Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Authors: Zimmermann, Yoel, Bazgir, Adib, Afzal, Zartashia, Agbere, Fariha, Ai, Qianxiang, Alampara, Nawaf, Al-Feghali, Alexander, Ansari, Mehrad, Antypov, Dmytro, Aswad, Amro, Bai, Jiaru, Baibakova, Viktoriia, Biswajeet, Devi Dutta, Bitzek, Erik, Bocarsly, Joshua D., Borisova, Anna, Bran, Andres M, Brinson, L. Catherine, Calderon, Marcel Moran, Canalicchio, Alessandro, Chen, Victor, Chiang, Yuan, Circi, Defne, Charmes, Benjamin, Chaudhary, Vikrant, Chen, Zizhang, Chiu, Min-Hsueh, Clymo, Judith, Dabhadkar, Kedar, Daelman, Nathan, Datar, Archit, de Jong, Wibe A., Evans, Matthew L., Fard, Maryam Ghazizade, Fisicaro, Giuseppe, Gangan, Abhijeet Sadashiv, George, Janine, Gonzalez, Jose D. Cojal, Götte, Michael, Gupta, Ankur K., Harb, Hassan, Hong, Pengyu, Ibrahim, Abdelrahman, Ilyas, Ahmed, Imran, Alishba, Ishimwe, Kevin, Issa, Ramsey, Jablonka, Kevin Maik, Jones, Colin, Josephson, Tyler R., Juhasz, Greg, Kapoor, Sarthak, Kang, Rongda, Khalighinejad, Ghazal, Khan, Sartaaj, Klawohn, Sascha, Kuman, Suneel, Ladines, Alvin Noe, Leang, Sarom, Lederbauer, Magdalena, Sheng-Lun, Liao, Liu, Hao, Liu, Xuefeng, Lo, Stanley, Madireddy, Sandeep, Maharana, Piyush Ranjan, Maheshwari, Shagun, Mahjoubi, Soroush, Márquez, José A., Mills, Rob, Mohanty, Trupti, Mohr, Bernadette, Moosavi, Seyed Mohamad, Moßhammer, Alexander, Naghdi, Amirhossein D., Naik, Aakash, Narykov, Oleksandr, Näsström, Hampus, Nguyen, Xuan Vu, Ni, Xinyi, O'Connor, Dana, Olayiwola, Teslim, Ottomano, Federico, Ozhan, Aleyna Beste, Pagel, Sebastian, Parida, Chiku, Park, Jaehee, Patel, Vraj, Patyukova, Elena, Petersen, Martin Hoffmann, Pinto, Luis, Pizarro, José M., Plessers, Dieter, Pradhan, Tapashree, Pratiush, Utkarsh, Puli, Charishma, Qin, Andrew, Rajabi, Mahyar, Ricci, Francesco, Risch, Elliot, Ríos-García, Martiño, Roy, Aritra, Rug, Tehseen, Sayeed, Hasan M, Scheidgen, Markus, Schilling-Wilhelmi, Mara, Schloz, Marcel, Schöppach, Fabian, Schumann, Julia, Schwaller, Philippe, Schwarting, Marcus, Sharlin, Samiha, Shen, Kevin, Shi, Jiale, Si, Pradip, D'Souza, Jennifer, Sparks, Taylor, Sudhakar, Suraj, Talirz, Leopold, Tang, Dandan, Taran, Olga, Terboven, Carla, Tropin, Mark, Tsymbal, Anastasiia, Ueltzen, Katharina, Unzueta, Pablo Andres, Vasan, Archit, Vinchurkar, Tirtha, Vo, Trung, Vogel, Gabriel, Völker, Christoph, Weinreich, Jan, Yang, Faradawn, Zaki, Mohd, Zhang, Chi, Zhang, Sylvester, Zhang, Weijie, Zhu, Ruijie, Zhu, Shang, Janssen, Jan, Li, Calvin, Foster, Ian, Blaiszik, Ben

Subject Terms: Computer Science - Machine Learning, Condensed Matter - Materials Science, Physics - Chemical Physics

Access URL: http://arxiv.org/abs/2411.15221

Thermoelectric properties of TaVO5 and GdTaO4: An experimental verification of machine learning prediction.

Authors: Allen, Travis¹, Graser, Jake², Issa, Ramsey², Sparks, Taylor D^2,3, sparks@eng.utah.edu

Source: Advances in Applied Ceramics: Structural, Functional & Bioceramics; May2024, Vol. 123 Issue 1-3, p15-21, 7p

Thermoelectric properties of TaVO5 and GdTaO4: An experimental verification of machine learning prediction.

Authors: Allen, Travis, Graser, Jake, Issa, Ramsey, Sparks, Taylor D

Source: Advances in Applied Ceramics: Structural, Functional & Bioceramics; May2024, Vol. 123 Issue 1-3, p15-21, 7p

Thermoelectric properties of TaVO5and GdTaO4: An experimental verification of machine learning prediction

Authors: Allen, Travis, Graser, Jake, Issa, Ramsey, Sparks, Taylor D

Source: Advances in Applied Ceramics; May 2024, Vol. 123 Issue: 1-3 p15-21, 7p

Structural coupling and magnetic tuning in Mn2−xCoxP magnetocalorics for thermomagnetic power generation

Authors: Levin, Emily E., Bocarsly, Joshua D., Grebenkemper, Jason H., Issa, Ramsey, Wilson, Stephen D., Pollock, Tresa M., Seshadri, Ram

Source: APL materials. 8(4)

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCvdc_100132337202.0x000001&indx=1&recIds=ETOCvdc_100132337202.0x000001

Materials science optimization benchmark dataset for multi-objective, multi-fidelity optimization of hard-sphere packing simulations

Authors: Baird, Sterling G., Issa, Ramsey, Sparks, Taylor D.

Source: In Data in Brief October 2023 50