Search NASA⌕ Search
Home/Archive/DOE OSTI

DOE OSTI · 3030880

A Bayesian desmearing algorithm for Bonse–Hart USANS with anisotropic scattering

Tung, Chi-Huan [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Neutron Scattering Division] (ORCID:0000000221972074)·Huang, Guan-Rong [National Tsing Hua Univ., Hsinchu (Taiwan)] (ORCID:0000000163939574)·Wang, Yangyang [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)] (ORCID:0000000170429804)·Carrillo, Jan-Michael [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)] (ORCID:000000018774697X)·Shinohara, Yuya [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Materials Science & Technology Division] (ORCID:000000018284751X)·Do, Changwoo [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Neutron Scattering Division] (ORCID:0000000183588417)·Rother, Gernot [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Neutron Scattering Division]·Shang, Yingrui [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Neutron Scattering Division] (ORCID:0000000301743992)·Chen, Wei-Ren [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Neutron Scattering Division] (ORCID:0000000251920777)
View original source ↗Read source document ↗Export metadata ↓

Abstract

Ultra-small-angle neutron scattering (USANS) using Bonse–Hart optics provides micrometer-scale structural insights but suffers from severe slit-geometry smearing. While well-established for isotropic systems, quantitative desmearing of anisotropic data remains a challenge because conventional corrections break down for non-radial scattering. In this work, we address this by developing a resolution-aware Bayesian framework that explicitly incorporates anisotropy via an affine deformation to the scattering pattern, guided by the principle of parsimony. This results in orientation-resolved point-spread functions that enable a self-consistent determination of both the resolution and deformation parameters. Using Gaussian process regression with uncertainty quantification and a probabilistic correction for multiple scattering, we demonstrate the framework’s effectiveness through numerical benchmarks and experimental studies of a stretched polymer melt. Our approach enables the seamless integration of SANS and USANS data, facilitating quantitative structural analysis of deformed materials at nanometer to micrometer scales.

Explore related subjects

36 MATERIALS SCIENCE

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tung, Chi-Huan [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Neutron Scattering Division] (ORCID:0000000221972074), Huang, Guan-Rong [National Tsing Hua Univ., Hsinchu (Taiwan)] (ORCID:0000000163939574), Wang, Yangyang [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)] (ORCID:0000000170429804), Carrillo, Jan-Michael [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Sciences (CNMS)] (ORCID:000000018774697X), Shinohara, Yuya [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Materials Science & Technology Division] (ORCID:000000018284751X), Do, Changwoo [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Neutron Scattering Division] (ORCID:0000000183588417), Rother, Gernot [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Neutron Scattering Division], Shang, Yingrui [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Neutron Scattering Division] (ORCID:0000000301743992), Chen, Wei-Ren [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Neutron Scattering Division] (ORCID:0000000251920777). 2026-04-23. A Bayesian desmearing algorithm for Bonse–Hart USANS with anisotropic scattering. https://doi.org/10.1063/5.0325436

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

DOE OSTI2026

Cyclic moisture reactivation of calcium sorbents for long duration thermochemical energy storage

The transition to a flexible and reliable energy infrastructure, using electro-thermal energy generation technologies such as geothermal, concentrated solar power, and nuclear, usually demands simultaneous advancement of thermal energy storage (TES) to support on-demand electricity generation and industrial applications while mitigating the inherent intermittency of renewable energy sources and power outages from direct energy generation. Among TES technologies, thermochemical energy storage (TCES) based on calcium looping emerges as a compelling high-power energy storage candidate due to its high reaction enthalpy, compatibility with elevated operating temperatures, and abundance of low-cost materials. However, the long-term durability of calcium-based sorbents for TCES is hindered by surface sintering and particle aggregation, leading to performance degradation over repeated thermal cycles. This study explores a moisture hydration-based strategy to regenerate a degraded calcium sorbent and mitigate performance degradation for long duration TCES. The addition of moisture transforms calcium oxide into calcium hydroxide and produces intercalation water layers, associated with a regenerated surface area and reduced calcium oxide crystallite size. Both these effects are beneficial in restoring the sorbents' reactivity for carbonization. Additionally, an optimized hydration-assisted reactivation protocol balances the recovered energy storage capacity with heating penalty required for moisture removal from hydrated samples, resulting in an enhanced energy storage capacity up to 176% compared to benchmark sorbents that undergo cycling without reactivation after 60 cycles. In conclusion, these results highlight the potential of hydration-assisted reactivation to enhance the long-term performance of TCES, providing an effective pathway to advancing electro-thermal storage technologies.

36 MATERIALS SCIENCE↗