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1,294 results for “reactions”
A droplet digital polymerase chain reaction assay to detect rare helminth parasites infecting natural host populations (Vancouver Island 2023, University of Wisconsin Madison Laboratory colony 2024)
Helminth infections represent a significant challenge to human, livestock, and wildlife health, yet they remain relatively under-studied, especially in terms of their ecological impacts. Better understanding of how these parasites spread in wildlife populations could improve our ability to predict and manage disease transmission across various species. Traditional detection methods, such as visually identifying parasites in environmental samples or infected hosts, often fall short, especially during the early stages of infection when parasite loads are minimal. In this study, we introduce a highly sensitive and precise droplet digital PCR (ddPCR) assay that quantifies helminth DNA in aquatic habitats, focusing on the 18S rRNA gene as a marker. These data utilize the model host-parasite system between the tapeworm Schistocephalus solidus, and its cyclopoid copepod host, Acanthocyclops robustus. The molecular assays are built around creating an infection standard in the lab, where copepods were singly infected with a single tapeworm parasite. We extracted DNA from 100 infected adults and used this as a standard to translate gene copy numbers from the ddPCR reactions to actual animal values. After creating a known lab standard, we then use the generated probes and primers to detect (and quantify!) infection burdens in field samples, which include both water filter samples (eDNA) and zooplankton tows from several lakes around Vancouver Island, B.C. The data presented here include well-specific data from ddPCR runs (amplitude of individual level oil droplets in the reaction) as well as each ddPCR analysis in its entirety. In order to prove the specificity of probes and probe-primers, we include here ddPCR runs of closely related helminth species, Schistocephalus cotti and Schistocephalus pungitii. We also consider the binding to another genera of copepod, the calanoid Eurytomora. All of the data wrangling, analysis, and data visualization are included as .Rmd files in th
ASRT (alternating serial reaction time)
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EEG, ECG and pupil data from young and older adults: rest and auditory cued reaction time tasks
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Dataset of "Cobalt and nickel doped WSe2 as efficient electrocatalysts for water splitting and as cathodes in hydrogen evolution reaction PEM water electrolysis"
<p>Efficient electrocatalysts are crucial for water splitting and fuel cells. Using cheap alternatives that can improve reaction kinetics is essntial for advancing fuel cell technology. Although, tungsten diselinide (WSe2) is promising for electrocatalysis is not fully explored, especially in oxygen evolution and in applications such as polymer electrolyte membrane water electrolyzer.<br>In this work, we used a simple approach to dope WSe2 with cobalt and/or nickel atoms. The doped material was subsequently tested for hydrogen evolution reaction and oxygen evolution reaction. Accordingly, the two electrocatalysts are highly active and stable, affording low overpotentials comparable to those of noble metals. The effective introduction of heteroatoms causes the retention of coordination vacancies, furnishing active catalytic sites that enhanced electrocatalytic performance both in activity and charge transfer. Moreover, both doped materials show excellent performance and stability as cathode electrocatalysts in the polymer electrolyte membrane water electrolyzer with great promise for real-world applications.</p>
Dataset for "Methodology of Evaluating the Activation Energy of Oxygen Reduction Reaction on Pt-based Electrodes"
