Role of doping agent degree of sulfonation and casting solvent on the electrical conductivity and morphology of pedot:Spaes thin films

Poly(3,4-ethylenedioxythiophene) (PEDOT) plays a key role in the field of electrically conducting materials, despite its poor solubility and processability. Various molecules and polymers carrying sulfonic groups can be used to enhance PEDOT’s electrical conductivity. Among all, sul-fonated polyarylether sulfone (SPAES), prepared via homogenous synthesis with controlled degree of sulfonation (DS), is a very promising PEDOT doping agent. In this work, PEDOT was synthesized via high-concentration solvent-based emulsion polymerization using 1% w/w of SPAES with different DS as dopant. It was found that the PEDOT:SPAESs obtained have improved solubility in the chosen reaction solvents, i.e., N, N-dimethylformamide, dimethylacetamide, dimethyl sulfoxide, and N-methyl-2-pyrrolidone and, for the first time, the role of doping agent, DS and polymerization solvents were investigated analyzing the electrical properties of SPAESs and PEDOT:SPAES samples and studying the different morphology of PEDOT-based thin films. High DS of SPAES, i.e., 2.4 meq R-SO3− × g−1 of polymer, proved crucial in enhancing PEDOT’s electrical conductivity. Furthermore, the DMSO capability to favor PEDOT and SPAES chains rearrangement and interaction results in the formation of a polymer film with more homogenous morphology and higher conductivity than the ones prepared from DMAc, DMF, and NMP. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

The Use of FPGA in Drift Chambers for High Energy Physics Experiments

In this chapter, we describe the design of a field programmable gate array (FPGA) board capable of acquiring the information coming from a fast digitization of the signals generated in a drift chambers. The digitized signals are analyzed using an ad hoc real‐time algorithm implemented in the FPGA in order to reduce the data throughput coming from the particle detector

Field Programmable Gate Array

In this chapter, we describe the design of a field programmable gate array (FPGA) board capable of acquiring the information coming from a fast digitization of the signals generated in a drift chambers. The digitized signals are analyzed using an ad hoc real‐time algorithm implemented in the FPGA in order to reduce the data throughput coming from the particle detector

The Tracking performance for the IDEA drift chamber

The IDEA detector concept for a future e$^{+}$e$^{-}$ collider adopts an ultra-low mass drift chamber as a central tracking system. The He-based ultra-low mass drift chamber is designed to provide efficient tracking, a high-precision momentum measurement, and excellent particle identification by exploiting the cluster counting technique. This paper describes the expected tracking performance, obtained with full and fast simulation, for track reconstruction on detailed simulated physics events. Moreover, the details of the construction parameters of the drift chamber, including the inspection of new material for the wires, new techniques for soldering the wires, the development of an improved schema for the drift cell, and the choice of a gas mixture, will be described

Microwave Photonic Notch Filter Based on Dynamic Brillouin Gratings Generated by PRBS Signals

A method to create a microwave notch filter through dynamic Brillouin gratings is proposed and numerically demonstrated. It exploits the thumbtack correlation peaks of pseudo random bit sequences

Bacterial ligands as flexible and sensitive detectors in rapid tests for antibodies to SARS-CoV-2

Lateral flow immunoassay (LFIA) is widely employed as point-of-care tests (POCT) for the diagnosis of infectious diseases. The accuracy of LFIA largely depends on the quality of the immunoreagents used. Typical LFIAs to reveal the immune response to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) employ anti-human immunoglobulin (hIG) antibodies and recombinant viral antigens, which usually are unstable and poorly soluble. Broad selective bacterial proteins, such as Staphylococcal protein A (SpA) and Streptococcal protein G (SpG) can be considered alternatives to anti-hIG to increase versatility and sensitivity of serological LFIAs because of their high binding capacity, interspecies reactivity, and robustness. We developed two colorimetric LFA devices including SpA and SpG linked to gold nanoparticles (GNP) as detectors and explored the use of a specific, stable, and soluble immunodominant fraction of the nucleocapsid protein from SARS-CoV-2 as the capturing agent. The optimal amount of SpA-GNP and SpG-GNP conjugates and the protein-to-GNP ratios were defined through a full factorial experimental design to maximize the diagnostic sensitivity of the LFIAs. The new LFA devices were applied to analyze 105 human serum samples (69 positive and 36 negatives according to reference molecular diagnostic methods). The results showed higher sensitivity (89.9%, 95% CI 82.7-97.0) and selectivity (91.7%, 82.6-100) for the SpA-based compared to the SpG-based LFA. In addition, 18 serum samples from cats and dogs living with COVID-19 patients were analyzed and 14 showed detectable levels of anti-SARS-CoV-2 antibodies, thus illustrating the flexibility of the SpA- and SpG-based LFAs

Cluster counting algorithms for particle identification at future colliders

Recognition of electron peaks and primary ionization clusters in real data-driven waveform signals is the main goal of research for the usage of the cluster counting technique in particle identification at future colliders. The state-of-the-art open-source algorithms fail in finding the cluster distribution Poisson behavior even in low-noise conditions. In this work, we present cutting-edge algorithms and their performance to search for electron peaks and identify ionization clusters in experimental data using the latest available computing tools and physics knowledge.Comment: 6 pages, 12 figures, Proceedings of: ACAT202