Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
94
datasets available to search
ShareScore release 0.9.0
Dataset results
94 results for “nanomaterials”
Figure 4 from: Loukanov A, Nikolova S, Filipov C, Nakabayashi S (2019) Nanomaterials for cancer medication: from individual nanoparticles toward nanomachines and nanorobots. Pharmacia 66(3): 147-156. https://doi.org/10.3897/pharmacia.66.e37739
Figure 4 (A) Schematic illustration on the fabrication and (B) electron microscopic image of doxorubicin@gold/mesoporous silica nanoparticles. The nanoparticles are prepared in dual surfactant system using classic fast self-assembling method containing both cationic and non-ionic surfactants. Scale bar: 50 nm.
Figure 3 from: Loukanov A, Nikolova S, Filipov C, Nakabayashi S (2019) Nanomaterials for cancer medication: from individual nanoparticles toward nanomachines and nanorobots. Pharmacia 66(3): 147-156. https://doi.org/10.3897/pharmacia.66.e37739
Figure 3 Electron microscopic images of gold nanoparticles with 5~10 nm diameter coated with (A) antibody IgG (Miao et al. 2018) and with (B) aptamer DNA (Loukanov et al. 2016a, b). Scale bar: 100 nm (A, B).
Figure 2 from: Loukanov A, Nikolova S, Filipov C, Nakabayashi S (2019) Nanomaterials for cancer medication: from individual nanoparticles toward nanomachines and nanorobots. Pharmacia 66(3): 147-156. https://doi.org/10.3897/pharmacia.66.e37739
Figure 2 Multilamellar liposome (A) or vesicles as self-assembled nano-drug carriers (B) of photosensitizer drugs for photodynamic therapy application. Scale bars: 5 µm (A, B).
Figure 1 from: Loukanov A, Nikolova S, Filipov C, Nakabayashi S (2019) Nanomaterials for cancer medication: from individual nanoparticles toward nanomachines and nanorobots. Pharmacia 66(3): 147-156. https://doi.org/10.3897/pharmacia.66.e37739
Figure 1 Overview of established nanoparticles for clinic use. (A) Various types nanoparticles used as nanocarrier platforms for cancer medication. (B) Timeline progress of the remarkable nano-medications in oncology.
Figure 6 from: Loukanov A, Nikolova S, Filipov C, Nakabayashi S (2019) Nanomaterials for cancer medication: from individual nanoparticles toward nanomachines and nanorobots. Pharmacia 66(3): 147-156. https://doi.org/10.3897/pharmacia.66.e37739
Figure 6 Light-powered nanomachine for inhibition of cancer cells. (A) TEM image and (B) schematic model of the nanomachine and principle of operation of the NIR-activated nanoconverter. The cancer cells are inhibited only in photodynamic regime of treatment. Scale bar: 10 nm.
Figure 5 from: Loukanov A, Nikolova S, Filipov C, Nakabayashi S (2019) Nanomaterials for cancer medication: from individual nanoparticles toward nanomachines and nanorobots. Pharmacia 66(3): 147-156. https://doi.org/10.3897/pharmacia.66.e37739
Figure 5 Transmission electron micrographs of nanoparticles chemically conjugated to peptides for cancer nanovaccination: (A) positive and (B) negative staining with uranyl acetate. Schematic illustration of the stained nanoparticles. Scale bar: 20 nm (A), 50 nm (B).
