Inferring effective electrostatic interaction of charge-stabilized colloids from scattering using deep learning

IF 5.2 3区 材料科学 Q2 CHEMISTRY, MULTIDISCIPLINARY Journal of Applied Crystallography Pub Date : 2024-06-27 DOI:10.1107/S1600576724004515
Chi-Huan Tung, Meng-Zhe Chen, Hsin-Lung Chen, Guan-Rong Huang, Lionel Porcar, Ming-Ching Chang, Jan-Michael Carrillo, Yangyang Wang, Bobby G. Sumpter, Yuya Shinohara, Changwoo Do, Wei-Ren Chen
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Abstract

An innovative strategy is presented that incorporates deep auto-encoder networks into a least-squares fitting framework to address the potential inversion problem in small-angle scattering. To evaluate the performance of the proposed approach, a detailed case study focusing on charged colloidal suspensions was carried out. The results clearly indicate that a deep learning solution offers a reliable and quantitative method for studying molecular interactions. The approach surpasses existing deterministic approaches with respect to both numerical accuracy and computational efficiency. Overall, this work demonstrates the potential of deep learning techniques in tackling complex problems in soft-matter structures and beyond.

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利用深度学习从散射推断电荷稳定胶体的有效静电相互作用
本文提出了一种创新策略,将深度自动编码器网络纳入最小二乘拟合框架,以解决小角散射中潜在的反演问题。为了评估所提出方法的性能,进行了一项详细的案例研究,重点是带电胶体悬浮液。结果清楚地表明,深度学习解决方案为研究分子相互作用提供了一种可靠的定量方法。该方法在数值精度和计算效率方面都超越了现有的确定性方法。总之,这项工作展示了深度学习技术在解决软物质结构及其他复杂问题方面的潜力。
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来源期刊
Journal of Applied Crystallography
Journal of Applied Crystallography CHEMISTRY, MULTIDISCIPLINARYCRYSTALLOGRAPH-CRYSTALLOGRAPHY
CiteScore
7.80
自引率
3.30%
发文量
178
期刊介绍: Many research topics in condensed matter research, materials science and the life sciences make use of crystallographic methods to study crystalline and non-crystalline matter with neutrons, X-rays and electrons. Articles published in the Journal of Applied Crystallography focus on these methods and their use in identifying structural and diffusion-controlled phase transformations, structure-property relationships, structural changes of defects, interfaces and surfaces, etc. Developments of instrumentation and crystallographic apparatus, theory and interpretation, numerical analysis and other related subjects are also covered. The journal is the primary place where crystallographic computer program information is published.
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