ArticleJournal of applied crystallography2019
Optimization of reflectometry experiments using information theory.
Article in Journal of applied crystallography, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
12 citing papers in PubMed.
- Optimization of magnetic reference layer for neutron reflectometry.Journal of applied crystallography · 2025Article
- Neural network analysis of neutron and X-ray reflectivity data incorporating prior knowledge.Journal of applied crystallography · 2024Article
- Article
- Closing the loop: autonomous experiments enabled by machine-learning-based online data analysis in synchrotron beamline environments.Journal of synchrotron radiation · 2023Article
- Machine learning for scattering data: strategies, perspectives and applications to surface scattering.Journal of applied crystallography · 2023Review
- Optimizing experimental design in neutron reflectometry.Journal of applied crystallography · 2022Article
- Exploiting neutron scattering contrast variation in biological membrane studies.Biophysics reviews · 2022Review
- Large scale model lipid membrane movement induced by a cation switch.Journal of colloid and interface science · 2021Article
- Determining the maximum information gain and optimizing experimental design in neutron reflectometry using the Fisher information.Journal of applied crystallography · 2021Article
- Charge Effects Provide Ångström-Level Control of Lipid Bilayer Morphology on Titanium Dioxide Surfaces.Langmuir : the ACS journal of surfaces and colloids · 2021Article
- Information gain from isotopic contrast variation in neutron reflectometry on protein-membrane complex structures.Journal of applied crystallography · 2020Article
- Association of Model Neurotransmitters with Lipid Bilayer Membranes.Biophysical journal · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A framework based on Bayesian statistics and information theory is developed to optimize the design of surface-sensitive reflectometry experiments. The method applies to model-based reflectivity data analysis, uses simulated reflectivity data and is capable of optimizing experiments that probe a sample under more than one condition. After presentation of the underlying theory and its implementation, the framework is applied to exemplary test problems for which the information gain Δ
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.