<p>High temperature proton-exchange membrane fuel cell (HT-PEMFC) technology is widely studied alternative to current energy conversion technologies based on fossil fuels. Compared to solid oxide fuel cells (SOFCs), HT-PEMFCs allow more flexibility and demand less operation control due to their lower temperature. On the other hand, HT-PEMFCs show an advantage over low-temperature PEMFCs in terms of less demand on the purity of the H2 used, the possibility to recover the generated heat, lower water management requirements, and easy heat management. One of the critical limitations of HT-PEMFC operation is a slow kinetics of the cathodic reduction of O2 (ORR) due to presence of H3PO4 which ensures proton conductivity in the system. Electrochemical dynamic methods such as cyclic voltammetry or linear sweep voltammetry (LSV) can be used to determine the kinetic parameters of ORR. These measurements can provide information on the Tafel slope and exchange current density (jex) of the ORR. However, performing these measurements under conditions relevant for HT-PEMFC operation is challenging due to presence highly concentrated H3PO4 and elevated temperature. First, determination of the kinetic parameters requires correct assessment of equilibrium potential of ORR (EORR). The value of the EORR is generally influenced by the activity (fugacity) of the reactants and products and the temperature, a discussion of the appropriate standard states of the components is also necessary. Second, the relationship between the jex and the reaction rate constant (k°), necessary for calculation of activation energy ( ), must be known. It includes consideration of the likely reaction mechanism. In this paper, the methodology for appropriate determination of was developed and used for estimation of of ORR from LSV curves measured on commercially available Pt/C catalyst under HT-PEMFC relevant conditions. In particular, the measurements were carried out using a rotating glassy carbon rod disk electrode (RRE) in purified 98 wt.% H3PO4 (as electrolyte) at temperatures of 120, 140, 160, 180 °C. Though the treatment was developed in context of ORR and HT-PEMFC, the approach is generally applicable to any electrochemical reaction.</p>
Data set for the journal article ''Nanoscale chemical reaction exploration with a quantum magnifying glass''
<div>This data set includes the raw data of the esterification and hydrogenation discussed in the journal article alongside with the Scine Puffin Singularity container, steering protocol files, Swoose parameters, (pre-)releases of the software, and Python scripts for individual steps without the graphical user interface to reproduce the data.</div>
Dataset of "Marcus cross relation in the space of H-atom abstraction reactions boosted through off-diagonal thermodynamics"
<p>Proton-coupled electron transfer (PCET) and hydrogen-atom transfer (HAT) reactions play critical roles in biological processes and modern organic synthesis. The kinetics of these processes can align with the principles described in the renowned Marcus cross relation (MCR), a framework initially formulated to describe electron transfer mechanisms. The MCR provides an outstanding link between the kinetics of PCET/HAT reaction involving two distinct reactants and two related auxiliary self-exchange reactions – each between a molecule of one of the reactants and its coupled radical. In this study, we investigate the applicability and limitations of the canonical MCR across over 300 PCET and HAT reactions, providing a comprehensive theoretical analysis. Our findings reveal the need for an enhanced framework that incorporates ‘off-diagonal’ thermodynamic factors—asynchronicity and frustration. Of these factors, asynchronicity, which quantifies the imbalance between the proton vs. electron transfer components of the reaction, is identified as the dominant contributor to the improved predictive accuracy of the MCR. Notably, the incorporation of off-diagonal thermodynamics yields a more pronounced enhancement for HAT reactions than for PCET reactions. This advancement offers a refined theoretical basis for understanding H-atom abstraction mechanisms and underscores the importance of off-diagonal effects in PCET/HAT chemistry.</p>
Dataset of "Hydrogen Evolution Reaction Activity in Mo₂TiC₂Tₓ MXene Derived from Mo₂TiAlC₂ MAX Phase: Insights from Compositional Transformations"
