Synthesis and characterization of exfoliated biochar from four agricultural feedstock View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03

AUTHORS

Shuvrodeb Roy, Uday Kumar, Pradip Bhattacharyya

ABSTRACT

Highly porous biochar (BC) structures have been prepared from inexpensive biomasses like rice straw, bamboo, sugarcane waste, and corn cob via a slow pyrolysis technique in nitrogenous atmosphere. A surface engineering technique has been applied to enhance the surface-to-volume ratio of each biochar sample and finally compared its characteristics through standard surface and elemental characterization techniques, viz. CHN (carbon, hydrogen, and nitrogen), FTIR (Fourier transform infrared spectroscopy), BET (Brunauer-Emmett-Teller), and SEM (scanning electron microscopy). All the biochar samples were observed to be highly carbonized and aromatized. Exfoliated structures were found to contain more elemental carbon (34.14-77.32%) than its native form (30.92-74.46%). Aromatic hydrocarbon, aromatic C=C, aromatics, aliphatic C-O, aliphatic hydrocarbon, and H-bonded OH groups were found to predominate in the surface of biochar structures independent of their precursor composition and extent of exfoliation. SEM micrographic images clearly ensured about the unoriented sheets like the morphology of different biochar samples. Although no significant structural difference was found to exist depending on their precursor compositions, quantitative enhancement of porosity was found to be observed after exfoliation. Both native (240.65 m2/g) and exfoliated (712.89 m2/g) biochars derived from sugarcane wastes were observed to have a maximum surface area in comparison to the biochars derived from rice straw (native, 22.08 m2/g; exfoliated, 29.92 m2/g), bamboo (native, 42.08 m2/g; exfoliated, 248.38 m2/g), and corn cob (native, 136.62 m2/g; exfoliated, 221.71 m2/g). Exfoliated biochars were found to be consistently more potent in comparison to its native form as per our comparative characterizations performed so far. More... »

PAGES

7272-7276

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11356-018-04117-7

DOI

http://dx.doi.org/10.1007/s11356-018-04117-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111541087

