Irmak Sargın

E-mail

isargin@metu.edu.tr

Department

Department of Metallurgical and Materials Engineering

Putting error bars on density functional theory Yuk, Simuck F.; Sargın, Irmak; Meyer, Noah; Krogel, Jaron T.; Beckman, Scott P.; Cooper, Valentino R. (2024-12-01) Predicting the error in density functional theory (DFT) calculations due to the choice of exchange–correlation (XC) functional is crucial to the success of DFT, but currently, there are limited options to estimate this a p...
Flow mechanisms and their influence on the properties of EGaIn-graphene-poly(ethylene) oxide composites during material extrusion-based additive manufacturing Tandel, Ruchira; Sargın, Irmak; Gozen, B. Arda (2024-03-25) Polymer composites featuring room temperature liquid alloy particles complimenting other conductive fillers enable unique thermal and electrical properties. Direct-ink-writing approach is an intriguing processing path for ...
Multivariate analysis: An essential for studying complex glasses Sargın, Irmak; McCloy, John S.; Beckman, Scott P. (2022-12-01) Understanding the impact of individual compositional components on the devitrification of complex multicomponent glasses, for example, 10-50+ oxides, typically requires numerous studies to examine each component's impact. ...
Predicting nepheline precipitation in waste glasses using ternary submixture model and machine learning Lu, Xiaonan; Sargın, Irmak; Vienna, John D. (2021-11-01) Nepheline precipitation in nuclear waste glasses during vitrification can be detrimental due to the negative effect on chemical durability often associated with its formation. Developing models to accurately predict nephel...
Machine learning to predict refractory corrosion during nuclear waste vitrification Smith-Gray, Natalie J.; Sargın, Irmak; Beckman, Scott; McCloy, John (2021-04-01) The goal of this study was to determine the effects of model nuclear waste glass composition on the corrosion of Monofrax(R) K-3 refractory, using machine learning (ML) methods for data investigation and modeling of publis...
A data-driven approach for predicting nepheline crystallization in high-level waste glasses Sargın, Irmak; Lonergan, Charmayne E.; Vienna, John D.; McCloy, John S.; Beckman, Scott P. (2020-09-01) High-level waste (HLW) glasses with high alumina content are prone to nepheline crystallization during the slow canister cooling that is experienced during large-scale production. Because of its detrimental effects on glas...
Modeling the effect of dose rate and time on crosslinking and scission in irradiated polyethylene Sargın, Irmak; Beckman, S. P. (2020-06-01) The insulation around the electrical cabling in nuclear power plants is frequently made of ethylene-propylene rubber and crosslinked polyethylene that is subjected to low levels of environmental stressors and radiation ove...
Corrigendum to: Modeling of reaction-diffusion transport into a core-shell geometry King, C.C.; Brown, A.A.; Sargın, Irmak; Bratlie, K.M.; Beckman, S.P. (2020-01-01)
A data-informatics method to quantitatively represent ternary eutectic microstructures Sargın, Irmak; Beckman, Scott P. (2019-02-01) Many of the useful properties of modern engineering materials are determined by the material's microstructure. Controlling the microstructure requires an understanding of the complex dynamics underlying its evolution durin...
Modeling of reaction-diffusion transport into a core-shell geometry King, Clarence C.; Brown, Amelia Ann; Sargın, Irmak; Bratlie, K. M.; Beckman, S. P. (2019-01-01) Fickian diffusion into a core-shell geometry is modeled. The interior core mimics pancreatic Langerhan islets and the exterior shell acts as inert protection. The consumption of oxygen diffusing into the cells is approxima...

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