<p>MAX phases represent a crucial building block for the synthesis of MXenes, which constitute an intriguing class of materials with significant application potential. This study investigates the catalytic properties of Mo₂TiAlC₂ MAX phase and the corresponding Mo₂TiC₂Tₓ MXene for hydrogen evolution reaction (HER). Characterization by X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and X-ray photoelectron spectroscopy (XPS) revealed that despite the presence of secondary phases, the HER catalytic activity is primarily influenced by the MAX phase and its derived MXene. Interestingly, the catalytic activity of the MXene improves over time, attributed to the formation of MoO₂ as identified by XPS. This work enhances the understanding of MXene-based materials for electrochemical applications, highlighting crucial structural and chemical transformations that optimize their performance in sustainable energy technologies.3D structure of lanthanum strontium manganite and yttria-stabilized zirconia composites is predicted based on conductivity measurements using Monte Carlo 3D equivalent circuit network approach. Validation experimental impedance spectra; scanning electron micrographs; cross sections of model simulation or prediction (MSP).</p>
Computational Supporting Information for How Chemical Environment Activates Anthralin and Molecular Oxygen for Direct Reaction
<p>The updated version of the dataset contains all original computational results, including validation of the level of theory, molecular structures, and analysis spreadsheets that are in support of our experimental observations of spontaneous reactivity of anthralin/dithranol molecule with molecular oxygen without any catalyst or co-substrate.<br> The paper was published in Journal of Organic Chemistry, 2020, 85(2), 1315–1321 (DOI: 10.1021/acs.joc.9b03133).</p> <p>In the meantime, the science was also also presented at the 8th ELSI Symposium, Tokyo Institute of Technology, Tokyo (Japan); February 3-7, 2020 in the context of molecular catalysis and their role in the chemical evolution of the building blocks of life.</p> <p>This version also has an important update that is being exclusively published here on Zenodo. The selected level of theory (MN15 functional with triple-zeta quality basis set supplemented with BOTH diffuse and polarization basis functions) is further confirmed to be one of the most reasonable one among 98 commonly used functionals.</p>
Data for: "Direct photochemical control of imine exchange reactions"
<div>This dataset is all of the data produced which relates to the text "Direct photochemical control of imine exchange reactions"</div> <div> </div> <div>The data set is separated loosely into </div> <div> </div> <div>1) Computational-data : All of the simulated data<br> <br>2) Kinetics : All of the data which lead to the nmr-time monitored experiments, where samples were equilibrated then irradiated and heated<br> <br>3) Photophysical-characterisation : All UV-VIS spectra and luminance spectra<br> <br>4) Synthetic-data-and-charcterisation : the details of the synthetises, and the 1H NMR, 13C NMR, IR, Mass-Spec, and Elemental analysis data<br> <br> <br>Generally within these folders, subfolders, subsubfolders etc. the folders contain zipped HTML copies of the lab notebooks, images of the graphs which result from them, and code which has generated them. Within further folders will be data which produces these graphs.<br> <br> <br>The way to interact with the compressed HTML lab notebooks, is to unzip them, and then open the HTML files.<br> <br> <br>Warning: The code for generating the graphs has not been cleaned up; it is presented as it was at time of publication. It will take some time for you to follow it, not because it is complex, but because it includes a lot of unnecessary diversions. Often I was working out how to process the data as I programmed them.<br> </div> <div> </div> <div> </div> <div>Where to find this data for each figure is given as follows:</div> <div> </div> <div>Figure 1: -not data-</div> <div> </div> <div>Figure 2: .\photophysical-characterisation\Imines-UV-VIS</div> <div> </div> <div>Figure 3: .\Kinetics\Kinetic-main</div> <div> </div> <div>Figure 4: .\Kinetics\Kinetic-temperature</div> <div> </div> <div>Figure 5: .\Computational-data</div> <div> </div> <div>Figure S1: .\photophysical-characterisation\Amines-UV-VIS</div> <div> </div> <div>Figure S2: .