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422 results for “SER”
Dataset of reports about MOF-based SERS substrates since 2011 until March 2023. Structure, characteristics, analytes, and performances.
<p>This dataset was generated to aid the creation of a review article addressing the use of Metal-Organic Frameworks (MOF)-based Surface Enhanced Raman Spectroscopy (SERS) platforms for the detection of Volatile Organic Compounds (VOCs).</p> <p>This dataset was generated employing the Web of Science database, encompassing manuscripts published up to March 2023. A literature search was initially conducted using a combination of keywords, including "MOF," "Metal-Organic Framework," "SERS," "Surface Enhanced Raman Spectroscopy," and "Surface Enhanced Raman Scattering." This search spanned the "Topic" category, enabling exploration across title, abstract, author keywords, and keyword-plus fields.</p> <p>From the initial pool of 238 documents, review articles and duplicates were systematically excluded, resulting in a refined collection of 182 articles. Subsequently, articles not concurrently addressing MOF and SERS or those utilizing MOF as sacrificial templates were further excluded, resulting in a final subset of 72 articles. From this curated set, relevant parameters were extracted, resulting in 229 entries for the dataset. </p> <p>Characteristics about the structure (in terms of MOF type and configuration; Plasmonic element type and configuration), target analyte (including type, phase, and incubation time), measurement specifications (in terms of laser, laser power, exposure time), and performance of the MOF-based SERS substrates were collected.</p> <p>Listed references 1-72 correspond with the manuscript number in the dataset.</p> <p>Listed references 73-80 correspond with references for selected examples of MOF pore diameters.</p>
Plexcitonic Nanorattles as Highly Efficient SERS-Encoded Tags
<p>Recent publication: </p> <h1>Plexcitonic Nanorattles as Highly Efficient SERS-Encoded Tags</h1> <div> </div> <div> <div> <div> <div><span><a href="https://onlinelibrary.wiley.com/authored-by/Est%C3%A9vez%E2%80%90Varela/Carla">Carla Estévez-Varela</a><span>, </span></span><span><a href="https://onlinelibrary.wiley.com/authored-by/N%C3%BA%C3%B1ez%E2%80%90S%C3%A1nchez/Sara">Sara Núñez-Sánchez</a><span>, </span></span><span><a href="https://onlinelibrary.wiley.com/authored-by/Pi%C3%B1eiro%E2%80%90Varela/Paula">Paula Piñeiro-Varela</a><span>, </span></span><span><a href="https://onlinelibrary.wiley.com/authored-by/Aberasturi/Dorleta+Jim%C3%A9nez">Dorleta Jiménez de Aberasturi</a><span>, </span></span><span><a href="https://onlinelibrary.wiley.com/authored-by/Liz%E2%80%90Marz%C3%A1n/Luis+M.">Luis M. Liz-Marzán</a><span>, </span></span><span><a href="https://onlinelibrary.wiley.com/authored-by/P%C3%A9rez%E2%80%90Juste/Jorge">Jorge Pérez-Juste</a><span>, </span></span><span><a href="https://onlinelibrary.wiley.com/authored-by/Pastoriza%E2%80%90Santos/Isabel">Isabel Pastoriza-Santos</a></span></div> </div> </div> </div> <div> <div><span>First published: </span><span>27 November 2023</span></div> <br> <div><a href="https://doi.org/10.1002/smll.202306045">https://doi.org/10.1002/smll.202306045</a></div> </div> <p> </p> <p>Abstract: Plexcitonic nanoparticles exhibit strong light-matter interactions, mediated by localized surface plasmon resonances, and thereby promise potential applications in fields such as photonics, solar cells, and sensing, among others. Herein, these light-matter interactions are investigated by UV-visible and surface-enhanced Raman scattering (SERS) spectroscopies, supported by finite-difference time-domain (FDTD) calculations. Our results reveal the importance of combining plasmonic nanomaterials and J-aggregates with near-zero-refractive index. As plexcitonic nanostructures nanorattles are employed, based on J-aggregates of the cyanine dye 5,5,6,6-tetrachloro-1,1-diethyl-3,3-bis(4-sulfobutyl)benzimidazolocarbocyanine (TDBC) and plasmonic silver-coated gold nanorods, confined within mesoporous silica shells, which facilitate the adsorption of the J-aggregates onto the metallic nanorod surface, while providing high colloidal stability. Electromagnetic simulations show that the electromagnetic field is strongly confined inside the J-aggregate layer, at wavelengths near the upper plexcitonic mode, but it is damped toward the J-aggregate/water interface at the lower plexcitonic mode. This behavior is ascribed to the sharp variation of dielectric properties of the J-aggregate shell close to the plasmon resonance, which leads to a high opposite refractive index contrast between water and the TDBC shell, at the upper and the lower plexcitonic modes. This behavior is responsible for the high SERS efficiency of the plexcitonic nanorattles under both 633 nm and 532 nm laser illumination. SERS analysis showed a detection sensitivity down to the single-nanoparticle level and, therefore, an exceptionally high average SERS intensity per particle. These findings may open new opportunities for ultrasensitive biosensing and bioimaging, as superbright and highly stable optical labels based on the strong coupling effect.</p>
