Zobrazeno 1 - 10
of 452
pro vyhledávání: '"Arroyave, Raymundo"'
Autor:
Alvi, Sk Md Ahnaf Akif, Janssen, Jan, Khatamsaz, Danial, Perez, Danny, Allaire, Douglas, Arroyave, Raymundo
Bayesian optimization (BO) is a powerful and data-efficient method for iterative materials discovery and design, particularly valuable when prior knowledge is limited, underlying functional relationships are complex or unknown, and the cost of queryi
Externí odkaz:
http://arxiv.org/abs/2410.04314
Autor:
Mulukutla, Mrinalini, Robinson, Robert, Khatamsaz, Danial, Vela, Brent, Vu, Nhu, Arróyave, Raymundo
Materials design is a critical driver of innovation, yet overlooking the technological, economic, and environmental risks inherent in materials and their supply chains can lead to unsustainable and risk-prone solutions. To address this, we present a
Externí odkaz:
http://arxiv.org/abs/2409.15391
Multi-Principal Element Alloys (MPEAs) have emerged as an exciting area of research in materials science in the 2020s, owing to the vast potential for discovering alloys with unique and tailored properties enabled by the combinations of elements. How
Externí odkaz:
http://arxiv.org/abs/2408.07681
Autor:
Mulukutla, Mrinalini, Person, A. Nicole, Voigt, Sven, Kuettner, Lindsey, Kappes, Branden, Khatamsaz, Danial, Robinson, Robert, Salas, Daniel, Xu, Wenle, Lewis, Daniel, Eoh, Hongkyu, Xiao, Kailu, Wang, Haoren, Saini, Jaskaran Singh, Mahat, Raj, Hastings, Trevor, Skokan, Matthew, Attari, Vahid, Elverud, Michael, Paramore, James D., Butler, Brady, Vecchio, Kenneth, Kalidindi, Surya R., Allaire, Douglas, Karaman, Ibrahim, Thomas, Edwin L., Pharr, George, Srivastava, Ankit, Arróyave, Raymundo
Algorithmic materials discovery is a multi-disciplinary domain that integrates insights from specialists in alloy design, synthesis, characterization, experimental methodologies, computational modeling, and optimization. Central to this effort is a r
Externí odkaz:
http://arxiv.org/abs/2405.13132
Autor:
Hastings, Trevor, Mulukutla, Mrinalini, Khatamsaz, Danial, Salas, Daniel, Xu, Wenle, Lewis, Daniel, Person, Nicole, Skokan, Matthew, Miller, Braden, Paramore, James, Butler, Brady, Allaire, Douglas, Karaman, Ibrahim, Pharr, George, Srivastava, Ankit, Arroyave, Raymundo
In this study, we introduce a groundbreaking framework for materials discovery, we efficiently navigate a vast phase space of material compositions by leveraging Batch Bayesian statistics in order to achieve specific performance objectives. This appr
Externí odkaz:
http://arxiv.org/abs/2405.08900
Autor:
Paramore, James D., Butler, Brady G., Hurst, Michael T., Hastings, Trevor, Lewis, Daniel O., Norris, Eli, Barkai, Benjamin, Cline, Joshua, Miller, Braden, Cortes, Jose, Karaman, Ibrahim, Pharr, George M., Arroyave, Raymundo
In this paper, a synergistic computational/experimental approach is presented for the rapid discovery and characterization of novel alloys within the compositionally complex (i.e., "medium/high entropy") refractory alloy space of Ti-V-Nb-Mo-Hf-Ta-W.
Externí odkaz:
http://arxiv.org/abs/2405.07130
This paper proposes a semi-supervised methodology for training physics-informed machine learning methods. This includes self-training of physics-informed neural networks and physics-informed Gaussian processes in isolation, and the integration of the
Externí odkaz:
http://arxiv.org/abs/2404.05817
The Cluster Expansion (CE) Method encounters significant computational challenges in multicomponent systems due to the computational expense of generating training data through density functional theory (DFT) calculations. This work aims to refine th
Externí odkaz:
http://arxiv.org/abs/2403.18298
Autor:
Zadeh, Sina Hossein, Cakirhan, Cem, Khatamsaz, Danial, Broucek, John, Brown, Timothy D., Qian, Xiaoning, Karaman, Ibrahim, Arroyave, Raymundo
The martensitic transformation in NiTi-based Shape Memory Alloys (SMAs) provides a basis for shape memory effect and superelasticity, thereby enabling applications requiring solid-state actuation and large recoverable shape changes upon mechanical lo
Externí odkaz:
http://arxiv.org/abs/2402.12520
Autor:
Munoz, Elias J., Attari, Vahid, Martinez, Marco, Dickerson, Matthew B., Radovic, Miladin, Arroyave, Raymundo
Silicon carbide (SiC) emerges as a promising ceramic material for high-temperature structural applications, especially within the aerospace sector. The utilization of SiC-based ceramic matrix composites (CMCs) instead of superalloys in components lik
Externí odkaz:
http://arxiv.org/abs/2311.05692