\Kinetics\Supplementary-kinetic</div> <div> </div> <div>Figure S3: .\Kinetics\Supplementary-temperature-kinetic</div> <div> </div> <div>Figure S4: .\Computational-data</div> <div> </div> <div>Figure S5: .\Kinetics\Kinetic-main\nmr\A-4-20-1mnova.mnova</div> <div> </div> <div>Figure S6: .\Kinetics\Kinetic-main\nmr\A-4-21-1mnova.mnova</div> <div> </div> <div>Figure S7: .\Synthetic-data-and-characterisation\[compound-data]\1H-NMR</div> <div> </div> <div>Figure S8: .\Synthetic-data-and-characterisation\[compound-data]\1H-NMR</div> <div> </div> <div>Figure S9: .\photophysical-characterisation\LED-Luminence</div> <div> </div> <div>Figure S10: .\photophysical-characterisation\LED-Luminence</div> <div> </div> <div>Figure S11: -not data-</div> <div> </div> <div>Figure S12: -not data-</div> <div> </div> <div>Figure S13: .\Synthetic-data-and-characterisation\Characterisation_A-imine\1H-NMR</div> <div> </div> <div>Figure S14: .\Synthetic-data-and-characterisation\Characterisation_MA-imine\1H-NMR</div> <div> </div> <div>Figure S15: .\Synthetic-data-and-characterisation\Characterisation_DMMA-imine\1H-NMR</div> <div> </div> <div>Figure S16: .\Synthetic-data-and-characterisation\Characterisation_FLUR-imine\1H-NMR</div> <div> </div> <div> </div> <div> </div> <div> </div> <div>The dataset contains details of the following compounds:</div> <div> </div> <div>Article name: A-Imine</div> <div> </div> <div>IUPAC name: (E)-N-phenyl-1-(thieno[3,2-b]thiophen-2-yl)methanimine</div> <div> </div> <div>SMILES Code: C1(/N=C/C2=CC(SC=C3)=C3S2)=CC=CC=C1</div> <div> </div> <div>SLN: C[2](N=[S=I]CC[8]=CC(SC=C[16])=C@16S@9)=CC=CC=C@3</div> <div> </div> <div>InChI: 1S/C13H9NS2/c1-2-4-10(5-3-1)14-9-11-8-13-12(16-11)6-7-15-13/h1-9H/b14-9+</div> <div> </div> <div>InChI key: FMENSGUUZYOJTA-NTEUORMPSA-N</div> <div> </div> <div> </div> <div>Article name: DMMA-Imine</div> <div> </div> <div>IUPAC name: (E)-N,N-dimethyl-4-((thieno[3,2-b]thiophen-2-ylmethylene)amino)aniline</div> <div> </div> <div>SMILES Code: CN(C)C1=CC=C(/N=C/C2=CC(SC=C3)=C3S2)C=C1</div> <div> </div> <div>SLN: CN(C)C[1]=CC=C(N=[S=I]CC[9]=CC(SC=C[17])=C@17S@10)C=C@2</div> <div> </div> <div>InChI: InChI=1S/C15H14N2S2/c1-17(2)12-5-3-11(4-6-12)16-10-13-9-15-14(19-13)7-8-18-15/h3-10H,1-2H3/b16-10+</div> <div> </div> <div>InChI key: XWBXQJOJYSCJCK-MHWRWJLKSA-N</div> <div> </div> <div> </div> <div>Article name: FLUR-Imine</div> <div> </div> <div>IUPAC name: (E)-N-(9H-fluoren-2-yl)-1-(thieno[3,2-b]thiophen-2-yl)methanimine</div> <div> </div> <div>SMILES Code: C1(C=CC=C2)=C2C(C=CC(/N=C/C3=CC(SC=C4)=C4S3)=C5)=C5C1</div> <div> </div> <div>SLN: C[1](C=CC=C[13])=C@13C(C=CC(N=[S=I]CC[16]=CC(SC=C[23])=C@23S@16)=C[8])=C@9C@2</div> <div> </div> <div>InChI: InChI=1S/C20H13NS2/c1-2-4-17-13(3-1)9-14-10-15(5-6-18(14)17)21-12-16-11-20-19(23-16)7-8-22-20/h1-8,10-12H,9H2/b21-12+</div> <div> </div> <div>InChI key: RSZKSUGPHCONDB-CIAFOILYSA-N</div> <div> </div> <div> </div> <div>Article name: MA-Imine</div> <div> </div> <div>IUPAC name: (E)-1-(thieno[3,2-b]thiophen-2-yl)-N-(p-tolyl)methanimine</div> <div> </div> <div>SMILES Code: CC1=CC=C(/N=C/C2=CC(SC=C3)=C3S2)C=C1</div> <div> </div> <div>SLN: CC[1]=CC=C(N=[S=I]CC[9]=CC(SC=C[17])=C@17S@10)C=C@2</div> <div> </div> <div>InChI: InChI=1S/C14H11NS2/c1-10-2-4-11(5-3-10)15-9-12-8-14-13(17-12)6-7-16-14/h2-9H,1H3/b15-9+</div> <div> </div> <div>InChI key: XARWNOWDJRWLJY-OQLLNIDSSA-N</div> <div> </div> <div> </div> <div>IUPAC name: (E)-4-((thieno[3,2-b]thiophen-2-ylmethylene)amino)benzonitrile</div> <div> </div> <div>SMILES Code: N#CC1=CC=C(/N=C/C2=CC(SC=C3)=C3S2)C=C1</div> <div> </div> <div>SLN: N#CC[5]=CC=C(N=[S=I]CC[8]=CC(SC=C[16])=C@16S@9)C=C@6</div> <div> </div> <div>InChI: InChI=1S/C14H8N2S2/c15-8-10-1-3-11(4-2-10)16-9-12-7-14-13(18-12)5-6-17-14/h1-7,9H/b16-9+</div> <div> </div> <div>InChI key: MTCNXZQWYYVDCG-CXUHLZMHSA-N</div> <div> </div> <div> </div> <div>IUPAC name: (E)-N-(4-methoxyphenyl)-1-(thieno[3,2-b]thiophen-2-yl)methanimine</div> <div> </div> <div>SMILES Code: COC1=CC=C(/N=C/C2=CC(SC=C3)=C3S2)C=C1</div> <div> </div> <div>SLN: COC[5]=CC=C(N=[S=I]CC[8]=CC(SC=C[16])=C@16S@9)C=C@6</div> <div> </div> <div>InChI: InChI=1S/C14H11NOS2/c1-16-11-4-2-10(3-5-11)15-9-12-8-14-13(18-12)6-7-17-14/h2-9H,1H3/b15-9+</div> <div> </div> <div>InChI key: WIBJKKCQZPFCIZ-OQLLNIDSSA-N</div> <div> </div> <div> </div> <div>Article name: A-Amine</div> <div> </div> <div>IUPAC name: Benzenamine</div> <div> </div> <div>Common name: Aniline</div> <div> </div> <div>SMILES Code: NC1=CC=CC=C1</div> <div> </div> <div>SLN: NC[2]=CC=CC=C@3</div> <div> </div> <div>InChI: InChI=1S/C6H7N/c7-6-4-2-1-3-5-6/h1-5H,7H2</div> <div> </div> <div>InChI key: PAYRUJLWNCNPSJ-UHFFFAOYSA-N</div> <div> </div> <div>CAS no: 62-53-3</div> <div> </div> <div> </div> <div> </div> <div>Article name: MA-Amine</div> <div> </div> <div>IUPAC name: 4-Aminotoluene</div> <div> </div> <div>Common name: p-toludine</div> <div> </div> <div>SMILES Code: NC1=CC=CC=C1</div> <div> </div> <div>SLN: NC[2]=CC=CC=C@3</div> <div> </div> <div>InChI: InChI=1S/C6H7N/c7-6-4-2-1-3-5-6/h1-5H,7H2</div> <div> </div> <div>InChI key: PAYRUJLWNCNPSJ-UHFFFAOYSA-N</div> <div> </div> <div>CAS no: 106-49-0</div> <div> </div> <div> </div> <div>Article name: DMMA-Amine</div> <div> </div> <div>IUPAC name: N1,N1-dimethylbenzene-1,4-diamine</div> <div> </div> <div>SMILES Code: NC1=CC=C(N(C)C)C=C1</div> <div> </div> <div>SLN: NC[2]=CC=C(N(C)C)C=C@3</div> <div> </div> <div>InChI: InChI=1S/C8H12N2/c1-10(2)8-5-3-7(9)4-6-8/h3-6H,9H2,1-2H3</div> <div> </div> <div>InChI key: BZORFPDSXLZWJF-UHFFFAOYSA-N</div> <div> </div> <div>CAS no: 99-98-9</div> <div> </div> <div> </div> <div>Article name: FLUR-Amine</div> <div> </div> <div>IUPAC name: 9H-fluoren-2-amine</div> <div> </div> <div>SMILES Code: NC1=CC(CC2=C3C=CC=C2)=C3C=C1</div> <div> </div> <div>SLN: NC[2]=CC(CC[8]=C[9]C=CC=C@9)=C(@10)C=C@3</div> <div> </div> <div>InChI: InChI=1S/C13H11N/c14-11-5-6-13-10(8-11)7-9-3-1-2-4-12(9)13/h1-6,8H,7,14H2</div> <div> </div> <div>InChI key: CFRFHWQYWJMEJN-UHFFFAOYSA-N</div> <div> </div> <div>CAS no: 153-78-6</div> <div> </div> <div> </div> <div>IUPAC name: 4-aminobenzonitrile</div> <div> </div> <div>SMILES Code: NC1=CC=C(C#N)C=C1</div> <div> </div> <div>SLN: NC[2]=CC=C(C#N)C=C@3</div> <div> </div> <div>InChI: InChI=1S/C7H6N2/c8-5-6-1-3-7(9)4-2-6/h1-4H,9H2</div> <div> </div> <div>InChI key: YBAZINRZQSAIAY-UHFFFAOYSA-N</div> <div> </div> <div>CAS no: 873-74-5</div> <div> </div>
heat of hydrogenation for diverse organic compounds -- experimental and calculated data for 166 unique reactions
<h3>General remarks</h3> <p>The experimental data was drawn from reactions involving H2 that are available at <a href="https://webbook.nist.gov/cgi/cbook.cgi?Name=H2&Units=SI&cTR=on" target="_blank" rel="noopener">NIST</a> (accessed on 15/03/2024). Only reactions of type<strong><em> M + H2 => MH2</em></strong>, where M is a neutral, closed-shell organic molecule that accepts one equivalent of H2, were included in the collection. M corresponds to the oxidized form of the molecule ( => suffix '_ox'), MH2 to the reduced form (=> suffix '_red'). For reasons of clarity, the references to original publications were abbreviated in the main table (look up in separate table).</p> <p>For the molecules involved, Smiles were manually assigned. From those, 3D structures were generated and evaluated in order to match the thermodynamic properties as accurately as possible (for details on the procedure refer to the related work, see below).</p> <p>In addition to the experimental uncertainty, a significant scatter is seen for replicate measurements.</p> <p><strong>Please note</strong>: To compute the heat of hydrogenation from the calculated data for M/MH2 the contribution of H2 needs to be considered, take e.g. -1.164816 hartree (Energy at 298.15K, calculated at CCSD(T)=FULL/aug-cc-pVDZ) from <a href="https://cccbdb.nist.gov/energy3x.asp?method=63&basis=17&charge=0" target="_blank" rel="noopener">CCCBDB</a> (accessed on 15/03/2024).</p> <h3> </h3> <h3>Description of files</h3> <p>The file <strong>01_heat_of_hydrogenation_XP+QM.csv</strong> contains experimentally measured and calculated data.</p> <ul> <li>columns are separated by "|"</li> <li>column names and explanations: <ul> <li><strong>NIST_idx</strong> -- index of original reaction, mostly unique. In a few cases, data of the reverse reaction were subsumed under a different index</li> <li><strong>env</strong> -- if available, information about the environment a reported reaction took place in, e.g. gas phase, hexane, etc...