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23 results for “block copolymers”
Research data supporting "Block copolymer-directed single diamond hybrid structures derived from X-ray nanotomography"
<p>Research data supporting "Block copolymer-directed single diamond hybrid structures derived from X-ray nanotomography"</p>
Artificial fingerprints engraved through block-copolymers as nanoscale physical unclonable functions for authentication and identification - Dataset
<p>This is the dataset of "Artificial fingerprints engraved through block-copolymers as nanoscale physical unclonable functions for authentication and identification" by Irdi Murataj, Chiara Magosso, Stefano Carignano, Matteo Fretto, Federico Ferrarese Lupi, and Gianluca Milano, Nature Communications (2024), DOI: 10.1038/s41467-024-54492-8</p> <p>Part of this was funded by the project MEMQuD, code 20FUN06. The project has received funding from the EMPIR program co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation program.</p> <p>Part of this work was supported by the European project OpMetBat, code 21GRD01. The project has received funding from the European Partnership on Metrology, cofinanced from the the European Union's Horizon Europe Research and Innovation Programme, and by Participating States.</p> <p>Part of this work was supported by the European Union - Next Generation EU under the National Recovery and Resilience Plan (NRRP), Mission 04 Component 2 Investment 3.1 | Project Code: IR0000027 - CUP: B33C22000710006 - iENTRANCE@ENL: Infrastructure for Energy TRAnsition aNd Circular Economy @EuroNanoLab.</p>
Antibacterial Hydrogel Adhesives based on Bifunctional Telechelic Dendritic-Linear-Dendritic Block Copolymers
<p><span>Antibiotic resistant pathogens have been declared by WHO as one of the major public health threats facing humanity.<span> </span>For that reason, there is an urgent need for materials with inherent antibacterial activity able to replace the use of antibiotics, and in this context, hydrogels have emerged as a promising strategy. Herein, we introduce the next generation of cationic hydrogels with antibacterial activity and high versatility that can be cured on demand in less than twenty seconds by using Thiolene Click Chemistry (TEC) in aqueous conditions. The approach capitalizes on a two-component system: i) telechelic polyester based Dendritic-Linear-Dendritic (DLDs) block copolymers of different generations heterofunctionalized with allyl and ammonium groups, as well as ii) polyethylene glycol (PEG) crosslinkers functionalized with thiol groups. These hydrogels resulted in highly tunable materials where the antibacterial performance can be adjusted by modifying the crosslinking density. Off-stoichiometric hydrogels showed narrow antibacterial activity directed towards Gram-negative bacteria. The presence of pending allyls opens up many possibilities for functionalization with biologically interesting molecules. <span> </span>As a proof-of-concept, hydrophilic cysteamine hydrochloride as well as N-hexyl-4-mercaptobutanamide, as an example of a thiol with a hydrophobic alkyl chain, generated three-component networks. In the case of cysteamine derivatives, a broader antibacterial activity was noted than the two-component networks, inhibiting also the growth of Gram-positive bacteria. Additionally, these systems presented high versatility, with storage modulus values ranging from 270 to 7024 Pa and different stability profiles ranging from 1 to 56 days in swelling experiments. Good biocompatibility towards skin cells as well as strong adhesion to multiple surfaces, place these hydrogels as interesting alternatives to conventional antibiotics.</span></p>
Dataset for Hyperbolic Optical Metamaterials from Shear-Aligned Block Copolymer Cylinder Arrays
<p>Research Data supporting “Hyperbolic Optical Metamaterials from Shear-Aligned Block Copolymer Cylinder Arrays”</p> <p>Published in Advanced Photonics Research</p> <p>doi: 10.1002/adpr.202000037</p>
Dataset: Design and Self-Assembly of Second-Generation Dendrimer-Like Block Copolymers
