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Summary Thermal tolerance may limit and therefore predict ectotherm geographic distributions. However, which of the many metrics of thermal tolerance best predict distribution is often unclear, even for drosophilids, which constitute a popular and well‐described animal model. Five metrics of cold tolerance were measured for 14 Drosophila species to determine which metrics most strongly correlate with geographic distribution. The species represent tropical to temperate regions but all were reared under similar (common garden) conditions (20 °C). The traits measured were: chill coma temperature (CTmin), lethal temperature (LTe50), lethal time at low temperature (LTi50), chill coma recovery time (CCRT) and supercooling point (SCP). Measures of CTmin, LTe50 and LTi50 proved to be the best predictors to describe the variation in realized latitudinal distributions (R2 = 0·699, R2 = 0·741 and 0·550, respectively) and estimated environmental cold exposure (R2 = 0·633, R2 = 0·641 and 0·511, respectively). Measures of CCRT also correlated significantly with estimated minimum temperature (R2 = 0·373), while the SCP did not. These results remained consistent after phylogenetically independent analysis or when applying nonlinear regression. Moreover, our findings were supported by a similar analysis based on existing data compiled from the Drosophila cold tolerance literature. Trait correlations were strong between LTe50, LTi50 and CTmin, respectively (0·83 > R2 > 0·55). However, surprisingly, there was only a weak correlation between the entrance into coma (CTmin) and the recovery from chill coma (CCRT) (R2 = 0·256). Considering the findings of the present study, data from previous studies and the logistical constraints of each measure of cold tolerance, we conclude that CTmin and LTe50 are superior measures when estimating the ecologically relevant cold tolerance of drosophilids. Of these two traits, CTmin requires less equipment, time and animals and thereby presents a relatively fast, simple and dynamic measure of cold tolerance. Lay Summary

The crystallization of the aluminum (Al) sample was detected by the differential scanning calorimetry (DSC) at the undercooling Δ T C ∼ 18.3°C. At the undercooling Δ T = 6.8°C < Δ T C , the crystallization event was detected after a time delay of several minutes. The nucleation kinetics on an inner droplet surface is analyzed by numerically solving of the nucleation equations to determine the number of nuclei formed in the Al droplet sample of the mass m 0 = 9.91 mg at Δ T = 6.8 °C. The depletion of the Al melt due to the formation of crystal nuclei is taken into account. The nucleation rate for different cluster sizes tends to a quasi-stationary limit which is lower than predicted by the classical nucleation model. Homogeneous nuclei in the droplet volume are formed earlier than heterogeneous ones, but at longer times (several minutes) the heterogeneous nucleation prevails.

Water freezing is ubiquitous and affects areas as diverse as climate, the chemical industry, cryobiology and materials science. Ice nucleation is the controlling step in water freezing 1 – 5 and has, for nearly a century, been assumed to require the formation of a critical ice nucleus 6 – 10 . But there has been no direct experimental evidence for the existence of such a nucleus, owing to its transient and nanoscale nature 6 , 7 . Here we report ice nucleation in water droplets containing graphene oxide nanosheets of controlled sizes and show that they have a notable impact on ice nucleation only above a certain size that varies with the degree of supercooling of the droplets. We infer from our experimental data and theoretical calculations that the critical size of the graphene oxide reflects the size of the critical ice nucleus, which in the case of sufficiently large graphene oxides sits on their surface and gives rise to ice formation behaviour consistent with classical nucleation theory. By contrast, when the graphene oxide size is smaller than that of the critical ice nucleus, pinning at the periphery of the graphene oxide deforms the ice nucleus as it grows. This gives rise to a much higher free-energy barrier for nucleation and suppresses the promoting effect of the graphene oxide 11 . The results provide experimental information on the existence and temperature-dependent size of the critical ice nucleus, which has previously only been explored theoretically and through simulations 12 – 16 . As pinning of a pre-critical nucleus at a nanoparticle edge is not specific to the ice nucleus on graphene oxides, we expect that our approach could be extended to probe the critical nuclei in other nucleation processes. Nucleation experiments with water droplets containing differently sized graphene oxide nanosheets provide an experimental indication of the temperature-dependent size of the critical ice nucleus.

The nature of electroweak (EW) phase transition (PT) is of great importance. It may give a clue to the origin of baryon asymmetry if EWPT is strong first order. Although it is a cross over within the standard model (SM), a great many extensions of the SM are capable of altering the nature. Thus, gravitational wave (GW), which is supposed to be relics of strong first order PT, is a good complementary probe to new physics beyond SM (BSM). We in this paper elaborate the patterns of strong first order EWPT in the next to simplest extension to the SM Higgs sector, by introducing a Z3-symmetric singlet scalar. We find that, in the Z3-symmetric limit, the tree level barrier could lead to strong first order EWPT either via three or two-step PT. Moreover, they could produce two sources of GW, despite of the undetectability from the first-step strong first order PT for the near future GW experiments. But the other source with significant supercooling which then gives rise to α∼O0.1 almost can be wholly covered by future space-based GW interferometers such as eLISA, DECIGO and BBO.

A bstract During a cosmological first-order phase transition, particles of the plasma crossing the bubble walls can radiate a gauge boson. The resulting pressure cannot be computed perturbatively for large coupling constant and/or large supercooling. We resum the real and virtual emissions at all leading-log orders, both analytically and numerically using a Monte-Carlo simulation. We find that radiated bosons are dominantly soft and that the resulting retarding pressure on relativistic bubble walls is linear both in the Lorentz boost and in the order parameter, up to a log. We further quantitatively discuss IR cut-offs, wall thickness effects, the impact of various approximations entering the calculation, and comment on the fate of radiated bosons that are reflected.

