Rethinking Ductility -- A Study Into the Size-Affected Fracture of Polymers

Ductility quantifies a material's capacity for plastic deformation, and it is a key property for preventing fracture driven failure in engineering parts. While some brittle materials exhibit improved ductility at small scales, the processes underlying this phenomenon are not well understood. This work establishes a mechanism for the origin of ductility via an investigation of size-affected fracture processes and polymer degree of conversion (DC) in two-photon lithography (TPL) fabricated materials. Microscale single edge notch bend ($\mu$SENB) specimens were written with widths from 8 to 26 $\mu$m and with different laser powers and post-write thermal annealing to control the DC between 17\% and 80\%. We find that shifting from low to high DC predictably causes a $\sim$3x and $\sim$4x increase in strength and bending stiffness, respectively, but that there is a corresponding $\sim$6x decrease in fracture energy from 180 $J/m^2$ to 30 $J/m^2$. Notably, this reduced fracture energy is accompanied by a ductile-to-brittle transition (DBT) in the failure behavior. Using finite element analysis, we demonstrate that the DBT occurs when the fracture yielding zone size ($r_p$) approaches the sample width, corresponding with a known fracture size-affected transition from flaw-based to strength-based failure. This finding provides a crucial insight that ductility is a size-induced property that occurs when features are reduced below a characteristic fracture length scale and that strength, stiffness, and toughness alone are insufficient predictors of ductility.Comment: 17 pages, 6 figure

A first update on mapping the human genetic architecture of COVID-19

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SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population

COVID-19 Host Genetics Initiative. A first update on mapping the human genetic architecture of COVID-19

The COVID-19 pandemic continues to pose a major public health threat, especially in countries with low vaccination rates. To better understand the biological underpinnings of SARS-CoV-2 infection and COVID-19 severity, we formed the COVID-19 Host Genetics Initiative1. Here we present a genome-wide association study meta-analysis of up to 125,584 cases and over 2.5 million control individuals across 60 studies from 25 countries, adding 11 genome-wide significant loci compared with those previously identified2. Genes at new loci, including SFTPD, MUC5B and ACE2, reveal compelling insights regarding disease susceptibility and severity.</p