<p>This dataset contains processed data (data) and plotting scripts (plots) of the simulation related to the paper: </p> <p><br>F. Hartmann, R. Dockhorn, S. Pusse, B.-J. Niebuur, M. Koch, T. Kraus, A. Schießer, B. N. Balzer, and M. Gallei, <br>"Design and Self-Assembly of Second-Generation Dendrimer-Like Block Copolymers"<br>Macromolecules <strong>2024</strong>; DOI: <a href="https://doi.org/10.1021/acs.macromol.4c00944">10.1021/acs.macromol.4c00944</a></p> <p>Please consult the ReadMe.md in the zip.</p>
Block Copolymer-Assembled Nanopores Enable Ultra-Sensitive Label-Free DNA Detection
<p>Relevant datasets for scientific manuscript: </p> <p><strong>Block Copolymer-Assembled Nanopores Enable Ultra-Sensitive Label-Free DNA Detection </strong></p> <p>Maximiliano Jesus Jara Fornerod <span>a</span>, Alberto Alvarez-Fernandez <span>a</span>, Mate Furedi <span>a</span>, Anandapadmanabhan A Rajendran <span>b</span>, Beatriz Prieto-Simon <span>c,d</span>, Nicolas H. Voelcker <span>e,f*</span>, Stefan Guldin <span>a,g*</span></p> <p> </p> <p><em>a Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK. </em></p> <p><em>b Department of Electronic Engineering, Universitat Rovira i Virgili, 43007, Tarragona, Spain </em></p> <p><em>c Institute of Chemical Research of Catalonia, The Barcelona Institute of Science and Technology, Av. Països Catalans, 16, 43007, Tarragona, Spain </em></p> <p><em>d ICREA, Pg. Lluís Companys 23, 08010, Barcelona, Spain </em></p> <p><em>e Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia </em></p> <p><em>f Melbourne Centre for Nanofabrication, Victorian Node of the Australian National Fabrication Facility, Clayton, Victoria, 3168, Australia </em></p> <p><em>g Technical University of Munich, Department of Life Science Engineering, Gregor-Mendel-Straße 4, 85354 Freising, Germany </em></p> <p>*corresponding authors. E-mail addresses: nicolas.voelcker@monash.edu, s.guldin@ucl.ac.uk, guldin@tum.de</p>
Accelerated discovery and mapping of block copolymer phase diagrams
<p class="MsoNormal">Block copolymers are widely used in many applications due to their spontaneous self-assembly into a variety of nanoscale morphologies. However, a grand challenge in navigating this diverse and ever-growing array of possible structures is the accelerated discovery, design, and implementation of new materials. Here, we report a versatile and efficient strategy to accelerate materials discovery by rapidly building expansive, high-quality, and detailed block copolymer libraries through a combination of controlled polymerization and chromatographic separation. To illustrate the potential of this approach, a family of 16 parent diblock copolymers was synthesized and separated, leading to over 300 distinct and well-defined samples at the multigram scale. The resulting materials span a wide range of compositions with exceptional resolution in volume fraction and domain spacing that allows for the impact of monomer design on polymer self-assembly to be elucidated. Phase behavior that can be gleaned from these libraries includes the precise location of order–order boundaries and the identification of morphologies with extremely narrow windows of stability. This user-friendly, scalable, and automated approach to discovery significantly increases the availability of well-defined block copolymers with tailored molecular weights, molar-mass dispersities, compositions, and segregation strengths, accelerating the study of structure–property relationships in advanced soft materials.</p>
Photoinduced Morphology Change in Ionic Supramolecular Block Copolymer
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Accelerated discovery and mapping of block copolymer phase diagrams
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Data from: High-throughput generation of block copolymer libraries via click chemistry and automated chromatography
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Telechelic dithiol copolymers as tunable building blocks for synthesizing multiblock materials