Dataset: Submicron‐ and Nanoplastic Detection at Low Micro‐ to Nanogram Concentrations Using Gold Nanostar‐Based Surface‐Enhanced Raman Scattering (SERS) Substrates
<p>ABSTRACT</p> <p>The presence of submicron- (1 µm – 100 nm) and nanoplastic (< 100 nm) particles within various sample matrices, ranging from marine environments to foods and beverages, has become a topic of increasing interest in recent years. Despite this interest, very few analytical techniques remain that allow for the detection of these small plastic particles in the low concentration ranges that they are anticipated to be present at. Research focused on optimizing surface-enhanced Raman scattering (SERS) to enhance signal obtained in Raman spectroscopy has been shown to have great potential for the detection of plastic particles below conventional resolution limits. In this study, we produce SERS substrates composed of gold nanostars and assess their potential for submicron- and nanoplastic detection. The results show 33 nm polystyrene could be detected down to 1.25 µg/mL while 36 nm poly(ethylene terephthalate) was detected down to 5 µg/mL. These results confirm the promising potential of the gold nanostar-based SERS substrates for nanoplastic detection. Furthermore, combined with findings for 121 nm polypropylene and 126 nm polyethylene particles, they highlight potential differences in analytical performance that depend on the properties of the plastics being studied.</p>
Datasets of titrations of mineral water hardness monitored using SERS
<p>These datasets contains the spectral information used in a publication regarding the implementation of complexometric titrations of water hardness monitored using Surface Enhanced Raman Spectroscopy (SERS).</p> <p>The data consists of two csv files with semi-column separators.</p> <p><em>« MD150 to 155_Master_df_638_corrected_mod_v02.csv »</em> and <em>« MD150 to 155_Master_df_785_corrected_mod_v02.csv »</em> correspond to spectral data acquired under 638 and 785 nm irradiation respectively.</p> <p>The data are organised as row vectors.</p> <p>Each dataset has 432 rows corresponding to 3 water samples (Evian, Volvic, Contrex), 3 replicate titration series + 1 blank titration per batch of NPs, 2 batches of NPs and 18 titration steps per titration series: .</p> <p>The row vectors consist of a first sub-vector of spectral descriptors (identity of spectra, identity and composition of measurement samples and conditions of spectral acquisition), followed by a sub-vector of baseline-substracted spectral intensities.</p> <p>In both datasets, the first 14 columns consists of the spectral descriptors.</p> <p>In the <em>« MD150 to 155_Master_df_638_corrected_mod_v02.csv » </em>dataset, the spectra section consists of 1010 columns which names are the values of the Raman shifts at which the intensities have been recorded.</p> <p>In the <em>« MD150 to 155_Master_df_785_corrected_mod_v02.csv »</em> dataset, the spectra section consists of 1746 columns which names are the values of the Raman shifts at which the intensities have been recorded.</p>
Datasets of pushing complexometric titrations in the nanomolar range thanks to SERS
<p>These datasets contains the spectral information used in a publication regarding the implementation of complexometric titrations of copper monitored using Surface Enhanced Raman Spectroscopy (SERS). In this study the sensitivity of a classic complexometric titration system for Cu2+ is pushed into the nanomolar regime thanks to SERS monitoring of the endpoint.</p> <p>All the data are organised as column vectors. </p> <p>The data consists of three csv files with semi-column separators.</p> <p>“AN334_and_AN338_laser_532nm_1microM_copper_variation_of_PAN_all_data_corrected_serie_11_points” correspond to spectral data acquired under 532 nm irradiation with variation of the PAN (100, 50 and 25 nM) concentration for 1 µM of copper.</p> <p>“AN335_and_AN341_laser_532nm_500nM_copper_variation_of_PAN_all_data_corrected_serie_11_points” correspond to spectral data acquired under 532 nm irradiation with variation of the PAN (100, 50 and 25 nM) concentration for 500 nM of copper.