, Yong, et al.
(författare)
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Characterization and formation mechanism of non-metallic inclusions in single bcc-phase high entropy alloy
- 2023
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Ingår i: Materials Characterization. - : Elsevier BV. - 1044-5803 .- 1873-4189. ; 205
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Tidskriftsartikel (refereegranskat)abstract
- This work aims to provide a fundamental study of inclusion characteristics in the single bcc-phase high entropy alloy (HEA), Mn-rich and Al-contained multicomponent system (Al-Cr-Mn-Fe-Co-Ni) was selected as the prototype alloy in this study. According to the differential thermal analysis (DTA) measurements, the solidus (TS) and liquidus (TL) temperatures of this alloy were in the range of 1225–1228 °C (1226 ± 2 °C) and 1268–1271 °C (1270 ± 2 °C), respectively. Non-metallic inclusions were investigated in a two-dimensional (2D) cross-section method as well as extracted by a three-dimensional (3D) electrolytic extraction method. It was found that AlN was the dominant inclusion phase, also a small amount of Al2O3 inclusions were observed. They formed in the liquid alloy and mostly presented as Al2O3-AlN agglomerates, where the size range of the AlN inclusions was larger than that of Al2O3. The theoretical calculation showed that AlN inclusion has a higher coagulation coefficient and collision rate than those of Al2O3 inclusions, which agrees well with the experimental observations. The inclusion characteristics of Al2O3 and AlN were closely related to the relative contents of O and N in the presence of high Al content in the alloy. The impurity elements of N and O were the key issues in controling the stable inclusion phase in high entropic alloy.
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| 3. |
- Wang, Yong, et al.
(författare)
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Effect of ferrochromium (FeCr) and ferroniobium (FeNb) alloys on inclusion and precipitate characteristics in austenitic stainless steels
- 2023
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Ingår i: Journal of Materials Research and Technology. - : Elsevier BV. - 2238-7854. ; 25, s. 4989-5002
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Tidskriftsartikel (refereegranskat)abstract
- Lab-scale alloying experiments were carried out by first adding commercial low-carbon ferrochrome (LCFeCr) alloys and then adding ferroniobium (FeNb) alloys in 316-grade austenitic stainless steel in this study. The inclusion and precipitation characteristics in LCFeCr and FeNb were evaluated as well as in a 316 austenitic stainless steel after the alloy additions by using two- and three-dimensional characterization methods in combination with thermodynamic calculations. The results showed that MnCr2O4 spinels and pure Al2O3 were the main types of inclusions in LCFeCr alloys, while pure TiOx, Al2O3 inclusions and complex TiOx-Al2O3 aggregates were mainly found in FeNb alloys. After the addition of LCFeCr alloy to the steel, the SiO2 contents in liquid inclusions decreased to some extent, while more inclusions containing higher MnO contents were observed. Some MnCr2O4 spinel inclusions can be reduced by Si in steel and form liquid inclusions. Some MnCr2O4 spinel and Al2O3 inclusions from LCFeCr alloy can remain in the steel melt, which decreased the steel cleanliness. After the addition of FeNb alloy, pure TiOx inclusions present in this alloy can hardly be found in the steel melt. The inclusion types in steel were not changed so much but high Nb-containing phases were found around the inclusions and coarse Laves phases were formed in the matrix. Overall, this work aims to understand the impurity particle behavior during the alloying process when using ferroalloys to produce high-performance stainless steels.
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| 4. |
- Wang, Yong, et al.
(författare)
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Estimation of the probable maximum size of inclusions using statistics of extreme values and particle size distribution methods
- 2022
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Ingår i: JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T. - : Elsevier BV. - 2238-7854. ; 20, s. 2454-2465
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Tidskriftsartikel (refereegranskat)abstract
- Prediction of the maximum size of inclusion in a large weight of steel using data from a small volume steel sample is an important topic for steelmakers. Therefore, the probable maximum sizes (PMS) of inclusions in three steel grades were evaluated by the statistics of extreme values (SEV) and the particle size distributions (PSD) methods based on three-dimensional (3D) investigations of inclusions using the electrolytic extraction (EE) method. The effect of number of measurements and size of unit area on the PMS of in-clusions were investigated. The results showed that at least 80 measurements of NMIs should be done in the SEV method, while in the PSD method the number of measurements has little influence when the number of inclusions in the observed areas was large enough. The effect of unit area size on the PMS of inclusions in the SEV method can be ignored for small-sized inclusions (less than 10 mm). The PMS of inclusions determined from the SEV method agreed with that from the PSD method by considering the 95% confidence interval. The SEV method was preferred when predicting the PMS of inclusions because of its simplicity by reducing the cost and labour involved compared to the PSD method.
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