Thermodynamic Limits of Spatial Resolution in Active Thermography View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-09

AUTHORS

Peter Burgholzer

ABSTRACT

Thermal waves are caused by pure diffusion: their amplitude is decreased by more than a factor of 500 within a propagation distance of one wavelength. The diffusion equation, which describes the temperature as a function of space and time, is linear. For every linear equation the superposition principle is valid, which is known as Huygens principle for optical or mechanical wave fields. This limits the spatial resolution, like the Abbe diffraction limit in optics. The resolution is the minimal size of a structure which can be detected at a certain depth. If an embedded structure at a certain depth in a sample is suddenly heated, e.g., by eddy current or absorbed light, an image of the structure can be reconstructed from the measured temperature at the sample surface. To get the resolution the image reconstruction can be considered as the time reversal of the thermal wave. This inverse problem is ill-conditioned and therefore regularization methods have to be used taking additional assumptions like smoothness of the solutions into account. In the present work for the first time, methods of non-equilibrium statistical physics are used to solve this inverse problem without the need of such additional assumptions and without the necessity to choose a regularization parameter. For reconstructing such an embedded structure by thermal waves the resolution turns out to be proportional to the depth and inversely proportional to the natural logarithm of the signal-to-noise ratio. This result could be derived from the diffusion equation by using a delta-source at a certain depth and setting the entropy production caused by thermal diffusion equal to the information loss. No specific model about the stochastic process of the fluctuations and about the distribution densities around the mean values was necessary to get this result. More... »

PAGES

2328-2341

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10765-015-1890-7

DOI

http://dx.doi.org/10.1007/s10765-015-1890-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1033439733

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26594081


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/2008/0299", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Other Physical Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/02", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Research Center for Non Destructive Testing (Austria)", 
          "id": "https://www.grid.ac/institutes/grid.451841.d", 
          "name": [
            "Christian Doppler Laboratory for Photoacoustic Imaging and Laser Ultrasonics, Research Center for Non Destructive Testing (RECENDT), Altenberger Strasse 69, 4040, Linz, Austria"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Burgholzer", 
        "givenName": "Peter", 
        "id": "sg:person.01035176677.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01035176677.43"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s10765-005-8599-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003544622", 
          "https://doi.org/10.1007/s10765-005-8599-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10765-005-8599-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003544622", 
          "https://doi.org/10.1007/s10765-005-8599-y"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.98.080602", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008080779"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.98.080602", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008080779"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10765-013-1513-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012732879", 
          "https://doi.org/10.1007/s10765-013-1513-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10765-013-1513-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012732879", 
          "https://doi.org/10.1007/s10765-013-1513-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.infrared.2010.04.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014636748"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-322-99202-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016034374", 
          "https://doi.org/10.1007/978-3-322-99202-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-322-99202-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016034374", 
          "https://doi.org/10.1007/978-3-322-99202-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1117/12.809074", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017884074"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1209/0295-5075/82/50002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020997124"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nphoton.2014.111", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026300711", 
          "https://doi.org/10.1038/nphoton.2014.111"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1023208217925", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029946085", 
          "https://doi.org/10.1023/a:1023208217925"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.60.2721", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031806362"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physreve.60.2721", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031806362"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physleta.2009.12.042", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032599203"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physleta.2010.11.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043416254"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0963-8695(93)90537-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044776877"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0963-8695(93)90537-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044776877"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4757-3548-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048962475", 
          "https://doi.org/10.1007/978-1-4757-3548-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4757-3548-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048962475", 
          "https://doi.org/10.1007/978-1-4757-3548-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.78.2690", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050584535"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1103/physrevlett.78.2690", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050584535"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1209/0295-5075/95/40004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050590711"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.3475498", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057958107"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.90960", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058131099"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/0031-9155/54/9/016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059028115"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1088/0031-9155/54/9/016", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059028115"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2015-09", 
    "datePublishedReg": "2015-09-01", 
    "description": "Thermal waves are caused by pure diffusion: their amplitude is decreased by more than a factor of 500 within a propagation distance of one wavelength. The diffusion equation, which describes the temperature as a function of space and time, is linear. For every linear equation the superposition principle is valid, which is known as Huygens principle for optical or mechanical wave fields. This limits the spatial resolution, like the Abbe diffraction limit in optics. The resolution is the minimal size of a structure which can be detected at a certain depth. If an embedded structure at a certain depth in a sample is suddenly heated, e.g., by eddy current or absorbed light, an image of the structure can be reconstructed from the measured temperature at the sample surface. To get the resolution the image reconstruction can be considered as the time reversal of the thermal wave. This inverse problem is ill-conditioned and therefore regularization methods have to be used taking additional assumptions like smoothness of the solutions into account. In the present work for the first time, methods of non-equilibrium statistical physics are used to solve this inverse problem without the need of such additional assumptions and without the necessity to choose a regularization parameter. For reconstructing such an embedded structure by thermal waves the resolution turns out to be proportional to the depth and inversely proportional to the natural logarithm of the signal-to-noise ratio. This result could be derived from the diffusion equation by using a delta-source at a certain depth and setting the entropy production caused by thermal diffusion equal to the information loss. No specific model about the stochastic process of the fluctuations and about the distribution densities around the mean values was necessary to get this result.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10765-015-1890-7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.7580426", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1043587", 
        "issn": [
          "0195-928X", 
          "1572-9567"
        ], 
        "name": "International Journal of Thermophysics", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "9", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "36"
      }
    ], 
    "name": "Thermodynamic Limits of Spatial Resolution in Active Thermography", 
    "pagination": "2328-2341", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "9f4ca69240767d9b1f9911904fbabf376767c1ec21fe60bbc9ab4b95e1ddd681"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "26594081"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101532093"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10765-015-1890-7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1033439733"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10765-015-1890-7", 
      "https://app.dimensions.ai/details/publication/pub.1033439733"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:12", 
    "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/v90/0000000367_0000000367/records_88257_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs10765-015-1890-7"
  }
]
 