</p> <p>“AN336_and_AN344_laser_532nm_250nM_copper_variation_of_PAN_all_data_corrected_serie_11_points” correspond to spectral data acquired under 532 nm irradiation with variation of the PAN (100, 50 and 25 nM) concentration for 250 nM of copper.</p> <p>Each dataset has 90 685 rows corresponding to 1 irradiation used (532 nm), 2 experimental replicate titration series including 1 titration + 1 blank titration for each titration and for 3 differents concentrations of PAN and 11 titration steps per titration series. For the 3 copper concentrations we obtain 396 samples.</p> <p>The columns vectors consist of a first sub-vector of spectral descriptors (identity of spectra, identity and composition of measurement samples and conditions of spectral acquisition), followed by a sub-vector of baseline-subtracted spectral intensities.</p> <p>The meaning of each column is in the .docx file titled "Structure of AN334-AN338 to AN336-AN344 datasets”.</p> <p>The other two csv fils with semi-column separators "AN339_AN342_AN345_laser_638nm_variation_of_copper_and_PAN_all_data_corrected_serie_11_points" and "AN340_AN343_AN346_laser_785nm_variation_of_copper_and_PAN_all_data_corrected_serie_11_points" correspond to spectral data acquired under 638 and 785 nm irradiation respectively. In both files, the data correspond to the 11-point experiments with PAN variation (100, 50 and 25 nM) and copper variation (1 µM, 500 and 250 nM).</p> <p><span>Finally, the data consists of one csv files with semi-column separators.</span></p> <p><span>“AN384_to_AN386_Laser_532_638_785nm_all_data_corrected_titration_serie_20_points” correspond to spectral data acquired under 532, 638 and 785 nm irradiation.</span></p> <p><span>The dataset has 111 241 rows corresponding to 3 irradiations used (532, 638 and 785), 2 replicate titration series + 1 blank titration and 20 titration steps per titration series.</span><span></span></p> <p><span>The columns vectors consist of a first sub-vector of spectral descriptors (identity of spectra, identity and composition of measurement samples and conditions of spectral acquisition), followed by a sub-vector of baseline-subtracted spectral intensities.</span></p> <p>The meaning of each column is in the .docx file titled "Structure of AN384 to AN386 datasets”.</p>
Dataset for Repeated double cross validation applied to the PCA-LDA classification of SERS spectra: a case study with serum samples from hepatocellular carcinoma patients
<p>This dataset contains all the spectra used in the paper "Repeated double cross validation applied to the PCA-LDA classification of SERS spectra: a case study with serum samples from hepatocellular carcinoma patients", plus the R code to import the TXT (ASCII) files into a dataset, preprocess data, set-up and cross validate the PCA-LDA model and generate the figures shown in the paper.</p> <p>Data are available in 2 different formats: </p> <p>- 1 compressed archive ("dataset.zip") containing all the 144 TXT files (1 file = 1 spectrum) </p> <p>- 1 single CSV file (“dataset.csv”) with all the 144 spectra in the form of a table. The data are structured as follow, with each row being 1 spectrum, preceded by metadata: "acquisition_date", "substrate_batch", "class", "sample_code".</p> <p>The code for R is available as a single file "Rcode.R".</p> <p> </p>
Cuscuta suaveolens Ser. (BR0000010050842)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Cuscuta suaveolens Ser. (BR0000011917564)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Gypsophila scorzonerifolia Ser. (BR0000010121764)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Gypsophila scorzonerifolia Ser. (BR0000010121795)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Gypsophila scorzonerifolia Ser. (BR0000010121825)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Hydrangea macrophylla (Thunb.) Ser. (BR0000024493314)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Hydrangea macrophylla (Thunb.) Ser. (BR0000024493338)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Hydrangea macrophylla (Thunb.) Ser. (BR0000024493307)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Hydrangea macrophylla (Thunb.) Ser. (BR0000015254801V)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Hydrangea macrophylla (Thunb.) Ser. (BR0000024493345)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Medicago lupulina L. f. corymbosa Ser. (BR0000011970910)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Medicago lupulina L. f. corymbosa Ser. (BR0000011971245)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Medicago lupulina L. f. corymbosa Ser. (BR0000011971139)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Medicago lupulina L. f. corymbosa Ser. (BR0000011970606)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
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