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30661167


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/2008/0306", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Physical Chemistry (incl. Structural)", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/03", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Chemical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Indian Statistical Institute", 
          "id": "https://www.grid.ac/institutes/grid.39953.35", 
          "name": [
            "Agricultural and Ecological Research Unit, Indian Statistical Institute, 700108, Kolkata, West Bengal, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Roy", 
        "givenName": "Shuvrodeb", 
        "id": "sg:person.01263212464.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01263212464.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Maulana Azad National Institute of Technology", 
          "id": "https://www.grid.ac/institutes/grid.419487.7", 
          "name": [
            "Department of Physics, National Institute of Technology, 831014, Jamshedpur, Jharkhand, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kumar", 
        "givenName": "Uday", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Indian Statistical Institute", 
          "id": "https://www.grid.ac/institutes/grid.39953.35", 
          "name": [
            "Agricultural and Ecological Research Unit, Indian Statistical Institute, 815301, Giridih, Jharkhand, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bhattacharyya", 
        "givenName": "Pradip", 
        "id": "sg:person.0631552577.96", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0631552577.96"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s11104-009-0050-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000171597", 
          "https://doi.org/10.1007/s11104-009-0050-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11104-009-0050-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000171597", 
          "https://doi.org/10.1007/s11104-009-0050-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11104-009-0050-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000171597", 
          "https://doi.org/10.1007/s11104-009-0050-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/442624a", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003082478", 
          "https://doi.org/10.1038/442624a"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/442624a", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003082478", 
          "https://doi.org/10.1038/442624a"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/442624a", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003082478", 
          "https://doi.org/10.1038/442624a"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1039/c4ta06110a", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004095151"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/gcbb.12030", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004873573"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.biortech.2016.04.093", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017201797"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/es101337x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018772007"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/es101337x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018772007"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jaap.2014.03.017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018833691"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cej.2013.10.081", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023140091"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.agee.2014.04.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024651309"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.biortech.2013.03.057", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031164266"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.still.2011.01.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032674026"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jiec.2015.09.029", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048306562"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.indcrop.2007.03.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050227793"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf104206c", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055909127"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1021/jf104206c", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1055909127"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0176884", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085394137"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10643389.2017.1418580", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100200196"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.scitotenv.2018.01.054", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1100563642"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11356-018-1460-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101038683", 
          "https://doi.org/10.1007/s11356-018-1460-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11356-018-2521-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1105010384", 
          "https://doi.org/10.1007/s11356-018-2521-1"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.scitotenv.2018.07.402", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1105899853"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-03", 
    "datePublishedReg": "2019-03-01", 
    "description": "Highly porous biochar (BC) structures have been prepared from inexpensive biomasses like rice straw, bamboo, sugarcane waste, and corn cob via a slow pyrolysis technique in nitrogenous atmosphere. A surface engineering technique has been applied to enhance the surface-to-volume ratio of each biochar sample and finally compared its characteristics through standard surface and elemental characterization techniques, viz. CHN (carbon, hydrogen, and nitrogen), FTIR (Fourier transform infrared spectroscopy), BET (Brunauer-Emmett-Teller), and SEM (scanning electron microscopy). All the biochar samples were observed to be highly carbonized and aromatized. Exfoliated structures were found to contain more elemental carbon (34.14-77.32%) than its native form (30.92-74.46%). Aromatic hydrocarbon, aromatic C=C, aromatics, aliphatic C-O, aliphatic hydrocarbon, and H-bonded OH groups were found to predominate in the surface of biochar structures independent of their precursor composition and extent of exfoliation. SEM micrographic images clearly ensured about the unoriented sheets like the morphology of different biochar samples. Although no significant structural difference was found to exist depending on their precursor compositions, quantitative enhancement of porosity was found to be observed after exfoliation. Both native (240.65\u00a0m2/g) and exfoliated (712.89\u00a0m2/g) biochars derived from sugarcane wastes were observed to have a maximum surface area in comparison to the biochars derived from rice straw (native, 22.08\u00a0m2/g; exfoliated, 29.92\u00a0m2/g), bamboo (native, 42.08\u00a0m2/g; exfoliated, 248.38\u00a0m2/g), and corn cob (native, 136.62\u00a0m2/g; exfoliated, 221.71\u00a0m2/g). Exfoliated biochars were found to be consistently more potent in comparison to its native form as per our comparative characterizations performed so far.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s11356-018-04117-7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1113424", 
        "issn": [
          "0944-1344", 
          "1614-7499"
        ], 
        "name": "Environmental Science and Pollution Research", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "7", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "26"
      }
    ], 
    "name": "Synthesis and characterization of exfoliated biochar from four agricultural feedstock", 
    "pagination": "7272-7276", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "91acc3311b467c0c14ac31ca8af99f615473039dbe5ad594358f9d0665fc9098"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30661167"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "9441769"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s11356-018-04117-7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1111541087"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s11356-018-04117-7", 
      "https://app.dimensions.ai/details/publication/pub.1111541087"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:20", 
    "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/v90/0000000368_0000000368/records_78965_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs11356-018-04117-7"
  }
]
 

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/s11356-018-04117-7'

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/s11356-018-04117-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s11356-018-04117-7'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s11356-018-04117-7'


 

