Publikationen

Heparin-induced thrombocytopenia (HIT) antibodies (Abs) can mediate and activate blood cells, forming blood clots. To detect HIT Abs, immunological assays with high sensitivity (≥95%) and fast response are widely used, but only about 50% of these tests are accurate as non-HIT Abs also bind to the same antigens. We aim to develop biosensor-based electrical detection to better differentiate HIT-like from non-HIT-like Abs. As a proof of principle, we tested with two types of commercially available monoclonal Abs including KKO (inducing HIT) and RTO (noninducing HIT). Platelet factor 4/Heparin antigens were immobilized on gold electrodes, and binding of antibodies on the chips was detected based on the change in the charge transfer resistance (Rct). Binding of KKO on sensors yielded a significantly lower charge transfer resistance than that of RTO. Bound antibodies and their binding characteristics on the sensors were confirmed and characterized by complementary techniques. Analysis of thermal kinetics showed that RTO bonds are more stable than those of KKO, whereas KKO exhibited a higher negative ζ potential than RTO. These different characteristics made it possible to electrically differentiate these two types of antibodies. Our study opens a new avenue for the development of sensors for better detection of pathogenic Abs in HIT patients.

It is common knowledge that molecular energy level offsets of a type II heterojunction formed at the donor-acceptor interface are considered to be the driving force for photoinduced charge transfer in organic solar cells. Usually, these offsets - present between molecular energy levels of the donor and acceptor - are obtained via cyclic voltammetry (CV) measurements of organic semiconductors cast in a film or dissolved in solution. Simply transferring such determined energy levels from solution or film of single materials to blend films may be obviously limited and not be possible in full generality. Herein, we report various cases of material combinations in which novel non-fullerene acceptors did not yield successful charge transfer, although energy levels obtained by CV on constituting single materials indicate a type II heterojunction. Whilst the integer charge transfer (ICT) model provides one explanation for a relative rise of molecular energy levels of acceptors, further details and other cases have not been studied so far in great detail. By applying energy-resolved electrochemical impedance spectroscopy (ER-EIS) on several donor-acceptor combinations, a Fano-like resonance feature associated with a distinctive molecular energy level of the acceptor as well as various relative molecular energy level shifts of different kinds could be observed. By analyzing ER-EIS and absorption spectra, not only the exciton binding energy within single materials could be determined, but also the commonly unknown binding energy of the CT state with regard to the joint density of states (jDOS) of the effective semiconductor. The latter is defined by transitions between the highest occupied molecular orbitals (HOMO) of the donor and the lowest unoccupied molecular orbitals (LUMO) of the acceptor. Using this technique among others, we identified cases in which charge generation may occur either via uphill or by downhill processes between the charge transfer exciton and the electronic gap of the effective semiconductor. Exceptionally high CT-exciton binding energies and thus low charge generation yields were obtained for a case in which the donor and acceptor yielded a too intimate blend morphology, indicating π-π stacking as a potential cause for unfavorable molecular energy level alignment.

Clean and efficient energy conversion systems can overcome the depletion of the fossil fuel and meet the increasing demand of the energy. Ordered nanostructures arrays convert energy more efficiently than their disordered counterparts, by virtue of their structural merits. Among various fabrication methods of these ordered nanostructures arrays, anodic aluminum oxide (AAO) template-directed fabrication have drawn increasing attention due to its low cost, high throughput, flexibility and high structural controllability. This article reviews the application of ordered nanostructures arrays fabricated by AAO template-directed methods in mechanical energy, solar energy, electrical energy and chemical energy conversions in four sections. In each section, the corresponding advantages of these ordered nanostructures arrays in the energy conversion system are analysed, and the limitation of the to-date research is evaluated. Finally, the future directions of the ordered nanostructures arrays fabricated by AAO template-directed methods (the promising method to explore new growth mechanisms of AAO, green fabrication based on reusable AAO templates, new potential energy conversion application) are discussed.

We describe a new approximation method for solving a PDE-constrained optimization problem numerically. Our method is based on the adjoint formulation of the optimization problem, leading to a system of weakly coupled, elliptic PDEs. These equations are then solved using kernel-based collocation. We derive an error analysis and give numerical examples.

Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve the reliability of outputs. Here we report insights from ten weeks of collaborative short-term forecasting of COVID-19 in Germany and Poland (12 October-19 December 2020). The study period covers the onset of the second wave in both countries, with tightening non-pharmaceutical interventions (NPIs) and subsequently a decay (Poland) or plateau and renewed increase (Germany) in reported cases. Thirteen independent teams provided probabilistic real-time forecasts of COVID-19 cases and deaths. These were reported for lead times of one to four weeks, with evaluation focused on one- and two-week horizons, which are less affected by changing NPIs. Heterogeneity between forecasts was considerable both in terms of point predictions and forecast spread. Ensemble forecasts showed good relative performance, in particular in terms of coverage, but did not clearly dominate single-model predictions. The study was preregistered and will be followed up in future phases of the pandemic.