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Sökning: WFRF:(Opitz Andreas) > (2020-2021)

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1.
  • Beyer, Paul, et al. (författare)
  • Fermi level pinned molecular donor/acceptor junctions : Reduction of induced carrier density by interfacial charge transfer complexes
  • 2020
  • Ingår i: Journal of Materials Chemistry C. - : Royal Society of Chemistry (RSC). - 2050-7534 .- 2050-7526. ; 8:43, s. 15199-15207
  • Tidskriftsartikel (refereegranskat)abstract
    • Increased hole density in an electron donor-type organic semiconductor can be achieved by deposition of a strong acceptor-type molecular layer on top, and has been shown to enable adjusting the carrier density in organic field effect transistors (OFETs). This interfacial charge transfer is due to simultaneous Fermi level (EF) pinning of the donor's highest occupied level and the acceptor's lowest unoccupied level. Here, we investigate the electrical properties of such an EF-pinned junction formed by diindenoperylene (DIP, as donor) and hexafluoro-tetracyano-naphthoquinodimethane (F6, as acceptor) in OFETs, as well as its electronic properties by photoelectron spectroscopy and electrostatic modelling. We find that, in addition to the EF-pinning induced integer charge transfer across the interface, DIP and F6 form charge transfer complexes (CPXs) at their junction. The molecularly thin CPX interlayer acts as insulator and significantly reduces the density of carriers induced on either side of the junction, compared to a scenario without such an interlayer. CPX formation is thus unfavourable for the effectiveness of controlling carrier density at molecular donor/acceptor junctions by EF-pinning. This journal is
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2.
  • Demichev, Vadim, et al. (författare)
  • A time-resolved proteomic and prognostic map of COVID-19
  • 2021
  • Ingår i: Cell Systems. - : Elsevier BV. - 2405-4712 .- 2405-4720. ; 12:8, s. 780-794.e7
  • Tidskriftsartikel (refereegranskat)abstract
    • COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.
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