Added preprints

shankar1729 · May 31, 2024 · 8bc48b2 · 8bc48b2
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 <h4> 2024 </h4>
 
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+<li> C. Tezak, J. Clary, S. Gerits, J. Quinton, B. Rich, N. Singstock, A. Alherz, T. Aubry, S. Clark, R. Hurst, M. Del Ben, C. Sutton, R. Sundararaman, C. Musgrave and D. Vigil-Fowler,
+	&ldquo;BEAST DB: Grand-Canonical Database of Electrocatalyst Properties&rdquo;,
+	<a href="https://arxiv.org/abs/2405.20239"><i>arXiv:</i><b>2405</b>.20239 (2024)</a>
+</li><br>
+
+<li> D. Weinberg, O. A. Hull, J. M. Clary, R. Sundararaman, D. Vigil-Fowler and M. Del Ben,
+	&ldquo;Static Subspace Approximation for Random Phase Approximation Correlation Energies: Implementation and Performance&rdquo;,
+	<a href="https://arxiv.org/abs/2405.20258"><i>arXiv:</i><b>2405</b>.20258 (2024)</a>
+</li><br>
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+<li> J. M. Clary, O. A. Hull, D. Weinberg, R. Sundararaman, M. Del Ben and D. Vigil-Fowler,
+	&ldquo;Static Subspace Approximation for Random Phase Approximation Correlation Energies: Applications to Materials for Catalysis and Electrochemistry&rdquo;,
+	<a href="https://doi.org/10.26434/chemrxiv-2024-25pch"><i>chemrxiv</i>-<b>2024</b>-25pch (2024)</a>
+</li><br>
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+<li> M. M. Kelley, J. Quinton, K. Fazel, N. Karimitari, C. Sutton and R. Sundararaman,
+	&ldquo;Bridging electronic and classical density-functional theory using universal machine-learned functional approximations&rdquo;,
+	<a href="https://arxiv.org/abs/2405.20270"><i>arXiv:</i><b>2405</b>.20270 (2024)</a>
+</li><br>
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 <li> K. Fazel, N. Karimitari, T. Shah, C. Sutton and R. Sundararaman,
 	&ldquo;Improving the reliability of machine learned potentials for modeling inhomogeneous liquids&rdquo;,
 	<a href="https://doi.org/10.1002/jcc.27353"><i>J. Comput. Chem.</i> <b></b>, in press (2024)</a>