Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
4
datasets available to search
ShareScore release 0.9.0
Dataset results
4 results for “TD-DFT”
TD-DFT of Dipyrrolonaphthyridinedione (DPND) Annihilators
<p><span>Molecular geometry of the first excited triplet (T1) and singlet (S1) state energies of DPND derivatives 1-6 were modelled using the quantum chemistry software Gaussian. Density functional theory (DFT) geometry optimization was performed using the B3LYP/6-31G(d) functional/basis set in a vacuum. The T1 and S1 energies were obtained by employing time dependent DFT calculations with the same functional/basis set.</span></p>
TD-DFT of Diketopyrrolopyrrole (DPP) Annihilators
<p>Molecular geometry of the excited triplet and singlet state energies of DPP derivatives (DPP-S-Th, DPP-Th, DPP-S-2tb-Th, and DPP-2tb-Th) were modelled using the quantum chemistry software ORCA. Density functional theory (DFT) geometry optimization was performed using the B3LYP/6-31G(d) functional/basis set in a vacuum. The T1, T2 and S1 energies were obtained by employing time dependent DFT calculations with the same functional/basis set.</p>
Progeny Project DFT and TD-DFT data for MW1 and its variants with different side chain length
<p>DFT and TD-DFT data, i.e. geometries, electronic excited states for the MW1 and its variants in vacuum with different length of side chains.</p> <p>See Readme.txt for more details.</p>
TS42 TD-DFT Dipole Polarizabilities as a function of imaginary frequency
<p><strong>How the data was generated</strong></p> <p>The list of molecules was taken from the paper <a href="https://doi.org/10.1103/PhysRevLett.102.073005">Accurate Molecular Van Der Waals Interactions from Ground-State Electron Density and Free-Atom Reference Data</a>, Alexandre Tkatchenko and Matthias Scheffler, Phys. Rev. Lett. 102, 073005 (2009).</p> <p>Initial molecular geometries were obtained from the <a href="https://cccbdb.nist.gov">CCCBDB</a> database. Various electronic structure calculations were performed on these molecular geometries.</p> <p>Computational details can be found in the software section below and in the paper <a href="https://doi.org/10.1063/5.0115151">A new framework for frequency-dependent polarizable force fields</a>, YingXing Cheng and Toon Verstraelen, J. Chem. Phys. 157, 124106 (2022)</p> <p><strong>Software that was used</strong></p> <p>The optimized structures were initially published as supporting information in <a href="https://doi.org/10.1063/5.0115151">A new framework for frequency-dependent polarizable force fields</a>. For this work, the molecular structures were optimized using DFT at <code>B3LYP/aug-cc-pVDZ</code> level with <a href="https://gaussian.com/">GAUSSIAN16</a>.</p> <p>The MBIS partitioning was done with <a href="https://theochem.github.io/horton/2.1.1/index.html">Horton 2.1.1</a> and the distributed response calculations were done with the <a href="https://github.com/yingxingcheng/LRC-CD/tree/for_acks2w_paper"><code>for_acks2w_paper</code></a> branch of the <code>LRC-CD</code> python package. <strong>Note</strong>: The LRC-CD package is still a private repository, but it is available upon proper request.</p> <p>The TD-DFT reference data are calculated with <a href="https://daltonprogram.org/">Dalton 2020</a>.</p> <p><strong>Directory and file organization</strong></p> <ul> <li><code>README.md</code>: This file.</li> <li><code>structures/*.xyz</code>: the molecular structures optimized at the <code>B3LYP/aug-cc-pVDZ</code> level of theory.</li> <li><code>aDZ_lda_0.json</code>: the ACKS2ω polarizability for ℓ<sub>max</sub>=0.</li> <li><code>aDZ_lda_1.json</code>: the ACKS2ω polarizability for ℓ<sub>max</sub>=1.</li> <li><code>aDZ_lda_2.json</code>: the ACKS2ω polarizability for ℓ<sub>max</sub>=2.</li> <li><code>aDZ_lda_3.json</code>: the ACKS2ω polarizability for ℓ<sub>max</sub>=3.</li> <li><code>aDZ_lda_4.json</code>: the ACKS2ω polarizability for ℓ<sub>max</sub>=4.</li> <li><code>aDZ_lda_tddft.json</code>: the reference results calculated using TD-DFT.</li> <li><code>aDZ_lda_1_00.json</code>: the charge-flow contribution to the ACKS2ω polarizability.</li> <li><code>aDZ_lda_1_11.json</code>: the dipole-dipole contribution to the ACKS2ω polarizability data with the dipole-dipole contribution.</li> <li><code>aDZ_lda_1_01.json</code>: the charge-dipole contribution to the ACKS2ω polarizability data with the charge-dipole contribution.</li> <li><code>aDZ_lda_1_10.json</code>: the dipole-charge contribution to the ACKS2ω polarizability data with the dipole-charge contribution.</li> </ul> <p><strong>Note</strong>: The results in <code>aDZ_lda_1_01.json</code> and <code>aDZ_lda_1_10.json</code> can be added to obtain the complete charge + dipole contribution to the polarizability.</p> <p><strong>File content details</strong></p> <p>Each JSON file corresponds to a specific multipole contributions, as explained above. The JSON files contains a hierarchical set of <em>dictionaries</em> (or <em>objects</em>), structured as follows:</p> <ol> <li>Top level = the molecule name</li> <li>For each molecule, data is grouped by (imaginary) frequency.</li> <li>For each molecule and frequency, a <em>list</em> (or <em>array</em>) of 9 elements represent components of the dipole polarizability tensor in the order α<sub>xx</sub>, α<sub>xy</sub>, α<sub>xz</sub>, α<sub>yx</sub>, α<sub>yy</sub>, α<sub>yz</sub>, α<sub>zx</sub>, α<sub>zy</sub>, α<sub>zz</sub>.</li> </ol>
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.