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Data-Driven Techniques for Materials...

Chitturi, Sathya Ranjan,

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Data-Driven Techniques for Materials Characterization and Intelligent Experimental Design at Advanced Scattering Facilities /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data-Driven Techniques for Materials Characterization and Intelligent Experimental Design at Advanced Scattering Facilities // Sathya Ranjan Chitturi.
作者:	Chitturi, Sathya Ranjan,
面頁冊數:	1 electronic resource (211 pages)
附註:	Source: Dissertations Abstracts International, Volume: 86-05, Section: A.
Contained By:	Dissertations Abstracts International86-05A.
標題:	Materials science. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31643373
ISBN:	9798346385042

Data-Driven Techniques for Materials Characterization and Intelligent Experimental Design at Advanced Scattering Facilities /
Chitturi, Sathya Ranjan,

Data-Driven Techniques for Materials Characterization and Intelligent Experimental Design at Advanced Scattering Facilities /Sathya Ranjan Chitturi. - 1 electronic resource (211 pages)

Source: Dissertations Abstracts International, Volume: 86-05, Section: A.

This dissertation addresses the need to accelerate materials discovery, particularly within the context of advanced scattering facilities. The complexity of materials discovery arises from vast design space sizes, the need to achieve multiple simultaneous property requirements, and the limitations of ab initiotheory leading to the necessity of performing time-consuming and expensive synthesis and characterization experiments. Advanced X-ray and neutron scattering facilities often play a key role in this materials design process, but now face challenges such as exploding data rates due to improvements in sources, detectors, and increased experimental complexity. This work focuses on developing methodology to enable closed-loop materials discovery at advanced scattering facilities. Specifically, data-driven techniques are introduced for the task of real-time analysis of scattering experiments and to guide materials experiments towards specific objectives.Real-time analysis, often a challenging bottleneck for closed-loop systems, is addressed through the design of methods for solving inverse scattering problems using supervised statistical learning. Emphasis is placed on using simulated data derived from physics-based forward models to aid in scattering analysis, as well as on the rational architectural design of supervised learning models to incorporate inductive biases that align with experimental data. Key frameworks introduced in this dissertation include automatic unit-cell estimation from powder X-ray di↵raction (PXRD) patterns, real-time photon assignment and contrast extraction for X-ray Photon Fluctuation Spectroscopy (XPFS), and robust Hamiltonian parameter inference from inelastic neutron scattering (INS) data.Furthermore, the dissertation presents novel methods for experimental materials design, adapting the recently proposed Bayesian algorithm execution (BAX) approach to frame materials discovery as the task of locating relevant regions of a design space aligned with specific experimental goals. This methodology o↵ers an automated way to convert complex experimental objectives into intelligent, goalaligned data acquisition strategies, allowing for addressing tasks that are impossible or impractical under current methods. The SwitchBAX data acquisition strategy, formulated in this dissertation, achieves state-of-the-art performance on datasets for TiO2nanoparticle synthesis and magnetic materials characterization, and should generally be applicable for any compound discovery task involving complex synthesis protocols, long data acquisition times, or limited sample quantities.Ultimately, this research helps enable closed-loop discovery at national facilities, o↵ering ecient solutions for accelerating materials research and discovery.

English

ISBN: 9798346385042Subjects--Topical Terms:

543314
Materials science.

Data-Driven Techniques for Materials Characterization and Intelligent Experimental Design at Advanced Scattering Facilities /
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