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The Keggin type polyoxotungstate [Ti2W10PO40]7- forms stable associates with the biopolymer chitosan in the nanometer size range. The cluster compound crystallizes from aqueous solution as K4H3[Ti2W10PO40] · 15H2O having a tetragonal structure. Both, the cluster compound and the chitosan/[Ti2W10PO40] associates show a high hydrolytic stability at pH 7.4. The associates formed between the cluster anion [Ti2W10PO40]7- with the polyaminosaccharide chitosan have been characterized by photon correlation spectroscopy, scanning electron microscopy, filtration, centrifugation and zeta potential measurements. The size of the associates formed is in the range of ca. 5×101 to 5×102 nm. These particles have a defined stoichiometry with 56 cluster anions bound per molecule chitosan. The isoelectric point determined by zeta potential measurements was found for a cluster anion to chitosan molar ratio of 5.5, indicating the charge neutralization between protonated chitosan and [Ti2W10PO40]7- anions. Cellular uptake studies with [Ti2W10PO40]7- using tumor cell lines FaDu (human squamous carcinoma) and HT-29 (human adenocarcinoma) showed that the tungsten amount inside the cells is remarkably enhanced in the presence of chitosan.
To accelerate the growth of Industry 4.0 technologies, the digitalization of mechanical testing laboratories as one of the main data-driven units of materials processing industries is introduced in this paper. The digital lab infrastructure consists of highly detailed and standard-compliant materials testing knowledge graphs for a wide range of mechanical testing processes, as well as some tools that enable the efficient ontology development and conversion of heterogeneous materials’ mechanical testing data to the machine-readable data of uniform and standardized structures. As a basis for designing such a digital lab, the mechanical testing ontology (MTO) was developed based on the ISO 23718 and ISO/IEC 21838-2 standards for the semantic representation of the mechanical testing experiments, quantities, artifacts, and report data. The trial digitalization of materials mechanical testing lab was successfully performed by utilizing the developed tools and knowledge graph of processes for converting the various experimental test data of heterogeneous structures, languages, and formats to standardized Resource Description Framework (RDF) data formats. The concepts of data storage and data sharing in data spaces were also introduced and SPARQL queries were utilized to evaluate how the introduced approach can result in the data retrieval and response to the competency questions. The proposed digital materials mechanical testing lab approach allows the industries to access lots of trustworthy and traceable mechanical testing data of other academic and industrial organizations, and subsequently organize various data-driven research for their faster and cheaper product development leading to a higher performance of products in engineering and ecological aspects.