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.10.1007/s10765-015-1890-7'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10765-015-1890-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10765-015-1890-7'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10765-015-1890-7'


 

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

134 TRIPLES      21 PREDICATES      48 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10765-015-1890-7 schema:about anzsrc-for:02
2 anzsrc-for:0299
3 schema:author Ne5ed8d1f38b84b57af33922e932e81a5
4 schema:citation sg:pub.10.1007/978-1-4757-3548-2
5 sg:pub.10.1007/978-3-322-99202-4
6 sg:pub.10.1007/s10765-005-8599-y
7 sg:pub.10.1007/s10765-013-1513-0
8 sg:pub.10.1023/a:1023208217925
9 sg:pub.10.1038/nphoton.2014.111
10 https://doi.org/10.1016/0963-8695(93)90537-5
11 https://doi.org/10.1016/j.infrared.2010.04.001
12 https://doi.org/10.1016/j.physleta.2009.12.042
13 https://doi.org/10.1016/j.physleta.2010.11.002
14 https://doi.org/10.1063/1.3475498
15 https://doi.org/10.1063/1.90960
16 https://doi.org/10.1088/0031-9155/54/9/016
17 https://doi.org/10.1103/physreve.60.2721
18 https://doi.org/10.1103/physrevlett.78.2690
19 https://doi.org/10.1103/physrevlett.98.080602
20 https://doi.org/10.1117/12.809074
21 https://doi.org/10.1209/0295-5075/82/50002
22 https://doi.org/10.1209/0295-5075/95/40004
23 schema:datePublished 2015-09
24 schema:datePublishedReg 2015-09-01
25 schema:description Thermal waves are caused by pure diffusion: their amplitude is decreased by more than a factor of 500 within a propagation distance of one wavelength. The diffusion equation, which describes the temperature as a function of space and time, is linear. For every linear equation the superposition principle is valid, which is known as Huygens principle for optical or mechanical wave fields. This limits the spatial resolution, like the Abbe diffraction limit in optics. The resolution is the minimal size of a structure which can be detected at a certain depth. If an embedded structure at a certain depth in a sample is suddenly heated, e.g., by eddy current or absorbed light, an image of the structure can be reconstructed from the measured temperature at the sample surface. To get the resolution the image reconstruction can be considered as the time reversal of the thermal wave. This inverse problem is ill-conditioned and therefore regularization methods have to be used taking additional assumptions like smoothness of the solutions into account. In the present work for the first time, methods of non-equilibrium statistical physics are used to solve this inverse problem without the need of such additional assumptions and without the necessity to choose a regularization parameter. For reconstructing such an embedded structure by thermal waves the resolution turns out to be proportional to the depth and inversely proportional to the natural logarithm of the signal-to-noise ratio. This result could be derived from the diffusion equation by using a delta-source at a certain depth and setting the entropy production caused by thermal diffusion equal to the information loss. No specific model about the stochastic process of the fluctuations and about the distribution densities around the mean values was necessary to get this result.
26 schema:genre research_article
27 schema:inLanguage en
28 schema:isAccessibleForFree true
29 schema:isPartOf N25ff0fa67e6847ac8d1d6f1c0270eb4d
30 N7a6f6bd7368c4fc995f5d2a013ffd576
31 sg:journal.1043587
32 schema:name Thermodynamic Limits of Spatial Resolution in Active Thermography
33 schema:pagination 2328-2341
34 schema:productId N026bb2acb40b41359f057074959ff8a4
35 N0addc354d2bd40df957ee97c02b60d8e
36 N182a4152f80a4c5b8eae31f0a27c306d
37 N629f543457a1492ba727b1aa5f77ce09
38 N87ff310d7ba846299324d03f1abfdf53
39 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033439733
40 https://doi.org/10.1007/s10765-015-1890-7
41 schema:sdDatePublished 2019-04-11T13:12
42 schema:sdLicense https://scigraph.springernature.com/explorer/license/
43 schema:sdPublisher Na9abe9230ee3470fb00403e5efdac892
44 schema:url http://link.springer.com/10.1007%2Fs10765-015-1890-7
45 sgo:license sg:explorer/license/
46 sgo:sdDataset articles
47 rdf:type schema:ScholarlyArticle
48 N026bb2acb40b41359f057074959ff8a4 schema:name readcube_id
49 schema:value 9f4ca69240767d9b1f9911904fbabf376767c1ec21fe60bbc9ab4b95e1ddd681
50 rdf:type schema:PropertyValue
51 N0addc354d2bd40df957ee97c02b60d8e schema:name doi
52 schema:value 10.1007/s10765-015-1890-7
53 rdf:type schema:PropertyValue
54 N182a4152f80a4c5b8eae31f0a27c306d schema:name nlm_unique_id
