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1篇 您的检索式：作者名="Simon D.M.Jacques"

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		题名	作者	年代	出处	被引量
	1	A deep convolutional neural network for real-time full profile analysis of big powder diffraction data显示文摘We present Parameter Quantification Network(PQ-Net),a regression deep convolutional neural network providing quantitative analysis of powder X-ray diffraction patterns from multi-phase systems.The network is tested against simulated and experimental datasets of increasing complexity with the last one being an X-ray diffraction computed tomography dataset of a multi-phase Ni-Pd/CeO_(2)-ZrO_(2)/Al_(2)O_(3) catalytic material system consisting of ca.20,000 diffraction patterns.It is shown that the network predicts accurate scale factor,lattice parameter and crystallite size maps for all phases,which are comparable to those obtained through full profile analysis using the Rietveld method,also providing a reliable uncertainty measure on the results.The main advantage of PQNet is its ability to yield these results orders of magnitude faster showing its potential as a tool for real-time diffraction data analysis during in situ/operando experiments.	Hongyang Dong Keith T.Butler Dorota Matras Stephen W.T.Price Yaroslav Odarchenko Rahul Khatry Andrew Thompson Vesna Middelkoop Simon D.M.Jacques Andrew M.Beale Antonis Vamvakeros	2021	npj Computational Materials2021，，1：	5

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