Ontology type: schema:ScholarlyArticle
2000-06
AUTHORS ABSTRACTThe Linear Driving Force (LDF) model for gas adsorption kinetics is frequently and successfully used for analysis of adsorption column dynamic data and for adsorptive process designs because it is simple, analytic, and physically consistent. Yet, there is a substantial difference in the characteristics of isothermal batch uptake curves on adsorbent particles by the LDF and the more rigorous Fickian Diffusion (FD) model. It is demonstrated by using simple model systems that the characteristics of the adsorption kinetics at the single pore or the adsorbent particle level are lost in (a) evaluating overall uptake on a heterogeneous porous solid, (b) calculating breakthrough curves from a packed adsorbent column, and (c) establishing the efficiency of separation by an adsorptive process due to repeated averaging of the base kinetic property. That is why the LDF model works in practice. More... »
PAGES137-147
http://scigraph.springernature.com/pub.10.1023/a:1008965317983
DOIhttp://dx.doi.org/10.1023/a:1008965317983
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1043357964
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/2008/0904",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Chemical 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": "Air Products & Chemicals (United States)",
"id": "https://www.grid.ac/institutes/grid.454238.c",
"name": [
"Air Products and Chemicals, Inc., 7201 Hamilton Boulevard, 18195-1501, Allentown, PA, USA"
],
"type": "Organization"
},
"familyName": "Sircar",
"givenName": "S.",
"id": "sg:person.016400612033.51",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016400612033.51"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "Air Products & Chemicals (United States)",
"id": "https://www.grid.ac/institutes/grid.454238.c",
"name": [
"Air Products and Chemicals, Inc., 7201 Hamilton Boulevard, 18195-1501, Allentown, PA, USA"
],
"type": "Organization"
},
"familyName": "Hufton",
"givenName": "J.R.",
"id": "sg:person.012671264211.20",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012671264211.20"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1023/a:1008917308002",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1003853261",
"https://doi.org/10.1023/a:1008917308002"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/aic.690260104",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1006410118"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1252/jcej.16.114",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1010078385"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf00705001",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011462320",
"https://doi.org/10.1007/bf00705001"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf00705001",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011462320",
"https://doi.org/10.1007/bf00705001"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0039-6028(88)90291-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011464916"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0039-6028(88)90291-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1011464916"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0009-2509(92)80033-9",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1014279537"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1252/jcej.16.53",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019209128"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1039/f19807600071",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019514308"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1039/tf9555101540",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019837741"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0009-2509(91)80052-z",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1020696035"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0009-2509(86)80010-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028690867"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/aic.690250229",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028702641"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/bf00707354",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029611413",
"https://doi.org/10.1007/bf00707354"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0009-2509(92)80041-a",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033273798"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/aic.690431009",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1033933063"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1039/f19837900785",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034961405"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0009-2509(93)80316-i",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1036589778"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/aic.690330819",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1038712595"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1252/jcej.24.538",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1044826450"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/aic.690460325",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1045438671"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/0009-2509(92)80034-a",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1047428671"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1002/aic.690320118",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1053669008"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1021/i200021a017",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1055526250"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1021/ie50524a025",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1055633783"
],
"type": "CreativeWork"
}
],
"datePublished": "2000-06",
"datePublishedReg": "2000-06-01",
"description": "The Linear Driving Force (LDF) model for gas adsorption kinetics is frequently and successfully used for analysis of adsorption column dynamic data and for adsorptive process designs because it is simple, analytic, and physically consistent. Yet, there is a substantial difference in the characteristics of isothermal batch uptake curves on adsorbent particles by the LDF and the more rigorous Fickian Diffusion (FD) model. It is demonstrated by using simple model systems that the characteristics of the adsorption kinetics at the single pore or the adsorbent particle level are lost in (a) evaluating overall uptake on a heterogeneous porous solid, (b) calculating breakthrough curves from a packed adsorbent column, and (c) establishing the efficiency of separation by an adsorptive process due to repeated averaging of the base kinetic property. That is why the LDF model works in practice.",
"genre": "research_article",
"id": "sg:pub.10.1023/a:1008965317983",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1134428",
"issn": [
"0929-5607",
"1572-8757"
],
"name": "Adsorption",
"type": "Periodical"
},
{
"issueNumber": "2",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "6"
}
],
"name": "Why Does the Linear Driving Force Model for Adsorption Kinetics Work?",
"pagination": "137-147",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"ce87ee89f53427759f4eeae1f7301d200e08cb8e96b5e60f130031c9b5e26e8c"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1023/a:1008965317983"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1043357964"
]
}
],
"sameAs": [
"https://doi.org/10.1023/a:1008965317983",
"https://app.dimensions.ai/details/publication/pub.1043357964"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T01:57",
"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_8700_00000501.jsonl",
"type": "ScholarlyArticle",
"url": "http://link.springer.com/10.1023/A:1008965317983"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
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:1008965317983'
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:1008965317983'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1023/a:1008965317983'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1023/a:1008965317983'
This table displays all metadata directly associated to this object as RDF triples.
143 TRIPLES
21 PREDICATES
51 URIs
19 LITERALS
7 BLANK NODES