Detection of Damage in Operating Wind Turbines by Signature Distances

Wind turbines operate in the atmospheric boundary layer and are subject to complex random loading. This precludes using a deterministic response of healthy turbines as the baseline for identifying the effect of damage on the measured response of operating turbines. In the absence of such a deterministic response, the stochastic dynamic response of the tower to a shutdown maneuver is found to be affected distinctively by damage in contrast to wind. Such a dynamic response, however, cannot be established for the blades. As an alternative, the estimate of blade damage is sought through its effect on the third or fourth modal frequency, each found to be mostly unaffected by wind. To discern the effect of damage from the wind effect on these responses, a unified method of damage detection is introduced that accommodates different responses. In this method, the dynamic responses are transformed to surfaces via continuous wavelet transforms to accentuate the effect of wind or damage on the dynamic response. Regions of significant deviations between these surfaces are then isolated in their corresponding planes to capture the change signatures. The image distances between these change signatures are shown to produce consistent estimates of damage for both the tower and the blades in presence of varying wind field profiles

Rechargeable-battery chemistry based on lithium oxide growth through nitrate anion redox

Next-generation lithium-battery cathodes often involve the growth of lithium-rich phases, which enable specific capacities that are 2−3 times higher than insertion cathode materials, such as lithium cobalt oxide. Here, we investigated battery chemistry previously deemed irreversible in which lithium oxide, a lithium-rich phase, grows through the reduction of the nitrate anion in a lithium nitrate-based molten salt at 150 °C. Using a suite of independent characterization techniques, we demonstrated that a Ni nanoparticle catalyst enables the reversible growth and dissolution of micrometre-sized lithium oxide crystals through the effective catalysis of nitrate reduction and nitrite oxidation, which results in high cathode areal capacities (~12 mAh cm^(–2)). These results enable a rechargeable battery system that has a full-cell theoretical specific energy of 1,579 Wh kg^(–1), in which a molten nitrate salt serves as both an active material and the electrolyte

A Molten Salt Lithium-Oxygen Battery

Despite the promise of extremely high theoretical capacity (2Li + O_2 ↔ Li_2O_2, 1675 mAh per gram of oxygen), many challenges currently impede development of Li/O_2 battery technology. Finding suitable electrode and electrolyte materials remains the most elusive challenge to date. A radical new approach is to replace volatile, unstable and air-intolerant organic electrolytes common to prior research in the field with alkali metal nitrate molten salt electrolytes and operate the battery above the liquidus temperature (>80 °C). Here we demonstrate an intermediate temperature Li/O_2 battery using a lithium anode, a molten nitrate-based electrolyte (e.g., LiNO_3–KNO_3 eutectic) and a porous carbon O_2 cathode with high energy efficiency (∼95%) and improved rate capability because the discharge product, lithium peroxide, is stable and moderately soluble in the molten salt electrolyte. The results, supported by essential state-of-the-art electrochemical and analytical techniques such as in situ pressure and gas analyses, scanning electron microscopy, rotating disk electrode voltammetry, demonstrate that Li_2O_2 electrochemically forms and decomposes upon cycling with discharge/charge overpotentials as low as 50 mV. We show that the cycle life of such batteries is limited only by carbon reactivity and by the uncontrolled precipitation of Li_2O_2, which eventually becomes electrically disconnected from the O_2 electrode

A cross-scale assessment of productivity–diversity relationships

Aim: Biodiversity and ecosystem productivity vary across the globe, and considerable effort has been made to describe their relationships. Biodiversity and ecosystem functioning research has traditionally focused on how experimentally controlled species richness affects net primary productivity (S → NPP) at small spatial grains. In contrast, the influence of productivity on richness (NPP → S) has been explored at many grains in naturally assembled communities. Mismatches in spatial scale between approaches have fuelled debate about the strength and direction of biodiversity–productivity relationships. Here, we examine the direction and strength of the influence of productivity on diversity (NPP → S) and the influence of diversity on productivity (S → NPP) and how these vary across spatial grains. Location: Contiguous USA. Time period: 1999–2015. Major taxa studied: Woody species (angiosperms and gymnosperms). Methods: Using data from North American forests at grains from local (672 m2) to coarse spatial units (median area = 35,677 km2), we assess relationships between diversity and productivity using structural equation and random forest models, while accounting for variation in climate, environmental heterogeneity, management and forest age. Results: We show that relationships between S and NPP strengthen with spatial grain. Within each grain, S → NPP and NPP → S have similar magnitudes, meaning that processes underlying S → NPP and NPP → S either operate simultaneously or that one of them is real and the other is an artefact. At all spatial grains, S was one of the weakest predictors of forest productivity, which was largely driven by biomass, temperature and forest management and age. Main conclusions: We conclude that spatial grain mediates relationships between biodiversity and productivity in real-world ecosystems and that results supporting predictions from each approach (NPP → S and S → NPP) serve as an impetus for future studies testing underlying mechanisms. Productivity–diversity relationships emerge at multiple spatial grains, which should widen the focus of national and global policy and research to larger spatial grains.</p

One thousand plant transcriptomes and the phylogenomics of green plants

Abstract: Green plants (Viridiplantae) include around 450,000–500,000 species1, 2 of great diversity and have important roles in terrestrial and aquatic ecosystems. Here, as part of the One Thousand Plant Transcriptomes Initiative, we sequenced the vegetative transcriptomes of 1,124 species that span the diversity of plants in a broad sense (Archaeplastida), including green plants (Viridiplantae), glaucophytes (Glaucophyta) and red algae (Rhodophyta). Our analysis provides a robust phylogenomic framework for examining the evolution of green plants. Most inferred species relationships are well supported across multiple species tree and supermatrix analyses, but discordance among plastid and nuclear gene trees at a few important nodes highlights the complexity of plant genome evolution, including polyploidy, periods of rapid speciation, and extinction. Incomplete sorting of ancestral variation, polyploidization and massive expansions of gene families punctuate the evolutionary history of green plants. Notably, we find that large expansions of gene families preceded the origins of green plants, land plants and vascular plants, whereas whole-genome duplications are inferred to have occurred repeatedly throughout the evolution of flowering plants and ferns. The increasing availability of high-quality plant genome sequences and advances in functional genomics are enabling research on genome evolution across the green tree of life