Microfluidic devices and methods of fabrication


Ontology type: sgo:Patent     


Patent Info

DATE

2014-02-25T00:00

AUTHORS

John T. Fourkas , Christopher N. LaFratta

ABSTRACT

The present invention relates to microfluidic devices that comprise a 3-D microfluidic network of microchannels of arbitrary complexity and to a method for fabricating such devices. In particular, the invention relates to a method of forming microfluidic devices having 3-D microfluidic networks that contain open or closed loop microchannels using a single-step molding process without the need for layer-by-layer fabrication, and to the resultant microfluidic devices. The networks of such microfluidic devices may comprise one or more microchannel circuits which may be discrete or interconnected. More... »

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/2953", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "name": "John T. Fourkas", 
        "type": "Person"
      }, 
      {
        "name": "Christopher N. LaFratta", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.mejo.2003.10.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010576235"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/17989", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025228833", 
          "https://doi.org/10.1038/17989"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/17989", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025228833", 
          "https://doi.org/10.1038/17989"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35089130", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041938448", 
          "https://doi.org/10.1038/35089130"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35089130", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041938448", 
          "https://doi.org/10.1038/35089130"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/cr030076o", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046771231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/cr030076o", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046771231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.288.5463.113", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053301497"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ac069363t", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054999024"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ac069363t", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054999024"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/cm0256007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055409719"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/cm0256007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055409719"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ja991990v", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055872424"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ja991990v", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055872424"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jp048525r", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056058783"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jp048525r", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056058783"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ma991042e", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056210197"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ma991042e", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056210197"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1049/ecej:19990603", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056748716"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.1728296", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057794798"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/15321790500304163", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058399739"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/15321790500304163", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058399739"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/jlt.2003.809564", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061282198"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/josaa.20.000948", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065160347"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/ol.22.000132", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065217176"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/ol.23.001745", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065218290"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/ol.28.000301", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065220828"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2014-02-25T00:00", 
    "description": "

The present invention relates to microfluidic devices that comprise a 3-D microfluidic network of microchannels of arbitrary complexity and to a method for fabricating such devices. In particular, the invention relates to a method of forming microfluidic devices having 3-D microfluidic networks that contain open or closed loop microchannels using a single-step molding process without the need for layer-by-layer fabrication, and to the resultant microfluidic devices. The networks of such microfluidic devices may comprise one or more microchannel circuits which may be discrete or interconnected.

", "id": "sg:patent.US-8656949-B2", "keywords": [ "Microfluidic Analytical Technique", "method", "fabrication", "invention", "microfluidic network", "microchannels", "arbitrary complexity", "fabricating", "Equipment and Supply", "molding process", "layer-by-layer", "microfluidics device", "network" ], "name": "Microfluidic devices and methods of fabrication", "recipient": [ { "id": "https://www.grid.ac/institutes/grid.164295.d", "type": "Organization" } ], "sameAs": [ "https://app.dimensions.ai/details/patent/US-8656949-B2" ], "sdDataset": "patents", "sdDatePublished": "2019-04-18T10:12", "sdLicense": "https://scigraph.springernature.com/explorer/license/", "sdPublisher": { "name": "Springer Nature - SN SciGraph project", "type": "Organization" }, "sdSource": "s3://com-uberresearch-data-patents-target-20190320-rc/data/sn-export/402f166718b70575fb5d4ffe01f064d1/0000100128-0000352499/json_export_00737.jsonl", "type": "Patent" } ]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/patent.US-8656949-B2'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/patent.US-8656949-B2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/patent.US-8656949-B2'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/patent.US-8656949-B2'


 

This table displays all metadata directly associated to this object as RDF triples.

