No abstract

A detailed investigation using X-ray diffraction and other supportive techniques was performed on a preceramic polysilazane to study its pyrolytic conversion to silicon nitride (Si3N4). Analytical techniques were developed to determine the volumetric degree of crystallinity with respect to pyrolysis temperature. Quantitative data for crystallite size, phase composition, and degree of crystallinity versus pyrolysis temperature and atmosphere (nitrogen and ammonia) are presented. Pyrolytic products produced under nitrogen and ammonia atmospheres consist of microcrystals of silicon, a-Si,N,, and P-Si,N,. Under both atmospheres, a majority of the char is crystalline at -1270"C, and the entire char is crystallized at 1400°C. Pyrolysis under an ammonia atmosphere produces nearly stoichiometric Si,N,, while pyrolysis under nitrogen produces silicon-rich material.

The reaction of GaC13 with three equivalents of ButzPLi, ButzAsLi, or ArP(H)Li (Ar = 2,4,6-But3C6Hz) affords G ~( P B U ~~) ~, G ~( A S B U ~~) ~, and Ga[P(H)ArI3, respectively, whilst the reaction of GaCI3 with one equivalent of BufzELi and two equivalents of RLi results in dimeric phosphido-or arsenido-bridged compounds of the type [Ga(p-EBut2)R2J2 (E = P, As; R = Me, Bun).

Habitat restoration is an important tool for managing degraded ecosystems, yet the success of restoration projects depends in part on adequately identifying preferred sites for restoration. Species distribution modeling using a machine learning approach provides novel tools for mapping areas of interest for restoration projects. Here we use stacked-species distribution models (s-SDMs) to identify candidate locations for installment of manmade reefs, a useful management tool for restoring structural habitat complexity and the associated biota in marine ecosystems. We created species distribution models for 21 species of commercial, recreational, ecological, or conservation importance within the Southern California Bight based on observations from long-term reef surveys combined with high resolution (200 m × 200 m) geospatial environmental data layers. We then combined the individual species models to create a stacked-species habitat suitability map, identifying over 800 km 2 of potential area for reef restoration within the Bight. When considering only the 21 focal species, s-SDM scores were positively associated with observed bootstrap species richness not only on natural reefs (linear model: slope = 0.27, 95% CI = 0.17-0.36, w = 1), but also this result was supported by two independent test datasets. The predicted richness from this linear model was associated with observed species richness when considering only the focal species on manmade reefs (linear model: slope = 0.52, 95% CI = 0.13-0.92, w = 1) and also when considering 204 other non-focal species on both natural and manmade reefs in southern California (slope = 3.65, 95% CI = 2.93-4.37, w = 1). Finally, our results demonstrate that the existing manmade reefs included in our study on average are located in regions with habitat suitability that is not only less suitable than natural reefs (t-value =-5.4; p < 0.05), but also only slightly significantly better than random (p < 0.05), demonstrating a need for more biologically informed placement of manmade reefs. The stacked-species distribution model provides insight for marine restoration projects in southern California specifically, but more generally this method can also be widely applied to other types of habitat restoration including both marine and terrestrial.