</li> <li><strong>method</strong> -- if available, reference about the experimental technique, e.g. 'Eqk' = Heat of equilibrium, 'Cm' = Calorimetry, 'Chyd' = Calorimetry of hydrogenation</li> <li><strong>Temperature K</strong> -- if available, reported values </li> <li><strong>reference</strong> -- Abbreviation of reference to original publication</li> <li><strong>experimental heat of reaction kJ/mol</strong> -- measured value as reported by experimentalists</li> <li><strong>experimental uncertainty </strong>-- if available, uncertainty of measurement reported by experimentalists</li> <li><strong>comments</strong> -- notes relating to identification of compounds</li> <li><strong>SMILES_ox</strong> -- isomeric canonical SMILES for oxidized form M</li> <li><strong>InChI_ox</strong> -- InChI for oxidized form M </li> <li><strong>SMILES_red</strong> -- isomeric canonical SMILES for reduced form M</li> <li><strong>InChI_red </strong>-- InChI for reduced form M</li> <li><strong>reaction_index </strong>-- consequtively numbered for identical pairs (SMILES_ox, SMILES_red)<strong><br></strong></li> <li>the calculated properties are given for the oxidized and reduced form of the molecule (in hartree) <ul> <li><strong>E(B3LYP/6-31G(2df,p))</strong></li> <li><strong>E_thermal</strong></li> <li><strong>E(G4(MP2))@0K</strong></li> <li><strong>E(G4(MP2))@298K</strong></li> <li><strong>H(G4(MP2))</strong></li> <li><strong>heat_of_formation@0K</strong></li> <li><strong>heat_of_formation@298K</strong></li> </ul> </li> </ul> </li> </ul> <p><strong>02_molecules.sdf:</strong> provides for each molecule a low-energy geometry along with some descriptors and calculated energetic properties:</p> <blockquote> <ul> <li>coordinate block + bond information</li> <li>properties <ul> <li><strong>SMILES</strong> -- isomeric canonical smiles linking compound to reactions defined in 01_heat_of_hydrogenation_XP+QM.csv</li> <li><strong>radical_electrons</strong> -- number of unpaired electrons as determined by RDKit</li> <li><strong>empirical_formula</strong> -- elemental composition of molecule</li> <li><strong>molecular_weight</strong> -- as determined by RDKit in g/mol</li> <li><strong>TPSA </strong>-- topological polar surface area (<em>TPSA</em>) as determined by RDKit</li> <li><strong>logP </strong>-- octanol/water partition coefficient as predicted by RDKit</li> <li><strong>nof_heavy_atoms --</strong> number of non-hydrogen atoms in molecule</li> <li><strong>degree_of_unsaturation</strong> -- sum of multiplebonds and/or rings present in the compound</li> <li><strong>rings</strong> -- number of rings in the compound as determined by RDKit</li> <li><strong>multiplicity</strong> -- spin multiplicity for use as input for QM calculations</li> <li><strong>nof_multiple_bonds</strong> -- number of multiple bonds as determined by RDKit</li> <li><strong>Std_InChI</strong> -- standard InChi</li> <li><strong>FixedH_InChI</strong> -- variant of InChI to differentiate tautomers</li> <li><strong>tag </strong>-- dataset label</li> <li><strong>total_atoms </strong>-- total number of atoms (including H)</li> <li><strong>net_charge</strong> -- total charge of molecule in units of elementary charge</li> <li> <p>energetic properties (in hartree) </p> <ul> <li> <p><code>E(B3LYP/6-31G(2df,p))</code></p> </li> <li> <p><code>E</code><code>(HF/maug-cc-p(T+d)Z) </code></p> </li> <li> <p><code>E(HF/CBS)</code></p> </li> <li> <p><code>E(HF/maug-cc-p(Q+d)Z) </code></p> </li> <li> <p><code>E(MP2/6-31G(d))</code></p> </li> <li> <p><code>E(CCSD(T)/6-31G(d))</code></p> </li> <li> <p><code>E(HF/G3MP2LARGEXP) </code></p> </li> <li> <p><code>E(MP2/G3MP2LARGEXP)</code></p> </li> <li> <p><code>DE(MP2) hartreeDE(HF)</code></p> </li> <li> <p><code>ZPE(B3LYP) hartree</code></p> </li> <li> <p><code>ZPE_scale_factor hartree</code></p> </li> <li> <p><code>E(HLC) hartree</code></p> </li> <li> <p><code>E_thermal hartree</code></p> </li> <li> <p><code>H_thermal hartree</code></p> </li> <li> <p><code>E(G4(MP2))@0K hartree</code></p> </li> <li> <p><code>E(G4(MP2))@298K hartree</code></p> </li> <li> <p><code>H(G4(MP2)) hartree</code></p> </li> <li> <p><code>heat_of_formation@0K kcal/mol</code></p> </li> <li> <p><code>heat_of_formation@298K kcal/mol</code></p> </li> </ul> </li> </ul> </li> </ul> </blockquote> <p><strong>03_references.csv</strong> (separated by "|") lists abbreviations and corresponding full reference to original publication of individual data points.</p>
