2023
DOI: 10.1039/d2lc00892k
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A versatile non-fouling multi-step flow reactor platform: demonstration for partial oxidation synthesis of iron oxide nanoparticles

Abstract: In the last decade flow reactors for material synthesis were firmly established, demonstrating advantageous operating conditions, reproducible and scalable production via continuous operation, as well as high-throughput screening of synthetic...

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Cited by 7 publications
(6 citation statements)
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“…[46][47][48][49] Fig. 1 Flow reactors that fouled during the synthesis of (a) silver, 35 (b) lipid, 36 (c) iron oxide, 37 (d) palladium, 18 (reproduced from ref.…”
Section: Definition Of Fouling With Regard To Nanoparticle Synthesismentioning
confidence: 99%
See 3 more Smart Citations
“…[46][47][48][49] Fig. 1 Flow reactors that fouled during the synthesis of (a) silver, 35 (b) lipid, 36 (c) iron oxide, 37 (d) palladium, 18 (reproduced from ref.…”
Section: Definition Of Fouling With Regard To Nanoparticle Synthesismentioning
confidence: 99%
“…[46][47][48][49] Fig. 1 Flow reactors that fouled during the synthesis of (a) silver, 35 (b) lipid, 36 (c) iron oxide, 37 (d) palladium, 18 (reproduced from ref. To better distinguish the fouling origin and consequences for flow reactors, we distinguish between local (small axial reactor fraction affected), or traversed (significant axial reactor fraction affected), and fouling affecting the surface only (depositions at the reactor wall not extending radially into the channel) or being constrictive (depositions extending from the reactor wall reducing the channel cross section), see Fig.…”
Section: Definition Of Fouling With Regard To Nanoparticle Synthesismentioning
confidence: 99%
See 2 more Smart Citations
“…Compared to batch reactors, droplet-based microfluidic synthesis strategies have been demonstrated as a reliable reactor of choice for high-throughput screening, mechanistic studies, and continuous production of colloidal NCs, including metal oxide, silver, and gold NCs, as well as II-VI, III-V, and Pb-based MHP NCs. [30][31][32][33][34][35][36][37][38][39] The continuous nature of microfluidic reactors along with their modularity, facile automation, and integration with multimodal in situ characterization tools (e.g., spectroscopy) 28,40,41 offer an exciting avenue to accelerate parameter space and synthesis-property relationship mapping of NCs through integration with data science tools in a closed-loop format. Such integration of an automated microfluidic reactor with machine learning (ML)-assisted process modelling and experiment-selection results in establishment of self-driving fluidic labs (SDFLs).…”
Section: Introductionmentioning
confidence: 99%