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The impact of the Double Asteroid Redirection Test (DART) spacecraft with Dimorphos allows us to study asteroid collision physics, including momentum transfer, the ejecta properties, and the visibility of such events in the Solar system. We report observations of the DART impact in the ultraviolet (UV), visible light, and near-infrared (IR) wavelengths. The observations support the existence of at least two separate components of the ejecta: a fast and a slow component. The fast-ejecta component is composed of a gaseous phase, moving at about 1.6 km s−1 with a mass of ≲104 kg. The fast ejecta is detected in the UV and visible light, but not in the near-IR z-band observations. Fitting a simplified optical thickness model to these observations allows us to constrain some of the properties of the fast ejecta, including its scattering efficiency and the opacity of the gas. The slow ejecta component is moving at typical velocities of up to about 10 m s−1. It is composed of micrometer-size particles, that have a scattering efficiency, at the direction of the observer, of the order of 10−3 and a total mass of ∼106 kg. The larger particles in the slow ejecta, whose size is bound to be in the range between ∼1 mm and ∼1 m, likely have a scattering efficiency larger than that of the pre-impact Didymos system.

 

The self-assembly of shape-anisotropic nanocrystals into large-scale structures is a versatile and scalable approach to creating multifunctional materials. The tetrahedral geometry is ubiquitous in natural and manmade materials, yet regular tetrahedra present a formidable challenge in understanding their self-assembly behavior as they do not tile space. Here, we report diverse supracrystals from gold nanotetrahedra including the quasicrystal (QC) and the dimer packing predicted more than a decade ago and hitherto unknown phases. We solve the complex three-dimensional (3D) structure of the QC by a combination of electron microscopy, tomography, and synchrotron X-ray scattering. Nanotetrahedron vertex sharpness, surface ligands, and assembly conditions work in concert to regulate supracrystal structure. We also discover that the surface curvature of supracrystals can induce structural changes of the QC tiling and eventually, for small supracrystals with high curvature, stabilize a hexagonal approximant. Our findings bridge the gap between computational design and experimental realization of soft matter assemblies and demonstrate the importance of accurate control over nanocrystal attributes and the assembly conditions to realize increasingly complex nanopolyhedron supracrystals. 

We present a phylogeny of Chrysopidae inferred from combining molecular and morphological data. Apochrysinae were recovered as sister to the rest of the family (Nothochrysinae and Chrysopinae). The monogeneric tribe Nothancylini is confirmed as sister to the remaining Chrysopinae. The other four tribes are grouped in two clades: Belonopterygini + Leucochrysini and Ankylopterygini + Chrysopini. The Nineta-group is herein transferred from Chrysopini to Ankylopterygini. Within the diverse and species-rich Chrysopini we recognize five genus-group clades: Chrysopa, Chrysoperla, Chrysopodes, Eremochrysa and Meleoma generic groups. The mapping of characters, such as the parameres, the tignum, the im cell or the tibial spurs, on the phylogeny provides insights into the evolution of these traits in the family. In addition, we propose the following taxonomic changes to the classification of the family: the inclusion of Chrysopidia, Nineta and Tumeochrysa in the tribe Ankylopterygini, and the synonymization of Furcochrysa with Chrysopa.

 