BIRAFFE2: The 2nd Study in Bio-Reactions and Faces for Emotion-based Personalization for AI Systems
<p>This is our 2nd Study in Bio-Reactions and Faces for Emotion-based Personalization for AI Systems (<strong>BIRAFFE2</strong>). It is a dataset consisting of <em><strong>electrocardiogram (ECG)</strong></em>, <em><strong>galvanic skin response (GSR)</strong></em>, changes in <em><strong>facial expression</strong></em> signals and <em><strong>hand movements</strong></em> (represented by gamepad's accelerometer and gyroscope) recorded during affect elicitation by means of <em><strong>audio-visual stimuli</strong></em> (from IADS and IAPS databases) and our proof-of-concept three-level <em><strong>emotion evoking game</strong></em>. All the signals were captured using portable and low-cost equipment: BITalino (r)evolution kit for ECG and GSR and Creative Live! web camera for face photos (further analyzed by MS Face API).</p> <p>Besides the signals, the dataset consists also of <em><strong>participants' self-assessment</strong></em> of their affective state after each stimuli (in the <em><strong>valence and arousal dimensions</strong></em>), <em><strong>"Big Five" personality traits</strong></em> assessment (using NEO-FFI inventory), and <em><strong>game involvement</strong></em>-related metrics (using GEQ questionnaire).</p> <p>In 1.1.0 version, RAW questionnaire data was included. The licence was changed from CC BY-NC-ND 4.0 to CC BY 4.0.</p> <p>For detailed description see <a href="https://doi.org/10.1038/s41597-022-01402-6">BIRAFFE2 Data Descriptor in Nature Scientific Data</a>.<br> For preview of the files before downloading the whole dataset see <em>sample-SUB211-[...]</em> files.</p> <p>All documents and papers that report on research that uses the BIRAFFE dataset should acknowledge this by <strong>citing the paper</strong>:<br> Kutt, K., Drążyk, D., Żuchowska, L., Szelążek, M., Bobek, S., & Nalepa, G. J. (2022). <strong>BIRAFFE2, a multimodal dataset for emotion-based personalization in rich affective game environments</strong>. <em>Scientific Data</em>, <em>9</em>, 274. <a href="https://doi.org/10.1038/s41597-022-01402-6">https://doi.org/10.1038/s41597-022-01402-6</a></p>
Dataset of Scanning Tunneling Microscopy (STM) images of model surfaces for elementary steps in catalytic reactions
<p>STM images presented in the dataset were recorded by the STRAS research group using a Omicron Variable Temperature STM (VT-STM) microscope, in the TASC laboratory of the CNR-IOM in Trieste.</p> <p>This work has been done within the NFFA-DI project funded by the European Union – NextGenerationEU - Missione 4, “Istruzione e Ricerca” – Componente 2, “Dalla ricerca all'impresa” – Linea di investimento 3.1,“Fondo per la realizzazione di un sistema integrato di infrastrutture di ricerca e innovazione” – Azione 3.1.1, “Creazione di nuove IR o potenziamento di quelle esistenti che concorrono agli obiettivi di Eccellenza Scientifica di Horizon Europe e costituzione di reti”.</p>
Seeing nanoscale electrocatalytic reactions at individual MoS2 particles under an optical microscope: probing sub-mM oxygen reduction reaction
<p><span>Data in this repository include raw iSCAT optical microscopy movies for the operando monitoring of oxygen reduction reaction at bare ITO and MoS2-coated ITO electrodes in KCl solution in the presence or absence of La<sup>3+</sup> with their respective electrochemical data (voltammograms). </span></p>
Data in New $^{63}$Ga(p,$\gamma$)$^{64}$Ge and $^{64}$Ge(p,$\gamma$)$^{65}$As reaction rates corresponding to the temperature regime of thermonuclear X-ray bursts
