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Current rates of habitat degradation and climate change are causing unprecedented declines in global biodiversity. Studies on vertebrates highlight how conservation genomics can be effective in identifying and managing threatened populations, but it is unclear how vertebrate‐derived metrics of genomic erosion translate to invertebrates, with their markedly different population sizes and life histories. The Black‐veined White butterfly (Aporia crataegi) was extirpated from Britain in the 1920s. Here, we sequenced historical DNA from 17 specimens collected between 1854 and 1924 to reconstruct demography and compare levels of genomic erosion between extirpated British and extant European mainland populations. We contrast these results using modern samples of the Common Blue butterfly (Polyommatus icarus); a species with relatively stable demographic trends in Great Britain. We provide evidence for bottlenecks in both these species around the period of post‐glacial colonization of the British Isles. Our results reveal different demographic histories and Ne for both species, consistent with their fates in Britain, likely driven by differences in life history, ecology and genome size. Despite a difference, by an order of magnitude, in historical effective population sizes (Ne), reduction in genome‐wide heterozygosity in A. crataegi was comparable to that in P. icarus. Symptomatic of A. crataegi's disappearance were marked increases in runs‐of‐homozygosity (RoH), potentially indicative of recent inbreeding, and accumulation of putatively mildly and weakly deleterious variants. Our results provide a rare glimpse of genomic erosion in a regionally extinct insect and support the potential use of genomic erosion metrics in identifying invertebrate populations or species in decline. [ABSTRACT FROM AUTHOR]

Boron carbide plays a crucial role in various extreme environment applications, including thermal barrier coatings, aerospace applications, and neutron absorbers, because of its high thermal and chemical stability. In this study, the temperature-dependent elastic stiffness constants, thermal expansion coefficient, Helmholtz free energy, entropy, and heat capacity at a constant volume ( C v ) of rhombohedral B4C have been predicted using a quasi-harmonic approach. A combination of volume-dependent first-principles calculations (density functional theory) and first-principles phonon calculations in the supercell framework has been performed. Good agreement between the elastic constants and structural parameters from static calculations is observed. The calculated thermodynamic properties from phonon calculations show trends that align with the literature. As the temperature rises, the predicted free energy follows a decreasing trend, while entropy and C v follow increasing trends with temperature. Comparisons between the predicted room temperature thermal expansion coefficient (TEC) ( 7.54 × 10 − 6 K−1) and bulk modulus (228 GPa) from the quasi-harmonic approach and literature results from experiments and models are performed, revealing that the calculated TEC and bulk modulus fall within the established range from the limited set of data from the literature (TEC = 5.73–9.50 × 10 − 6 K−1, B = 221–246 GPa). Temperature-dependent C i j s are predicted, enabling stress analysis at elevated temperatures. Overall, the outcomes of this study can be used when performing mechanical and thermal stress analysis (e.g., space shielding applications) and optimizing the design of boron carbide materials for elevated temperature applications. [ABSTRACT FROM AUTHOR]

Manufacturing defects, such as porosity and inclusions, can significantly compromise the structural integrity and performance of additively manufactured parts by acting as stress concentrators and potential initiation sites for failure. This paper investigates the effects of pore system morphology (number of pores, total volume, volume fraction, and standard deviation of size of pores) on the material response of additively manufactured Ti6Al4V specimens under a shear–compression stress state. An automatic approach for finite element simulations, using the J2 plasticity model, was utilized on a shear–compression specimen with artificial pores of varying characteristics to generate the dataset. An artificial neural network (ANN) surrogate model was developed to predict peak force and failure displacement of specimens with different pore attributes. The ANN demonstrated effective prediction capabilities, offering insights into the importance of individual input variables on mechanical performance of additively manufactured parts. Additionally, a sensitivity analysis using the Garson equation was performed to identify the most influential parameters affecting the material's behaviour. It was observed that materials with more uniform pore sizes exhibit better mechanical properties than those with a wider size distribution. Overall, the study contributes to a better understanding of the interplay between pore characteristics and material response, providing better defect-aware design and property–porosity linkage in additive manufacturing processes. [ABSTRACT FROM AUTHOR]