From 280016cda2bacc98e300b6940ba891d6db0f7744 Mon Sep 17 00:00:00 2001
From: Marie Weiel <marie.weiel@kit.edu>
Date: Wed, 2 Oct 2024 09:12:01 +0200
Subject: [PATCH] fix typo

---
 html/templates/papers.html | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/html/templates/papers.html b/html/templates/papers.html
index 6cccf9c..826c5db 100644
--- a/html/templates/papers.html
+++ b/html/templates/papers.html
@@ -14,7 +14,7 @@ <h4 class="my-4 py-2 text-primary">Papers based on PAINT</h4>
 
 <ul>
     <li>M. Pargmann, J. Ebert, M. Götz, D.M. Quinto, R. Pitz-Paal, S. Kesselheim "Automatic Heliostat Learning for In-situ Concentrating Solar Power Plant Metrology with Differentiable Ray Tracing" <i>Nature Communications</i> 15(1) (2024): 6997, doi: <a href="https://doi.org/10.1038/s41467-024-51019-z">10.1038/s41467-024-51019-z</a>.</li>
-    <li>M. Kuhl, M. Pargmann, M. Cherti, J. Jitsev, D. M. Quinto, R. Pitz-Paal "Flux density distribution forecasting in concentrated solar tower plants: A data-driven approach" <i>Solar Energy</i> 282 (2024): 112894, doi: <a href="https://doi.org/10.1016/j.solener.2024.112894">10.1016/j.solener.2024.112894</a>.</li>
+    <li>M. Kuhl, M. Pargmann, M. Cherti, J. Jitsev, D.M. Quinto, R. Pitz-Paal "Flux density distribution forecasting in concentrated solar tower plants: A data-driven approach" <i>Solar Energy</i> 282 (2024): 112894, doi: <a href="https://doi.org/10.1016/j.solener.2024.112894">10.1016/j.solener.2024.112894</a>.</li>
     <li>M. Pargmann, D.M. Quinto, P. Schwarzbözl, R. Pitz-Paal "High accuracy data-driven heliostat calibration and state prediction with pretrained deep neural networks." <i>Solar Energy</i> 218 (2021): 48-56, doi: <a href="https://doi.org/10.1016/j.solener.2021.01.046">10.1016/j.solener.2021.01.046</a>.</li>
 </ul>