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<h1><span style="color: rgb(144, 144, 144);">M</span><span style="color: rgb(97, 131, 216);">X</span>enes Database</h1>
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This database was created based on the results obtained after a comprehensive computational screening of over 4000 MXene structures, published in
<a href="https://doi.org/10.1002/eem2.12774" target="_blank"><em>Energy Environ. Mater.</em> 2024, <strong>7</strong>, e12774</a> and
<a href="https://doi.org/10.1039/D3TA01933K" target="_blank"><em>J. Mater. Chem. A</em> 2023, <strong>11</strong>, 13754-13764</a>.
It has been used to develop the <a href="https://github.com/diegonti/mxgap">MXgap</a> program, a Machine Learning tool to predict MXene bandgaps.
The database is oficially published in <a href="https://doi.org/10.1021/acscatal.5c04191" target="_blank"><em>ACS Catal.</em> 2025, <strong> 15</strong>, 14403-14413</a>. So, if you use this database, please cite:
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<pre>D. Ontiveros, S. Vela, F. Viñes, C. Sousa, ACS Catal., 2025, 15, 14403-14413. DOI: 10.1021/acscatal.5c04191</pre>
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On the website, you can easily search for various MXene structures and retrieve essential information such as lattice parameters, widths, bandgap information, and even download the optimized CONTCAR file.
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Keep in mind that this is a smaller version of the full one used to train the MXgap models, just to make the web. The full official database can be found at
<a href="https://doi.org/10.5281/zenodo.14858915" target="_blank">https://doi.org/10.5281/zenodo.14858915</a>, and can be cited through the corresponding publication:
<a href="https://doi.org/10.1021/acscatal.5c04191" target="_blank"><em>ACS Catal.</em> 2025, <strong> 15</strong>, 14403-14413</a>.
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If you are curious about me or my work, you can check out my <a href="https://diegonti.github.io/" target="_blank">webpage</a> or you can contact <a href="mailto:diegonti.doc@gmail.com" target="_blank">me</a> for more information.
<br><br> - Diego Ontiveros
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<img src="img/screening.jpg" alt="MXene Screening" width="800" />
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