English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Autonomous synthesis and characterization of inorganic materials requires theautomatic and accurate analysis of X-ray diffraction spectra. For this task, wedesigned a probabilistic deep learning algorithm to identify complexmulti-phase mixtures. At the core of this algorithm lies an ensembleconvolutional neural network trained on simulated diffraction spectra, whichare systematically augmented with physics-informed perturbations to account forartifacts that can arise during experimental sample preparation and synthesis.Larger perturbations associated with off-stoichiometry are also captured bysupplementing the training set with hypothetical solid solutions. Spectracontaining mixtures of materials are analyzed with a newly developed branchingalgorithm that utilizes the probabilistic nature of the neural network toexplore suspected mixtures and identify the set of phases that maximizeconfidence in the prediction. Our model is benchmarked on simulated andexperimentally measured diffraction spectra, showing exceptional performancewith accuracies exceeding those given by previously reported methods based onprofile matching and deep learning. We envision that the algorithm presentedhere may be integrated in experimental workflows to facilitate thehigh-throughput and autonomous discovery of inorganic materials.

A probabilistic deep learning approach to automate the interpretation of multi-phase diffraction spectra