Find research datasets worth reusing
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7
datasets available to search
ShareScore release 0.9.0
Dataset results
7 results for “polarizable embedding”
Dataset for the article "Cost-effective Potential for Accurate Polarizable Embedding Calculations in Protein Environments"
<p>This dataset contains additional material related to the article: "Cost-effective Potential for Accurate Polarizable Embedding Calculations in Protein Environments". Final version of the article is available at <a href="https://doi.org/10.1021/acs.jctc.9b00616">https://doi.org/10.1021/acs.jctc.9b00616</a> (paywall). A preprint is freely available at <a href="https://doi.org/10.26434/chemrxiv.8126912">https://doi.org/10.26434/chemrxiv.8126912</a>. See <em>readme.md</em> for further description.</p>
Dataset for "Analytic High-order Geometric Derivatives with Polarizable Embedding in a Response Function Framework"
<p>This dataset contains data for the article "Analytic High-order Geometric Derivatives with Polarizable Embedding in a Response Function Framework"</p>
Dataset for the tutorial: "Response properties of embedded molecules through the polarizable embedding model"
<p>Dataset for the tutorial "<em>Response properties of embedded molecules through the polarizable embedding model</em>". The abstract is the following:</p> <blockquote> <p>"<em>The polarizable embedding (PE) model is a fragment-based quantum–classical approach aimed at accurate inclusion of environment effects in quantum-mechanical response property calculations. The aim of this tutorial is to give insight into the practical use of the PE model. Starting from a set of molecular structures and until you arrive at the final property, there are many crucial details to consider in order to obtain trustworthy results in an efficient manner. To lower the threshold for new users wanting to explore the use of the PE model, we describe and discuss important aspects related to its practical use. This includes directions on how to generate input files and how to run a calculation.</em>"</p> </blockquote> <p>The dataset contains files that can be used in direct connection with the tutorial (<em>getting-started.zip</em>), and an additional set of files that can be used for further exploration (<em>peqm-inputs.zip</em>). </p>
Dataset for the article "Polarizable Embedding without Artificial Boundary Polarization"
<p>This dataset contains additional material related to the article: "Polarizable Embedding without Artificial Boundary Polarization". A preprint is freely available at https://doi.org/10.26434/chemrxiv-2023-fc0gk. See readme.md for further description.</p>
Dataset for the article "Polarizable Embedding Potentials through Molecular Fractionation with Conjugate Caps including Hydrogen Bonds"
<p>This dataset contains additional material related to the article: "Polarizable Embedding Potentials through Molecular Fractionation with Conjugate Caps including Hydrogen Bonds". The published article can be found at <a href="https://doi.org/10.1021/acs.jctc.3c00613">https://doi.org/10.1021/acs.jctc.3c00613</a>. A preprint is freely available at <a href="https://doi.org/10.26434/chemrxiv-2023-vb01m-v2">https://doi.org/10.26434/chemrxiv-2023-vb01m-v2</a>. Each folder contains a <em>Readme.md</em> for further description.</p>
Dataset for the "Harmonic Infrared and Raman Spectra in Molecular Environments using the Polarizable Embedding Model"
<p>This dataset contains data connected to the article "Harmonic infrared and Raman spectra using a polarizable embedding model".</p>
Supplementary Information: On the Role of Dielectric Screening in Calculating Excited States of Solvated Azobenzene: A Benchmark Study Comparing Quantum Embedding and Polarizable Continuum Model for Representing the Solvent
<p>Link to Gitlab repo: https://gitlab.com/jezsmartinez/azobencene_ep/-/tree/main</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.