Development of an Extended Corresponding States Principle Method for Volumetric Property Predictions Based on a Lee–Kesler Reference Fluid View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2002-05

AUTHORS

R. S. Pai-Panandiker, C. A. Nieto de Castro, I. M. Marrucho, J. F. Ely

ABSTRACT

The corresponding states principle (CSP) and the extended CSP have proven to be valuable tools in the prediction of properties of fluids and fluid mixtures. However, the accuracy of the application of these principles to property prediction is crucially dependent on the accuracy of the equation of state of the reference fluid or fluids involved. In this work, a new methodology of property prediction is developed and discussed. The revised extended corresponding states method, as developed by Marrucho and Ely, is combined with a reformulated (Teja-like) Lee–Kesler approach. The reformulated Lee–Kesler method is used to generate a pseudo-reference fluid, specific to each target fluid, which allows better mapping characteristics with any specified target fluid. This methodology is tested for the prediction of bulk volumetric properties of non-polar as well as polar fluids (specifically, alternative refrigerants). The results with different pseudo-reference fluids are compared with those of the original Lee–Kesler model and those obtained with n-propane as a single reference fluid. In the case of polar fluids, the prediction of properties is improved if the Taylor series expansion of the compressibility factor in the Lee–Kesler approach is affected in terms of the dipole moment rather than the acentric factor. The details of the combined “reformulated Lee–Kesler extended corresponding states” methodology are elucidated. More... »

PAGES

771-785

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1015419607914

DOI

http://dx.doi.org/10.1023/a:1015419607914

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1015357430


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

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/2008/0915", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Interdisciplinary Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/09", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Engineering", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Lisbon", 
          "id": "https://www.grid.ac/institutes/grid.9983.b", 
          "name": [
            "Departamento de Qu\u00edmica e Bioqu\u00edmica and Centro de Ci\u00eancias Moleculares e Materiais, Faculdade de Ci\u00eancias da Universidade de Lisboa, 1749-016, Lisboa, Portugal"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pai-Panandiker", 
        "givenName": "R. S.", 
        "id": "sg:person.015217323363.33", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015217323363.33"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Lisbon", 
          "id": "https://www.grid.ac/institutes/grid.9983.b", 
          "name": [
            "Departamento de Qu\u00edmica e Bioqu\u00edmica and Centro de Ci\u00eancias Moleculares e Materiais, Faculdade de Ci\u00eancias da Universidade de Lisboa, 1749-016, Lisboa, Portugal"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nieto de Castro", 
        "givenName": "C. A.", 
        "id": "sg:person.013433616377.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013433616377.13"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Aveiro", 
          "id": "https://www.grid.ac/institutes/grid.7311.4", 
          "name": [
            "Departamento de Qu\u00edmica, Universidade de Aveiro, 3800, Aveiro, Portugal"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Marrucho", 
        "givenName": "I. M.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Colorado School of Mines", 
          "id": "https://www.grid.ac/institutes/grid.254549.b", 
          "name": [
            "Department of Chemical and Petroleuum-Refining Engineering, Colorado School of Mines, 80401, Golden, Colorado, U.S.A"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ely", 
        "givenName": "J. F.", 
        "id": "sg:person.012014412040.38", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012014412040.38"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/0300-9467(81)80053-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001019319"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1252/jcej.6.10", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017943441"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/aic.690210313", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026949347"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/aic.690311007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027792797"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0378-3812(94)87051-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033043116"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01496398008055612", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034534199"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1006631512597", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037500655", 
          "https://doi.org/10.1023/a:1006631512597"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0009-2509(81)80041-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038954521"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00500790", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039241517", 
          "https://doi.org/10.1007/bf00500790"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00500790", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039241517", 
          "https://doi.org/10.1007/bf00500790"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/i260032a023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055527613"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ie00100a021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055594908"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/j100184a053", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055657598"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ja01567a007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055808167"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/ja01618a001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055813074"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/je00029a014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055878274"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/je60047a012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055886692"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.1698871", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057769411"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.1750658", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057812652"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.3253132", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057925133"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2002-05", 
    "datePublishedReg": "2002-05-01", 
    "description": "The corresponding states principle (CSP) and the extended CSP have proven to be valuable tools in the prediction of properties of fluids and fluid mixtures. However, the accuracy of the application of these principles to property prediction is crucially dependent on the accuracy of the equation of state of the reference fluid or fluids involved. In this work, a new methodology of property prediction is developed and discussed. The revised extended corresponding states method, as developed by Marrucho and Ely, is combined with a reformulated (Teja-like) Lee\u2013Kesler approach. The reformulated Lee\u2013Kesler method is used to generate a pseudo-reference fluid, specific to each target fluid, which allows better mapping characteristics with any specified target fluid. This methodology is tested for the prediction of bulk volumetric properties of non-polar as well as polar fluids (specifically, alternative refrigerants). The results with different pseudo-reference fluids are compared with those of the original Lee\u2013Kesler model and those obtained with n-propane as a single reference fluid. In the case of polar fluids, the prediction of properties is improved if the Taylor series expansion of the compressibility factor in the Lee\u2013Kesler approach is affected in terms of the dipole moment rather than the acentric factor. The details of the combined \u201creformulated Lee\u2013Kesler extended corresponding states\u201d methodology are elucidated.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1023/a:1015419607914", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1043587", 
        "issn": [
          "0195-928X", 
          "1572-9567"
        ], 
        "name": "International Journal of Thermophysics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "3", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "23"
      }
    ], 
    "name": "Development of an Extended Corresponding States Principle Method for Volumetric Property Predictions Based on a Lee\u2013Kesler Reference Fluid", 
    "pagination": "771-785", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "492c390d02645b1f4c1537496f263105bdcebbe9cd4c041fe443c48671ece116"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1023/a:1015419607914"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1015357430"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1023/a:1015419607914", 
      "https://app.dimensions.ai/details/publication/pub.1015357430"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T00:14", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8695_00000504.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1023/A:1015419607914"
  }
]
 

