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    <id>63489</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
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    <language>eng</language>
    <pageFirst>10630</pageFirst>
    <pageLast>10717</pageLast>
    <pageNumber/>
    <edition/>
    <issue>11</issue>
    <volume>19</volume>
    <type>article</type>
    <publisherName>ACS Publications</publisherName>
    <publisherPlace/>
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    <belongsToBibliography>1</belongsToBibliography>
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    <title language="eng">Interfacing with the Brain: How Nanotechnology Can Contribute</title>
    <abstract language="eng">Interfacing artificial devices with the human brain is the central goal of neurotechnology. Yet, our imaginations are often limited by currently available paradigms and technologies. Suggestions for brain−machine interfaces have changed over time, along with the available technology.&#13;
Mechanical levers and cable winches were used to move parts of the brain during the mechanical age. Sophisticated electronic wiring and remote control have arisen during the electronic age, ultimately leading to plug-and-play computer interfaces. Nonetheless, our brains are so complex that these visions, until recently, largely remained unreachable dreams. The general problem, thus far, is that most of our technology is mechanically and/or electrically engineered, whereas the brain is a living, dynamic entity. As a result, these worlds are difficult to interface with one another. Nanotechnology, which encompasses engineered solid-state objects and integrated circuits, excels at small length scales of single to a few hundred nanometers and, thus, matches the sizes of biomolecules, biomolecular assemblies, and parts of cells. Consequently, we envision nanomaterials and nanotools as opportunities to interface with the brain in alternative ways. Here, we review the existing literature on the use of nanotechnology in brain−machine interfaces and look forward in discussing perspectives and limitations based on the authors’ expertise across a range of complementary disciplines from neuroscience, engineering, physics, and chemistry to biology and medicine, computer science and mathematics, and social science and jurisprudence. We focus on nanotechnology but also include information from related fields when useful and complementary.</abstract>
    <parentTitle language="eng">ACS Nano</parentTitle>
    <identifier type="doi">10.1021/acsnano.4c10525</identifier>
    <identifier type="issn">1936-086X</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-634893</identifier>
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    <enrichment key="date_peer_review">26.06.2025</enrichment>
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    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>A. A. A. Ahmed</author>
    <author>N. Alegret</author>
    <author>B. Almeida</author>
    <author>R. Alvarez-Puebla</author>
    <author>A. M. Andrews</author>
    <author>L. Ballerini</author>
    <author>J. J. Barrios-Capuchino</author>
    <author>C. Becker</author>
    <author>R. H. Blick</author>
    <author>S. Bonakdar</author>
    <author>I. Chakraborty</author>
    <author>X. Chen</author>
    <author>J. Cheon</author>
    <author>G. Chilla</author>
    <author>A. L. C. Conceicao</author>
    <author>J. Delehanty</author>
    <author>M. Dulle</author>
    <author>A. L. Efros</author>
    <author>M. Epple</author>
    <author>M. Fedyk</author>
    <author>N. Feliu</author>
    <author>M. Feng</author>
    <author>R. Fernandez-Chacon</author>
    <author>I. Fernandez-Cuesta</author>
    <author>N. Fertig</author>
    <author>S. Förster</author>
    <author>J. A. Garrido</author>
    <author>M. George</author>
    <author>A. H. Guse</author>
    <author>N. Hampp</author>
    <author>J. Harberts</author>
    <author>J. Han</author>
    <author>H. R. Heekeren</author>
    <author>U. G. Hofmann</author>
    <author>M. Holzapfel</author>
    <author>H. Hosseinkazemi</author>
    <author>Y. Huang</author>
    <author>P. Huber</author>
    <author>T. Hyeon</author>
    <author>S. Ingebrandt</author>
    <author>M. Ienca</author>
    <author>A. Iske</author>
    <author>Y. Kang</author>
    <author>G. Kasieczka</author>
    <author>D.-H. Kim</author>
    <author>K. Kostarelos</author>
    <author>J.-H. Lee</author>
    <author>K.-W. Lin</author>
    <author>S. Liu</author>
    <author>X. Liu</author>
    <author>Y. Liu</author>
    <author>C. Lohr</author>
    <author>V. Mailänder</author>
    <author>L. Maffongelli</author>
    <author>S. Megahed</author>
    <author>A. Mews</author>
    <author>M. Mutas</author>
    <author>L. Nack</author>
    <author>N. Nakatsuka</author>
    <author>T. G. Oertner</author>
    <author>A. Offenhäusser</author>
    <author>M. Oheim</author>
    <author>B. Otange</author>
    <author>F. Otto</author>
    <author>E. Patrono</author>
    <author>B. Peng</author>
    <author>A. Picchiotti</author>
    <author>F. Pierini</author>
    <author>M. Pötter-Nerger</author>
    <author>M. Pozzi</author>
    <author>A. Pralle</author>
    <author>M. Prato</author>
    <author>B. Qi</author>
    <author>P. Ramos-Cabrer</author>
    <author>Ute Resch-Genger</author>
    <author>N. Ritter</author>
    <author>M. Rittner</author>
    <author>S. Roy</author>
    <author>F. Santoro</author>
    <author>N. W. Schuck</author>
    <author>F. Schulz</author>
    <author>E. Seker</author>