95 TRIPLES      15 PREDICATES      45 URIs      21 LITERALS      2 BLANK NODES

Subject Predicate Object
1 sg:patent.US-8656949-B2 schema:about anzsrc-for:2953
2 schema:author N49865a544c9f462a8fefc5446af56b87
3 schema:citation sg:pub.10.1038/17989
4 sg:pub.10.1038/35089130
5 https://doi.org/10.1016/j.mejo.2003.10.003
6 https://doi.org/10.1021/ac069363t
7 https://doi.org/10.1021/cm0256007
8 https://doi.org/10.1021/cr030076o
9 https://doi.org/10.1021/ja991990v
10 https://doi.org/10.1021/jp048525r
11 https://doi.org/10.1021/ma991042e
12 https://doi.org/10.1049/ecej:19990603
13 https://doi.org/10.1063/1.1728296
14 https://doi.org/10.1080/15321790500304163
15 https://doi.org/10.1109/jlt.2003.809564
16 https://doi.org/10.1126/science.288.5463.113
17 https://doi.org/10.1364/josaa.20.000948
18 https://doi.org/10.1364/ol.22.000132
19 https://doi.org/10.1364/ol.23.001745
20 https://doi.org/10.1364/ol.28.000301
21 schema:datePublished 2014-02-25T00:00
22 schema:description <p num="p-0001">The present invention relates to microfluidic devices that comprise a 3-D microfluidic network of microchannels of arbitrary complexity and to a method for fabricating such devices. In particular, the invention relates to a method of forming microfluidic devices having 3-D microfluidic networks that contain open or closed loop microchannels using a single-step molding process without the need for layer-by-layer fabrication, and to the resultant microfluidic devices. The networks of such microfluidic devices may comprise one or more microchannel circuits which may be discrete or interconnected.</p>
23 schema:keywords Equipment and Supply
24 Microfluidic Analytical Technique
25 arbitrary complexity
26 fabricating
27 fabrication
28 invention
29 layer-by-layer
30 method
31 microchannels
32 microfluidic network
33 microfluidics device
34 molding process
35 network
36 schema:name Microfluidic devices and methods of fabrication
37 schema:recipient https://www.grid.ac/institutes/grid.164295.d
38 schema:sameAs https://app.dimensions.ai/details/patent/US-8656949-B2
39 schema:sdDatePublished 2019-04-18T10:12
40 schema:sdLicense https://scigraph.springernature.com/explorer/license/
41 schema:sdPublisher N8002c5a447ea42d6b5b3c34a38b064e3
42 sgo:license sg:explorer/license/
43 sgo:sdDataset patents
44 rdf:type sgo:Patent
45 N05836a8f9ef94ca08b9bd8fb9d8bb92e schema:name Christopher N. LaFratta
46 rdf:type schema:Person
47 N49865a544c9f462a8fefc5446af56b87 rdf:first Ndb0e98b29fcd459487eb75f1e78619f9
48 rdf:rest N9befcabbf7db44fba3ad714995310524
49 N8002c5a447ea42d6b5b3c34a38b064e3 schema:name Springer Nature - SN SciGraph project
50 rdf:type schema:Organization
51 N9befcabbf7db44fba3ad714995310524 rdf:first N05836a8f9ef94ca08b9bd8fb9d8bb92e
52 rdf:rest rdf:nil
53 Ndb0e98b29fcd459487eb75f1e78619f9 schema:name John T. Fourkas
54 rdf:type schema:Person
55 anzsrc-for:2953 schema:inDefinedTermSet anzsrc-for:
56 rdf:type schema:DefinedTerm
57 sg:pub.10.1038/17989 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025228833
58 https://doi.org/10.1038/17989
59 rdf:type schema:CreativeWork
60 sg:pub.10.1038/35089130 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041938448
61 https://doi.org/10.1038/35089130
62 rdf:type schema:CreativeWork
63 https://doi.org/10.1016/j.mejo.2003.10.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010576235
64 rdf:type schema:CreativeWork
65 https://doi.org/10.1021/ac069363t schema:sameAs https://app.dimensions.ai/details/publication/pub.1054999024
66 rdf:type schema:CreativeWork
67 https://doi.org/10.1021/cm0256007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055409719
68 rdf:type schema:CreativeWork
69 https://doi.org/10.1021/cr030076o schema:sameAs https://app.dimensions.ai/details/publication/pub.1046771231
70 rdf:type schema:CreativeWork
71 https://doi.org/10.1021/ja991990v schema:sameAs https://app.dimensions.ai/details/publication/pub.1055872424
72 rdf:type schema:CreativeWork
73 https://doi.org/10.1021/jp048525r schema:sameAs https://app.dimensions.ai/details/publication/pub.1056058783
74 rdf:type schema:CreativeWork
75 https://doi.org/10.1021/ma991042e schema:sameAs https://app.dimensions.ai/details/publication/pub.1056210197
76 rdf:type schema:CreativeWork
77 https://doi.org/10.1049/ecej:19990603 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056748716
78 rdf:type schema:CreativeWork
79 https://doi.org/10.1063/1.1728296 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057794798
80 rdf:type schema:CreativeWork
81 https://doi.org/10.1080/15321790500304163 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058399739
82 rdf:type schema:CreativeWork
83 https://doi.org/10.1109/jlt.2003.809564 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061282198
84 rdf:type schema:CreativeWork
85 https://doi.org/10.1126/science.288.5463.113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053301497
86 rdf:type schema:CreativeWork
87 https://doi.org/10.1364/josaa.20.000948 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065160347
88 rdf:type schema:CreativeWork
89 https://doi.org/10.1364/ol.22.000132 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065217176
90 rdf:type schema:CreativeWork
91 https://doi.org/10.1364/ol.23.001745 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065218290
92 rdf:type schema:CreativeWork
93 https://doi.org/10.1364/ol.28.000301 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065220828
94 rdf:type schema:CreativeWork
95 https://www.grid.ac/institutes/grid.164295.d schema:Organization
 




Preview window. Press ESC to close (or click here)


...