TY - JOUR A1 - Ahmed, A. A. A. A1 - Alegret, N. A1 - Almeida, B. A1 - Alvarez-Puebla, R. A1 - Andrews, A. M. A1 - Ballerini, L. A1 - Barrios-Capuchino, J. J. A1 - Becker, C. A1 - Blick, R. H. A1 - Bonakdar, S. A1 - Chakraborty, I. A1 - Chen, X. A1 - Cheon, J. A1 - Chilla, G. A1 - Conceicao, A. L. C. A1 - Delehanty, J. A1 - Dulle, M. A1 - Efros, A. L. A1 - Epple, M. A1 - Fedyk, M. A1 - Feliu, N. A1 - Feng, M. A1 - Fernandez-Chacon, R. A1 - Fernandez-Cuesta, I. A1 - Fertig, N. A1 - Förster, S. A1 - Garrido, J. A. A1 - George, M. A1 - Guse, A. H. A1 - Hampp, N. A1 - Harberts, J. A1 - Han, J. A1 - Heekeren, H. R. A1 - Hofmann, U. G. A1 - Holzapfel, M. A1 - Hosseinkazemi, H. A1 - Huang, Y. A1 - Huber, P. A1 - Hyeon, T. A1 - Ingebrandt, S. A1 - Ienca, M. A1 - Iske, A. A1 - Kang, Y. A1 - Kasieczka, G. A1 - Kim, D.-H. A1 - Kostarelos, K. A1 - Lee, J.-H. A1 - Lin, K.-W. A1 - Liu, S. A1 - Liu, X. A1 - Liu, Y. A1 - Lohr, C. A1 - Mailänder, V. A1 - Maffongelli, L. A1 - Megahed, S. A1 - Mews, A. A1 - Mutas, M. A1 - Nack, L. A1 - Nakatsuka, N. A1 - Oertner, T. G. A1 - Offenhäusser, A. A1 - Oheim, M. A1 - Otange, B. A1 - Otto, F. A1 - Patrono, E. A1 - Peng, B. A1 - Picchiotti, A. A1 - Pierini, F. A1 - Pötter-Nerger, M. A1 - Pozzi, M. A1 - Pralle, A. A1 - Prato, M. A1 - Qi, B. A1 - Ramos-Cabrer, P. A1 - Resch-Genger, Ute A1 - Ritter, N. A1 - Rittner, M. A1 - Roy, S. A1 - Santoro, F. A1 - Schuck, N. W. A1 - Schulz, F. A1 - Seker, E. A1 - Skiba, M. A1 - Sosniok, M. A1 - Stephan, H. A1 - Wang, R. A1 - Wang, T. A1 - Wegner, Karl David A1 - Weiss, P. S. A1 - Xu, M. A1 - Yang, C. A1 - Zargarin, S. S. A1 - Zeng, Y. A1 - Zhou, Y. A1 - Zhu, D. A1 - Zierold, R. A1 - Parak, W. J. T1 - Interfacing with the Brain: How Nanotechnology Can Contribute N2 - 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. 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. KW - Nanoneuro interface KW - Brain-on-a-chip KW - Nanostructured interface KW - Electrode arrays KW - Neuro-implants KW - Advanced nanomaterials KW - Quality assurance PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-634893 DO - https://doi.org/10.1021/acsnano.4c10525 SN - 1936-086X VL - 19 IS - 11 SP - 10630 EP - 10717 PB - ACS Publications AN - OPUS4-63489 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Meng, M. A1 - Zhang, T. A1 - Wang, J. A1 - Cheng, Z. A1 - Yang, J. A1 - Qiao, X. A1 - Wen, J. A1 - Resch-Genger, Ute A1 - Ou, J. T1 - Fluorescence temperature sensing of NaYF4:Yb3+/Tm3+@NaGdF4:Nd3+/Yb3+ nanoparticles at low and high temperatures N2 - NaYF4:Yb3+/Tm3+@NaGdF4:Nd3+/Yb3+ upconversion nanoparticles (UCNPs) were prepared using a solvothermal method, and the effects of key factors such as the content of sensitiser Nd 3+ and Yb3+ on their luminescence properties were investigated. The nanoparticles are homogeneous in size and well dispersed. Under 808 nm excitation, it can produce strong upconversion fluorescence. At the same time, the nanoparticles have good temperature-sensing properties at the thermally coupled energy levels of 700 nm and 646 nm for Tm3+. Using its fluorescence intensity ratio (FIR), accurate temperature measurements can be performed, and it has been found that it exhibits different temperature sensing properties in low and high-temperature regions. The maximum relative sensitivity was found to be 0.88% K-1 and 1.89% K-1 for the lowtemperature region of 285 K-345 K and the high-temperature region of 345 K-495 K. The nanoparticles were applied to the internal temperature measurement of lithium batteries and the actual high-temperature environment, respectively, and