55 schema:value 101532093
56 rdf:type schema:PropertyValue
57 N25ff0fa67e6847ac8d1d6f1c0270eb4d schema:issueNumber 9
58 rdf:type schema:PublicationIssue
59 N629f543457a1492ba727b1aa5f77ce09 schema:name pubmed_id
60 schema:value 26594081
61 rdf:type schema:PropertyValue
62 N7a6f6bd7368c4fc995f5d2a013ffd576 schema:volumeNumber 36
63 rdf:type schema:PublicationVolume
64 N87ff310d7ba846299324d03f1abfdf53 schema:name dimensions_id
65 schema:value pub.1033439733
66 rdf:type schema:PropertyValue
67 Na9abe9230ee3470fb00403e5efdac892 schema:name Springer Nature - SN SciGraph project
68 rdf:type schema:Organization
69 Ne5ed8d1f38b84b57af33922e932e81a5 rdf:first sg:person.01035176677.43
70 rdf:rest rdf:nil
71 anzsrc-for:02 schema:inDefinedTermSet anzsrc-for:
72 schema:name Physical Sciences
73 rdf:type schema:DefinedTerm
74 anzsrc-for:0299 schema:inDefinedTermSet anzsrc-for:
75 schema:name Other Physical Sciences
76 rdf:type schema:DefinedTerm
77 sg:grant.7580426 http://pending.schema.org/fundedItem sg:pub.10.1007/s10765-015-1890-7
78 rdf:type schema:MonetaryGrant
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.01035176677.43 schema:affiliation https://www.grid.ac/institutes/grid.451841.d
84 schema:familyName Burgholzer
85 schema:givenName Peter
86 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01035176677.43
87 rdf:type schema:Person
88 sg:pub.10.1007/978-1-4757-3548-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048962475
89 https://doi.org/10.1007/978-1-4757-3548-2
90 rdf:type schema:CreativeWork
91 sg:pub.10.1007/978-3-322-99202-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016034374
92 https://doi.org/10.1007/978-3-322-99202-4
93 rdf:type schema:CreativeWork
94 sg:pub.10.1007/s10765-005-8599-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1003544622
95 https://doi.org/10.1007/s10765-005-8599-y
96 rdf:type schema:CreativeWork
97 sg:pub.10.1007/s10765-013-1513-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012732879
98 https://doi.org/10.1007/s10765-013-1513-0
99 rdf:type schema:CreativeWork
100 sg:pub.10.1023/a:1023208217925 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029946085
101 https://doi.org/10.1023/a:1023208217925
102 rdf:type schema:CreativeWork
103 sg:pub.10.1038/nphoton.2014.111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026300711
104 https://doi.org/10.1038/nphoton.2014.111
105 rdf:type schema:CreativeWork
106 https://doi.org/10.1016/0963-8695(93)90537-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044776877
107 rdf:type schema:CreativeWork
108 https://doi.org/10.1016/j.infrared.2010.04.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014636748
109 rdf:type schema:CreativeWork
110 https://doi.org/10.1016/j.physleta.2009.12.042 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032599203
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1016/j.physleta.2010.11.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043416254
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1063/1.3475498 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057958107
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1063/1.90960 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058131099
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1088/0031-9155/54/9/016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059028115
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1103/physreve.60.2721 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031806362
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1103/physrevlett.78.2690 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050584535
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1103/physrevlett.98.080602 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008080779
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1117/12.809074 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017884074
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1209/0295-5075/82/50002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020997124
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1209/0295-5075/95/40004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050590711
131 rdf:type schema:CreativeWork
132 https://www.grid.ac/institutes/grid.451841.d schema:alternateName Research Center for Non Destructive Testing (Austria)
133 schema:name Christian Doppler Laboratory for Photoacoustic Imaging and Laser Ultrasonics, Research Center for Non Destructive Testing (RECENDT), Altenberger Strasse 69, 4040, Linz, Austria
134 rdf:type schema:Organization
 




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


...