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

150 TRIPLES      21 PREDICATES      49 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s11356-018-04117-7 schema:about anzsrc-for:03
2 anzsrc-for:0306
3 schema:author N4f6627b6618e404f91bc134f056e3b7d
4 schema:citation sg:pub.10.1007/s11104-009-0050-x
5 sg:pub.10.1007/s11356-018-1460-1
6 sg:pub.10.1007/s11356-018-2521-1
7 sg:pub.10.1038/442624a
8 https://doi.org/10.1016/j.agee.2014.04.010
9 https://doi.org/10.1016/j.biortech.2013.03.057
10 https://doi.org/10.1016/j.biortech.2016.04.093
11 https://doi.org/10.1016/j.cej.2013.10.081
12 https://doi.org/10.1016/j.indcrop.2007.03.004
13 https://doi.org/10.1016/j.jaap.2014.03.017
14 https://doi.org/10.1016/j.jiec.2015.09.029
15 https://doi.org/10.1016/j.scitotenv.2018.01.054
16 https://doi.org/10.1016/j.scitotenv.2018.07.402
17 https://doi.org/10.1016/j.still.2011.01.002
18 https://doi.org/10.1021/es101337x
19 https://doi.org/10.1021/jf104206c
20 https://doi.org/10.1039/c4ta06110a
21 https://doi.org/10.1080/10643389.2017.1418580
22 https://doi.org/10.1111/gcbb.12030
23 https://doi.org/10.1371/journal.pone.0176884
24 schema:datePublished 2019-03
25 schema:datePublishedReg 2019-03-01
26 schema:description Highly porous biochar (BC) structures have been prepared from inexpensive biomasses like rice straw, bamboo, sugarcane waste, and corn cob via a slow pyrolysis technique in nitrogenous atmosphere. A surface engineering technique has been applied to enhance the surface-to-volume ratio of each biochar sample and finally compared its characteristics through standard surface and elemental characterization techniques, viz. CHN (carbon, hydrogen, and nitrogen), FTIR (Fourier transform infrared spectroscopy), BET (Brunauer-Emmett-Teller), and SEM (scanning electron microscopy). All the biochar samples were observed to be highly carbonized and aromatized. Exfoliated structures were found to contain more elemental carbon (34.14-77.32%) than its native form (30.92-74.46%). Aromatic hydrocarbon, aromatic C=C, aromatics, aliphatic C-O, aliphatic hydrocarbon, and H-bonded OH groups were found to predominate in the surface of biochar structures independent of their precursor composition and extent of exfoliation. SEM micrographic images clearly ensured about the unoriented sheets like the morphology of different biochar samples. Although no significant structural difference was found to exist depending on their precursor compositions, quantitative enhancement of porosity was found to be observed after exfoliation. Both native (240.65 m<sup>2</sup>/g) and exfoliated (712.89 m<sup>2</sup>/g) biochars derived from sugarcane wastes were observed to have a maximum surface area in comparison to the biochars derived from rice straw (native, 22.08 m<sup>2</sup>/g; exfoliated, 29.92 m<sup>2</sup>/g), bamboo (native, 42.08 m<sup>2</sup>/g; exfoliated, 248.38 m<sup>2</sup>/g), and corn cob (native, 136.62 m<sup>2</sup>/g; exfoliated, 221.71 m<sup>2</sup>/g). Exfoliated biochars were found to be consistently more potent in comparison to its native form as per our comparative characterizations performed so far.
27 schema:genre research_article
28 schema:inLanguage en
29 schema:isAccessibleForFree false
30 schema:isPartOf N7cb65dd469cd419bb98f3b4174e648c5
31 Nbcd473aebd5c4e10937844624dee55d9
32 sg:journal.1113424
33 schema:name Synthesis and characterization of exfoliated biochar from four agricultural feedstock
34 schema:pagination 7272-7276
35 schema:productId N0cdca48e459e4baabaf055483c3f070d
36 N2f9579446f90488889dcf83fd9bb21a5
37 N62c58f94fc9b4e1e975deeedf18773b0
38 Nb4a71397ec1949ec823ce1475796ee3d
39 Nba476e3976094f00bd488202d37b5c0c
40 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111541087
41 https://doi.org/10.1007/s11356-018-04117-7
42 schema:sdDatePublished 2019-04-11T13:20
43 schema:sdLicense https://scigraph.springernature.com/explorer/license/
44 schema:sdPublisher Na4093056a4564918898549c6ea0d6d5b
45 schema:url https://link.springer.com/10.1007%2Fs11356-018-04117-7
46 sgo:license sg:explorer/license/
47 sgo:sdDataset articles
48 rdf:type schema:ScholarlyArticle
49 N0cdca48e459e4baabaf055483c3f070d schema:name pubmed_id
50 schema:value 30661167
51 rdf:type schema:PropertyValue
52 N2f9579446f90488889dcf83fd9bb21a5 schema:name dimensions_id
53 schema:value pub.1111541087
54 rdf:type schema:PropertyValue
55 N4f6627b6618e404f91bc134f056e3b7d rdf:first sg:person.01263212464.27
56 rdf:rest N7a3087454eb84c728c1424ae0802c320
57 N62c58f94fc9b4e1e975deeedf18773b0 schema:name readcube_id
58 schema:value 91acc3311b467c0c14ac31ca8af99f615473039dbe5ad594358f9d0665fc9098
59 rdf:type schema:PropertyValue
60 N77e3b22c5f724c7fa8bb05714c91c26b rdf:first sg:person.0631552577.96
61 rdf:rest rdf:nil
62 N7a3087454eb84c728c1424ae0802c320 rdf:first Nbab86bf0315c464488589281cd71fb28
63 rdf:rest N77e3b22c5f724c7fa8bb05714c91c26b
64 N7cb65dd469cd419bb98f3b4174e648c5 schema:issueNumber 7
65 rdf:type schema:PublicationIssue
66 Na4093056a4564918898549c6ea0d6d5b schema:name Springer Nature - SN SciGraph project
67 rdf:type schema:Organization