Data from: Structural and catalytic properties of copper silicate nanomaterials
<p><span>Nanosized copper silicates with three different structural morphology (amorphous, nanotubes and MEL) were prepared using different synthesis methods. The physico-chemical properties of copper silicates were characterized by XRD, FT-IR, SEM, HRTEM, N<sub>2</sub>-physisorption, XPS and H<sub>2</sub>-TPR techniques. The results indicated that the preparation conditions affect reduction behavior and textural properties of nanosized copper silicates. Hydrothermal synthesis method yielded chrysocolla-like CuSiO<sub>3</sub> nanotubes, which possessed high surface area and pore volume with easy reducibility. The catalytic performances of synthesized copper silicate nanostructures were evaluated for dehydrogenation of methanol.<b> </b>It was found that dehydrogenation activity is depended on the structural properties of copper silicates. Highest activity was observed for copper silicates with nanotube morphology. Catalytic dehydrogenation activity of copper silicates was also related to presence of more number of Cu-O-Si species, easy reducibility and Lewis acid centers. The CuSiO<sub>3</sub> nanotubes sample also exhibited good stability under investigated reaction conditions that deactivation was not detected for 48 h.</span></p>
Data from: Effects of carbon-based nanomaterials on seed germination, biomass accumulation and salt stress response of bioenergy crops
Bioenergy crops are an attractive option for use in energy production. A good plant candidate for bioenergy applications should produce a high amount of biomass and resist harsh environmental conditions. Carbon-based nanomaterials (CBNs) have been described as promising seed germination and plant growth regulators. In this paper, we tested the impact of two CBNs: graphene and multi-walled carbon nanotubes (CNTs) on germination and biomass production of two major bioenergy crops (sorghum and switchgrass). The application of graphene and CNTs increased the germination rate of switchgrass seeds and led to an early germination of sorghum seeds. The exposure of switchgrass to graphene (200 mg/l) resulted in a 28% increase of total biomass produced compared to untreated plants. We tested the impact of CBNs on bioenergy crops under salt stress conditions and discovered that CBNs can significantly reduce symptoms of salt stress imposed by the addition of NaCl into the growth medium. Using an ion selective electrode, we demonstrated that the concentration of Na+ ions in NaCl solution can be significantly decreased by the addition of CNTs to the salt solution. Our data confirmed the potential of CBNs as plant growth regulators for non-food crops and demonstrated the role of CBNs in the protection of plants against salt stress by desalination of saline growth medium.
Raw data used for the preparation of the article Nanomaterials 2021, 11, 2020. DOI: 10.3390/nano11082020
<p>Raw data (SEM, XRD, AFM, magnetotransport) used for the preparation of the article R. Sondors, G. Kunakova, L. Jasulaneca, J. Andzane, E. Kauranens, M. Bechelany, and D. Erts, <em>High-Yield Growth and Tunable Morphology of Bi<sub>2</sub>Se<sub>3</sub> Nanoribbons Synthesized on Thermally Dewetted Au</em>, Nanomaterials 11, (2021). DOI: 10.3390/nano11082020</p>
Nanomaterials-Support information
Open the record for dataset details and reuse information.
Videos for Nanomaterials Submission
<p>These videos are the supplementary files for an accepted article to Nanomaterials.</p>
Data from: Effects of carbon-based nanomaterials on seed germination, biomass accumulation and salt stress response of bioenergy crops
Open the record for dataset details and reuse information.
Data from: Structural and catalytic properties of copper silicate nanomaterials
Open the record for dataset details and reuse information.
Data from: Adsorption of Cd(II) in water by mesoporous ceramic functional nanomaterials
Open the record for dataset details and reuse information.
Mechanisms of (photo)toxicity of TiO2 nanomaterials (NM103, NM104, NM105): using high-throughput gene expression in Enchytraeus crypticus
GEO Series GSE81699. Enchytraeus crypticus. 30 samples. Type: Expression profiling by array.
Transcriptional profiling to identify physical-chemical properties detrimental to nanomaterial-induced pulmonary response (part 1)
GEO Series GSE60797. Mus musculus. 70 samples. Type: Expression profiling by array.
Transcriptional profiling to identify physical-chemical properties detrimental to nanomaterial-induced pulmonary response
GEO Series GSE60801. Mus musculus. 278 samples. Type: Expression profiling by array.
Single-cell mass cytometry reveals the impact of graphene nanomaterials with human primary immune cells
GEO Series GSE99929. Homo sapiens. 18 samples. Type: Expression profiling by array.
Protein Fe-S centers as a molecular target of toxicity of a complex transition metal oxide nanomaterial with downstream impacts on metabolism and growth
GEO Series GSE161036. Chironomus riparius. 20 samples. Type: Expression profiling by array.
Transcriptional profiling to identify physical-chemical properties detrimental to nanomaterial-induced pulmonary response (part 4)
GEO Series GSE60800. Mus musculus. 70 samples. Type: Expression profiling by array.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.