were found to have good temperature measurementt performance. KW - Fluorescence KW - Sensor KW - Temperature KW - Ratiometric KW - Lanthanide KW - Quantum yield KW - Integrating sphere spectroscopy KW - Absolute fluorescence KW - Quality assurance KW - Nano KW - Particle KW - Application KW - Upconversion nanoparticle PY - 2022 DO - https://doi.org/10.1088/1361-6528/ac84e4 SN - 1361-6528 VL - 33 IS - 34 SP - 1 EP - 15 PB - IOP Publishing CY - Bristol AN - OPUS4-55454 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Rezvani, A. A1 - Wang, Z. A1 - Wegner, Karl David A1 - Soltanmoradi, H. A1 - Kichigin, A. A1 - Zhou, X. A1 - Gantenberg, T. A1 - Schram, J. A1 - Zubiri, B. A. A1 - Spiecker, E. A1 - Walter, J. A1 - Resch-Genger, Ute A1 - Segets, D. T1 - Separation of Indium Phosphide/Zinc Sulfide Core−Shell Quantum Dots from Shelling Byproducts through Multistep Agglomeration N2 - Semiconductor quantum dots (QDs) possess unique electronic and optical properties, making them promising candidates for applications in lightemitting diodes, solar cells, bioimaging, and photocatalysis. Precise control over their size, shape, and chemical and electronic structure is crucial to ensure the desired functional properties and optimize device performance. However, challenges in QD synthesis and post-synthesis modification persist, especially in large-scale production. This study addresses the classification of QDs synthesized in a tubular flow reactor consisting of a mixture of the desired InP/ZnS core−shell QDs and QDs made from the shell material, i.e., here ZnS QDs formed as a byproduct during the formation step of the ZnS shell. The homogeneous nucleation of ZnS nanoparticles from the shelling material introduces a heterogeneity in size and composition and affects the optical properties of the resulting QDs. To address this issue, we developed a size-selective agglomeration (SSA) technique by incrementally introducing ethanol as a poor solvent and classified the synthesized QDs into 13 distinct fractions. These 13 fractions are sorted into three distinct groups: (i) larger InP/ZnS QDs, (ii) a combination of smaller InP/ZnS QDs and larger ZnS QDs, and (iii) predominant ZnS QDs with some very tiny InP/ZnS QDs. The comprehensive characterization of the fractions was conducted using UV−visible absorption spectroscopy, photoluminescence spectroscopy, high-resolution scanning transmission electron microscopy, energy-dispersive X-ray spectroscopy, total reflection X-ray fluorescence, and analytical ultracentrifugation. We could demonstrate that our method effectively separated unwanted ZnS QDs from the target InP/ZnS QDs. In addition, the fractions enriched in smaller InP/ZnS QDs exhibited a higher photoluminescence quantum yield compared to the fractions with larger QDs. This demonstrates the efficacy of SSA in finetuning the composition of QD mixtures produced on a larger scale to improve their functional properties. This approach provides fundamental understanding toward the development of a scalable two-dimensional classification process for such ultrasmall nanoparticles by particle size and composition. KW - Quality assurance KW - Reference material KW - Nano KW - Particle KW - Quantum dot KW - Synthesis KW - Flow reactor KW - InP KW - Shell KW - ZnS KW - Surface chemistry KW - Method KW - Fluorescence KW - Quantum yield KW - TEM PY - 2025 DO - https://doi.org/10.1021/acsnano.4c18530 SN - 1936-086X VL - 19 IS - 20 SP - 19080 EP - 19094 PB - ACS Publications AN - OPUS4-63215 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -