Find research datasets worth reusing

opencc-by-4.0Feb 2022View details →

Data for 'Formalizing Artisanal and Small-scale Gold Mining: a Grand Challenge of the Minamata Convention'

Signatories to the Minamata Convention on Mercury with ‘more than insignificant’ artisanal and small-scale gold mining (ASGM) sectors are required to develop and implement National Action Plans (NAPs) to reform their ASGM sectors in line with Annexe C of the Convention. We compiled the budgets of available NAPs for reducing mercury emissions from ASGM sectors. As of 2021-12-31, these were available for 16 countries from: www.mercuryconvention.org/en/parties/national-action-plans. We used these data to estimate the approximate costs of expanding such approaches globally.

opencc-by-4.0Feb 2022View details →

GAP interatomic potential for gold

Gaussian approximation potential (GAP) for gold [1]. It has been fitted with QUIP/GAP [1,2] by generating a new database of atomic structures containing: <ol> <li>dimers;</li> <li>fcc, bcc, hcp and simple-cubic supercells, including strained, distorted and high-temperature configurations;</li> <li>surface slabs;</li> <li>clusters.</li> </ol> The calculations were carried out at the PBE level of theory [3] using the VASP code [4,5]. This potential uses 2-body (distance_2b) and SOAP-type descriptors (soap_turbo) [6,7], as implemented in the TurboGAP code [8]. The files can be used both with QUIP/GAP (compiled with the soap_turbo libraries) and TurboGAP. When using this potential, please read and cite: <blockquote> J. Kloppenburg, A. Pedersen, K. Laasonen, M. A. Caro, and H. Jónsson "Reassignment of magic numbers for icosahedral Au clusters: 310, 564, 928 and 1426" <a href="https://doi.org/10.1039/D2NR01763F">Nanoscale 14, 9053 (2022)</a> </blockquote> References <ol> <li>A.P. Bartók, M.C. Payne, R. Kondor, and G. Csányi. Phys. Rev. Lett. 104, 136403 (2010).</li> <li>LibAtoms: <a href="https://libatoms.github.io/">https://libatoms.github.io</a></li> <li>J.P. Perdew, K. Burke and M. Ernzerhof. Phys. Rev. Lett. 77, 3865 (1996).</li> <li>VASP: <a href="http://vasp.at/">http://vasp.at</a></li> <li>G. Kresse and J. Furthmüller. Phys. Rev. B 54, 11169 (1996).</li> <li>A.P. Bartók, R. Kondor, and G. Csányi. Phys. Rev. B 87, 184115 (2013).</li> <li>M.A. Caro. Phys. Rev. B 100, 024112 (2019).</li> <li>TurboGAP: <a href="http://turbogap.fi/">http://turbogap.fi</a></li> </ol>

opencc-by-4.0Mar 2022View details →

DataSet: Structural and optical properties of gold nanosponges revealed via 3D nano-reconstruction and phase-field models

These are the main raw and processed data for the publication "Structural and optical properties of gold nanosponges revealed via 3D nano-reconstruction and phasefield models". Abstract: Nanoporous gold nanoparticles are subject of intensive research due to their unique morphology, which leads to electric field localizations generating a strongly nonlinear optical response, allowing a wide range of applications. However, accurate predictions of physical properties require detailed knowledge of the sponges’ chaotic nanometer-sized geometrical structures, posing a metrological challenge. Therefore, a main goal is to obtain computer models with equivalent structural and optical properties. To understand the sponges’ morphology, a procedure for their accurate three-dimensional reconstruction using focused ion beam tomography is presented. Next, a small number of morphological key parameters is derived that sufficiently characterize the complex topology. Additionally, a new simulation method for the computer-aided creation of finite-sized sponges with adjustable geometric properties is presented. It is shown that if certain morphological parameters are similar for computer-generated and experimental sponges, their optical response, including number and locations of field localizations, are also similar. Finally, the anisotropy of the experimental sponges is analyzed and an easy-to-use procedure to replicate arbitrary anisotropies in computer-generated sponges is presented.

opencc-by-4.0Apr 2022View details →

DLCC Gold Standard

Corresponding GitHub repository: <a href="https://github.com/janothan/DL-TC-Generator">DL-TC-Generator on GitHub</a>   Abstract Knowledge graph embedding is a representation learning technique which projects entities and relations in a knowledge graph to continuous vector spaces. Embeddings have gained a lot of uptake and have been heavily used in link prediction and other downstream prediction tasks. Most approaches are evaluated on a single task or a single group of tasks to determine their overall performance. The evaluation is then assessed in terms of how well the embedding approach performs on the task at hand, but it is hardly evaluated (and often not even deeply understood) what information the embedding approaches are actually learning to represent. To fill this gap, we present the DLCC (Description Logic Class Constructors) benchmark, a resource to analyze embedding approaches in terms of which kinds of classes they can represent. Two gold standards are presented, one based on the real world knowledge graph DBpedia, and one synthetic gold standard.

Chemical activities of platinum and gold under a hydrous condition at high pressure with implication for deep volatile storage

This file contains published datasets for "Chemical activities of platinum and gold under a hydrous condition at high pressure with implication for deep volatile storage"

Gold Nanoparticles Synthesized in the Presence of Peptides - UV-Vis Spectra, Fluorescence, USAXS, Electron Microscopy

Content Summary: <ul> <li>Data from experiments in which gold nanoparticles were synthesized in the presence of peptides using a liquid-handling robot. Samples were analyzed using UV-Vis spectroscopy, fluorescence emission, USAXS, TEM, and SEM. </li> <li>Notebooks for loading and plotting data</li> <li>Code for synthesizing samples using an OT2 Opentrons liquid-handling robot.</li> </ul> README: /Data Contains all UV-Vis, electron microscopy, fluorescence, and SAXS data for gold nanoparticles synthesized in the presence of peptides and HEPES. /Data/2021_12_30_Prepared_UV_Vis_Data The primary portion of the experimental dataset. UV-Vis spectroscopy data collected on a Biotek Epoch 2 microplate spectrophotometer 24 hours after samples were synthesized using a liquid handling robot (Opentrons OT2). The 4x4x4_SI.csv file is the compilation of all sample information: <ul> <li>Concentrations (M) of peptide, HAuCl4, and HEPES</li> <li>UID – unique ID based on date of synthesis, sample position, and peptide which was used to synthesize the sample.</li> <li>Peptide names: Z2: RMRMKMK; MZ2: myristoylated - RMRMKMK; MZ2R: myristoylated - KMKMRMR; PZ2: palmitoylated – RMRMKMK; Z2M6I: RMRMKIK; Z2M246I: RIRIKIK; AG3: AYSSGAPPMPPF.</li> </ul> Each sample’s UID is a key to match with UV-Vis measurement result stored in the {UID}.txt files. Each of these files contains the wavelength, absorbance, and absorbance after subtraction of a water measurement. /Data/2022_02_13_AuPeptide_Kinetics Measurement_Data.xlsx and Measurement_Times.xlsx contain UV-Vis spectra at several time points for each well measured, and the time corresponding to each time step, respectively. See /Notebooks/UV_Vis_Kinetics.ipynb for data plotting and sample concentration information. /Data/ElectronMicroscopy Scanning electron microscopy and transmission electron microscopy results of gold nanoparticles formed from the reduction of HAuCl4 in the presence or absence of different peptides. Fig A, B, C, D, E/F were prepared in the presence of Z2, Z2M6I, Z2M246I, no peptide, and MZ2R, respectively. /Data/Fluorescence Pyrene fluorescence data collected in the presence of different concentrations of lipidated peptides (MZ2, MZ2R, and PZ2) for estimation of the peptide critical micelle concentration. /Data/SAXS SAXS data of a high concentration of MZ2 which was fit using a cylindrical model form factor. The evaluated model is also shared in this directory. /Data/USAXS Similarly to the UV-Vis data directory, the USAXS_SI.csv file contains sample information for all of the USAXS measurements. The dsm_rg.csv file contains the output of AUTORG evaluated on the desmeared data after subtraction of a flat background at high-q. /DSM_Nexus, DSM_sub_AUTORG, and SMR_Nexus contain the desmeared, desmeared with background subtraction, and smeared versions of the USAXS data, respectively. /Notebooks Notebooks for plotting the shared data and estimating the CMC from the fluorescence data. See /Notebooks/environment.yml for packages necessary to execute the notebooks here and in /Synthesis_Protocol. We recommend installing this environment by using: conda env create -f /environment.yml Refer to  <a href="https://github.com/SasView/sasmodels">https://github.com/SasView/sasmodels</a> and the first cell of /Notebooks/USAXS.ipynb for specific instructions on how to complete installation of the sasmodels module (sasmodels will be installed by Pip if you correctly use the shared environment.yml file). /Figures Figures generated from /Notebooks. /Synthesis_Protocol Please read the instructions within /Synthesis_Procol/Example.ipynb. In short, this folder contains the code used to synthesize the samples in this dataset using an OT2 Opentrons liquid handling robot.

opencc-by-4.0Jun 2022View details →

Data: Computed tomography lacks sensitivity to image gold labelled mesenchymal stromal cells in vivo as evidenced by multispectral optoacoustic tomography.

This data set includes all the raw data collected for the following article: "Computed tomography lacks sensitivity to image gold labelled mesenchymal stromal cells in vivo as evidenced by multispectral optoacoustic tomography."

opencc-by-4.0Mar 2022View details →

SocialDisNER corpus: gold standard annotations for detection of disease mentions in Spanish tweets

If you use any data from this repository, please cite our scientific paper instead of the Zenodo repo:  Luis Gasco Sánchez, Darryl Estrada Zavala, Eulàlia Farré-Maduell, Salvador Lima-López, Antonio Miranda-Escalada, and Martin Krallinger. 2022. <a href="https://aclanthology.org/2022.smm4h-1.48">The SocialDisNER shared task on detection of disease mentions in health-relevant content from social media: methods, evaluation, guidelines and corpora</a>. In Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task, pages 182–189, Gyeongju, Republic of Korea. Association for Computational Linguistics. <pre><code class="language-json">@inproceedings{gasco2022socialdisner, title = "The {S}ocial{D}is{NER} shared task on detection of disease mentions in health-relevant content from social media: methods, evaluation, guidelines and corpora", author = "Gasco S{\'a}nchez, Luis and Estrada Zavala, Darryl and Farr{\'e}-Maduell, Eul{\`a}lia and Lima-L{\'o}pez, Salvador and Miranda-Escalada, Antonio and Krallinger, Martin", booktitle = "Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop {\&} Shared Task", month = oct, year = "2022", address = "Gyeongju, Republic of Korea", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2022.smm4h-1.48", pages = "182--189" }</code></pre>   Introduction: The SocialDisNER corpus of the SMM4H 2022 – Task 10 task focus on the recognition of disease mentions in tweets written in Spanish after selecting primarily first-hand experience of diseases and other health-relevant content (from patient associations, professional healthcare institutions, and through followers of patient association accounts of a diversity of pathologies including rare diseases, mental health, cancer, etc..). SocialDisNER Gold Standard The Gold Standard corpus was manually annotated by medical experts following the <a href="https://doi.org/10.5281/zenodo.6983041">SMM4H-SocialDisNER guidelines</a>. These guidelines were adapted from previous efforts used to annotate patient clinical records and medical literature. It covers rules for annotating mentions of diseases in health-related tweets in Spanish, The training set consists of 5000 tweets written in Spanish and the validation set consists of 2500 tweets written in Spanish. Both sets have been manually annotated by healthcare professionals. The test dataset contains 23430 tweets, although only 2000 will be used to evaluate the systems participating in the task (the rest is background set). We don't plan to publish the test set, but if you want you can test your system from <a href="https://codalab.lisn.upsaclay.fr/competitions/3531">SocialDisNER Codalab</a>. SocialDisNER Large Scale Corpus The large-scale data contains mentions automatically extracted from a set of 85000 tweets. Separate datasets are shown for each entity including diseases, drugs, symptoms, professions, procedures, species, morphology neoplasm, and persons. SocialDisNER co-mention networks We have computed a co-occurrence matrix of the extracted diseases, as well as several co-mention matrices between the disease mentions and the rest of the entities in the large-scale corpora.   File structure: The structure of the corpus is:  <ul> <li>SocialDisNER_Data: <ul> <li>training-validation-data folder <ul> <li>train-valid-txt-files:  folder with training and validation text files. One text file per tweet, the file name corresponds to the tweet id. One sub-directory per corpus split (train and valid). The files named ids_dev_set.txt and ids_train_set.txt contain the list of file identifiers for each of the data splits (validation and train).</li> <li>mentions.tsv: This file contains the manually annotated disease mentions. The file has the following fields: <ul> <li>tweets_id: This is the id of the tweet, using Twitter API you can query the content of the tweet.</li> <li>Begin: This is the position in the tweet where the annotation was found.</li> <li>End: This is the position of the last character of the annotation in the tweet.</li> <li>Type: This is the type of entity found, in our case "ENFERMEDAD".</li> <li>Extraction: This is the literal extraction, in other words, the fragment of text which refers to the annotation. </li> </ul> </li> </ul> </li> <li>test-data folder: <ul> <li>test-data-txt-files: folder with test text files. One file per tweet, the file name corresponds to the tweet id. The folder contains 23430 tweets to be used as test set of the task. Of them, 2000 will be used to evaluate the participating systems.</li> </ul> </li> </ul> </li> </ul>   <ul> <li>SocialDisNER_LargeScale_additionaldata: <ul> <li>socialdisner_diseases: <ul> <li>tweets_txt: Folder with large-scale tweet database. One text file per tweet, the file name corresponds to the tweet id.</li> <li>diseases_mentions.tsv: This file contains the automatically annotated disease mentions from the large-scale SocialDisNER corpus (Silver Standard). The structure is the same than the Golden Standard annotations.</li> </ul> </li> <li>socialdisner_ENTITY: Each folder with this naming convention contains the following data structure. Corpora have been generated with mentions of diseases, drugs, symptoms, professions, procedures, species, morphology neoplasm and persons <ul> <li>tweets_txt: Folder with large-scale tweet database. One text file per tweet, the file name corresponds to the tweet id.</li> <li>ENTITY_mentions.tsv: This file contains the automatically annotated mentions of type “ENTITY” from the large-scale SocialDisNER corpus (Silver Standard). The structure is the same than the Golden Standard annotations.</li> </ul> </li> <li>socialdisner_networks: This folder contains tsv files containing the co-mention matrices between the diseases and the rest of the entities of the large-scale socialdisner data. Each file follows the following naming convention: <ul> <li>socialdisner_disease-ENTITY_net.tsv:  The tsv file contains a series of columns and rows corresponding to the mentions used for building the matrix. Each column is separated by “;”. The type of each mention is identified by the label in parentheses of each title. The count represents the number of times that mention x and mention y were found in the same tweet of the large-scale dataset.</li> <li>socialdiser_disease_net.tsv: This tsv file contains the array of socialdisner-disease large-scale corpus co-mentions separated by ";". This file can be loaded into NetworkX to perform disease co-morbidity analysis on the socialdisner-disease large-scale data.</li> </ul> </li> </ul> </li> </ul> Note: In previous versions of the dataset the order of the columns in the mentions.tsv file was not in the correct order. From this version onwards the order is correct and adequate to send the predictions of the task.   For further information, please visit <a href="https://temu.bsc.es/socialdisner/">https://temu.bsc.es/socialdisner/</a> Summary statistics: <table> <caption>Manually annotated data</caption> <thead> <tr> <th scope="row"> </th> <th scope="col">Training set</th> <th scope="col">Development set</th> </tr> </thead> <tbody> <tr> <th scope="row"># tweets</th> <td>5000</td> <td>2500</td> </tr> <tr> <th scope="row"># characters</th> <td>1253431</td> <td>516768</td> </tr> <tr> <th scope="row"># tokens</th> <td>211555</td> <td>84478</td> </tr> <tr> <th scope="row">Avg. char / tweet</th> <td>250.69</td> <td>206.71</td> </tr> <tr> <th scope="row">Avg. tok. / tweet</th> <td>42.31</td> <td>33.79</td> </tr> <tr> <th scope="row"># mentions</th> <td>15173</td> <td>4252</td> </tr> <tr> <th scope="row"># unique mentions</th> <td>4407</td> <td>1413</td> </tr> </tbody> </table>   <table> <caption>Large-scale annotated data (Silver Standard)</caption> <tbody> <tr> <td> </td> <td>Socialdisner-diseases</td> <td>Socialdisner-pharma</td> <td>Socialdisner-morphology_neoplasms</td> <td>Socialdisner-symptoms</td> <td>Socialdisner-professions</td> <td>Socialdisner-Procedures</td> <td>Socialdisnerv-Person</td> <td>Socialdisner-Species</td> </tr> <tr> <td># tweets</td> <td>85077</td> <td>1759</td> <td>8518</td> <td>12624</td> <td>15831</td> <td>11462</td> <td>41033</td> <td>12118</td> </tr> <tr> <td># characters</td> <td>19920670</td> <td>435141</td> <td>2082574</td> <td>3023784</td> <td>4063114</td> <td>2873791</td> <td>10273278</td> <td>2933925</td> </tr> <tr> <td># tokens</td> <td>3236411</td> <td>68269</td> <td>332539</td> <td>521503</td> <td>660071</td> <td>467059</td> <td>1689479</td> <td>486249</td> </tr> <tr> <td>Avg. char / tweet</td> <td>234.15</td> <td>247.38</td> <td>244.49</td> <td>239.53</td> <td>256.66</td> <td>250.72</td> <td>250.37</td> <td>242.11</td> </tr> <tr> <td>Avg. tok. / tweet</td> <td>38.04</td> <td>38.81</td> <td>39.04</td> <td>41.31</td> <td>41.69</td> <td>40.75</td> <td>41.17</td> <td>40.13</td> </tr> <tr> <td># mentions</td> <td>116260</td> <td>1029</td> <td>8943</td> <td>12896</td> <td>18590</td> <td>10080</td> <td>58007</td> <td>14014</td> </tr> <tr> <td># unique mentions</td> <td>16034</td> <td>530</td> <td>541</td> <td>6991</td> <td>3667</td> <td>3841</td> <td>3446</td> <td>1676</td> </tr> </tbody> </table>       Do not share the data with other individuals/teams without permission from the task organizer. Tweets IDs are the primary source of information. Tweet texts are provided as support material. By downloading this resource, you agree to the Twitter <a href="https://twitter.com/en/tos">Terms of Service</a>, <a href="https://twitter.com/en/privacy">Privacy Policy</a>, <a href="https://developer.twitter.com/en/developer-terms/agreement">Developer Agreement</a>, and <a href="https://developer.twitter.com/en/developer-terms/policy">Developer Policy</a>.

opencc-by-4.0Jul 2022View details →

Imaging data of mechanically loaded, micro-patterned, silk-reinforced cellulose films with gold coating for flexible electrodes in medical implants

Neurodegenerative diseases can be treated using a functional interface between the physically soft tissue such as brain and the man-made electrodes. The orders of magnitude harder neural probes cause local injuries, due to periodic micromovements owing to breathing and pulsatile blood flow leading to encapsulation and related collapsing signals. An alternative to the currently used neural implant films including polyimide, poly(p-xylylene), SU-8 - epoxy-based negative photoresist, liquid crystal polymer, and benzocyclobutene is the natural polymer cellulose with an elastic modulus between 100 and 200 MPa. This article elucidates the measurement of the mechanical properties of bare as well as mono- and double-layer silk-reinforced cellulose in phosphate-buffered saline using a universal testing machine. In addition, the article contains electron microscopy data of these micro-structured, gold-coated films subsequent to peel-off tests to access the impact of micro-structures on gold adhesion on cellulose. These imaging data were completed by electron micrographs of mechanically loaded gold-coated cellulose films to demonstrate the impact of micro-structures on crack formation. Finally, the phosphate-buffered saline-induced swelling of the micro-structure was visualized by electron micrographs obtained before and after two-month storage in air and phosphate-buffered saline, respectively.

opencc-by-4.0Dec 2021View details →

X-ray scattering Datasets of gold and silver nanoparticle composites, relating to the publication "Gold and silver dichroic nanocomposite in the quest for 3D printing the Lycurgus cup"

Wide-range X-ray scattering datasets and analyses for all samples described in the 2020 publication "Gold and silver dichroic nanocomposite in the quest for 3D printing the Lycurgus cup". These datasets are composed by combining multiple small-angle x-ray scattering and wide-angle x-ray scattering curves into a single dataset. They have been analyzed using McSAS to extract polydispersities and volume fractions. They have been collected using the MOUSE project (instrument and methodology).

FDTD simulation of 290 nm PAAO with gold nanoparticles: varying incidence angle, s-polarization, n=1

Version 2 has the same files as version 1 and some additional files. FDTD software: Lumerical (Ansys, version 2021 R2.3). Structure: aluminum (Palik) substrate; 290 nm thickness (h) aluminum oxide (Palik) layer with 35 nm diameter (RPo) cylindrical pores with 100 nm distance (D) between the pore centers (representing porous anodized aluminum oxide - PAAO); 60 nm diameter (RNP) gold (Johnson and Christy) nanoparticles placed directly above each pore. Refractive index of the surrounding medium (n): 1.0. Simulation region: from 300 nm below the substrate/PAAO interface to 1.3 µm above PAAO surface; x and y spans are equal to one period of the structure. Mesh override region: from 50 nm below the PAAO to 50 nm above the nanoparticles; 2 nm step size in each direction. Light source: BFAST plane wave light source; 500 nm above PAAO; varying (20° - 70° in steps of 5°) angle of incidence (ang); 300 nm – 1000 nm wavelength range; s-polarization (pol). Monitor (frequency domain field and power): 2D Z-normal; 1 µm above PAAO; results are in "_reflection.txt" files. Information in the file name: h - thickness of PAAO; pol - polarization; RNP - diameter of gold nanoparticles; RPo - diameter of pores; D - distance between pore centers; ang - angle of incidence; n - refractive index of surrounding medium. Files: (1) "_reflection.txt" - lambda(nm) (first column) - wavelength in nanometers; Y (second column) - T data from the monitor above the structure. (2) "_p0.log" - log file produced by the software while running the simulation. (3) ".fsp" - Lumerical software file containing the simulation project (license required to open these files). Consecutive numbering corresponds to the angles of incidence: 1 - 20°, 2 - 25°, 3 - 30°, 4 - 35°, 5 - 40°, 6 - 45°, 7 - 50°, 8 - 55°, 9 - 60°, 10 - 65°, 11 - 70°. (4) "Lumerical_Screenshots.pdf" - shows software screenshots for every object and its every property; red text is added to show which values are different for different simulations. (5) "Structure_Illustration.png" - a schematic of modeled structure. (6) "290nm-Spol_varying-angle.jpg" - a preview of data from "_reflection.txt" files.

FDTD simulation of 290 nm PAAO with gold nanoparticles: varying refractive index of surrounding medium, s-polarization

Version 2 has the same files as version 1 and some additional files. FDTD software: Lumerical (Ansys, version 2021 R2.3). Structure: aluminum (Palik) substrate; 290 nm thickness (h) aluminum oxide (Palik) layer with 35 nm diameter (RPo) cylindrical pores with 100 nm distance (D) between the pore centers (representing porous anodized aluminum oxide - PAAO); 60 nm diameter (RNP) gold (Johnson and Christy) nanoparticles placed directly above each pore. Refractive index of the surrounding medium (n): 1.0; 1.1; 1.2; 1.3. Simulation region: from 300 nm below the substrate/PAAO interface to 1.3 µm above PAAO surface; x and y spans are equal to one period of the structure. Mesh override region: from 50 nm below the PAAO to 50 nm above the nanoparticles; 2 nm step size in each direction. Light source: BFAST plane wave light source; 500 nm above PAAO; 45° angle of incidence (ang); 300 nm – 1000 nm wavelength range; s-polarization (pol). Monitor (frequency domain field and power): 2D Z-normal; 1 µm above PAAO; results are in "_reflection.txt" files. Information in the file name: h - thickness of PAAO; pol - polarization; RNP/AuRNP - diameter of gold nanoparticles; RPo - diameter of pores; D - distance between pore centers; ang - angle of incidence; n - refractive index of surrounding medium. Files: (1) "_reflection.txt" - lambda(nm) (first column) - wavelength in nanometers; Y (second column) - T data from the monitor above the structure. (2) "_p0.log" - log file produced by the software while running the simulation. (3) ".fsp" - Lumerical software file containing the simulation project; it can be used to extract data from Y- and X-normal monitors (license required to open these files). (4) "Lumerical_Screenshots.pdf" - shows software screenshots for every object and its every property; red text is added to show which values are different for different simulations. (5) "Structure_Illustration.png" - a schematic of modeled structure. (6) "h290,varN.jpg" - a preview of data from "_reflection.txt" files.

FDTD simulation of PAAO with gold nanoparticles: varying thickness, s-polarization

Version 2 has the same files as version 1 and some additional files. FDTD software: Lumerical (Ansys, version 2021 R2.3). Structure: aluminum (Palik) substrate; 230/260/290/320/350/500 nm thickness (h) aluminum oxide (Palik) layer with 35 nm diameter (RPo) cylindrical pores with 100 nm distance (D) between the pore centers (representing porous anodized aluminum oxide - PAAO); 60 nm diameter (RNP) gold (Johnson and Christy) nanoparticles placed directly above each pore. Refractive index of the surrounding medium: 1.0. Simulation region: from 300 nm below the substrate/PAAO interface to 1.3 µm above PAAO surface; x and y spans are equal to one period of the structure. Mesh override region: from 50 nm below the PAAO to 50 nm above the nanoparticles; 2 nm step size in each direction. Light source: BFAST plane wave light source; 500 nm above PAAO; 45° angle of incidence (ang); 300 nm – 1000 nm wavelength range; s-polarization (pol). Monitor (frequency domain field and power): 2D Z-normal; 1 µm above PAAO; results are in "_reflection.txt" files. Information in the file name: h - thickness of PAAO; pol - polarization; RNP - diameter of gold nanoparticles; RPo - diameter of pores; D - distance between pore centers; ang - angle of incidence; n - refractive index of surrounding medium (if there is no n in the file name, then n = 1.0). Files: (1) "_reflection.txt" - lambda(nm) (first column) - wavelength in nanometers; Y (second column) - T data from the monitor above the structure. (2) "_p0.log" - log file produced by the software while running the simulation. (3) ".fsp" - Lumerical software file containing the simulation project. (4) "Lumerical_Screenshots.pdf" - shows software screenshots for every object and its every property; red text is added to show which values are different for different simulations. (5) "Structure_Illustration.png" - a schematic of modeled structure. (6) "diff_PAAO_thickness_Spol.jpg" - a preview of data from "_reflection.txt" files.

opencc-by-4.0Dec 2017View details →

Research data supporting "Platinum Nanocatalyst Amplification: Redefining the Gold Standard for Lateral Flow Immunoassays with Ultra-Broad Dynamic Range"

Research data supporting the publication: Loynachan C. N., et al., 2017, ACS Nano, DOI: http://dx.doi.org/10.1021/acsnano.7b06229.

РИС. 1. ОбЩий вид фиксированных Этанолом глохидиев в световой (А) и сканируюЩий Электронный (В) микроскопы (Amuranodonta kijaensis, бассейн р. Амур, Хинганский Заповедник, АмурскаЯ обл.). МасШтаб 100 мкм. Микроскопы Nikon (А) и Zeiss EVO 40 (B), напыление Золотом FIG. 1. Ethanol-fixed glochidia (Amuranodonta kijaensis, Amur River basin, Khingansky Nature Reserve, Amur Oblast), light (A) and scanning electron (B) microscopes. Scale bar 100 mµ. Light Nikon (A) and scanning electron Zeiss EVO 40 (B) microscopes, sputter coating with gold. in Методика подготовки раковин глохидиев (Bivalvia, Unionidae) длЯ работы на сканируюЩем Электронном микроскопе

РИС. 1. ОбЩий вид фиксированных Этанолом глохидиев в световой (А) и сканируюЩий Электронный (В) микроскопы (Amuranodonta kijaensis, бассейн р. Амур, Хинганский Заповедник, АмурскаЯ обл.). МасШтаб 100 мкм. Микроскопы Nikon (А) и Zeiss EVO 40 (B), напыление Золотом FIG. 1. Ethanol-fixed glochidia (Amuranodonta kijaensis, Amur River basin, Khingansky Nature Reserve, Amur Oblast), light (A) and scanning electron (B) microscopes. Scale bar 100 mµ. Light Nikon (A) and scanning electron Zeiss EVO 40 (B) microscopes, sputter coating with gold.

РИС. 9. ВнеШний вид раковин глохидиев (Sinanodonta woodiana, р. Одра, ПольШа), очиЩенных с помоЩью Щелочи (5% KOH). A. Темные пЯтна на поверхности, свидетельствуюЩие о недостаточной промывке после Щелочи. B. ХороШо очиЩеннаЯ и правильно промытаЯ раковина. МасШтаб 50 мкм. Микроскоп Zeiss EVO 40, напыление Золотом. FIG. 9. Glochidia shells (Sinanodonta woodiana, Odra River, Poland) cleaned in alkali (5% KOH). A. Dark spots on the shell surface, indicating insufficient rinsing after alkali. B. Properly cleaned and rinsed shell. Scale bars 50 μm. Zeiss EVO 40 microscope, sputter coating with gold. in Методика подготовки раковин глохидиев (Bivalvia, Unionidae) длЯ работы на сканируюЩем Электронном микроскопе

РИС. 9. ВнеШний вид раковин глохидиев (Sinanodonta woodiana, р. Одра, ПольШа), очиЩенных с помоЩью Щелочи (5% KOH). A. Темные пЯтна на поверхности, свидетельствуюЩие о недостаточной промывке после Щелочи. B. ХороШо очиЩеннаЯ и правильно промытаЯ раковина. МасШтаб 50 мкм. Микроскоп Zeiss EVO 40, напыление Золотом. FIG. 9. Glochidia shells (Sinanodonta woodiana, Odra River, Poland) cleaned in alkali (5% KOH). A. Dark spots on the shell surface, indicating insufficient rinsing after alkali. B. Properly cleaned and rinsed shell. Scale bars 50 μm. Zeiss EVO 40 microscope, sputter coating with gold.

РИС. 10. НаружнаЯ микроскульптура раковин глохидиев при напылении раЗными материалами. А. Углеродом (Kunashiria haconensis, оЗ. Песчаное, о-в КунаШир, Курильские о-ва). В. Хромом (Kunashiria haconensis, оЗ. Песчаное, о-в КунаШир, Курильские о-ва). C. Хромом (Anodonta cygnea, оЗ. Хамржицкое, ПольШа). D. Золотом (Anodonta cygnea, оЗ. Хамржицкое, ПольШа). МасШтабнаЯ линейка 2 мкм. Микроскопы Zeiss EVO 40 (А, С), Zeiss MERLIN (В, D). FIG. 10. External glochidia microsculpture with different material coating. A. Carbon coated (Kunashiria haconensis, Peschanoe Lake, Kunashir Island, Kuril Islands). B. Chromium coated (Kunashiria haconensis, Peschanoe Lake, Kunashir Island, Kuril Islands). C. Chromium coated (Anodonta cygnea, Khamrzhitskoe Lake, Poland). D. Gold coated (Anodonta cygnea, Khamrzhitskoe Lake, Poland). Scale bars 2 μm. Zeiss EVO 40 (A, C) and Zeiss MERLIN (B, D) microscopes. in Методика подготовки раковин глохидиев (Bivalvia, Unionidae) длЯ работы на сканируюЩем Электронном микроскопе

РИС. 10. НаружнаЯ микроскульптура раковин глохидиев при напылении раЗными материалами. А. Углеродом (Kunashiria haconensis, оЗ. Песчаное, о-в КунаШир, Курильские о-ва). В. Хромом (Kunashiria haconensis, оЗ. Песчаное, о-в КунаШир, Курильские о-ва). C. Хромом (Anodonta cygnea, оЗ. Хамржицкое, ПольШа). D. Золотом (Anodonta cygnea, оЗ. Хамржицкое, ПольШа). МасШтабнаЯ линейка 2 мкм. Микроскопы Zeiss EVO 40 (А, С), Zeiss MERLIN (В, D). FIG. 10. External glochidia microsculpture with different material coating. A. Carbon coated (Kunashiria haconensis, Peschanoe Lake, Kunashir Island, Kuril Islands). B. Chromium coated (Kunashiria haconensis, Peschanoe Lake, Kunashir Island, Kuril Islands). C. Chromium coated (Anodonta cygnea, Khamrzhitskoe Lake, Poland). D. Gold coated (Anodonta cygnea, Khamrzhitskoe Lake, Poland). Scale bars 2 μm. Zeiss EVO 40 (A, C) and Zeiss MERLIN (B, D) microscopes.

РИС. 4. НаружнаЯ микроскульптура глохидиев при раЗных условиЯх очистки раковин (Inversiunio yanagawensis, р. Гион, о-в Хонсю, ЯпониЯ) в растворе Щелочи. А. НеповрежденнаЯ микроскульптура. B. ПоврежденнаЯ при передержке в растворе Щелочи. МасШтаб 2 мкм. Микроскопы Zeiss MERLIN (А), Zeiss EVO 40 (В), напыление хромом (А), Золотом (В). FIG. 4. Exterior valve microsculpture under different conditions of cleaning in alkali (Inversiunio yanagawensis, Gion River, Honshu Island, Japan). A. Undamaged microsculpture. B. Damaged microsculpture by excessive treatment in alkali. Scale bars 2 μm. Zeiss MERLIN (A) and Zeiss EVO 40 (B) microscopes, sputter coating with chromium (A) and gold (B). in Методика подготовки раковин глохидиев (Bivalvia, Unionidae) длЯ работы на сканируюЩем Электронном микроскопе

РИС. 4. НаружнаЯ микроскульптура глохидиев при раЗных условиЯх очистки раковин (Inversiunio yanagawensis, р. Гион, о-в Хонсю, ЯпониЯ) в растворе Щелочи. А. НеповрежденнаЯ микроскульптура. B. ПоврежденнаЯ при передержке в растворе Щелочи. МасШтаб 2 мкм. Микроскопы Zeiss MERLIN (А), Zeiss EVO 40 (В), напыление хромом (А), Золотом (В). FIG. 4. Exterior valve microsculpture under different conditions of cleaning in alkali (Inversiunio yanagawensis, Gion River, Honshu Island, Japan). A. Undamaged microsculpture. B. Damaged microsculpture by excessive treatment in alkali. Scale bars 2 μm. Zeiss MERLIN (A) and Zeiss EVO 40 (B) microscopes, sputter coating with chromium (A) and gold (B).

РИС. 5. ЗагрЯЗнение готовых обраЗцов длЯ СЭМ при длительном хранении в негерметичных условиЯх (A–C) либо при хранении проШедШих процедуру мацерированиЯ беЗ последуюЩего обеЗЗараживаниЯ (D, E). A–С. Бактерии на поверхности глохидиев (Nodularia douglasiae, р. ИлистаЯ, бассейн оЗ. Ханка, Приморский кр.). А. ВнеШний вид глохидиЯ, основное ЗагрЯЗнение на створке в верхней части фото. В. Крючок глохидиЯ, основное ЗагрЯЗнение в левой части фото. С. Створка, вид иЗнутри. D. Единичные бактерии на створке глохидиЯ, вид иЗнутри (Kunashiria japonica, оЗ. Утиное, о-в Зелёный, Курильские о-ва). E. Гифы гриба на створке глохидиЯ, вид на наружную пору (Beringiana beringiana, оЗ. АЗабачье, Камчатка). МасШтаб 50 мкм (А, C), 10 мкм (В, D), 1 мкм (Е). Микроскопы Zeiss MERLIN (А, B, C, E), Zeiss EVO 40 (D), напыление хромом (А–С), Золотом (D), углеродом (Е). FIG. 5. Contamination of the SEM ready-made samples during long-term storage under unsealed conditions (A–C) or during storage the samples that have passed the maceration procedure without subsequent disinfection (D, E). A–C. Bacteria on the glochidia surface (Nodularia douglasiae, Ilistaya River, Khanka Lake basin, Primorsky Krai). A. Glochidium with the main pollution on the valve in the upper part of the photo. B. Hook with the main pollution on the left side of the photo. C. Interior valve. D. Bacteria on the interior valve (Kunashiria japonica, Utinoe Lake, Zeliony Island, Kuril Islands). E. Fungal hyphae on the pore of exterior valve (Beringiana beringiana, Azabachye Lake, Kamchatka). Scale bars 50 μm (A, C), 10 μm (B, D), 1 μm (E). Zeiss MERLIN (A, B, C, E) and Zeiss EVO 40 (D) microscopes, sputter coating with chromium (A–C), gold (D), and carbon (E). in Методика подготовки раковин глохидиев (Bivalvia, Unionidae) длЯ работы на сканируюЩем Электронном микроскопе

РИС. 5. ЗагрЯЗнение готовых обраЗцов длЯ СЭМ при длительном хранении в негерметичных условиЯх (A–C) либо при хранении проШедШих процедуру мацерированиЯ беЗ последуюЩего обеЗЗараживаниЯ (D, E). A–С. Бактерии на поверхности глохидиев (Nodularia douglasiae, р. ИлистаЯ, бассейн оЗ. Ханка, Приморский кр.). А. ВнеШний вид глохидиЯ, основное ЗагрЯЗнение на створке в верхней части фото. В. Крючок глохидиЯ, основное ЗагрЯЗнение в левой части фото. С. Створка, вид иЗнутри. D. Единичные бактерии на створке глохидиЯ, вид иЗнутри (Kunashiria japonica, оЗ. Утиное, о-в Зелёный, Курильские о-ва). E. Гифы гриба на створке глохидиЯ, вид на наружную пору (Beringiana beringiana, оЗ. АЗабачье, Камчатка). МасШтаб 50 мкм (А, C), 10 мкм (В, D), 1 мкм (Е). Микроскопы Zeiss MERLIN (А, B, C, E), Zeiss EVO 40 (D), напыление хромом (А–С), Золотом (D), углеродом (Е). FIG. 5. Contamination of the SEM ready-made samples during long-term storage under unsealed conditions (A–C) or during storage the samples that have passed the maceration procedure without subsequent disinfection (D, E). A–C. Bacteria on the glochidia surface (Nodularia douglasiae, Ilistaya River, Khanka Lake basin, Primorsky Krai). A. Glochidium with the main pollution on the valve in the upper part of the photo. B. Hook with the main pollution on the left side of the photo. C. Interior valve. D. Bacteria on the interior valve (Kunashiria japonica, Utinoe Lake, Zeliony Island, Kuril Islands). E. Fungal hyphae on the pore of exterior valve (Beringiana beringiana, Azabachye Lake, Kamchatka). Scale bars 50 μm (A, C), 10 μm (B, D), 1 μm (E). Zeiss MERLIN (A, B, C, E) and Zeiss EVO 40 (D) microscopes, sputter coating with chromium (A–C), gold (D), and carbon (E).