<div dir="ltr"><div dir="ltr">Hi All,<div><br></div><div>I have performed a TS search using CI-NEB method and this is the procedure, I have adopted. </div><div><br></div><div>1. The Reactant (Image initial) and Product (Image final) are relaxed with geometry optimization.</div><div>2. Images (image1.png in the attachment) between the initial and final images are chosen and CI-NEB is performed with these parameters :</div><div><br></div><div><ul><li><span style="line-height:normal">ROTATE_FRAMES F</span></li><li><span style="line-height:normal">ALIGN_FRAMES F</span></li><li><span style="line-height:normal">OPTIMIZE_END_POINTS F</span></li></ul><img src="data:image/png;base64,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" width="320" height="196"><br></div><div>This is the energy profile that is obtained and as it is clearly seen that the reactants and products are no longer at the minima. I have tried this with 10,12 and 16 images.</div><div>But in all the cases the images that are next to the reactant (first) and product (last) reach minimum. </div><div><img><br></div><div>This (image2.png in the attachement) is the energy profile that is obtained with using the same images as above but with OPTIMIZE_END_POINTS as TRUE. The reactants and products are relaxed using geometry optimization for this case as well.</div><div>This plot makes sense as the reactants and products are at minima with respect to other images. </div><div><ul><li><span style="line-height:normal">ROTATE_FRAMES F</span></li><li><span style="line-height:normal">ALIGN_FRAMES F</span></li><li><span style="line-height:normal">OPTIMIZE_END_POINTS T</span></li></ul><img src="data:image/png;base64,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" width="320" height="197"><img><br></div><div>Can someone please explain what could have been going on with and without using the OPTIMIZE_END_POINTS and which one show be considered ?</div><div><br></div><div>Thanks,</div><div>Abhishek</div><div><br></div><div><div style="font-family:arial,sans-serif"><div><div><div><div><div><font size="1"><span style="font-family:georgia,serif"><span style="color:rgb(0,0,255)"><br>------------------------------<wbr>------------------------------<wbr>------------------------------<wbr>-----------------<br>Abhishek Bagusetty<br></span></span></font></div><font size="1"><span style="font-family:georgia,serif"><span style="color:rgb(0,0,255)">PhD Student, Computational Modeling & Simulation<br></span></span></font></div><font size="1"><span style="font-family:georgia,serif"><span style="color:rgb(0,0,255)">Center for Simulation and Modeling<br></span></span></font></div><span style="color:rgb(80,0,80)"><font size="1"><span style="font-family:georgia,serif"><span style="color:rgb(0,0,255)">Department of Chemical & Petroleum Engineering<br></span></span></font></span></div><font size="1"><span style="font-family:georgia,serif"><span style="color:rgb(0,0,255)">University of Pittsburgh</span><br><span style="color:rgb(0,0,255)">Pittsburgh, PA - 15261</span></span></font></div><font size="1"><span style="font-family:georgia,serif"><span style="color:rgb(0,0,255)">Office : 920 Benedum Hall<br></span></span></font></div><div style="font-family:arial,sans-serif"><font size="1"><span style="font-family:georgia,serif"><span style="color:rgb(0,0,255)">------------------------------<wbr>------------------------------<wbr>------------------------------<wbr>-----------------</span></span></font></div></div></div></div>