Crossing the ballistic-ohmic transition via high energy electron irradiation

P.H.M. and M.D.B. received PhD studentship support from the UK Engineering and Physical Science Research Council via Grant No. EP/L015110/1. C.P. and P.J.W.M. are supported by the European Research Council under the European Union's Horizon 2020 research and innovation programme (Microstructured Topological Materials Grant No. 715730). E. Z. acknowledges support from the International Max Planck Research School for Chemistry and Physics of Quantum Materials (IMPRS-CPQM). Irradiation experiments performed on the SIRIUS platform were supported by the French National Network of Accelerators for Irradiation and Analysis of Molecules and Materials (EMIR&A) under Project No. EMIR 2019 18-7099.The delafossite metal PtCoO2 is among the highest-purity materials known, with low-temperature mean free path up to 5 μm in the best as-grown single crystals. It exhibits a strongly faceted, nearly hexagonal Fermi surface. This property has profound consequences for nonlocal transport within this material, such as in the classic ballistic-regime measurement of bend resistance in mesoscopic squares. Here, we report the results of experiments in which high-energy electron irradiation was used to introduce pointlike disorder into such squares, reducing the mean free path and therefore the strength of the ballistic-regime transport phenomena. We demonstrate that high-energy electron irradiation is a well-controlled technique to cross from nonlocal to local transport behavior and therefore determine the nature and extent of unconventional transport regimes. Using this technique, we confirm the origins of the directional ballistic effects observed in delafossite metals and demonstrate how the strongly faceted Fermi surface both leads to unconventional transport behavior and enhances the length scale over which such effects are important. © 2023 authors. Published by the American Physical Society. Published by the American Physical Society under the terms of the "https://creativecommons.org/licenses/by/4.0/"Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Open access publication funded by the Max Planck Society.Publisher PDFPeer reviewe

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease