When a higher degree of accuracy is required than offered by commercially available rapid tests, laboratories use PCR technology to amplify and enrich the genetic material of the pathogen from nasal and pharyngeal mucus samples. In the next step, even the smallest amounts of corona viruses can be easily and conclusively detected. However, in order for the enriching chain reaction to first produce ever new copies of the genetic material, the samples undergo a kind of alternating temperature bath: The laboratory equipment must repeatedly heat the reaction vessels up to 96 °C and then cool them back down to 55 °C or less. These processes have to be repeated about 30 times in a precisely specified regime. Depending on the test variant, this takes around four to six hours.
A team of IKTS scientists led by electrical engineer Dr. Lars Rebenklau and 3D printing expert Dr. Uwe Scheithauer, however, has now developed a promising, faster alternative. To fabricate their μPCR modules, they use additive manufacturing processes. A ceramic sleeve with integrated cooling channels is first realized on industrial 3D printers. “Using our additive manufacturing, even these complex shapes are no longer a problem, which would be impossible or very time-consuming and expensive to produce using conventional methods,” said Uwe Scheithauer. The researchers then fire the “green body” created in this way at over 1000 °C to form a solid and very durable ceramic. They then print metallic spiral patterns on this base body, which later serve as radiators, and fire them at 850 °C. Electrical connections and coolant hoses ultimately complete the compact μPCR modules.
These units are currently about 15 millimeters in diameter and about 45 mm long. They are both mini-ovens and mini-refrigerators: within a few seconds, the imprinted heating electrics bring the inserted sample vessels to the desired temperatures. Gaseous nitrogen flowing through the integrated 3D cooling channels cools the samples down again just as quickly. The individual modules can also be coupled to form larger matrix assemblies for analyzing many samples at once.