| dc.contributor.author | Alexander E. Siemenn, Basita Das, Eunice Aissi, Fang Sheng, Lleyton Elliott, Blake Hudspeth, Marilyn Meyers, James Serdy and Tonio Buonassisi | |
| dc.date.accessioned | 2026-02-26T15:41:44Z | |
| dc.date.available | 2026-02-26T15:41:44Z | |
| dc.date.issued | 2025-01-31 | |
| dc.date.submitted | 2024-08-05 | |
| dc.identifier.issn | 2635-098X | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/164964 | |
| dc.description.abstract | The maturation of 3D printing technology has enabled low-cost, rapid prototyping capabilities for mainstreaming accelerated product design. The materials research community has recognized this need, but no universally accepted rapid prototyping technique currently exists for material design. Toward this end, we develop Archerfish, a 3D printer retrofitted to dispense liquid with in situ mixing capabilities for performing high-throughput combinatorial printing (HTCP) of material compositions. Using this HTCP design, we demonstrate continuous printing throughputs of up to 250 unique compositions per minute, 100× faster than similar tools such as Opentrons that utilize stepwise printing with ex situ mixing. We validate the formation of these combinatorial “prototype” material gradients using hyperspectral image analysis and energy-dispersive X-ray spectroscopy. Furthermore, we describe hardware challenges to realizing reproducible, accurate, and precise composition gradients with continuous printing, including those related to precursor dispensing, mixing, and deposition. Despite these limitations, the continuous printing and low-cost design of Archerfish demonstrate promising accelerated materials screening results across a range of materials systems from nanoparticles to perovskites. | en_US |
| dc.publisher | Royal Society of Chemistry | en_US |
| dc.relation.isversionof | https://doi.org/10.1039/D4DD00249K | en_US |
| dc.rights | Creative Commons Attribution-Noncommercial | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | en_US |
| dc.source | Royal Society of Chemistry | en_US |
| dc.title | Archerfish: A Retrofitted 3D Printer for High-throughput Combinatorial Experimentation via Continuous Printing | en_US |
| dc.type | Article | en_US |
| dc.identifier.citation | Alexander E. Siemenn, Basita Das, Eunice Aissi, Fang Sheng, Lleyton Elliott, Blake Hudspeth, Marilyn Meyers, James Serdy and Tonio Buonassisi. 2025. "Archerfish: A Retrofitted 3D Printer for High-throughput Combinatorial Experimentation via Continuous Printing." Digital Discovery, (4). | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Mechanical Engineering | en_US |
| dc.relation.journal | Digital Discovery | en_US |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dspace.date.submission | 2026-02-13T16:40:00Z | |
| mit.journal.issue | 4 | en_US |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | en_US |