68 Nb4a71397ec1949ec823ce1475796ee3d schema:name doi
69 schema:value 10.1007/s11356-018-04117-7
70 rdf:type schema:PropertyValue
71 Nba476e3976094f00bd488202d37b5c0c schema:name nlm_unique_id
72 schema:value 9441769
73 rdf:type schema:PropertyValue
74 Nbab86bf0315c464488589281cd71fb28 schema:affiliation https://www.grid.ac/institutes/grid.419487.7
75 schema:familyName Kumar
76 schema:givenName Uday
77 rdf:type schema:Person
78 Nbcd473aebd5c4e10937844624dee55d9 schema:volumeNumber 26
79 rdf:type schema:PublicationVolume
80 anzsrc-for:03 schema:inDefinedTermSet anzsrc-for:
81 schema:name Chemical Sciences
82 rdf:type schema:DefinedTerm
83 anzsrc-for:0306 schema:inDefinedTermSet anzsrc-for:
84 schema:name Physical Chemistry (incl. Structural)
85 rdf:type schema:DefinedTerm
86 sg:journal.1113424 schema:issn 0944-1344
87 1614-7499
88 schema:name Environmental Science and Pollution Research
89 rdf:type schema:Periodical
90 sg:person.01263212464.27 schema:affiliation https://www.grid.ac/institutes/grid.39953.35
91 schema:familyName Roy
92 schema:givenName Shuvrodeb
93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01263212464.27
94 rdf:type schema:Person
95 sg:person.0631552577.96 schema:affiliation https://www.grid.ac/institutes/grid.39953.35
96 schema:familyName Bhattacharyya
97 schema:givenName Pradip
98 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0631552577.96
99 rdf:type schema:Person
100 sg:pub.10.1007/s11104-009-0050-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1000171597
101 https://doi.org/10.1007/s11104-009-0050-x
102 rdf:type schema:CreativeWork
103 sg:pub.10.1007/s11356-018-1460-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101038683
104 https://doi.org/10.1007/s11356-018-1460-1
105 rdf:type schema:CreativeWork
106 sg:pub.10.1007/s11356-018-2521-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105010384
107 https://doi.org/10.1007/s11356-018-2521-1
108 rdf:type schema:CreativeWork
109 sg:pub.10.1038/442624a schema:sameAs https://app.dimensions.ai/details/publication/pub.1003082478
110 https://doi.org/10.1038/442624a
111 rdf:type schema:CreativeWork
112 https://doi.org/10.1016/j.agee.2014.04.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024651309
113 rdf:type schema:CreativeWork
114 https://doi.org/10.1016/j.biortech.2013.03.057 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031164266
115 rdf:type schema:CreativeWork
116 https://doi.org/10.1016/j.biortech.2016.04.093 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017201797
117 rdf:type schema:CreativeWork
118 https://doi.org/10.1016/j.cej.2013.10.081 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023140091
119 rdf:type schema:CreativeWork
120 https://doi.org/10.1016/j.indcrop.2007.03.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050227793
121 rdf:type schema:CreativeWork
122 https://doi.org/10.1016/j.jaap.2014.03.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018833691
123 rdf:type schema:CreativeWork
124 https://doi.org/10.1016/j.jiec.2015.09.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048306562
125 rdf:type schema:CreativeWork
126 https://doi.org/10.1016/j.scitotenv.2018.01.054 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100563642
127 rdf:type schema:CreativeWork
128 https://doi.org/10.1016/j.scitotenv.2018.07.402 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105899853
129 rdf:type schema:CreativeWork
130 https://doi.org/10.1016/j.still.2011.01.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032674026
131 rdf:type schema:CreativeWork
132 https://doi.org/10.1021/es101337x schema:sameAs https://app.dimensions.ai/details/publication/pub.1018772007
133 rdf:type schema:CreativeWork
134 https://doi.org/10.1021/jf104206c schema:sameAs https://app.dimensions.ai/details/publication/pub.1055909127
135 rdf:type schema:CreativeWork
136 https://doi.org/10.1039/c4ta06110a schema:sameAs https://app.dimensions.ai/details/publication/pub.1004095151
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1080/10643389.2017.1418580 schema:sameAs https://app.dimensions.ai/details/publication/pub.1100200196
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1111/gcbb.12030 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004873573
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1371/journal.pone.0176884 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085394137
143 rdf:type schema:CreativeWork
144 https://www.grid.ac/institutes/grid.39953.35 schema:alternateName Indian Statistical Institute
145 schema:name Agricultural and Ecological Research Unit, Indian Statistical Institute, 700108, Kolkata, West Bengal, India
146 Agricultural and Ecological Research Unit, Indian Statistical Institute, 815301, Giridih, Jharkhand, India
147 rdf:type schema:Organization
148 https://www.grid.ac/institutes/grid.419487.7 schema:alternateName Maulana Azad National Institute of Technology
149 schema:name Department of Physics, National Institute of Technology, 831014, Jamshedpur, Jharkhand, India
150 rdf:type schema:Organization
 




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


...