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/pub.10.1023/a:1015419607914'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1023/a:1015419607914'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1023/a:1015419607914'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1023/a:1015419607914'


 

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

146 TRIPLES      21 PREDICATES      46 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1023/a:1015419607914 schema:about anzsrc-for:09
2 anzsrc-for:0915
3 schema:author N8f32a99e91254d83b9e608d41bd2a343
4 schema:citation sg:pub.10.1007/bf00500790
5 sg:pub.10.1023/a:1006631512597
6 https://doi.org/10.1002/aic.690210313
7 https://doi.org/10.1002/aic.690311007
8 https://doi.org/10.1016/0009-2509(81)80041-3
9 https://doi.org/10.1016/0300-9467(81)80053-6
10 https://doi.org/10.1016/0378-3812(94)87051-9
11 https://doi.org/10.1021/i260032a023
12 https://doi.org/10.1021/ie00100a021
13 https://doi.org/10.1021/j100184a053
14 https://doi.org/10.1021/ja01567a007
15 https://doi.org/10.1021/ja01618a001
16 https://doi.org/10.1021/je00029a014
17 https://doi.org/10.1021/je60047a012
18 https://doi.org/10.1063/1.1698871
19 https://doi.org/10.1063/1.1750658
20 https://doi.org/10.1063/1.3253132
21 https://doi.org/10.1080/01496398008055612
22 https://doi.org/10.1252/jcej.6.10
23 schema:datePublished 2002-05
24 schema:datePublishedReg 2002-05-01
25 schema:description The corresponding states principle (CSP) and the extended CSP have proven to be valuable tools in the prediction of properties of fluids and fluid mixtures. However, the accuracy of the application of these principles to property prediction is crucially dependent on the accuracy of the equation of state of the reference fluid or fluids involved. In this work, a new methodology of property prediction is developed and discussed. The revised extended corresponding states method, as developed by Marrucho and Ely, is combined with a reformulated (Teja-like) Lee–Kesler approach. The reformulated Lee–Kesler method is used to generate a pseudo-reference fluid, specific to each target fluid, which allows better mapping characteristics with any specified target fluid. This methodology is tested for the prediction of bulk volumetric properties of non-polar as well as polar fluids (specifically, alternative refrigerants). The results with different pseudo-reference fluids are compared with those of the original Lee–Kesler model and those obtained with n-propane as a single reference fluid. In the case of polar fluids, the prediction of properties is improved if the Taylor series expansion of the compressibility factor in the Lee–Kesler approach is affected in terms of the dipole moment rather than the acentric factor. The details of the combined “reformulated Lee–Kesler extended corresponding states” methodology are elucidated.
26 schema:genre research_article
27 schema:inLanguage en
28 schema:isAccessibleForFree false
29 schema:isPartOf Nabb18242496c435291cdc7d9df21b6b3
30 Ne74ed25fbd384aa381696abc0be3de12
31 sg:journal.1043587
32 schema:name Development of an Extended Corresponding States Principle Method for Volumetric Property Predictions Based on a Lee–Kesler Reference Fluid
33 schema:pagination 771-785
34 schema:productId N38b26a9a0a6b48ad8dda1413197ae2a2
35 Nb6658e4555ae4dbe85bfa0668da96911
36 Ne6089e6defbc4f22b04440e4d18d41b6
37 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015357430
38 https://doi.org/10.1023/a:1015419607914
39 schema:sdDatePublished 2019-04-11T00:14
40 schema:sdLicense https://scigraph.springernature.com/explorer/license/
41 schema:sdPublisher N733347b324c447f7aec5589fcdafdc89
42 schema:url http://link.springer.com/10.1023/A:1015419607914
43 sgo:license sg:explorer/license/
44 sgo:sdDataset articles
45 rdf:type schema:ScholarlyArticle
46 N2daa9c424d0a48e594207d86cfb572d8 rdf:first N9629b3e203a54ceea2ef96d68295f867
47 rdf:rest Ne77b5d511355409fb2f96b436187c6bb
48 N38b26a9a0a6b48ad8dda1413197ae2a2 schema:name doi
49 schema:value 10.1023/a:1015419607914
50 rdf:type schema:PropertyValue
51 N733347b324c447f7aec5589fcdafdc89 schema:name Springer Nature - SN SciGraph project
52 rdf:type schema:Organization
53 N8f32a99e91254d83b9e608d41bd2a343 rdf:first sg:person.015217323363.33
54 rdf:rest Naccebcf28f314a2db0c678bc17af0afd
55 N9629b3e203a54ceea2ef96d68295f867 schema:affiliation https://www.grid.ac/institutes/grid.7311.4
56 schema:familyName Marrucho
57 schema:givenName I. M.
58 rdf:type schema:Person
59 Nabb18242496c435291cdc7d9df21b6b3 schema:issueNumber 3
60 rdf:type schema:PublicationIssue
61 Naccebcf28f314a2db0c678bc17af0afd rdf:first sg:person.013433616377.13
62 rdf:rest N2daa9c424d0a48e594207d86cfb572d8
63 Nb6658e4555ae4dbe85bfa0668da96911 schema:name dimensions_id
64 schema:value pub.1015357430
65 rdf:type schema:PropertyValue
66 Ne6089e6defbc4f22b04440e4d18d41b6 schema:name readcube_id
67 schema:value 492c390d02645b1f4c1537496f263105bdcebbe9cd4c041fe443c48671ece116
68 rdf:type schema:PropertyValue
69 Ne74ed25fbd384aa381696abc0be3de12 schema:volumeNumber 23
70 rdf:type schema:PublicationVolume
71 Ne77b5d511355409fb2f96b436187c6bb rdf:first sg:person.012014412040.38
72 rdf:rest rdf:nil
73 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
74 schema:name Engineering
75 rdf:type schema:DefinedTerm
76 anzsrc-for:0915 schema:inDefinedTermSet anzsrc-for:
77 schema:name Interdisciplinary Engineering
78 rdf:type schema:DefinedTerm
79 sg:journal.1043587 schema:issn 0195-928X
80 1572-9567
81 schema:name International Journal of Thermophysics
82 rdf:type schema:Periodical
83 sg:person.012014412040.38 schema:affiliation https://www.grid.ac/institutes/grid.254549.b
84 schema:familyName Ely
85 schema:givenName J. F.
86 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012014412040.38
87 rdf:type schema:Person
88 sg:person.013433616377.13 schema:affiliation https://www.grid.ac/institutes/grid.9983.b
89 schema:familyName Nieto de Castro
90 schema:givenName C. A.
91 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013433616377.13
92 rdf:type schema:Person
93 sg:person.015217323363.33 schema:affiliation https://www.grid.ac/institutes/grid.9983.b
94 schema:familyName Pai-Panandiker
95 schema:givenName R. S.
96 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015217323363.33
97 rdf:type schema:Person
98 sg:pub.10.1007/bf00500790 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039241517
99 https://doi.org/10.1007/bf00500790
100 rdf:type schema:CreativeWork
101 sg:pub.10.1023/a:1006631512597 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037500655
102 https://doi.org/10.1023/a:1006631512597
103 rdf:type schema:CreativeWork
104 https://doi.org/10.1002/aic.690210313 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026949347
105 rdf:type schema:CreativeWork
106 https://doi.org/10.1002/aic.690311007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027792797
107 rdf:type schema:CreativeWork
108 https://doi.org/10.1016/0009-2509(81)80041-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038954521
109 rdf:type schema:CreativeWork
110 https://doi.org/10.1016/0300-9467(81)80053-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001019319
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1016/0378-3812(94)87051-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033043116
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1021/i260032a023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055527613
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1021/ie00100a021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055594908
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1021/j100184a053 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055657598
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1021/ja01567a007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055808167
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1021/ja01618a001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055813074
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1021/je00029a014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055878274
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1021/je60047a012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1055886692
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1063/1.1698871 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057769411
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1063/1.1750658 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057812652
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1063/1.3253132 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057925133
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1080/01496398008055612 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034534199
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1252/jcej.6.10 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017943441
137 rdf:type schema:CreativeWork
138 https://www.grid.ac/institutes/grid.254549.b schema:alternateName Colorado School of Mines
139 schema:name Department of Chemical and Petroleuum-Refining Engineering, Colorado School of Mines, 80401, Golden, Colorado, U.S.A
140 rdf:type schema:Organization
141 https://www.grid.ac/institutes/grid.7311.4 schema:alternateName University of Aveiro
142 schema:name Departamento de Química, Universidade de Aveiro, 3800, Aveiro, Portugal
143 rdf:type schema:Organization
144 https://www.grid.ac/institutes/grid.9983.b schema:alternateName University of Lisbon
145 schema:name Departamento de Química e Bioquímica and Centro de Ciências Moleculares e Materiais, Faculdade de Ciências da Universidade de Lisboa, 1749-016, Lisboa, Portugal
146 rdf:type schema:Organization
 




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


...