125: Remote, plant-enabled continuous-flow synthesis of artemisinin as a platform for green chemistry education and distributed research

Abstract: We report an inquiry-driven, remotely accessible educational platform that integrates natural product extraction, analytical characterization, and continuous-flow synthesis in a green chemistry framework centered on the conversion of dihydroartemisinic acid (DHAA) to artemisinin. High school students cultivate Artemisia annua (or other locally available plants), perform a guided toluene-based extraction of photoactive phytochemicals, and analyze their extracts using portable UV–Vis spectroscopy to quantify key absorbance features. These student-generated extracts are then deployed as sustainable photocatalyst sources in a standardized continuous-flow oxidation of DHAA (0.5 M in toluene, trifluoroacetic acid additive, air as the terminal oxidant), operated at defined gas–liquid flow rates within a safe, automated reactor platform. Through the University of Connecticut’s Remote Research Network (RRN), students can control mobile or laboratory-based flow pumps in real time via cloud software, enabling authentic participation in chemical research regardless of local instrumentation access. For participants without UV capability, plant extracts can be shipped to UConn, where the same RRN workflow is executed on their behalf, preserving agency in experimental design and data ownership. Reaction outcomes are quantified by ^1H NMR spectroscopy, with yield determination based on the diagnostic olefinic resonances of DHAA (δ ≈ 5.11) and artemisinin (δ ≈ 5.82). This modular curriculum couples renewable feedstocks, solvent-efficient extraction, benign oxidants, and process-intensified flow chemistry with open, remote experimentation, fostering scientific self-efficacy while illustrating core principles of green chemistry and chemical engineering. More broadly, the platform demonstrates how distributed, cloud-enabled laboratories can democratize access to advanced chemical research, generate open datasets, and create scalable pathways for inclusive, community-engaged chemistry education.