Core-shell Fe@Fex_xOy_y nanoring system: A versatile platform for biomedical applications

Iron oxide (maghemite and magnetite) nanoparticles are the most commonly used magnetic materials in nanomedicine because of their high biocompatibility. However, their low saturation magnetization (60–90 emu/g) limits their applicability. Here, we report a new core–shell (Fe@Fe$_x$O$_y$) nanoring system, which combines the high magnetic saturation of a metallic iron core (220 emu/g) and the biocompatibility of an iron oxide shell. To produce these nanostructures, hematite (α-Fe$_2$O$_3$) nanorings were annealed in a H$_2$ gas atmosphere for different periods to optimize the amount of metallic iron percentage (δ) in the system. Thus, nanostructures with different magnetic saturation (97 to 178 emu/g) could be obtained; based on their metallic iron content, these particles are labeled as Vortex Iron oxide Particle δ (VIPδ). Micromagnetic simulations confirmed that the VIPδ nanorings exhibit a vortex configuration, guaranteeing low remanence and coercitivity. Moreover, the system shows good biocompatibility in various assays as determined through cell viability measurements performed using two different human cell lines, which were exposed to VIP78% for 24 h. Therefore, VIPδ nanorings combine a magnetic vortex state and biocompatibility with their high magnetic saturation and can thus serve as a platform that can be tuned during the synthesis based on desired biomedical application

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Role of the metal-support interface in the hydrodeoxygenation reaction of phenol

In this work, the effect of interfacial sites between Pd particles and Nb2O5 species is investigated by testing a series of Pd-Nb2O5/SiO2 catalysts with different niobium loadings for the HDO reaction of phenol in the gas phase. Important differences in the selectivity to deoxygenated product were observed depending on the presence of niobium oxide close to Pd particles, which reveals the key role of the type of active phase in the control of reaction steps. It was found that Pd/SiO2 catalyst promotes hydrogenation pathways, producing cyclohex-anone as the major product. For Pd-Nb2O5/SiO2 catalyst containing a Nb/Pd molar ratio of 0.5, a sharp increase in the selectivity to benzene is observed (7.5-fold). Increasing the Nb/Pd molar ratio, the formation of benzene is enhanced. The results showed that the Pd-Nb2O5 interface, composed by an oxophilic oxide in the perimeter of the metal particle, is responsible for the activation of the C-O bond, promoting the deoxygenation reaction.Peer reviewe

Controlling carbon formation over Ni/CeO2 catalyst for dry reforming of CH4 by tuning Ni crystallite size and oxygen vacancies of the support

International audienceThis work investigates the effect of Ni crystallite size and oxygen vacancies of the support on the formation of carbon over Ni/CeO2 catalysts for dry reforming of methane at 1073 K. A large crystallite size variation is achieved by using different Ni loading (5 and 10 wt%) and calcination temperatures (673, 873, 1073 and 1473 K). In situ XRD and XANES experiments reveal that the increase in calcination temperature increases the Ni crystallite size, whereas the amount of oxygen vacancies decreases. The amount of carbon formed during DRM increases as Ni crystallite size increases, achieving a maximum at around 20−30 nm and then, it continuously decreases. However, carbon deposition is negligeable below 10 nm and above 100 nm. For the catalysts with very large Ni crystallite sizes, the CH4 dissociation rate is likely so low that carbon species formed reacts and carbon accumulation does not take place. However, the oxygen vacancies of ceria do not contribute to the carbon removal from the Ni surface due to the low metal-support interface on these large Ni particles

Hydrodeoxygenation of Lignin-Derived Compound Mixtures on Pd-Supported on Various Oxides

International audienceAs a plethora of different unsaturated oxygenates is produced from the pyrolysis of biomass into bio-oil, understanding the role of competitive adsorption in catalytic upgrading is essential. To this end, the relative reactivities of representative molecules of key families within a single feed mixture were examined through reaction testing and in situ infrared spectroscopy characterization. The influence of the support (silica, ceria, zirconia, titania, and niobia) on the rate of elimination of hydroxyl and methoxy groups was evaluated on single compounds (phenol, m-cresol, and anisole) and binary mixtures (phenol/anisole and m-cresol/anisole). The removal of hydroxyl groups depends significantly on the support type. Pd supported on SiO2 and CeO2 favored ring hydrogenation resulting in the production of oxygenated products such as cyclohexanone/3-methylacylohexanone. The use of ZrO2, TiO2, and Nb2O5 as supports promotes the formation of benzene/toluene by hydrogenation of the carbonyl group of the tautomer intermediate formed or even direct deoxygenation. The reaction pathways for removal of methoxy groups also depend on the support. The demethylation route that yields methane and phenol and its further deoxygenation to benzene is proposed to take place over all catalysts, except on Pd/Nb2O5. Due to the superior oxophilicity of Nb cations, the niobia-supported catalyst greatly favors the direct deoxygenation, with formation of benzene and methanol (demethoxylation). The reaction with binary mixtures of phenol/anisole and m-cresol/anisole revealed that the hydroxyl groups react preferentially. Insight into the mode and strength of adsorption of the different molecules on the catalyst surface was obtained by DRIFTS analysis upon adsorption and desorption. The results indicate that under the HDO reaction conditions investigated phenol and m-cresol seem to adsorb more strongly on the catalyst surface and react more readily than anisole. Thus, this study shows that competitive adsorption is a predominant factor impacting product selectivity