    <author>M. Skiba</author>
    <author>M. Sosniok</author>
    <author>H. Stephan</author>
    <author>R. Wang</author>
    <author>T. Wang</author>
    <author>Karl David Wegner</author>
    <author>P. S. Weiss</author>
    <author>M. Xu</author>
    <author>C. Yang</author>
    <author>S. S. Zargarin</author>
    <author>Y. Zeng</author>
    <author>Y. Zhou</author>
    <author>D. Zhu</author>
    <author>R. Zierold</author>
    <author>W. J. Parak</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Nanoneuro interface</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Brain-on-a-chip</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Nanostructured interface</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Electrode arrays</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Neuro-implants</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Advanced nanomaterials</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Quality assurance</value>
    </subject>
    <collection role="ddc" number="620">Ingenieurwissenschaften und zugeordnete Tätigkeiten</collection>
    <collection role="ddc" number="628">Sanitär- und Kommunaltechnik; Umwelttechnik</collection>
    <collection role="institutes" number="">1 Analytische Chemie; Referenzmaterialien</collection>
    <collection role="institutes" number="">1.2 Biophotonik</collection>
    <collection role="themenfelder" number="">Umwelt</collection>
    <collection role="themenfelder" number="">Material</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
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    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
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    <collection role="themenfelder" number="">Sensorik</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/63489/QD Neuron_ASC Nano_2025.pdf</file>
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  <doc>
    <id>65061</id>
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    <publishedYear>2025</publishedYear>
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    <language>eng</language>
    <pageFirst>S281</pageFirst>
    <pageLast>S282</pageLast>
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    <issue/>
    <volume>411</volume>
    <type>article</type>
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    <title language="eng">Knowledge Infrastructure supporting image-based characterisation of 2D graphene materials</title>
    <abstract language="eng">As part of the European Horizon ACCORDs project, advanced methods are being developed for the image-based characterisation of 2D nanomaterials. Given the complexity of this task, robust  nd wellorganised data management is critical to ensuring high-quality outcomes. To support this, we have established a knowledge infrastructure that serves as the central repository for protocols, images and experimental data which are stored in a standardised, harmonised manner and in accordance with the FAIR principles – Findable, Accessible, Interoperable and Reusable and open science. This machine-readable framework enables the systematic and computationally automated correlation of image features with experimental descriptors, facilitating accurate material characterisation and transparent reporting which is all integrated in the ACCORDs KI.</abstract>
    <parentTitle language="eng">Toxicology Letters</parentTitle>
    <identifier type="issn">0378-4274</identifier>
    <identifier type="doi">10.1016/j.toxlet.2025.07.660</identifier>
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    <author>P. P. Ankli</author>
    <author>A. A. Abdelwahab</author>
    <author>A. Logachov</author>
    <author>R. Bugiel</author>
    <author>D. Drobne</author>
    <author>S. Novak</author>
    <author>E. Kranjc</author>
    <author>S. Saje</author>
    <author>F. Pellegrino</author>
    <author>E. Alladio</author>
    <author>F. Sordello</author>
    <author>E. Corrao</author>
    <author>Vasile-Dan Hodoroaba</author>
    <author>Jörg Radnik</author>
    <author>Paul Mrkwitschka</author>
    <author>Loay Akmaal Madbouly</author>
    <author>Yücel Akdemir</author>
    <author>M. Gulumian</author>
    <author>V. Wepener</author>
    <author>C. Andraos</author>
    <author>K. Boodhia</author>
    <author>E. Jones</author>
    <author>A. Doolin</author>
    <author>K. Leuchtenberg</author>
    <author>E. Valsami Jones</author>
    <author>C. Rocca</author>
    <author>B. Ibrahim</author>
    <author>D. Singh</author>
    <author>S. Chakraborty</author>
    <author>K. Jurkschat</author>
    <author>C. Johnston</author>
    <author>M. Van Der Zande</author>
    <author>D. Fernandez</author>
    <author>P. Queipo</author>
    <author>C. Clifford</author>
    <author>B. Hardy</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Graphene-related 2D materials (GR2M)</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>2D materials</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Knowledge infrastructure</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Characterisation</value>
    </subject>
    <collection role="ddc" number="620">Ingenieurwissenschaften und zugeordnete Tätigkeiten</collection>
    <collection role="institutes" number="">6 Materialchemie</collection>
    <collection role="institutes" number="">6.1 Oberflächen- und Dünnschichtanalyse</collection>
    <collection role="themenfelder" number="">Material</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="themenfelder" number="">Advanced Materials</collection>
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