Experiments provide evidence for two liquid phases in supercooled water droplets When a substance remains liquid below its melting point, it is said to be in a metastable supercooled state. In the region where the substance can be supercooled, the crystal is still the stable state, but crystallization can be avoided if the cooling occurs fast enough. The supercooled phase diagram of water has received particular attention ( 1 ). The anomalous thermodynamic properties of water point to the possible existence of two different liquid phases—one with high density and the other with low density—that become identical at a liquid-liquid critical point in the supercooled phase (C′, see the figure). But whereas mild supercooling of water is moderately easy to achieve, the deeply supercooled region has been out of the reach of experiments. On page 1589 of this issue, Kim et al. ( 2 ) use an evaporative cooling technique to cool micrometer-sized water droplets to deeply supercooled temperatures and provide evidence for the postulated critical point.

Additive manufacturing, often known as three-dimensional (3D) printing, is a process in which a part is built layer-by-layer and is a promising approach for creating components close to their final (net) shape. This process is challenging the dominance of conventional manufacturing processes for products with high complexity and low material waste 1 . Titanium alloys made by additive manufacturing have been used in applications in various industries. However, the intrinsic high cooling rates and high thermal gradient of the fusion-based metal additive manufacturing process often leads to a very fine microstructure and a tendency towards almost exclusively columnar grains, particularly in titanium-based alloys 1 . (Columnar grains in additively manufactured titanium components can result in anisotropic mechanical properties and are therefore undesirable 2 .) Attempts to optimize the processing parameters of additive manufacturing have shown that it is difficult to alter the conditions to promote equiaxed growth of titanium grains 3 . In contrast with other common engineering alloys such as aluminium, there is no commercial grain refiner for titanium that is able to effectively refine the microstructure. To address this challenge, here we report on the development of titanium–copper alloys that have a high constitutional supercooling capacity as a result of partitioning of the alloying element during solidification, which can override the negative effect of a high thermal gradient in the laser-melted region during additive manufacturing. Without any special process control or additional treatment, our as-printed titanium–copper alloy specimens have a fully equiaxed fine-grained microstructure. They also display promising mechanical properties, such as high yield strength and uniform elongation, compared to conventional alloys under similar processing conditions, owing to the formation of an ultrafine eutectoid microstructure that appears as a result of exploiting the high cooling rates and multiple thermal cycles of the manufacturing process. We anticipate that this approach will be applicable to other eutectoid-forming alloy systems, and that it will have applications in the aerospace and biomedical industries. Titanium–copper alloys with fully equiaxed grains and a fine microstructure are realized via an additive manufacturing process that exploits high cooling rates and multiple thermal cycles.

Elemental gallium possesses several intriguing properties, such as a low melting point, a density anomaly and an electronic structure in which covalent and metallic features coexist. In order to simulate this complex system, we construct an ab initio quality interaction potential by training a neural network on a set of density functional theory calculations performed on configurations generated in multithermal–multibaric simulations. Here we show that the relative equilibrium between liquid gallium, α -Ga, β -Ga, and Ga-II is well described. The resulting phase diagram is in agreement with the experimental findings. The local structure of liquid gallium and its nucleation into α -Ga and β -Ga are studied. We find that the formation of metastable β -Ga is kinetically favored over the thermodinamically stable α -Ga. Finally, we provide insight into the experimental observations of extreme undercooling of liquid Ga. Exploring nucleation processes of gallium by molecular simulation is extremely challenging due to its structural complexity. Here the authors demonstrate a neural network potential trained on a multithermal–multibaric DFT data for the study of the phase diagram of gallium in a wide temperature and pressure range.

A bstract We study the dynamics of the Peccei-Quinn (PQ) phase transition for the QCD axion. In weakly coupled models the transition is typically second order except in the region of parameters where the PQ symmetry is broken through the Coleman-Weinberg mechanism. In strongly coupled realizations the transition is often first order. We show examples where the phase transition leads to strong supercooling lowering the nucleation temperature and enhancing the stochastic gravitational wave signals. The models predict a frequency peak in the range 100–1000 Hz with an amplitude that is already within the sensitivity of LIGO and can be thoroughly tested with future gravitational wave interferometers.

One of the less desirable aspects of fusion-based additive manufacturing is the propensity for coarse columnar grain structures crossing build layers to form. This paper initially attempts to explain the reason for the formation of columnar grain structures in terms of the high thermal gradients typically observed during solidification and the alloy compositions that are typically used which promote epitaxial growth. Successful approaches to the grain refinement of titanium alloys using alloying elements that produce constitutional supercooling are discussed along with the difficulty with nucleant additions. Much of the grain-refining technology already used in aluminium casting is shown to also be applicable to additive manufacturing, although the novelty of the effective use of nanoparticles as nucleants is highlighted. It is also shown that for other alloy systems for which there is a lack of grain-refining technology using chemical means, mechanical means, such as ultrasonic treatment, can be effective across a wide range of alloys. Finally, consideration is given to the difficulties and the possible solutions of producing parts layer by layer. In particular, the importance of understanding nucleation in solidification conditions characterized by high cooling rates and thermal gradients; the importance of melt dynamics; and how previous layers could provide possibilities for refinement of the subsequent layer are highlighted.