Zobrazeno 1 - 10
of 95
pro vyhledávání: '"Kolmogorov, Aleksey N."'
Autor:
Mishra, Shashi B., Marcial, Edan T., Debata, Suryakanti, Kolmogorov, Aleksey N., Margine, Elena R.
A recent ab initio investigation of Na-C binary compounds under moderate pressures has uncovered a possible stable NaC$_4$ superconductor with an estimated critical temperature up to 41K. We revisit this promising binary system by performing a more f
Externí odkaz:
http://arxiv.org/abs/2407.16056
Autor:
Tomassetti, Charlsey R., Gochitashvili, Daviti, Renskers, Christopher, Margine, Elena R., Kolmogorov, Aleksey N.
We employ ab initio modeling to investigate the possibility of attaining high-temperature conventional superconductivity in ambient-pressure materials based on the known MgB$_2$C$_2$ and recently proposed thermodynamically stable NaBC ternary compoun
Externí odkaz:
http://arxiv.org/abs/2407.09347
Autor:
Tomassetti, Charlsey R., Kafle, Gyanu P., Marcial, Edan T., Margine, Elena R., Kolmogorov, Aleksey N.
Delithiation of the known layered LiBC compound was predicted to induce conventional superconductivity at liquid nitrogen temperatures but extensive experimental work over the past two decades has detected no signs of the expected superconducting tra
Externí odkaz:
http://arxiv.org/abs/2403.00738
Publikováno v:
Phys. Chem. Chem. Phys., 2023, 25, 22415-22436
We present our findings of a large-scale screening for new synthesizable materials in five M-Sn binaries, M = Na, Ca, Cu, Pd, and Ag. The focus on these systems was motivated by the known richness of M-Sn properties with potential applications in ene
Externí odkaz:
http://arxiv.org/abs/2306.10223
Autor:
Kharabadze, Saba, Meyers, Maxwell, Tomassetti, Charlsey R., Margine, Elena R., Mazin, Igor I., Kolmogorov, Aleksey N.
Prediction of high-$T_{\rm{c}}$ superconductivity in hole-doped Li$_x$BC two decades ago has brought about an extensive effort to synthesize new materials with honeycomb B-C layers, but the thermodynamic stability of Li-B-C compounds remains largely
Externí odkaz:
http://arxiv.org/abs/2302.05325
Autor:
Kafle, Gyanu P., Tomassetti, Charlsey R., Mazin, Igor I., Kolmogorov, Aleksey N., Margine, Elena R.
Publikováno v:
Physical Review Materials 6, 084801 (2022)
LiB, a predicted layered compound analogous to the MgB$_2$ superconductor, has been recently synthesized via cold compression and quenched to ambient pressure, yet its superconducting properties have not been measured. According to prior isotropic su
Externí odkaz:
http://arxiv.org/abs/2208.12855
Publikováno v:
npj Computational Materials volume 8, Article number: 136 (2022)
The Li-Sn binary system has been the focus of extensive research because it features Li-rich alloys with potential applications as battery anodes. Our present re-examination of the binary system with a combination of machine learning and ab initio me
Externí odkaz:
http://arxiv.org/abs/2203.06283
Autor:
Kavai, Mariam, Friedman, Joel, Sherman, Kyle, Gong, Mingda, Giannakis, Ioannis, Hajinazar, Samad, Hu, Haoyu, Grefe, Sarah E., Leshen, Justin, Yang, Qiu, Nakatsuji, Satoru, Kolmogorov, Aleksey N., Si, Qimiao, Lawler, Michael, Aynajian, Pegor
Magnetic fluctuations induced by geometric frustration of local Ir-spins disturb the formation of long range magnetic order in the family of pyrochlore iridates, R$_{2}$Ir$_{2}$O$_{7}$ (R = lanthanide)$^{1}$. As a consequence, Pr$_{2}$Ir$_{2}$O$_{7}$
Externí odkaz:
http://arxiv.org/abs/2006.07424
Autor:
Hajinazar, Samad, Thorn, Aidan, Sandoval, Ernesto D., Kharabadze, Saba, Kolmogorov, Aleksey N.
Module for ab initio structure evolution (MAISE) is an open-source package for materials modeling and prediction. The code's main feature is an automated generation of neural network (NN) interatomic potentials for use in global structure searches. T
Externí odkaz:
http://arxiv.org/abs/2005.12131
Autor:
Toher, Cormac, Oses, Corey, Hicks, David, Gossett, Eric, Rose, Frisco, Nath, Pinku, Usanmaz, Demet, Ford, Denise C., Perim, Eric, Calderon, Camilo E., Plata, Jose J., Lederer, Yoav, Jahnátek, Michal, Setyawan, Wahyu, Wang, Shidong, Xue, Junkai, Rasch, Kevin, Chepulskii, Roman V., Taylor, Richard H., Gomez, Geena, Shi, Harvey, Supka, Andrew R., Orabi, Rabih Al Rahal Al, Gopal, Priya, Cerasoli, Frank T., Liyanage, Laalitha, Wang, Haihang, Siloi, Ilaria, Agapito, Luis A., Nyshadham, Chandramouli, Hart, Gus L. W, Carrete, Jesús, Legrain, Fleur, Mingo, Natalio, Zurek, Eva, Isayev, Olexandr, Tropsha, Alexander, Sanvito, Stefano, Hanson, Robert M., Takeuchi, Ichiro, Mehl, Michael J., Kolmogorov, Aleksey N., Yang, Kesong, D'Amico, Pino, Calzolari, Arrigo, Costa, Marcio, De Gennaro, Riccardo, Nardelli, Marco Buongiorno, Fornari, Marco, Levy, Ohad, Curtarolo, Stefano
The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational mater
Externí odkaz:
http://arxiv.org/abs/1712.00422