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Uranium monocarbide (UC) is an advanced ceramic fuel candidate due to its superior uranium density and thermal conductivity compared to traditional fuels. To accurately model UC at reactor operating conditions, we developed a machine…

A deep neural network was developed for the purpose of predicting thermal conductivity with a case study performed on neutron irradiated nuclear fuel. Traditional thermal conductivity modeling approaches rely on existing theoretical…

材料科学 · 物理学 2019-01-04 Elizabeth Kautz , Alexander Hagen , Jesse Johns , Douglas Burkes

Uranium mononitride (UN) is a promising accident-tolerant fuel because of its high fissile density and high thermal conductivity. In this study, we developed the first machine learning interatomic potentials for reliable atomic-scale…

In this work we developed a practical and general modeling approach for thermal conductivity of metals and metal alloys that integrates ab initio and semiempirical physics-based models to maximize the strengths of both techniques. The…

材料科学 · 物理学 2022-04-25 Shuxiang Zhou , Ryan Jacobs , Wei Xie , Eric Tea , Celine Hin , Dane Morgan

Uranium borides are promising candidate fuel forms for use in advanced nuclear reactors due to their high thermal conductivity and potential for dual use as both fuel and burnable absorber materials. In this work, uranium tetraboride…

We present a combined computational and experimental investigation of the thermal properties of uranium nitride (UN), focusing on the development of a machine learning interatomic potential (MLIP) using the moment tensor potential (MTP)…

Uranium dioxide (UO2) is a prototypical nuclear fuel material, yet predicting its thermophysical properties across a wide temperature range remains challenging. One factor contributing to this difficulty is the complex magnetic ordering at…

材料科学 · 物理学 2026-03-10 Keita Kobayashi , Hiroki Nakamura , Mitsuhiro Itakura

Quantitative descriptions of the structure-thermal property correlation have been a bottleneck in designing materials with superb thermal properties. In the past decade, the first-principles phonon calculations using density functional…

材料科学 · 物理学 2021-10-19 Xin Qian , Ronggui Yang

UZr based metallic nuclear fuel is the leading candidate for next-generation sodium-cooled fast reactors in the United States. US research reactors have been using and testing this fuel type since the 1960s and accumulated considerable…

Molecular dynamics simulations have been extensively used to predict thermal properties, but simulating different phases with similar precision using a unified force field is often difficult, due to the lack of accurate and transferrable…

材料科学 · 物理学 2019-12-12 Ruiyang Li , Eungkyu Lee , Tengfei Luo

Uranium mononitride, UN, is considered a potential accident tolerant fuel due to its high uranium density, high thermal conductivity, and high melting point. Compared with the relatively inert UO2, UN has a high reactivity in water,…

材料科学 · 物理学 2018-10-30 E. Lawrence Bright , S. Rennie , A. Siberry , K. Samani , K. Clarke , D. T. Goddard , R. Springell

Uranium dioxide (UO$_2$), one of the most important nuclear fuels, can accumulate excess oxygen atoms as interstitial defects, which significantly impacts thermal properties. In this study, thermal conductivities and inelastic neutron…

Machine-learning methods are nowadays of common use in the field of material science. For example, they can aid in optimizing the physicochemical properties of new materials, or help in the characterization of highly complex chemical…

无序系统与神经网络 · 物理学 2022-11-29 Maciej J. Karcz , Luca Messina , Eiji Kawasaki , Serenah Rajaonson , Didier Bathellier , Emeric Bourasseau

Interatomic potentials of uranium dioxide are investigated on their applicability to model structural stabilities beyond fluorite phase by comparing with ab-initio results. A high pressure cotunnite phase and loosely stacking virtual…

材料科学 · 物理学 2010-08-31 H. Y. Geng , Y. Chen , Y. Kaneta , M. Kinoshita

We use machine learning models to predict ion density and electron temperature from visible emission spectra, in a high energy density pulsed-power-driven aluminum plasma, generated by an exploding wire array. Radiation transport…

等离子体物理 · 物理学 2023-09-01 Rishabh Datta , Faez Ahmed , Jack D Hare

We present a proof of concept that machine learning techniques can be used to predict the properties of CNOHF energetic molecules from their molecular structures. We focus on a small but diverse dataset consisting of 109 molecular…

材料科学 · 物理学 2018-06-14 Daniel C. Elton , Zois Boukouvalas , Mark S. Butrico , Mark D. Fuge , Peter W. Chung

The accurate calculation and uncertainty quantification of the characteristics of spent nuclear fuel (SNF) play a crucial role in ensuring the safety, efficiency, and sustainability of nuclear energy production, waste management, and…

机器学习 · 计算机科学 2023-08-17 Arnau Albà , Andreas Adelmann , Lucas Münster , Dimitri Rochman , Romana Boiger

Our series of articles is devoted to high-precision molecular dynamics simulation of mixed actinide-oxide (MOX) fuel in the approximation of rigid ions and pair interactions (RIPI) using high-performance graphics processors (GPU). In this…

材料科学 · 物理学 2011-12-06 S. I. Potashnikov , A. S. Boyarchenkov , K. A. Nekrasov , A. Ya. Kupryazhkin

The knowledge of thermal radiative and thermodynamic properties of uranium and plutonium carbides under extreme conditions is essential for designing a new metallic fuel materials for next generation of a nuclear reactor. The present work…

化学物理 · 物理学 2016-08-24 Anatoliy I Fisenko , Vladimir F Lemberg

Uranium dioxide which is used as a fuel in light water nuclear reactors, is continually exposed to radiation damage originated from the collision of high-energy particles. Accumulation of the resulting defects gives rise to the evolution in…

材料科学 · 物理学 2025-04-14 Mahmoud Payami , Samira Sheykhi , Mohammad-Reza Basaadat
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