Quasicrystals have been discovered in a variety of materials ranging from metals to polymers. Yet, why and how they form is incompletely understood. In situ transmission electron microscopy of alloy quasicrystal formation in metals suggests an error-and-repair mechanism, whereby quasiperiodic crystals grow imperfectly with phason strain present, and only perfect themselves later into a high-quality quasicrystal with negligible phason strain. The growth mechanism has not been investigated for other types of quasicrystals, such as dendrimeric, polymeric, or colloidal quasicrystals. Soft-matter quasicrystals typically result from entropic, rather than energetic, interactions, and are not usually grown (either in laboratories or in silico ) into large-volume quasicrystals. Consequently, it is unknown whether soft-matter quasicrystals form with the high degree of structural quality found in metal alloy quasicrystals. Here, we investigate the entropically driven growth of colloidal dodecagonal quasicrystals (DQCs) via computer simulation of systems of hard tetrahedra, which are simple models for anisotropic colloidal particles that form a quasicrystal. Using a pattern recognition algorithm applied to particle trajectories during DQC growth, we analyze phason strain to follow the evolution of quasiperiodic order. As in alloys, we observe high structural quality; DQCs with low phason strain crystallize directly from the melt and only require minimal further reduction of phason strain. We also observe transformation from a denser approximant to the DQC via continuous phason strain relaxation. Our results demonstrate that soft-matter quasicrystals dominated by entropy can be thermodynamically stable and grown with high structural quality––just like their alloy quasicrystal counterparts. 

The rigid constraints of chemistry—dictated by quantum mechanics and the discrete nature of the atom—limit the set of observable atomic crystal structures. What structures are possible in the absence of these constraints? Here, we systematically crystallize one-component systems of particles interacting with isotropic multiwell pair potentials. We investigate two tunable families of pairwise interaction potentials. Our simulations self-assemble a multitude of crystal structures ranging from basic lattices to complex networks. Sixteen of the structures have natural analogs spanning all coordination numbers found in inorganic chemistry. Fifteen more are hitherto unknown and occupy the space between covalent and metallic coordination environments. The discovered crystal structures constitute targets for self-assembly and expand our understanding of what a crystal structure can look like.

 

The field of self-assembly has moved far beyond early work, where the focus was primarily the resultant beautiful two- and three-dimensional structures, to a focus on forming materials and devices with important properties either otherwise not available, or only available at great cost. Over the last few years, materials with unprecedented electronic, photonic, energy-storage, and chemical separation functionalities were created with self-assembly, while at the same time, the ability to form even more complex structures in two and three dimensions has only continued to advance. Self-assembly crosscuts all areas of materials. Functional structures have now been realized in polymer, ceramic, metallic, and semiconducting systems, as well as composites containing multiple classes of materials. As the field of self-assembly continues to advance, the number of highly functional systems will only continue to grow and make increasingly greater impacts in both the consumer and industrial space. 

While bees are critical to sustaining a large proportion of global food production, as well as pollinating both wild and cultivated plants, they are decreasing in both numbers and diversity. Our understanding of the factors driving these declines is limited, in part, because we lack sufficient data on the distribution of bee species to predict changes in their geographic range under climate change scenarios. Additionally lacking is adequate data on the behavioral and anatomical traits that may make bees either vulnerable or resilient to human-induced environmental changes, such as habitat loss and climate change. Fortunately, a wealth of associated attributes can be extracted from the specimens deposited in natural history collections for over 100 years. Extending Anthophila Research Through Image and Trait Digitization (Big-Bee) is a newly funded US National Science Foundation Advancing Digitization of Biodiversity Collections project. Over the course of three years, we will create over one million high-resolution 2D and 3D images of bee specimens (Fig. 1), representing over 5,000 worldwide bee species, including most of the major pollinating species. We will also develop tools to measure bee traits from images and generate comprehensive bee trait and image datasets to measure changes through time. The Big-Bee network of participating institutions includes 13 US institutions (Fig. 2) and partnerships with US government agencies. We will develop novel mechanisms for sharing image datasets and datasets of bee traits that will be available through an open, Symbiota-Light (Gilbert et al. 2020) data portal called the Bee Library. In addition, biotic interaction and species association data will be shared via Global Biotic Interactions (Poelen et al. 2014). The Big-Bee project will engage the public in research through community science via crowdsourcing trait measurements and data transcription from images using Notes from Nature (Hill et al. 2012). Training and professional development for natural history collection staff, researchers, and university students in data science will be provided through the creation and implementation of workshops focusing on bee traits and species identification. We are also planning a short, artistic college radio segment called "the Buzz" to get people excited about bees, biodiversity, and the wonders of our natural world.