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Akademický článek

Customized Statistically Downscaled CMIP5 and CMIP6 Projections: Application in the Edwards Aquifer Region in South‐Central Texas

Autor: A. M. Wootten, H. Başağaoğlu, F. P. Bertetti, D. Chakraborty, C. Sharma, M. Samimi, A. Mirchi

Publikováno v: Earth's Future, Vol 12, Iss 10, Pp n/a-n/a (2024)

Abstract Climate projections are being used for decision‐making related to climate mitigation and adaptation and as inputs for impacts modeling related to climate change. The plethora of available projections presents end users with the challenge o

Externí odkaz: https://doaj.org/article/d50b3626cc85473b9a8f67576664368d

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Akademický článek

The future of water in a desert river basin facing climate change and competing demands: A holistic approach to water sustainability in arid and semi-arid regions

Autor: W.L. Hargrove, J.M. Heyman, A. Mayer, A. Mirchi, A. Granados-Olivas, G. Ganjegunte, D. Gutzler, D.D. Pennington, F.A. Ward, L. Garnica Chavira, Z. Sheng, S. Kumar, N. Villanueva-Rosales, W.S. Walker

Publikováno v: Journal of Hydrology: Regional Studies, Vol 46, Iss , Pp 101336- (2023)

Study region: The Middle Rio Grande (MRG), defined by the portion of the basin from Elephant Butte Reservoir in New Mexico to the confluence with the Rio Conchos in Far West Texas, U.S.A. and Northern Chihuahua, Mexico. Study focus: The future of wat

Externí odkaz: https://doaj.org/article/5bfa0a1f8d994044a712e1161ffea8a9

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Accurate estimation of interfacial thermal conductance between silicon and diamond enabled by a machine learning interatomic potential

Autor: Rajabpour, Ali, Mortazavi, Bohayra, Mirchi, Pedram, Hajj, Julien El, Guo, Yangyu, Zhuang, Xiaoying, Merabia, Samy

Thermal management at silicon-diamond interface is critical for advancing high-performance electronic and optoelectronic devices. In this study, we calculate the interfacial thermal conductance between silicon and diamond using machine learning (ML)

Externí odkaz: http://arxiv.org/abs/2407.15404

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Lattice thermal conductivity and mechanical properties of the single-layer penta-NiN2 explored by a deep-learning interatomic potential

Autor: Mirchi, Pedram, Adessi, Christophe, Merabia, Samy, Rajabpour, Ali

Penta-NiN2, a novel pentagonal 2D sheet with potential nanoelectronic applications, is investigated in terms of its lattice thermal conductivity, stability, and mechanical behavior. A deep learning interatomic potential (DLP) is firstly generated fro

Externí odkaz: http://arxiv.org/abs/2403.03515

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Lattice thermal conductivity and elastic modulus of XN4 (X=Be, Mg and Pt) 2D materials using machine learning interatomic potentials

Autor: Ghorbani, K., Mirchi, P., Arabha, S., Rajabpour, Ali, Volz, Sebastian

The newly synthesized BeN4 monolayer has introduced a novel group of 2D materials called nitrogen-rich 2D materials. In the present study, the anisotropic mechanical and thermal properties of three members of this group, BeN4, MgN4, and PtN4, are inv

Externí odkaz: http://arxiv.org/abs/2212.00263

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