{"doi":"10.1039/d0lc00538j","title":"Deterministic droplet coding <i>via</i> acoustofluidics","abstract":"Droplet microfluidics has become an indispensable tool for biomedical research and lab-on-a-chip applications owing to its unprecedented throughput, precision, and cost-effectiveness. Although droplets can be generated and screened in a high-throughput manner, the inability to label the inordinate amounts of droplets hinders identifying the individual droplets after generation. Herein, we demonstrate an acoustofluidic platform that enables on-demand, real-time dispensing, and deterministic coding of droplets based on their volumes. By dynamically splitting the aqueous flow using an oil jet triggered by focused traveling surface acoustic waves, a sequence of droplets with deterministic volumes can be continuously dispensed at a throughput of 100 Hz. These sequences encode barcoding information through the combination of various droplet lengths. As a proof-of-concept, we encoded droplet sequences into end-to-end packages (e.g., a series of 50 droplets), which consisted of an address barcode with binary volumetric combinations and a sample package with consistent volumes for hosting analytes. This acoustofluidics-based, deterministic droplet coding technique enables the tagging of droplets with high capacity and high error-tolerance, and can potentially benefit various applications involving single cell phenotyping and multiplexed screening.","journal":"Lab on a Chip","year":2020,"id":78283,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":18,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9522,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":407335,"name":"Wei Wang","orcid":"0000-0001-5508-7359","position":1,"is_corresponding":false},{"id":307730,"name":"Hai Fu","orcid":"0000-0002-6322-3186","position":2,"is_corresponding":false},{"id":407336,"name":"Joseph Rich","orcid":"0000-0002-6249-2093","position":3,"is_corresponding":false},{"id":307727,"name":"Xingyu Su","orcid":"0000-0001-9764-0968","position":4,"is_corresponding":false},{"id":235105,"name":"Hunter Bachman","orcid":"0000-0002-2356-5392","position":5,"is_corresponding":false},{"id":274161,"name":"Jianping Xia","orcid":"0000-0001-9902-0228","position":6,"is_corresponding":false},{"id":281047,"name":"Jinxin Zhang","orcid":"0000-0001-6492-8519","position":7,"is_corresponding":false},{"id":274156,"name":"Shuaiguo Zhao","orcid":"0000-0002-0139-8466","position":8,"is_corresponding":false},{"id":407337,"name":"Jia Zhou","orcid":"0000-0002-9098-5661","position":9,"is_corresponding":false},{"id":235107,"name":"Tony Jun Huang","orcid":"0000-0003-1205-3313","position":10,"is_corresponding":false},{"id":235104,"name":"Peiran Zhang","orcid":"0000-0002-3873-9949","position":0,"is_corresponding":true}],"reference_count":66,"raw_metadata":null,"created_at":"2026-07-18T21:49:40.769098Z","pmid":"33103674","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}