<p>Abstract quoted from <a href="https://doi.org/10.1103/PhysRevC.110.065804" target="_blank" rel="noopener">Physical Review C 110 (2024) 065804</a> [<a href="https://arxiv.org/abs/2406.14624">arXiv:2406.14624</a>] </p> <p>We compute the $^{63}$Ga(p,$\gamma$)$^{64}$Ge and $^{64}$Ge(p,$\gamma$)$^{65}$As thermonuclear reaction rates using the latest experimental input supplemented with theoretical nuclear spectroscopic information. The experimental input consists of the latest proton thresholds of $^{64}$Ge and $^{65}$As, and the nuclear spectroscopic information of $^{65}$As, whereas the theoretical nuclear spectroscopic information for $^{64}$Ge and $^{65}$As are deduced from the full <em>pf</em>-shell space configuration-interaction shell-model calculations with the GXPF1A Hamiltonian. Both thermonuclear reaction rates are determined with known uncertainties at the energies that correspond to the Gamow windows of the temperature regime relevant to type I x-ray bursts, covering the typical temperature range of the thermonuclear runaway of the GS 1826$-$24 periodic bursts and SAX J1808.4$-$3658 photospheric radius expansion bursts. </p>
Dataset for Reaction-Induced Formation of Stable Mononuclear Cu(I)Cl Species on Carbon for Low-Footprint Vinyl Chloride Production
<p>This dataset complements the publication entitled "Reaction-Induced Formation of Stable Mononuclear Cu(I)Cl Species on Carbon for Low-Footprint Vinyl Chloride Production" by Dario Faust Akl, Georgios Giannakakis, Andrea Ruiz-Ferrando, Mikhail Agrachev, Juan D. Medrano-García, Gonzalo Guillén-Gosálbez, Gunnar Jeschke, Adam H. Clark, Olga V. Safonova, Sharon Mitchell, Núria López, Javier Pérez-Ramírez.</p>
Imaging the footprint of nanoscale electrochemical reactions for assessing synergistic hydrogen evolution
<p>Dataset complementary to supporting information, such as optical movies, COMSOL model, and Python codes to analyze the experimental and simulated data according to the manuscript submitted for publication.<br> The movies correspond to cyclic voltammetry operando monitoring by optical microscopy of the reduction of water + KCl in the presence of NiCl2 at an ITO electrode or NiCl2 or MgCl2 at ITO electrode coated with Pt nanoparticles.</p> <p>The python function was used to extract the halo size around each nanoparticle from optical images, the python routines were used to postprocess the COMSOL simulation and evalaute the simulated halo size.</p>
Optimized structures of the stationary points on the potential energy surface of the OH(2Π) + C2H4 reaction
<p>This Zip file contains the cartesian coordinates of optimized stationary points of the OH(<sup>2</sup>Π) + C<sub>2</sub>H<sub>4</sub> potential energy surface published in our article “OH(<sup>2</sup>Π) + C<sub>2</sub>H<sub>4</sub> Reaction: A Combined Crossed Molecular Beam and Theoretical Study” (P<em>hys. Chem. A</em> 2023, 127, 21, 4609–4623), that can be found in <a href="https://doi.org/10.1021/acs.jpca.2c08662">https://doi.org/10.1021/acs.jpca.2c08662</a>.</p> <p>All calculations have been performed with Gaussian 09, Revision D.01.</p> <p>All structures have been optimized at B3LYP/aug-cc-pVTZ level of theory.</p>
Optimized structures of the stationary points on the potential energy surface of the O(3P, 1D) + HCCCN(X1Σ+) reaction
<p>This Zip file contains the cartesian coordinates of optimized stationary points of the O(<sup>3</sup>P, <sup>1</sup>D) + HCCCN(X<sup>1</sup>Σ<sup>+</sup>) potential energy surface published in our article “Reactions O(<sup>3</sup>P, <sup>1</sup>D) + HCCCN(X<sup>1</sup>Σ<sup>+</sup>) (Cyanoacetylene): Crossed-Beam and Theoretical Studies and Implications for the Chemistry of Extraterrestrial Environments” (<em>J. Phys. Chem. A</em> 2023, 127, 3, 685–703), that can be found in <a href="https://doi.org/10.1021/acs.jpca.2c07708">https://doi.org/10.1021/acs.jpca.2c07708</a>.</p> <p>All calculations have been performed with Gaussian 09, Revision D.01.</p> <p>All structures have been optimized at B3LYP/aug-cc-pVTZ level of theory.</p>
Supplementary files for "A comparison of single and double Co sites incorporated in N-doped graphene for the oxygen reduction reaction"
<p>DFT optimised structures used for the paper "A comparison of single and double Co sites incorporated in N-doped graphene for the oxygen reduction reaction". There is a separate database for structures on the Co-N4 single site, each of the Co double sites and the molecular references. Manual and NEB paths for the splitting of OOH and O2 are included as separate databases. The structures can be retrieved using the Atomic Simulation Environment (ASE, https://wiki.fysik.dtu.dk/ase/).</p>
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.