2019, Naji, Ahmed, Krause, Beate, Pötschke, Petra, Ameli, Amir

Here, we report multifunctional polycarbonate (PC)-based conductive polymer composites (CPCs) with outstanding performance manufactured by a simple extrusion process and intended for use in bipolar plate (BPP) applications in polymer electrolyte membrane (PEM) fuel cells. CPCs were developed using a ternary conductive filler system containing carbon nanotube (CNT), carbon fiber (CF), and graphite (G) and by introducing di-allyl phthalate (DAP) as a plasticizer to PC matrix. The samples were fabricated using twin-screw extrusion followed by compression molding and the microstructure, electrical conductivity, thermal conductivity, and mechanical properties were investigated. The results showed a good dispersion of the fillers with some degree of interconnection between dissimilar fillers. The addition of DAP enhanced the electrical conductivity and tensile strength of the CPCs. Due to its plasticizing effect, DAP reduced the processing temperature by 75 °C and facilitated the extrusion of CPCs with filler loads as high as 63 wt% (3 wt% CNT, 30 wt% CF, 30 wt% G). Consequently, CPCs with the through-plane electrical, in-plane electrical and thermal conductivities and tensile strength of 4.2 S cm-1, 34.3 S cm-1, 2.9 W m-1 K-1, and 75.4 MPa, respectively, were achieved. This combination of properties indicates the potential of PC-based composites enriched with hybrid fillers and plasticizers as an alternative material for BPP application.

2020, Rzeczkowski, P., Pötschke, Petra, Fischer, M., Kühnert, I., Krause, Beate

A graphite-modified adhesive was developed in order to simultaneously enhance the thermal conductivity and the strength of an adhesive joint. The thermal conductivity through the joint was investigated by using highly filled PP/graphite composite substrates, which were joined with an epoxy adhesive of different layer thicknesses. Similar measurements were carried out with a constant adhesive layer thickness, whilst applying an epoxy adhesive modified with expanded graphite (EG) (6, 10, and 20 wt%). By reducing the adhesive layer thickness or modifying the adhesive with conductive fillers, a significant increase of the thermal conductivity through the joint was achieved. The examination of the mechanical properties of the modified adhesives was carried out by tensile tests (adhesive only), lap-shear tests, and fracture energy tests (mode 1) with aluminium substrates. Modification of the adhesive with EG led to an increase of the tensile lap-shear strength and the adhesive fracture energy (mode 1) of the joint. In addition, burst pressure tests were performed to determine the strength of the joint in a complex component. The strength of the joint increased with the graphite content in the PP substrate and in the epoxy adhesive.

2020, Chaves-Fraga, David, Ruckhaus, Edna, Priyatna, Freddy, Vidal, Maria-Esther, Corchio, Oscar

Ontology-Based Data Access (OBDA) has traditionally focused on providing a unified view of heterogeneous datasets, either by materializing integrated data into RDF or by performing on-the fly querying via SPARQL query translation. In the specific case of tabular datasets represented as several CSV or Excel files, query translation approaches have been applied by considering each source as a single table that can be loaded into a relational database management system (RDBMS). Nevertheless, constraints over these tables are not represented; thus, neither consistency among attributes nor indexes over tables are enforced. As a consequence, efficiency of the SPARQL-to-SQL translation process may be affected, as well as the completeness of the answers produced during the evaluation of the generated SQL query. Our work is focused on applying implicit constraints on the OBDA query translation process over tabular data. We propose Morph-CSV, a framework for querying tabular data that exploits information from typical OBDA inputs (e.g., mappings, queries) to enforce constraints that can be used together with any SPARQL-to-SQL OBDA engine. Morph-CSV relies on both a constraint component and a set of constraint operators. For a given set of constraints, the operators are applied to each type of constraint with the aim of enhancing query completeness and performance. We evaluate Morph-CSV in several domains: e-commerce with the BSBM benchmark; transportation with a benchmark using the GTFS dataset from the Madrid subway; and biology with a use case extracted from the Bio2RDF project. We compare and report the performance of two SPARQL-to-SQL OBDA engines, without and with the incorporation of MorphCSV. The observed results suggest that Morph-CSV is able to speed up the total query execution time by up to two orders of magnitude, while it is able to produce all the query answers.