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Supplemental Data for Cell Reports Physical Science article "Probing transference and field-induced polymer velocity in block copolymer electrolytes"
<p>The data and Jupyter notebook uploaded here is Supplemental Information for the article:</p><p><strong>Probing transference and field-induced polymer velocity in block copolymer electrolytes </strong></p><p>Coauthored by:</p><p>Michael D. Galluzzo, Hans-Georg Steinrück, Christopher J. Takacs, Aashutosh Mistry, Lorena S. Grundy, Chuntian Cao, Suresh Narayanan, Eric M. Dufresne, Qingteng Zhang, Venkat Srinivasan, Michael F. Toney, and Nitash P. Balsara.</p><p>Journal: Cell Reports Physical Science</p><p>Notes:</p><ul><li>This depository includes the experimental data used in Figure 2, 3, and 4 of the main text and an additional data set.</li><li>The Jupyter notebook "velocity_Echem_Data.ipynb' can be used to visualize the data in the .csv files provided in the folder 'echem' and 'XPCS_fits'.</li><li>The folder 'echem' contains the raw electrochemical data obtained from the two XPCS experiments discussed in the main text and an additional experiment set.</li><li>The folder 'XPCS_fits' contains the results of fitting the autocorrelation functions at each spatial position in the cell at each time point for the two XPCS experiments discussed in the main text and an additional experiment set. </li><li>The additional experiment included here (reffered to as Cell P in the Jupyter notebook) is not discussed in the main text, however it demonstrates that the second 'hump' in velocity (see Figure 3 and S5) that is observed after switching the direction of polarization was replicated in a separate experiment.</li></ul><p> </p>
Light-responsive block copolymers with a spiropyran located at the block junction
<p>Data of manuscript "Light-responsive block copolymers with a spiropyran located at the block junction", published by the European Polymer Journal.</p>
Dataset for "Machine Learning-Aided High Throughput Examination of Block Copolymer Processing Conditions"
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Synthesis and Complex Self-Assembly of Amphiphilic Block Copolymers with a Branched Hydrophobic Poly(2-oxazoline) into Multicompartment Micelles, Pseudovesicles and Yolk/Shell Nanoparticles
<p>Data underlying the figures in the publication “Synthesis and complex self-assembly of amphiphilic block copolymers with a branched hydrophobic poly(2-oxazoline) into multicompartment micelles, pseudovesicles and yolk/shell nanoparticles”, published in <em>Polym. Chem.</em>, <strong>2020</strong>, 11, 1237–1248. <a href="https://pubs.rsc.org/en/content/articlepdf/2020/py/c9py01559k">https://pubs.rsc.org/en/content/articlepdf/2020/py/c9py01559k</a></p> <p>Table of contents:</p> <p><strong>1. Figure 2_Kinetics</strong>; Origin file with the data for <em>Figure 2</em>, presenting the kinetics of polymerization of EHOx on PEO-Nos in Chlorobenzene and Acetonitrile. </p> <p><strong>2. Figure 3_GPC Trace</strong>; Origin file with the data for the GPC traces in <em>Figure 3</em>. It contains the exportation of the raw data from our GPC instrument, processing of the data (normalization) and the final illustration as a graphic. </p> <p><strong>3. Figure 4_DSC</strong>; Origin file with the data for <em>Figure 4.</em> It contains the exportation of all the DSC curves measured by our DSC and the final curves/graphic used.</p> <p><strong>4. Figure 5</strong>; Zip file containing all the different Cryo-TEM and TEM images used for <em>Figure 5 </em>with a precise label, please refer to Table 1 for the name of the polymers.</p> <p><strong>5. Figure 7_Self-assembly</strong>; Origin file with the data for <em>Figure 7</em>. It contains all the data from the deblocks used in this publication and gathered it in the corresponding graph. Labels were added later by Powerpoint.</p> <p><strong>6. Table 1</strong>; Excel file that contains all the various information about the different polymers used in this publication that were obtained by NMR, GPC. (Cf Materials and Methods)</p> <p><strong>7. Table 2</strong>; Excel file that contains all the various information about DLS/SLS of the various self-assemblies by film rehydration and solvent switch.</p> <p><strong>8. SI Dataset</strong>; Zip file that contains all the various TEM and Cryo-TEM images in jpg/tif and in higher resolution, the extra DSC diblocks curves as well as the calculation of dn/dc used in the Supplementary Information.</p> <p> </p>
Raw data for 'Poly(sitosterol)-Based Hydrophobic Blocks in Amphiphilic Block Copolymers for the Assembly of Hybrid Vesicles'
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Block copolymer micelles as colloidal catalysts for photocatalytic NAD+ reduction
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Expanding the Potential of the Solvent-Assisted Method to CreateBio-Interfaces from Amphiphilic Block Copolymers
<p>Data underlying the figures in the publication “Expanding the Potential of the Solvent-Assisted Method to Create Bio-Interfaces from Amphiphilic Block Copolymers”, published in <em>Biomacromolecules, </em><strong>2021</strong><em>. <a href="https://doi.org/10.1021/acs.biomac.1c00424">https://doi.org/10.1021/acs.biomac.1c00424</a></em></p> <p>Table of contents:</p> <p><strong>1. Figure 1</strong>; Zip file containing the QCM-D data in <em>.qsd</em> format for <em>Figure 1</em>.</p> <p><strong>2. Figure 2_AFM</strong>; Zip file containing the AFM images for <em>Figure 2</em>.</p> <p><strong>3. Figure 3</strong>; Zip file containing the QCM-D data in <em>.qsd</em> format for <em>Figure 3</em>.</p> <p><strong>4. Figure 4</strong>; Zip file containing the QCM-D data in <em>.xls</em> format for <em>Figure 4</em>.</p> <p><strong>5. Figure 5</strong>; Zip file containing the QCM-D data in <em>.qsd</em> format for <em>Figure 5</em>.</p> <p><strong>6. Figure 6_Fluorimetry</strong>; Zip file containing the data in <em>.qsd</em> format for <em>Figure 6</em>.</p>
Research Data supporting "Photonic particles made by the confined self-assembly of a supramolecular comb-like block copolymer"
<p><strong>Research Data supporting “</strong><strong>Photonic particles made by the confined self-assembly of a supramolecular comb-like block copolymer</strong><strong>”</strong></p> <p><strong><em>Macromolecular Rapid Communications,</em></strong> doi: 10.1002/marc.202100522</p> <p>The data is arranged into different folders (.zip file), containing the following files (.txt, .tif, etc.; <em>italics</em>). This data and the descriptions below should be read in conjunction with the manuscript and “Supporting Info”, both of which may be found at the following DOI: <a href="https://doi.org/10.1002/marc.202100522">https://doi.org/10.1002/marc.202100522</a></p>
Block copolymer binders with hard and soft segments for scalable fabrication of sulfide-based all-solid-state batteries
<p>Sulfide-based all-solid-state batteries (ASSBs) have attracted much attention owing to their superior safety and potentially high-energy density. Nevertheless, sulfide-based ASSBs suffer from limited performance in terms of their cycle life and rate capability, which is closely related to interfacial degradation during cycling. Another weakness is the absence of manufacturing protocols. Having noted that the binder can play a pivotal role in both the cell performance and scale-up, here, we report poly(1,2-butadiene)-<em>b</em>-poly(methyl methacrylate) (PBD-<em>b</em>-PMMA) block copolymers as the binders. At the optimal ratio, the soft PBD segments and hard PMMA segments work synergistically to strengthen adhesion among particles in the electrode and introduce elasticity in the binder network, enabling the key battery performance indicators to be improved markedly. The systematic study also reveals the importance of the microscopic distributions of these two segments. This study signifies the appropriate combination of adhesion and elasticity in designing binders for sulfide-based ASSBs.</p>
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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)
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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.