Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Khatamsaz, Danial"'
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
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:
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
Uncertainty analysis in the outcomes of model predictions is a key element in decision-based material design to establish confidence in the models and evaluate the fidelity of models. Uncertainty Propagation (UP) is a technique to determine model out
Externí odkaz:
http://arxiv.org/abs/2302.04945
Autor:
Hossein Zadeh, Sina, Cakirhan, Cem, Khatamsaz, Danial, Broucek, John, Brown, Timothy D., Qian, Xiaoning, Karaman, Ibrahim, Arroyave, Raymundo
Publikováno v:
In Materials & Design August 2024 244
Akademický článek
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Publikováno v:
In Acta Materialia 15 October 2023 259
Publikováno v:
In Acta Materialia September 2023